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def has_matching_etag ( remote_storage , source_storage , path , prefixed_path ) : storage_etag = get_etag ( remote_storage , path , prefixed_path ) local_etag = get_file_hash ( source_storage , path ) return storage_etag == local_etag
Compare etag of path in source storage with remote .
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def should_copy_file ( remote_storage , path , prefixed_path , source_storage ) : if has_matching_etag ( remote_storage , source_storage , path , prefixed_path ) : logger . info ( "%s: Skipping based on matching file hashes" % path ) return False destroy_etag ( path ) logger . info ( "%s: Hashes did not match" % path )...
Returns True if the file should be copied otherwise False .
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def set_options ( self , ** options ) : ignore_etag = options . pop ( 'ignore_etag' , False ) disable = options . pop ( 'disable_collectfast' , False ) if ignore_etag : warnings . warn ( "--ignore-etag is deprecated since 0.5.0, use " "--disable-collectfast instead." ) if ignore_etag or disable : self . collectfast_ena...
Set options and handle deprecation .
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def handle ( self , ** options ) : super ( Command , self ) . handle ( ** options ) return "{} static file{} copied." . format ( self . num_copied_files , '' if self . num_copied_files == 1 else 's' )
Override handle to supress summary output
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def do_copy_file ( self , args ) : path , prefixed_path , source_storage = args reset_connection ( self . storage ) if self . collectfast_enabled and not self . dry_run : try : if not should_copy_file ( self . storage , path , prefixed_path , source_storage ) : return False except Exception as e : if settings . debug :...
Determine if file should be copied or not and handle exceptions .
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def copy_file ( self , path , prefixed_path , source_storage ) : args = ( path , prefixed_path , source_storage ) if settings . threads : self . tasks . append ( args ) else : self . do_copy_file ( args )
Appends path to task queue if threads are enabled otherwise copies the file with a blocking call .
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def delete_file ( self , path , prefixed_path , source_storage ) : if not self . collectfast_enabled : return super ( Command , self ) . delete_file ( path , prefixed_path , source_storage ) if not self . dry_run : self . log ( "Deleting '%s'" % path ) self . storage . delete ( prefixed_path ) else : self . log ( "Pret...
Override delete_file to skip modified time and exists lookups .
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def join ( rasters ) : raster = rasters [ 0 ] mask_band = None nodata = None with raster . _raster_opener ( raster . source_file ) as r : nodata = r . nodata mask_flags = r . mask_flag_enums per_dataset_mask = all ( [ rasterio . enums . MaskFlags . per_dataset in flags for flags in mask_flags ] ) if per_dataset_mask an...
This method takes a list of rasters and returns a raster that is constructed of all of them
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def merge_all ( rasters , roi = None , dest_resolution = None , merge_strategy = MergeStrategy . UNION , shape = None , ul_corner = None , crs = None , pixel_strategy = PixelStrategy . FIRST , resampling = Resampling . nearest ) : first_raster = rasters [ 0 ] if roi : crs = crs or roi . crs dest_resolution = dest_resol...
Merge a list of rasters cropping by a region of interest . There are cases that the roi is not precise enough for this cases one can use the upper left corner the shape and crs to precisely define the roi . When roi is provided the ul_corner shape and crs are ignored
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def _merge_common_bands ( rasters ) : all_bands = IndexedSet ( [ rs . band_names [ 0 ] for rs in rasters ] ) def key ( rs ) : return all_bands . index ( rs . band_names [ 0 ] ) rasters_final = [ ] for band_name , rasters_group in groupby ( sorted ( rasters , key = key ) , key = key ) : rasters_final . append ( reduce (...
Combine the common bands .
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def _explode_raster ( raster , band_names = [ ] ) : if not band_names : band_names = raster . band_names else : band_names = list ( IndexedSet ( raster . band_names ) . intersection ( band_names ) ) return [ _Raster ( image = raster . bands_data ( [ band_name ] ) , band_names = [ band_name ] ) for band_name in band_nam...
