temporal package¶
Submodules¶
temporal.abstract_dataset module¶
The abstract_dataset module provides the AbstractDataset class that is the base class for all map layer and Space Time Datasets.
(C) 2011-2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
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class
temporal.abstract_dataset.
AbstractDataset
[source]¶ Bases:
temporal.spatial_topology_dataset_connector.SpatialTopologyDatasetConnector
,temporal.temporal_topology_dataset_connector.TemporalTopologyDatasetConnector
This is the base class for all datasets (raster, vector, raster3d, strds, stvds, str3ds)
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check_relative_time_unit
(unit)[source]¶ Check if unit is of type year(s), month(s), day(s), hour(s), minute(s) or second(s)
Parameters: unit – The unit string Returns: True if success, False otherwise
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get_absolute_time
()[source]¶ Returns the start time, the end time of the map as tuple
The start time is of type datetime.
The end time is of type datetime in case of interval time, or None on case of a time instance.
Returns: A tuple of (start_time, end_time)
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get_id
()[source]¶ Return the unique identifier of the dataset :return: The id of the dataset “name(:layer)@mapset” as string
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get_mapset
()[source]¶ Return the mapset :return: The mapset in which the dataset was created as string
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get_new_instance
(ident)[source]¶ Return a new instance with the type of this class
Parameters: ident – The identifier of the new dataset instance Returns: A new instance with the type of this object
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get_number_of_relations
()[source]¶ Return a dictionary in which the keys are the relation names and the value are the number of relations.
The following relations are available:
Spatial relations:
- equivalent
- overlap
- in
- contain
- meet
- cover
- covered
Temporal relations:
- equal
- follows
- precedes
- overlaps
- overlapped
- during (including starts, finishes)
- contains (including started, finished)
- starts
- started
- finishes
- finished
To access topological information the spatial, temporal or booth topologies must be build first using the SpatioTemporalTopologyBuilder.
Returns: The dictionary with relations as keys and number as values or None in case the topology wasn’t build
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get_relative_time
()[source]¶ Returns the start time, the end time and the temporal unit of the dataset as tuple
The start time is of type integer.
The end time is of type integer in case of interval time, or None on case of a time instance.
Returns: A tuple of (start_time, end_time, unit)
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get_relative_time_unit
()[source]¶ Returns the relative time unit :return: The relative time unit as string, None if not present
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get_spatial_extent_as_tuple
()[source]¶ Return the spatial extent as tuple
Top and bottom are set to 0 in case of a two dimensional spatial extent.
Returns: A the spatial extent as tuple (north, south, east, west, top, bottom)
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get_temporal_extent_as_tuple
()[source]¶ Returns a tuple of the valid start and end time
Start and end time can be either of type datetime or of type integer, depending on the temporal type.
Returns: A tuple of (start_time, end_time)
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get_temporal_type
()[source]¶ Return the temporal type of this dataset
The temporal type can be absolute or relative
Returns: The temporal type of the dataset as string
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get_type
()[source]¶ Return the type of this class as string
The type can be “vector”, “raster”, “raster3d”, “stvds”, “strds” or “str3ds”
Returns: “vector”, “raster”, “raster3d”, “stvds”, “strds” or “str3ds”
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insert
(dbif=None, execute=True)[source]¶ Insert dataset into database
Parameters: - dbif – The database interface to be used
- execute – If True the SQL statements will be executed. If False the prepared SQL statements are returned and must be executed by the caller.
Returns: The SQL insert statement in case execute=False, or an empty string otherwise
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is_in_db
(dbif=None)[source]¶ Check if the dataset is registered in the database
Parameters: dbif – The database interface to be used Returns: True if the dataset is registered in the database
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is_stds
()[source]¶ Return True if this class is a space time dataset
Returns: True if this class is a space time dataset, False otherwise
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is_time_absolute
()[source]¶ Return True in case the temporal type is absolute
Returns: True if temporal type is absolute, False otherwise
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is_time_relative
()[source]¶ Return True in case the temporal type is relative
Returns: True if temporal type is relative, False otherwise
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is_topology_build
()[source]¶ Check if the spatial and temporal topology was build
Returns: A dictionary with “spatial” and “temporal” as keys that have boolen values
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reset
(ident)[source]¶ Reset the internal structure and set the identifier
This method creates the dataset specific internal objects that store the base information, the spatial and temporal extent and the metadata. It must be implemented in the dataset specific subclasses. This is the code for the vector dataset:
self.base = VectorBase(ident=ident) self.absolute_time = VectorAbsoluteTime(ident=ident) self.relative_time = VectorRelativeTime(ident=ident) self.spatial_extent = VectorSpatialExtent(ident=ident) self.metadata = VectorMetadata(ident=ident)
Parameters: ident – The identifier of the dataset that “name@mapset” or in case of vector maps “name:layer@mapset”
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select
(dbif=None)[source]¶ Select temporal dataset entry from database and fill the internal structure
The content of every dataset is stored in the temporal database. This method must be used to fill this object with the content from the temporal database.
Parameters: dbif – The database interface to be used
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spatial_disjoint_union
(dataset)[source]¶ Return the spatial union as spatial_extent object.
Parameters: dataset – The abstract dataset to create a union with Returns: The union spatial extent
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spatial_intersection
(dataset)[source]¶ Return the spatial intersection as spatial_extent object or None in case no intersection was found.
Parameters: dataset – The abstract dataset to intersect with Returns: The intersection spatial extent
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spatial_overlapping
(dataset)[source]¶ Return True if the spatial extents overlap
Parameters: dataset – The abstract dataset to check spatial overlapping Returns: True if self and the provided dataset spatial overlap
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spatial_relation
(dataset)[source]¶ Return the spatial relationship between self and dataset
Parameters: dataset – The abstract dataset to compute the spatial relation with self Returns: The spatial relationship as string
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spatial_union
(dataset)[source]¶ Return the spatial union as spatial_extent object or None in case the extents does not overlap or meet.
Parameters: dataset – The abstract dataset to create a union with Returns: The union spatial extent
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temporal_disjoint_union
(dataset)[source]¶ Creates a union with the provided dataset and return a new temporal extent with the new start and end time.
Parameters: dataset – The abstract dataset to create temporal union with Returns: The new temporal extent with start and end time
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temporal_extent
¶ Return the temporal extent of the correct internal type
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temporal_intersection
(dataset)[source]¶ Intersect self with the provided dataset and return a new temporal extent with the new start and end time
Parameters: dataset – The abstract dataset to temporal intersect with Returns: The new temporal extent with start and end time, or None in case of no intersection
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temporal_relation
(dataset)[source]¶ Return the temporal relation of self and the provided dataset
Returns: The temporal relation as string
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temporal_union
(dataset)[source]¶ Creates a union with the provided dataset and return a new temporal extent with the new start and end time.
Parameters: dataset – The abstract dataset to create temporal union with Returns: The new temporal extent with start and end time, or None in case of no intersection
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update
(dbif=None, execute=True, ident=None)[source]¶ Update the dataset entry in the database from the internal structure excluding None variables
Parameters: - dbif – The database interface to be used
- execute – If True the SQL statements will be executed. If False the prepared SQL statements are returned and must be executed by the caller.
- ident – The identifier to be updated, useful for renaming
Returns: The SQL update statement in case execute=False, or an empty string otherwise
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update_all
(dbif=None, execute=True, ident=None)[source]¶ Update the dataset entry in the database from the internal structure and include None variables.
Parameters: - dbif – The database interface to be used
- execute – If True the SQL statements will be executed. If False the prepared SQL statements are returned and must be executed by the caller.
- ident – The identifier to be updated, useful for renaming
Returns: The SQL update statement in case execute=False, or an empty string otherwise
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class
temporal.abstract_dataset.
AbstractDatasetComparisonKeyEndTime
(obj, *args)[source]¶ Bases:
object
This comparison key can be used to sort lists of abstract datasets by end time
Example:
# Return all maps in a space time raster dataset as map objects map_list = strds.get_registered_maps_as_objects() # Sort the maps in the list by end time sorted_map_list = sorted(map_list, key=AbstractDatasetComparisonKeyEndTime)
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class
temporal.abstract_dataset.
AbstractDatasetComparisonKeyStartTime
(obj, *args)[source]¶ Bases:
object
This comparison key can be used to sort lists of abstract datasets by start time
Example:
# Return all maps in a space time raster dataset as map objects map_list = strds.get_registered_maps_as_objects() # Sort the maps in the list by start time sorted_map_list = sorted(map_list, key=AbstractDatasetComparisonKeyStartTime)
temporal.abstract_map_dataset module¶
The abstract_map_dataset module provides the AbstractMapDataset class that is the base class for all map layer.
(C) 2011-2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
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class
temporal.abstract_map_dataset.
AbstractMapDataset
[source]¶ Bases:
temporal.abstract_dataset.AbstractDataset
This is the base class for all maps (raster, vector, raster3d).
The temporal extent, the spatial extent and the metadata of maps are stored in the temporal database. Maps can be registered in the temporal database, updated and deleted.
This class provides all functionalities that are needed to manage maps in the temporal database. That are:
- insert() to register the map and therefore its spatio-temporal extent and metadata in the temporal database
- update() to update the map spatio-temporal extent and metadata in the temporal database
- unregister() to unregister the map from each space time dataset in which this map is registered
- delete() to remove the map from the temporal database
- Methods to set relative and absolute time stamps
- Abstract methods that must be implemented in the map specific subclasses
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add_stds_to_register
(stds_id, dbif=None, execute=True)[source]¶ Add a new space time dataset to the register
Parameters: - stds_id – The id of the space time dataset to be registered
- dbif – The database interface to be used
- execute – If True the SQL INSERT table statements will be executed. If False the prepared SQL statements are returned and must be executed by the caller.
Returns: The SQL statements if execute=False, else an empty string
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static
build_id
(name, mapset, layer=None)[source]¶ Convenient method to build the unique identifier
Existing layer and mapset definitions in the name string will be reused
Parameters: - name – The name of the map
- mapset – The mapset in which the map is located
- layer – The layer of the vector map, use None in case no layer exists
Returns: the id of the map as “name(:layer)@mapset” while layer is optional
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check_for_correct_time
()[source]¶ Check for correct time
Returns: True in case of success, False otherwise
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check_resolution_with_current_region
()[source]¶ Check if the raster or voxel resolution is finer than the current resolution
- Return “finer” in case the raster/voxel resolution is finer than the current region
- Return “coarser” in case the raster/voxel resolution is coarser than the current region
Vector maps have no resolution, since they store the coordinates directly.
Returns: “finer” or “coarser”
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delete
(dbif=None, update=True, execute=True)[source]¶ Delete a map entry from database if it exists
Remove dependent entries:
- Remove the map entry in each space time dataset in which this map is registered
- Remove the space time dataset register table
Parameters: - dbif – The database interface to be used
- update – Call for each unregister statement the update from registered maps of the space time dataset. This can slow down the un-registration process significantly.
- execute – If True the SQL DELETE and DROP table statements will be executed. If False the prepared SQL statements are returned and must be executed by the caller.
Returns: The SQL statements if execute=False, else an empty string, None in case of a failure
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get_layer
()[source]¶ Return the layer of the map
Returns: the layer of the map or None in case no layer is defined
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get_map_id
()[source]¶ Return the map id. The map id is the unique identifier in grass and must not be equal to the primary key identifier (id) of the map in the database. Since vector maps may have layer information, the unique id is a combination of name, layer and mapset.
Use get_map_id() every time your need to access the grass map in the file system but not to identify map information in the temporal database.
Returns: The map id “name@mapset”
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get_new_stds_instance
(ident)[source]¶ Return a new space time dataset instance that store maps with the type of this map object (raster, raster_3d or vector)
:param ident The identifier of the space time dataset :return: The new space time dataset instance
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get_registered_stds
(dbif=None)[source]¶ Return all space time dataset ids in which this map is registered as as a list of strings, or None if this map is not registered in any space time dataset.
Parameters: dbif – The database interface to be used Returns: A list of ids of all space time datasets in which this map is registered
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has_grass_timestamp
()[source]¶ Check if a grass file based time stamp exists for this map.
Returns: True is the grass file based time stamped exists for this map
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insert
(dbif=None, execute=True)[source]¶ Insert the map content into the database from the internal structure
This functions assures that the timestamp is written to the grass file system based database in addition to the temporal database entry. The stds register table will be created as well. Hence maps can only be registered in a space time dataset, when they were inserted in the temporal database beforehand.
Parameters: - dbif – The database interface to be used
- execute – If True the SQL statements will be executed. If False the prepared SQL statements are returned and must be executed by the caller.
Returns: The SQL insert statement in case execute=False, or an empty string otherwise
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map_exists
()[source]¶ Return True in case the map exists in the grass spatial database
Returns: True if map exists, False otherwise
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read_timestamp_from_grass
()[source]¶ Read the timestamp of this map from the map metadata in the grass file system based spatial database and set the internal time stamp that should be insert/updated in the temporal database.
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remove_stds_from_register
(stds_id, dbif=None, execute=True)[source]¶ Remove a space time dataset from the register
Parameters: - stds_id – The id of the space time dataset to removed from the registered
- dbif – The database interface to be used
- execute – If True the SQL INSERT table statements will be executed. If False the prepared SQL statements are returned and must be executed by the caller.
Returns: The SQL statements if execute=False, else an empty string
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remove_timestamp_from_grass
()[source]¶ Remove the timestamp from the grass file system based spatial database
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set_absolute_time
(start_time, end_time=None)[source]¶ Set the absolute time with start time and end time
The end time is optional and must be set to None in case of time instance.
This method only modifies this object and does not commit the modifications to the temporal database.
Parameters: - start_time – A datetime object specifying the start time of the map
- end_time – A datetime object specifying the end time of the map, None in case or time instance
Returns: True for success and False otherwise
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set_relative_time
(start_time, end_time, unit)[source]¶ Set the relative time interval
The end time is optional and must be set to None in case of time instance.
This method only modifies this object and does not commit the modifications to the temporal database.
Parameters: - start_time – An integer value
- end_time – An integer value, None in case or time instance
- unit – The unit of the relative time. Supported units: year(s), month(s), day(s), hour(s), minute(s), second(s)
Returns: True for success and False otherwise
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set_spatial_extent
(spatial_extent)[source]¶ Set the spatial extent of the map
This method only modifies this object and does not commit the modifications to the temporal database.
param spatial_extent: An object of type SpatialExtent or its subclasses
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set_spatial_extent_from_values
(north, south, east, west, top=0, bottom=0)[source]¶ Set the spatial extent of the map from values
This method only modifies this object and does not commit the modifications to the temporal database.Parameters: - north – The northern edge
- south – The southern edge
- east – The eastern edge
- west – The western edge
- top – The top edge
- bottom – The bottom edge
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set_temporal_extent
(extent)[source]¶ Convenient method to set the temporal extent from a temporal extent object
Parameters: extent – The temporal extent that should be set for this object
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spatial_buffer
(size, update=False, dbif=None)[source]¶ Buffer the spatial extent by a given size in all spatial directions.
Parameters: - size – The buffer size, using the unit of the grass region
- update – If True perform an immediate database update, otherwise only the internal variables are set
- dbif – The database interface to be used
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spatial_buffer_2d
(size, update=False, dbif=None)[source]¶ Buffer the spatial extent by a given size in 2d spatial directions.
Parameters: - size – The buffer size, using the unit of the grass region
- update – If True perform an immediate database update, otherwise only the internal variables are set
- dbif – The database interface to be used
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temporal_buffer
(increment, update=False, dbif=None)[source]¶ Create a temporal buffer based on an increment
For absolute time the increment must be a string of type “integer unit” Unit can be year, years, month, months, day, days, hour, hours, minute, minutes, day or days.
Parameters: - increment – This is the increment, a string in case of absolute time or an integer in case of relative time
- update – Perform an immediate database update to store the modified temporal extent, otherwise only this object will be modified
Usage:
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unregister
(dbif=None, update=True, execute=True)[source]¶ Remove the map entry in each space time dataset in which this map is registered
Parameters: - dbif – The database interface to be used
- update – Call for each unregister statement the update from registered maps of the space time dataset. This can slow down the un-registration process significantly.
- execute – If True the SQL DELETE and DROP table statements will be executed. If False the prepared SQL statements are returned and must be executed by the caller.
Returns: The SQL statements if execute=False, else an empty string
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update
(dbif=None, execute=True)[source]¶ Update the map content in the database from the internal structure excluding None variables
This functions assures that the timestamp is written to the grass file system based database in addition to the temporal database entry.
Parameters: - dbif – The database interface to be used
- execute – If True the SQL statements will be executed. If False the prepared SQL statements are returned and must be executed by the caller.
Returns: The SQL insert statement in case execute=False, or an empty string otherwise
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update_absolute_time
(start_time, end_time=None, dbif=None)[source]¶ Update the absolute time
The end time is optional and must be set to None in case of time instance.
This functions assures that the timestamp is written to the grass file system based database in addition to the temporal database entry.
Parameters: - start_time – A datetime object specifying the start time of the map
- end_time – A datetime object specifying the end time of the map, None in case or time instance
- dbif – The database interface to be used
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update_all
(dbif=None, execute=True)[source]¶ Update the map content in the database from the internal structure including None variables
This functions assures that the timestamp is written to the grass file system based database in addition to the temporal database entry.
Parameters: - dbif – The database interface to be used
- execute – If True the SQL statements will be executed. If False the prepared SQL statements are returned and must be executed by the caller.
Returns: The SQL insert statement in case execute=False, or an empty string otherwise
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update_relative_time
(start_time, end_time, unit, dbif=None)[source]¶ Update the relative time interval
The end time is optional and must be set to None in case of time instance.
This functions assures that the timestamp is written to the grass file system based database in addition to the temporal database entry.
Parameters: - start_time – An integer value
- end_time – An integer value, None in case or time instance
- unit – The relative time unit
- dbif – The database interface to be used
temporal.abstract_space_time_dataset module¶
The abstract_space_time_dataset module provides the AbstractSpaceTimeDataset class that is the base class for all space time datasets.
(C) 2011-2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
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class
temporal.abstract_space_time_dataset.
AbstractSpaceTimeDataset
(ident)[source]¶ Bases:
temporal.abstract_dataset.AbstractDataset
Abstract space time dataset class
Base class for all space time datasets.
This class represents an abstract space time dataset. Convenient functions to select, update, insert or delete objects of this type in the SQL temporal database exists as well as functions to register or unregister raster maps.
Parts of the temporal logic are implemented in the SQL temporal database, like the computation of the temporal and spatial extent as well as the collecting of metadata.
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check_temporal_topology
(maps=None, dbif=None)[source]¶ Check the temporal topology of all maps of the current space time dataset or of an optional list of maps
Correct topology means, that time intervals are not overlap or that intervals does not contain other intervals. Equal time intervals are not allowed.
The optional map list must be ordered by start time
Allowed and not allowed temporal relationships for correct topology:
- after -> allowed
- precedes -> allowed
- follows -> allowed
- precedes -> allowed
- equal -> not allowed
- during -> not allowed
- contains -> not allowed
- overlaps -> not allowed
- overlapped -> not allowed
- starts -> not allowed
- finishes -> not allowed
- started -> not allowed
- finished -> not allowed
Parameters: - maps – An optional list of AbstractDataset objects, in case of None all maps of the space time dataset are checked
- dbif – The database interface to be used
Returns: True if topology is correct
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count_gaps
(maps=None, dbif=None)[source]¶ Count the number of gaps between temporal neighbors
Parameters: - maps – A sorted (start_time) list of AbstractDataset objects
- dbif – The database interface to be used
Returns: The numbers of gaps between temporal neighbors
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count_temporal_relations
(maps=None, dbif=None)[source]¶ Count the temporal relations between the registered maps.
The map list must be ordered by start time. Temporal relations are counted by analysing the sparse upper right side temporal relationships matrix.
Parameters: - maps – A sorted (start_time) list of AbstractDataset objects
- dbif – The database interface to be used
Returns: A dictionary with counted temporal relationships
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count_temporal_types
(maps=None, dbif=None)[source]¶ Return the temporal type of the registered maps as dictionary
The map list must be ordered by start time
The temporal type can be:
- point -> only the start time is present
- interval -> start and end time
- invalid -> No valid time point or interval found
Parameters: - maps – A sorted (start_time) list of AbstractDataset objects
- dbif – The database interface to be used
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create_command_string
()[source]¶ Create the command string that was used to create this space time dataset.
The command string should be set with self.metadata.set_command()
Returns: The command string
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create_map_register_name
()[source]¶ Create the name of the map register table of this space time dataset
A uuid and the map type are used to create the table name
ATTENTION: It must be assured that the base object has selected its content from the database.
Returns: The name of the map register table
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delete
(dbif=None, execute=True)[source]¶ Delete a space time dataset from the temporal database
This method removes the space time dataset from the temporal database and drops its map register table
Parameters: - dbif – The database interface to be used
- execute – If True the SQL DELETE and DROP table statements will be executed. If False the prepared SQL statements are returned and must be executed by the caller.
Returns: The SQL statements if execute == False, else an empty string
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get_granularity
()[source]¶ Return the granularity of the space time dataset
Granularity can be of absolute time or relative time. In case of absolute time a string containing an integer value and the time unit (years, months, days, hours, minuts, seconds). In case of relative time an integer value is expected.
Returns: The granularity
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get_initial_values
()[source]¶ Return the initial values: temporal_type, semantic_type, title, description
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get_map_register
()[source]¶ Return the name of the map register table :return: The map register table name
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get_new_map_instance
(ident=None)[source]¶ Return a new instance of a map which is associated with the type of this object
Parameters: ident – The unique identifier of the new object
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get_registered_maps
(columns=None, where=None, order=None, dbif=None)[source]¶ Return SQL rows of all registered maps.
In case columns are not specified, each row includes all columns specified in the datatype specific view.
Parameters: - columns – Columns to be selected as SQL compliant string
- where – The SQL where statement to select a subset of the registered maps without “WHERE”
- order – The SQL order statement to be used to order the objects in the list without “ORDER BY”
- dbif – The database interface to be used
Returns: SQL rows of all registered maps, In case nothing found None is returned
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get_registered_maps_as_objects
(where=None, order='start_time', dbif=None)[source]¶ Return all or a subset of the registered maps as ordered object list for spatio-temporal topological operations that require the spatio-temporal extent only
The objects are initialized with their id’s‘ and the spatio-temporal extent (temporal type, start time, end time, west, east, south, north, bottom and top). In case more map information are needed, use the select() method for each listed object.
Parameters: - where – The SQL where statement to select a subset of the registered maps without “WHERE”
- order – The SQL order statement to be used to order the objects in the list without “ORDER BY”
- dbif – The database interface to be used
Returns: The ordered map object list, In case nothing found None is returned
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get_registered_maps_as_objects_by_granularity
(gran=None, dbif=None)[source]¶ Return all registered maps as ordered (by start_time) object list with “gap” map objects (id==None) for spatio-temporal topological operations that require the temporal extent only.
Each list entry is a list of AbstractMapDatasets objects which are potentially equal the actual granule, contain the actual granule or are located in the actual granule. Hence for each granule a list of AbstractMapDatasets can be expected.
Maps that overlap the granule are ignored.
The granularity of the space time dataset is used as increment in case the granule is not user defined.
A valid temporal topology (no overlapping or inclusion allowed) is needed to get correct results.
Space time datasets with interval time, time instances and mixed time are supported.
Gaps between maps are identified as unregistered maps with id==None.
The objects are initialized with their id’s‘ and the spatio-temporal extent (temporal type, start time, end time, west, east, south, north, bottom and top). In case more map information are needed, use the select() method for each listed object.
Parameters: - gran – The granularity string to be used, if None the granularity of the space time dataset is used. Absolute time has the format “number unit”, relative time has the format “number”. The unit in case of absolute time can be one of “second, seconds, minute, minutes, hour, hours, day, days, week, weeks, month, months, year, years”. The unit of the relative time granule is always the space time dataset unit and can not be changed.
- dbif – The database interface to be used
Returns: ordered list of map lists. Each list represents a single granule, or None in case nothing found
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get_registered_maps_as_objects_with_gaps
(where=None, dbif=None)[source]¶ Return all or a subset of the registered maps as ordered (by start_time) object list with “gap” map objects (id==None) for spatio-temporal topological operations that require the spatio-temporal extent only.
Gaps between maps are identified as maps with id==None
The objects are initialized with their id’s‘ and the spatio-temporal extent (temporal type, start time, end time, west, east, south, north, bottom and top). In case more map information are needed, use the select() method for each listed object.
Parameters: - where – The SQL where statement to select a subset of the registered maps without “WHERE”
- dbif – The database interface to be used
Returns: ordered object list, in case nothing found None is returned
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get_registered_maps_as_objects_with_temporal_topology
(where=None, order='start_time', dbif=None)[source]¶ Return all or a subset of the registered maps as ordered object list with spatio-temporal topological relationship information.
The objects are initialized with their id’s‘ and the spatio-temporal extent (temporal type, start time, end time, west, east, south, north, bottom and top). In case more map information are needed, use the select() method for each listed object.
Parameters: - where – The SQL where statement to select a subset of the registered maps without “WHERE”
- order – The SQL order statement to be used to order the objects in the list without “ORDER BY”
- dbif – The database interface to be used
Returns: The ordered map object list, In case nothing found None is returned
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insert
(dbif=None, execute=True)[source]¶ Insert the space time dataset content into the database from the internal structure
The map register table will be created, so that maps can be registered.
Parameters: - dbif – The database interface to be used
- execute – If True the SQL statements will be executed. If False the prepared SQL statements are returned and must be executed by the caller.
Returns: The SQL insert statement in case execute=False, or an empty string otherwise
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is_map_registered
(map_id, dbif=None)[source]¶ Check if a map is registered in the space time dataset
Parameters: - map_id – The map id
- dbif – The database interface to be used
Returns: True if success, False otherwise
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print_spatio_temporal_relationships
(maps=None, spatial=None, dbif=None)[source]¶ Print the spatio-temporal relationships for each map of the space time dataset or for each map of the optional list of maps
Parameters: - maps – a ordered by start_time list of map objects, if None the registered maps of the space time dataset are used
- spatial – This indicates if the spatial topology is created as well: spatial can be None (no spatial topology), “2D” using west, east, south, north or “3D” using west, east, south, north, bottom, top
- dbif – The database interface to be used
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register_map
(map, dbif=None)[source]¶ Register a map in the space time dataset.
This method takes care of the registration of a map in a space time dataset.
In case the map is already registered this function will break with a warning and return False.
This method raises a FatalError exception in case of a fatal error
Parameters: - map – The AbstractMapDataset object that should be registered
- dbif – The database interface to be used
Returns: True if success, False otherwise
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rename
(ident, dbif=None)[source]¶ Rename the space time dataset
This method renames the space time dataset, the map register table and updates the entries in registered maps stds register.
Renaming does not work with Postgresql yet.
Parameters: - ident – The new identifier “name@mapset”
- dbif – The database interface to be used
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static
resample_maplist_by_granularity
(maps, start, end, gran)[source]¶ Resample a list of AbstractMapDatasets by a given granularity
The provided map list must be sorted by start time. A valid temporal topology (no overlapping or inclusion allowed) is needed to receive correct results.
Maps with interval time, time instances and mixed time are supported.
The temporal topology search order is as follows:
- Maps that are equal to the actual granule are used
- If no euqal found then maps that contain the actual granule are used
- If no maps are found that contain the actual granule then maps are used that overlaps the actual granule
- If no overlaps maps found then overlapped maps are used
- If no overlapped maps are found then maps are used that are durin the actual granule
Each entry in the resulting list is a list of AbstractMapDatasets objects. Hence for each granule a list of AbstractMapDatasets can be expected.
Gaps between maps are identified as unregistered maps with id==None.
Parameters: - maps – An ordered list (by start time) of AbstractMapDatasets objects. All maps must have the same temporal type and the same unit in case of relative time.
- start – The start time of the provided map list
- end – The end time of the provided map list
- gran – The granularity string to be used, if None the granularity of the space time dataset is used. Absolute time has the format “number unit”, relative time has the format “number”. The unit in case of absolute time can be one of “second, seconds, minute, minutes, hour, hours, day, days, week, weeks, month, months, year, years”. The unit of the relative time granule is always the space time dataset unit and can not be changed.
Returns: ordered list of map lists. Each list represents a single granule, or None in case nothing found
Usage:
>>> import grass.temporal as tgis >>> maps = [] >>> for i in range(3): ... map = tgis.RasterDataset("map%i@PERMANENT"%i) ... check = map.set_relative_time(i + 2, i + 3, "days") ... maps.append(map) >>> grans = tgis.AbstractSpaceTimeDataset.resample_maplist_by_granularity(maps,0,8,1) >>> for map_list in grans: ... print(map_list[0].get_id(), map_list[0].get_temporal_extent_as_tuple()) None (0, 1) None (1, 2) map0@PERMANENT (2, 3) map1@PERMANENT (3, 4) map2@PERMANENT (4, 5) None (5, 6) None (6, 7) None (7, 8) >>> maps = [] >>> map1 = tgis.RasterDataset("map1@PERMANENT") >>> check = map1.set_relative_time(2, 6, "days") >>> maps.append(map1) >>> map2 = tgis.RasterDataset("map2@PERMANENT") >>> check = map2.set_relative_time(7, 13, "days") >>> maps.append(map2) >>> grans = tgis.AbstractSpaceTimeDataset.resample_maplist_by_granularity(maps,0,16,2) >>> for map_list in grans: ... print(map_list[0].get_id(), map_list[0].get_temporal_extent_as_tuple()) None (0, 2) map1@PERMANENT (2, 4) map1@PERMANENT (4, 6) map2@PERMANENT (6, 8) map2@PERMANENT (8, 10) map2@PERMANENT (10, 12) map2@PERMANENT (12, 14) None (14, 16) >>> maps = [] >>> map1 = tgis.RasterDataset("map1@PERMANENT") >>> check = map1.set_relative_time(2, None, "days") >>> maps.append(map1) >>> map2 = tgis.RasterDataset("map2@PERMANENT") >>> check = map2.set_relative_time(7, None, "days") >>> maps.append(map2) >>> grans = tgis.AbstractSpaceTimeDataset.resample_maplist_by_granularity(maps,0,16,2) >>> for map_list in grans: ... print(map_list[0].get_id(), map_list[0].get_temporal_extent_as_tuple()) None (0, 2) map1@PERMANENT (2, 4) None (4, 6) map2@PERMANENT (6, 8) None (8, 10) None (10, 12) None (12, 14) None (14, 16) >>> maps = [] >>> map1 = tgis.RasterDataset("map1@PERMANENT") >>> check = map1.set_absolute_time(datetime(2000, 4,1), datetime(2000, 6, 1)) >>> maps.append(map1) >>> map2 = tgis.RasterDataset("map2@PERMANENT") >>> check = map2.set_absolute_time(datetime(2000, 8,1), datetime(2000, 12, 1)) >>> maps.append(map2) >>> grans = tgis.AbstractSpaceTimeDataset.resample_maplist_by_granularity(maps,datetime(2000,1,1),datetime(2001,4,1),"1 month") >>> for map_list in grans: ... print(map_list[0].get_id(), map_list[0].get_temporal_extent_as_tuple()) None (datetime.datetime(2000, 1, 1, 0, 0), datetime.datetime(2000, 2, 1, 0, 0)) None (datetime.datetime(2000, 2, 1, 0, 0), datetime.datetime(2000, 3, 1, 0, 0)) None (datetime.datetime(2000, 3, 1, 0, 0), datetime.datetime(2000, 4, 1, 0, 0)) map1@PERMANENT (datetime.datetime(2000, 4, 1, 0, 0), datetime.datetime(2000, 5, 1, 0, 0)) map1@PERMANENT (datetime.datetime(2000, 5, 1, 0, 0), datetime.datetime(2000, 6, 1, 0, 0)) None (datetime.datetime(2000, 6, 1, 0, 0), datetime.datetime(2000, 7, 1, 0, 0)) None (datetime.datetime(2000, 7, 1, 0, 0), datetime.datetime(2000, 8, 1, 0, 0)) map2@PERMANENT (datetime.datetime(2000, 8, 1, 0, 0), datetime.datetime(2000, 9, 1, 0, 0)) map2@PERMANENT (datetime.datetime(2000, 9, 1, 0, 0), datetime.datetime(2000, 10, 1, 0, 0)) map2@PERMANENT (datetime.datetime(2000, 10, 1, 0, 0), datetime.datetime(2000, 11, 1, 0, 0)) map2@PERMANENT (datetime.datetime(2000, 11, 1, 0, 0), datetime.datetime(2000, 12, 1, 0, 0)) None (datetime.datetime(2000, 12, 1, 0, 0), datetime.datetime(2001, 1, 1, 0, 0)) None (datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2001, 2, 1, 0, 0)) None (datetime.datetime(2001, 2, 1, 0, 0), datetime.datetime(2001, 3, 1, 0, 0)) None (datetime.datetime(2001, 3, 1, 0, 0), datetime.datetime(2001, 4, 1, 0, 0))
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sample_by_dataset
(stds, method=None, spatial=False, dbif=None)[source]¶ Sample this space time dataset with the temporal topology of a second space time dataset
In case spatial is True, the spatial overlap between temporal related maps is performed. Only temporal related and spatial overlapping maps are returned.
Return all registered maps as ordered (by start_time) object list. Each list entry is a list of map objects which are potentially located in temporal relation to the actual granule of the second space time dataset.
Each entry in the object list is a dict. The actual sampler map and its temporal extent (the actual granule) and the list of samples are stored:
list = self.sample_by_dataset(stds=sampler, method=[ "during","overlap","contains","equal"]) for entry in list: granule = entry["granule"] maplist = entry["samples"] for map in maplist: map.select() map.print_info()
A valid temporal topology (no overlapping or inclusion allowed) is needed to get correct results in case of gaps in the sample dataset.
Gaps between maps are identified as unregistered maps with id==None.
The objects are initialized with their id’s‘ and the spatio-temporal extent (temporal type, start time, end time, west, east, south, north, bottom and top). In case more map information are needed, use the select() method for each listed object.
Parameters: - stds – The space time dataset to be used for temporal sampling
- method –
- This option specifies what sample method should be
- used. In case the registered maps are of temporal point type, only the start time is used for sampling. In case of mixed of interval data the user can chose between:
- Example [“start”, “during”, “equals”]
- start: Select maps of which the start time is
located in the selection granule:
map : s granule: s-----------------e map : s--------------------e granule: s-----------------e map : s--------e granule: s-----------------e
- contains: Select maps which are temporal
- during the selection granule:
map : s-----------e granule: s-----------------e
- overlap: Select maps which temporal overlap
the selection granule, this includes overlaps and
overlapped:
map : s-----------e granule: s-----------------e map : s-----------e granule: s----------e
- during: Select maps which temporally contains
the selection granule:
map : s-----------------e granule: s-----------e
- equals: Select maps which temporally equal
to the selection granule:
map : s-----------e granule: s-----------e
- follows: Select maps which temporally follow
the selection granule:
map : s-----------e granule: s-----------e
- precedes: Select maps which temporally precedes
the selection granule:
map : s-----------e granule: s-----------e
All these methods can be combined. Method must be of type tuple including the identification strings.
- spatial – If set True additional the 2d spatial overlapping is used for selection -> spatio-temporal relation. The returned map objects will have temporal and spatial extents
- dbif – The database interface to be used
Returns: A list of lists of map objects or None in case nothing was found None
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sample_by_dataset_sql
(stds, method=None, spatial=False, dbif=None)[source]¶ Sample this space time dataset with the temporal topology of a second space time dataset using SQL queries.
This function is very slow for huge large space time datasets but can run several times in the same process without problems.
The sample dataset must have “interval” as temporal map type, so all sample maps have valid interval time.
In case spatial is True, the spatial overlap between temporal related maps is performed. Only temporal related and spatial overlapping maps are returned.
Return all registered maps as ordered (by start_time) object list with “gap” map objects (id==None). Each list entry is a list of map objects which are potentially located in temporal relation to the actual granule of the second space time dataset.
Each entry in the object list is a dict. The actual sampler map and its temporal extent (the actual granule) and the list of samples are stored:
list = self.sample_by_dataset(stds=sampler, method=[ "during","overlap","contain","equal"]) for entry in list: granule = entry["granule"] maplist = entry["samples"] for map in maplist: map.select() map.print_info()
A valid temporal topology (no overlapping or inclusion allowed) is needed to get correct results in case of gaps in the sample dataset.
Gaps between maps are identified as unregistered maps with id==None.
The objects are initialized with their id’s‘ and the spatio-temporal extent (temporal type, start time, end time, west, east, south, north, bottom and top). In case more map information are needed, use the select() method for each listed object.
Parameters: - stds – The space time dataset to be used for temporal sampling
- method –
- This option specifies what sample method should be
- used. In case the registered maps are of temporal point type, only the start time is used for sampling. In case of mixed of interval data the user can chose between:
- Example [“start”, “during”, “equals”]
- start: Select maps of which the start time is
located in the selection granule:
map : s granule: s-----------------e map : s--------------------e granule: s-----------------e map : s--------e granule: s-----------------e
- contains: Select maps which are temporal
during the selection granule:
map : s-----------e granule: s-----------------e
- overlap: Select maps which temporal overlap
the selection granule, this includes overlaps and
overlapped:
map : s-----------e granule: s-----------------e map : s-----------e granule: s----------e
- during: Select maps which temporally contains
the selection granule:
map : s-----------------e granule: s-----------e
- equals: Select maps which temporally equal
to the selection granule:
map : s-----------e granule: s-----------e
- follows: Select maps which temporally follow
the selection granule:
map : s-----------e granule: s-----------e
- precedes: Select maps which temporally precedes
the selection granule:
map : s-----------e granule: s-----------e
All these methods can be combined. Method must be of type tuple including the identification strings.
- spatial – If set True additional the 2d spatial overlapping is used for selection -> spatio-temporal relation. The returned map objects will have temporal and spatial extents
- dbif – The database interface to be used
Returns: A list of lists of map objects or None in case nothing was found None
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set_aggregation_type
(aggregation_type)[source]¶ Set the aggregation type of the space time dataset
Parameters: aggregation_type – The aggregation type of the space time dataset
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set_granularity
(granularity)[source]¶ Set the granularity
The granularity is usually computed by the space time dataset at runtime.
Granularity can be of absolute time or relative time. In case of absolute time a string containing an integer value and the time unit (years, months, days, hours, minuts, seconds). In case of relative time an integer value is expected.
This method only modifies this object and does not commit the modifications to the temporal database.
Parameters: granularity – The granularity of the dataset
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set_initial_values
(temporal_type, semantic_type=None, title=None, description=None)[source]¶ Set the initial values of the space time dataset
In addition the command creation string is generated an inserted into the metadata object.
This method only modifies this object and does not commit the modifications to the temporal database.
The insert() function must be called to commit this content into the temporal database.
Parameters: - temporal_type – The temporal type of this space time dataset (absolute or relative)
- semantic_type – The semantic type of this dataset
- title – The title
- description – The description of this dataset
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set_map_register
(name)[source]¶ Set the name of the map register table
This table stores all map names which are registered in this space time dataset.
This method only modifies this object and does not commit the modifications to the temporal database.
Parameters: name – The name of the register table
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set_relative_time_unit
(unit)[source]¶ Set the relative time unit which may be of type: years, months, days, hours, minutes or seconds
All maps registered in a (relative time) space time dataset must have the same unit
This method only modifies this object and does not commit the modifications to the temporal database.
Parameters: unit – The relative time unit
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shift
(gran, dbif=None)[source]¶ Temporally shift each registered map with the provided granularity
Parameters: - gran – The granularity to be used for shifting
- dbif – The database interface to be used
Returns: True something to shift, False if nothing to shift or wrong granularity
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static
shift_map_list
(maps, gran)[source]¶ Temporally shift each map in the list with the provided granularity
This method does not perform any temporal database operations.
Parameters: - maps – A list of maps with initialized temporal extent
- gran – The granularity to be used for shifting
Returns: The modified map list, None if nothing to shift or wrong granularity
>>> import grass.temporal as tgis >>> maps = [] >>> for i in range(5): ... map = tgis.RasterDataset(None) ... if i%2 == 0: ... check = map.set_relative_time(i, i + 1, 'years') ... else: ... check = map.set_relative_time(i, None, 'years') ... maps.append(map) >>> for map in maps: ... map.temporal_extent.print_info() +-------------------- Relative time -----------------------------------------+ | Start time:................. 0 | End time:................... 1 | Relative time unit:......... years +-------------------- Relative time -----------------------------------------+ | Start time:................. 1 | End time:................... None | Relative time unit:......... years +-------------------- Relative time -----------------------------------------+ | Start time:................. 2 | End time:................... 3 | Relative time unit:......... years +-------------------- Relative time -----------------------------------------+ | Start time:................. 3 | End time:................... None | Relative time unit:......... years +-------------------- Relative time -----------------------------------------+ | Start time:................. 4 | End time:................... 5 | Relative time unit:......... years >>> maps = tgis.AbstractSpaceTimeDataset.shift_map_list(maps, 5) >>> for map in maps: ... map.temporal_extent.print_info() +-------------------- Relative time -----------------------------------------+ | Start time:................. 5 | End time:................... 6 | Relative time unit:......... years +-------------------- Relative time -----------------------------------------+ | Start time:................. 6 | End time:................... None | Relative time unit:......... years +-------------------- Relative time -----------------------------------------+ | Start time:................. 7 | End time:................... 8 | Relative time unit:......... years +-------------------- Relative time -----------------------------------------+ | Start time:................. 8 | End time:................... None | Relative time unit:......... years +-------------------- Relative time -----------------------------------------+ | Start time:................. 9 | End time:................... 10 | Relative time unit:......... years
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snap
(dbif=None)[source]¶ For each registered map snap the end time to the start time of its temporal nearest neighbor in the future
Maps with equal time stamps are not snapped
Parameters: dbif – The database interface to be used
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static
snap_map_list
(maps)[source]¶ For each map in the list snap the end time to the start time of its temporal nearest neighbor in the future.
Maps with equal time stamps are not snapped.
The granularity of the map list will be used to create the end time of the last map in case it has a time instance as timestamp.
This method does not perform any temporal database operations.
Parameters: maps – A list of maps with initialized temporal extent Returns: The modified map list, None nothing to shift or wrong granularity Usage:
>>> import grass.temporal as tgis >>> maps = [] >>> for i in range(5): ... map = tgis.RasterDataset(None) ... if i%2 == 0: ... check = map.set_relative_time(i, i + 1, 'years') ... else: ... check = map.set_relative_time(i, None, 'years') ... maps.append(map) >>> for map in maps: ... map.temporal_extent.print_info() +-------------------- Relative time -----------------------------------------+ | Start time:................. 0 | End time:................... 1 | Relative time unit:......... years +-------------------- Relative time -----------------------------------------+ | Start time:................. 1 | End time:................... None | Relative time unit:......... years +-------------------- Relative time -----------------------------------------+ | Start time:................. 2 | End time:................... 3 | Relative time unit:......... years +-------------------- Relative time -----------------------------------------+ | Start time:................. 3 | End time:................... None | Relative time unit:......... years +-------------------- Relative time -----------------------------------------+ | Start time:................. 4 | End time:................... 5 | Relative time unit:......... years >>> maps = tgis.AbstractSpaceTimeDataset.snap_map_list(maps) >>> for map in maps: ... map.temporal_extent.print_info() +-------------------- Relative time -----------------------------------------+ | Start time:................. 0 | End time:................... 1 | Relative time unit:......... years +-------------------- Relative time -----------------------------------------+ | Start time:................. 1 | End time:................... 2 | Relative time unit:......... years +-------------------- Relative time -----------------------------------------+ | Start time:................. 2 | End time:................... 3 | Relative time unit:......... years +-------------------- Relative time -----------------------------------------+ | Start time:................. 3 | End time:................... 4 | Relative time unit:......... years +-------------------- Relative time -----------------------------------------+ | Start time:................. 4 | End time:................... 5 | Relative time unit:......... years
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unregister_map
(map, dbif=None, execute=True)[source]¶ Unregister a map from the space time dataset.
This method takes care of the un-registration of a map from a space time dataset.
Parameters: - map – The map object to unregister
- dbif – The database interface to be used
- execute – If True the SQL DELETE and DROP table statements will be executed. If False the prepared SQL statements are returned and must be executed by the caller.
Returns: The SQL statements if execute == False, else an empty string, None in case of a failure
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update_command_string
(dbif=None)[source]¶ Append the current command string to any existing command string in the metadata class and calls metadata update
Parameters: dbif – The database interface to be used
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update_from_registered_maps
(dbif=None)[source]¶ This methods updates the modification time, the spatial and temporal extent as well as type specific metadata. It should always been called after maps are registered or unregistered/deleted from the space time dataset.
The update of the temporal extent checks if the end time is set correctly. In case the registered maps have no valid end time (None) the maximum start time will be used. If the end time is earlier than the maximum start time, it will be replaced by the maximum start time.
Parameters: dbif – The database interface to be used
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temporal.aggregation module¶
Aggregation methods for space time raster datasets
Usage:
import grass.temporal as tgis
tgis.aggregate_raster_maps(dataset, mapset, inputs, base, start, end, count, method, register_null, dbif)
(C) 2012-2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
author: | Soeren Gebbert |
---|
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temporal.aggregation.
aggregate_by_topology
(granularity_list, granularity, map_list, topo_list, basename, time_suffix, offset=0, method='average', nprocs=1, spatial=None, dbif=None, overwrite=False, file_limit=1000)[source]¶ Aggregate a list of raster input maps with r.series
Parameters: - granularity_list – A list of AbstractMapDataset objects. The temporal extents of the objects are used to build the spatio-temporal topology with the map list objects
- granularity – The granularity of the granularity list
- map_list – A list of RasterDataset objects that contain the raster maps that should be aggregated
- topo_list – A list of strings of topological relations that are used to select the raster maps for aggregation
- basename – The basename of the new generated raster maps
- time_suffix – Use the granularity truncated start time of the actual granule to create the suffix for the basename
- offset – Use a numerical offset for suffix generation (overwritten by time_suffix)
- method – The aggregation method of r.series (average,min,max, …)
- nprocs – The number of processes used for parallel computation
- spatial – This indicates if the spatial topology is created as well: spatial can be None (no spatial topology), “2D” using west, east, south, north or “3D” using west, east, south, north, bottom, top
- dbif – The database interface to be used
- overwrite – Overwrite existing raster maps
- file_limit – The maximum number of raster map layers that should be opened at once by r.series
Returns: A list of RasterDataset objects that contain the new map names and the temporal extent for map registration
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temporal.aggregation.
aggregate_raster_maps
(inputs, base, start, end, count, method, register_null, dbif, offset=0)[source]¶ Aggregate a list of raster input maps with r.series
Parameters: - inputs – The names of the raster maps to be aggregated
- base – The basename of the new created raster maps
- start – The start time of the sample interval, may be relative or absolute
- end – The end time of the sample interval, may be relative or absolute
- count – The number to be attached to the basename of the new created raster map
- method – The aggreation method to be used by r.series
- register_null – If true null maps will be registered in the space time raster dataset, if false not
- dbif – The temporal database interface to use
- offset – Offset to be added to the map counter to create the map ids
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temporal.aggregation.
collect_map_names
(sp, dbif, start, end, sampling)[source]¶ Gather all maps from dataset using a specific sample method
Parameters: - sp – The space time raster dataset to select aps from
- dbif – The temporal database interface to use
- start – The start time of the sample interval, may be relative or absolute
- end – The end time of the sample interval, may be relative or absolute
- sampling – The sampling methods to use
temporal.base module¶
This packages includes all base classes to store basic information like id, name, mapset creation and modification time as well as sql serialization and de-serialization and the sql database interface.
Usage:
>>> import grass.temporal as tgis
>>> tgis.init()
>>> rbase = tgis.RasterBase(ident="soil@PERMANENT")
>>> vbase = tgis.VectorBase(ident="soil:1@PERMANENT")
>>> r3base = tgis.Raster3DBase(ident="soil@PERMANENT")
>>> strdsbase = tgis.STRDSBase(ident="soil@PERMANENT")
>>> stvdsbase = tgis.STVDSBase(ident="soil@PERMANENT")
>>> str3dsbase = tgis.STR3DSBase(ident="soil@PERMANENT")
(C) 2011-2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
author: | Soeren Gebbert |
---|
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class
temporal.base.
AbstractSTDSRegister
(table=None, ident=None, registered_stds=None)[source]¶ Bases:
temporal.base.SQLDatabaseInterface
This is the base class for all maps to store the space time datasets as comma separated string in which they are registered
Usage:
>>> init() >>> t = AbstractSTDSRegister("raster", "soil@PERMANENT", "A@P,B@P,C@P") >>> t.id 'soil@PERMANENT' >>> t.registered_stds 'A@P,B@P,C@P'
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get_id
()[source]¶ Convenient method to get the unique identifier (primary key)
Returns: None if not found
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get_registered_stds
()[source]¶ Get the comma separated list of space time datasets ids in which this map is registered
Returns: None if not found
-
id
¶ Convenient method to get the unique identifier (primary key)
Returns: None if not found
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registered_stds
¶ Get the comma separated list of space time datasets ids in which this map is registered
Returns: None if not found
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set_id
(ident)[source]¶ Convenient method to set the unique identifier (primary key)
Parameters: ident – The unique identifier must be a combination of the dataset name, layer name and the mapset “name@mapset” or “name:layer@mapset”
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class
temporal.base.
DatasetBase
(table=None, ident=None, name=None, mapset=None, creator=None, ctime=None, ttype=None)[source]¶ Bases:
temporal.base.SQLDatabaseInterface
This is the base class for all maps and spacetime datasets storing basic identification information
Usage:
>>> init() >>> t = DatasetBase("raster", "soil@PERMANENT", creator="soeren", ctime=datetime(2001,1,1), ttype="absolute") >>> t.id 'soil@PERMANENT' >>> t.name 'soil' >>> t.mapset 'PERMANENT' >>> t.creator 'soeren' >>> t.ctime datetime.datetime(2001, 1, 1, 0, 0) >>> t.ttype 'absolute' >>> t.print_info() +-------------------- Basic information -------------------------------------+ | Id: ........................ soil@PERMANENT | Name: ...................... soil | Mapset: .................... PERMANENT | Creator: ................... soeren | Temporal type: ............. absolute | Creation time: ............. 2001-01-01 00:00:00 >>> t.print_shell_info() id=soil@PERMANENT name=soil mapset=PERMANENT creator=soeren temporal_type=absolute creation_time='2001-01-01 00:00:00'
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creator
¶ Get the creator of the dataset :return: None if not found
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ctime
¶ Get the creation time of the dataset, datatype is datetime :return: None if not found
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get_ctime
()[source]¶ Get the creation time of the dataset, datatype is datetime :return: None if not found
-
get_id
()[source]¶ Convenient method to get the unique identifier (primary key)
Returns: None if not found
-
get_layer
()[source]¶ Convenient method to get the layer of the map (part of primary key)
Layer are currently supported for vector maps
Returns: None if not found
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get_map_id
()[source]¶ Convenient method to get the unique map identifier without layer information
Returns: the name of the vector map as “name@mapset” or None in case the id was not set
-
id
¶ Convenient method to get the unique identifier (primary key)
Returns: None if not found
-
map_id
¶ Convenient method to get the unique map identifier without layer information
Returns: the name of the vector map as “name@mapset” or None in case the id was not set
-
mapset
¶ Get the name of mapset of this dataset :return: None if not found
-
name
¶ Get the name of the dataset :return: None if not found
-
set_creator
(creator)[source]¶ Set the creator of the dataset
Parameters: creator – The name of the creator
-
set_ctime
(ctime=None)[source]¶ Set the creation time of the dataset, if nothing set the current time is used
Parameters: ctime – The current time of type datetime
-
set_id
(ident)[source]¶ Convenient method to set the unique identifier (primary key)
Parameters: ident – The unique identifier must be a combination of the dataset name, layer name and the mapset “name@mapset” or “name:layer@mapset”
-
set_layer
(layer)[source]¶ Convenient method to set the layer of the map (part of primary key)
Layer are supported for vector maps
Parameters: layer – The layer of the map
-
set_mapset
(mapset)[source]¶ Set the mapset of the dataset
Parameters: mapset – The name of the mapset in which this dataset is stored
-
set_ttype
(ttype)[source]¶ Set the temporal type of the dataset: absolute or relative, if nothing set absolute time will assumed
Parameters: ttype – The temporal type of the dataset “absolute or relative”
-
ttype
¶ Get the temporal type of the map :return: None if not found
-
-
class
temporal.base.
DictSQLSerializer
[source]¶ Bases:
object
-
deserialize
(row)[source]¶ Convert the content of the dbmi dictionary like row into the internal dictionary
Parameters: row – The dictionary like row to store in the internal dict
-
serialize
(type, table, where=None)[source]¶ Convert the internal dictionary into a string of semicolon separated SQL statements The keys are the column names and the values are the row entries
Usage:
>>> init() >>> t = DictSQLSerializer() >>> t.D["id"] = "soil@PERMANENT" >>> t.D["name"] = "soil" >>> t.D["mapset"] = "PERMANENT" >>> t.D["creator"] = "soeren" >>> t.D["creation_time"] = datetime(2001,1,1) >>> t.D["modification_time"] = datetime(2001,1,1) >>> t.serialize(type="SELECT", table="raster_base") ('SELECT name , creator , creation_time , modification_time , mapset , id FROM raster_base ;\n', ()) >>> t.serialize(type="INSERT", table="raster_base") ('INSERT INTO raster_base ( name ,creator ,creation_time ,modification_time ,mapset ,id ) VALUES (? ,? ,? ,? ,? ,?) ;\n', ('soil', 'soeren', datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2001, 1, 1, 0, 0), 'PERMANENT', 'soil@PERMANENT')) >>> t.serialize(type="UPDATE", table="raster_base") ('UPDATE raster_base SET name = ? ,creator = ? ,creation_time = ? ,modification_time = ? ,mapset = ? ,id = ? ;\n', ('soil', 'soeren', datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2001, 1, 1, 0, 0), 'PERMANENT', 'soil@PERMANENT')) >>> t.serialize(type="UPDATE ALL", table="raster_base") ('UPDATE raster_base SET name = ? ,creator = ? ,creation_time = ? ,modification_time = ? ,mapset = ? ,id = ? ;\n', ('soil', 'soeren', datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2001, 1, 1, 0, 0), 'PERMANENT', 'soil@PERMANENT')) :param type: must be SELECT. INSERT, UPDATE :param table: The name of the table to select, insert or update :param where: The optional where statement :return: a tuple containing the SQL string and the arguments
-
-
class
temporal.base.
Raster3DBase
(ident=None, name=None, mapset=None, creator=None, creation_time=None, temporal_type=None)[source]¶ Bases:
temporal.base.DatasetBase
Time stamped 3D raster map base information class
-
class
temporal.base.
Raster3DSTDSRegister
(ident=None, registered_stds=None)[source]¶ Bases:
temporal.base.AbstractSTDSRegister
Time stamped 3D raster map base information class
-
class
temporal.base.
RasterBase
(ident=None, name=None, mapset=None, creator=None, creation_time=None, temporal_type=None)[source]¶ Bases:
temporal.base.DatasetBase
Time stamped raster map base information class
-
class
temporal.base.
RasterSTDSRegister
(ident=None, registered_stds=None)[source]¶ Bases:
temporal.base.AbstractSTDSRegister
Time stamped raster map base information class
-
class
temporal.base.
SQLDatabaseInterface
(table=None, ident=None)[source]¶ Bases:
temporal.base.DictSQLSerializer
This class represents the SQL database interface
Functions to insert, select and update the internal structure of this class in the temporal database are implemented. This is the base class for raster, raster3d, vector and space time datasets data management classes:
- Identification information (base)
- Spatial extent
- Temporal extent
- Metadata
Usage:
>>> init() >>> t = SQLDatabaseInterface("raster", "soil@PERMANENT") >>> t.mapset = get_current_mapset() >>> t.D["name"] = "soil" >>> t.D["mapset"] = "PERMANENT" >>> t.D["creator"] = "soeren" >>> t.D["creation_time"] = datetime(2001,1,1) >>> t.get_delete_statement() "DELETE FROM raster WHERE id = 'soil@PERMANENT';\n" >>> t.get_is_in_db_statement() "SELECT id FROM raster WHERE id = 'soil@PERMANENT';\n" >>> t.get_select_statement() ("SELECT creation_time , mapset , name , creator FROM raster WHERE id = 'soil@PERMANENT';\n", ()) >>> t.get_select_statement_mogrified() "SELECT creation_time , mapset , name , creator FROM raster WHERE id = 'soil@PERMANENT';\n" >>> t.get_insert_statement() ('INSERT INTO raster ( creation_time ,mapset ,name ,creator ) VALUES (? ,? ,? ,?) ;\n', (datetime.datetime(2001, 1, 1, 0, 0), 'PERMANENT', 'soil', 'soeren')) >>> t.get_insert_statement_mogrified() "INSERT INTO raster ( creation_time ,mapset ,name ,creator ) VALUES ('2001-01-01 00:00:00' ,'PERMANENT' ,'soil' ,'soeren') ;\n" >>> t.get_update_statement() ("UPDATE raster SET creation_time = ? ,mapset = ? ,name = ? ,creator = ? WHERE id = 'soil@PERMANENT';\n", (datetime.datetime(2001, 1, 1, 0, 0), 'PERMANENT', 'soil', 'soeren')) >>> t.get_update_statement_mogrified() "UPDATE raster SET creation_time = '2001-01-01 00:00:00' ,mapset = 'PERMANENT' ,name = 'soil' ,creator = 'soeren' WHERE id = 'soil@PERMANENT';\n" >>> t.get_update_all_statement() ("UPDATE raster SET creation_time = ? ,mapset = ? ,name = ? ,creator = ? WHERE id = 'soil@PERMANENT';\n", (datetime.datetime(2001, 1, 1, 0, 0), 'PERMANENT', 'soil', 'soeren')) >>> t.get_update_all_statement_mogrified() "UPDATE raster SET creation_time = '2001-01-01 00:00:00' ,mapset = 'PERMANENT' ,name = 'soil' ,creator = 'soeren' WHERE id = 'soil@PERMANENT';\n"
-
delete
(dbif=None)[source]¶ Delete the entry of this object from the temporal database
Parameters: dbif – The database interface to be used, if None a temporary connection will be established
-
get_insert_statement
()[source]¶ Return the sql statement and the argument list in database specific style :return: The INSERT string
-
get_insert_statement_mogrified
(dbif=None)[source]¶ Return the insert statement as mogrified string
Parameters: dbif – The database interface to be used, if None a temporary connection will be established Returns: The INSERT string
-
get_is_in_db_statement
()[source]¶ Return the selection string that checks if this object is registered in the temporal database :return: The SELECT string
-
get_select_statement
()[source]¶ Return the sql statement and the argument list in database specific style :return: The SELECT string
-
get_select_statement_mogrified
(dbif=None)[source]¶ Return the select statement as mogrified string
Parameters: dbif – The database interface to be used, if None a temporary connection will be established Returns: The SELECT string
-
get_table_name
()[source]¶ Return the name of the table in which the internal data are inserted, updated or selected :return: The name of the table
-
get_update_all_statement
(ident=None)[source]¶ Return the sql statement and the argument list in database specific style
Parameters: ident – The identifier to be updated, useful for renaming Returns: The UPDATE string
-
get_update_all_statement_mogrified
(dbif=None, ident=None)[source]¶ Return the update all statement as mogrified string
Parameters: - dbif – The database interface to be used, if None a temporary connection will be established
- ident – The identifier to be updated, useful for renaming
Returns: The UPDATE string
-
get_update_statement
(ident=None)[source]¶ Return the sql statement and the argument list in database specific style
Parameters: ident – The identifier to be updated, useful for renaming Returns: The UPDATE string
-
get_update_statement_mogrified
(dbif=None, ident=None)[source]¶ Return the update statement as mogrified string
Parameters: - dbif – The database interface to be used, if None a temporary connection will be established
- ident – The identifier to be updated, useful for renaming
Returns: The UPDATE string
-
insert
(dbif=None)[source]¶ Serialize the content of this object and store it in the temporal database using the internal identifier
Parameters: dbif – The database interface to be used, if None a temporary connection will be established
-
is_in_db
(dbif=None)[source]¶ Check if this object is present in the temporal database
Parameters: dbif – The database interface to be used, if None a temporary connection will be established Returns: True if this object is present in the temporal database, False otherwise
-
select
(dbif=None)[source]¶ Select the content from the temporal database and store it in the internal dictionary structure
Parameters: dbif – The database interface to be used, if None a temporary connection will be established
-
update
(dbif=None, ident=None)[source]¶ Serialize the content of this object and update it in the temporal database using the internal identifier
Only object entries which are exists (not None) are updated
Parameters: - dbif – The database interface to be used, if None a temporary connection will be established
- ident – The identifier to be updated, useful for renaming
-
update_all
(dbif=None, ident=None)[source]¶ Serialize the content of this object, including None objects, and update it in the temporal database using the internal identifier
param dbif: The database interface to be used, if None a temporary connection will be established param ident: The identifier to be updated, useful for renaming
-
class
temporal.base.
STDSBase
(table=None, ident=None, name=None, mapset=None, semantic_type=None, creator=None, ctime=None, ttype=None, mtime=None)[source]¶ Bases:
temporal.base.DatasetBase
Base class for space time datasets
This class adds the semantic type member variable to the dataset base class.Usage:
>>> init() >>> t = STDSBase("stds", "soil@PERMANENT", semantic_type="average", creator="soeren", ctime=datetime(2001,1,1), ttype="absolute", mtime=datetime(2001,1,1)) >>> t.semantic_type 'average' >>> t.print_info() +-------------------- Basic information -------------------------------------+ | Id: ........................ soil@PERMANENT | Name: ...................... soil | Mapset: .................... PERMANENT | Creator: ................... soeren | Temporal type: ............. absolute | Creation time: ............. 2001-01-01 00:00:00 | Modification time:.......... 2001-01-01 00:00:00 | Semantic type:.............. average >>> t.print_shell_info() id=soil@PERMANENT name=soil mapset=PERMANENT creator=soeren temporal_type=absolute creation_time='2001-01-01 00:00:00' modification_time='2001-01-01 00:00:00' semantic_type=average
-
get_mtime
()[source]¶ Get the modification time of the space time dataset, datatype is datetime
Returns: None if not found
-
get_semantic_type
()[source]¶ Get the semantic type of the space time dataset :return: None if not found
-
semantic_type
¶ Get the semantic type of the space time dataset :return: None if not found
-
-
class
temporal.base.
STR3DSBase
(ident=None, name=None, mapset=None, semantic_type=None, creator=None, ctime=None, ttype=None)[source]¶ Bases:
temporal.base.STDSBase
Space time 3D raster dataset base information class
-
class
temporal.base.
STRDSBase
(ident=None, name=None, mapset=None, semantic_type=None, creator=None, ctime=None, ttype=None)[source]¶ Bases:
temporal.base.STDSBase
Space time raster dataset base information class
-
class
temporal.base.
STVDSBase
(ident=None, name=None, mapset=None, semantic_type=None, creator=None, ctime=None, ttype=None)[source]¶ Bases:
temporal.base.STDSBase
Space time vector dataset base information class
-
class
temporal.base.
VectorBase
(ident=None, name=None, mapset=None, layer=None, creator=None, creation_time=None, temporal_type=None)[source]¶ Bases:
temporal.base.DatasetBase
Time stamped vector map base information class
-
class
temporal.base.
VectorSTDSRegister
(ident=None, registered_stds=None)[source]¶ Bases:
temporal.base.AbstractSTDSRegister
Time stamped vector map base information class
temporal.c_libraries_interface module¶
Fast and exit-safe interface to GRASS C-library functions using ctypes and multiprocessing
(C) 2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
-
class
temporal.c_libraries_interface.
CLibrariesInterface
[source]¶ Bases:
grass.pygrass.rpc.base.RPCServerBase
Fast and exit-safe interface to GRASS C-libraries functions
This class implements a fast and exit-safe interface to the GRASS gis, raster, 3D raster and vector C-libraries functions.
The C-libraries functions are called via ctypes in a subprocess using a pipe (multiprocessing.Pipe) to transfer the text messages. Hence, the process that uses the CLibrariesInterface will not be exited, if a G_fatal_error() was invoked in the subprocess. In this case the CLibrariesInterface object will simply start a new subprocess and restarts the pipeline.
Usage:
>>> import grass.script as gscript >>> import grass.temporal as tgis >>> gscript.use_temp_region() >>> gscript.run_command("g.region", n=80.0, s=0.0, e=120.0, w=0.0, ... t=1.0, b=0.0, res=10.0, res3=10.0) 0 >>> tgis.init() >>> gscript.run_command("r.mapcalc", expression="test = 1", overwrite=True, quiet=True) 0 >>> gscript.run_command("r3.mapcalc", expression="test = 1", overwrite=True, quiet=True) 0 >>> gscript.run_command("v.random", output="test", n=10, overwrite=True, quiet=True) 0 >>> gscript.run_command("r.timestamp", map="test", date='12 Mar 1995 10:34:40', overwrite=True, quiet=True) 0 >>> gscript.run_command("r3.timestamp", map="test", date='12 Mar 1995 10:34:40', overwrite=True, quiet=True) 0 >>> gscript.run_command("v.timestamp", map="test", date='12 Mar 1995 10:34:40', overwrite=True, quiet=True) 0 # Check mapsets >>> ciface = tgis.CLibrariesInterface() >>> mapsets = ciface.available_mapsets() >>> mapsets[0] == tgis.get_current_mapset() True # Raster map >>> ciface = tgis.CLibrariesInterface() >>> check = ciface.raster_map_exists("test", tgis.get_current_mapset()) >>> print check True >>> ciface.read_raster_info("test", tgis.get_current_mapset()) {'rows': 12, 'north': 80.0, 'min': 1, 'datatype': 'CELL', 'max': 1, 'ewres': 10.0, 'cols': 8, 'west': 0.0, 'east': 120.0, 'nsres': 10.0, 'south': 0.0} >>> info = ciface.read_raster_full_info("test", tgis.get_current_mapset()) >>> info {u'tbres': 1.0, ... 'keyword': 'generated by r.mapcalc', u'bottom': 0.0, 'end_time': None, 'title': 'test', u'south': 0.0} >>> info["start_time"] datetime.datetime(1995, 3, 12, 10, 34, 40) >>> info["end_time"] >>> check = ciface.has_raster_timestamp("test", tgis.get_current_mapset()) >>> print check True >>> if check: ... res = ciface.read_raster_timestamp("test", tgis.get_current_mapset()) ... if res[0]: ... print str(res[1][0]), str(res[1][0]) ... ciface.remove_raster_timestamp("test", tgis.get_current_mapset()) 1995-03-12 10:34:40 1995-03-12 10:34:40 1 >>> ciface.has_raster_timestamp("test", tgis.get_current_mapset()) False >>> ciface.write_raster_timestamp("test", tgis.get_current_mapset(), "13 Jan 1999 14:30:05") 1 >>> ciface.has_raster_timestamp("test", tgis.get_current_mapset()) True # 3D raster map >>> check = ciface.raster3d_map_exists("test", tgis.get_current_mapset()) >>> print check True >>> ciface.read_raster3d_info("test", tgis.get_current_mapset()) {'tbres': 1.0, 'rows': 12, 'north': 80.0, 'bottom': 0.0, 'datatype': 'DCELL', 'max': 1.0, 'top': 1.0, 'min': 1.0, 'cols': 8, 'depths': 1, 'west': 0.0, 'ewres': 10.0, 'east': 120.0, 'nsres': 10.0, 'south': 0.0} >>> check = ciface.has_raster3d_timestamp("test", tgis.get_current_mapset()) >>> print check True >>> if check: ... res = ciface.read_raster3d_timestamp("test", tgis.get_current_mapset()) ... if res[0]: ... print str(res[1][0]), str(res[1][0]) ... ciface.remove_raster3d_timestamp("test", tgis.get_current_mapset()) 1995-03-12 10:34:40 1995-03-12 10:34:40 1 >>> ciface.has_raster3d_timestamp("test", tgis.get_current_mapset()) False >>> ciface.write_raster3d_timestamp("test", tgis.get_current_mapset(), "13 Jan 1999 14:30:05") 1 >>> ciface.has_raster3d_timestamp("test", tgis.get_current_mapset()) True # Vector map >>> check = ciface.vector_map_exists("test", tgis.get_current_mapset()) >>> print check True >>> kvp = ciface.read_vector_info("test", tgis.get_current_mapset()) >>> kvp['points'] 10 >>> kvp = ciface.read_vector_full_info("test", tgis.get_current_mapset()) >>> print kvp['points'] 10 >>> kvp['point'] 10 >>> kvp['area'] 0 >>> kvp['lines'] 0 >>> kvp['line'] 0 >>> 'columns' in kvp False >>> kvp["start_time"] datetime.datetime(1995, 3, 12, 10, 34, 40) >>> kvp["end_time"] >>> check = ciface.has_vector_timestamp("test", tgis.get_current_mapset(), None) >>> print check True >>> if check: ... res = ciface.read_vector_timestamp("test", tgis.get_current_mapset()) ... if res[0]: ... print str(res[1][0]), str(res[1][0]) ... ciface.remove_vector_timestamp("test", tgis.get_current_mapset()) 1995-03-12 10:34:40 1995-03-12 10:34:40 1 >>> ciface.has_vector_timestamp("test", tgis.get_current_mapset()) False >>> ciface.write_vector_timestamp("test", tgis.get_current_mapset(), "13 Jan 1999 14:30:05") 1 >>> ciface.has_vector_timestamp("test", tgis.get_current_mapset()) True >>> ciface.get_driver_name() 'sqlite' >>> ciface.get_database_name().split("/")[-1] 'sqlite.db' >>> mapset = ciface.get_mapset() >>> location = ciface.get_location() >>> gisdbase = ciface.get_gisdbase() >>> ciface.fatal_error() Traceback (most recent call last): raise FatalError("Exception raised: " + str(e) + " Message: " + message) FatalError: Exception raised: ... >>> ciface.fatal_error() Traceback (most recent call last): raise FatalError("Exception raised: " + str(e) + " Message: " + message) FatalError: Exception raised: ... >>> ciface.fatal_error() Traceback (most recent call last): raise FatalError("Exception raised: " + str(e) + " Message: " + message) FatalError: Exception raised: ... >>> ciface.fatal_error() Traceback (most recent call last): raise FatalError("Exception raised: " + str(e) + " Message: " + message) FatalError: Exception raised: ... >>> ciface.stop() >>> gscript.del_temp_region()
-
available_mapsets
()[source]¶ Return all available mapsets the user can access as a list of strings
Returns: Names of available mapsets as list of strings
-
fatal_error
(mapset=None)[source]¶ Generate a fatal error in libgis.
This function is only for testing purpose.
-
get_database_name
(mapset=None)[source]¶ Return the temporal database name of a specific mapset
Parameters: mapset – Name of the mapset Returns: Name of the database or None if no temporal database present
-
get_driver_name
(mapset=None)[source]¶ Return the temporal database driver of a specific mapset
Parameters: mapset – Name of the mapset Returns: Name of the driver or None if no temporal database present
-
has_raster3d_timestamp
(name, mapset)[source]¶ Check if a file based 3D raster timestamp exists
Parameters: - name – The name of the map
- mapset – The mapset of the map
Returns: True if exists, False if not
-
has_raster_timestamp
(name, mapset)[source]¶ Check if a file based raster timestamp exists
Parameters: - name – The name of the map
- mapset – The mapset of the map
Returns: True if exists, False if not
-
has_vector_timestamp
(name, mapset, layer=None)[source]¶ Check if a file based vector timestamp exists
Parameters: - name – The name of the map
- mapset – The mapset of the map
- layer – The layer of the vector map
Returns: True if exists, False if not
-
raster3d_map_exists
(name, mapset)[source]¶ Check if a 3D raster map exists in the spatial database
Parameters: - name – The name of the map
- mapset – The mapset of the map
Returns: True if exists, False if not
-
raster_map_exists
(name, mapset)[source]¶ Check if a raster map exists in the spatial database
Parameters: - name – The name of the map
- mapset – The mapset of the map
Returns: True if exists, False if not
-
read_raster3d_info
(name, mapset)[source]¶ Read the 3D raster map info from the file system and store the content into a dictionary
Parameters: - name – The name of the map
- mapset – The mapset of the map
Returns: The key value pairs of the map specific metadata, or None in case of an error
-
read_raster3d_timestamp
(name, mapset)[source]¶ Read a file based 3D raster timestamp
Please have a look at the documentation G_read_raster3d_timestamp for the return values description.
- The timestamps to be send are tuples of values:
- relative time (start, end, unit), start and end are of type integer, unit is of type string.
- absolute time (start, end), start and end are of type datetime
The end time may be None in case of a time instance.
Parameters: - name – The name of the map
- mapset – The mapset of the map
Returns: The return value of G_read_raster3d_timestamp
-
read_raster_full_info
(name, mapset)[source]¶ Read raster info, history and cats using PyGRASS RasterRow and return a dictionary. Colors should be supported in the future.
Parameters: - name – The name of the map
- mapset – The mapset of the map
Returns: The key value pairs of the map specific metadata, or None in case of an error
-
read_raster_info
(name, mapset)[source]¶ Read the raster map info from the file system and store the content into a dictionary
Parameters: - name – The name of the map
- mapset – The mapset of the map
Returns: The key value pairs of the map specific metadata, or None in case of an error
-
read_raster_timestamp
(name, mapset)[source]¶ Read a file based raster timestamp
Please have a look at the documentation G_read_raster_timestamp for the return values description.
- The timestamps to be send are tuples of values:
- relative time (start, end, unit), start and end are of type integer, unit is of type string.
- absolute time (start, end), start and end are of type datetime
The end time may be None in case of a time instance.
Parameters: - name – The name of the map
- mapset – The mapset of the map
Returns: The return value of G_read_raster_timestamp
-
read_vector_full_info
(name, mapset)[source]¶ Read vector info using PyGRASS VectorTopo and return a dictionary.
Parameters: - name – The name of the map
- mapset – The mapset of the map
Returns: The key value pairs of the map specific metadata, or None in case of an error
-
read_vector_info
(name, mapset)[source]¶ Read the vector map info from the file system and store the content into a dictionary
Parameters: - name – The name of the map
- mapset – The mapset of the map
Returns: The key value pairs of the map specific metadata, or None in case of an error
-
read_vector_timestamp
(name, mapset, layer=None)[source]¶ Read a file based vector timestamp
Please have a look at the documentation G_read_vector_timestamp for the return values description.
- The timestamps to be send are tuples of values:
- relative time (start, end, unit), start and end are of type integer, unit is of type string.
- absolute time (start, end), start and end are of type datetime
The end time may be None in case of a time instance.
Parameters: - name – The name of the map
- mapset – The mapset of the map
- layer – The layer of the vector map
Returns: The return value ofG_read_vector_timestamp and the timestamps
-
remove_raster3d_timestamp
(name, mapset)[source]¶ Remove a file based 3D raster timestamp
Please have a look at the documentation G_remove_raster3d_timestamp for the return values description.
Parameters: - name – The name of the map
- mapset – The mapset of the map
Returns: The return value of G_remove_raster3d_timestamp
-
remove_raster_timestamp
(name, mapset)[source]¶ Remove a file based raster timestamp
Please have a look at the documentation G_remove_raster_timestamp for the return values description.
Parameters: - name – The name of the map
- mapset – The mapset of the map
Returns: The return value of G_remove_raster_timestamp
-
remove_vector_timestamp
(name, mapset, layer=None)[source]¶ Remove a file based vector timestamp
Please have a look at the documentation G_remove_vector_timestamp for the return values description.
Parameters: - name – The name of the map
- mapset – The mapset of the map
- layer – The layer of the vector map
Returns: The return value of G_remove_vector_timestamp
-
vector_map_exists
(name, mapset)[source]¶ Check if a vector map exists in the spatial database
Parameters: - name – The name of the map
- mapset – The mapset of the map
Returns: True if exists, False if not
-
write_raster3d_timestamp
(name, mapset, timestring)[source]¶ Write a file based 3D raster timestamp
Please have a look at the documentation G_write_raster3d_timestamp for the return values description.
- Note:
- Only timestamps of maps from the current mapset can written.
Parameters: - name – The name of the map
- mapset – The mapset of the map
- timestring – A GRASS datetime C-library compatible string
Returns: The return value of G_write_raster3d_timestamp
-
write_raster_timestamp
(name, mapset, timestring)[source]¶ Write a file based raster timestamp
Please have a look at the documentation G_write_raster_timestamp for the return values description.
- Note:
- Only timestamps of maps from the current mapset can written.
Parameters: - name – The name of the map
- mapset – The mapset of the map
- timestring – A GRASS datetime C-library compatible string
Returns: The return value of G_write_raster_timestamp
-
write_vector_timestamp
(name, mapset, timestring, layer=None)[source]¶ Write a file based vector timestamp
Please have a look at the documentation G_write_vector_timestamp for the return values description.
- Note:
- Only timestamps pf maps from the current mapset can written.
Parameters: - name – The name of the map
- mapset – The mapset of the map
- timestring – A GRASS datetime C-library compatible string
- layer – The layer of the vector map
Returns: The return value of G_write_vector_timestamp
-
-
class
temporal.c_libraries_interface.
RPCDefs
[source]¶ Bases:
object
-
AVAILABLE_MAPSETS
= 8¶
-
GET_DATABASE_NAME
= 10¶
-
GET_DRIVER_NAME
= 9¶
-
G_FATAL_ERROR
= 49¶
-
G_GISDBASE
= 13¶
-
G_LOCATION
= 12¶
-
G_MAPSET
= 11¶
-
HAS_TIMESTAMP
= 1¶
-
MAP_EXISTS
= 6¶
-
READ_MAP_FULL_INFO
= 14¶
-
READ_MAP_INFO
= 7¶
-
READ_TIMESTAMP
= 3¶
-
REMOVE_TIMESTAMP
= 4¶
-
STOP
= 0¶
-
TYPE_RASTER
= 0¶
-
TYPE_RASTER3D
= 1¶
-
TYPE_VECTOR
= 2¶
-
WRITE_TIMESTAMP
= 2¶
-
temporal.core module¶
This module provides the functionality to create the temporal SQL database and to establish a connection to the database.
Usage:
>>> import grass.temporal as tgis
>>> # Create the temporal database
>>> tgis.init()
>>> # Establish a database connection
>>> dbif, connected = tgis.init_dbif(None)
>>> dbif.connect()
>>> # Execute a SQL statement
>>> dbif.execute_transaction("SELECT datetime(0, 'unixepoch', 'localtime');")
>>> # Mogrify an SQL statement
>>> dbif.mogrify_sql_statement(["SELECT name from raster_base where name = ?",
... ("precipitation",)])
"SELECT name from raster_base where name = 'precipitation'"
>>> dbif.close()
(C) 2011-2014 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
author: | Soeren Gebbert |
---|
-
class
temporal.core.
DBConnection
(backend=None, dbstring=None)[source]¶ Bases:
object
This class represents the database interface connection and provides access to the chosen backend modules.
The following DBMS are supported:
- sqlite via the sqlite3 standard library
- postgresql via psycopg2
-
check_table
(table_name)[source]¶ Check if a table exists in the temporal database
Parameters: - table_name – The name of the table to be checked for existence
- mapset – The mapset of the abstract dataset or temporal database location, if None the current mapset will be used
Returns: True if the table exists, False otherwise
TODO: There may be several temporal databases in a location, hence the mapset is used to query the correct temporal database.
-
close
()[source]¶ Close the DBMI connection TODO: There may be several temporal databases in a location, hence close all temporal databases that have been opened. Use a dictionary to manage different connections.
-
connect
(dbstring=None)[source]¶ Connect to the DBMI to execute SQL statements
Supported backends are sqlite3 and postgresql
param dbstring: The database connection string
-
execute
(statement, args=None)[source]¶ Execute a SQL statement
Parameters: statement – The executable SQL statement or SQL script
-
execute_transaction
(statement, mapset=None)[source]¶ Execute a transactional SQL statement
The BEGIN and END TRANSACTION statements will be added automatically to the sql statement
Parameters: statement – The executable SQL statement or SQL script
-
mogrify_sql_statement
(content)[source]¶ Return the SQL statement and arguments as executable SQL string
TODO: Use the mapset argument to identify the correct database driver
Parameters: - content – The content as tuple with two entries, the first entry is the SQL statement with DBMI specific place holder (?), the second entry is the argument list that should substitute the place holder.
- mapset – The mapset of the abstract dataset or temporal database location, if None the current mapset will be used
Usage:
>>> init() >>> dbif = SQLDatabaseInterfaceConnection() >>> dbif.mogrify_sql_statement(["SELECT ctime FROM raster_base WHERE id = ?", ... ["soil@PERMANENT",]]) "SELECT ctime FROM raster_base WHERE id = 'soil@PERMANENT'"
-
class
temporal.core.
SQLDatabaseInterfaceConnection
[source]¶ Bases:
object
-
check_table
(table_name, mapset=None)[source]¶ Check if a table exists in the temporal database
Parameters: - table_name – The name of the table to be checked for existence
- mapset – The mapset of the abstract dataset or temporal database location, if None the current mapset will be used
Returns: True if the table exists, False otherwise
TODO: There may be several temporal databases in a location, hence the mapset is used to query the correct temporal database.
-
close
()[source]¶ Close the DBMI connection
There may be several temporal databases in a location, hence close all temporal databases that have been opened.
-
connect
()[source]¶ Connect to the DBMI to execute SQL statements
Supported backends are sqlite3 and postgresql
-
execute
(statement, args=None, mapset=None)[source]¶ Parameters: mapset – The mapset of the abstract dataset or temporal database location, if None the current mapset will be used
-
execute_transaction
(statement, mapset=None)[source]¶ Execute a transactional SQL statement
The BEGIN and END TRANSACTION statements will be added automatically to the sql statement
Parameters: statement – The executable SQL statement or SQL script
-
mogrify_sql_statement
(content, mapset=None)[source]¶ Return the SQL statement and arguments as executable SQL string
Parameters: - content – The content as tuple with two entries, the first entry is the SQL statement with DBMI specific place holder (?), the second entry is the argument list that should substitute the place holder.
- mapset – The mapset of the abstract dataset or temporal database location, if None the current mapset will be used
-
-
temporal.core.
create_temporal_database
(dbif)[source]¶ This function will create the temporal database
It will create all tables and triggers that are needed to run the temporal GIS
Parameters: dbif – The database interface to be used
-
temporal.core.
downgrade_temporal_database
(dbif)[source]¶ This function will downgrade the temporal database if needed.
It will downdate all tables and triggers that are requested by currently supported TGIS DB version.
Parameters: dbif – The database interface to be used
-
temporal.core.
get_available_temporal_mapsets
()[source]¶ Return a list of of mapset names with temporal database driver and names that are accessible from the current mapset.
Returns: A dictionary, mapset names are keys, the tuple (driver, database) are the values
-
temporal.core.
get_current_gisdbase
()[source]¶ Return the current gis database (gisdbase)
This is the fastest way to receive the current gisdbase. The current gisdbase is set by init() and stored in a global variable. This function provides access to this global variable.
-
temporal.core.
get_current_location
()[source]¶ Return the current location
This is the fastest way to receive the current location. The current location is set by init() and stored in a global variable. This function provides access to this global variable.
-
temporal.core.
get_current_mapset
()[source]¶ Return the current mapset
This is the fastest way to receive the current mapset. The current mapset is set by init() and stored in a global variable. This function provides access to this global variable.
-
temporal.core.
get_enable_mapset_check
()[source]¶ Return True if the mapsets should be checked while insert, update, delete requests and space time dataset registration.
If this global variable is set True, then maps can only be registered in space time datasets with the same mapset. In addition, only maps in the current mapset can be inserted, updated or deleted from the temporal database. Overwrite this global variable by: g.gisenv set=”TGIS_DISABLE_MAPSET_CHECK=True”
..warning:
Be aware to face corrupted temporal database in case this global variable is set to False. This feature is highly experimental and violates the grass permission guidance.
-
temporal.core.
get_enable_timestamp_write
()[source]¶ Return True if the map timestamps should be written to the spatial database metadata as well.
If this global variable is set True, the timestamps of maps will be written as textfiles for each map that will be inserted or updated in the temporal database using the C-library timestamp interface. Overwrite this global variable by: g.gisenv set=”TGIS_DISABLE_TIMESTAMP_WRITE=True”
..warning:
Be aware that C-libraries can not access timestamp information if they are not written as spatial database metadata, hence modules that make use of timestamps using the C-library interface will not work with maps that were created without writing the timestamps.
-
temporal.core.
get_raise_on_error
()[source]¶ Return True if a FatalError exception is raised instead of calling sys.exit(1) in case a fatal error was invoked with msgr.fatal()
-
temporal.core.
get_tgis_backend
()[source]¶ Return the temporal GIS backend as string
Returns: either “sqlite” or “pg”
-
temporal.core.
get_tgis_c_library_interface
()[source]¶ Return the C-library interface that provides a fast and exit safe interface to the C-library libgis, libraster, libraster3d and libvector functions
-
temporal.core.
get_tgis_database
()[source]¶ Return the temporal database string specified with t.connect
-
temporal.core.
get_tgis_database_string
()[source]¶ Return the preprocessed temporal database string
This string is the temporal database string set with t.connect that was processed to substitue location, gisdbase and mapset variables.
-
temporal.core.
get_tgis_db_version
()[source]¶ Get the version number of the temporal framework :returns: The version number of the temporal framework as string
-
temporal.core.
get_tgis_db_version_from_metadata
(metadata=None)[source]¶ Get the version number of the temporal database from metadata
Parameters: metadata (list) – list of metadata items or None Returns: The version number of the temporal database as integer
-
temporal.core.
get_tgis_dbmi_paramstyle
()[source]¶ Return the temporal database backend parameter style
Returns: “qmark” or “”
-
temporal.core.
get_tgis_message_interface
()[source]¶ Return the temporal GIS message interface which is of type grass.pygrass.message.Messenger()
Use this message interface to print messages to stdout using the GRASS C-library messaging system.
-
temporal.core.
get_tgis_metadata
(dbif=None)[source]¶ Return the tgis metadata table as a list of rows (dicts) or None if not present
Parameters: dbif – The database interface to be used Returns: The selected rows with key/value columns or None
-
temporal.core.
get_tgis_version
()[source]¶ Get the version number of the temporal framework :returns: The version number of the temporal framework as string
-
temporal.core.
init
(raise_fatal_error=False, skip_db_version_check=False)[source]¶ - This function set the correct database backend from GRASS environmental
variables and creates the grass temporal database structure for raster, vector and raster3d maps as well as for the space-time datasets strds, str3ds and stvds in case it does not exist.
Several global variables are initiated and the messenger and C-library interface subprocesses are spawned.
Re-run this function in case the following GRASS variables change while the process runs:
- MAPSET
- LOCATION_NAME
- GISDBASE
- TGIS_DISABLE_MAPSET_CHECK
- TGIS_DISABLE_TIMESTAMP_WRITE
Re-run this function if the following t.connect variables change while the process runs:
- temporal GIS driver (set by t.connect driver=)
- temporal GIS database (set by t.connect database=)
The following environmental variables are checked:
- GRASS_TGIS_PROFILE (True, False, 1, 0)
- GRASS_TGIS_RAISE_ON_ERROR (True, False, 1, 0)
..warning:
This functions must be called before any spatio-temporal processing can be started
param raise_fatal_error: Set this True to assure that the init() function does not kill a persistent process like the GUI. If set True a grass.pygrass.messages.FatalError exception will be raised in case a fatal error occurs in the init process, otherwise sys.exit(1) will be called.
Parameters: skip_db_version_check – Set this True to skip mismatch temporal database version check. Recommended to be used only for downgrade_temporal_database().
-
temporal.core.
init_dbif
(dbif)[source]¶ This method checks if the database interface connection exists, if not a new one will be created, connected and True will be returned. If the database interface exists but is connected, the connection will be established.
Returns: the tuple (dbif, True|False) Usage code sample:
dbif, connect = tgis.init_dbif(None) sql = dbif.mogrify_sql_statement(["SELECT * FROM raster_base WHERE ? = ?"], ["id", "soil@PERMANENT"]) dbif.execute_transaction(sql) if connect: dbif.close()
-
temporal.core.
set_raise_on_error
(raise_exp=True)[source]¶ Define behavior on fatal error, invoked using the tgis messenger interface (msgr.fatal())
The messenger interface will be restarted using the new error policy
Parameters: raise_exp – True to raise a FatalError exception instead of calling sys.exit(1) when using the tgis messenger interface >>> import grass.temporal as tgis >>> tgis.init() >>> ignore = tgis.set_raise_on_error(False) >>> msgr = tgis.get_tgis_message_interface() >>> tgis.get_raise_on_error() False >>> msgr.fatal("Ohh no no no!") Traceback (most recent call last): File "__init__.py", line 239, in fatal sys.exit(1) SystemExit: 1 >>> tgis.set_raise_on_error(True) False >>> msgr.fatal("Ohh no no no!") Traceback (most recent call last): File "__init__.py", line 241, in fatal raise FatalError(message) FatalError: Ohh no no no!