Splits a raster into multiband rasters .
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def _fill_pixels ( one , other ) : assert len ( one . band_names ) == len ( other . band_names ) == 1 , "Rasters are not single band" if one . band_names != other . band_names : raise ValueError ( "rasters have no bands in common, use another merge strategy" ) new_image = one . image . copy ( ) other_image = other . im...
Merges two single band rasters with the same band by filling the pixels according to depth .
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def _stack_bands ( one , other ) : assert set ( one . band_names ) . intersection ( set ( other . band_names ) ) == set ( ) if one . band_names == other . band_names : raise ValueError ( "rasters have the same bands, use another merge strategy" ) new_mask = np . ma . getmaskarray ( one . image ) [ 0 ] | np . ma . getma...
Merges two rasters with non overlapping bands by stacking the bands .
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def merge_two ( one , other , merge_strategy = MergeStrategy . UNION , silent = False , pixel_strategy = PixelStrategy . FIRST ) : other_res = _prepare_other_raster ( one , other ) if other_res is None : if silent : return one else : raise ValueError ( "rasters do not intersect" ) else : other = other . copy_with ( ima...
Merge two rasters into one .
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def _set_image ( self , image , nodata = None ) : if isinstance ( image , np . ma . core . MaskedArray ) : masked = image elif isinstance ( image , np . core . ndarray ) : masked = self . _build_masked_array ( image , nodata ) else : raise GeoRaster2NotImplementedError ( 'only ndarray or masked array supported, got %s'...
Set self . _image .
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def from_wms ( cls , filename , vector , resolution , destination_file = None ) : doc = wms_vrt ( filename , bounds = vector , resolution = resolution ) . tostring ( ) filename = cls . _save_to_destination_file ( doc , destination_file ) return GeoRaster2 . open ( filename )
Create georaster from the web service definition file .
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def from_rasters ( cls , rasters , relative_to_vrt = True , destination_file = None , nodata = None , mask_band = None ) : if isinstance ( rasters , list ) : doc = raster_list_vrt ( rasters , relative_to_vrt , nodata , mask_band ) . tostring ( ) else : doc = raster_collection_vrt ( rasters , relative_to_vrt , nodata , ...
Create georaster out of a list of rasters .
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def open ( cls , filename , band_names = None , lazy_load = True , mutable = False , ** kwargs ) : if mutable : geo_raster = MutableGeoRaster ( filename = filename , band_names = band_names , ** kwargs ) else : geo_raster = cls ( filename = filename , band_names = band_names , ** kwargs ) if not lazy_load : geo_raster ...
Read a georaster from a file .
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def tags ( cls , filename , namespace = None ) : return cls . _raster_opener ( filename ) . tags ( ns = namespace )
Extract tags from file .
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def image ( self ) : if self . _image is None : self . _populate_from_rasterio_object ( read_image = True ) return self . _image
Raster bitmap in numpy array .
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def crs ( self ) : if self . _crs is None : self . _populate_from_rasterio_object ( read_image = False ) return self . _crs
Raster crs .
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def shape ( self ) : if self . _shape is None : self . _populate_from_rasterio_object ( read_image = False ) return self . _shape
Raster shape .
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def source_file ( self ) : if self . _filename is None : self . _filename = self . _as_in_memory_geotiff ( ) . _filename return self . _filename
When using open returns the filename used
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def blockshapes ( self ) : if self . _blockshapes is None : if self . _filename : self . _populate_from_rasterio_object ( read_image = False ) else : self . _blockshapes = [ ( self . height , self . width ) for z in range ( self . num_bands ) ] return self . _blockshapes
Raster all bands block shape .
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def get ( self , point ) : if not ( isinstance ( point , GeoVector ) and point . type == 'Point' ) : raise TypeError ( 'expect GeoVector(Point), got %s' % ( point , ) ) target = self . to_raster ( point ) return self . image [ : , int ( target . y ) , int ( target . x ) ]
Get the pixel values at the requested point .