Returns: current status
temporal.datetime_math module¶
Functions for mathematical datetime operations
(C) 2011-2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
-
temporal.datetime_math.
adjust_datetime_to_granularity
(mydate, granularity)[source]¶ Modify the datetime object to fit the given granularity
- Years will start at the first of Januar
- Months will start at the first day of the month
- Days will start at the first Hour of the day
- Hours will start at the first minute of an hour
- Minutes will start at the first second of a minute
Usage:
>>> dt = datetime(2001, 8, 8, 12,30,30) >>> adjust_datetime_to_granularity(dt, "5 seconds") datetime.datetime(2001, 8, 8, 12, 30, 30) >>> adjust_datetime_to_granularity(dt, "20 minutes") datetime.datetime(2001, 8, 8, 12, 30) >>> adjust_datetime_to_granularity(dt, "20 minutes") datetime.datetime(2001, 8, 8, 12, 30) >>> adjust_datetime_to_granularity(dt, "3 hours") datetime.datetime(2001, 8, 8, 12, 0) >>> adjust_datetime_to_granularity(dt, "5 days") datetime.datetime(2001, 8, 8, 0, 0) >>> adjust_datetime_to_granularity(dt, "2 weeks") datetime.datetime(2001, 8, 6, 0, 0) >>> adjust_datetime_to_granularity(dt, "6 months") datetime.datetime(2001, 8, 1, 0, 0) >>> adjust_datetime_to_granularity(dt, "2 years") datetime.datetime(2001, 1, 1, 0, 0) >>> adjust_datetime_to_granularity(dt, "2 years, 3 months, 5 days, 3 hours, 3 minutes, 2 seconds") datetime.datetime(2001, 8, 8, 12, 30, 30) >>> adjust_datetime_to_granularity(dt, "3 months, 5 days, 3 minutes") datetime.datetime(2001, 8, 8, 12, 30) >>> adjust_datetime_to_granularity(dt, "3 weeks, 5 days") datetime.datetime(2001, 8, 8, 0, 0)
-
temporal.datetime_math.
check_datetime_string
(time_string, use_dateutil=True)[source]¶ Check if a string can be converted into a datetime object and return the object
In case datutil is not installed the supported ISO string formats are:
- YYYY-mm-dd
- YYYY-mm-dd HH:MM:SS
- YYYY-mm-ddTHH:MM:SS
- YYYY-mm-dd HH:MM:SS.s
- YYYY-mm-ddTHH:MM:SS.s
Time zones are not supported
If dateutil is installed, all string formats of the dateutil module are supported, as well as time zones Time zones are not supported
Parameters: - time_string – The time string to be checked for conversion
- use_dateutil – Use dateutil if available for datetime string parsing
Returns: datetime: object or an error message string in case of an error
>>> s = "2000-01-01" >>> check_datetime_string(s) datetime.datetime(2000, 1, 1, 0, 0) >>> s = "2000-01-01T10:00:00" >>> check_datetime_string(s) datetime.datetime(2000, 1, 1, 10, 0) >>> s = "2000-01-01 10:00:00" >>> check_datetime_string(s) datetime.datetime(2000, 1, 1, 10, 0) >>> s = "2000-01-01T10:00:00.000001" >>> check_datetime_string(s) datetime.datetime(2000, 1, 1, 10, 0, 0, 1) >>> s = "2000-01-01 10:00:00.000001" >>> check_datetime_string(s) datetime.datetime(2000, 1, 1, 10, 0, 0, 1)
# using native implementation, ignoring dateutil >>> s = “2000-01-01” >>> check_datetime_string(s, False) datetime.datetime(2000, 1, 1, 0, 0) >>> s = “2000-01-01T10:00:00” >>> check_datetime_string(s, False) datetime.datetime(2000, 1, 1, 10, 0) >>> s = “2000-01-01 10:00:00” >>> check_datetime_string(s, False) datetime.datetime(2000, 1, 1, 10, 0) >>> s = “2000-01-01T10:00:00.000001” >>> check_datetime_string(s, False) datetime.datetime(2000, 1, 1, 10, 0, 0, 1) >>> s = “2000-01-01 10:00:00.000001” >>> check_datetime_string(s, False) datetime.datetime(2000, 1, 1, 10, 0, 0, 1)
-
temporal.datetime_math.
compute_datetime_delta
(start, end)[source]¶ Return a dictionary with the accumulated delta in year, month, day, hour, minute and second
Usage:
>>> start = datetime(2001, 1, 1, 00,00,00) >>> end = datetime(2001, 1, 1, 00,00,00) >>> compute_datetime_delta(start, end) {'hour': 0, 'month': 0, 'second': 0, 'max_days': 0, 'year': 0, 'day': 0, 'minute': 0} >>> start = datetime(2001, 1, 1, 00,00,14) >>> end = datetime(2001, 1, 1, 00,00,44) >>> compute_datetime_delta(start, end) {'hour': 0, 'month': 0, 'second': 30, 'max_days': 0, 'year': 0, 'day': 0, 'minute': 0} >>> start = datetime(2001, 1, 1, 00,00,44) >>> end = datetime(2001, 1, 1, 00,01,14) >>> compute_datetime_delta(start, end) {'hour': 0, 'month': 0, 'second': 30, 'max_days': 0, 'year': 0, 'day': 0, 'minute': 1} >>> start = datetime(2001, 1, 1, 00,00,30) >>> end = datetime(2001, 1, 1, 00,05,30) >>> compute_datetime_delta(start, end) {'hour': 0, 'month': 0, 'second': 300, 'max_days': 0, 'year': 0, 'day': 0, 'minute': 5} >>> start = datetime(2001, 1, 1, 00,00,00) >>> end = datetime(2001, 1, 1, 00,01,00) >>> compute_datetime_delta(start, end) {'hour': 0, 'month': 0, 'second': 0, 'max_days': 0, 'year': 0, 'day': 0, 'minute': 1} >>> start = datetime(2011,10,31, 00,45,00) >>> end = datetime(2011,10,31, 01,45,00) >>> compute_datetime_delta(start, end) {'hour': 1, 'second': 0, 'max_days': 0, 'year': 0, 'day': 0, 'minute': 60} >>> start = datetime(2011,10,31, 00,45,00) >>> end = datetime(2011,10,31, 01,15,00) >>> compute_datetime_delta(start, end) {'hour': 1, 'second': 0, 'max_days': 0, 'year': 0, 'day': 0, 'minute': 30} >>> start = datetime(2011,10,31, 00,45,00) >>> end = datetime(2011,10,31, 12,15,00) >>> compute_datetime_delta(start, end) {'hour': 12, 'second': 0, 'max_days': 0, 'year': 0, 'day': 0, 'minute': 690} >>> start = datetime(2011,10,31, 00,00,00) >>> end = datetime(2011,10,31, 01,00,00) >>> compute_datetime_delta(start, end) {'hour': 1, 'second': 0, 'max_days': 0, 'year': 0, 'day': 0, 'minute': 0} >>> start = datetime(2011,10,31, 00,00,00) >>> end = datetime(2011,11,01, 01,00,00) >>> compute_datetime_delta(start, end) {'hour': 25, 'second': 0, 'max_days': 1, 'year': 0, 'day': 1, 'minute': 0} >>> start = datetime(2011,10,31, 12,00,00) >>> end = datetime(2011,11,01, 06,00,00) >>> compute_datetime_delta(start, end) {'hour': 18, 'second': 0, 'max_days': 0, 'year': 0, 'day': 0, 'minute': 0} >>> start = datetime(2011,11,01, 00,00,00) >>> end = datetime(2011,12,01, 01,00,00) >>> compute_datetime_delta(start, end) {'hour': 721, 'month': 1, 'second': 0, 'max_days': 30, 'year': 0, 'day': 0, 'minute': 0} >>> start = datetime(2011,11,01, 00,00,00) >>> end = datetime(2011,11,05, 00,00,00) >>> compute_datetime_delta(start, end) {'hour': 0, 'second': 0, 'max_days': 4, 'year': 0, 'day': 4, 'minute': 0} >>> start = datetime(2011,10,06, 00,00,00) >>> end = datetime(2011,11,05, 00,00,00) >>> compute_datetime_delta(start, end) {'hour': 0, 'second': 0, 'max_days': 30, 'year': 0, 'day': 30, 'minute': 0} >>> start = datetime(2011,12,02, 00,00,00) >>> end = datetime(2012,01,01, 00,00,00) >>> compute_datetime_delta(start, end) {'hour': 0, 'second': 0, 'max_days': 30, 'year': 1, 'day': 30, 'minute': 0} >>> start = datetime(2011,01,01, 00,00,00) >>> end = datetime(2011,02,01, 00,00,00) >>> compute_datetime_delta(start, end) {'hour': 0, 'month': 1, 'second': 0, 'max_days': 31, 'year': 0, 'day': 0, 'minute': 0} >>> start = datetime(2011,12,01, 00,00,00) >>> end = datetime(2012,01,01, 00,00,00) >>> compute_datetime_delta(start, end) {'hour': 0, 'month': 1, 'second': 0, 'max_days': 31, 'year': 1, 'day': 0, 'minute': 0} >>> start = datetime(2011,12,01, 00,00,00) >>> end = datetime(2012,06,01, 00,00,00) >>> compute_datetime_delta(start, end) {'hour': 0, 'month': 6, 'second': 0, 'max_days': 183, 'year': 1, 'day': 0, 'minute': 0} >>> start = datetime(2011,06,01, 00,00,00) >>> end = datetime(2021,06,01, 00,00,00) >>> compute_datetime_delta(start, end) {'hour': 0, 'month': 120, 'second': 0, 'max_days': 3653, 'year': 10, 'day': 0, 'minute': 0} >>> start = datetime(2011,06,01, 00,00,00) >>> end = datetime(2012,06,01, 12,00,00) >>> compute_datetime_delta(start, end) {'hour': 8796, 'month': 12, 'second': 0, 'max_days': 366, 'year': 1, 'day': 0, 'minute': 0} >>> start = datetime(2011,06,01, 00,00,00) >>> end = datetime(2012,06,01, 12,30,00) >>> compute_datetime_delta(start, end) {'hour': 8796, 'month': 12, 'second': 0, 'max_days': 366, 'year': 1, 'day': 0, 'minute': 527790} >>> start = datetime(2011,06,01, 00,00,00) >>> end = datetime(2012,06,01, 12,00,05) >>> compute_datetime_delta(start, end) {'hour': 8796, 'month': 12, 'second': 31665605, 'max_days': 366, 'year': 1, 'day': 0, 'minute': 0} >>> start = datetime(2011,06,01, 00,00,00) >>> end = datetime(2012,06,01, 00,30,00) >>> compute_datetime_delta(start, end) {'hour': 0, 'month': 12, 'second': 0, 'max_days': 366, 'year': 1, 'day': 0, 'minute': 527070} >>> start = datetime(2011,06,01, 00,00,00) >>> end = datetime(2012,06,01, 00,00,05) >>> compute_datetime_delta(start, end) {'hour': 0, 'month': 12, 'second': 31622405, 'max_days': 366, 'year': 1, 'day': 0, 'minute': 0}
Returns: A dictionary with year, month, day, hour, minute and second as keys()
-
temporal.datetime_math.
create_numeric_suffix
(base, count, zeros)[source]¶ Create a string based on count and number of zeros decided by zeros
Parameters: - base – the basename for new map
- count – a number
- zeros – a string containing the expected number, coming from suffix option like “%05”
-
temporal.datetime_math.
create_suffix_from_datetime
(start_time, granularity)[source]¶ Create a datetime string based on a datetime object and a provided granularity that can be used as suffix for map names.
dateteime=2001-01-01 00:00:00, granularity=”1 month” returns “2001_01”
Parameters: - start_time – The datetime object
- granularity – The granularity for example “1 month” or “100 seconds”
Returns: A string
-
temporal.datetime_math.
create_time_suffix
(mapp, end=False)[source]¶ Create a datetime string based on a map datetime object
Parameters: - mapp – a temporal map dataset
- end – True if you want add also end time to the suffix
-
temporal.datetime_math.
datetime_to_grass_datetime_string
(dt)[source]¶ Convert a python datetime object into a GRASS datetime string
>>> import grass.temporal as tgis >>> import dateutil.parser as parser >>> dt = parser.parse("2011-01-01 10:00:00 +01:30") >>> tgis.datetime_to_grass_datetime_string(dt) '01 jan 2011 10:00:00 +0090' >>> dt = parser.parse("2011-01-01 10:00:00 +02:30") >>> tgis.datetime_to_grass_datetime_string(dt) '01 jan 2011 10:00:00 +0150' >>> dt = parser.parse("2011-01-01 10:00:00 +12:00") >>> tgis.datetime_to_grass_datetime_string(dt) '01 jan 2011 10:00:00 +0720' >>> dt = parser.parse("2011-01-01 10:00:00 -01:30") >>> tgis.datetime_to_grass_datetime_string(dt) '01 jan 2011 10:00:00 -0090'
-
temporal.datetime_math.
decrement_datetime_by_string
(mydate, increment, mult=1)[source]¶ Return a new datetime object decremented with the provided relative dates specified as string. Additional a multiplier can be specified to multiply the increment before adding to the provided datetime object.
Usage:
>>> dt = datetime(2001, 1, 1, 0, 0, 0) >>> string = "31 days" >>> decrement_datetime_by_string(dt, string) datetime.datetime(2000, 12, 1, 0, 0) >>> dt = datetime(2001, 1, 1, 0, 0, 0) >>> string = "1 month" >>> decrement_datetime_by_string(dt, string) datetime.datetime(2000, 12, 1, 0, 0) >>> dt = datetime(2001, 1, 1, 0, 0, 0) >>> string = "2 month" >>> decrement_datetime_by_string(dt, string) datetime.datetime(2000, 11, 1, 0, 0) >>> dt = datetime(2001, 1, 1, 0, 0, 0) >>> string = "24 months" >>> decrement_datetime_by_string(dt, string) datetime.datetime(1999, 1, 1, 0, 0) >>> dt = datetime(2001, 1, 1, 0, 0, 0) >>> string = "48 months" >>> decrement_datetime_by_string(dt, string) datetime.datetime(1997, 1, 1, 0, 0) >>> dt = datetime(2001, 6, 1, 0, 0, 0) >>> string = "5 months" >>> decrement_datetime_by_string(dt, string) datetime.datetime(2001, 1, 1, 0, 0) >>> dt = datetime(2001, 6, 1, 0, 0, 0) >>> string = "7 months" >>> decrement_datetime_by_string(dt, string) datetime.datetime(2000, 11, 1, 0, 0) >>> dt = datetime(2001, 1, 1, 0, 0, 0) >>> string = "1 year" >>> decrement_datetime_by_string(dt, string) datetime.datetime(2000, 1, 1, 0, 0)
Parameters: - mydate – A datetime object to incremented
- increment – A string providing increment information: The string may include comma separated values of type seconds, minutes, hours, days, weeks, months and years Example: Increment the datetime 2001-01-01 00:00:00 with “60 seconds, 4 minutes, 12 hours, 10 days, 1 weeks, 5 months, 1 years” will result in the datetime 2003-02-18 12:05:00
- mult – A multiplier, default is 1
Returns: The new datetime object or none in case of an error
-
temporal.datetime_math.
increment_datetime_by_string
(mydate, increment, mult=1)[source]¶ Return a new datetime object incremented with the provided relative dates specified as string. Additional a multiplier can be specified to multiply the increment before adding to the provided datetime object.
Usage:
>>> dt = datetime(2001, 9, 1, 0, 0, 0) >>> string = "60 seconds, 4 minutes, 12 hours, 10 days, 1 weeks, 5 months, 1 years" >>> increment_datetime_by_string(dt, string) datetime.datetime(2003, 2, 18, 12, 5) >>> dt = datetime(2001, 11, 1, 0, 0, 0) >>> string = "1 months" >>> increment_datetime_by_string(dt, string) datetime.datetime(2001, 12, 1, 0, 0) >>> dt = datetime(2001, 11, 1, 0, 0, 0) >>> string = "13 months" >>> increment_datetime_by_string(dt, string) datetime.datetime(2002, 12, 1, 0, 0) >>> dt = datetime(2001, 1, 1, 0, 0, 0) >>> string = "72 months" >>> increment_datetime_by_string(dt, string) datetime.datetime(2007, 1, 1, 0, 0) >>> dt = datetime(2001, 1, 1, 0, 0, 0) >>> string = "72 months" >>> increment_datetime_by_string(dt, string) datetime.datetime(2007, 1, 1, 0, 0) >>> dt = datetime(2001, 1, 1, 0, 0, 0) >>> string = "5 minutes" >>> increment_datetime_by_string(dt, string) datetime.datetime(2001, 1, 1, 0, 5) >>> dt = datetime(2001, 1, 1, 0, 0, 0) >>> string = "49 hours" >>> increment_datetime_by_string(dt, string) datetime.datetime(2001, 1, 3, 1, 0) >>> dt = datetime(2001, 1, 1, 0, 0, 0) >>> string = "3600 seconds" >>> increment_datetime_by_string(dt, string) datetime.datetime(2001, 1, 1, 1, 0) >>> dt = datetime(2001, 1, 1, 0, 0, 0) >>> string = "30 days" >>> increment_datetime_by_string(dt, string) datetime.datetime(2001, 1, 31, 0, 0)
Parameters: - mydate – A datetime object to incremented
- increment – A string providing increment information: The string may include comma separated values of type seconds, minutes, hours, days, weeks, months and years Example: Increment the datetime 2001-01-01 00:00:00 with “60 seconds, 4 minutes, 12 hours, 10 days, 1 weeks, 5 months, 1 years” will result in the datetime 2003-02-18 12:05:00
- mult – A multiplier, default is 1
Returns: The new datetime object or none in case of an error
-
temporal.datetime_math.
modify_datetime
(mydate, years=0, months=0, weeks=0, days=0, hours=0, minutes=0, seconds=0)[source]¶ Return a new datetime object incremented with the provided relative dates and times
-
temporal.datetime_math.
modify_datetime_by_string
(mydate, increment, mult=1, sign=1)[source]¶ Return a new datetime object incremented with the provided relative dates specified as string. Additional a multiplier can be specified to multiply the increment before adding to the provided datetime object.
Parameters: - mydate – A datetime object to incremented
- increment – A string providing increment information: The string may include comma separated values of type seconds, minutes, hours, days, weeks, months and years Example: Increment the datetime 2001-01-01 00:00:00 with “60 seconds, 4 minutes, 12 hours, 10 days, 1 weeks, 5 months, 1 years” will result in the datetime 2003-02-18 12:05:00
- mult – A multiplier, default is 1
- sign – Choose 1 for positive sign (incrementing) or -1 for negative sign (decrementing).
Returns: The new datetime object or none in case of an error
-
temporal.datetime_math.
relative_time_to_time_delta
(value)[source]¶ Convert the double value representing days into a timedelta object.
-
temporal.datetime_math.
relative_time_to_time_delta_seconds
(value)[source]¶ Convert the double value representing seconds into a timedelta object.
-
temporal.datetime_math.
string_to_datetime
(time_string)[source]¶ Convert a string into a datetime object
In case datutil is not installed the supported ISO string formats are:
- YYYY-mm-dd
- YYYY-mm-dd HH:MM:SS
- YYYY-mm-ddTHH:MM:SS
- YYYY-mm-dd HH:MM:SS.s
- YYYY-mm-ddTHH:MM:SS.s
Time zones are not supported
If dateutil is installed, all string formats of the dateutil module are supported, as well as time zones
Parameters: time_string – The time string to convert Returns: datetime object or None in case the string could not be converted
temporal.extract module¶
Extract functions for space time raster, 3d raster and vector datasets
(C) 2012-2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
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temporal.extract.
extract_dataset
(input, output, type, where, expression, base, time_suffix, nprocs=1, register_null=False, layer=1, vtype='point, line, boundary, centroid, area, face')[source]¶ Extract a subset of a space time raster, raster3d or vector dataset
A mapcalc expression can be provided to process the temporal extracted maps. Mapcalc expressions are supported for raster and raster3d maps.
Parameters: - input – The name of the input space time raster/raster3d dataset
- output – The name of the extracted new space time raster/raster3d dataset
- type – The type of the dataset: “raster”, “raster3d” or vector
- where – The temporal SQL WHERE statement for subset extraction
- expression – The r(3).mapcalc expression or the v.extract where statement
- base – The base name of the new created maps in case a mapclac expression is provided
- time_suffix – string to choose which suffix to use: gran, time, num%* (where * are digits)
- nprocs – The number of parallel processes to be used for mapcalc processing
- register_null – Set this number True to register empty maps (only raster and raster3d maps)
- layer – The vector layer number to be used when no timestamped layer is present, default is 1
- vtype – The feature type to be extracted for vector maps, default is point,line,boundary,centroid,area and face
temporal.factory module¶
Object factory
Usage:
import grass.temporal as tgis
tgis.register_maps_in_space_time_dataset(type, name, maps)
(C) 2012-2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
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temporal.factory.
dataset_factory
(type, id)[source]¶ A factory functions to create space time or map datasets
Parameters: - type – the dataset type: rast or raster; rast3d, raster3d or raster_3d; vect or vector; strds; str3ds; stvds
- id – The id of the dataset (“name@mapset”)
temporal.gui_support module¶
GUI support functions
(C) 2008-2011 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
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temporal.gui_support.
tlist
(type, dbif=None)[source]¶ Return a list of space time datasets of absolute and relative time
Parameters: type – element type (strds, str3ds, stvds) Returns: a list of space time dataset ids
-
temporal.gui_support.
tlist_grouped
(type, group_type=False, dbif=None)[source]¶ List of temporal elements grouped by mapsets.
Returns a dictionary where the keys are mapset names and the values are lists of space time datasets in that mapset. Example:
>>> import grass.temporalas tgis >>> tgis.tlist_grouped('strds')['PERMANENT'] ['precipitation', 'temperature']
Parameters: - type – element type (strds, str3ds, stvds)
- group_type – TBD
Returns: directory of mapsets/elements
temporal.list_stds module¶
Functions to create space time dataset lists
Usage:
import grass.temporal as tgis
tgis.register_maps_in_space_time_dataset(type, name, maps)
(C) 2012-2016 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS GIS for details.
authors: | Soeren Gebbert |
---|
-
temporal.list_stds.
get_dataset_list
(type, temporal_type, columns=None, where=None, order=None, dbif=None)[source]¶ Return a list of time stamped maps or space time datasets of a specific temporal type that are registered in the temporal database
This method returns a dictionary, the keys are the available mapsets, the values are the rows from the SQL database query.
Parameters: - type – The type of the datasets (strds, str3ds, stvds, raster, raster_3d, vector)
- temporal_type – The temporal type of the datasets (absolute, relative)
- columns – A comma separated list of columns that will be selected
- where – A where statement for selected listing without “WHERE”
- order – A comma separated list of columns to order the datasets by category
- dbif – The database interface to be used
Returns: A dictionary with the rows of the SQL query for each available mapset
>>> import grass.temporal as tgis >>> tgis.core.init() >>> name = "list_stds_test" >>> sp = tgis.open_stds.open_new_stds(name=name, type="strds", ... temporaltype="absolute", title="title", descr="descr", ... semantic="mean", dbif=None, overwrite=True) >>> mapset = tgis.get_current_mapset() >>> stds_list = tgis.list_stds.get_dataset_list("strds", "absolute", columns="name") >>> rows = stds_list[mapset] >>> for row in rows: ... if row["name"] == name: ... print(True) True >>> stds_list = tgis.list_stds.get_dataset_list("strds", "absolute", columns="name,mapset", where="mapset = '%s'"%(mapset)) >>> rows = stds_list[mapset] >>> for row in rows: ... if row["name"] == name and row["mapset"] == mapset: ... print(True) True >>> check = sp.delete()
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temporal.list_stds.
list_maps_of_stds
(type, input, columns, order, where, separator, method, no_header=False, gran=None, dbif=None, outpath=None)[source]¶ List the maps of a space time dataset using different methods
Parameters: - type – The type of the maps raster, raster3d or vector
- input – Name of a space time raster dataset
- columns – A comma separated list of columns to be printed to stdout
- order – A comma separated list of columns to order the maps by category
- where – A where statement for selected listing without “WHERE” e.g: start_time < “2001-01-01” and end_time > “2001-01-01”
- separator – The field separator character between the columns
- method – String identifier to select a method out of cols, comma,delta or deltagaps
- dbif –
The database interface to be used
- ”cols” Print preselected columns specified by columns
- ”comma” Print the map ids (“name@mapset”) as comma separated string
- ”delta” Print the map ids (“name@mapset”) with start time,
- end time, relative length of intervals and the relative distance to the begin
- ”deltagaps” Same as “delta” with additional listing of gaps.
- Gaps can be easily identified as the id is “None”
- ”gran” List map using the granularity of the space time dataset,
- columns are identical to deltagaps
- no_header – Suppress the printing of column names
- gran – The user defined granule to be used if method=gran is set, in case gran=None the granule of the space time dataset is used
- outpath – The path to file where to save output
temporal.mapcalc module¶
Raster and 3d raster mapcalculation functions
(C) 2012-2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
-
temporal.mapcalc.
dataset_mapcalculator
(inputs, output, type, expression, base, method, nprocs=1, register_null=False, spatial=False)[source]¶ Perform map-calculations of maps from different space time raster/raster3d datasets, using a specific sampling method to select temporal related maps.
A mapcalc expression must be provided to process the temporal selected maps. Temporal operators are available in addition to the r.mapcalc operators:
Supported operators for relative and absolute time are:
- td() - the time delta of the current interval in days
- and fractions of days or the unit in case of relative time
- start_time() - The start time of the interval from the begin of
- the time series in days and fractions of days or the unit in case of relative time
- end_time() - The end time of the current interval from the begin of
- the time series in days and fractions of days or the unit in case of relative time
Supported operators for absolute time:
- start_doy() - Day of year (doy) from the start time [1 - 366]
- start_dow() - Day of week (dow) from the start time [1 - 7],
- the start of the week is monday == 1
- start_year() - The year of the start time [0 - 9999]
- start_month() - The month of the start time [1 - 12]
- start_week() - Week of year of the start time [1 - 54]
- start_day() - Day of month from the start time [1 - 31]
- start_hour() - The hour of the start time [0 - 23]
- start_minute() - The minute of the start time [0 - 59]
- start_second() - The second of the start time [0 - 59]
- end_doy() - Day of year (doy) from the end time [1 - 366]
- end_dow() - Day of week (dow) from the end time [1 - 7],
- the start of the week is monday == 1
- end_year() - The year of the end time [0 - 9999]
- end_month() - The month of the end time [1 - 12]
- end_week() - Week of year of the end time [1 - 54]
- end_day() - Day of month from the end time [1 - 31]
- end_hour() - The hour of the end time [0 - 23]
- end_minute() - The minute of the end time [0 - 59]
- end_second() - The minute of the end time [0 - 59]
Parameters: - inputs – The names of the input space time raster/raster3d datasets
- output – The name of the extracted new space time raster(3d) dataset
- type – The type of the dataset: “raster” or “raster3d”
- expression – The r(3).mapcalc expression
- base – The base name of the new created maps in case a mapclac expression is provided
- method – The method to be used for temporal sampling
- nprocs – The number of parallel processes to be used for mapcalc processing
- register_null – Set this number True to register empty maps
- spatial – Check spatial overlap
temporal.metadata module¶
Metadata classes for map layer and space time datasets
Usage:
>>> import grass.temporal as tgis
>>> tgis.init()
>>> meta = tgis.RasterMetadata()
>>> meta = tgis.Raster3DMetadata()
>>> meta = tgis.VectorMetadata()
>>> meta = tgis.STRDSMetadata()
>>> meta = tgis.STR3DSMetadata()
>>> meta = tgis.STVDSMetadata()
(C) 2012-2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
-
class
temporal.metadata.
Raster3DMetadata
(ident=None, datatype=None, cols=None, rows=None, depths=None, number_of_cells=None, nsres=None, ewres=None, tbres=None, min=None, max=None)[source]¶ Bases:
temporal.metadata.RasterMetadataBase
This is the raster3d metadata class
This class is the interface to the raster3d_metadata table in the temporal database that stores the metadata of all registered 3D raster maps.
The metadata includes all raster metadata variables and additional the number of depths, the top-bottom resolution and the space time 3D raster dataset register table is stored.
Usage:
>>> init() >>> meta = Raster3DMetadata(ident="soil@PERMANENT", ... datatype="FCELL", cols=100, rows=100, depths=100, ... number_of_cells=1000000, nsres=0.1, ewres=0.1, tbres=0.1, ... min=0, max=100) >>> meta.datatype 'FCELL' >>> meta.cols 100 >>> meta.rows 100 >>> meta.depths 100 >>> meta.number_of_cells 1000000 >>> meta.nsres 0.1 >>> meta.ewres 0.1 >>> meta.tbres 0.1 >>> meta.min 0.0 >>> meta.max 100.0 >>> meta.print_info() +-------------------- Metadata information ----------------------------------+ | Datatype:................... FCELL | Number of columns:.......... 100 | Number of rows:............. 100 | Number of cells:............ 1000000 | North-South resolution:..... 0.1 | East-west resolution:....... 0.1 | Minimum value:.............. 0.0 | Maximum value:.............. 100.0 | Number of depths:........... 100 | Top-Bottom resolution:...... 0.1 >>> meta.print_shell_info() datatype=FCELL cols=100 rows=100 number_of_cells=1000000 nsres=0.1 ewres=0.1 min=0.0 max=100.0 depths=100 tbres=0.1
-
depths
¶ Get number of depths :return: None if not found
-
tbres
¶ Get top-bottom resolution :return: None if not found
-
-
class
temporal.metadata.
RasterMetadata
(ident=None, datatype=None, cols=None, rows=None, number_of_cells=None, nsres=None, ewres=None, min=None, max=None)[source]¶ Bases:
temporal.metadata.RasterMetadataBase
This is the raster metadata class
This class is the interface to the raster_metadata table in the temporal database that stores the metadata of all registered raster maps.
The metadata includes the datatype, number of cols, rows and cells and the north-south and east west resolution of the map. Additionally the minimum and maximum valuesare stored.
Usage:
>>> init() >>> meta = RasterMetadata(ident="soil@PERMANENT", ... datatype="CELL", cols=100, rows=100, number_of_cells=10000, nsres=0.1, ... ewres=0.1, min=0, max=100) >>> meta.datatype 'CELL' >>> meta.cols 100 >>> meta.rows 100 >>> meta.number_of_cells 10000 >>> meta.nsres 0.1 >>> meta.ewres 0.1 >>> meta.min 0.0 >>> meta.max 100.0 >>> meta.print_info() +-------------------- Metadata information ----------------------------------+ | Datatype:................... CELL | Number of columns:.......... 100 | Number of rows:............. 100 | Number of cells:............ 10000 | North-South resolution:..... 0.1 | East-west resolution:....... 0.1 | Minimum value:.............. 0.0 | Maximum value:.............. 100.0 >>> meta.print_shell_info() datatype=CELL cols=100 rows=100 number_of_cells=10000 nsres=0.1 ewres=0.1 min=0.0 max=100.0
-
class
temporal.metadata.
RasterMetadataBase
(table=None, ident=None, datatype=None, cols=None, rows=None, number_of_cells=None, nsres=None, ewres=None, min=None, max=None)[source]¶ Bases:
temporal.base.SQLDatabaseInterface
This is the metadata base class for time stamped raster and raster3d maps
Usage:
>>> init() >>> meta = RasterMetadataBase(table="metadata", ident="soil@PERMANENT", ... datatype="CELL", cols=100, rows=100, number_of_cells=10000, nsres=0.1, ... ewres=0.1, min=0, max=100) >>> meta.datatype 'CELL' >>> meta.cols 100 >>> meta.rows 100 >>> meta.number_of_cells 10000 >>> meta.nsres 0.1 >>> meta.ewres 0.1 >>> meta.min 0.0 >>> meta.max 100.0 >>> meta.print_info() | Datatype:................... CELL | Number of columns:.......... 100 | Number of rows:............. 100 | Number of cells:............ 10000 | North-South resolution:..... 0.1 | East-west resolution:....... 0.1 | Minimum value:.............. 0.0 | Maximum value:.............. 100.0 >>> meta.print_shell_info() datatype=CELL cols=100 rows=100 number_of_cells=10000 nsres=0.1 ewres=0.1 min=0.0 max=100.0
-
cols
¶ Get number of cols :return: None if not found
-
datatype
¶ Get the map type :return: None if not found
-
ewres
¶ Get east-west resolution :return: None if not found
-
get_id
()[source]¶ Convenient method to get the unique identifier (primary key) :return: None if not found
-
max
¶ Get the maximum cell value :return: None if not found
-
min
¶ Get the minimum cell value :return: None if not found
-
nsres
¶ Get the north-south resolution :return: None if not found
-
number_of_cells
¶ Get number of cells :return: None if not found
-
rows
¶ Get number of rows :return: None if not found
-
-
class
temporal.metadata.
STDSMetadataBase
(table=None, ident=None, title=None, description=None, command=None)[source]¶ Bases:
temporal.base.SQLDatabaseInterface
This is the space time dataset metadata base class for strds, stvds and str3ds datasets setting/getting the id, the title and the description
Usage:
>>> init() >>> meta = STDSMetadataBase(ident="soils@PERMANENT", ... title="Soils", description="Soils 1950 - 2010") >>> meta.id 'soils@PERMANENT' >>> meta.title 'Soils' >>> meta.description 'Soils 1950 - 2010' >>> meta.number_of_maps >>> meta.print_info() | Number of registered maps:.. None | | Title: | Soils | Description: | Soils 1950 - 2010 | Command history: >>> meta.print_shell_info() number_of_maps=None
-
description
¶ Get description :return: None if not found
-
get_id
()[source]¶ Convenient method to get the unique identifier (primary key) :return: None if not found
-
get_number_of_maps
()[source]¶ Get the number of registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
id
¶ Convenient method to get the unique identifier (primary key) :return: None if not found
-
number_of_maps
¶ Get the number of registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
title
¶ Get the title :return: None if not found
-
-
class
temporal.metadata.
STDSRasterMetadataBase
(table=None, ident=None, title=None, description=None, aggregation_type=None)[source]¶ Bases:
temporal.metadata.STDSMetadataBase
This is the space time dataset metadata base class for strds and str3ds datasets
Most of the metadata values are set by SQL scripts in the database when new maps are added. Therefor only some set- an many get-functions are available.
Usage:
>>> init() >>> meta = STDSRasterMetadataBase(ident="soils@PERMANENT", ... title="Soils", description="Soils 1950 - 2010") >>> meta.id 'soils@PERMANENT' >>> meta.title 'Soils' >>> meta.description 'Soils 1950 - 2010' >>> meta.number_of_maps >>> meta.min_max >>> meta.max_max >>> meta.min_min >>> meta.max_min >>> meta.nsres_min >>> meta.nsres_max >>> meta.ewres_min >>> meta.ewres_max >>> meta.print_info() | North-South resolution min:. None | North-South resolution max:. None | East-west resolution min:... None | East-west resolution max:... None | Minimum value min:.......... None | Minimum value max:.......... None | Maximum value min:.......... None | Maximum value max:.......... None | Aggregation type:........... None | Number of registered maps:.. None | | Title: | Soils | Description: | Soils 1950 - 2010 | Command history: >>> meta.print_shell_info() aggregation_type=None number_of_maps=None nsres_min=None nsres_max=None ewres_min=None ewres_max=None min_min=None min_max=None max_min=None max_max=None
-
aggregation_type
¶ Get the aggregation type of the dataset (mean, min, max, …) :return: None if not found
-
ewres_max
¶ Get the maximal east-west resolution of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
ewres_min
¶ Get the minimal east-west resolution of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
get_aggregation_type
()[source]¶ Get the aggregation type of the dataset (mean, min, max, …) :return: None if not found
-
get_ewres_max
()[source]¶ Get the maximal east-west resolution of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
get_ewres_min
()[source]¶ Get the minimal east-west resolution of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
get_max_max
()[source]¶ Get the maximal maximum of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
get_max_min
()[source]¶ Get the minimal maximum of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
get_min_max
()[source]¶ Get the maximal minimum of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
get_min_min
()[source]¶ Get the minimal minimum of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
get_nsres_max
()[source]¶ Get the maximal north-south resolution of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
get_nsres_min
()[source]¶ Get the minimal north-south resolution of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
max_max
¶ Get the maximal maximum of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
max_min
¶ Get the minimal maximum of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
min_max
¶ Get the maximal minimum of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
min_min
¶ Get the minimal minimum of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
nsres_max
¶ Get the maximal north-south resolution of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
nsres_min
¶ Get the minimal north-south resolution of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
-
class
temporal.metadata.
STR3DSMetadata
(ident=None, raster3d_register=None, title=None, description=None)[source]¶ Bases:
temporal.metadata.STDSRasterMetadataBase
This is the space time 3D raster metadata class
This class is the interface to the str3ds_metadata table in the temporal database that stores the metadata of all registered space time 3D raster datasets
Most of the metadata values are set by SQL scripts in the database when new 3D raster maps are added. Therefor only some set- an many get-functions are available.
Usage:
>>> init() >>> meta = STR3DSMetadata(ident="soils@PERMANENT", ... title="Soils", description="Soils 1950 - 2010") >>> meta.id 'soils@PERMANENT' >>> meta.title 'Soils' >>> meta.description 'Soils 1950 - 2010' >>> meta.number_of_maps >>> meta.min_max >>> meta.max_max >>> meta.min_min >>> meta.max_min >>> meta.nsres_min >>> meta.nsres_max >>> meta.ewres_min >>> meta.ewres_max >>> meta.tbres_min >>> meta.tbres_max >>> meta.raster3d_register >>> meta.print_info() +-------------------- Metadata information ----------------------------------+ | 3D raster register table:... None | Top-bottom resolution min:.. None | Top-bottom resolution max:.. None | North-South resolution min:. None | North-South resolution max:. None | East-west resolution min:... None | East-west resolution max:... None | Minimum value min:.......... None | Minimum value max:.......... None | Maximum value min:.......... None | Maximum value max:.......... None | Aggregation type:........... None | Number of registered maps:.. None | | Title: | Soils | Description: | Soils 1950 - 2010 | Command history: >>> meta.print_shell_info() aggregation_type=None number_of_maps=None nsres_min=None nsres_max=None ewres_min=None ewres_max=None min_min=None min_max=None max_min=None max_max=None tbres_min=None tbres_max=None raster3d_register=None
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get_raster3d_register
()[source]¶ Get the raster3d map register table name :return: None if not found
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get_tbres_max
()[source]¶ Get the maximal top-bottom resolution of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
get_tbres_min
()[source]¶ Get the minimal top-bottom resolution of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
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raster3d_register
¶ Get the raster3d map register table name :return: None if not found
-
tbres_max
¶ Get the maximal top-bottom resolution of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
tbres_min
¶ Get the minimal top-bottom resolution of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
-
class
temporal.metadata.
STRDSMetadata
(ident=None, raster_register=None, title=None, description=None)[source]¶ Bases:
temporal.metadata.STDSRasterMetadataBase
This is the raster metadata class
This class is the interface to the strds_metadata table in the temporal database that stores the metadata of all registered space time raster datasets
Most of the metadata values are set by SQL scripts in the database when new raster maps are added. Therefor only some set- an many get-functions are available.
Usage:
>>> init() >>> meta = STRDSMetadata(ident="soils@PERMANENT", ... title="Soils", description="Soils 1950 - 2010") >>> meta.id 'soils@PERMANENT' >>> meta.title 'Soils' >>> meta.description 'Soils 1950 - 2010' >>> meta.number_of_maps >>> meta.min_max >>> meta.max_max >>> meta.min_min >>> meta.max_min >>> meta.nsres_min >>> meta.nsres_max >>> meta.ewres_min >>> meta.ewres_max >>> meta.raster_register >>> meta.print_info() +-------------------- Metadata information ----------------------------------+ | Raster register table:...... None | North-South resolution min:. None | North-South resolution max:. None | East-west resolution min:... None | East-west resolution max:... None | Minimum value min:.......... None | Minimum value max:.......... None | Maximum value min:.......... None | Maximum value max:.......... None | Aggregation type:........... None | Number of registered maps:.. None | | Title: | Soils | Description: | Soils 1950 - 2010 | Command history: >>> meta.print_shell_info() aggregation_type=None number_of_maps=None nsres_min=None nsres_max=None ewres_min=None ewres_max=None min_min=None min_max=None max_min=None max_max=None raster_register=None
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raster_register
¶ Get the raster map register table name :return: None if not found
-
-
class
temporal.metadata.
STVDSMetadata
(ident=None, vector_register=None, title=None, description=None)[source]¶ Bases:
temporal.metadata.STDSMetadataBase
This is the space time vector dataset metadata class
This class is the interface to the stvds_metadata table in the temporal database that stores the metadata of all registered space time vector datasets
Most of the metadata values are set by SQL scripts in the database when new vector maps are added. Therefor only some set- an many get-functions are available.
Usage:
>>> init() >>> meta = STVDSMetadata(ident="lidars@PERMANENT", ... title="LIDARS", description="LIDARS 2008 - 2010") >>> meta.id 'lidars@PERMANENT' >>> meta.title 'LIDARS' >>> meta.description 'LIDARS 2008 - 2010' >>> meta.number_of_maps >>> meta.number_of_points >>> meta.number_of_lines >>> meta.number_of_boundaries >>> meta.number_of_centroids >>> meta.number_of_faces >>> meta.number_of_kernels >>> meta.number_of_primitives >>> meta.number_of_nodes >>> meta.number_of_areas >>> meta.number_of_islands >>> meta.number_of_holes >>> meta.number_of_volumes >>> meta.print_info() +-------------------- Metadata information ----------------------------------+ | Vector register table:...... None | Number of points ........... None | Number of lines ............ None | Number of boundaries ....... None | Number of centroids ........ None | Number of faces ............ None | Number of kernels .......... None | Number of primitives ....... None | Number of nodes ............ None | Number of areas ............ None | Number of islands .......... None | Number of holes ............ None | Number of volumes .......... None | Number of registered maps:.. None | | Title: | LIDARS | Description: | LIDARS 2008 - 2010 | Command history: >>> meta.print_shell_info() number_of_maps=None vector_register=None points=None lines=None boundaries=None centroids=None faces=None kernels=None primitives=None nodes=None areas=None islands=None holes=None volumes=None
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get_number_of_areas
()[source]¶ Get the number of areas of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
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get_number_of_boundaries
()[source]¶ Get the number of boundaries of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
get_number_of_centroids
()[source]¶ Get the number of centroids of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
get_number_of_faces
()[source]¶ Get the number of faces of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
get_number_of_holes
()[source]¶ Get the number of holes of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
get_number_of_islands
()[source]¶ Get the number of islands of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
get_number_of_kernels
()[source]¶ Get the number of kernels of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
get_number_of_lines
()[source]¶ Get the number of lines of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
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get_number_of_nodes
()[source]¶ Get the number of nodes of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
get_number_of_points
()[source]¶ Get the number of points of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
get_number_of_primitives
()[source]¶ Get the number of primitives of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
get_number_of_volumes
()[source]¶ Get the number of volumes of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
number_of_areas
¶ Get the number of areas of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
number_of_boundaries
¶ Get the number of boundaries of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
number_of_centroids
¶ Get the number of centroids of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
number_of_faces
¶ Get the number of faces of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
number_of_holes
¶ Get the number of holes of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
number_of_islands
¶ Get the number of islands of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
number_of_kernels
¶ Get the number of kernels of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
number_of_lines
¶ Get the number of lines of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
number_of_nodes
¶ Get the number of nodes of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
number_of_points
¶ Get the number of points of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
number_of_primitives
¶ Get the number of primitives of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
number_of_volumes
¶ Get the number of volumes of all registered maps, this value is set in the database automatically via SQL, so no setter exists :return: None if not found
-
vector_register
¶ Get the vector map register table name :return: None if not found
-
-
class
temporal.metadata.
VectorMetadata
(ident=None, is_3d=False, number_of_points=None, number_of_lines=None, number_of_boundaries=None, number_of_centroids=None, number_of_faces=None, number_of_kernels=None, number_of_primitives=None, number_of_nodes=None, number_of_areas=None, number_of_islands=None, number_of_holes=None, number_of_volumes=None)[source]¶ Bases:
temporal.base.SQLDatabaseInterface
This is the vector metadata class
This class is the interface to the vector_metadata table in the temporal database that stores the metadata of all registered vector maps.
Usage:
>>> init() >>> meta = VectorMetadata(ident="lidar@PERMANENT", is_3d=True, ... number_of_points=1, number_of_lines=2, number_of_boundaries=3, ... number_of_centroids=4, number_of_faces=5, number_of_kernels=6, ... number_of_primitives=7, number_of_nodes=8, number_of_areas=9, ... number_of_islands=10, number_of_holes=11, number_of_volumes=12) >>> meta.id 'lidar@PERMANENT' >>> meta.is_3d True >>> meta.number_of_points 1 >>> meta.number_of_lines 2 >>> meta.number_of_boundaries 3 >>> meta.number_of_centroids 4 >>> meta.number_of_faces 5 >>> meta.number_of_kernels 6 >>> meta.number_of_primitives 7 >>> meta.number_of_nodes 8 >>> meta.number_of_areas 9 >>> meta.number_of_islands 10 >>> meta.number_of_holes 11 >>> meta.number_of_volumes 12 >>> meta.print_info() +-------------------- Metadata information ----------------------------------+ | Is map 3d .................. True | Number of points ........... 1 | Number of lines ............ 2 | Number of boundaries ....... 3 | Number of centroids ........ 4 | Number of faces ............ 5 | Number of kernels .......... 6 | Number of primitives ....... 7 | Number of nodes ............ 8 | Number of areas ............ 9 | Number of islands .......... 10 | Number of holes ............ 11 | Number of volumes .......... 12 >>> meta.print_shell_info() is_3d=True points=1 lines=2 boundaries=3 centroids=4 faces=5 kernels=6 primitives=7 nodes=8 areas=9 islands=10 holes=11 volumes=12
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get_3d_info
()[source]¶ Return True if the map is three dimensional, False if not and None if not info was found
-
get_id
()[source]¶ Convenient method to get the unique identifier (primary key) :return: None if not found
-
get_number_of_boundaries
()[source]¶ Get the number of boundaries of the vector map :return: None if not found
-
get_number_of_centroids
()[source]¶ Get the number of centroids of the vector map :return: None if not found
-
get_number_of_islands
()[source]¶ Get the number of islands of the vector map :return: None if not found
-
get_number_of_kernels
()[source]¶ Get the number of kernels of the vector map :return: None if not found
-
get_number_of_points
()[source]¶ Get the number of points of the vector map :return: None if not found
-
get_number_of_primitives
()[source]¶ Get the number of primitives of the vector map :return: None if not found
-
get_number_of_volumes
()[source]¶ Get the number of volumes of the vector map :return: None if not found
-
id
¶ Convenient method to get the unique identifier (primary key) :return: None if not found
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is_3d
¶ Return True if the map is three dimensional, False if not and None if not info was found
-
number_of_areas
¶ Get the number of areas of the vector map :return: None if not found
-
number_of_boundaries
¶ Get the number of boundaries of the vector map :return: None if not found
-
number_of_centroids
¶ Get the number of centroids of the vector map :return: None if not found
-
number_of_faces
¶ Get the number of faces of the vector map :return: None if not found
-
number_of_holes
¶ Get the number of holes of the vector map :return: None if not found
-
number_of_islands
¶ Get the number of islands of the vector map :return: None if not found
-
number_of_kernels
¶ Get the number of kernels of the vector map :return: None if not found
-
number_of_lines
¶ Get the number of lines of the vector map :return: None if not found
-
number_of_nodes
¶ Get the number of nodes of the vector map :return: None if not found
-
number_of_points
¶ Get the number of points of the vector map :return: None if not found
-
number_of_primitives
¶ Get the number of primitives of the vector map :return: None if not found
-
number_of_volumes
¶ Get the number of volumes of the vector map :return: None if not found
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set_number_of_boundaries
(number_of_boundaries)[source]¶ Set the number of boundaries of the vector map
-
temporal.open_stds module¶
Functions to open or create space time datasets
Usage:
import grass.temporal as tgis
tgis.register_maps_in_space_time_dataset(type, name, maps)
(C) 2012-2014 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
-
temporal.open_stds.
check_new_map_dataset
(name, layer=None, type='raster', overwrite=False, dbif=None)[source]¶ - Check if a new map dataset of a specific type can be created in
- the temporal database
Parameters: - name – The name of the new map dataset
- layer – The layer of the new map dataset
- type – The type of the new map dataset (raster, vector, raster3d)
- dbif – The temporal database interface to be used
- overwrite – Flag to allow overwriting
Returns: A map dataset object
This function will raise a FatalError in case of an error.
-
temporal.open_stds.
check_new_stds
(name, type, dbif=None, overwrite=False)[source]¶ Check if a new space time dataset of a specific type can be created
Parameters: - name – The name of the new space time dataset
- type – The type of the new space time dataset (strd, str3ds, stvds, raster, vector, raster3d)
- dbif – The temporal database interface to be used
- overwrite – Flag to allow overwriting
Returns: A space time dataset object that must be filled with content before insertion in the temporal database
This function will raise a FatalError in case of an error.
-
temporal.open_stds.
open_new_map_dataset
(name, layer=None, type='raster', temporal_extent=None, overwrite=False, dbif=None)[source]¶ - Create a new map dataset object of a specific type that can be
- registered in the temporal database
Parameters: - name – The name of the new map dataset
- layer – The layer of the new map dataset
- type – The type of the new map dataset (raster, vector, raster3d)
- dbif – The temporal database interface to be used
- overwrite – Flag to allow overwriting
Returns: A map dataset object
-
temporal.open_stds.
open_new_stds
(name, type, temporaltype, title, descr, semantic, dbif=None, overwrite=False)[source]¶ Create a new space time dataset of a specific type
Parameters: - name – The name of the new space time dataset
- type – The type of the new space time dataset (strd, str3ds, stvds, raster, vector, raster3d)
- temporaltype – The temporal type (relative or absolute)
- title – The title
- descr – The dataset description
- semantic – Semantical information
- dbif – The temporal database interface to be used
- overwrite – Flag to allow overwriting
Returns: The new created space time dataset
This function will raise a FatalError in case of an error.
-
temporal.open_stds.
open_old_stds
(name, type, dbif=None)[source]¶ This function opens an existing space time dataset and return the created and initialized object of the specified type.
This function will call exit() or raise a grass.pygrass.messages.FatalError in case the type is wrong, or the space time dataset was not found.
Parameters: - name – The name of the space time dataset, if the name does not contain the mapset (name@mapset) then the current mapset will be used to identifiy the space time dataset
- type – The type of the space time dataset (strd, str3ds, stvds, raster, vector, raster3d)
- dbif – The optional database interface to be used
Returns: New stds object
temporal.register module¶
Functions to register map layer in space time datasets and the temporal database
Usage:
import grass.temporal as tgis
tgis.register_maps_in_space_time_dataset(type, name, maps)
(C) 2012-2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
-
temporal.register.
assign_valid_time_to_map
(ttype, map, start, end, unit, increment=None, mult=1, interval=False)[source]¶ Assign the valid time to a map dataset
Parameters: - ttype – The temporal type which should be assigned and which the time format is of
- map – A map dataset object derived from abstract_map_dataset
- start – The start date and time of the first map (format absolute: “yyyy-mm-dd HH:MM:SS” or “yyyy-mm-dd”, format relative is integer 5)
- end – The end date and time of the first map (format absolute: “yyyy-mm-dd HH:MM:SS” or “yyyy-mm-dd”, format relative is integer 5)
- unit – The unit of the relative time: years, months, days, hours, minutes, seconds
- increment – Time increment between maps for time stamp creation (format absolute: NNN seconds, minutes, hours, days, weeks, months, years; format relative is integer 1)
- mult – A multiplier for the increment
- interval – If True, time intervals are created in case the start time and an increment is provided
-
temporal.register.
register_map_object_list
(type, map_list, output_stds, delete_empty=False, unit=None, dbif=None)[source]¶ Register a list of AbstractMapDataset objects in the temporal database and optional in a space time dataset.
Parameters: - type – The type of the map layer (raster, raster_3d, vector)
- map_list – List of AbstractMapDataset objects
- output_stds – The output stds
- delete_empty – Set True to delete empty map layer found in the map_list
- unit – The temporal unit of the space time dataset
- dbif – The database interface to be used
-
temporal.register.
register_maps_in_space_time_dataset
(type, name, maps=None, file=None, start=None, end=None, unit=None, increment=None, dbif=None, interval=False, fs='|', update_cmd_list=True)[source]¶ Use this method to register maps in space time datasets.
Additionally a start time string and an increment string can be specified to assign a time interval automatically to the maps.
It takes care of the correct update of the space time datasets from all registered maps.
Parameters: - type – The type of the maps raster, raster_3d or vector
- name – The name of the space time dataset. Maps will be registered in the temporal database if the name was set to None
- maps – A comma separated list of map names
- file – Input file, one map per line map with start and optional end time
- start – The start date and time of the first map (format absolute: “yyyy-mm-dd HH:MM:SS” or “yyyy-mm-dd”, format relative is integer 5)
- end – The end date and time of the first map (format absolute: “yyyy-mm-dd HH:MM:SS” or “yyyy-mm-dd”, format relative is integer 5)
- unit – The unit of the relative time: years, months, days, hours, minutes, seconds
- increment – Time increment between maps for time stamp creation (format absolute: NNN seconds, minutes, hours, days, weeks, months, years; format relative: 1.0)
- dbif – The database interface to be used
- interval – If True, time intervals are created in case the start time and an increment is provided
- fs – Field separator used in input file
- update_cmd_list – If is True, the command that was invoking this process will be written to the process history
temporal.sampling module¶
Sampling functions for space time datasets
Usage:
import grass.temporal as tgis
tgis.register_maps_in_space_time_dataset(type, name, maps)
(C) 2012-2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
-
temporal.sampling.
sample_stds_by_stds_topology
(intype, sampletype, inputs, sampler, header, separator, method, spatial=False, print_only=True)[source]¶ Sample the input space time datasets with a sample space time dataset, return the created map matrix and optionally print the result to stdout
In case multiple maps are located in the current granule, the map names are separated by comma.
In case a layer is present, the names map ids are extended in this form: “name:layer@mapset”
Attention: Do not use the comma as separator for printing
param intype: Type of the input space time dataset (strds, stvds or str3ds) param sampletype: Type of the sample space time datasets (strds, stvds or str3ds) param inputs: Name or comma separated names of space time datasets or a list of map names param sampler: Name of a space time dataset used for temporal sampling param header: Set True to print column names param separator: The field separator character between the columns param method: The method to be used for temporal sampling (start,during,contain,overlap,equal) as comma separated string or as a list of methods param spatial: Perform spatial overlapping check param print_only: If set True (default) then the result of the sampling will be printed to stdout, if set to False the resulting map matrix will be returned. return: The map matrix or None if nothing found
temporal.space_time_datasets module¶
Map layer and space time dataset classes
(C) 2012-2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
-
class
temporal.space_time_datasets.
Raster3DDataset
(ident)[source]¶ Bases:
temporal.abstract_map_dataset.AbstractMapDataset
Raster3d dataset class
This class provides functions to select, update, insert or delete raster3d map information and valid time stamps into the SQL temporal database.
Usage:
>>> import grass.script as grass >>> init() >>> grass.use_temp_region() >>> grass.run_command("g.region", n=80.0, s=0.0, e=120.0, w=0.0, ... t=100.0, b=0.0, res=10.0, res3=10.0) 0 >>> grass.run_command("r3.mapcalc", overwrite=True, quiet=True, ... expression="str3ds_map_test_case = 1") 0 >>> grass.run_command("r3.timestamp", map="str3ds_map_test_case", ... date="15 jan 1999", quiet=True) 0 >>> mapset = get_current_mapset() >>> name = "str3ds_map_test_case" >>> identifier = "%s@%s" % (name, mapset) >>> r3map = Raster3DDataset(identifier) >>> r3map.map_exists() True >>> r3map.read_timestamp_from_grass() True >>> r3map.get_temporal_extent_as_tuple() (datetime.datetime(1999, 1, 15, 0, 0), None) >>> r3map.load() True >>> r3map.spatial_extent.print_info() +-------------------- Spatial extent ----------------------------------------+ | North:...................... 80.0 | South:...................... 0.0 | East:.. .................... 120.0 | West:....................... 0.0 | Top:........................ 100.0 | Bottom:..................... 0.0 >>> r3map.absolute_time.print_info() +-------------------- Absolute time -----------------------------------------+ | Start time:................. 1999-01-15 00:00:00 | End time:................... None >>> r3map.metadata.print_info() +-------------------- Metadata information ----------------------------------+ | Datatype:................... DCELL | Number of columns:.......... 8 | Number of rows:............. 12 | Number of cells:............ 960 | North-South resolution:..... 10.0 | East-west resolution:....... 10.0 | Minimum value:.............. 1.0 | Maximum value:.............. 1.0 | Number of depths:........... 10 | Top-Bottom resolution:...... 10.0 >>> grass.run_command("r3.timestamp", map="str3ds_map_test_case", ... date="2 years", quiet=True) 0 >>> r3map.read_timestamp_from_grass() True >>> r3map.get_temporal_extent_as_tuple() (2, None) >>> r3map.get_relative_time_unit() 'years' >>> r3map.is_in_db() False >>> r3map.is_stds() False >>> newmap = r3map.get_new_instance("new@PERMANENT") >>> isinstance(newmap, Raster3DDataset) True >>> newstr3ds = r3map.get_new_stds_instance("new@PERMANENT") >>> isinstance(newstr3ds, SpaceTimeRaster3DDataset) True >>> r3map.get_type() 'raster3d' >>> r3map.set_absolute_time(start_time=datetime(2001,1,1), ... end_time=datetime(2012,1,1)) True >>> r3map.get_absolute_time() (datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2012, 1, 1, 0, 0)) >>> r3map.get_temporal_extent_as_tuple() (datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2012, 1, 1, 0, 0)) >>> r3map.get_name() 'str3ds_map_test_case' >>> r3map.get_mapset() == mapset True >>> r3map.get_temporal_type() 'absolute' >>> r3map.get_spatial_extent_as_tuple() (80.0, 0.0, 120.0, 0.0, 100.0, 0.0) >>> r3map.is_time_absolute() True >>> r3map.is_time_relative() False >>> grass.run_command("g.remove", flags="f", type="raster_3d", name=name, quiet=True) 0 >>> grass.del_temp_region()
-
get_new_stds_instance
(ident)[source]¶ Return a new space time dataset instance in which maps are stored with the type of this class
-
get_np_array
()[source]¶ Return this 3D raster map as memmap numpy style array to access the 3D raster values in numpy style without loading the whole map in the RAM.
In case this 3D raster map does exists in the grass spatial database, the map will be exported using r3.out.bin to a temporary location and assigned to the memmap object that is returned by this function.
In case the 3D raster map does not exist, an empty temporary binary file will be created and assigned to the memap object.
You need to call the write function to write the memmap array back into grass.
-
get_type
()[source]¶ Return the type of this class as string
The type can be “vector”, “raster”, “raster3d”, “stvds”, “strds” or “str3ds”
Returns: “vector”, “raster”, “raster3d”, “stvds”, “strds” or “str3ds”
-
has_grass_timestamp
()[source]¶ Check if a grass file bsased time stamp exists for this map.
Returns: True if success, False on error
-
is_stds
()[source]¶ Return True if this class is a space time dataset
Returns: True if this class is a space time dataset, False otherwise
-
load
()[source]¶ Load all info from an existing 3d raster map into the internal structure
This method checks first if the map exists, in case it exists the metadata of the map is put into this object and True is returned
Returns: True is the map exists and the metadata was filled successfully and getting the data was successful, False otherwise
-
map_exists
()[source]¶ Return True in case the map exists in the grass spatial database
Returns: True if map exists, False otherwise
-
read_timestamp_from_grass
()[source]¶ Read the timestamp of this map from the map metadata in the grass file system based spatial database and set the internal time stamp that should be insert/updated in the temporal database.
Returns: True if success, False on error
-
remove_timestamp_from_grass
()[source]¶ Remove the timestamp from the grass file system based spatial database
Returns: True if success, False on error
-
spatial_disjoint_union
(dataset)[source]¶ Return the three or two dimensional union as spatial_extent object.
Parameters: dataset – The abstract dataset to create a union with Returns: The union spatial extent
-
spatial_intersection
(dataset)[source]¶ Return the three or two dimensional intersection as spatial_extent object or None in case no intersection was found.
Parameters: dataset – The abstract dataset to intersect with Returns: The intersection spatial extent or None
-
-
class
temporal.space_time_datasets.
RasterDataset
(ident)[source]¶ Bases:
temporal.abstract_map_dataset.AbstractMapDataset
Raster dataset class
This class provides functions to select, update, insert or delete raster map information and valid time stamps into the SQL temporal database.
Usage:
>>> import grass.script as grass >>> import grass.temporal as tgis >>> init() >>> grass.use_temp_region() >>> grass.run_command("g.region", n=80.0, s=0.0, e=120.0, w=0.0, ... t=1.0, b=0.0, res=10.0) 0 >>> grass.run_command("r.mapcalc", overwrite=True, quiet=True, ... expression="strds_map_test_case = 1") 0 >>> grass.run_command("r.timestamp", map="strds_map_test_case", ... date="15 jan 1999", quiet=True) 0 >>> mapset = tgis.get_current_mapset() >>> name = "strds_map_test_case" >>> identifier = "%s@%s" % (name, mapset) >>> rmap = RasterDataset(identifier) >>> rmap.map_exists() True >>> rmap.read_timestamp_from_grass() True >>> rmap.get_temporal_extent_as_tuple() (datetime.datetime(1999, 1, 15, 0, 0), None) >>> rmap.load() True >>> rmap.spatial_extent.print_info() +-------------------- Spatial extent ----------------------------------------+ | North:...................... 80.0 | South:...................... 0.0 | East:.. .................... 120.0 | West:....................... 0.0 | Top:........................ 0.0 | Bottom:..................... 0.0 >>> rmap.absolute_time.print_info() +-------------------- Absolute time -----------------------------------------+ | Start time:................. 1999-01-15 00:00:00 | End time:................... None >>> rmap.metadata.print_info() +-------------------- Metadata information ----------------------------------+ | Datatype:................... CELL | Number of columns:.......... 8 | Number of rows:............. 12 | Number of cells:............ 96 | North-South resolution:..... 10.0 | East-west resolution:....... 10.0 | Minimum value:.............. 1.0 | Maximum value:.............. 1.0 >>> grass.run_command("r.timestamp", map="strds_map_test_case", ... date="2 years", quiet=True) 0 >>> rmap.read_timestamp_from_grass() True >>> rmap.get_temporal_extent_as_tuple() (2, None) >>> rmap.get_relative_time_unit() 'years' >>> rmap.is_in_db() False >>> rmap.is_stds() False >>> newmap = rmap.get_new_instance("new@PERMANENT") >>> isinstance(newmap, RasterDataset) True >>> newstrds = rmap.get_new_stds_instance("new@PERMANENT") >>> isinstance(newstrds, SpaceTimeRasterDataset) True >>> rmap.get_type() 'raster' >>> rmap.set_absolute_time(start_time=datetime(2001,1,1), ... end_time=datetime(2012,1,1)) True >>> rmap.get_absolute_time() (datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2012, 1, 1, 0, 0)) >>> rmap.get_temporal_extent_as_tuple() (datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2012, 1, 1, 0, 0)) >>> rmap.get_name() 'strds_map_test_case' >>> rmap.get_mapset() == mapset True >>> rmap.get_temporal_type() 'absolute' >>> rmap.get_spatial_extent_as_tuple() (80.0, 0.0, 120.0, 0.0, 0.0, 0.0) >>> rmap.is_time_absolute() True >>> rmap.is_time_relative() False >>> grass.run_command("g.remove", flags="f", type="raster", name=name, quiet=True) 0 >>> grass.del_temp_region()
-
get_new_stds_instance
(ident)[source]¶ Return a new space time dataset instance in which maps are stored with the type of this class
-
get_np_array
()[source]¶ Return this raster map as memmap numpy style array to access the raster values in numpy style without loading the whole map in the RAM.
In case this raster map does exists in the grass spatial database, the map will be exported using r.out.bin to a temporary location and assigned to the memmap object that is returned by this function.
In case the raster map does not exist, an empty temporary binary file will be created and assigned to the memap object.
You need to call the write function to write the memmap array back into grass.
-
get_type
()[source]¶ Return the type of this class as string
The type can be “vector”, “raster”, “raster3d”, “stvds”, “strds” or “str3ds”
Returns: “vector”, “raster”, “raster3d”, “stvds”, “strds” or “str3ds”
-
has_grass_timestamp
()[source]¶ Check if a grass file based time stamp exists for this map.
Returns: True if success, False on error
-
is_stds
()[source]¶ Return True if this class is a space time dataset
Returns: True if this class is a space time dataset, False otherwise
-
load
()[source]¶ Load all info from an existing raster map into the internal structure
This method checks first if the map exists, in case it exists the metadata of the map is put into this object and True is returned
Returns: True is the map exists and the metadata was filled successfully and getting the data was successful, False otherwise
-
map_exists
()[source]¶ Return True in case the map exists in the grass spatial database
Returns: True if map exists, False otherwise
-
read_timestamp_from_grass
()[source]¶ Read the timestamp of this map from the map metadata in the grass file system based spatial database and set the internal time stamp that should be insert/updated in the temporal database.
Returns: True if success, False on error
-
remove_timestamp_from_grass
()[source]¶ Remove the timestamp from the grass file system based spatial database
Internally the libgis API functions are used for removal
Returns: True if success, False on error
-
spatial_disjoint_union
(dataset)[source]¶ Return the two dimensional union as spatial_extent object.
Parameters: dataset – The abstract dataset to create a union with Returns: The union spatial extent
-
spatial_intersection
(dataset)[source]¶ Return the two dimensional intersection as spatial_extent object or None in case no intersection was found.
Parameters: dataset – The abstract dataset to intersect with Returns: The intersection spatial extent or None
-
-
class
temporal.space_time_datasets.
SpaceTimeRaster3DDataset
(ident)[source]¶ Bases:
temporal.abstract_space_time_dataset.AbstractSpaceTimeDataset
Space time raster3d dataset class
>>> import grass.temporal as tgis >>> tgis.init() >>> mapset = tgis.get_current_mapset() >>> str3ds = tgis.SpaceTimeRaster3DDataset("old@%s"%mapset) >>> str3ds.is_in_db() False >>> str3ds.is_stds() True >>> str3ds.get_type() 'str3ds' >>> newstrds = str3ds.get_new_instance("newstrds@%s"%mapset) >>> isinstance(newstrds, SpaceTimeRaster3DDataset) True >>> newmap = str3ds.get_new_map_instance("newmap@%s"%mapset) >>> isinstance(newmap, Raster3DDataset) True >>> str3ds.reset("new@%s"%mapset) >>> str3ds.is_in_db() False >>> str3ds.reset(None) >>> str3ds.is_in_db() False >>> str3ds.get_id()
…
-
get_new_map_instance
(ident)[source]¶ Return a new instance of a map dataset which is associated with the type of this class
-
get_type
()[source]¶ Return the type of this class as string
The type can be “vector”, “raster”, “raster3d”, “stvds”, “strds” or “str3ds”
Returns: “vector”, “raster”, “raster3d”, “stvds”, “strds” or “str3ds”
-
is_stds
()[source]¶ Return True if this class is a space time dataset
Returns: True if this class is a space time dataset, False otherwise
-
spatial_disjoint_union
(dataset)[source]¶ Return the three or two dimensional union as spatial_extent object.
Parameters: dataset – The abstract dataset to create a union with Returns: The union spatial extent
-
-
class
temporal.space_time_datasets.
SpaceTimeRasterDataset
(ident)[source]¶ Bases:
temporal.abstract_space_time_dataset.AbstractSpaceTimeDataset
Space time raster dataset class
>>> import grass.temporal as tgis >>> tgis.init() >>> mapset = tgis.get_current_mapset() >>> strds = tgis.SpaceTimeRasterDataset("old@%s"%mapset) >>> strds.is_in_db() False >>> strds.is_stds() True >>> strds.get_type() 'strds' >>> newstrds = strds.get_new_instance("newstrds@%s"%mapset) >>> isinstance(newstrds, SpaceTimeRasterDataset) True >>> newmap = strds.get_new_map_instance("newmap@%s"%mapset) >>> isinstance(newmap, RasterDataset) True >>> strds.reset("new@%s"%mapset) >>> strds.is_in_db() False >>> strds.reset(None) >>> strds.is_in_db() False >>> strds.get_id()
…
-
get_new_map_instance
(ident)[source]¶ Return a new instance of a map dataset which is associated ” “with the type of this class
-
get_type
()[source]¶ Return the type of this class as string
The type can be “vector”, “raster”, “raster3d”, “stvds”, “strds” or “str3ds”
Returns: “vector”, “raster”, “raster3d”, “stvds”, “strds” or “str3ds”
-
is_stds
()[source]¶ Return True if this class is a space time dataset
Returns: True if this class is a space time dataset, False otherwise
-
spatial_disjoint_union
(dataset)[source]¶ Return the two dimensional union as spatial_extent object.
Parameters: dataset – The abstract dataset to create a union with Returns: The union spatial extent
-
-
class
temporal.space_time_datasets.
SpaceTimeVectorDataset
(ident)[source]¶ Bases:
temporal.abstract_space_time_dataset.AbstractSpaceTimeDataset
Space time vector dataset class
>>> import grass.temporal as tgis >>> tgis.init() >>> mapset = tgis.get_current_mapset() >>> stvds = tgis.SpaceTimeVectorDataset("old@%s"%mapset) >>> stvds.is_in_db() False >>> stvds.is_stds() True >>> stvds.get_type() 'stvds' >>> newstvds = stvds.get_new_instance("newstvds@%s"%mapset) >>> isinstance(newstvds, SpaceTimeVectorDataset) True >>> newmap = stvds.get_new_map_instance("newmap@%s"%mapset) >>> isinstance(newmap, VectorDataset) True >>> stvds.reset("new@%s"%mapset) >>> stvds.is_in_db() False >>> stvds.reset(None) >>> stvds.is_in_db() False >>> stvds.get_id()
…
-
get_new_map_instance
(ident)[source]¶ Return a new instance of a map dataset which is associated with the type of this class
-
get_type
()[source]¶ Return the type of this class as string
The type can be “vector”, “raster”, “raster3d”, “stvds”, “strds” or “str3ds”
Returns: “vector”, “raster”, “raster3d”, “stvds”, “strds” or “str3ds”
-
is_stds
()[source]¶ Return True if this class is a space time dataset
Returns: True if this class is a space time dataset, False otherwise
-
spatial_disjoint_union
(dataset)[source]¶ Return the two dimensional union as spatial_extent object.
Parameters: dataset – The abstract dataset to create a union with Returns: The union spatial extent
-
-
class
temporal.space_time_datasets.
VectorDataset
(ident)[source]¶ Bases:
temporal.abstract_map_dataset.AbstractMapDataset
Vector dataset class
This class provides functions to select, update, insert or delete vector map information and valid time stamps into the SQL temporal database.
Usage:
>>> import grass.script as grass >>> init() >>> grass.use_temp_region() >>> grass.run_command("g.region", n=80.0, s=0.0, e=120.0, w=0.0, ... t=1.0, b=0.0, res=10.0) 0 >>> grass.run_command("v.random", overwrite=True, output="stvds_map_test_case", ... n=100, zmin=0, zmax=100, flags="z", column="elevation", quiet=True) 0 >>> grass.run_command("v.timestamp", map="stvds_map_test_case", ... date="15 jan 1999", quiet=True) 0 >>> mapset = get_current_mapset() >>> name = "stvds_map_test_case" >>> identifier = "%s@%s" % (name, mapset) >>> vmap = VectorDataset(identifier) >>> vmap.map_exists() True >>> vmap.read_timestamp_from_grass() True >>> vmap.get_temporal_extent_as_tuple() (datetime.datetime(1999, 1, 15, 0, 0), None) >>> vmap.load() True >>> vmap.absolute_time.print_info() +-------------------- Absolute time -----------------------------------------+ | Start time:................. 1999-01-15 00:00:00 | End time:................... None >>> vmap.metadata.print_info() +-------------------- Metadata information ----------------------------------+ | Is map 3d .................. True | Number of points ........... 100 | Number of lines ............ 0 | Number of boundaries ....... 0 | Number of centroids ........ 0 | Number of faces ............ 0 | Number of kernels .......... 0 | Number of primitives ....... 100 | Number of nodes ............ 0 | Number of areas ............ 0 | Number of islands .......... 0 | Number of holes ............ 0 | Number of volumes .......... 0 >>> grass.run_command("v.timestamp", map="stvds_map_test_case", ... date="2 years", quiet=True) 0 >>> vmap.read_timestamp_from_grass() True >>> vmap.get_temporal_extent_as_tuple() (2, None) >>> vmap.get_relative_time_unit() 'years' >>> vmap.is_in_db() False >>> vmap.is_stds() False >>> newmap = vmap.get_new_instance("new@PERMANENT") >>> isinstance(newmap, VectorDataset) True >>> newstvds = vmap.get_new_stds_instance("new@PERMANENT") >>> isinstance(newstvds, SpaceTimeVectorDataset) True >>> vmap.get_type() 'vector' >>> vmap.set_absolute_time(start_time=datetime(2001,1,1), ... end_time=datetime(2012,1,1)) True >>> vmap.get_absolute_time() (datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2012, 1, 1, 0, 0)) >>> vmap.get_temporal_extent_as_tuple() (datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2012, 1, 1, 0, 0)) >>> vmap.get_name() 'stvds_map_test_case' >>> vmap.get_mapset() == mapset True >>> vmap.get_temporal_type() 'absolute' >>> vmap.is_time_absolute() True >>> vmap.is_time_relative() False >>> grass.run_command("g.remove", flags="f", type="vector", name=name, quiet=True) 0 >>> grass.del_temp_region()
-
get_new_stds_instance
(ident)[source]¶ Return a new space time dataset instance in which maps are stored with the type of this class
-
get_type
()[source]¶ Return the type of this class as string
The type can be “vector”, “raster”, “raster3d”, “stvds”, “strds” or “str3ds”
Returns: “vector”, “raster”, “raster3d”, “stvds”, “strds” or “str3ds”
-
is_stds
()[source]¶ Return True if this class is a space time dataset
Returns: True if this class is a space time dataset, False otherwise
-
load
()[source]¶ Load all info from an existing vector map into the internal structure
This method checks first if the map exists, in case it exists the metadata of the map is put into this object and True is returned
Returns: True is the map exists and the metadata was filled successfully and getting the data was successful, False otherwise
-
map_exists
()[source]¶ Return True in case the map exists in the grass spatial database
Returns: True if map exists, False otherwise
-
read_timestamp_from_grass
()[source]¶ Read the timestamp of this map from the map metadata in the grass file system based spatial database and set the internal time stamp that should be insert/updated in the temporal database.
-
remove_timestamp_from_grass
()[source]¶ Remove the timestamp from the grass file system based spatial database
Internally the libgis API functions are used for removal
-
spatial_disjoint_union
(dataset)[source]¶ Return the two dimensional union as spatial_extent object.
Parameters: dataset – The abstract dataset to create a union with Returns: The union spatial extent
-
spatial_intersection
(dataset)[source]¶ Return the two dimensional intersection as spatial_extent object or None in case no intersection was found.
Parameters: dataset – The abstract dataset to intersect with Returns: The intersection spatial extent or None
-
temporal.spatial_extent module¶
Spatial extents classes for map layer and space time datasets
Usage:
>>> import grass.temporal as tgis
>>> tgis.init()
>>> extent = tgis.RasterSpatialExtent(
... ident="raster@PERMANENT", north=90, south=90, east=180, west=180,
... top=100, bottom=-20)
>>> extent = tgis.Raster3DSpatialExtent(
... ident="raster3d@PERMANENT", north=90, south=90, east=180, west=180,
... top=100, bottom=-20)
>>> extent = tgis.VectorSpatialExtent(
... ident="vector@PERMANENT", north=90, south=90, east=180, west=180,
... top=100, bottom=-20)
>>> extent = tgis.STRDSSpatialExtent(
... ident="strds@PERMANENT", north=90, south=90, east=180, west=180,
... top=100, bottom=-20)
>>> extent = tgis.STR3DSSpatialExtent(
... ident="str3ds@PERMANENT", north=90, south=90, east=180, west=180,
... top=100, bottom=-20)
>>> extent = tgis.STVDSSpatialExtent(
... ident="stvds@PERMANENT", north=90, south=90, east=180, west=180,
... top=100, bottom=-20)
(C) 2012-2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
-
class
temporal.spatial_extent.
Raster3DSpatialExtent
(ident=None, north=None, south=None, east=None, west=None, top=None, bottom=None)[source]¶
-
class
temporal.spatial_extent.
RasterSpatialExtent
(ident=None, north=None, south=None, east=None, west=None, top=None, bottom=None)[source]¶
-
class
temporal.spatial_extent.
STR3DSSpatialExtent
(ident=None, north=None, south=None, east=None, west=None, top=None, bottom=None)[source]¶
-
class
temporal.spatial_extent.
STRDSSpatialExtent
(ident=None, north=None, south=None, east=None, west=None, top=None, bottom=None)[source]¶
-
class
temporal.spatial_extent.
STVDSSpatialExtent
(ident=None, north=None, south=None, east=None, west=None, top=None, bottom=None)[source]¶
-
class
temporal.spatial_extent.
SpatialExtent
(table=None, ident=None, north=None, south=None, east=None, west=None, top=None, bottom=None, proj='XY')[source]¶ Bases:
temporal.base.SQLDatabaseInterface
This is the spatial extent base class for all maps and space time datasets
This class implements a three dimensional axis aligned bounding box and functions to compute topological relationships
Usage:
>>> init() >>> extent = SpatialExtent(table="raster_spatial_extent", ... ident="soil@PERMANENT", north=90, south=90, east=180, west=180, ... top=100, bottom=-20) >>> extent.id 'soil@PERMANENT' >>> extent.north 90.0 >>> extent.south 90.0 >>> extent.east 180.0 >>> extent.west 180.0 >>> extent.top 100.0 >>> extent.bottom -20.0 >>> extent.print_info() +-------------------- Spatial extent ----------------------------------------+ | North:...................... 90.0 | South:...................... 90.0 | East:.. .................... 180.0 | West:....................... 180.0 | Top:........................ 100.0 | Bottom:..................... -20.0 >>> extent.print_shell_info() north=90.0 south=90.0 east=180.0 west=180.0 top=100.0 bottom=-20.0
-
bottom
¶ Get the bottom edge of the map :return: None if not found
-
contain
(extent)[source]¶ Return True if this extent (A) contains the provided spatial extent (B) in three dimensions.
Usage:
>>> A = SpatialExtent(north=80, south=20, east=60, west=10, ... bottom=-50, top=50) >>> B = SpatialExtent(north=79, south=21, east=59, west=11, ... bottom=-49, top=49) >>> A.contain(B) True >>> B.contain(A) False
Parameters: extent – The spatial extent Returns: True or False
-
contain_2d
(extent)[source]¶ Return True if this extent (A) contains the provided spatial extent (B) in two dimensions.
Usage:
>>> A = SpatialExtent(north=80, south=20, east=60, west=10) >>> B = SpatialExtent(north=79, south=21, east=59, west=11) >>> A.contain_2d(B) True >>> B.contain_2d(A) False
Parameters: extent – The spatial extent Returns: True or False
-
cover
(extent)[source]¶ Return True if this extent covers the provided spatial extent in three dimensions.
The following cases are excluded:
- contain
- in
- equivalent
Parameters: extent – The spatial extent Returns: True or False
-
cover_2d
(extent)[source]¶ Return True if this extent (A) covers the provided spatial extent (B) in two dimensions.
_____ _____ _____ _____ |A __| |__ A| |A | B| |B | A| | |B | | B| | | |__| |__| | |__|__| |__|__| |_____| |_____| _____ _____ _____ _____ |A|B| | |A __| |A _ | |__ A| | |_| | | |__|B | |B| | B|__| | |_____| |_____| |_|_|_| |_____| _____ _____ _____ _____ |A|B | |_____|A |A|B|A| |_____|A | | | |B | | | | | |_____|B |_|___| |_____| |_|_|_| |_____|A
The following cases are excluded:
- contain
- in
- equivalent
Parameters: extent – The spatial extent Returns: True or False
-
covered
(extent)[source]¶ Return True if this extent is covered by the provided spatial extent in three dimensions.
The following cases are excluded:
- contain
- in
- equivalent
Parameters: extent – The spatial extent Returns: True or False
-
covered_2d
(extent)[source]¶ Return True if this extent is covered by the provided spatial extent in two dimensions.
The following cases are excluded:
- contain
- in
- equivalent
Parameters: extent – The spatial extent Returns: True or False
-
disjoint
(extent)[source]¶ Return True if this extent is disjoint with the provided spatial extent in three dimensions.
Parameters: extent – The spatial extent Returns: True or False
-
disjoint_2d
(extent)[source]¶ Return True if this extent (A) is disjoint with the provided spatial extent (B) in three dimensions.
_____ | A | |_____| _______ | B | |_______|
Parameters: extent – The spatial extent Returns: True or False
-
disjoint_union
(extent)[source]¶ Return the three dimensional union as spatial_extent .
Usage:
>>> A = SpatialExtent(north=80, south=20, east=60, west=10, ... bottom=-50, top=50) >>> B = SpatialExtent(north=80, south=20, east=60, west=10, ... bottom=-50, top=50) >>> C = A.disjoint_union(B) >>> C.print_info() +-------------------- Spatial extent ----------------------------------------+ | North:...................... 80.0 | South:...................... 20.0 | East:.. .................... 60.0 | West:....................... 10.0 | Top:........................ 50.0 | Bottom:..................... -50.0 >>> B = SpatialExtent(north=40, south=30, east=60, west=10, ... bottom=-50, top=50) >>> C = A.disjoint_union(B) >>> C.print_info() +-------------------- Spatial extent ----------------------------------------+ | North:...................... 80.0 | South:...................... 20.0 | East:.. .................... 60.0 | West:....................... 10.0 | Top:........................ 50.0 | Bottom:..................... -50.0 >>> B = SpatialExtent(north=40, south=30, east=60, west=30, ... bottom=-50, top=50) >>> C = A.disjoint_union(B) >>> C.print_info() +-------------------- Spatial extent ----------------------------------------+ | North:...................... 80.0 | South:...................... 20.0 | East:.. .................... 60.0 | West:....................... 10.0 | Top:........................ 50.0 | Bottom:..................... -50.0 >>> B = SpatialExtent(north=40, south=30, east=60, west=30, ... bottom=-30, top=50) >>> C = A.disjoint_union(B) >>> C.print_info() +-------------------- Spatial extent ----------------------------------------+ | North:...................... 80.0 | South:...................... 20.0 | East:.. .................... 60.0 | West:....................... 10.0 | Top:........................ 50.0 | Bottom:..................... -50.0 >>> B = SpatialExtent(north=40, south=30, east=60, west=30, ... bottom=-30, top=30) >>> C = A.disjoint_union(B) >>> C.print_info() +-------------------- Spatial extent ----------------------------------------+ | North:...................... 80.0 | South:...................... 20.0 | East:.. .................... 60.0 | West:....................... 10.0 | Top:........................ 50.0 | Bottom:..................... -50.0 >>> A = SpatialExtent(north=80, south=20, east=60, west=10, ... bottom=-50, top=50) >>> B = SpatialExtent(north=90, south=80, east=70, west=20, ... bottom=-30, top=60) >>> C = A.disjoint_union(B) >>> C.print_info() +-------------------- Spatial extent ----------------------------------------+ | North:...................... 90.0 | South:...................... 20.0 | East:.. .................... 70.0 | West:....................... 10.0 | Top:........................ 60.0 | Bottom:..................... -50.0 :param extent: The spatial extent to create a disjoint union with :return: The union spatial extent
-
disjoint_union_2d
(extent)[source]¶ Return the two dimensional union as spatial_extent.
Parameters: extent – The spatial extent to create a union with Returns: The union spatial extent
-
east
¶ Get the eastern edge of the map :return: None if not found
-
equivalent
(extent)[source]¶ Return True if this extent (A) is equal to the provided spatial extent (B) in three dimensions.
Usage:
>>> A = SpatialExtent(north=80, south=20, east=60, west=10, ... bottom=-50, top=50) >>> B = SpatialExtent(north=80, south=20, east=60, west=10, ... bottom=-50, top=50) >>> A.equivalent(B) True >>> B.equivalent(A) True
Parameters: extent – The spatial extent Returns: True or False
-
equivalent_2d
(extent)[source]¶ Return True if this extent (A) is equal to the provided spatial extent (B) in two dimensions.
Usage:
>>> A = SpatialExtent(north=80, south=20, east=60, west=10) >>> B = SpatialExtent(north=80, south=20, east=60, west=10) >>> A.equivalent_2d(B) True >>> B.equivalent_2d(A) True
Parameters: extent – The spatial extent Returns: True or False
-
get_id
()[source]¶ Convenient method to get the unique identifier (primary key) :return: None if not found
-
get_spatial_extent_as_tuple
()[source]¶ Return a tuple (north, south, east, west, top, bottom) of the spatial extent
-
get_spatial_extent_as_tuple_2d
()[source]¶ Return a tuple (north, south, east, west,) of the 2d spatial extent
-
get_volume
()[source]¶ Compute the volume of the extent, in case z is zero (top == bottom or top - bottom = 1) the area is returned
-
id
¶ Convenient method to get the unique identifier (primary key) :return: None if not found
-
intersect
(extent)[source]¶ Return the three dimensional intersection as spatial_extent object or None in case no intersection was found.
Usage:
>>> A = SpatialExtent(north=80, south=20, east=60, west=10, ... bottom=-50, top=50) >>> B = SpatialExtent(north=80, south=20, east=60, west=10, ... bottom=-50, top=50) >>> C = A.intersect(B) >>> C.print_info() +-------------------- Spatial extent ----------------------------------------+ | North:...................... 80.0 | South:...................... 20.0 | East:.. .................... 60.0 | West:....................... 10.0 | Top:........................ 50.0 | Bottom:..................... -50.0 >>> B = SpatialExtent(north=40, south=30, east=60, west=10, ... bottom=-50, top=50) >>> C = A.intersect(B) >>> C.print_info() +-------------------- Spatial extent ----------------------------------------+ | North:...................... 40.0 | South:...................... 30.0 | East:.. .................... 60.0 | West:....................... 10.0 | Top:........................ 50.0 | Bottom:..................... -50.0 >>> B = SpatialExtent(north=40, south=30, east=60, west=30, ... bottom=-50, top=50) >>> C = A.intersect(B) >>> C.print_info() +-------------------- Spatial extent ----------------------------------------+ | North:...................... 40.0 | South:...................... 30.0 | East:.. .................... 60.0 | West:....................... 30.0 | Top:........................ 50.0 | Bottom:..................... -50.0 >>> B = SpatialExtent(north=40, south=30, east=60, west=30, ... bottom=-30, top=50) >>> C = A.intersect(B) >>> C.print_info() +-------------------- Spatial extent ----------------------------------------+ | North:...................... 40.0 | South:...................... 30.0 | East:.. .................... 60.0 | West:....................... 30.0 | Top:........................ 50.0 | Bottom:..................... -30.0 >>> B = SpatialExtent(north=40, south=30, east=60, west=30, ... bottom=-30, top=30) >>> C = A.intersect(B) >>> C.print_info() +-------------------- Spatial extent ----------------------------------------+ | North:...................... 40.0 | South:...................... 30.0 | East:.. .................... 60.0 | West:....................... 30.0 | Top:........................ 30.0 | Bottom:..................... -30.0 :param extent: The spatial extent to intersect with :return: The intersection spatial extent
-
intersect_2d
(extent)[source]¶ - Return the two dimensional intersection as spatial_extent
- object or None in case no intersection was found.
Parameters: extent – The spatial extent to intersect with Returns: The intersection spatial extent
-
is_in
(extent)[source]¶ Return True if this extent (A) is located in the provided spatial extent (B) in three dimensions.
Usage:
>>> A = SpatialExtent(north=79, south=21, east=59, west=11, ... bottom=-49, top=49) >>> B = SpatialExtent(north=80, south=20, east=60, west=10, ... bottom=-50, top=50) >>> A.is_in(B) True >>> B.is_in(A) False
Parameters: extent – The spatial extent Returns: True or False
-
is_in_2d
(extent)[source]¶ Return True if this extent (A) is located in the provided spatial extent (B) in two dimensions.
_____ |A _ | | |_| | |_____|B
Parameters: extent – The spatial extent Returns: True or False
-
meet
(extent)[source]¶ Return True if this extent meets with the provided spatial extent in three dimensions.
Parameters: extent – The spatial extent Returns: True or False
-
meet_2d
(extent)[source]¶ Return True if this extent (A) meets with the provided spatial extent (B) in two dimensions.
_____ _____ | A | B | |_____| | |_____| _____ _____ | B | A | | | | |_____|_____| ___ | A | | | |___| | B | | | |_____| _____ | B | | | |_____|_ | A | | | |_____|
Parameters: extent – The spatial extent Returns: True or False
-
north
¶ Get the northern edge of the map :return: None if not found
-
overlap
(extent)[source]¶ Return True if this extent overlaps with the provided spatial extent in three dimensions.
The following cases are excluded:
- contain
- in
- cover
- covered
- equivalent
Parameters: extent – The spatial extent Returns: True or False
-
overlap_2d
(extent)[source]¶ Return True if this extent (A) overlaps with the provided spatial extent (B) in two dimensions. Code is lend from wind_overlap.c in lib/gis
_____ |A __|__ | | | B| |__|__| | |_____|
The following cases are excluded:
- contain
- in
- cover
- covered
- equivalent
Parameters: extent – The spatial extent Returns: True or False
-
overlapping
(extent)[source]¶ Return True if this (A) and the provided spatial extent (B) overlaps in three dimensional space.
Overlapping includes the spatial relations:
- contain
- in
- cover
- covered
- equivalent
Usage:
>>> A = SpatialExtent(north=80, south=20, east=60, west=10, bottom=-50, top=50) >>> B = SpatialExtent(north=80, south=20, east=60, west=10, bottom=-50, top=50) >>> A.overlapping(B) True
Parameters: extent – The spatial extent to check overlapping with Returns: True or False
-
overlapping_2d
(extent)[source]¶ Return True if this (A) and the provided spatial extent (B) overlaps in two dimensional space. Code is lend from wind_overlap.c in lib/gis
Overlapping includes the spatial relations:
- contain
- in
- cover
- covered
- equivalent
>>> A = SpatialExtent(north=80, south=20, east=60, west=10) >>> B = SpatialExtent(north=80, south=20, east=60, west=10) >>> A.overlapping_2d(B) True
Parameters: extent – The spatial extent to check overlapping with Returns: True or False
-
set_projection
(proj)[source]¶ Set the projection of the spatial extent it should be XY or LL. As default the projection is XY
-
set_spatial_extent
(spatial_extent)[source]¶ Set the three dimensional spatial extent
Parameters: spatial_extent – An object of type SpatialExtent or its subclasses
-
set_spatial_extent_2d
(spatial_extent)[source]¶ Set the three dimensional spatial extent
Parameters: spatial_extent – An object of type SpatialExtent or its subclasses
-
set_spatial_extent_from_values
(north, south, east, west, top, bottom)[source]¶ Set the three dimensional spatial extent
Parameters: - north – The northern edge
- south – The southern edge
- east – The eastern edge
- west – The western edge
- top – The top edge
- bottom – The bottom edge
-
set_spatial_extent_from_values_2d
(north, south, east, west)[source]¶ Set the two dimensional spatial extent from values
Parameters: - north – The northern edge
- south – The southern edge
- east – The eastern edge
- west – The western edge
-
south
¶ Get the southern edge of the map :return: None if not found
-
spatial_relation
(extent)[source]¶ Returns the two dimensional spatial relation between this extent and the provided spatial extent in three dimensions.