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def copy ( self , mutable = False ) : if self . not_loaded ( ) : _cls = self . __class__ if mutable : _cls = MutableGeoRaster return _cls . open ( self . _filename ) return self . copy_with ( mutable = mutable )
Return a copy of this GeoRaster with no modifications .
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def _resize ( self , ratio_x , ratio_y , resampling ) : new_width = int ( np . ceil ( self . width * ratio_x ) ) new_height = int ( np . ceil ( self . height * ratio_y ) ) dest_affine = self . affine * Affine . scale ( 1 / ratio_x , 1 / ratio_y ) if self . not_loaded ( ) : window = rasterio . windows . Window ( 0 , 0 ,...
Return raster resized by ratio .
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def to_pillow_image ( self , return_mask = False ) : img = np . rollaxis ( np . rollaxis ( self . image . data , 2 ) , 2 ) img = Image . fromarray ( img [ : , : , 0 ] ) if img . shape [ 2 ] == 1 else Image . fromarray ( img ) if return_mask : mask = np . ma . getmaskarray ( self . image ) mask = Image . fromarray ( np ...
Return Pillow . Image and optionally also mask .
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def from_bytes ( cls , image_bytes , affine , crs , band_names = None ) : b = io . BytesIO ( image_bytes ) image = imageio . imread ( b ) roll = np . rollaxis ( image , 2 ) if band_names is None : band_names = [ 0 , 1 , 2 ] elif isinstance ( band_names , str ) : band_names = [ band_names ] return GeoRaster2 ( image = r...
Create GeoRaster from image BytesIo object .
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def _repr_html_ ( self ) : TileServer . run_tileserver ( self , self . footprint ( ) ) capture = "raster: %s" % self . _filename mp = TileServer . folium_client ( self , self . footprint ( ) , capture = capture ) return mp . _repr_html_ ( )
Required for jupyter notebook to show raster as an interactive map .
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def image_corner ( self , corner ) : if corner not in self . corner_types ( ) : raise GeoRaster2Error ( 'corner %s invalid, expected: %s' % ( corner , self . corner_types ( ) ) ) x = 0 if corner [ 1 ] == 'l' else self . width y = 0 if corner [ 0 ] == 'u' else self . height return Point ( x , y )
Return image corner in pixels as shapely . Point .
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def center ( self ) : image_center = Point ( self . width / 2 , self . height / 2 ) return self . to_world ( image_center )
Return footprint center in world coordinates as GeoVector .
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def bounds ( self ) : corners = [ self . image_corner ( corner ) for corner in self . corner_types ( ) ] return Polygon ( [ [ corner . x , corner . y ] for corner in corners ] )
Return image rectangle in pixels as shapely . Polygon .
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def _calc_footprint ( self ) : corners = [ self . corner ( corner ) for corner in self . corner_types ( ) ] coords = [ ] for corner in corners : shape = corner . get_shape ( corner . crs ) coords . append ( [ shape . x , shape . y ] ) shp = Polygon ( coords ) self . _footprint = GeoVector ( shp , self . crs ) return se...
Return rectangle in world coordinates as GeoVector .
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def to_raster ( self , vector ) : return transform ( vector . get_shape ( vector . crs ) , vector . crs , self . crs , dst_affine = ~ self . affine )
Return the vector in pixel coordinates as shapely . Geometry .
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def reduce ( self , op ) : per_band = [ getattr ( np . ma , op ) ( self . image . data [ band , np . ma . getmaskarray ( self . image ) [ band , : , : ] == np . False_ ] ) for band in range ( self . num_bands ) ] return per_band
Reduce the raster to a score using op operation .
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def mask ( self , vector , mask_shape_nodata = False ) : from telluric . collections import BaseCollection cropped = self . crop ( vector ) if isinstance ( vector , BaseCollection ) : shapes = [ cropped . to_raster ( feature ) for feature in vector ] else : shapes = [ cropped . to_raster ( vector ) ] mask = geometry_ma...
Set pixels outside vector as nodata .
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def mask_by_value ( self , nodata ) : return self . copy_with ( image = np . ma . masked_array ( self . image . data , mask = self . image . data == nodata ) )
Return raster with a mask calculated based on provided value . Only pixels with value = nodata will be masked .
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def save_cloud_optimized ( self , dest_url , resampling = Resampling . gauss , blocksize = 256 , overview_blocksize = 256 , creation_options = None ) : src = self with tempfile . NamedTemporaryFile ( suffix = '.tif' ) as tf : src . save ( tf . name , overviews = False ) convert_to_cog ( tf . name , dest_url , resamplin...
Save as Cloud Optimized GeoTiff object to a new file .
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def _get_window_out_shape ( self , bands , window , xsize , ysize ) : if xsize and ysize is None : ratio = window . width / xsize ysize = math . ceil ( window . height / ratio ) elif ysize and xsize is None : ratio = window . height / ysize xsize = math . ceil ( window . width / ratio ) elif xsize is None and ysize is ...
Get the outshape of a window .
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def _read_with_mask ( raster , masked ) : if masked is None : mask_flags = raster . mask_flag_enums per_dataset_mask = all ( [ rasterio . enums . MaskFlags . per_dataset in flags for flags in mask_flags ] ) masked = per_dataset_mask return masked
returns if we should read from rasterio using the masked
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def get_window ( self , window , bands = None , xsize = None , ysize = None , resampling = Resampling . cubic , masked = None , affine = None ) : bands = bands or list ( range ( 1 , self . num_bands + 1 ) ) out_shape = self . _get_window_out_shape ( bands , window , xsize , ysize ) try : read_params = { "window" : wind...
Get window from raster .
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def _get_tile_when_web_mercator_crs ( self , x_tile , y_tile , zoom , bands = None , masked = None , resampling = Resampling . cubic ) : roi = GeoVector . from_xyz ( x_tile , y_tile , zoom ) coordinates = roi . get_bounds ( WEB_MERCATOR_CRS ) window = self . _window ( coordinates , to_round = False ) bands = bands or l...
The reason we want to treat this case in a special way is that there are cases where the rater is aligned so you need to be precise on which raster you want
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def get_tile ( self , x_tile , y_tile , zoom , bands = None , masked = None , resampling = Resampling . cubic ) : if self . crs == WEB_MERCATOR_CRS : return self . _get_tile_when_web_mercator_crs ( x_tile , y_tile , zoom , bands , masked , resampling ) roi = GeoVector . from_xyz ( x_tile , y_tile , zoom ) left , bottom...
Convert mercator tile to raster window .
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def colorize ( self , colormap , band_name = None , vmin = None , vmax = None ) : vmin = vmin if vmin is not None else min ( self . min ( ) ) vmax = vmax if vmax is not None else max ( self . max ( ) ) cmap = matplotlib . cm . get_cmap ( colormap ) band_index = 0 if band_name is None : if self . num_bands > 1 : warning...
Apply a colormap on a selected band .
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def chunks ( self , shape = 256 , pad = False ) : _self = self . _raster_backed_by_a_file ( ) if isinstance ( shape , int ) : shape = ( shape , shape ) ( width , height ) = shape col_steps = int ( _self . width / width ) row_steps = int ( _self . height / height ) col_extra_step = 1 if _self . width % width > 0 else 0 ...
This method returns GeoRaster chunks out of the original raster .
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def dissolve ( collection , aggfunc = None ) : new_properties = { } if aggfunc : temp_properties = defaultdict ( list ) for feature in collection : for key , value in feature . attributes . items ( ) : temp_properties [ key ] . append ( value ) for key , values in temp_properties . items ( ) : try : new_properties [ ke...