Spatial relations are:
- disjoint
- meet
- overlap
- cover
- covered
- in
- contain
- equivalent
Usage:
>>> A = SpatialExtent(north=80, south=20, east=60, west=10, bottom=-50, top=50) >>> B = SpatialExtent(north=80, south=20, east=60, west=10, bottom=-50, top=50) >>> A.spatial_relation(B) 'equivalent' >>> B.spatial_relation(A) 'equivalent' >>> B = SpatialExtent(north=70, south=20, east=60, west=10, bottom=-50, top=50) >>> A.spatial_relation_2d(B) 'cover' >>> A.spatial_relation(B) 'cover' >>> B = SpatialExtent(north=70, south=30, east=60, west=10, bottom=-50, top=50) >>> A.spatial_relation_2d(B) 'cover' >>> A.spatial_relation(B) 'cover' >>> B.spatial_relation_2d(A) 'covered' >>> B.spatial_relation(A) 'covered' >>> B = SpatialExtent(north=70, south=30, east=50, west=10, bottom=-50, top=50) >>> A.spatial_relation_2d(B) 'cover' >>> B.spatial_relation_2d(A) 'covered' >>> A.spatial_relation(B) 'cover' >>> B = SpatialExtent(north=70, south=30, east=50, west=20, bottom=-50, top=50) >>> B.spatial_relation(A) 'covered' >>> B = SpatialExtent(north=70, south=30, east=50, west=20, bottom=-50, top=50) >>> A.spatial_relation_2d(B) 'contain' >>> A.spatial_relation(B) 'cover' >>> B = SpatialExtent(north=70, south=30, east=50, west=20, bottom=-40, top=50) >>> A.spatial_relation(B) 'cover' >>> B = SpatialExtent(north=70, south=30, east=50, west=20, bottom=-40, top=40) >>> A.spatial_relation(B) 'contain' >>> B.spatial_relation(A) 'in' >>> B = SpatialExtent(north=90, south=30, east=50, west=20, bottom=-40, top=40) >>> A.spatial_relation_2d(B) 'overlap' >>> A.spatial_relation(B) 'overlap' >>> B = SpatialExtent(north=90, south=5, east=70, west=5, bottom=-40, top=40) >>> A.spatial_relation_2d(B) 'in' >>> A.spatial_relation(B) 'overlap' >>> B = SpatialExtent(north=90, south=5, east=70, west=5, bottom=-40, top=60) >>> A.spatial_relation(B) 'overlap' >>> B = SpatialExtent(north=90, south=5, east=70, west=5, bottom=-60, top=60) >>> A.spatial_relation(B) 'in' >>> A = SpatialExtent(north=80, south=60, east=60, west=10, bottom=-50, top=50) >>> B = SpatialExtent(north=60, south=20, east=60, west=10, bottom=-50, top=50) >>> A.spatial_relation_2d(B) 'meet' >>> A.spatial_relation(B) 'meet' >>> A = SpatialExtent(north=60, south=40, east=60, west=10, bottom=-50, top=50) >>> B = SpatialExtent(north=80, south=60, east=60, west=10, bottom=-50, top=50) >>> A.spatial_relation_2d(B) 'meet' >>> A.spatial_relation(B) 'meet' >>> A = SpatialExtent(north=80, south=40, east=60, west=40, bottom=-50, top=50) >>> B = SpatialExtent(north=80, south=40, east=40, west=20, bottom=-50, top=50) >>> A.spatial_relation_2d(B) 'meet' >>> A.spatial_relation(B) 'meet' >>> A = SpatialExtent(north=80, south=40, east=40, west=20, bottom=-50, top=50) >>> B = SpatialExtent(north=90, south=30, east=60, west=40, bottom=-50, top=50) >>> A.spatial_relation_2d(B) 'meet' >>> A.spatial_relation(B) 'meet' >>> A = SpatialExtent(north=80, south=40, east=40, west=20, bottom=-50, top=50) >>> B = SpatialExtent(north=70, south=50, east=60, west=40, bottom=-50, top=50) >>> A.spatial_relation_2d(B) 'meet' >>> A.spatial_relation(B) 'meet' >>> A = SpatialExtent(north=80, south=40, east=40, west=20, bottom=-50, top=50) >>> B = SpatialExtent(north=60, south=20, east=60, west=40, bottom=-50, top=50) >>> A.spatial_relation_2d(B) 'meet' >>> A.spatial_relation(B) 'meet' >>> A = SpatialExtent(north=80, south=40, east=40, west=20, bottom=-50, top=50) >>> B = SpatialExtent(north=40, south=20, east=60, west=40, bottom=-50, top=50) >>> A.spatial_relation_2d(B) 'disjoint' >>> A.spatial_relation(B) 'disjoint' >>> A = SpatialExtent(north=80, south=40, east=40, west=20, bottom=-50, top=50) >>> B = SpatialExtent(north=60, south=20, east=60, west=40, bottom=-60, top=60) >>> A.spatial_relation(B) 'meet' >>> A = SpatialExtent(north=80, south=40, east=40, west=20, bottom=-50, top=50) >>> B = SpatialExtent(north=90, south=30, east=60, west=40, bottom=-40, top=40) >>> A.spatial_relation(B) 'meet' >>> A = SpatialExtent(north=80, south=40, east=60, west=20, bottom=0, top=50) >>> B = SpatialExtent(north=80, south=40, east=60, west=20, bottom=-50, top=0) >>> A.spatial_relation(B) 'meet' >>> A = SpatialExtent(north=80, south=40, east=60, west=20, bottom=0, top=50) >>> B = SpatialExtent(north=80, south=50, east=60, west=30, bottom=-50, top=0) >>> A.spatial_relation(B) 'meet' >>> A = SpatialExtent(north=80, south=40, east=60, west=20, bottom=0, top=50) >>> B = SpatialExtent(north=70, south=50, east=50, west=30, bottom=-50, top=0) >>> A.spatial_relation(B) 'meet' >>> A = SpatialExtent(north=80, south=40, east=60, west=20, bottom=0, top=50) >>> B = SpatialExtent(north=90, south=30, east=70, west=10, bottom=-50, top=0) >>> A.spatial_relation(B) 'meet' >>> A = SpatialExtent(north=80, south=40, east=60, west=20, bottom=0, top=50) >>> B = SpatialExtent(north=70, south=30, east=50, west=10, bottom=-50, top=0) >>> A.spatial_relation(B) 'meet' >>> A = SpatialExtent(north=80, south=40, east=60, west=20, bottom=-50, top=0) >>> B = SpatialExtent(north=80, south=40, east=60, west=20, bottom=0, top=50) >>> A.spatial_relation(B) 'meet' >>> A = SpatialExtent(north=80, south=40, east=60, west=20, bottom=-50, top=0) >>> B = SpatialExtent(north=80, south=50, east=60, west=30, bottom=0, top=50) >>> A.spatial_relation(B) 'meet' >>> A = SpatialExtent(north=80, south=40, east=60, west=20, bottom=-50, top=0) >>> B = SpatialExtent(north=70, south=50, east=50, west=30, bottom=0, top=50) >>> A.spatial_relation(B) 'meet' >>> A = SpatialExtent(north=80, south=40, east=60, west=20, bottom=-50, top=0) >>> B = SpatialExtent(north=90, south=30, east=70, west=10, bottom=0, top=50) >>> A.spatial_relation(B) 'meet' >>> A = SpatialExtent(north=80, south=40, east=60, west=20, bottom=-50, top=0) >>> B = SpatialExtent(north=70, south=30, east=50, west=10, bottom=0, top=50) >>> A.spatial_relation(B) 'meet' >>> A = SpatialExtent(north=80, south=20, east=60, west=10, bottom=-50, top=50) >>> B = SpatialExtent(north=90, south=81, east=60, west=10, bottom=-50, top=50) >>> A.spatial_relation(B) 'disjoint' >>> A = SpatialExtent(north=80, south=20, east=60, west=10, bottom=-50, top=50) >>> B = SpatialExtent(north=90, south=80, east=60, west=10, bottom=-50, top=50) >>> A.spatial_relation(B) 'meet'
-
spatial_relation_2d
(extent)[source]¶ Returns the two dimensional spatial relation between this extent and the provided spatial extent in two dimensions.
Spatial relations are:
- disjoint
- meet
- overlap
- cover
- covered
- in
- contain
- equivalent
Usage: see self.spatial_relation()
-
top
¶ Get the top edge of the map :return: None if not found
-
union
(extent)[source]¶ - Return the three dimensional union as spatial_extent
- object or None in case the extents does not overlap or meet.
Parameters: extent – The spatial extent to create a union with Returns: The union spatial extent
-
union_2d
(extent)[source]¶ - Return the two dimensional union as spatial_extent
- object or None in case the extents does not overlap or meet.
Parameters: extent – The spatial extent to create a union with Returns: The union spatial extent
-
west
¶ Get the western edge of the map :return: None if not found
-
temporal.spatial_topology_dataset_connector module¶
Spatial topology connector class
Usage:
>>> import grass.temporal as tgis
>>> tmr = tgis.SpatialTopologyDatasetConnector()
(C) 2012-2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
-
class
temporal.spatial_topology_dataset_connector.
SpatialTopologyDatasetConnector
[source]¶ Bases:
object
This class implements a spatial topology access structure to connect spatial related datasets
This object will be set up by spatial topology creation method provided by the SpatioTemporalTopologyBuilder.
The following spatial relations with access methods are supported:
- equivalent
- overlap
- in
- contain
- meet
- cover
- covered
Usage:
>>> import grass.temporal as tgis >>> tgis.init() >>> map = tgis.RasterDataset("a@P") >>> tmr = tgis.SpatialTopologyDatasetConnector() >>> tmr.append_equivalent(map) >>> tmr.append_overlap(map) >>> tmr.append_in(map) >>> tmr.append_contain(map) >>> tmr.append_meet(map) >>> tmr.append_cover(map) >>> tmr.append_covered(map) >>> tmr.print_spatial_topology_info() +-------------------- Spatial Topology --------------------------------------+ | Equivalent: ................ a@P | Cover: ..................... a@P | Covered: ................... a@P | Overlap: ................... a@P | In: ........................ a@P | Contain: ................... a@P | Meet: ...................... a@P >>> tmr.print_spatial_topology_shell_info() equivalent=a@P cover=a@P covered=a@P overlap=a@P in=a@P contain=a@P meet=a@P >>> rlist = tmr.get_spatial_relations() >>> if "COVER" in rlist.keys(): ... print(rlist["COVER"][0].get_id()) a@P
-
append_contain
(map)[source]¶ Append a map that this map spatially contains
Parameters: map – This object should be of type AbstractMapDataset or derived classes
-
append_cover
(map)[source]¶ Append a map that spatially cover this map
Parameters: map – This object should be of type AbstractMapDataset or derived classes
-
append_covered
(map)[source]¶ Append a map that is spatially covered by this map
Parameters: map – This object should be of type AbstractMapDataset or derived classes
-
append_equivalent
(map)[source]¶ Append a map with equivalent spatial extent as this map
Parameters: map – This object should be of type AbstractMapDataset or derived classes
-
append_in
(map)[source]¶ Append a map that this is spatial in this map
Parameters: map – This object should be of type AbstractMapDataset or derived classes
-
append_meet
(map)[source]¶ Append a map that spatially meet with this map
Parameters: map – This object should be of type AbstractMapDataset or derived classes
-
append_overlap
(map)[source]¶ Append a map that this spatial overlap with this map
Parameters: map – This object should be of type AbstractMapDataset or derived classes
-
contain
¶ Return a list of map objects that this map contains
Returns: A list of map objects or None
-
cover
¶ Return a list of map objects that spatially cover this map
Returns: A list of map objects or None
-
covered
¶ Return a list of map objects that are spatially covered by this map
Returns: A list of map objects or None
-
equivalent
¶ Return a list of map objects with equivalent spatial extent as this map
Returns: A list of map objects or None
-
get_contain
()[source]¶ Return a list of map objects that this map contains
Returns: A list of map objects or None
-
get_cover
()[source]¶ Return a list of map objects that spatially cover this map
Returns: A list of map objects or None
-
get_covered
()[source]¶ Return a list of map objects that are spatially covered by this map
Returns: A list of map objects or None
-
get_equivalent
()[source]¶ Return a list of map objects with equivalent spatial extent as this map
Returns: A list of map objects or None
-
get_in
()[source]¶ Return a list of map objects that are spatial in this map
Returns: A list of map objects or None
-
get_meet
()[source]¶ Return a list of map objects that spatially meet with this map
Returns: A list of map objects or None
-
get_number_of_spatial_relations
()[source]¶ Return a dictionary in which the keys are the relation names and the value are the number of relations.
The following relations are available:
- equivalent
- overlap
- in
- contain
- meet
- cover
- covered
To access topological information the spatial topology must be build first using the SpatialTopologyBuilder.
Returns: the dictionary with relations as keys and number as values or None in case the topology wasn’t build
-
get_overlap
()[source]¶ Return a list of map objects that this map spatial overlap with
Returns: A list of map objects or None
-
get_spatial_relations
()[source]¶ Return the dictionary of spatial relationships
Keys are the spatial relationships in upper case, values are abstract map objects.
Returns: The spatial relations dictionary
-
in_
¶ Return a list of map objects that are spatial in this map
Returns: A list of map objects or None
-
meet
¶ Return a list of map objects that spatially meet with this map
Returns: A list of map objects or None
-
overlap
¶ Return a list of map objects that this map spatial overlap with
Returns: A list of map objects or None
temporal.spatio_temporal_relationships module¶
Class to build the spatio-temporal topology between map lists
Usage:
import grass.temporal as tgis
tgis.print_temporal_relations(maps)
(C) 2012-2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
-
class
temporal.spatio_temporal_relationships.
SpatioTemporalTopologyBuilder
[source]¶ Bases:
object
This class is designed to build the spatio-temporal topology of spatio-temporally related abstract dataset objects.
The abstract dataset objects must be provided as a single list, or in two lists.
Example:
# We have a space time raster dataset and build a map list # from all registered maps ordered by start time maps = strds.get_registered_maps_as_objects() # Now lets build the temporal topology of the maps in the list tb = SpatioTemporalTopologyBuilder() tb.build(maps) dbif, connected = init_dbif(None) for map in tb: map.select(dbif) map.print_info() # Same can be done with the existing map list # But be aware that this is might not be temporally ordered for map in maps: map.select(dbf) map.print_info() # Using the next and previous methods, we can iterate over the # topological related maps in this way first = tb.get_first() while first: first.print_topology_info() first = first.next() # Dictionary like accessed map = tb["name@mapset"] >>> # Example with two lists of maps >>> import grass.temporal as tgis >>> import datetime >>> # Create two list of maps with equal time stamps >>> mapsA = [] >>> mapsB = [] >>> for i in range(4): ... idA = "a%i@B"%(i) ... mapA = tgis.RasterDataset(idA) ... idB = "b%i@B"%(i) ... mapB = tgis.RasterDataset(idB) ... check = mapA.set_relative_time(i, i + 1, "months") ... check = mapB.set_relative_time(i, i + 1, "months") ... mapsA.append(mapA) ... mapsB.append(mapB) >>> # Build the topology between the two map lists >>> tb = SpatioTemporalTopologyBuilder() >>> tb.build(mapsA, mapsB, None) >>> # Check relations of mapsA >>> for map in mapsA: ... if map.get_equal(): ... relations = map.get_equal() ... print("Map %s has equal relation to map %s"%(map.get_name(), ... relations[0].get_name())) Map a0 has equal relation to map b0 Map a1 has equal relation to map b1 Map a2 has equal relation to map b2 Map a3 has equal relation to map b3 >>> # Check relations of mapsB >>> for map in mapsB: ... if map.get_equal(): ... relations = map.get_equal() ... print("Map %s has equal relation to map %s"%(map.get_name(), ... relations[0].get_name())) Map b0 has equal relation to map a0 Map b1 has equal relation to map a1 Map b2 has equal relation to map a2 Map b3 has equal relation to map a3 >>> mapsA = [] >>> mapsB = [] >>> for i in range(4): ... idA = "a%i@B"%(i) ... mapA = tgis.RasterDataset(idA) ... idB = "b%i@B"%(i) ... mapB = tgis.RasterDataset(idB) ... check = mapA.set_relative_time(i, i + 1, "months") ... check = mapB.set_relative_time(i + 1, i + 2, "months") ... mapsA.append(mapA) ... mapsB.append(mapB) >>> # Build the topology between the two map lists >>> tb = SpatioTemporalTopologyBuilder() >>> tb.build(mapsA, mapsB, None) >>> # Check relations of mapsA >>> for map in mapsA: ... print(map.get_temporal_extent_as_tuple()) ... m = map.get_temporal_relations() ... for key in m.keys(): ... if key not in ["NEXT", "PREV"]: ... print((key, m[key][0].get_temporal_extent_as_tuple())) (0, 1) ('PRECEDES', (1, 2)) (1, 2) ('PRECEDES', (2, 3)) ('EQUAL', (1, 2)) (2, 3) ('FOLLOWS', (1, 2)) ('PRECEDES', (3, 4)) ('EQUAL', (2, 3)) (3, 4) ('FOLLOWS', (2, 3)) ('EQUAL', (3, 4)) ('PRECEDES', (4, 5)) >>> mapsA = [] >>> mapsB = [] >>> for i in range(4): ... idA = "a%i@B"%(i) ... mapA = tgis.RasterDataset(idA) ... idB = "b%i@B"%(i) ... mapB = tgis.RasterDataset(idB) ... start = datetime.datetime(2000 + i, 1, 1) ... end = datetime.datetime(2000 + i + 1, 1, 1) ... check = mapA.set_absolute_time(start, end) ... start = datetime.datetime(2000 + i + 1, 1, 1) ... end = datetime.datetime(2000 + i + 2, 1, 1) ... check = mapB.set_absolute_time(start, end) ... mapsA.append(mapA) ... mapsB.append(mapB) >>> # Build the topology between the two map lists >>> tb = SpatioTemporalTopologyBuilder() >>> tb.build(mapsA, mapsB, None) >>> # Check relations of mapsA >>> for map in mapsA: ... print(map.get_temporal_extent_as_tuple()) ... m = map.get_temporal_relations() ... for key in m.keys(): ... if key not in ["NEXT", "PREV"]: ... print((key, m[key][0].get_temporal_extent_as_tuple())) (datetime.datetime(2000, 1, 1, 0, 0), datetime.datetime(2001, 1, 1, 0, 0)) ('PRECEDES', (datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2002, 1, 1, 0, 0))) (datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2002, 1, 1, 0, 0)) ('PRECEDES', (datetime.datetime(2002, 1, 1, 0, 0), datetime.datetime(2003, 1, 1, 0, 0))) ('EQUAL', (datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2002, 1, 1, 0, 0))) (datetime.datetime(2002, 1, 1, 0, 0), datetime.datetime(2003, 1, 1, 0, 0)) ('FOLLOWS', (datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2002, 1, 1, 0, 0))) ('PRECEDES', (datetime.datetime(2003, 1, 1, 0, 0), datetime.datetime(2004, 1, 1, 0, 0))) ('EQUAL', (datetime.datetime(2002, 1, 1, 0, 0), datetime.datetime(2003, 1, 1, 0, 0))) (datetime.datetime(2003, 1, 1, 0, 0), datetime.datetime(2004, 1, 1, 0, 0)) ('FOLLOWS', (datetime.datetime(2002, 1, 1, 0, 0), datetime.datetime(2003, 1, 1, 0, 0))) ('EQUAL', (datetime.datetime(2003, 1, 1, 0, 0), datetime.datetime(2004, 1, 1, 0, 0))) ('PRECEDES', (datetime.datetime(2004, 1, 1, 0, 0), datetime.datetime(2005, 1, 1, 0, 0))) >>> mapsA = [] >>> mapsB = [] >>> for i in range(4): ... idA = "a%i@B"%(i) ... mapA = tgis.RasterDataset(idA) ... idB = "b%i@B"%(i) ... mapB = tgis.RasterDataset(idB) ... start = datetime.datetime(2000 + i, 1, 1) ... end = datetime.datetime(2000 + i + 1, 1, 1) ... check = mapA.set_absolute_time(start, end) ... start = datetime.datetime(2000 + i, 1, 1) ... end = datetime.datetime(2000 + i + 3, 1, 1) ... check = mapB.set_absolute_time(start, end) ... mapsA.append(mapA) ... mapsB.append(mapB) >>> # Build the topology between the two map lists >>> tb = SpatioTemporalTopologyBuilder() >>> tb.build(mapsA, mapsB, None) >>> # Check relations of mapsA >>> for map in mapsA: ... print(map.get_temporal_extent_as_tuple()) ... m = map.get_temporal_relations() ... for key in m.keys(): ... if key not in ["NEXT", "PREV"]: ... print((key, m[key][0].get_temporal_extent_as_tuple())) (datetime.datetime(2000, 1, 1, 0, 0), datetime.datetime(2001, 1, 1, 0, 0)) ('DURING', (datetime.datetime(2000, 1, 1, 0, 0), datetime.datetime(2003, 1, 1, 0, 0))) ('STARTS', (datetime.datetime(2000, 1, 1, 0, 0), datetime.datetime(2003, 1, 1, 0, 0))) ('PRECEDES', (datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2004, 1, 1, 0, 0))) (datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2002, 1, 1, 0, 0)) ('DURING', (datetime.datetime(2000, 1, 1, 0, 0), datetime.datetime(2003, 1, 1, 0, 0))) ('STARTS', (datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2004, 1, 1, 0, 0))) ('PRECEDES', (datetime.datetime(2002, 1, 1, 0, 0), datetime.datetime(2005, 1, 1, 0, 0))) (datetime.datetime(2002, 1, 1, 0, 0), datetime.datetime(2003, 1, 1, 0, 0)) ('PRECEDES', (datetime.datetime(2003, 1, 1, 0, 0), datetime.datetime(2006, 1, 1, 0, 0))) ('FINISHES', (datetime.datetime(2000, 1, 1, 0, 0), datetime.datetime(2003, 1, 1, 0, 0))) ('DURING', (datetime.datetime(2000, 1, 1, 0, 0), datetime.datetime(2003, 1, 1, 0, 0))) ('STARTS', (datetime.datetime(2002, 1, 1, 0, 0), datetime.datetime(2005, 1, 1, 0, 0))) (datetime.datetime(2003, 1, 1, 0, 0), datetime.datetime(2004, 1, 1, 0, 0)) ('FOLLOWS', (datetime.datetime(2000, 1, 1, 0, 0), datetime.datetime(2003, 1, 1, 0, 0))) ('DURING', (datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2004, 1, 1, 0, 0))) ('FINISHES', (datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2004, 1, 1, 0, 0))) ('STARTS', (datetime.datetime(2003, 1, 1, 0, 0), datetime.datetime(2006, 1, 1, 0, 0))) >>> mapsA = [] >>> mapsB = [] >>> for i in range(4): ... idA = "a%i@B"%(i) ... mapA = tgis.RasterDataset(idA) ... idB = "b%i@B"%(i) ... mapB = tgis.RasterDataset(idB) ... start = datetime.datetime(2000 + i, 1, 1) ... end = datetime.datetime(2000 + i + 2, 1, 1) ... check = mapA.set_absolute_time(start, end) ... start = datetime.datetime(2000 + i, 1, 1) ... end = datetime.datetime(2000 + i + 3, 1, 1) ... check = mapB.set_absolute_time(start, end) ... mapsA.append(mapA) ... mapsB.append(mapB) >>> # Build the topology between the two map lists >>> tb = SpatioTemporalTopologyBuilder() >>> tb.build(mapsA, mapsB, None) >>> # Check relations of mapsA >>> for map in mapsA: ... print(map.get_temporal_extent_as_tuple()) ... m = map.get_temporal_relations() ... for key in m.keys(): ... if key not in ["NEXT", "PREV"]: ... print((key, m[key][0].get_temporal_extent_as_tuple())) (datetime.datetime(2000, 1, 1, 0, 0), datetime.datetime(2002, 1, 1, 0, 0)) ('OVERLAPS', (datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2004, 1, 1, 0, 0))) ('DURING', (datetime.datetime(2000, 1, 1, 0, 0), datetime.datetime(2003, 1, 1, 0, 0))) ('STARTS', (datetime.datetime(2000, 1, 1, 0, 0), datetime.datetime(2003, 1, 1, 0, 0))) ('PRECEDES', (datetime.datetime(2002, 1, 1, 0, 0), datetime.datetime(2005, 1, 1, 0, 0))) (datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2003, 1, 1, 0, 0)) ('OVERLAPS', (datetime.datetime(2002, 1, 1, 0, 0), datetime.datetime(2005, 1, 1, 0, 0))) ('PRECEDES', (datetime.datetime(2003, 1, 1, 0, 0), datetime.datetime(2006, 1, 1, 0, 0))) ('FINISHES', (datetime.datetime(2000, 1, 1, 0, 0), datetime.datetime(2003, 1, 1, 0, 0))) ('DURING', (datetime.datetime(2000, 1, 1, 0, 0), datetime.datetime(2003, 1, 1, 0, 0))) ('STARTS', (datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2004, 1, 1, 0, 0))) (datetime.datetime(2002, 1, 1, 0, 0), datetime.datetime(2004, 1, 1, 0, 0)) ('OVERLAPS', (datetime.datetime(2003, 1, 1, 0, 0), datetime.datetime(2006, 1, 1, 0, 0))) ('OVERLAPPED', (datetime.datetime(2000, 1, 1, 0, 0), datetime.datetime(2003, 1, 1, 0, 0))) ('FINISHES', (datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2004, 1, 1, 0, 0))) ('DURING', (datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2004, 1, 1, 0, 0))) ('STARTS', (datetime.datetime(2002, 1, 1, 0, 0), datetime.datetime(2005, 1, 1, 0, 0))) (datetime.datetime(2003, 1, 1, 0, 0), datetime.datetime(2005, 1, 1, 0, 0)) ('OVERLAPPED', (datetime.datetime(2001, 1, 1, 0, 0), datetime.datetime(2004, 1, 1, 0, 0))) ('DURING', (datetime.datetime(2002, 1, 1, 0, 0), datetime.datetime(2005, 1, 1, 0, 0))) ('FINISHES', (datetime.datetime(2002, 1, 1, 0, 0), datetime.datetime(2005, 1, 1, 0, 0))) ('STARTS', (datetime.datetime(2003, 1, 1, 0, 0), datetime.datetime(2006, 1, 1, 0, 0))) ('FOLLOWS', (datetime.datetime(2000, 1, 1, 0, 0), datetime.datetime(2003, 1, 1, 0, 0))) >>> mapsA = [] >>> mapsB = [] >>> for i in range(4): ... idA = "a%i@B"%(i) ... mapA = tgis.RasterDataset(idA) ... idB = "b%i@B"%(i) ... mapB = tgis.RasterDataset(idB) ... start = datetime.datetime(2000, 1, 1, 0, 0, i) ... end = datetime.datetime(2000, 1, 1, 0, 0, i + 2) ... check = mapA.set_absolute_time(start, end) ... start = datetime.datetime(2000, 1, 1, 0, 0, i + 1) ... end = datetime.datetime(2000, 1, 1, 0, 0, i + 3) ... check = mapB.set_absolute_time(start, end) ... mapsA.append(mapA) ... mapsB.append(mapB) >>> # Build the topology between the two map lists >>> tb = SpatioTemporalTopologyBuilder() >>> tb.build(mapsA, mapsB, None) >>> # Check relations of mapsA >>> for map in mapsA: ... print(map.get_temporal_extent_as_tuple()) ... m = map.get_temporal_relations() ... for key in m.keys(): ... if key not in ["NEXT", "PREV"]: ... print((key, m[key][0].get_temporal_extent_as_tuple())) (datetime.datetime(2000, 1, 1, 0, 0), datetime.datetime(2000, 1, 1, 0, 0, 2)) ('OVERLAPS', (datetime.datetime(2000, 1, 1, 0, 0, 1), datetime.datetime(2000, 1, 1, 0, 0, 3))) ('PRECEDES', (datetime.datetime(2000, 1, 1, 0, 0, 2), datetime.datetime(2000, 1, 1, 0, 0, 4))) (datetime.datetime(2000, 1, 1, 0, 0, 1), datetime.datetime(2000, 1, 1, 0, 0, 3)) ('OVERLAPS', (datetime.datetime(2000, 1, 1, 0, 0, 2), datetime.datetime(2000, 1, 1, 0, 0, 4))) ('PRECEDES', (datetime.datetime(2000, 1, 1, 0, 0, 3), datetime.datetime(2000, 1, 1, 0, 0, 5))) ('EQUAL', (datetime.datetime(2000, 1, 1, 0, 0, 1), datetime.datetime(2000, 1, 1, 0, 0, 3))) (datetime.datetime(2000, 1, 1, 0, 0, 2), datetime.datetime(2000, 1, 1, 0, 0, 4)) ('OVERLAPS', (datetime.datetime(2000, 1, 1, 0, 0, 3), datetime.datetime(2000, 1, 1, 0, 0, 5))) ('OVERLAPPED', (datetime.datetime(2000, 1, 1, 0, 0, 1), datetime.datetime(2000, 1, 1, 0, 0, 3))) ('PRECEDES', (datetime.datetime(2000, 1, 1, 0, 0, 4), datetime.datetime(2000, 1, 1, 0, 0, 6))) ('EQUAL', (datetime.datetime(2000, 1, 1, 0, 0, 2), datetime.datetime(2000, 1, 1, 0, 0, 4))) (datetime.datetime(2000, 1, 1, 0, 0, 3), datetime.datetime(2000, 1, 1, 0, 0, 5)) ('OVERLAPS', (datetime.datetime(2000, 1, 1, 0, 0, 4), datetime.datetime(2000, 1, 1, 0, 0, 6))) ('FOLLOWS', (datetime.datetime(2000, 1, 1, 0, 0, 1), datetime.datetime(2000, 1, 1, 0, 0, 3))) ('OVERLAPPED', (datetime.datetime(2000, 1, 1, 0, 0, 2), datetime.datetime(2000, 1, 1, 0, 0, 4))) ('EQUAL', (datetime.datetime(2000, 1, 1, 0, 0, 3), datetime.datetime(2000, 1, 1, 0, 0, 5))) >>> mapsA = [] >>> for i in range(4): ... idA = "a%i@B"%(i) ... mapA = tgis.RasterDataset(idA) ... start = datetime.datetime(2000, 1, 1, 0, 0, i) ... end = datetime.datetime(2000, 1, 1, 0, 0, i + 2) ... check = mapA.set_absolute_time(start, end) ... mapsA.append(mapA) >>> tb = SpatioTemporalTopologyBuilder() >>> tb.build(mapsA) >>> # Check relations of mapsA >>> for map in mapsA: ... print(map.get_temporal_extent_as_tuple()) ... m = map.get_temporal_relations() ... for key in m.keys(): ... if key not in ["NEXT", "PREV"]: ... print((key, m[key][0].get_temporal_extent_as_tuple())) (datetime.datetime(2000, 1, 1, 0, 0), datetime.datetime(2000, 1, 1, 0, 0, 2)) ('OVERLAPS', (datetime.datetime(2000, 1, 1, 0, 0, 1), datetime.datetime(2000, 1, 1, 0, 0, 3))) ('PRECEDES', (datetime.datetime(2000, 1, 1, 0, 0, 2), datetime.datetime(2000, 1, 1, 0, 0, 4))) (datetime.datetime(2000, 1, 1, 0, 0, 1), datetime.datetime(2000, 1, 1, 0, 0, 3)) ('OVERLAPS', (datetime.datetime(2000, 1, 1, 0, 0, 2), datetime.datetime(2000, 1, 1, 0, 0, 4))) ('OVERLAPPED', (datetime.datetime(2000, 1, 1, 0, 0), datetime.datetime(2000, 1, 1, 0, 0, 2))) ('PRECEDES', (datetime.datetime(2000, 1, 1, 0, 0, 3), datetime.datetime(2000, 1, 1, 0, 0, 5))) (datetime.datetime(2000, 1, 1, 0, 0, 2), datetime.datetime(2000, 1, 1, 0, 0, 4)) ('OVERLAPS', (datetime.datetime(2000, 1, 1, 0, 0, 3), datetime.datetime(2000, 1, 1, 0, 0, 5))) ('FOLLOWS', (datetime.datetime(2000, 1, 1, 0, 0), datetime.datetime(2000, 1, 1, 0, 0, 2))) ('OVERLAPPED', (datetime.datetime(2000, 1, 1, 0, 0, 1), datetime.datetime(2000, 1, 1, 0, 0, 3))) (datetime.datetime(2000, 1, 1, 0, 0, 3), datetime.datetime(2000, 1, 1, 0, 0, 5)) ('FOLLOWS', (datetime.datetime(2000, 1, 1, 0, 0, 1), datetime.datetime(2000, 1, 1, 0, 0, 3))) ('OVERLAPPED', (datetime.datetime(2000, 1, 1, 0, 0, 2), datetime.datetime(2000, 1, 1, 0, 0, 4)))
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build
(mapsA, mapsB=None, spatial=None)[source]¶ Build the spatio-temporal topology structure between one or two unordered lists of abstract dataset objects
This method builds the temporal or spatio-temporal topology from mapsA to mapsB and vice verse. The spatio-temporal topology structure of each map will be reset and rebuild for mapsA and mapsB.
After building the temporal or spatio-temporal topology the modified map objects of mapsA can be accessed in the same way as a dictionary using there id. The implemented iterator assures the chronological iteration over the mapsA.
Parameters: - mapsA – A list of abstract_dataset objects with initiated spatio-temporal extent
- mapsB – An optional list of abstract_dataset objects with initiated spatio-temporal extent
- spatial – This indicates if the spatial topology is created as well: spatial can be None (no spatial topology), “2D” using west, east, south, north or “3D” using west, east, south, north, bottom, top
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temporal.spatio_temporal_relationships.
count_temporal_topology_relationships
(maps1, maps2=None, dbif=None)[source]¶ Count the temporal relations of a single list of maps or between two lists of maps
param maps1: A list of abstract_dataset objects with initiated temporal extent param maps2: A list of abstract_dataset objects with initiated temporal extent param dbif: The database interface to be used return: A dictionary with counted temporal relationships
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temporal.spatio_temporal_relationships.
create_temporal_relation_sql_where_statement
(start, end, use_start=True, use_during=False, use_overlap=False, use_contain=False, use_equal=False, use_follows=False, use_precedes=False)[source]¶ Create a SQL WHERE statement for temporal relation selection of maps in space time datasets
param start: The start time
param end: The end time
param use_start: Select maps of which the start time is located in the selection granule
map : s granule: s-----------------e map : s--------------------e granule: s-----------------e map : s--------e granule: s-----------------e
param use_during: Select maps which are temporal during the selection granule
map : s-----------e granule: s-----------------e
param use_overlap: Select maps which temporal overlap the selection granule
map : s-----------e granule: s-----------------e map : s-----------e granule: s----------e
param use_contain: Select maps which temporally contain the selection granule
map : s-----------------e granule: s-----------e
param use_equal: Select maps which temporally equal to the selection granule
map : s-----------e granule: s-----------e
param use_follows: Select maps which temporally follow the selection granule
map : s-----------e granule: s-----------e
param use_precedes: Select maps which temporally precedes the selection granule
map : s-----------e granule: s-----------e
Usage:
>>> # Relative time >>> start = 1 >>> end = 2 >>> create_temporal_relation_sql_where_statement(start, end, ... use_start=False) >>> create_temporal_relation_sql_where_statement(start, end) '((start_time >= 1 and start_time < 2) )' >>> create_temporal_relation_sql_where_statement(start, end, ... use_start=True) '((start_time >= 1 and start_time < 2) )' >>> create_temporal_relation_sql_where_statement(start, end, ... use_start=False, use_during=True) '(((start_time > 1 and end_time < 2) OR (start_time >= 1 and end_time < 2) OR (start_time > 1 and end_time <= 2)))' >>> create_temporal_relation_sql_where_statement(start, end, ... use_start=False, use_overlap=True) '(((start_time < 1 and end_time > 1 and end_time < 2) OR (start_time < 2 and start_time > 1 and end_time > 2)))' >>> create_temporal_relation_sql_where_statement(start, end, ... use_start=False, use_contain=True) '(((start_time < 1 and end_time > 2) OR (start_time <= 1 and end_time > 2) OR (start_time < 1 and end_time >= 2)))' >>> create_temporal_relation_sql_where_statement(start, end, ... use_start=False, use_equal=True) '((start_time = 1 and end_time = 2))' >>> create_temporal_relation_sql_where_statement(start, end, ... use_start=False, use_follows=True) '((start_time = 2))' >>> create_temporal_relation_sql_where_statement(start, end, ... use_start=False, use_precedes=True) '((end_time = 1))' >>> create_temporal_relation_sql_where_statement(start, end, ... use_start=True, use_during=True, use_overlap=True, use_contain=True, ... use_equal=True, use_follows=True, use_precedes=True) '((start_time >= 1 and start_time < 2) OR ((start_time > 1 and end_time < 2) OR (start_time >= 1 and end_time < 2) OR (start_time > 1 and end_time <= 2)) OR ((start_time < 1 and end_time > 1 and end_time < 2) OR (start_time < 2 and start_time > 1 and end_time > 2)) OR ((start_time < 1 and end_time > 2) OR (start_time <= 1 and end_time > 2) OR (start_time < 1 and end_time >= 2)) OR (start_time = 1 and end_time = 2) OR (start_time = 2) OR (end_time = 1))' >>> # Absolute time >>> start = datetime(2001, 1, 1, 12, 30) >>> end = datetime(2001, 3, 31, 14, 30) >>> create_temporal_relation_sql_where_statement(start, end, ... use_start=False) >>> create_temporal_relation_sql_where_statement(start, end) "((start_time >= '2001-01-01 12:30:00' and start_time < '2001-03-31 14:30:00') )" >>> create_temporal_relation_sql_where_statement(start, end, ... use_start=True) "((start_time >= '2001-01-01 12:30:00' and start_time < '2001-03-31 14:30:00') )" >>> create_temporal_relation_sql_where_statement(start, end, ... use_start=False, use_during=True) "(((start_time > '2001-01-01 12:30:00' and end_time < '2001-03-31 14:30:00') OR (start_time >= '2001-01-01 12:30:00' and end_time < '2001-03-31 14:30:00') OR (start_time > '2001-01-01 12:30:00' and end_time <= '2001-03-31 14:30:00')))" >>> create_temporal_relation_sql_where_statement(start, end, ... use_start=False, use_overlap=True) "(((start_time < '2001-01-01 12:30:00' and end_time > '2001-01-01 12:30:00' and end_time < '2001-03-31 14:30:00') OR (start_time < '2001-03-31 14:30:00' and start_time > '2001-01-01 12:30:00' and end_time > '2001-03-31 14:30:00')))" >>> create_temporal_relation_sql_where_statement(start, end, ... use_start=False, use_contain=True) "(((start_time < '2001-01-01 12:30:00' and end_time > '2001-03-31 14:30:00') OR (start_time <= '2001-01-01 12:30:00' and end_time > '2001-03-31 14:30:00') OR (start_time < '2001-01-01 12:30:00' and end_time >= '2001-03-31 14:30:00')))" >>> create_temporal_relation_sql_where_statement(start, end, ... use_start=False, use_equal=True) "((start_time = '2001-01-01 12:30:00' and end_time = '2001-03-31 14:30:00'))" >>> create_temporal_relation_sql_where_statement(start, end, ... use_start=False, use_follows=True) "((start_time = '2001-03-31 14:30:00'))" >>> create_temporal_relation_sql_where_statement(start, end, ... use_start=False, use_precedes=True) "((end_time = '2001-01-01 12:30:00'))" >>> create_temporal_relation_sql_where_statement(start, end, ... use_start=True, use_during=True, use_overlap=True, use_contain=True, ... use_equal=True, use_follows=True, use_precedes=True) "((start_time >= '2001-01-01 12:30:00' and start_time < '2001-03-31 14:30:00') OR ((start_time > '2001-01-01 12:30:00' and end_time < '2001-03-31 14:30:00') OR (start_time >= '2001-01-01 12:30:00' and end_time < '2001-03-31 14:30:00') OR (start_time > '2001-01-01 12:30:00' and end_time <= '2001-03-31 14:30:00')) OR ((start_time < '2001-01-01 12:30:00' and end_time > '2001-01-01 12:30:00' and end_time < '2001-03-31 14:30:00') OR (start_time < '2001-03-31 14:30:00' and start_time > '2001-01-01 12:30:00' and end_time > '2001-03-31 14:30:00')) OR ((start_time < '2001-01-01 12:30:00' and end_time > '2001-03-31 14:30:00') OR (start_time <= '2001-01-01 12:30:00' and end_time > '2001-03-31 14:30:00') OR (start_time < '2001-01-01 12:30:00' and end_time >= '2001-03-31 14:30:00')) OR (start_time = '2001-01-01 12:30:00' and end_time = '2001-03-31 14:30:00') OR (start_time = '2001-03-31 14:30:00') OR (end_time = '2001-01-01 12:30:00'))"
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temporal.spatio_temporal_relationships.
print_spatio_temporal_topology_relationships
(maps1, maps2=None, spatial='2D', dbif=None)[source]¶ Print the temporal relationships of the map lists maps1 and maps2 to stdout.
param maps1: A list of abstract_dataset objects with initiated temporal extent param maps2: An optional list of abstract_dataset objects with initiated temporal extent param spatial: The dimension of the spatial extent to be used: “2D” using west, east, south, north or “3D” using west, east, south, north, bottom, top param dbif: The database interface to be used
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temporal.spatio_temporal_relationships.
print_temporal_topology_relationships
(maps1, maps2=None, dbif=None)[source]¶ Print the temporal relationships of the map lists maps1 and maps2 to stdout.
param maps1: A list of abstract_dataset objects with initiated temporal extent param maps2: An optional list of abstract_dataset objects with initiated temporal extent param dbif: The database interface to be used
temporal.stds_export module¶
Export functions for space time datasets
Usage:
import grass.temporal as tgis
input="temp_1950_2012@PERMANENT"
output="/tmp/temp_1950_2012.tar.gz"
compression="gzip"
directory="/tmp"
where=None
format_="GTiff"
type_="strds"
tgis.export_stds(input, output, compression, directory, where, format_, type_)
(C) 2012-2019 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
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temporal.stds_export.
export_stds
(input, output, compression, directory, where, format_='pack', type_='strds', datatype=None, **kwargs)[source]¶ Export space time datasets as tar archive with optional compression
This method should be used to export space time datasets of type raster and vector as tar archive that can be reimported with the method import_stds().
Parameters: - input – The name of the space time dataset to export
- output – The name of the archive file
- compression –
The compression of the archive file:
- ”no” no compression
- ”gzip” GNU zip compression
- ”bzip2” Bzip compression
- directory – The working directory used for extraction and packing
- where – The temporal WHERE SQL statement to select a subset of maps from the space time dataset
- format –
The export format:
- ”GTiff” Geotiff format, only for raster maps
- ”AAIGrid” Arc/Info ASCII Grid format, only for raster maps
- ”pack” The GRASS raster, 3D raster or vector Pack format,
- this is the default setting
- ”GML” GML file export format, only for vector maps,
- v.out.ogr export option
- ”GPKG” GPKG file export format, only for vector maps,
- v.out.ogr export option
- type –
The space time dataset type
- ”strds” Space time raster dataset
- ”str3ds” Space time 3D raster dataset
- ”stvds” Space time vector dataset
- datatype – Force the output datatype for r.out.gdal
temporal.stds_import module¶
Space time dataset import functions
Usage:
import grass.temporal as tgis
input="/tmp/temp_1950_2012.tar.gz"
output="temp_1950_2012"
directory="/tmp"
title="My new dataset"
descr="May new shiny dataset"
location=None
link=True
exp=True
overr=False
create=False
tgis.import_stds(input, output, directory, title, descr, location,
link, exp, overr, create, "strds")
(C) 2012-2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
-
temporal.stds_import.
import_stds
(input, output, directory, title=None, descr=None, location=None, link=False, exp=False, overr=False, create=False, stds_type='strds', base=None, set_current_region=False, memory=300)[source]¶ Import space time datasets of type raster and vector
Parameters: - input – Name of the input archive file
- output – The name of the output space time dataset
- directory – The extraction directory
- title – The title of the new created space time dataset
- descr – The description of the new created space time dataset
- location – The name of the location that should be created, maps are imported into this location
- link – Switch to link raster maps instead importing them
- exp – Extend location extents based on new dataset
- overr – Override projection (use location’s projection)
- create – Create the location specified by the “location” parameter and exit. Do not import the space time datasets.
- stds_type – The type of the space time dataset that should be imported
- base – The base name of the new imported maps, it will be extended using a numerical index.
- memory – Cache size for raster rows, used in r.in.gdal
temporal.temporal_algebra module¶
@package grass.temporal
Temporal algebra parser class
(C) 2014 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Thomas Leppelt and Soeren Gebbert |
---|
>>> import grass.temporal as tgis
>>> tgis.init(True)
>>> p = tgis.TemporalAlgebraLexer()
>>> p.build()
>>> p.debug = True
>>> expression = "C = A : B"
>>> p.test(expression)
C = A : B
LexToken(NAME,'C',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(NAME,'A',1,4)
LexToken(T_SELECT,':',1,6)
LexToken(NAME,'B',1,8)
>>> expression = "C = test1 !: test2"
>>> p.test(expression)
C = test1 !: test2
LexToken(NAME,'C',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(NAME,'test1',1,4)
LexToken(T_NOT_SELECT,'!:',1,10)
LexToken(NAME,'test2',1,13)
>>> expression = "C = test1 {:,equal} test2"
>>> p.test(expression)
C = test1 {:,equal} test2
LexToken(NAME,'C',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(NAME,'test1',1,4)
LexToken(T_SELECT_OPERATOR,'{:,equal}',1,10)
LexToken(NAME,'test2',1,20)
>>> expression = "C = test1 {!:,equal} test2"
>>> p.test(expression)
C = test1 {!:,equal} test2
LexToken(NAME,'C',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(NAME,'test1',1,4)
LexToken(T_SELECT_OPERATOR,'{!:,equal}',1,10)
LexToken(NAME,'test2',1,21)
>>> expression = "C = test1 # test2"
>>> p.test(expression)
C = test1 # test2
LexToken(NAME,'C',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(NAME,'test1',1,4)
LexToken(HASH,'#',1,10)
LexToken(NAME,'test2',1,12)
>>> expression = "C = test1 {#} test2"
>>> p.test(expression)
C = test1 {#} test2
LexToken(NAME,'C',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(NAME,'test1',1,4)
LexToken(T_HASH_OPERATOR,'{#}',1,10)
LexToken(NAME,'test2',1,14)
>>> expression = "C = test1 {#,equal} test2"
>>> p.test(expression)
C = test1 {#,equal} test2
LexToken(NAME,'C',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(NAME,'test1',1,4)
LexToken(T_HASH_OPERATOR,'{#,equal}',1,10)
LexToken(NAME,'test2',1,20)
>>> expression = "C = test1 {#,equal|during} test2"
>>> p.test(expression)
C = test1 {#,equal|during} test2
LexToken(NAME,'C',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(NAME,'test1',1,4)
LexToken(T_HASH_OPERATOR,'{#,equal|during}',1,10)
LexToken(NAME,'test2',1,27)
>>> expression = "E = test1 : test2 !: test1"
>>> p.test(expression)
E = test1 : test2 !: test1
LexToken(NAME,'E',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(NAME,'test1',1,4)
LexToken(T_SELECT,':',1,10)
LexToken(NAME,'test2',1,12)
LexToken(T_NOT_SELECT,'!:',1,18)
LexToken(NAME,'test1',1,21)
>>> expression = 'D = buff_t(test1,"10 months")'
>>> p.test(expression)
D = buff_t(test1,"10 months")
LexToken(NAME,'D',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(BUFF_T,'buff_t',1,4)
LexToken(LPAREN,'(',1,10)
LexToken(NAME,'test1',1,11)
LexToken(COMMA,',',1,16)
LexToken(QUOTE,'"',1,17)
LexToken(INT,10,1,18)
LexToken(NAME,'months',1,21)
LexToken(QUOTE,'"',1,27)
LexToken(RPAREN,')',1,28)
>>> expression = 'H = tsnap(test1)'
>>> p.test(expression)
H = tsnap(test1)
LexToken(NAME,'H',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(TSNAP,'tsnap',1,4)
LexToken(LPAREN,'(',1,9)
LexToken(NAME,'test1',1,10)
LexToken(RPAREN,')',1,15)
>>> expression = 'H = tsnap(test2 {:,during} buff_t(test1, "1 days"))'
>>> p.test(expression)
H = tsnap(test2 {:,during} buff_t(test1, "1 days"))
LexToken(NAME,'H',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(TSNAP,'tsnap',1,4)
LexToken(LPAREN,'(',1,9)
LexToken(NAME,'test2',1,10)
LexToken(T_SELECT_OPERATOR,'{:,during}',1,16)
LexToken(BUFF_T,'buff_t',1,27)
LexToken(LPAREN,'(',1,33)
LexToken(NAME,'test1',1,34)
LexToken(COMMA,',',1,39)
LexToken(QUOTE,'"',1,41)
LexToken(INT,1,1,42)
LexToken(NAME,'days',1,44)
LexToken(QUOTE,'"',1,48)
LexToken(RPAREN,')',1,49)
LexToken(RPAREN,')',1,50)
>>> expression = 'H = tshift(test2 {:,during} buff_t(test1, "1 days"), "1 months")'
>>> p.test(expression)
H = tshift(test2 {:,during} buff_t(test1, "1 days"), "1 months")
LexToken(NAME,'H',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(TSHIFT,'tshift',1,4)
LexToken(LPAREN,'(',1,10)
LexToken(NAME,'test2',1,11)
LexToken(T_SELECT_OPERATOR,'{:,during}',1,17)
LexToken(BUFF_T,'buff_t',1,28)
LexToken(LPAREN,'(',1,34)
LexToken(NAME,'test1',1,35)
LexToken(COMMA,',',1,40)
LexToken(QUOTE,'"',1,42)
LexToken(INT,1,1,43)
LexToken(NAME,'days',1,45)
LexToken(QUOTE,'"',1,49)
LexToken(RPAREN,')',1,50)
LexToken(COMMA,',',1,51)
LexToken(QUOTE,'"',1,53)
LexToken(INT,1,1,54)
LexToken(NAME,'months',1,56)
LexToken(QUOTE,'"',1,62)
LexToken(RPAREN,')',1,63)
>>> expression = 'H = tshift(A , 10)'
>>> p.test(expression)
H = tshift(A , 10)
LexToken(NAME,'H',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(TSHIFT,'tshift',1,4)
LexToken(LPAREN,'(',1,10)
LexToken(NAME,'A',1,11)
LexToken(COMMA,',',1,13)
LexToken(INT,10,1,15)
LexToken(RPAREN,')',1,17)
>>> expression = 'H = if(td(A) > 10, A)'
>>> p.test(expression)
H = if(td(A) > 10, A)
LexToken(NAME,'H',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(IF,'if',1,4)
LexToken(LPAREN,'(',1,6)
LexToken(TD,'td',1,7)
LexToken(LPAREN,'(',1,9)
LexToken(NAME,'A',1,10)
LexToken(RPAREN,')',1,11)
LexToken(GREATER,'>',1,13)
LexToken(INT,10,1,15)
LexToken(COMMA,',',1,17)
LexToken(NAME,'A',1,19)
LexToken(RPAREN,')',1,20)
>>> expression = 'H = if(td(A) > 10, A, B)'
>>> p.test(expression)
H = if(td(A) > 10, A, B)
LexToken(NAME,'H',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(IF,'if',1,4)
LexToken(LPAREN,'(',1,6)
LexToken(TD,'td',1,7)
LexToken(LPAREN,'(',1,9)
LexToken(NAME,'A',1,10)
LexToken(RPAREN,')',1,11)
LexToken(GREATER,'>',1,13)
LexToken(INT,10,1,15)
LexToken(COMMA,',',1,17)
LexToken(NAME,'A',1,19)
LexToken(COMMA,',',1,20)
LexToken(NAME,'B',1,22)
LexToken(RPAREN,')',1,23)
>>> expression = 'I = if(equals,td(A) > 10 {||,equals} td(B) < 10, A)'
>>> p.test(expression)
I = if(equals,td(A) > 10 {||,equals} td(B) < 10, A)
LexToken(NAME,'I',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(IF,'if',1,4)
LexToken(LPAREN,'(',1,6)
LexToken(NAME,'equals',1,7)
LexToken(COMMA,',',1,13)
LexToken(TD,'td',1,14)
LexToken(LPAREN,'(',1,16)
LexToken(NAME,'A',1,17)
LexToken(RPAREN,')',1,18)
LexToken(GREATER,'>',1,20)
LexToken(INT,10,1,22)
LexToken(T_COMP_OPERATOR,'{||,equals}',1,25)
LexToken(TD,'td',1,37)
LexToken(LPAREN,'(',1,39)
LexToken(NAME,'B',1,40)
LexToken(RPAREN,')',1,41)
LexToken(LOWER,'<',1,43)
LexToken(INT,10,1,45)
LexToken(COMMA,',',1,47)
LexToken(NAME,'A',1,49)
LexToken(RPAREN,')',1,50)
>>> expression = 'I = if(equals,td(A) > 10 || start_day() < 10, A)'
>>> p.test(expression)
I = if(equals,td(A) > 10 || start_day() < 10, A)
LexToken(NAME,'I',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(IF,'if',1,4)
LexToken(LPAREN,'(',1,6)
LexToken(NAME,'equals',1,7)
LexToken(COMMA,',',1,13)
LexToken(TD,'td',1,14)
LexToken(LPAREN,'(',1,16)
LexToken(NAME,'A',1,17)
LexToken(RPAREN,')',1,18)
LexToken(GREATER,'>',1,20)
LexToken(INT,10,1,22)
LexToken(OR,'|',1,25)
LexToken(OR,'|',1,26)
LexToken(START_DAY,'start_day',1,28)
LexToken(LPAREN,'(',1,37)
LexToken(RPAREN,')',1,38)
LexToken(LOWER,'<',1,40)
LexToken(INT,10,1,42)
LexToken(COMMA,',',1,44)
LexToken(NAME,'A',1,46)
LexToken(RPAREN,')',1,47)
>>> expression = 'E = if({equals},td(A) >= 4 {&&,contain} td(B) == 2, C : D)'
>>> p.test(expression)
E = if({equals},td(A) >= 4 {&&,contain} td(B) == 2, C : D)
LexToken(NAME,'E',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(IF,'if',1,4)
LexToken(LPAREN,'(',1,6)
LexToken(T_REL_OPERATOR,'{equals}',1,7)
LexToken(COMMA,',',1,15)
LexToken(TD,'td',1,16)
LexToken(LPAREN,'(',1,18)
LexToken(NAME,'A',1,19)
LexToken(RPAREN,')',1,20)
LexToken(GREATER_EQUALS,'>=',1,22)
LexToken(INT,4,1,25)
LexToken(T_COMP_OPERATOR,'{&&,contain}',1,27)
LexToken(TD,'td',1,40)
LexToken(LPAREN,'(',1,42)
LexToken(NAME,'B',1,43)
LexToken(RPAREN,')',1,44)
LexToken(CEQUALS,'==',1,46)
LexToken(INT,2,1,49)
LexToken(COMMA,',',1,50)
LexToken(NAME,'C',1,52)
LexToken(T_SELECT,':',1,54)
LexToken(NAME,'D',1,56)
LexToken(RPAREN,')',1,57)
>>> expression = 'F = if({equals},A {#,equal}, B, C : D)'
>>> p.test(expression)
F = if({equals},A {#,equal}, B, C : D)
LexToken(NAME,'F',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(IF,'if',1,4)
LexToken(LPAREN,'(',1,6)
LexToken(T_REL_OPERATOR,'{equals}',1,7)
LexToken(COMMA,',',1,15)
LexToken(NAME,'A',1,16)
LexToken(T_HASH_OPERATOR,'{#,equal}',1,18)
LexToken(COMMA,',',1,27)
LexToken(NAME,'B',1,29)
LexToken(COMMA,',',1,30)
LexToken(NAME,'C',1,32)
LexToken(T_SELECT,':',1,34)
LexToken(NAME,'D',1,36)
LexToken(RPAREN,')',1,37)
>>> p = tgis.TemporalAlgebraParser()
>>> p.run = False
>>> p.debug = True
>>> expression = "D = A {!:} B {:,during} C"
>>> print(expression)
D = A {!:} B {:,during} C
>>> ret = p.parse(expression)
A* = A {!:} B
A** = A* {:,during} C
D = A**
>>> expression = "D = A {:} B {!:,during} C"
>>> print(expression)
D = A {:} B {!:,during} C
>>> ret = p.parse(expression)
A* = A {:} B
A** = A* {!:,during} C
D = A**
>>> p.run = False
>>> p.debug = False
>>> expression = "C = test1 : test2"
>>> print(expression)
C = test1 : test2
>>> ret = p.parse(expression, 'stvds')
>>> expression = 'D = buff_t(test1,"10 months")'
>>> print(expression)
D = buff_t(test1,"10 months")
>>> ret = p.parse(expression, 'stvds')
>>> expression = 'E = test2 {:,during} buff_t(test1,"1 days")'
>>> print(expression)
E = test2 {:,during} buff_t(test1,"1 days")
>>> ret = p.parse(expression, 'stvds')
>>> expression = 'F = test2 {:,equal} buff_t(test1,"1 days")'
>>> print(expression)
F = test2 {:,equal} buff_t(test1,"1 days")
>>> ret = p.parse(expression, 'stvds')
>>> p.debug = True
>>> expression = 'H = tsnap(test2 {:,during} buff_t(test1, "1 days"))'
>>> ret = p.parse(expression, 'stvds')
test1* = buff_t( test1 , " 1 days " )
test2* = test2 {:,during} test1*
test2** = tsnap( test2* )
H = test2**
>>> expression = 'H = tshift(test2 {:,during} test1, "1 days")'
>>> ret = p.parse(expression, 'stvds')
test2* = test2 {:,during} test1
test2** = tshift( test2* , " 1 days " )
H = test2**
>>> expression = 'H = tshift(H, 3)'
>>> ret = p.parse(expression, 'stvds')
H* = tshift( H , 3 )
H = H*
>>> expression = 'C = if(td(A) == 2, A)'
>>> ret = p.parse(expression, 'stvds')
td(A)
td(A) == 2
A* = if condition None then A
C = A*
>>> expression = 'C = if(td(A) == 5, A, B)'
>>> ret = p.parse(expression, 'stvds')
td(A)
td(A) == 5
A* = if condition None then A else B
C = A*
>>> expression = 'C = if(td(A) == 5 || start_date(A) > "2010-01-01", A, B)'
>>> ret = p.parse(expression, 'stvds')
td(A)
td(A) == 5
start_date A > "2010-01-01"
None || None
A* = if condition None then A else B
C = A*
>>> p = tgis.TemporalAlgebraLexer()
>>> p.build()
>>> p.debug = True
>>> expression = "D = strds(A) : stvds(B) : str3ds(C)"
>>> p.test(expression)
D = strds(A) : stvds(B) : str3ds(C)
LexToken(NAME,'D',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(STRDS,'strds',1,4)
LexToken(LPAREN,'(',1,9)
LexToken(NAME,'A',1,10)
LexToken(RPAREN,')',1,11)
LexToken(T_SELECT,':',1,13)
LexToken(STVDS,'stvds',1,15)
LexToken(LPAREN,'(',1,20)
LexToken(NAME,'B',1,21)
LexToken(RPAREN,')',1,22)
LexToken(T_SELECT,':',1,24)
LexToken(STR3DS,'str3ds',1,26)
LexToken(LPAREN,'(',1,32)
LexToken(NAME,'C',1,33)
LexToken(RPAREN,')',1,34)
>>> p = tgis.TemporalAlgebraLexer()
>>> p.build()
>>> p.debug = True
>>> expression = "R = if(A {#,during} stvds(C) == 1, A)"
>>> p.test(expression)
R = if(A {#,during} stvds(C) == 1, A)
LexToken(NAME,'R',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(IF,'if',1,4)
LexToken(LPAREN,'(',1,6)
LexToken(NAME,'A',1,7)
LexToken(T_HASH_OPERATOR,'{#,during}',1,9)
LexToken(STVDS,'stvds',1,20)
LexToken(LPAREN,'(',1,25)
LexToken(NAME,'C',1,26)
LexToken(RPAREN,')',1,27)
LexToken(CEQUALS,'==',1,29)
LexToken(INT,1,1,32)
LexToken(COMMA,',',1,33)
LexToken(NAME,'A',1,35)
LexToken(RPAREN,')',1,36)
>>> p = tgis.TemporalAlgebraLexer()
>>> p.build()
>>> p.debug = True
>>> expression = "R = if({during}, stvds(C) {#,contains} A == 2, A)"
>>> p.test(expression)
R = if({during}, stvds(C) {#,contains} A == 2, A)
LexToken(NAME,'R',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(IF,'if',1,4)
LexToken(LPAREN,'(',1,6)
LexToken(T_REL_OPERATOR,'{during}',1,7)
LexToken(COMMA,',',1,15)
LexToken(STVDS,'stvds',1,17)
LexToken(LPAREN,'(',1,22)
LexToken(NAME,'C',1,23)
LexToken(RPAREN,')',1,24)
LexToken(T_HASH_OPERATOR,'{#,contains}',1,26)
LexToken(NAME,'A',1,39)
LexToken(CEQUALS,'==',1,41)
LexToken(INT,2,1,44)
LexToken(COMMA,',',1,45)
LexToken(NAME,'A',1,47)
LexToken(RPAREN,')',1,48)
-
class
temporal.temporal_algebra.
GlobalTemporalVar
[source]¶ Bases:
object
This class handles global temporal variable conditional expressions, like start_doy() == 3. The three parts of the statement are stored separately in tfunc (START_DOY), compop (==) and value (3). But also boolean values, time differences and relation operators for comparison in if-statements can be stored in this class.
-
class
temporal.temporal_algebra.
TemporalAlgebraLexer
[source]¶ Bases:
object
Lexical analyzer for the GRASS GIS temporal algebra
-
conditional_functions
= {'buff_t': 'BUFF_T', 'if': 'IF', 'merge': 'MERGE', 'str3ds': 'STR3DS', 'strds': 'STRDS', 'stvds': 'STVDS', 'tmap': 'TMAP', 'tshift': 'TSHIFT', 'tsnap': 'TSNAP'}¶
-
datetime_functions
= {'end_date': 'END_DATE', 'end_datetime': 'END_DATETIME', 'end_time': 'END_TIME', 'start_date': 'START_DATE', 'start_datetime': 'START_DATETIME', 'start_time': 'START_TIME'}¶
-
t_AND
= '[&]'¶
-
t_CEQUALS
= '=='¶
-
t_COMMA
= ','¶
-
t_DATETIME
(t)[source]¶ “dddd-(0[1-9]|1[012])-(0[1-9]|[12][0-9]|3[01])[ T](0[0-9]|1(0-9)|2[0-4]):(0[0-9]|[1-5][0-9]|60):(0[0-9]|[1-5][0-9]|60)”
-
t_EQUALS
= '='¶
-
t_GREATER
= '>'¶
-
t_GREATER_EQUALS
= '>='¶
-
t_HASH
= '\\#'¶
-
t_LOWER
= '<'¶
-
t_LOWER_EQUALS
= '<='¶
-
t_LPAREN
= '\\('¶
-
t_OR
= '[\\|]'¶
-
t_QUOTE
= '[\\"\\\']'¶
-
t_RPAREN
= '\\)'¶
-
t_T_COMP_OPERATOR
= '\\{(\\|\\||&&)[,][a-zA-Z\\| ]*[,]?[\\|&]?([,])?([lrudi]|left|right|union|disjoint|intersect)?\\}'¶
-
t_T_HASH_OPERATOR
= '\\{[#][,]?[a-zA-Z\\| ]*([,])?([lrudi]|left|right|union|disjoint|intersect)?\\}'¶
-
t_T_NOT_SELECT
= '!:'¶
-
t_T_REL_OPERATOR
= '\\{([a-zA-Z\\| ])+\\}'¶
-
t_T_SELECT
= ':'¶
-
t_T_SELECT_OPERATOR
= '\\{[!]?[:][,]?[a-zA-Z\\| ]*([,])?([lrudi]|left|right|union|disjoint|intersect)?\\}'¶
-
t_UNEQUALS
= '!='¶
-
t_ignore
= ' \t\n'¶
-
time_functions
= {'end_day': 'END_DAY', 'end_dow': 'END_DOW', 'end_doy': 'END_DOY', 'end_hour': 'END_HOUR', 'end_minute': 'END_MINUTE', 'end_month': 'END_MONTH', 'end_second': 'END_SECOND', 'end_week': 'END_WEEK', 'end_year': 'END_YEAR', 'start_day': 'START_DAY', 'start_dow': 'START_DOW', 'start_doy': 'START_DOY', 'start_hour': 'START_HOUR', 'start_minute': 'START_MINUTE', 'start_month': 'START_MONTH', 'start_second': 'START_SECOND', 'start_week': 'START_WEEK', 'start_year': 'START_YEAR', 'td': 'TD'}¶
-
tokens
= ('DATETIME', 'TIME', 'DATE', 'INT', 'FLOAT', 'LPAREN', 'RPAREN', 'COMMA', 'CEQUALS', 'EQUALS', 'UNEQUALS', 'LOWER', 'LOWER_EQUALS', 'GREATER', 'GREATER_EQUALS', 'HASH', 'OR', 'AND', 'T_SELECT_OPERATOR', 'T_HASH_OPERATOR', 'T_COMP_OPERATOR', 'T_REL_OPERATOR', 'T_SELECT', 'T_NOT_SELECT', 'NAME', 'QUOTE', 'START_TIME', 'START_DATE', 'START_DATETIME', 'END_TIME', 'END_DATE', 'END_DATETIME', 'TD', 'START_DOY', 'START_DOW', 'START_YEAR', 'START_MONTH', 'START_WEEK', 'START_DAY', 'START_HOUR', 'START_MINUTE', 'START_SECOND', 'END_DOY', 'END_DOW', 'END_YEAR', 'END_MONTH', 'END_WEEK', 'END_DAY', 'END_HOUR', 'END_MINUTE', 'END_SECOND', 'IF', 'BUFF_T', 'TSNAP', 'TSHIFT', 'TMAP', 'MERGE', 'STRDS', 'STR3DS', 'STVDS')¶
-
-
class
temporal.temporal_algebra.
TemporalAlgebraParser
(pid=None, run=True, debug=False, spatial=False, register_null=False, dry_run=False, nprocs=1, time_suffix=None)[source]¶ Bases:
object
The temporal algebra class
-
assign_bool_value
(map_i, temporal_topo_list=['EQUAL'], spatial_topo_list=[])[source]¶ Function to assign boolean map value based on the map_values from the compared map list by topological relationships.
param map_i: Map object with temporal extent. param temporal_topo_list: List of strings for given temporal relations. param spatial_topo_list: List of strings for given spatial relations. return: Map object with conditional value that has been assigned by relation maps that fulfil the topological relationships to maplistB specified in temporal_topo_list.
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build_condition_list
(tvarexpr, thenlist, topolist=['EQUAL'])[source]¶ This function evaluates temporal variable expressions of a conditional expression in two steps. At first it combines stepwise the single conditions by their relations with LALR. In this process sub condition map lists will be created which will include information of the underlying single conditions. Important: The temporal relations between conditions are evaluated by implicit aggregation. In the second step the aggregated condition map list will be compared with the map list of conclusion statements by the given temporal relation.
The result is written as ‘condition_value’ attribute to the resulting map objects. These attribute consists of boolean expressions and operators which can be evaluated with the eval_condition_list function. [True, ‘||’, False, ‘&&’, True]
- For example: td(A) == 1 && start_day() > 5 –> [True || False]
- (for one map.condition_value in a then map list)
Parameters: - tvarexpr – List of GlobalTemporalVar objects and map lists. The list is constructed by the TemporalAlgebraParser in order of expression evaluation in the parser.
- thenlist – Map list object of the conclusion statement. It will be compared and evaluated by the conditions.
- topolist – List of temporal relations between the conditions and the conclusions.
Returns: Map list with conditional values for all temporal expressions.
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build_spatio_temporal_topology_list
(maplistA, maplistB=None, topolist=['EQUAL'], assign_val=False, count_map=False, compare_bool=False, compop=None, aggregate=None)[source]¶ Build spatio-temporal topology for two space time data sets, copy map objects for given relation into map list.
Parameters: - maplistA – List of maps.
- maplistB – List of maps.
- topolist – List of strings of spatio-temporal relations.
- assign_val – Boolean for assigning a boolean map value based on the map_values from the compared map list by topological relationships.
- count_map – Boolean if the number of topological related maps should be returned.
- compare_bool – Boolean for comparing boolean map values based on related map list and comparison operator.
- compop – Comparison operator, && or ||.
- aggregate – Aggregation operator for relation map list, & or |.
Returns: List of maps from maplistA that fulfil the topological relationships to maplistB specified in topolist.
# Example with two lists of maps >>> import grass.temporal as tgis >>> tgis.init(True) >>> l = tgis.TemporalAlgebraParser() >>> # Create two list of maps with equal time stamps >>> mapsA = [] >>> mapsB = [] >>> for i in range(10): ... idA = "a%i@B"%(i) ... mapA = tgis.RasterDataset(idA) ... mapA.uid = idA ... idB = "b%i@B"%(i) ... mapB = tgis.RasterDataset(idB) ... mapB.uid = idB ... check = mapA.set_relative_time(i, i + 1, "months") ... check = mapB.set_relative_time(i, i + 1, "months") ... mapsA.append(mapA) ... mapsB.append(mapB) >>> resultlist = l.build_spatio_temporal_topology_list(mapsA, mapsB, ['EQUAL']) >>> for map in resultlist: ... if map.get_equal(): ... relations = map.get_equal() ... print("Map %s has equal relation to map %s"%(map.get_name(), ... relations[0].get_name())) Map a0 has equal relation to map b0 Map a1 has equal relation to map b1 Map a2 has equal relation to map b2 Map a3 has equal relation to map b3 Map a4 has equal relation to map b4 Map a5 has equal relation to map b5 Map a6 has equal relation to map b6 Map a7 has equal relation to map b7 Map a8 has equal relation to map b8 Map a9 has equal relation to map b9 >>> resultlist = l.build_spatio_temporal_topology_list(mapsA, mapsB, ['DURING']) >>> print(resultlist) [] >>> # Create two list of maps with equal time stamps >>> mapsA = [] >>> mapsB = [] >>> for i in range(10): ... idA = "a%i@B"%(i) ... mapA = tgis.RasterDataset(idA) ... mapA.uid = idA ... idB = "b%i@B"%(i) ... mapB = tgis.RasterDataset(idB) ... mapB.uid = idB ... check = mapA.set_relative_time(i, i + 1, "months") ... check = mapB.set_relative_time(i, i + 2, "months") ... mapsA.append(mapA) ... mapsB.append(mapB) >>> resultlist = l.build_spatio_temporal_topology_list(mapsA, mapsB, ['starts','during']) >>> for map in resultlist: ... if map.get_starts(): ... relations = map.get_starts() ... print("Map %s has start relation to map %s"%(map.get_name(), ... relations[0].get_name())) Map a0 has start relation to map b0 Map a1 has start relation to map b1 Map a2 has start relation to map b2 Map a3 has start relation to map b3 Map a4 has start relation to map b4 Map a5 has start relation to map b5 Map a6 has start relation to map b6 Map a7 has start relation to map b7 Map a8 has start relation to map b8 Map a9 has start relation to map b9 >>> for map in resultlist: ... if map.get_during(): ... relations = map.get_during() ... print("Map %s has during relation to map %s"%(map.get_name(), ... relations[0].get_name())) Map a0 has during relation to map b0 Map a1 has during relation to map b0 Map a2 has during relation to map b1 Map a3 has during relation to map b2 Map a4 has during relation to map b3 Map a5 has during relation to map b4 Map a6 has during relation to map b5 Map a7 has during relation to map b6 Map a8 has during relation to map b7 Map a9 has during relation to map b8 >>> # Create two list of maps with equal time stamps and map_value method. >>> mapsA = [] >>> mapsB = [] >>> for i in range(10): ... idA = "a%i@B"%(i) ... mapA = tgis.RasterDataset(idA) ... mapA.uid = idA ... idB = "b%i@B"%(i) ... mapB = tgis.RasterDataset(idB) ... mapB.uid = idB ... check = mapA.set_relative_time(i, i + 1, "months") ... check = mapB.set_relative_time(i, i + 1, "months") ... mapB.map_value = True ... mapsA.append(mapA) ... mapsB.append(mapB) >>> # Create two list of maps with equal time stamps >>> mapsA = [] >>> mapsB = [] >>> for i in range(10): ... idA = "a%i@B"%(i) ... mapA = tgis.RasterDataset(idA) ... mapA.uid = idA ... mapA.map_value = True ... idB = "b%i@B"%(i) ... mapB = tgis.RasterDataset(idB) ... mapB.uid = idB ... mapB.map_value = False ... check = mapA.set_absolute_time(datetime(2000,1,i+1), ... datetime(2000,1,i + 2)) ... check = mapB.set_absolute_time(datetime(2000,1,i+6), ... datetime(2000,1,i + 7)) ... mapsA.append(mapA) ... mapsB.append(mapB) >>> resultlist = l.build_spatio_temporal_topology_list(mapsA, mapsB) >>> for map in resultlist: ... print(map.get_id()) a5@B a6@B a7@B a8@B a9@B >>> resultlist = l.build_spatio_temporal_topology_list(mapsA, mapsB, ['during']) >>> for map in resultlist: ... print(map.get_id())
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check_stds
(input, clear=False, stds_type=None, check_type=True)[source]¶ Check if input space time dataset exist in database and return its map list.
Parameters: - input – Name of space time data set as string or list of maps.
- clear – Reset the stored conditional values to empty list.
- check_type – Check the type of the space time dataset to match the global stds type
- stds_type – The type of the space time dataset to be opened, if not provided then self.stdstype will be used
Returns: List of maps.
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compare_bool_value
(map_i, compop, aggregate, temporal_topo_list=['EQUAL'], spatial_topo_list=[])[source]¶ - Function to evaluate two map lists with boolean values by boolean
- comparison operator.
Parameters: - map_i – Map object with temporal extent.
- compop – Comparison operator, && or ||.
- aggregate – Aggregation operator for relation map list, & or |.
- temporal_topo_list – List of strings for given temporal relations.
- spatial_topo_list – List of strings for given spatial relations.
Returns: Map object with conditional value that has been evaluated by comparison operators.
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eval_condition_list
(maplist, inverse=False)[source]¶ This function evaluates conditional values of a map list. A recursive function is used to evaluate comparison statements from left to right in the given conditional list.
For example:
- [True, '||', False, '&&', True] -> True - [True, '||', False, '&&', False] -> False - [True, '&&', False, '&&', True] -> False - [False, '||', True, '||', False] -> True - [False, '&&', True, '&&', True] -> False - [True, '&&', True, '&&', True] -> True - [True, '&&', True] -> True - [True, '&&', False] -> False - [False, '||', True] -> True
Parameters: tvarexpr – List of GlobalTemporalVar objects and map lists. The list is constructed by the TemporalAlgebraParser in order of expression evaluation in the parser. Returns: Map list with conditional values for all temporal expressions.
-
eval_global_var
(gvar, maplist)[source]¶ - This function evaluates a global variable expression for a map list.
- For example: start_day() > 5 , end_month() == 2.
Parameters: - gvar – Object of type GlobalTemporalVar containing temporal.
- maplist – List of map objects.
Returns: List of maps from maplist with added conditional boolean values.
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eval_map_list
(maplist, thenlist, topolist=['EQUAL'])[source]¶ - This function transfers boolean values from temporal expression
- from one map list to another by their topology. These boolean values are added to the maps as condition_value.
Parameters: - maplist – List of map objects containing boolean map values.
- thenlist – List of map objects where the boolean values should be added.
Returns: List of maps from thenlist with added conditional boolean values.
-
eval_toperator
(operator, optype='relation')[source]¶ This function evaluates a string containing temporal operations.
param operator: String of temporal operations, e.g. {!=,equal|during,l}. param optype: String to define operator type. - :return :List of temporal relations (equal, during), the given function
- (!:) and the interval/instances (l).
>>> import grass.temporal as tgis >>> tgis.init() >>> p = tgis.TemporalOperatorParser() >>> operator = "{+, during}" >>> p.parse(operator, optype = 'raster') >>> print((p.relations, p.temporal, p.function)) (['during'], 'l', '+')
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generate_map_name
()[source]¶ Generate an unique map name and register it in the objects map list
The map names are unique between processes. Do not use the same object for map name generation in multiple threads.
-
generate_new_map
(base_map, bool_op='and', copy=True, rename=True, remove=False)[source]¶ Generate a new map using the spatio-temporal extent of the base map
Parameters: - base_map – This map is used to create the new map
- bool_op – The boolean operator specifying the spatial extent operation (intersection, union, disjoint union)
- copy – Specifies if the temporal extent of mapB should be copied to mapA
- rename –
- Specifies if the generated map get a random name or get
- the id from the base map.
param remove: Set this True if this map is an intermediate or empty map that should be removed
Returns: Map object
-
get_temporal_func_dict
(map)[source]¶ - This function creates a dictionary containing temporal functions for a
- map dataset with time stamp.
Parameters: map – Map object with time stamps. Returns: Dictionary with temporal functions for given input map. >>> import grass.temporal as tgis >>> import datetime >>> tgis.init() >>> l = tgis.TemporalAlgebraParser() >>> # Example with one list of maps >>> # Create one list of maps with equal time stamps >>> for i in range(1): ... idA = "a%i@B"%(i) ... mapA = tgis.RasterDataset(idA) ... mapA.uid = idA ... check = mapA.set_absolute_time(datetime.datetime(2000,1,1), ... datetime.datetime(2000,10,1)) ... tfuncdict = l.get_temporal_func_dict(mapA) >>> print(tfuncdict["START_YEAR"]) 2000 >>> print(tfuncdict["START_TIME"]) 00:00:00 >>> print(tfuncdict["START_DATE"]) 2000-01-01 >>> print(tfuncdict["START_DATETIME"]) 2000-01-01 00:00:00
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overlay_map_extent
(mapA, mapB, bool_op=None, temp_op='l', copy=False)[source]¶ Compute the spatio-temporal extent of two topological related maps
Parameters: - mapA – The first map
- mapB – The second maps
- bool_op – The boolean operator specifying the spatial extent operation (intersection, union, disjoint union)
- temp_op – The temporal operator specifying the temporal extent operation (intersection, union, disjoint union, right reference) Left reference is the default temporal extent behaviour.
- copy – Specifies if the temporal extent of mapB should be copied to mapA
Returns: 0 if there is no overlay
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p_expr_condition_elif
(t)[source]¶ - expr : IF LPAREN t_var_expr COMMA stds COMMA stds RPAREN
- IF LPAREN t_var_expr COMMA stds COMMA expr RPARENIF LPAREN t_var_expr COMMA expr COMMA stds RPARENIF LPAREN t_var_expr COMMA expr COMMA expr RPAREN
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p_expr_condition_elif_relation
(t)[source]¶ - expr : IF LPAREN T_REL_OPERATOR COMMA t_var_expr COMMA stds COMMA stds RPAREN
- IF LPAREN T_REL_OPERATOR COMMA t_var_expr COMMA stds COMMA expr RPARENIF LPAREN T_REL_OPERATOR COMMA t_var_expr COMMA expr COMMA stds RPARENIF LPAREN T_REL_OPERATOR COMMA t_var_expr COMMA expr COMMA expr RPAREN
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p_expr_condition_if
(t)[source]¶ - expr : IF LPAREN t_var_expr COMMA stds RPAREN
- IF LPAREN t_var_expr COMMA expr RPAREN
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p_expr_condition_if_relation
(t)[source]¶ - expr : IF LPAREN T_REL_OPERATOR COMMA t_var_expr COMMA stds RPAREN
- IF LPAREN T_REL_OPERATOR COMMA t_var_expr COMMA expr RPAREN
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p_expr_t_buff
(t)[source]¶ - expr : BUFF_T LPAREN stds COMMA QUOTE number NAME QUOTE RPAREN
- BUFF_T LPAREN expr COMMA QUOTE number NAME QUOTE RPARENBUFF_T LPAREN stds COMMA number RPARENBUFF_T LPAREN expr COMMA number RPAREN
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p_expr_t_not_select
(t)[source]¶ - expr : stds T_NOT_SELECT stds
- expr T_NOT_SELECT stdsstds T_NOT_SELECT exprexpr T_NOT_SELECT expr
-
p_expr_t_select
(t)[source]¶ - expr : stds T_SELECT stds
- expr T_SELECT stdsstds T_SELECT exprexpr T_SELECT expr
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p_expr_t_select_operator
(t)[source]¶ - expr : stds T_SELECT_OPERATOR stds
- expr T_SELECT_OPERATOR stdsstds T_SELECT_OPERATOR exprexpr T_SELECT_OPERATOR expr
-
p_expr_t_shift
(t)[source]¶ - expr : TSHIFT LPAREN stds COMMA QUOTE number NAME QUOTE RPAREN
- TSHIFT LPAREN expr COMMA QUOTE number NAME QUOTE RPARENTSHIFT LPAREN stds COMMA number RPARENTSHIFT LPAREN expr COMMA number RPAREN
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p_expr_tmerge_function
(t)[source]¶ - expr : MERGE LPAREN stds COMMA stds RPAREN
- MERGE LPAREN expr COMMA stds RPARENMERGE LPAREN stds COMMA expr RPARENMERGE LPAREN expr COMMA expr RPAREN
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p_t_hash2
(t)[source]¶ - t_hash_var : stds T_HASH_OPERATOR stds
- stds T_HASH_OPERATOR exprexpr T_HASH_OPERATOR stdsexpr T_HASH_OPERATOR expr
-
p_t_time_var
(t)[source]¶ - t_var : START_DOY
- START_DOWSTART_YEARSTART_MONTHSTART_WEEKSTART_DAYSTART_HOURSTART_MINUTESTART_SECONDEND_DOYEND_DOWEND_YEAREND_MONTHEND_WEEKEND_DAYEND_HOUREND_MINUTEEND_SECOND
-
p_t_var_expr_comp
(t)[source]¶ - t_var_expr : t_var_expr AND AND t_var_expr
- t_var_expr OR OR t_var_expr
-
p_t_var_expr_number
(t)[source]¶ - t_var_expr : t_var LPAREN stds RPAREN comp_op number
- t_var LPAREN expr RPAREN comp_op number
-
p_t_var_expr_time
(t)[source]¶ - t_var_expr : START_TIME LPAREN stds RPAREN comp_op TIME
- START_DATE LPAREN stds RPAREN comp_op DATESTART_DATETIME LPAREN stds RPAREN comp_op DATETIMEEND_TIME LPAREN stds RPAREN comp_op TIMEEND_DATE LPAREN stds RPAREN comp_op DATEEND_DATETIME LPAREN stds RPAREN comp_op DATETIMESTART_TIME LPAREN expr RPAREN comp_op TIMESTART_DATE LPAREN expr RPAREN comp_op DATESTART_DATETIME LPAREN expr RPAREN comp_op DATETIMEEND_TIME LPAREN expr RPAREN comp_op TIMEEND_DATE LPAREN expr RPAREN comp_op DATEEND_DATETIME LPAREN expr RPAREN comp_op DATETIME
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parse
(expression, stdstype='strds', maptype='rast', mapclass=<class 'temporal.space_time_datasets.RasterDataset'>, basename=None, overwrite=False)[source]¶ Parse the algebra expression and run the computation
Parameters: - expression –
- stdstype –
- maptype –
- mapclass –
- basename –
- overwrite –
Returns: The process chain dictionary is dry-run was enabled, None otherwise
-
perform_temporal_selection
(maplistA, maplistB, topolist=['EQUAL'], inverse=False, assign_val=False)[source]¶ This function performs temporal selection operation.
Parameters: - maplistA – List of maps representing the left side of a temporal expression.
- maplistB – List of maps representing the right side of a temporal expression.
- topolist – List of strings of temporal relations.
- inverse – Boolean value that specifies if the selection should be inverted.
- assign_val – Boolean for assigning a boolean map value based on the map_values from the compared map list by topological relationships.
Returns: List of selected maps from maplistA.
>>> import grass.temporal as tgis >>> tgis.init() >>> l = tgis.TemporalAlgebraParser() >>> # Example with two lists of maps >>> # Create two list of maps with equal time stamps >>> mapsA = [] >>> mapsB = [] >>> for i in range(10): ... idA = "a%i@B"%(i) ... mapA = tgis.RasterDataset(idA) ... mapA.uid = idA ... idB = "b%i@B"%(i) ... mapB = tgis.RasterDataset(idB) ... mapB.uid = idB ... check = mapA.set_relative_time(i, i + 1, "months") ... check = mapB.set_relative_time(i + 5, i + 6, "months") ... mapsA.append(mapA) ... mapsB.append(mapB) >>> resultlist = l.perform_temporal_selection(mapsA, mapsB, ['EQUAL'], ... False) >>> for map in resultlist: ... if map.get_equal(): ... relations = map.get_equal() ... print("Map %s has equal relation to map %s"%(map.get_name(), ... relations[0].get_name())) Map a5 has equal relation to map b0 Map a6 has equal relation to map b1 Map a7 has equal relation to map b2 Map a8 has equal relation to map b3 Map a9 has equal relation to map b4 >>> resultlist = l.perform_temporal_selection(mapsA, mapsB, ['EQUAL'], ... True) >>> for map in resultlist: ... if not map.get_equal(): ... print("Map %s has no equal relation to mapset mapsB"%(map.get_name())) Map a0 has no equal relation to mapset mapsB Map a1 has no equal relation to mapset mapsB Map a2 has no equal relation to mapset mapsB Map a3 has no equal relation to mapset mapsB Map a4 has no equal relation to mapset mapsB
-
precedence
= (('left', 'T_SELECT_OPERATOR', 'T_SELECT', 'T_NOT_SELECT', 'T_HASH_OPERATOR', 'HASH'), ('left', 'AND', 'OR', 'T_COMP_OPERATOR'))¶
-
set_granularity
(maplistA, maplistB, toperator='l', topolist=['EQUAL'])[source]¶ - This function sets the temporal extends of a list of maps based on
- another map list.
Parameters: - maplistB – List of maps.
- maplistB – List of maps.
- toperator – String containing the temporal operator: l, r, d, i, u.
- topolist – List of topological relations.
Returns: List of maps with the new temporal extends.
>>> import grass.temporal as tgis >>> tgis.init() >>> p = tgis.TemporalAlgebraParser() >>> # Create two list of maps with equal time stamps >>> mapsA = [] >>> mapsB = [] >>> for i in range(10): ... idA = "a%i@B"%(i) ... mapA = tgis.RasterDataset(idA) ... mapA.uid = idA ... idB = "b%i@B"%(i) ... mapB = tgis.RasterDataset(idB) ... mapB.uid = idB ... check = mapA.set_relative_time(i, i + 1, "months") ... check = mapB.set_relative_time(i*2, i*2 + 2, "months") ... mapsA.append(mapA) ... mapsB.append(mapB) >>> resultlist = p.set_granularity(mapsA, mapsB, toperator = "u", topolist = ["during"]) >>> for map in resultlist: ... start,end,unit = map.get_relative_time() ... print(map.get_id() + ' - start: ' + str(start) + ' end: ' + str(end)) a1@B - start: 0 end: 2 a0@B - start: 0 end: 2 a3@B - start: 2 end: 4 a2@B - start: 2 end: 4 a5@B - start: 4 end: 6 a4@B - start: 4 end: 6 a7@B - start: 6 end: 8 a6@B - start: 6 end: 8 a9@B - start: 8 end: 10 a8@B - start: 8 end: 10
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set_temporal_extent_list
(maplist, topolist=['EQUAL'], temporal='l')[source]¶ - Change temporal extent of map list based on temporal relations to
- other map list and given temporal operator.
Parameters: - maplist – List of map objects for which relations has been build correctly.
- topolist – List of strings of temporal relations.
- temporal – The temporal operator specifying the temporal extent operation (intersection, union, disjoint union, right reference, left reference).
Returns: Map list with specified temporal extent.
-
setup_common_granularity
(expression, stdstype='strds', lexer=None)[source]¶ Configure the temporal algebra to use the common granularity of all space time datasets in the expression to generate the map lists.
This function will analyze the expression to detect space time datasets and computes the common granularity from all granularities of the input space time datasets.
This granularity is then be used to generate the map lists. Hence, all maps from all STDS will have equidistant temporal extents. The only meaningful temporal relation is therefore “equal”.
Parameters: - expression – The algebra expression to analyze
- lexer – The temporal algebra lexer (select, raster, voxel, vector) that should be used to parse the expression, default is TemporalAlgebraLexer
Returns: True if successful, False otherwise
-
tokens
= ('DATETIME', 'TIME', 'DATE', 'INT', 'FLOAT', 'LPAREN', 'RPAREN', 'COMMA', 'CEQUALS', 'EQUALS', 'UNEQUALS', 'LOWER', 'LOWER_EQUALS', 'GREATER', 'GREATER_EQUALS', 'HASH', 'OR', 'AND', 'T_SELECT_OPERATOR', 'T_HASH_OPERATOR', 'T_COMP_OPERATOR', 'T_REL_OPERATOR', 'T_SELECT', 'T_NOT_SELECT', 'NAME', 'QUOTE', 'START_TIME', 'START_DATE', 'START_DATETIME', 'END_TIME', 'END_DATE', 'END_DATETIME', 'TD', 'START_DOY', 'START_DOW', 'START_YEAR', 'START_MONTH', 'START_WEEK', 'START_DAY', 'START_HOUR', 'START_MINUTE', 'START_SECOND', 'END_DOY', 'END_DOW', 'END_YEAR', 'END_MONTH', 'END_WEEK', 'END_DAY', 'END_HOUR', 'END_MINUTE', 'END_SECOND', 'IF', 'BUFF_T', 'TSNAP', 'TSHIFT', 'TMAP', 'MERGE', 'STRDS', 'STR3DS', 'STVDS')¶
-
temporal.temporal_extent module¶
Temporal extent classes
Usage:
>>> import grass.temporal as tgis
>>> from datetime import datetime
>>> tgis.init()
>>> t = tgis.RasterRelativeTime()
>>> t = tgis.RasterAbsoluteTime()
(C) 2012-2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
-
class
temporal.temporal_extent.
AbsoluteTemporalExtent
(table=None, ident=None, start_time=None, end_time=None)[source]¶ Bases:
temporal.temporal_extent.TemporalExtent
This is the absolute time class for all maps and spacetime datasets
start_time and end_time must be of type datetime
-
class
temporal.temporal_extent.
Raster3DAbsoluteTime
(ident=None, start_time=None, end_time=None)[source]¶
-
class
temporal.temporal_extent.
Raster3DRelativeTime
(ident=None, start_time=None, end_time=None, unit=None)[source]¶
-
class
temporal.temporal_extent.
RasterAbsoluteTime
(ident=None, start_time=None, end_time=None)[source]¶
-
class
temporal.temporal_extent.
RasterRelativeTime
(ident=None, start_time=None, end_time=None, unit=None)[source]¶
-
class
temporal.temporal_extent.
RelativeTemporalExtent
(table=None, ident=None, start_time=None, end_time=None, unit=None)[source]¶ Bases:
temporal.temporal_extent.TemporalExtent
This is the relative time class for all maps and space time datasets
start_time and end_time must be of type integer
Usage:
>>> init() >>> A = RelativeTemporalExtent(table="raster_relative_time", ... ident="soil@PERMANENT", start_time=0, end_time=1, unit="years") >>> A.id 'soil@PERMANENT' >>> A.start_time 0 >>> A.end_time 1 >>> A.unit 'years' >>> A.print_info() +-------------------- Relative time -----------------------------------------+ | Start time:................. 0 | End time:................... 1 | Relative time unit:......... years >>> A.print_shell_info() start_time='0' end_time='1' unit=years
-
set_unit
(unit)[source]¶ Set the unit of the relative time. Valid units are:
- years
- months
- days
- hours
- minutes
- seconds
-
temporal_relation
(map)[source]¶ Returns the temporal relation between temporal objects Temporal relationships are implemented after [Allen and Ferguson 1994 Actions and Events in Interval Temporal Logic]
-
unit
¶ Get the unit of the relative time :return: None if not found
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class
temporal.temporal_extent.
STDSAbsoluteTime
(table=None, ident=None, start_time=None, end_time=None, granularity=None, map_time=None)[source]¶ Bases:
temporal.temporal_extent.AbsoluteTemporalExtent
This class implements the absolute time extent for space time dataset
In addition to the existing functionality the granularity and the map_time are added.
Usage:
>>> init() >>> A = STDSAbsoluteTime(table="strds_absolute_time", ... ident="strds@PERMANENT", start_time=datetime(2001, 01, 01), ... end_time=datetime(2005,01,01), granularity="1 days", ... map_time="interval") >>> A.id 'strds@PERMANENT' >>> A.start_time datetime.datetime(2001, 1, 1, 0, 0) >>> A.end_time datetime.datetime(2005, 1, 1, 0, 0) >>> A.granularity '1 days' >>> A.map_time 'interval' >>> A.print_info() +-------------------- Absolute time -----------------------------------------+ | Start time:................. 2001-01-01 00:00:00 | End time:................... 2005-01-01 00:00:00 | Granularity:................ 1 days | Temporal type of maps:...... interval >>> A.print_shell_info() start_time='2001-01-01 00:00:00' end_time='2005-01-01 00:00:00' granularity='1 days' map_time=interval
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get_map_time
()[source]¶ Get the type of the map time
Registered maps may have different types of time:
- Single point of time “point”
- Time intervals “interval”
- Single point and interval time “mixed”
This variable will be set automatically when maps are registered.
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granularity
¶ Get the granularity of the space time dataset :return: None if not found
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map_time
¶ Get the type of the map time
Registered maps may have different types of time:
- Single point of time “point”
- Time intervals “interval”
- Single point and interval time “mixed”
This variable will be set automatically when maps are registered.
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class
temporal.temporal_extent.
STDSRelativeTime
(table=None, ident=None, start_time=None, end_time=None, unit=None, granularity=None, map_time=None)[source]¶ Bases:
temporal.temporal_extent.RelativeTemporalExtent
This is the relative time class for all maps and space time datasets
start_time and end_time must be of type integer
Usage:
>>> init() >>> A = STDSRelativeTime(table="strds_relative_time", ... ident="strds@PERMANENT", start_time=0, end_time=1, unit="years", ... granularity=5, map_time="interval") >>> A.id 'strds@PERMANENT' >>> A.start_time 0 >>> A.end_time 1 >>> A.unit 'years' >>> A.granularity 5 >>> A.map_time 'interval' >>> A.print_info() +-------------------- Relative time -----------------------------------------+ | Start time:................. 0 | End time:................... 1 | Relative time unit:......... years | Granularity:................ 5 | Temporal type of maps:...... interval >>> A.print_shell_info() start_time='0' end_time='1' unit=years granularity=5 map_time=interval
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get_map_time
()[source]¶ Get the type of the map time
Registered maps may have different types of time:
- Single point of time “point”
- Time intervals “interval”
- Single point and interval time “mixed”
This variable will be set automatically when maps are registered.
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granularity
¶ Get the granularity of the space time dataset :return: None if not found
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map_time
¶ Get the type of the map time
Registered maps may have different types of time:
- Single point of time “point”
- Time intervals “interval”
- Single point and interval time “mixed”
This variable will be set automatically when maps are registered.
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class
temporal.temporal_extent.
STR3DSAbsoluteTime
(ident=None, start_time=None, end_time=None, granularity=None)[source]¶
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class
temporal.temporal_extent.
STR3DSRelativeTime
(ident=None, start_time=None, end_time=None, unit=None, granularity=None, map_time=None)[source]¶
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class
temporal.temporal_extent.
STRDSAbsoluteTime
(ident=None, start_time=None, end_time=None, granularity=None)[source]¶
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class
temporal.temporal_extent.
STRDSRelativeTime
(ident=None, start_time=None, end_time=None, unit=None, granularity=None, map_time=None)[source]¶
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class
temporal.temporal_extent.
STVDSAbsoluteTime
(ident=None, start_time=None, end_time=None, granularity=None)[source]¶
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class
temporal.temporal_extent.
STVDSRelativeTime
(ident=None, start_time=None, end_time=None, unit=None, granularity=None, map_time=None)[source]¶
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class
temporal.temporal_extent.
TemporalExtent
(table=None, ident=None, start_time=None, end_time=None)[source]¶ Bases:
temporal.base.SQLDatabaseInterface
This is the abstract time base class for relative and absolute time objects.
It abstract class implements the interface to absolute and relative time. Absolute time is represented by datetime time stamps, relative time is represented by a unit an integer value.
This class implements temporal topology relationships computation after [Allen and Ferguson 1994 Actions and Events in Interval Temporal Logic].
Usage:
>>> init() >>> A = TemporalExtent(table="raster_absolute_time", ... ident="soil@PERMANENT", start_time=datetime(2001, 01, 01), ... end_time=datetime(2005,01,01) ) >>> A.id 'soil@PERMANENT' >>> A.start_time datetime.datetime(2001, 1, 1, 0, 0) >>> A.end_time datetime.datetime(2005, 1, 1, 0, 0) >>> A.print_info() | Start time:................. 2001-01-01 00:00:00 | End time:................... 2005-01-01 00:00:00 >>> A.print_shell_info() start_time='2001-01-01 00:00:00' end_time='2005-01-01 00:00:00' >>> # relative time >>> A = TemporalExtent(table="raster_absolute_time", ... ident="soil@PERMANENT", start_time=0, end_time=1 ) >>> A.id 'soil@PERMANENT' >>> A.start_time 0 >>> A.end_time 1 >>> A.print_info() | Start time:................. 0 | End time:................... 1 >>> A.print_shell_info() start_time='0' end_time='1'
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adjacent
(extent)[source]¶ Return True if this temporal extent (A) is a meeting neighbor the provided temporal extent (B)
A |---------| B |---------| A |---------| B |---------|
Parameters: extent – The temporal extent object that is a meeting neighbor of this extent Usage:
>>> A = TemporalExtent(start_time=5, end_time=7 ) >>> B = TemporalExtent(start_time=7, end_time=9 ) >>> A.adjacent(B) True >>> B.adjacent(A) True >>> A = TemporalExtent(start_time=5, end_time=7 ) >>> B = TemporalExtent(start_time=3, end_time=5 ) >>> A.adjacent(B) True >>> B.adjacent(A) True
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after
(extent)[source]¶ Return True if this temporal extent (A) is located after the provided temporal extent (B)
A |---------| B |---------|
Parameters: extent – The temporal extent object that is located before this extent Usage:
>>> A = TemporalExtent(start_time=8, end_time=9 ) >>> B = TemporalExtent(start_time=6, end_time=7 ) >>> A.after(B) True >>> B.after(A) False
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before
(extent)[source]¶ Return True if this temporal extent (A) is located before the provided temporal extent (B)
A |---------| B |---------|
Parameters: extent – The temporal extent object that is located after this extent Usage:
>>> A = TemporalExtent(start_time=6, end_time=7 ) >>> B = TemporalExtent(start_time=8, end_time=9 ) >>> A.before(B) True >>> B.before(A) False
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contains
(extent)[source]¶ Return True if this temporal extent (A) contains the provided temporal extent (B)
A |---------| B |-------|
Parameters: extent – The temporal extent object that is located during this extent Usage:
>>> A = TemporalExtent(start_time=4, end_time=9 ) >>> B = TemporalExtent(start_time=5, end_time=8 ) >>> A.contains(B) True >>> B.contains(A) False
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disjoint_union
(extent)[source]¶ Creates a disjoint union with this temporal extent and the provided one. Return a new temporal extent with the new start and end time.
Parameters: extent – The temporal extent to create a union with Returns: The new temporal extent with start and end time Usage:
>>> A = TemporalExtent(start_time=5, end_time=6 ) >>> inter = A.intersect(A) >>> inter.print_info() | Start time:................. 5 | End time:................... 6 >>> A = TemporalExtent(start_time=5, end_time=6 ) >>> B = TemporalExtent(start_time=5, end_time=7 ) >>> inter = A.disjoint_union(B) >>> inter.print_info() | Start time:................. 5 | End time:................... 7 >>> inter = B.disjoint_union(A) >>> inter.print_info() | Start time:................. 5 | End time:................... 7 >>> A = TemporalExtent(start_time=3, end_time=6 ) >>> B = TemporalExtent(start_time=5, end_time=7 ) >>> inter = A.disjoint_union(B) >>> inter.print_info() | Start time:................. 3 | End time:................... 7 >>> inter = B.disjoint_union(A) >>> inter.print_info() | Start time:................. 3 | End time:................... 7 >>> A = TemporalExtent(start_time=3, end_time=8 ) >>> B = TemporalExtent(start_time=5, end_time=6 ) >>> inter = A.disjoint_union(B) >>> inter.print_info() | Start time:................. 3 | End time:................... 8 >>> inter = B.disjoint_union(A) >>> inter.print_info() | Start time:................. 3 | End time:................... 8 >>> A = TemporalExtent(start_time=5, end_time=8 ) >>> B = TemporalExtent(start_time=3, end_time=6 ) >>> inter = A.disjoint_union(B) >>> inter.print_info() | Start time:................. 3 | End time:................... 8 >>> inter = B.disjoint_union(A) >>> inter.print_info() | Start time:................. 3 | End time:................... 8 >>> A = TemporalExtent(start_time=5, end_time=None ) >>> B = TemporalExtent(start_time=3, end_time=6 ) >>> inter = A.disjoint_union(B) >>> inter.print_info() | Start time:................. 3 | End time:................... 6 >>> inter = B.disjoint_union(A) >>> inter.print_info() | Start time:................. 3 | End time:................... 6 >>> A = TemporalExtent(start_time=5, end_time=8 ) >>> B = TemporalExtent(start_time=3, end_time=4 ) >>> inter = A.disjoint_union(B) >>> inter.print_info() | Start time:................. 3 | End time:................... 8 >>> inter = B.disjoint_union(A) >>> inter.print_info() | Start time:................. 3 | End time:................... 8 >>> A = TemporalExtent(start_time=5, end_time=8 ) >>> B = TemporalExtent(start_time=3, end_time=None ) >>> inter = A.disjoint_union(B) >>> inter.print_info() | Start time:................. 3 | End time:................... 8 >>> inter = B.disjoint_union(A) >>> inter.print_info() | Start time:................. 3 | End time:................... 8 >>> A = TemporalExtent(start_time=5, end_time=None ) >>> B = TemporalExtent(start_time=3, end_time=8 ) >>> inter = A.disjoint_union(B) >>> inter.print_info() | Start time:................. 3 | End time:................... 8 >>> inter = B.disjoint_union(A) >>> inter.print_info() | Start time:................. 3 | End time:................... 8 >>> A = TemporalExtent(start_time=5, end_time=None ) >>> B = TemporalExtent(start_time=3, end_time=None ) >>> inter = A.disjoint_union(B) >>> inter.print_info() | Start time:................. 3 | End time:................... 5 >>> inter = B.disjoint_union(A) >>> inter.print_info() | Start time:................. 3 | End time:................... 5 >>> A = RelativeTemporalExtent(start_time=5, end_time=None, unit="years" ) >>> B = RelativeTemporalExtent(start_time=3, end_time=None, unit="years" ) >>> inter = A.disjoint_union(B) >>> inter.print_info() +-------------------- Relative time -----------------------------------------+ | Start time:................. 3 | End time:................... 5 | Relative time unit:......... years >>> inter = B.disjoint_union(A) >>> inter.print_info() +-------------------- Relative time -----------------------------------------+ | Start time:................. 3 | End time:................... 5 | Relative time unit:......... years >>> from datetime import datetime as dt >>> A = AbsoluteTemporalExtent(start_time=dt(2001,1,10), end_time=dt(2003,1,1)) >>> B = AbsoluteTemporalExtent(start_time=dt(2005,1,10), end_time=dt(2008,1,1)) >>> inter = A.disjoint_union(B) >>> inter.print_info() +-------------------- Absolute time -----------------------------------------+ | Start time:................. 2001-01-10 00:00:00 | End time:................... 2008-01-01 00:00:00 >>> inter = B.disjoint_union(A) >>> inter.print_info() +-------------------- Absolute time -----------------------------------------+ | Start time:................. 2001-01-10 00:00:00 | End time:................... 2008-01-01 00:00:00
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during
(extent)[source]¶ Return True if this temporal extent (A) is located during the provided temporal extent (B)
A |-------| B |---------|
Parameters: extent – The temporal extent object that contains this extent Usage:
>>> A = TemporalExtent(start_time=5, end_time=7 ) >>> B = TemporalExtent(start_time=4, end_time=9 ) >>> A.during(B) True >>> B.during(A) False
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end_time
¶ Get the valid end time of the extent :return: None if not found
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equal
(extent)[source]¶ Return True if this temporal extent (A) is equal to the provided temporal extent (B)
A |---------| B |---------|
Parameters: extent – The temporal extent object that is equal during this extent Usage:
>>> A = TemporalExtent(start_time=5, end_time=6 ) >>> B = TemporalExtent(start_time=5, end_time=6 ) >>> A.equal(B) True >>> B.equal(A) True
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finished
(extent)[source]¶ Return True if this temporal extent (A) starts before the start of the provided temporal extent (B) and finishes with it
A |---------| B |-----|
Parameters: extent – The temporal extent object with which this extent finishes Usage:
>>> A = TemporalExtent(start_time=5, end_time=7 ) >>> B = TemporalExtent(start_time=6, end_time=7 ) >>> A.finished(B) True >>> B.finished(A) False
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finishes
(extent)[source]¶ Return True if this temporal extent (A) starts after the start of the provided temporal extent (B) and finishes with it
A |-----| B |---------|
Parameters: extent – The temporal extent object with which this extent finishes Usage:
>>> A = TemporalExtent(start_time=6, end_time=7 ) >>> B = TemporalExtent(start_time=5, end_time=7 ) >>> A.finishes(B) True >>> B.finishes(A) False
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follows
(extent)[source]¶ Return True if this temporal extent (A) follows the provided temporal extent (B)
A |---------| B |---------|
Parameters: extent – The temporal extent object that is the predecessor of this extent Usage:
>>> A = TemporalExtent(start_time=5, end_time=7 ) >>> B = TemporalExtent(start_time=3, end_time=5 ) >>> A.follows(B) True >>> B.follows(A) False
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get_id
()[source]¶ Convenient method to get the unique identifier (primary key) :return: None if not found
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id
¶ Convenient method to get the unique identifier (primary key) :return: None if not found
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intersect
(extent)[source]¶ Intersect this temporal extent with the provided temporal extent and return a new temporal extent with the new start and end time
Parameters: extent – The temporal extent to intersect with Returns: The new temporal extent with start and end time, or None in case of no intersection Usage:
>>> A = TemporalExtent(start_time=5, end_time=6 ) >>> inter = A.intersect(A) >>> inter.print_info() | Start time:................. 5 | End time:................... 6 >>> A = TemporalExtent(start_time=5, end_time=6 ) >>> B = TemporalExtent(start_time=5, end_time=7 ) >>> inter = A.intersect(B) >>> inter.print_info() | Start time:................. 5 | End time:................... 6 >>> inter = B.intersect(A) >>> inter.print_info() | Start time:................. 5 | End time:................... 6 >>> A = TemporalExtent(start_time=3, end_time=6 ) >>> B = TemporalExtent(start_time=5, end_time=7 ) >>> inter = A.intersect(B) >>> inter.print_info() | Start time:................. 5 | End time:................... 6 >>> inter = B.intersect(A) >>> inter.print_info() | Start time:................. 5 | End time:................... 6 >>> A = TemporalExtent(start_time=3, end_time=8 ) >>> B = TemporalExtent(start_time=5, end_time=6 ) >>> inter = A.intersect(B) >>> inter.print_info() | Start time:................. 5 | End time:................... 6 >>> inter = B.intersect(A) >>> inter.print_info() | Start time:................. 5 | End time:................... 6 >>> A = TemporalExtent(start_time=5, end_time=8 ) >>> B = TemporalExtent(start_time=3, end_time=6 ) >>> inter = A.intersect(B) >>> inter.print_info() | Start time:................. 5 | End time:................... 6 >>> inter = B.intersect(A) >>> inter.print_info() | Start time:................. 5 | End time:................... 6 >>> A = TemporalExtent(start_time=5, end_time=None ) >>> B = TemporalExtent(start_time=3, end_time=6 ) >>> inter = A.intersect(B) >>> inter.print_info() | Start time:................. 5 | End time:................... None >>> inter = B.intersect(A) >>> inter.print_info() | Start time:................. 5 | End time:................... None >>> A = TemporalExtent(start_time=5, end_time=8 ) >>> B = TemporalExtent(start_time=3, end_time=4 ) >>> inter = A.intersect(B) >>> print(inter) None >>> A = TemporalExtent(start_time=5, end_time=8 ) >>> B = TemporalExtent(start_time=3, end_time=None ) >>> inter = A.intersect(B) >>> print(inter) None
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overlapped
(extent)[source]¶ Return True if this temporal extent (A) overlapps the provided temporal extent (B)
A |---------| B |---------|
Parameters: extent – The temporal extent object that is overlapped this extent Usage:
>>> A = TemporalExtent(start_time=6, end_time=8 ) >>> B = TemporalExtent(start_time=5, end_time=7 ) >>> A.overlapped(B) True >>> B.overlapped(A) False >>> A = TemporalExtent(start_time=6, end_time=8 ) >>> B = TemporalExtent(start_time=5, end_time=6 ) >>> A.overlapped(B) False >>> B.overlapped(A) False
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overlaps
(extent)[source]¶ Return True if this temporal extent (A) overlapped the provided temporal extent (B)
A |---------| B |---------|
Parameters: extent – The temporal extent object that is overlaps this extent Usage:
>>> A = TemporalExtent(start_time=5, end_time=7 ) >>> B = TemporalExtent(start_time=6, end_time=8 ) >>> A.overlaps(B) True >>> B.overlaps(A) False >>> A = TemporalExtent(start_time=5, end_time=6 ) >>> B = TemporalExtent(start_time=6, end_time=8 ) >>> A.overlaps(B) False >>> B.overlaps(A) False
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precedes
(extent)[source]¶ Return True if this temporal extent (A) precedes the provided temporal extent (B)
A |---------| B |---------|
Parameters: extent – The temporal extent object that is the successor of this extent Usage:
>>> A = TemporalExtent(start_time=5, end_time=7 ) >>> B = TemporalExtent(start_time=7, end_time=9 ) >>> A.precedes(B) True >>> B.precedes(A) False
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start_time
¶ Get the valid start time of the extent :return: None if not found
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started
(extent)[source]¶ Return True if this temporal extent (A) started at the start of the provided temporal extent (B) and finishes after it
A |---------| B |-----|
Parameters: extent – The temporal extent object with which this extent started Usage:
>>> A = TemporalExtent(start_time=5, end_time=7 ) >>> B = TemporalExtent(start_time=5, end_time=6 ) >>> A.started(B) True >>> B.started(A) False
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starts
(extent)[source]¶ Return True if this temporal extent (A) starts at the start of the provided temporal extent (B) and finishes within it
A |-----| B |---------|
Parameters: extent – The temporal extent object with which this extent starts Usage:
>>> A = TemporalExtent(start_time=5, end_time=6 ) >>> B = TemporalExtent(start_time=5, end_time=7 ) >>> A.starts(B) True >>> B.starts(A) False
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temporal_relation
(extent)[source]¶ Returns the temporal relation between temporal objects Temporal relationships are implemented after [Allen and Ferguson 1994 Actions and Events in Interval Temporal Logic]
The following temporal relationships are supported:
- equal
- during
- contains
- overlaps
- overlapped
- after
- before
- starts
- finishes
- started
- finished
- follows
- precedes
Parameters: extent – The temporal extent Returns: The name of the temporal relation or None if no relation found
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union
(extent)[source]¶ Creates a union with this temporal extent and the provided one. Return a new temporal extent with the new start and end time.
Parameters: extent – The temporal extent to create a union with Returns: The new temporal extent with start and end time, or None in case the temporal extents are unrelated (before or after) >>> A = TemporalExtent(start_time=5, end_time=8 ) >>> B = TemporalExtent(start_time=3, end_time=4 ) >>> inter = A.intersect(B) >>> print(inter) None >>> A = TemporalExtent(start_time=5, end_time=8 ) >>> B = TemporalExtent(start_time=3, end_time=None ) >>> inter = A.intersect(B) >>> print(inter) None
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-
class
temporal.temporal_extent.
VectorAbsoluteTime
(ident=None, start_time=None, end_time=None)[source]¶
temporal.temporal_granularity module¶
Functions to compute the temporal granularity of a map list
Usage:
import grass.temporal as tgis
tgis.compute_relative_time_granularity(maps)
(C) 2012-2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
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temporal.temporal_granularity.
check_granularity_string
(granularity, temporal_type)[source]¶ Check if the granularity string is valid
Parameters: - granularity – The granularity string
- temporal_type – The temporal type of the granularity relative or absolute
Returns: True if valid, False if invalid
>>> check_granularity_string("1 year", "absolute") True >>> check_granularity_string("1 month", "absolute") True >>> check_granularity_string("1 day", "absolute") True >>> check_granularity_string("1 minute", "absolute") True >>> check_granularity_string("1 hour", "absolute") True >>> check_granularity_string("1 second", "absolute") True >>> check_granularity_string("5 months", "absolute") True >>> check_granularity_string("5 days", "absolute") True >>> check_granularity_string("5 minutes", "absolute") True >>> check_granularity_string("5 years", "absolute") True >>> check_granularity_string("5 hours", "absolute") True >>> check_granularity_string("2 seconds", "absolute") True >>> check_granularity_string("1 secondo", "absolute") False >>> check_granularity_string("bla second", "absolute") False >>> check_granularity_string("bla", "absolute") False >>> check_granularity_string(1, "relative") True >>> check_granularity_string("bla", "relative") False
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temporal.temporal_granularity.
compute_absolute_time_granularity
(maps)[source]¶ Compute the absolute time granularity
Attention: The computation of the granularity is only correct in case of not overlapping intervals. Hence a correct temporal topology is required for computation.
The computed granularity is returned as number of seconds or minutes or hours or days or months or years.
Parameters: maps – a ordered by start_time list of map objects Returns: The temporal topology as string “integer unit” >>> import grass.temporal as tgis >>> import datetime >>> dt = datetime.datetime >>> tgis.init() >>> maps = [] >>> count = 0 >>> timelist = ((dt(2000,01,01),None), (dt(2000,02,01),None)) >>> for t in timelist: ... map = tgis.RasterDataset("a%i@P"%count) ... check = map.set_absolute_time(t[0],t[1]) ... if check: ... maps.append(map) ... count += 1 >>> tgis.compute_absolute_time_granularity(maps) '1 month' >>> maps = [] >>> count = 0 >>> timelist = ((dt(2000,01,01),None), (dt(2000,01,02),None), (dt(2000,01,03),None)) >>> for t in timelist: ... map = tgis.RasterDataset("a%i@P"%count) ... check = map.set_absolute_time(t[0],t[1]) ... if check: ... maps.append(map) ... count += 1 >>> tgis.compute_absolute_time_granularity(maps) '1 day' >>> maps = [] >>> count = 0 >>> timelist = ((dt(2000,01,01),None), (dt(2000,01,02),None), (dt(2000,05,04,0,5,30),None)) >>> for t in timelist: ... map = tgis.RasterDataset("a%i@P"%count) ... check = map.set_absolute_time(t[0],t[1]) ... if check: ... maps.append(map) ... count += 1 >>> tgis.compute_absolute_time_granularity(maps) '30 seconds' >>> maps = [] >>> count = 0 >>> timelist = ((dt(2000,01,01),dt(2000,05,02)), (dt(2000,05,04,2),None)) >>> for t in timelist: ... map = tgis.RasterDataset("a%i@P"%count) ... check = map.set_absolute_time(t[0],t[1]) ... if check: ... maps.append(map) ... count += 1 >>> tgis.compute_absolute_time_granularity(maps) '2 hours' >>> maps = [] >>> count = 0 >>> timelist = ((dt(2000,01,01),dt(2000,02,01)), (dt(2005,05,04,12),dt(2007,05,20,6))) >>> for t in timelist: ... map = tgis.RasterDataset("a%i@P"%count) ... check = map.set_absolute_time(t[0],t[1]) ... if check: ... maps.append(map) ... count += 1 >>> tgis.compute_absolute_time_granularity(maps) '6 hours'
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temporal.temporal_granularity.
compute_common_absolute_time_granularity
(gran_list, start_date_list=None)[source]¶ Compute the greatest common granule from a list of absolute time granules, considering the start times of the related space time datasets in the common granularity computation.
The list of start dates is optional. If you use this function to compute a common granularity between space time datasets, then you should provide their start times to avoid wrong synchronization.
Parameters: - gran_list – List of granularities
- start_date_list – List of the start times of related space time datasets
Returns: The common granularity
>>> from datetime import datetime >>> import grass.temporal as tgis >>> tgis.init() >>> grans = ["20 second", "10 minutes", "2 hours"] >>> dates = [datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0),] >>> tgis.compute_common_absolute_time_granularity(grans, dates) '20 seconds' >>> grans = ["20 second", "10 minutes", "2 hours"] >>> dates = [datetime(2001,1,1,0,0,20), ... datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0),] >>> tgis.compute_common_absolute_time_granularity(grans, dates) '1 second' >>> grans = ["7200 second", "240 minutes", "1 year"] >>> dates = [datetime(2001,1,1,0,0,10), ... datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0),] >>> tgis.compute_common_absolute_time_granularity(grans, dates) '1 second' >>> grans = ["7200 second", "89 minutes", "1 year"] >>> dates = [datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0),] >>> tgis.compute_common_absolute_time_granularity(grans, dates) '60 seconds' >>> grans = ["120 minutes", "2 hours"] >>> dates = [datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0),] >>> tgis.compute_common_absolute_time_granularity(grans, dates) '60 minutes' >>> grans = ["120 minutes", "2 hours"] >>> dates = [datetime(2001,1,1,0,30,0), ... datetime(2001,1,1,0,0,0),] >>> tgis.compute_common_absolute_time_granularity(grans, dates) '1 minute' >>> grans = ["360 minutes", "3 hours"] >>> dates = [datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0),] >>> tgis.compute_common_absolute_time_granularity(grans, dates) '60 minutes' >>> grans = ["2 hours", "4 hours", "8 hours"] >>> dates = [datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0),] >>> tgis.compute_common_absolute_time_granularity(grans, dates) '2 hours' >>> grans = ["2 hours", "4 hours", "8 hours"] >>> dates = [datetime(2001,1,1,2,0,0), ... datetime(2001,1,1,4,0,0), ... datetime(2001,1,1,8,0,0),] >>> tgis.compute_common_absolute_time_granularity(grans, dates) '1 hour' >>> grans = ["8 hours", "2 days"] >>> dates = [datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0),] >>> tgis.compute_common_absolute_time_granularity(grans, dates) '8 hours' >>> grans = ["8 hours", "2 days"] >>> dates = [datetime(2001,1,1,10,0,0), ... datetime(2001,1,1,0,0,0),] >>> tgis.compute_common_absolute_time_granularity(grans, dates) '1 hour' >>> grans = ["120 months", "360 months", "4 years"] >>> dates = [datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0),] >>> tgis.compute_common_absolute_time_granularity(grans, dates) '12 months' >>> grans = ["30 days", "10 days", "5 days"] >>> dates = [datetime(2001,2,1,0,0,0), ... datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0),] >>> tgis.compute_common_absolute_time_granularity(grans, dates) '5 days' >>> grans = ["30 days", "10 days", "5 days"] >>> dates = [datetime(2001,2,2,0,0,0), ... datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0),] >>> tgis.compute_common_absolute_time_granularity(grans, dates) '1 day' >>> grans = ["2 days", "360 months", "4 years"] >>> dates = [datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0),] >>> tgis.compute_common_absolute_time_granularity(grans, dates) '2 days' >>> grans = ["2 days", "360 months", "4 years"] >>> dates = [datetime(2001,1,2,0,0,0), ... datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0),] >>> tgis.compute_common_absolute_time_granularity(grans, dates) '1 day' >>> grans = ["120 months", "360 months", "4 years"] >>> dates = [datetime(2001,2,1,0,0,0), ... datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0),] >>> tgis.compute_common_absolute_time_granularity(grans, dates) '1 month' >>> grans = ["120 months", "361 months", "4 years"] >>> dates = [datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0),] >>> tgis.compute_common_absolute_time_granularity(grans, dates) '1 month' >>> grans = ["120 months", "360 months", "4 years"] >>> dates = [datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0), ... datetime(2001,1,1,0,0,0),] >>> tgis.compute_common_absolute_time_granularity(grans, dates) '12 months'
-
temporal.temporal_granularity.
compute_common_absolute_time_granularity_simple
(gran_list)[source]¶ Compute the greatest common granule from a list of absolute time granules
Parameters: gran_list – List of granularities Returns: The common granularity >>> import grass.temporal as tgis >>> tgis.init() >>> grans = ["1 second", "2 seconds", "30 seconds"] >>> tgis.compute_common_absolute_time_granularity(grans) '1 second' >>> grans = ["3 second", "6 seconds", "30 seconds"] >>> tgis.compute_common_absolute_time_granularity(grans) '3 seconds' >>> grans = ["12 second", "18 seconds", "30 seconds", "10 minutes"] >>> tgis.compute_common_absolute_time_granularity(grans) '6 seconds' >>> grans = ["20 second", "10 minutes", "2 hours"] >>> tgis.compute_common_absolute_time_granularity(grans) '20 seconds' >>> grans = ["7200 second", "240 minutes", "1 year"] >>> tgis.compute_common_absolute_time_granularity(grans) '7200 seconds' >>> grans = ["7200 second", "89 minutes", "1 year"] >>> tgis.compute_common_absolute_time_granularity(grans) '60 seconds' >>> grans = ["10 minutes", "20 minutes", "30 minutes", "40 minutes", "2 hours"] >>> tgis.compute_common_absolute_time_granularity(grans) '10 minutes' >>> grans = ["120 minutes", "2 hours"] >>> tgis.compute_common_absolute_time_granularity(grans) '120 minutes' >>> grans = ["360 minutes", "3 hours"] >>> tgis.compute_common_absolute_time_granularity(grans) '180 minutes' >>> grans = ["2 hours", "4 hours", "8 hours"] >>> tgis.compute_common_absolute_time_granularity(grans) '2 hours' >>> grans = ["8 hours", "2 days"] >>> tgis.compute_common_absolute_time_granularity(grans) '8 hours' >>> grans = ["48 hours", "1 month"] >>> tgis.compute_common_absolute_time_granularity(grans) '24 hours' >>> grans = ["48 hours", "1 year"] >>> tgis.compute_common_absolute_time_granularity(grans) '24 hours' >>> grans = ["2 months", "4 months", "1 year"] >>> tgis.compute_common_absolute_time_granularity(grans) '2 months' >>> grans = ["120 months", "360 months", "4 years"] >>> tgis.compute_common_absolute_time_granularity(grans) '24 months' >>> grans = ["120 months", "361 months", "4 years"] >>> tgis.compute_common_absolute_time_granularity(grans) '1 month' >>> grans = ["2 years", "3 years", "4 years"] >>> tgis.compute_common_absolute_time_granularity(grans) '1 year'
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temporal.temporal_granularity.
compute_common_relative_time_granularity
(gran_list)[source]¶ Compute the greatest common granule from a list of relative time granules
>>> import grass.temporal as tgis >>> tgis.init() >>> grans = [1,2,30] >>> tgis.compute_common_relative_time_granularity(grans) 1 >>> import grass.temporal as tgis >>> tgis.init() >>> grans = [10,20,30] >>> tgis.compute_common_relative_time_granularity(grans) 10
-
temporal.temporal_granularity.
compute_relative_time_granularity
(maps)[source]¶ Compute the relative time granularity
Attention: The computation of the granularity is only correct in case of not overlapping intervals. Hence a correct temporal topology is required for computation.
Parameters: maps – a ordered by start_time list of map objects Returns: An integer >>> import grass.temporal as tgis >>> tgis.init() >>> maps = [] >>> for i in range(5): ... map = tgis.RasterDataset("a%i@P"%i) ... check = map.set_relative_time(i,i + 1,"seconds") ... if check: ... maps.append(map) >>> tgis.compute_relative_time_granularity(maps) 1 >>> maps = [] >>> count = 0 >>> timelist = ((0,3), (3,6), (6,9)) >>> for t in timelist: ... map = tgis.RasterDataset("a%i@P"%count) ... check = map.set_relative_time(t[0],t[1],"years") ... if check: ... maps.append(map) ... count += 1 >>> tgis.compute_relative_time_granularity(maps) 3 >>> maps = [] >>> count = 0 >>> timelist = ((0,3), (4,6), (8,11)) >>> for t in timelist: ... map = tgis.RasterDataset("a%i@P"%count) ... check = map.set_relative_time(t[0],t[1],"years") ... if check: ... maps.append(map) ... count += 1 >>> tgis.compute_relative_time_granularity(maps) 1 >>> maps = [] >>> count = 0 >>> timelist = ((0,8), (2,6), (5,9)) >>> for t in timelist: ... map = tgis.RasterDataset("a%i@P"%count) ... check = map.set_relative_time(t[0],t[1],"months") ... if check: ... maps.append(map) ... count += 1 >>> tgis.compute_relative_time_granularity(maps) 4 >>> maps = [] >>> count = 0 >>> timelist = ((0,8), (8,12), (12,18)) >>> for t in timelist: ... map = tgis.RasterDataset("a%i@P"%count) ... check = map.set_relative_time(t[0],t[1],"days") ... if check: ... maps.append(map) ... count += 1 >>> tgis.compute_relative_time_granularity(maps) 2 >>> maps = [] >>> count = 0 >>> timelist = ((0,None), (8,None), (12,None), (24,None)) >>> for t in timelist: ... map = tgis.RasterDataset("a%i@P"%count) ... check = map.set_relative_time(t[0],t[1],"minutes") ... if check: ... maps.append(map) ... count += 1 >>> tgis.compute_relative_time_granularity(maps) 4 >>> maps = [] >>> count = 0 >>> timelist = ((0,None), (8,14), (18,None), (24,None)) >>> for t in timelist: ... map = tgis.RasterDataset("a%i@P"%count) ... check = map.set_relative_time(t[0],t[1],"hours") ... if check: ... maps.append(map) ... count += 1 >>> tgis.compute_relative_time_granularity(maps) 2 >>> maps = [] >>> count = 0 >>> timelist = ((0,21),) >>> for t in timelist: ... map = tgis.RasterDataset("a%i@P"%count) ... check = map.set_relative_time(t[0],t[1],"hours") ... if check: ... maps.append(map) ... count += 1 >>> tgis.compute_relative_time_granularity(maps) 21
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temporal.temporal_granularity.
gcd_list
(list)[source]¶ Finds the GCD of numbers in a list.
Parameters: list – List of numbers you want to find the GCD of E.g. [8, 24, 12] Returns: GCD of all numbers
-
temporal.temporal_granularity.
gran_plural_unit
(gran)[source]¶ Return the absolute granularity unit in its singular term
Parameters: gran – input granularity Returns: granularity unit >>> import grass.temporal as tgis >>> tgis.init() >>> tgis.gran_singular_unit('1 month') 'month' >>> tgis.gran_singular_unit('2 months') 'month' >>> tgis.gran_singular_unit('6 seconds') 'second' >>> tgis.gran_singular_unit('1 year') 'year'
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temporal.temporal_granularity.
gran_singular_unit
(gran)[source]¶ Return the absolute granularity unit in its singular term
Parameters: gran – input granularity Returns: granularity unit >>> import grass.temporal as tgis >>> tgis.init() >>> tgis.gran_singular_unit('1 month') 'month' >>> tgis.gran_singular_unit('2 months') 'month' >>> tgis.gran_singular_unit('6 seconds') 'second' >>> tgis.gran_singular_unit('1 year') 'year'
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temporal.temporal_granularity.
gran_to_gran
(from_gran, to_gran='days', shell=False)[source]¶ Converts the computed absolute granularity of a STDS to a smaller granularity based on the Gregorian calendar hierarchy that 1 year equals 12 months or 365.2425 days or 24 * 365.2425 hours or 86400 * 365.2425 seconds.
Parameters: - from_gran – input granularity, this should be bigger than to_gran
- to_gran – output granularity
Returns: The output granularity
>>> import grass.temporal as tgis >>> tgis.init() >>> tgis.gran_to_gran('1 month', '1 day') '30.436875 days' >>> tgis.gran_to_gran('1 month', '1 day', True) 30.436875 >>> tgis.gran_to_gran('10 year', '1 hour') '87658.2 hours' >>> tgis.gran_to_gran('10 year', '1 minute') '5259492.0 minutes' >>> tgis.gran_to_gran('6 months', '1 day') '182.62125 days' >>> tgis.gran_to_gran('1 months', '1 second') '2629746.0 seconds' >>> tgis.gran_to_gran('1 month', '1 second', True) 2629746.0 >>> tgis.gran_to_gran('30 month', '1 month', True) 30
temporal.temporal_operator module¶
@package grass.temporal
Temporal operator evaluation with PLY
(C) 2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Thomas Leppelt and Soeren Gebbert |
---|
>>> p = TemporalOperatorParser()
>>> expression = "{equal|equivalent|cover|in|meet|contain|overlap}"
>>> p.parse(expression, optype = 'relation')
>>> print((p.relations, p.temporal, p.function))
(['equal', 'equivalent', 'cover', 'in', 'meet', 'contain', 'overlap'], None, None)
>>> p = TemporalOperatorParser()
>>> expression = "{equal| during}"
>>> p.parse(expression, optype = 'relation')
>>> print((p.relations, p.temporal, p.function))
(['equal', 'during'], None, None)
>>> p = TemporalOperatorParser()
>>> expression = "{contains | starts}"
>>> p.parse(expression)
>>> print((p.relations, p.temporal, p.function))
(['contains', 'starts'], None, None)
>>> p = TemporalOperatorParser()
>>> expression = "{&&, during}"
>>> p.parse(expression, optype = 'boolean')
>>> print((p.relations, p.temporal, p.function, p.aggregate))
(['during'], 'l', '&&', '&')
>>> p = TemporalOperatorParser()
>>> expression = "{||, equal | during}"
>>> p.parse(expression, optype = 'boolean')
>>> print((p.relations, p.temporal, p.function, p.aggregate))
(['equal', 'during'], 'l', '||', '|')
>>> p = TemporalOperatorParser()
>>> expression = "{||, equal | during, &}"
>>> p.parse(expression, optype = 'boolean')
>>> print((p.relations, p.temporal, p.function, p.aggregate))
(['equal', 'during'], 'l', '||', '&')
>>> p = TemporalOperatorParser()
>>> expression = "{&&, during, |}"
>>> p.parse(expression, optype = 'boolean')
>>> print((p.relations, p.temporal, p.function, p.aggregate))
(['during'], 'l', '&&', '|')
>>> p = TemporalOperatorParser()
>>> expression = "{&&, during, |, r}"
>>> p.parse(expression, optype = 'boolean')
>>> print((p.relations, p.temporal, p.function, p.aggregate))
(['during'], 'r', '&&', '|')
>>> p = TemporalOperatorParser()
>>> expression = "{&&, during, u}"
>>> p.parse(expression, optype = 'boolean')
>>> print((p.relations, p.temporal, p.function, p.aggregate))
(['during'], 'u', '&&', '&')
>>> p = TemporalOperatorParser()
>>> expression = "{:, during, r}"
>>> p.parse(expression, optype = 'select')
>>> print((p.relations, p.temporal, p.function))
(['during'], 'r', ':')
>>> p = TemporalOperatorParser()
>>> expression = "{!:, equal | contains, d}"
>>> p.parse(expression, optype = 'select')
>>> print((p.relations, p.temporal, p.function))
(['equal', 'contains'], 'd', '!:')
>>> p = TemporalOperatorParser()
>>> expression = "{#, during, r}"
>>> p.parse(expression, optype = 'hash')
>>> print((p.relations, p.temporal, p.function))
(['during'], 'r', '#')
>>> p = TemporalOperatorParser()
>>> expression = "{#, equal | contains}"
>>> p.parse(expression, optype = 'hash')
>>> print((p.relations, p.temporal, p.function))
(['equal', 'contains'], 'l', '#')
>>> p = TemporalOperatorParser()
>>> expression = "{+, during, r}"
>>> p.parse(expression, optype = 'raster')
>>> print((p.relations, p.temporal, p.function))
(['during'], 'r', '+')
>>> p = TemporalOperatorParser()
>>> expression = "{/, equal | contains}"
>>> p.parse(expression, optype = 'raster')
>>> print((p.relations, p.temporal, p.function))
(['equal', 'contains'], 'l', '/')
>>> p = TemporalOperatorParser()
>>> expression = "{+, equal | contains,intersect}"
>>> p.parse(expression, optype = 'raster')
>>> print((p.relations, p.temporal, p.function))
(['equal', 'contains'], 'i', '+')
>>> p = TemporalOperatorParser()
>>> expression = "{*, contains,disjoint}"
>>> p.parse(expression, optype = 'raster')
>>> print((p.relations, p.temporal, p.function))
(['contains'], 'd', '*')
>>> p = TemporalOperatorParser()
>>> expression = "{~, equal,left}"
>>> p.parse(expression, optype = 'overlay')
>>> print((p.relations, p.temporal, p.function))
(['equal'], 'l', '~')
>>> p = TemporalOperatorParser()
>>> expression = "{^, over,right}"
>>> p.parse(expression, optype = 'overlay')
>>> print((p.relations, p.temporal, p.function))
(['overlaps', 'overlapped'], 'r', '^')
>>> p = TemporalOperatorParser()
>>> expression = "{&&, equal | during | contains | starts, &}"
>>> p.parse(expression, optype = 'boolean')
>>> print((p.relations, p.temporal, p.function, p.aggregate))
(['equal', 'during', 'contains', 'starts'], 'l', '&&', '&')
>>> p = TemporalOperatorParser()
>>> expression = "{&&, equal | during | contains | starts, &&&&&}"
>>> p.parse(expression, optype = 'boolean')
Traceback (most recent call last):
SyntaxError: Unexpected syntax error in expression "{&&, equal | during | contains | starts, &&&&&}" at position 42 near &
>>> p = TemporalOperatorParser()
>>> expression = "{+, starting}"
>>> p.parse(expression)
Traceback (most recent call last):
SyntaxError: syntax error on line 1 position 4 near 'starting'
>>> p = TemporalOperatorParser()
>>> expression = "{nope, start, |, l}"
>>> p.parse(expression)
Traceback (most recent call last):
SyntaxError: syntax error on line 1 position 1 near 'nope'
>>> p = TemporalOperatorParser()
>>> expression = "{++, start, |, l}"
>>> p.parse(expression)
Traceback (most recent call last):
SyntaxError: Unexpected syntax error in expression "{++, start, |, l}" at position 2 near +
>>> p = TemporalOperatorParser()
>>> expression = "{^, over, right}"
>>> p.parse(expression, optype='rter')
Traceback (most recent call last):
SyntaxError: Unknown optype rter, must be one of ['select', 'boolean', 'raster', 'hash', 'relation', 'overlay']
-
class
temporal.temporal_operator.
TemporalOperatorLexer
[source]¶ Bases:
object
Lexical analyzer for the GRASS GIS temporal operator
-
relations
= {'contain': 'CONTAIN', 'contains': 'CONTAINS', 'cover': 'COVER', 'during': 'DURING', 'equal': 'EQUAL', 'equivalent': 'EQUIVALENT', 'finished': 'FINISHED', 'finishes': 'FINISHES', 'follows': 'FOLLOWS', 'in': 'IN', 'meet': 'MEET', 'over': 'OVER', 'overlap': 'OVERLAP', 'overlapped': 'OVERLAPPED', 'overlaps': 'OVERLAPS', 'precedes': 'PRECEDES', 'started': 'STARTED', 'starts': 'STARTS'}¶
-
t_ADD
= '[\\+]'¶
-
t_AND
= '[&]'¶
-
t_CLPAREN
= '\\{'¶
-
t_COMMA
= ','¶
-
t_CRPAREN
= '\\}'¶
-
t_DISJOINT
= '^[d|disjoint]'¶
-
t_DISOR
= '\\+'¶
-
t_DIV
= '[\\/]'¶
-
t_HASH
= '\\#'¶
-
t_INTERSECT
= '^[i|intersect]'¶
-
t_LEFTREF
= '^[l|left]'¶
-
t_MOD
= '[\\%]'¶
-
t_MULT
= '[\\*]'¶
-
t_NOT
= '\\~'¶
-
t_OR
= '[\\|]'¶
-
t_RIGHTREF
= '^[r|right]'¶
-
t_SUB
= '[-]'¶
-
t_T_NOT_SELECT
= '!:'¶
-
t_T_SELECT
= ':'¶
-
t_UNION
= '^[u|union]'¶
-
t_XOR
= '\\^'¶
-
t_ignore
= ' \t\n'¶
-
tokens
= ('COMMA', 'LEFTREF', 'RIGHTREF', 'UNION', 'DISJOINT', 'INTERSECT', 'HASH', 'OR', 'AND', 'DISOR', 'XOR', 'NOT', 'MOD', 'DIV', 'MULT', 'ADD', 'SUB', 'T_SELECT', 'T_NOT_SELECT', 'CLPAREN', 'CRPAREN', 'EQUAL', 'FOLLOWS', 'PRECEDES', 'OVERLAPS', 'OVERLAPPED', 'DURING', 'STARTS', 'FINISHES', 'CONTAINS', 'STARTED', 'FINISHED', 'OVER', 'EQUIVALENT', 'COVER', 'OVERLAP', 'IN', 'CONTAIN', 'MEET')¶
-
-
class
temporal.temporal_operator.
TemporalOperatorParser
[source]¶ Bases:
object
The temporal operator class
-
p_hash_relation_operator
(t)[source]¶ - operator : CLPAREN HASH CRPAREN
- CLPAREN HASH COMMA relation CRPARENCLPAREN HASH COMMA relationlist CRPARENCLPAREN HASH COMMA relation COMMA temporal CRPARENCLPAREN HASH COMMA relationlist COMMA temporal CRPAREN
-
p_overlay_relation_operator
(t)[source]¶ - operator : CLPAREN overlay CRPAREN
- CLPAREN overlay COMMA relation CRPARENCLPAREN overlay COMMA relationlist CRPARENCLPAREN overlay COMMA relation COMMA temporal CRPARENCLPAREN overlay COMMA relationlist COMMA temporal CRPAREN
-
p_raster_relation_operator
(t)[source]¶ - operator : CLPAREN arithmetic CRPAREN
- CLPAREN arithmetic COMMA relation CRPARENCLPAREN arithmetic COMMA relationlist CRPARENCLPAREN arithmetic COMMA relation COMMA temporal CRPARENCLPAREN arithmetic COMMA relationlist COMMA temporal CRPAREN
-
p_relation
(t)[source]¶ - relation : EQUAL
- FOLLOWSPRECEDESOVERLAPSOVERLAPPEDDURINGSTARTSFINISHESCONTAINSSTARTEDFINISHEDEQUIVALENTCOVEROVERLAPINCONTAINMEET
-
p_relation_bool_combi_operator
(t)[source]¶ - operator : CLPAREN OR OR COMMA relation COMMA OR CRPAREN
- CLPAREN OR OR COMMA relation COMMA AND CRPARENCLPAREN AND AND COMMA relation COMMA OR CRPARENCLPAREN AND AND COMMA relation COMMA AND CRPARENCLPAREN OR OR COMMA relationlist COMMA OR CRPARENCLPAREN OR OR COMMA relationlist COMMA AND CRPARENCLPAREN AND AND COMMA relationlist COMMA OR CRPARENCLPAREN AND AND COMMA relationlist COMMA AND CRPAREN
-
p_relation_bool_combi_operator2
(t)[source]¶ - operator : CLPAREN OR OR COMMA relation COMMA temporal CRPAREN
- CLPAREN AND AND COMMA relation COMMA temporal CRPARENCLPAREN OR OR COMMA relationlist COMMA temporal CRPARENCLPAREN AND AND COMMA relationlist COMMA temporal CRPAREN
-
p_relation_bool_combi_operator3
(t)[source]¶ - operator : CLPAREN OR OR COMMA relation COMMA OR COMMA temporal CRPAREN
- CLPAREN OR OR COMMA relation COMMA AND COMMA temporal CRPARENCLPAREN AND AND COMMA relation COMMA OR COMMA temporal CRPARENCLPAREN AND AND COMMA relation COMMA AND COMMA temporal CRPARENCLPAREN OR OR COMMA relationlist COMMA OR COMMA temporal CRPARENCLPAREN OR OR COMMA relationlist COMMA AND COMMA temporal CRPARENCLPAREN AND AND COMMA relationlist COMMA OR COMMA temporal CRPARENCLPAREN AND AND COMMA relationlist COMMA AND COMMA temporal CRPAREN
-
p_relation_bool_operator
(t)[source]¶ - operator : CLPAREN OR OR COMMA relation CRPAREN
- CLPAREN AND AND COMMA relation CRPARENCLPAREN OR OR COMMA relationlist CRPARENCLPAREN AND AND COMMA relationlist CRPAREN
-
p_select_relation_operator
(t)[source]¶ - operator : CLPAREN select CRPAREN
- CLPAREN select COMMA relation CRPARENCLPAREN select COMMA relationlist CRPARENCLPAREN select COMMA relation COMMA temporal CRPARENCLPAREN select COMMA relationlist COMMA temporal CRPAREN
-
parse
(expression, optype='relation')[source]¶ Parse the expression and fill the object variables
Parameters: Returns:
-
tokens
= ('COMMA', 'LEFTREF', 'RIGHTREF', 'UNION', 'DISJOINT', 'INTERSECT', 'HASH', 'OR', 'AND', 'DISOR', 'XOR', 'NOT', 'MOD', 'DIV', 'MULT', 'ADD', 'SUB', 'T_SELECT', 'T_NOT_SELECT', 'CLPAREN', 'CRPAREN', 'EQUAL', 'FOLLOWS', 'PRECEDES', 'OVERLAPS', 'OVERLAPPED', 'DURING', 'STARTS', 'FINISHES', 'CONTAINS', 'STARTED', 'FINISHED', 'OVER', 'EQUIVALENT', 'COVER', 'OVERLAP', 'IN', 'CONTAIN', 'MEET')¶
-
temporal.temporal_raster3d_algebra module¶
!@package grass.temporal
Temporal raster algebra
(C) 2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Thomas Leppelt and Soeren Gebbert |
---|
-
class
temporal.temporal_raster3d_algebra.
TemporalRaster3DAlgebraParser
(pid=None, run=False, debug=True, spatial=False, register_null=False, dry_run=False, nprocs=1)[source]¶ Bases:
temporal.temporal_raster_base_algebra.TemporalRasterBaseAlgebraParser
The temporal raster algebra class
temporal.temporal_raster_algebra module¶
!@package grass.temporal
Temporal raster algebra
(C) 2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Thomas Leppelt and Soeren Gebbert |
---|
>>> p = TemporalRasterAlgebraLexer()
>>> p.build()
>>> p.debug = True
>>> expression = 'R = A[0,1,0] / B[0,0,1] * 20 + C[0,1,1] - 2.45'
>>> p.test(expression)
R = A[0,1,0] / B[0,0,1] * 20 + C[0,1,1] - 2.45
LexToken(NAME,'R',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(NAME,'A',1,4)
LexToken(L_SPAREN,'[',1,5)
LexToken(INT,0,1,6)
LexToken(COMMA,',',1,7)
LexToken(INT,1,1,8)
LexToken(COMMA,',',1,9)
LexToken(INT,0,1,10)
LexToken(R_SPAREN,']',1,11)
LexToken(DIV,'/',1,13)
LexToken(NAME,'B',1,15)
LexToken(L_SPAREN,'[',1,16)
LexToken(INT,0,1,17)
LexToken(COMMA,',',1,18)
LexToken(INT,0,1,19)
LexToken(COMMA,',',1,20)
LexToken(INT,1,1,21)
LexToken(R_SPAREN,']',1,22)
LexToken(MULT,'*',1,24)
LexToken(INT,20,1,26)
LexToken(ADD,'+',1,29)
LexToken(NAME,'C',1,31)
LexToken(L_SPAREN,'[',1,32)
LexToken(INT,0,1,33)
LexToken(COMMA,',',1,34)
LexToken(INT,1,1,35)
LexToken(COMMA,',',1,36)
LexToken(INT,1,1,37)
LexToken(R_SPAREN,']',1,38)
LexToken(SUB,'-',1,40)
LexToken(FLOAT,2.45,1,42)
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class
temporal.temporal_raster_algebra.
TemporalRasterAlgebraParser
(pid=None, run=False, debug=True, spatial=False, register_null=False, dry_run=False, nprocs=1, time_suffix=None)[source]¶ Bases:
temporal.temporal_raster_base_algebra.TemporalRasterBaseAlgebraParser
The temporal raster algebra class
temporal.temporal_raster_base_algebra module¶
@package grass.temporal
Temporal raster algebra
(C) 2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Thomas Leppelt and Soeren Gebbert |
---|
>>> p = TemporalRasterAlgebraLexer()
>>> p.build()
>>> p.debug = True
>>> expression = 'R = A {+,equal,l} B'
>>> p.test(expression)
R = A {+,equal,l} B
LexToken(NAME,'R',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(NAME,'A',1,4)
LexToken(T_ARITH2_OPERATOR,'{+,equal,l}',1,6)
LexToken(NAME,'B',1,18)
>>> expression = 'R = A {*,equal|during,r} B'
>>> p.test(expression)
R = A {*,equal|during,r} B
LexToken(NAME,'R',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(NAME,'A',1,4)
LexToken(T_ARITH1_OPERATOR,'{*,equal|during,r}',1,6)
LexToken(NAME,'B',1,25)
>>> expression = 'R = A {+,equal|during} B'
>>> p.test(expression)
R = A {+,equal|during} B
LexToken(NAME,'R',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(NAME,'A',1,4)
LexToken(T_ARITH2_OPERATOR,'{+,equal|during}',1,6)
LexToken(NAME,'B',1,23)
-
class
temporal.temporal_raster_base_algebra.
TemporalRasterAlgebraLexer
[source]¶ Bases:
temporal.temporal_algebra.TemporalAlgebraLexer
Lexical analyzer for the GRASS GIS temporal algebra
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map_functions
= {'map': 'MAP'}¶
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mapcalc_functions
= {'abs': 'ABS', 'acos': 'ACOS', 'asin': 'ASIN', 'cos': 'COS', 'double': 'DOUBLE', 'exist': 'EXIST', 'exp': 'EXP', 'float': 'FLOATEXP', 'int': 'INTEXP', 'isntnull': 'ISNTNULL', 'isnull': 'ISNULL', 'log': 'LOG', 'null': 'NULL', 'sin': 'SIN', 'sqrt': 'SQRT', 'tan': 'TAN'}¶
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raster_tokens
= ('MOD', 'DIV', 'MULT', 'ADD', 'SUB', 'T_ARITH1_OPERATOR', 'T_ARITH2_OPERATOR', 'L_SPAREN', 'R_SPAREN')¶
-
t_ADD
= '[\\+]'¶
-
t_DIV
= '[\\/]'¶
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t_L_SPAREN
= '\\['¶
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t_MOD
= '[\\%]'¶
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t_MULT
= '[\\*]'¶
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t_R_SPAREN
= '\\]'¶
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t_SUB
= '[-]'¶
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t_T_ARITH1_OPERATOR
= '\\{[\\%\\*\\/][,]?[a-zA-Z\\| ]*([,])?([lrudi]|left|right|union|disjoint|intersect)?\\}'¶
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t_T_ARITH2_OPERATOR
= '\\{[+-][,]?[a-zA-Z\\| ]*([,])?([lrudi]|left|right|union|disjoint|intersect)?\\}'¶
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tokens
= ('DATETIME', 'TIME', 'DATE', 'INT', 'FLOAT', 'LPAREN', 'RPAREN', 'COMMA', 'CEQUALS', 'EQUALS', 'UNEQUALS', 'LOWER', 'LOWER_EQUALS', 'GREATER', 'GREATER_EQUALS', 'HASH', 'OR', 'AND', 'T_SELECT_OPERATOR', 'T_HASH_OPERATOR', 'T_COMP_OPERATOR', 'T_REL_OPERATOR', 'T_SELECT', 'T_NOT_SELECT', 'NAME', 'QUOTE', 'START_TIME', 'START_DATE', 'START_DATETIME', 'END_TIME', 'END_DATE', 'END_DATETIME', 'TD', 'START_DOY', 'START_DOW', 'START_YEAR', 'START_MONTH', 'START_WEEK', 'START_DAY', 'START_HOUR', 'START_MINUTE', 'START_SECOND', 'END_DOY', 'END_DOW', 'END_YEAR', 'END_MONTH', 'END_WEEK', 'END_DAY', 'END_HOUR', 'END_MINUTE', 'END_SECOND', 'IF', 'BUFF_T', 'TSNAP', 'TSHIFT', 'TMAP', 'MERGE', 'STRDS', 'STR3DS', 'STVDS', 'MOD', 'DIV', 'MULT', 'ADD', 'SUB', 'T_ARITH1_OPERATOR', 'T_ARITH2_OPERATOR', 'L_SPAREN', 'R_SPAREN', 'EXP', 'LOG', 'SQRT', 'ABS', 'COS', 'ACOS', 'SIN', 'ASIN', 'TAN', 'DOUBLE', 'FLOATEXP', 'INTEXP', 'ISNULL', 'ISNTNULL', 'NULL', 'EXIST', 'MAP')¶
-
-
class
temporal.temporal_raster_base_algebra.
TemporalRasterBaseAlgebraParser
(pid=None, run=True, debug=False, spatial=False, register_null=False, dry_run=False, nprocs=1, time_suffix=None)[source]¶ Bases:
temporal.temporal_algebra.TemporalAlgebraParser
The temporal algebra class
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build_command_string
(map_i, relmap, operator=None, cmd_type=None)[source]¶ This function build the r.mapcalc command string for conditionals, spatial variable combinations and boolean comparisons.
For Example: ‘if(a1 == 1, b1, c2)’ or ‘exist(a1) && sin(b1)’
Parameters: - map_i – map object with temporal extent and built relations.
- relmap – map object with defined temporal relation to map_i.
- operator – String representing operator between two spatial variables (&&,||,+,-,*,/).
- cmd_type – map object with defined temporal relation to map_i: condition, conclusion or operator.
Returns: the resulting command string for conditionals or spatial variable combinations
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build_condition_cmd_list
(iflist, thenlist, elselist=None, condition_topolist=['EQUAL'], conclusion_topolist=['EQUAL'], temporal='l', null=False)[source]¶ This function build the r.mapcalc command strings for spatial conditionals. For Example: ‘if(a1 == 1, b1, c2)’
Parameters: - iflist – Map list with temporal extents and command list.
- thenlist – Map list with temporal extents and command list or numeric string.
- elselist – Map list with temporal extents and command list or numeric string.
- condition_topolist – List of strings for given temporal relations between conditions and conclusions.
- conclusion_topolist – List of strings for given temporal relations between conditions (then and else).
- temporal – The temporal operator specifying the temporal extent operation (intersection, union, disjoint union, right reference, left reference).
- null – Boolean if null map support should be activated.
Returns: map list with resulting command string for given condition type.
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build_spatio_temporal_topology_list
(maplistA, maplistB=None, topolist=['EQUAL'], assign_val=False, count_map=False, compare_bool=False, compare_cmd=False, compop=None, aggregate=None, new=False, convert=False, operator_cmd=False)[source]¶ Build temporal topology for two space time data sets, copy map objects for given relation into map list.
Parameters: - maplistA – List of maps.
- maplistB – List of maps.
- topolist – List of strings of temporal relations.
- assign_val – Boolean for assigning a boolean map value based on the map_values from the compared map list by topological relationships.
- count_map – Boolean if the number of topological related maps should be returned.
- compare_bool – Boolean for comparing boolean map values based on related map list and compariosn operator.
- compare_cmd – Boolean for comparing command list values based on related map list and compariosn operator.
- compop – Comparison operator, && or ||.
- aggregate – Aggregation operator for relation map list, & or |.
- new – Boolean if new temporary maps should be created.
- convert – Boolean if conditional values should be converted to r.mapcalc command strings.
- operator_cmd – Boolean for aggregate arithmetic operators implicitly in command list values based on related map lists.
Returns: List of maps from maplistA that fulfil the topological relationships to maplistB specified in topolist.
>>> # Create two list of maps with equal time stamps >>> from datetime import datetime >>> import grass.temporal as tgis >>> tgis.init(True) >>> l = tgis.TemporalAlgebraParser() >>> mapsA = [] >>> mapsB = [] >>> for i in range(10): ... idA = "a%i@B"%(i) ... mapA = tgis.RasterDataset(idA) ... mapA.uid = idA ... mapA.map_value = True ... idB = "b%i@B"%(i) ... mapB = tgis.RasterDataset(idB) ... mapB.uid = idB ... mapB.map_value = False ... check = mapA.set_absolute_time(datetime(2000,1,i+1), ... datetime(2000,1,i + 2)) ... check = mapB.set_absolute_time(datetime(2000,1,i+6), ... datetime(2000,1,i + 7)) ... mapsA.append(mapA) ... mapsB.append(mapB) >>> resultlist = l.build_spatio_temporal_topology_list(mapsA, mapsB) >>> for map in resultlist: ... print(map.get_id()) a5@B a6@B a7@B a8@B a9@B
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compare_cmd_value
(map_i, compop, aggregate, temporal_topo_list=['EQUAL'], spatial_topo_list=[], convert=False)[source]¶ Function to evaluate two map lists with boolean values by boolean comparison operator.
R = A && B
R = if(A < 1 && B > 1, A, B)
R = if(A < 1 {&&,equal|equivalent} B > 1, A, B)
Extended temporal algebra version with command list builder for temporal raster algebra.
Parameters: - map_i – Map object with temporal extent.
- temporal_relations – List of temporal relation to map_i.
- temporal_topo_list – List of strings for given temporal relations.
- compop – Comparison operator, && or ||.
- aggregate – Aggregation operator for relation map list, & or |.
- convert – Boolean if conditional values should be converted to r.mapcalc command strings.
Returns: Map object with conditional value that has been evaluated by comparison operators.
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operator_cmd_value
(map_i, operator, temporal_topo_list=['EQUAL'], spatial_topo_list=[])[source]¶ Function to evaluate two map lists by given arithmetic operator.
Parameters: - map_i – Map object with temporal extent.
- operator – Arithmetic operator, +-*/%.
- temporal_topo_list – List of strings for given temporal relations.
- spatial_topo_list – List of strings for given spatial relations.
Returns: Map object with command list with operators that has been evaluated by implicit aggregation.
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p_arith1_operation
(t)[source]¶ - expr : stds MOD stds
- expr MOD stdsstds MOD exprexpr MOD exprstds DIV stdsexpr DIV stdsstds DIV exprexpr DIV exprstds MULT stdsexpr MULT stdsstds MULT exprexpr MULT exprstds MOD t_td_varexpr MOD t_td_varstds DIV t_td_varexpr DIV t_td_varstds MULT t_td_varexpr MULT t_td_var
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p_arith1_operation_numeric1
(t)[source]¶ - expr : stds MOD number
- expr MOD numberstds DIV numberexpr DIV numberstds MULT numberexpr MULT numberstds MOD numberstrexpr MOD numberstrstds DIV numberstrexpr DIV numberstrstds MULT numberstrexpr MULT numberstrstds MOD mapexprexpr MOD mapexprstds DIV mapexprexpr DIV mapexprstds MULT mapexprexpr MULT mapexpr
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p_arith1_operation_numeric2
(t)[source]¶ - expr : number MOD stds
- number MOD exprnumber DIV stdsnumber DIV exprnumber MULT stdsnumber MULT exprnumberstr MOD stdsnumberstr MOD exprnumberstr DIV stdsnumberstr DIV exprnumberstr MULT stdsnumberstr MULT exprmapexpr MOD stdsmapexpr MOD exprmapexpr DIV stdsmapexpr DIV exprmapexpr MULT stdsmapexpr MULT expr
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p_arith1_operation_relation
(t)[source]¶ - expr : stds T_ARITH1_OPERATOR stds
- expr T_ARITH1_OPERATOR stdsstds T_ARITH1_OPERATOR exprexpr T_ARITH1_OPERATOR exprstds T_ARITH1_OPERATOR t_td_varexpr T_ARITH1_OPERATOR t_td_var
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p_arith2_operation
(t)[source]¶ - expr : stds ADD stds
- expr ADD stdsstds ADD exprexpr ADD exprstds SUB stdsexpr SUB stdsstds SUB exprexpr SUB exprstds ADD t_td_varexpr ADD t_td_varexpr SUB t_td_varstds SUB t_td_var
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p_arith2_operation_numeric1
(t)[source]¶ - expr : stds ADD number
- expr ADD numberstds SUB numberexpr SUB numberstds ADD numberstrexpr ADD numberstrstds SUB numberstrexpr SUB numberstrstds ADD mapexprexpr ADD mapexprstds SUB mapexprexpr SUB mapexpr
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p_arith2_operation_numeric2
(t)[source]¶ - expr : number ADD stds
- number ADD exprnumber SUB stdsnumber SUB exprnumberstr ADD stdsnumberstr ADD exprnumberstr SUB stdsnumberstr SUB exprmapexpr ADD stdsmapexpr ADD exprmapexpr SUB stdsmapexpr SUB expr
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p_arith2_operation_relation
(t)[source]¶ - expr : stds T_ARITH2_OPERATOR stds
- expr T_ARITH2_OPERATOR stdsstds T_ARITH2_OPERATOR exprexpr T_ARITH2_OPERATOR exprstds T_ARITH2_OPERATOR t_td_varexpr T_ARITH2_OPERATOR t_td_var
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p_arith_operation_numeric_string
(t)[source]¶ - numberstr : number ADD number
- number SUB numbernumber DIV numbernumber MULT numbernumber MOD number
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p_mapcalc_function
(t)[source]¶ - mapcalc_arith : ABS
- LOGSQRTEXPCOSACOSSINASINTANDOUBLEFLOATEXPINTEXP
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p_mapcalc_operation1
(t)[source]¶ - expr : mapcalc_arith LPAREN stds RPAREN
- mapcalc_arith LPAREN expr RPAREN
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p_s_expr_condition_elif
(t)[source]¶ - expr : IF LPAREN s_var_expr COMMA stds COMMA stds RPAREN
- IF LPAREN s_var_expr COMMA stds COMMA expr RPARENIF LPAREN s_var_expr COMMA expr COMMA stds RPARENIF LPAREN s_var_expr COMMA expr COMMA expr RPARENIF LPAREN ts_var_expr COMMA stds COMMA stds RPARENIF LPAREN ts_var_expr COMMA stds COMMA expr RPARENIF LPAREN ts_var_expr COMMA expr COMMA stds RPARENIF LPAREN ts_var_expr COMMA expr COMMA expr RPAREN
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p_s_expr_condition_elif_relation
(t)[source]¶ - expr : IF LPAREN T_REL_OPERATOR COMMA s_var_expr COMMA stds COMMA stds RPAREN
- IF LPAREN T_REL_OPERATOR COMMA s_var_expr COMMA stds COMMA expr RPARENIF LPAREN T_REL_OPERATOR COMMA s_var_expr COMMA expr COMMA stds RPARENIF LPAREN T_REL_OPERATOR COMMA s_var_expr COMMA expr COMMA expr RPARENIF LPAREN T_REL_OPERATOR COMMA ts_var_expr COMMA stds COMMA stds RPARENIF LPAREN T_REL_OPERATOR COMMA ts_var_expr COMMA stds COMMA expr RPARENIF LPAREN T_REL_OPERATOR COMMA ts_var_expr COMMA expr COMMA stds RPARENIF LPAREN T_REL_OPERATOR COMMA ts_var_expr COMMA expr COMMA expr RPAREN
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p_s_expr_condition_if
(t)[source]¶ - expr : IF LPAREN s_var_expr COMMA stds RPAREN
- IF LPAREN s_var_expr COMMA expr RPARENIF LPAREN ts_var_expr COMMA stds RPARENIF LPAREN ts_var_expr COMMA expr RPAREN
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p_s_expr_condition_if_relation
(t)[source]¶ - expr : IF LPAREN T_REL_OPERATOR COMMA s_var_expr COMMA stds RPAREN
- IF LPAREN T_REL_OPERATOR COMMA s_var_expr COMMA expr RPARENIF LPAREN T_REL_OPERATOR COMMA ts_var_expr COMMA stds RPARENIF LPAREN T_REL_OPERATOR COMMA ts_var_expr COMMA expr RPAREN
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p_s_numeric_condition_elif
(t)[source]¶ - expr : IF LPAREN s_var_expr COMMA number COMMA number RPAREN
- IF LPAREN s_var_expr COMMA NULL LPAREN RPAREN COMMA number RPARENIF LPAREN s_var_expr COMMA number COMMA NULL LPAREN RPAREN RPARENIF LPAREN s_var_expr COMMA NULL LPAREN RPAREN COMMA NULL LPAREN RPAREN RPARENIF LPAREN ts_var_expr COMMA number COMMA number RPARENIF LPAREN ts_var_expr COMMA NULL LPAREN RPAREN COMMA number RPARENIF LPAREN ts_var_expr COMMA number COMMA NULL LPAREN RPAREN RPARENIF LPAREN ts_var_expr COMMA NULL LPAREN RPAREN COMMA NULL LPAREN RPAREN RPAREN
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p_s_numeric_condition_if
(t)[source]¶ - expr : IF LPAREN s_var_expr COMMA number RPAREN
- IF LPAREN s_var_expr COMMA NULL LPAREN RPAREN RPARENIF LPAREN ts_var_expr COMMA number RPARENIF LPAREN ts_var_expr COMMA NULL LPAREN RPAREN RPAREN
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p_s_numeric_expr_condition_elif
(t)[source]¶ - expr : IF LPAREN s_var_expr COMMA number COMMA stds RPAREN
- IF LPAREN s_var_expr COMMA NULL LPAREN RPAREN COMMA stds RPARENIF LPAREN s_var_expr COMMA number COMMA expr RPARENIF LPAREN s_var_expr COMMA NULL LPAREN RPAREN COMMA expr RPARENIF LPAREN s_var_expr COMMA stds COMMA number RPARENIF LPAREN s_var_expr COMMA stds COMMA NULL LPAREN RPAREN RPARENIF LPAREN s_var_expr COMMA expr COMMA number RPARENIF LPAREN s_var_expr COMMA expr COMMA NULL LPAREN RPAREN RPARENIF LPAREN ts_var_expr COMMA number COMMA stds RPARENIF LPAREN ts_var_expr COMMA NULL LPAREN RPAREN COMMA stds RPARENIF LPAREN ts_var_expr COMMA number COMMA expr RPARENIF LPAREN ts_var_expr COMMA NULL LPAREN RPAREN COMMA expr RPARENIF LPAREN ts_var_expr COMMA stds COMMA number RPARENIF LPAREN ts_var_expr COMMA stds COMMA NULL LPAREN RPAREN RPARENIF LPAREN ts_var_expr COMMA expr COMMA number RPARENIF LPAREN ts_var_expr COMMA expr COMMA NULL LPAREN RPAREN RPAREN
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p_s_numeric_expr_condition_elif_relation
(t)[source]¶ - expr : IF LPAREN T_REL_OPERATOR COMMA s_var_expr COMMA number COMMA stds RPAREN
- IF LPAREN T_REL_OPERATOR COMMA s_var_expr COMMA NULL LPAREN RPAREN COMMA stds RPARENIF LPAREN T_REL_OPERATOR COMMA s_var_expr COMMA number COMMA expr RPARENIF LPAREN T_REL_OPERATOR COMMA s_var_expr COMMA NULL LPAREN RPAREN COMMA expr RPARENIF LPAREN T_REL_OPERATOR COMMA s_var_expr COMMA stds COMMA number RPARENIF LPAREN T_REL_OPERATOR COMMA s_var_expr COMMA stds COMMA NULL LPAREN RPAREN RPARENIF LPAREN T_REL_OPERATOR COMMA s_var_expr COMMA expr COMMA number RPARENIF LPAREN T_REL_OPERATOR COMMA s_var_expr COMMA expr COMMA NULL LPAREN RPAREN RPARENIF LPAREN T_REL_OPERATOR COMMA ts_var_expr COMMA number COMMA stds RPARENIF LPAREN T_REL_OPERATOR COMMA ts_var_expr COMMA NULL LPAREN RPAREN COMMA stds RPARENIF LPAREN T_REL_OPERATOR COMMA ts_var_expr COMMA number COMMA expr RPARENIF LPAREN T_REL_OPERATOR COMMA ts_var_expr COMMA NULL LPAREN RPAREN COMMA expr RPARENIF LPAREN T_REL_OPERATOR COMMA ts_var_expr COMMA stds COMMA number RPARENIF LPAREN T_REL_OPERATOR COMMA ts_var_expr COMMA stds COMMA NULL LPAREN RPAREN RPARENIF LPAREN T_REL_OPERATOR COMMA ts_var_expr COMMA expr COMMA number RPARENIF LPAREN T_REL_OPERATOR COMMA ts_var_expr COMMA expr COMMA NULL LPAREN RPAREN RPAREN
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p_s_var_expr_comp
(t)[source]¶ - s_var_expr : s_var_expr AND AND s_var_expr
- s_var_expr OR OR s_var_expr
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p_ts_var_expr1
(t)[source]¶ - ts_var_expr : s_var_expr AND AND t_var_expr
- t_var_expr AND AND s_var_exprt_var_expr OR OR s_var_exprs_var_expr OR OR t_var_exprts_var_expr AND AND s_var_exprts_var_expr AND AND t_var_exprts_var_expr OR OR s_var_exprts_var_expr OR OR t_var_exprs_var_expr AND AND ts_var_exprt_var_expr AND AND ts_var_exprs_var_expr OR OR ts_var_exprt_var_expr OR OR ts_var_expr
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precedence
= (('left', 'T_SELECT_OPERATOR', 'T_SELECT', 'T_NOT_SELECT'), ('left', 'ADD', 'SUB', 'T_ARITH2_OPERATOR', 'T_HASH_OPERATOR', 'HASH'), ('left', 'AND', 'OR', 'T_COMP_OPERATOR', 'MOD', 'DIV', 'MULT', 'T_ARITH1_OPERATOR'))¶
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set_temporal_extent_list
(maplist, topolist=['EQUAL'], temporal='l', cmd_bool=False, cmd_type=None, operator=None)[source]¶ Change temporal extent of map list based on temporal relations to other map list and given temporal operator.
Parameters: - maplist – List of map objects for which relations has been build correctly.
- topolist – List of strings of temporal relations.
- temporal – The temporal operator specifying the temporal extent operation (intersection, union, disjoint union, right reference, left reference).
- cmd_bool – Boolean if command string should be merged for related maps.
- cmd_type – map object with defined temporal relation to map_i: condition, conclusion or operator.
- operator – String defining the type of operator.
Returns: Map list with specified temporal extent and optional command string.
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tokens
= ('DATETIME', 'TIME', 'DATE', 'INT', 'FLOAT', 'LPAREN', 'RPAREN', 'COMMA', 'CEQUALS', 'EQUALS', 'UNEQUALS', 'LOWER', 'LOWER_EQUALS', 'GREATER', 'GREATER_EQUALS', 'HASH', 'OR', 'AND', 'T_SELECT_OPERATOR', 'T_HASH_OPERATOR', 'T_COMP_OPERATOR', 'T_REL_OPERATOR', 'T_SELECT', 'T_NOT_SELECT', 'NAME', 'QUOTE', 'START_TIME', 'START_DATE', 'START_DATETIME', 'END_TIME', 'END_DATE', 'END_DATETIME', 'TD', 'START_DOY', 'START_DOW', 'START_YEAR', 'START_MONTH', 'START_WEEK', 'START_DAY', 'START_HOUR', 'START_MINUTE', 'START_SECOND', 'END_DOY', 'END_DOW', 'END_YEAR', 'END_MONTH', 'END_WEEK', 'END_DAY', 'END_HOUR', 'END_MINUTE', 'END_SECOND', 'IF', 'BUFF_T', 'TSNAP', 'TSHIFT', 'TMAP', 'MERGE', 'STRDS', 'STR3DS', 'STVDS', 'MOD', 'DIV', 'MULT', 'ADD', 'SUB', 'T_ARITH1_OPERATOR', 'T_ARITH2_OPERATOR', 'L_SPAREN', 'R_SPAREN', 'EXP', 'LOG', 'SQRT', 'ABS', 'COS', 'ACOS', 'SIN', 'ASIN', 'TAN', 'DOUBLE', 'FLOATEXP', 'INTEXP', 'ISNULL', 'ISNTNULL', 'NULL', 'EXIST', 'MAP')¶
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temporal.temporal_topology_dataset_connector module¶
Temporal topology dataset connector class
Usage:
>>> import grass.temporal as tgis
>>> tmr = tgis.TemporalTopologyDatasetConnector()
(C) 2012-2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
-
class
temporal.temporal_topology_dataset_connector.
TemporalTopologyDatasetConnector
[source]¶ Bases:
object
This class implements a temporal topology access structure to connect temporal related datasets
This object will be set up by temporal topology creation method provided by the SpatioTemporalTopologyBuilder.
If correctly initialize the calls next() and prev() let the user walk temporally forward and backward in time.
The following temporal relations with access methods are supported:
- equal
- follows
- precedes
- overlaps
- overlapped
- during (including starts, finishes)
- contains (including started, finished)
- starts
- started
- finishes
- finished
# We have build the temporal topology and we know the first map start = first while start: # Print all maps this map temporally contains dlist = start.get_contains() for map in dlist: map.print_info() start = start.next() >>> import grass.temporal as tgis >>> tgis.init() >>> map = tgis.RasterDataset("a@P") >>> tmr = tgis.TemporalTopologyDatasetConnector() >>> tmr.set_next(map) >>> tmr.set_prev(map) >>> tmr.append_equal(map) >>> tmr.append_follows(map) >>> tmr.append_precedes(map) >>> tmr.append_overlapped(map) >>> tmr.append_overlaps(map) >>> tmr.append_during(map) >>> tmr.append_contains(map) >>> tmr.append_starts(map) >>> tmr.append_started(map) >>> tmr.append_finishes(map) >>> tmr.append_finished(map) >>> tmr.print_temporal_topology_info() +-------------------- Temporal Topology -------------------------------------+ | Next: ...................... a@P | Previous: .................. a@P | Equal:...................... a@P | Follows: ................... a@P | Precedes: .................. a@P | Overlaps: .................. a@P | Overlapped: ................ a@P | During: .................... a@P | Contains: .................. a@P | Starts:.. .................. a@P | Started:. .................. a@P | Finishes:................... a@P | Finished:................... a@P >>> tmr.print_temporal_topology_shell_info() next=a@P prev=a@P equal=a@P follows=a@P precedes=a@P overlaps=a@P overlapped=a@P during=a@P contains=a@P starts=a@P started=a@P finishes=a@P finished=a@P >>> rlist = tmr.get_temporal_relations() >>> if "FINISHED" in rlist.keys(): ... print(rlist["FINISHED"][0].get_id()) a@P
-
append_contains
(map)[source]¶ Append a map that this map temporally contains This includes temporal relationships started and finished
Parameters: map – This object should be of type AbstractMapDataset or derived classes
-
append_during
(map)[source]¶ Append a map that this map is temporally located during This includes temporal relationships starts and finishes
Parameters: map – This object should be of type AbstractMapDataset or derived classes
-
append_equal
(map)[source]¶ Append a map with equivalent temporal extent as this map
Parameters: map – This object should be of type AbstractMapDataset or derived classes
-
append_finished
(map)[source]¶ Append a map that this map temporally finished with
Parameters: map – This object should be of type AbstractMapDataset or derived classes
-
append_finishes
(map)[source]¶ Append a map that this map temporally finishes with
Parameters: map – This object should be of type AbstractMapDataset or derived classes
-
append_follows
(map)[source]¶ Append a map that this map temporally follows
Parameters: map – This object should be of type AbstractMapDataset or derived classes
-
append_overlapped
(map)[source]¶ Append a map that this map temporally overlapped
Parameters: map – This object should be of type AbstractMapDataset or derived classes
-
append_overlaps
(map)[source]¶ Append a map that this map temporally overlaps
Parameters: map – This object should be of type AbstractMapDataset or derived classes
-
append_precedes
(map)[source]¶ Append a map that this map temporally precedes
Parameters: map – This object should be of type AbstractMapDataset or derived classes
-
append_started
(map)[source]¶ Append a map that this map temporally started with
Parameters: map – This object should be of type AbstractMapDataset or derived classes
-
append_starts
(map)[source]¶ Append a map that this map temporally starts with
Parameters: map – This object should be of type AbstractMapDataset or derived classes
-
contains
¶ Return a list of map objects that this map temporally contains This includes temporal relationships started and finished
Returns: A list of map objects or None
-
during
¶ Return a list of map objects that this map is temporally located during This includes temporally relationships starts and finishes
Returns: A list of map objects or None
-
equal
¶ Return a list of map objects with equivalent temporal extent as this map
Returns: A list of map objects or None
-
finished
¶ Return a list of map objects that this map temporally finished with
Returns: A list of map objects or None
-
finishes
¶ Return a list of map objects that this map temporally finishes with
Returns: A list of map objects or None
-
follows
¶ Return a list of map objects that this map temporally follows
Returns: A list of map objects or None
-
get_contains
()[source]¶ Return a list of map objects that this map temporally contains This includes temporal relationships started and finished
Returns: A list of map objects or None
-
get_during
()[source]¶ Return a list of map objects that this map is temporally located during This includes temporally relationships starts and finishes
Returns: A list of map objects or None
-
get_equal
()[source]¶ Return a list of map objects with equivalent temporal extent as this map
Returns: A list of map objects or None
-
get_finished
()[source]¶ Return a list of map objects that this map temporally finished with
Returns: A list of map objects or None
-
get_finishes
()[source]¶ Return a list of map objects that this map temporally finishes with
Returns: A list of map objects or None
-
get_follows
()[source]¶ Return a list of map objects that this map temporally follows
Returns: A list of map objects or None
-
get_number_of_temporal_relations
()[source]¶ Return a dictionary in which the keys are the relation names and the value are the number of relations.
The following relations are available:
- equal
- follows
- precedes
- overlaps
- overlapped
- during (including starts, finishes)
- contains (including started, finished)
- starts
- started
- finishes
- finished
To access topological information the temporal topology must be build first using the SpatioTemporalTopologyBuilder.
Returns: the dictionary with relations as keys and number as values or None in case the topology wasn’t build
-
get_overlapped
()[source]¶ Return a list of map objects that this map temporally overlapped
Returns: A list of map objects or None
-
get_overlaps
()[source]¶ Return a list of map objects that this map temporally overlaps
Returns: A list of map objects or None
-
get_precedes
()[source]¶ Return a list of map objects that this map temporally precedes
Returns: A list of map objects or None
-
get_started
()[source]¶ Return a list of map objects that this map temporally started with
Returns: A list of map objects or None
-
get_starts
()[source]¶ Return a list of map objects that this map temporally starts with
Returns: A list of map objects or None
-
get_temporal_relations
()[source]¶ Return the dictionary of temporal relationships
Keys are the temporal relationships in upper case, values are abstract map objects.
Returns: The temporal relations dictionary
-
next
()[source]¶ Return the map with a start time temporally located after the start time of this map, but temporal closer than other maps
Returns: A map object or None
-
overlapped
¶ Return a list of map objects that this map temporally overlapped
Returns: A list of map objects or None
-
overlaps
¶ Return a list of map objects that this map temporally overlaps
Returns: A list of map objects or None
-
precedes
¶ Return a list of map objects that this map temporally precedes
Returns: A list of map objects or None
-
prev
()[source]¶ Return the map with a start time temporally located before the start time of this map, but temporal closer than other maps
Returns: A map object or None
-
set_next
(map)[source]¶ Set the map that is temporally as closest located after this map.
Temporally located means that the start time of the “next” map is temporally located AFTER the start time of this map, but temporally near than other maps of the same dataset.
Parameters: map – This object should be of type AbstractMapDataset or derived classes
-
set_prev
(map)[source]¶ Set the map that is temporally as closest located before this map.
Temporally located means that the start time of the “previous” map is temporally located BEFORE the start time of this map, but temporally near than other maps of the same dataset.
Parameters: map – This object should be of type AbstractMapDataset or derived classes
-
started
¶ Return a list of map objects that this map temporally started with
Returns: A list of map objects or None
-
starts
¶ Return a list of map objects that this map temporally starts with
Returns: A list of map objects or None
temporal.temporal_vector_algebra module¶
@package grass.temporal
Temporal vector algebra
(C) 2014 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Thomas Leppelt and Soeren Gebbert |
---|
>>> import grass.temporal as tgis
>>> tgis.init(True)
>>> p = tgis.TemporalVectorAlgebraLexer()
>>> p.build()
>>> p.debug = True
>>> expression = 'E = A : B ^ C : D'
>>> p.test(expression)
E = A : B ^ C : D
LexToken(NAME,'E',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(NAME,'A',1,4)
LexToken(T_SELECT,':',1,6)
LexToken(NAME,'B',1,8)
LexToken(XOR,'^',1,10)
LexToken(NAME,'C',1,12)
LexToken(T_SELECT,':',1,14)
LexToken(NAME,'D',1,16)
>>> expression = 'E = buff_a(A, 10)'
>>> p.test(expression)
E = buff_a(A, 10)
LexToken(NAME,'E',1,0)
LexToken(EQUALS,'=',1,2)
LexToken(BUFF_AREA,'buff_a',1,4)
LexToken(LPAREN,'(',1,10)
LexToken(NAME,'A',1,11)
LexToken(COMMA,',',1,12)
LexToken(INT,10,1,14)
LexToken(RPAREN,')',1,16)
-
class
temporal.temporal_vector_algebra.
TemporalVectorAlgebraLexer
[source]¶ Bases:
temporal.temporal_algebra.TemporalAlgebraLexer
Lexical analyzer for the GRASS GIS temporal vector algebra
-
t_DISOR
= '\\+'¶
-
t_NOT
= '\\~'¶
-
t_T_OVERLAY_OPERATOR
= '\\{[\\|&+\\^\\~][,]?[a-zA-Z\\| ]*([,])?([lrudi]|left|right|union|disjoint|intersect)?\\}'¶
-
t_XOR
= '\\^'¶
-
tokens
= ('DATETIME', 'TIME', 'DATE', 'INT', 'FLOAT', 'LPAREN', 'RPAREN', 'COMMA', 'CEQUALS', 'EQUALS', 'UNEQUALS', 'LOWER', 'LOWER_EQUALS', 'GREATER', 'GREATER_EQUALS', 'HASH', 'OR', 'AND', 'T_SELECT_OPERATOR', 'T_HASH_OPERATOR', 'T_COMP_OPERATOR', 'T_REL_OPERATOR', 'T_SELECT', 'T_NOT_SELECT', 'NAME', 'QUOTE', 'START_TIME', 'START_DATE', 'START_DATETIME', 'END_TIME', 'END_DATE', 'END_DATETIME', 'TD', 'START_DOY', 'START_DOW', 'START_YEAR', 'START_MONTH', 'START_WEEK', 'START_DAY', 'START_HOUR', 'START_MINUTE', 'START_SECOND', 'END_DOY', 'END_DOW', 'END_YEAR', 'END_MONTH', 'END_WEEK', 'END_DAY', 'END_HOUR', 'END_MINUTE', 'END_SECOND', 'IF', 'BUFF_T', 'TSNAP', 'TSHIFT', 'TMAP', 'MERGE', 'STRDS', 'STR3DS', 'STVDS', 'DISOR', 'XOR', 'NOT', 'T_OVERLAY_OPERATOR', 'BUFF_POINT', 'BUFF_LINE', 'BUFF_AREA')¶
-
vector_buff_functions
= {'buff_a': 'BUFF_AREA', 'buff_l': 'BUFF_LINE', 'buff_p': 'BUFF_POINT'}¶
-
vector_tokens
= ('DISOR', 'XOR', 'NOT', 'T_OVERLAY_OPERATOR')¶
-
-
class
temporal.temporal_vector_algebra.
TemporalVectorAlgebraParser
(pid=None, run=False, debug=True, spatial=False)[source]¶ Bases:
temporal.temporal_algebra.TemporalAlgebraParser
The temporal algebra class
-
build_spatio_temporal_topology_list
(maplistA, maplistB=None, topolist=['EQUAL'], assign_val=False, count_map=False, compare_bool=False, compare_cmd=False, compop=None, aggregate=None, new=False, convert=False, overlay_cmd=False)[source]¶ Build temporal topology for two space time data sets, copy map objects for given relation into map list.
Parameters: - maplistA – List of maps.
- maplistB – List of maps.
- topolist – List of strings of temporal relations.
- assign_val – Boolean for assigning a boolean map value based on the map_values from the compared map list by topological relationships.
- count_map – Boolean if the number of topological related maps should be returned.
- compare_bool – Boolean for comparing boolean map values based on related map list and compariosn operator.
- compare_cmd – Boolean for comparing command list values based on related map list and compariosn operator.
- compop – Comparison operator, && or ||.
- aggregate – Aggregation operator for relation map list, & or |.
- new – Boolean if new temporary maps should be created.
- convert – Boolean if conditional values should be converted to r.mapcalc command strings.
- overlay_cmd – Boolean for aggregate overlay operators implicitly in command list values based on related map lists.
Returns: List of maps from maplistA that fulfil the topological relationships to maplistB specified in topolist.
-
overlay_cmd_value
(map_i, tbrelations, function, topolist=['EQUAL'])[source]¶ Function to evaluate two map lists by given overlay operator.
Parameters: - map_i – Map object with temporal extent.
- tbrelations – List of temporal relation to map_i.
- topolist – List of strings for given temporal relations.
- function – Overlay operator, &|+^~.
Returns: Map object with command list with operators that has been evaluated by implicit aggregration.
-
p_buffer_operation
(t)[source]¶ - expr : buff_function LPAREN stds COMMA number RPAREN
- buff_function LPAREN expr COMMA number RPAREN
-
p_overlay_operation
(t)[source]¶ - expr : stds AND stds
- expr AND stdsstds AND exprexpr AND exprstds OR stdsexpr OR stdsstds OR exprexpr OR exprstds XOR stdsexpr XOR stdsstds XOR exprexpr XOR exprstds NOT stdsexpr NOT stdsstds NOT exprexpr NOT exprstds DISOR stdsexpr DISOR stdsstds DISOR exprexpr DISOR expr
-
p_overlay_operation_relation
(t)[source]¶ - expr : stds T_OVERLAY_OPERATOR stds
- expr T_OVERLAY_OPERATOR stdsstds T_OVERLAY_OPERATOR exprexpr T_OVERLAY_OPERATOR expr
-
parse
(expression, basename=None, overwrite=False)[source]¶ Parse the algebra expression and run the computation
Parameters: - expression –
- stdstype –
- maptype –
- mapclass –
- basename –
- overwrite –
Returns: The process chain dictionary is dry-run was enabled, None otherwise
-
precedence
= (('left', 'T_SELECT_OPERATOR', 'T_SELECT', 'T_NOT_SELECT', 'T_HASH_OPERATOR', 'HASH'), ('left', 'AND', 'OR', 'T_COMP_OPERATOR', 'T_OVERLAY_OPERATOR', 'DISOR', 'NOT', 'XOR'))¶
-
set_temporal_extent_list
(maplist, topolist=['EQUAL'], temporal='l')[source]¶ - Change temporal extent of map list based on temporal relations to
- other map list and given temporal operator.
Parameters: - maplist – List of map objects for which relations has been build correctely.
- topolist – List of strings of temporal relations.
- temporal – The temporal operator specifying the temporal extent operation (intersection, union, disjoint union, right reference, left reference).
Returns: Map list with specified temporal extent.
-
tokens
= ('DATETIME', 'TIME', 'DATE', 'INT', 'FLOAT', 'LPAREN', 'RPAREN', 'COMMA', 'CEQUALS', 'EQUALS', 'UNEQUALS', 'LOWER', 'LOWER_EQUALS', 'GREATER', 'GREATER_EQUALS', 'HASH', 'OR', 'AND', 'T_SELECT_OPERATOR', 'T_HASH_OPERATOR', 'T_COMP_OPERATOR', 'T_REL_OPERATOR', 'T_SELECT', 'T_NOT_SELECT', 'NAME', 'QUOTE', 'START_TIME', 'START_DATE', 'START_DATETIME', 'END_TIME', 'END_DATE', 'END_DATETIME', 'TD', 'START_DOY', 'START_DOW', 'START_YEAR', 'START_MONTH', 'START_WEEK', 'START_DAY', 'START_HOUR', 'START_MINUTE', 'START_SECOND', 'END_DOY', 'END_DOW', 'END_YEAR', 'END_MONTH', 'END_WEEK', 'END_DAY', 'END_HOUR', 'END_MINUTE', 'END_SECOND', 'IF', 'BUFF_T', 'TSNAP', 'TSHIFT', 'TMAP', 'MERGE', 'STRDS', 'STR3DS', 'STVDS', 'DISOR', 'XOR', 'NOT', 'T_OVERLAY_OPERATOR', 'BUFF_POINT', 'BUFF_LINE', 'BUFF_AREA')¶
-
temporal.unit_tests module¶
Depricazed unittests
(C) 2008-2011 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
temporal.univar_statistics module¶
Univariate statistic function for space time datasets
Usage:
import grass.temporal as tgis
tgis.print_gridded_dataset_univar_statistics(type, input, output, where, extended, no_header, fs, rast_region)
(C) 2012-2013 by the GRASS Development Team This program is free software under the GNU General Public License (>=v2). Read the file COPYING that comes with GRASS for details.
authors: | Soeren Gebbert |
---|
-
temporal.univar_statistics.
print_gridded_dataset_univar_statistics
(type, input, output, where, extended, no_header=False, fs='|', rast_region=False)[source]¶ Print univariate statistics for a space time raster or raster3d dataset
Parameters: - type – Must be “strds” or “str3ds”
- input – The name of the space time dataset
- output – Name of the optional output file, if None stdout is used
- where – A temporal database where statement
- extended – If True compute extended statistics
- no_header – Suppress the printing of column names
- fs – Field separator
- rast_region – If set True ignore the current region settings and use the raster map regions for univar statistical calculation. Only available for strds.
-
temporal.univar_statistics.
print_vector_dataset_univar_statistics
(input, output, twhere, layer, type, column, where, extended, no_header=False, fs='|')[source]¶ Print univariate statistics for a space time vector dataset
Parameters: - input – The name of the space time dataset
- output – Name of the optional output file, if None stdout is used
- twhere – A temporal database where statement
- layer – The layer number used in case no layer is present in the temporal dataset
- type – options: point,line,boundary,centroid,area
- column – The name of the attribute column
- where – A temporal database where statement
- extended – If True compute extended statistics
- no_header – Suppress the printing of column names
- fs – Field separator