Dissolves features contained in a FeatureCollection and applies an aggregation function to its properties .
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def filter ( self , intersects ) : try : crs = self . crs vector = intersects . geometry if isinstance ( intersects , GeoFeature ) else intersects prepared_shape = prep ( vector . get_shape ( crs ) ) hits = [ ] for feature in self : target_shape = feature . geometry . get_shape ( crs ) if prepared_shape . overlaps ( ta...
Filter results that intersect a given GeoFeature or Vector .
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def sort ( self , by , desc = False ) : if callable ( by ) : key = by else : def key ( feature ) : return feature [ by ] sorted_features = sorted ( list ( self ) , reverse = desc , key = key ) return self . __class__ ( sorted_features )
Sorts by given property or function ascending or descending order .
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def groupby ( self , by ) : results = OrderedDict ( ) for feature in self : if callable ( by ) : value = by ( feature ) else : value = feature [ by ] results . setdefault ( value , [ ] ) . append ( feature ) if hasattr ( self , "_schema" ) : schema = getattr ( self , "_schema" ) return _CollectionGroupBy ( results , sc...
Groups collection using a value of a property .
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def dissolve ( self , by = None , aggfunc = None ) : if by : agg = partial ( dissolve , aggfunc = aggfunc ) return self . groupby ( by ) . agg ( agg ) else : return FeatureCollection ( [ dissolve ( self , aggfunc ) ] )
Dissolve geometries and rasters within groupby .
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def rasterize ( self , dest_resolution , * , polygonize_width = 0 , crs = WEB_MERCATOR_CRS , fill_value = None , bounds = None , dtype = None , ** polygonize_kwargs ) : from telluric . georaster import merge_all , MergeStrategy from telluric . rasterization import rasterize , NODATA_DEPRECATION_WARNING if not isinstanc...
Binarize a FeatureCollection and produce a raster with the target resolution .
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def save ( self , filename , driver = None , schema = None ) : if driver is None : driver = DRIVERS . get ( os . path . splitext ( filename ) [ - 1 ] ) if schema is None : schema = self . schema if driver == "GeoJSON" : with contextlib . suppress ( FileNotFoundError ) : os . remove ( filename ) crs = WGS84_CRS else : c...
Saves collection to file .
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def apply ( self , ** kwargs ) : def _apply ( f ) : properties = copy . deepcopy ( f . properties ) for prop , value in kwargs . items ( ) : if callable ( value ) : properties [ prop ] = value ( f ) else : properties [ prop ] = value return f . copy_with ( properties = properties ) new_fc = self . map ( _apply ) new_sc...
Return a new FeatureCollection with the results of applying the statements in the arguments to each element .
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def validate ( self ) : if self . _schema is not None : with MemoryFile ( ) as memfile : with memfile . open ( driver = "ESRI Shapefile" , schema = self . schema ) as target : for _item in self . _results : item = GeoFeature ( _item . geometry , _item . properties ) target . write ( item . to_record ( item . crs ) )
if schema exists we run shape file validation code of fiona by trying to save to in MemoryFile
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def open ( cls , filename , crs = None ) : with fiona . Env ( ) : with fiona . open ( filename , 'r' ) as source : original_crs = CRS ( source . crs ) schema = source . schema length = len ( source ) crs = crs or original_crs ret_val = cls ( filename , crs , schema , length ) return ret_val
Creates a FileCollection from a file in disk .
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def filter ( self , func ) : results = OrderedDict ( ) for name , group in self : if func ( group ) : results [ name ] = group return self . __class__ ( results )
Filter out Groups based on filtering function .
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def reset_context ( ** options ) : local_context . _options = { } local_context . _options . update ( options ) log . debug ( "New TelluricContext context %r created" , local_context . _options )
Reset context to default .
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def get_context ( ) : if not local_context . _options : raise TelluricContextError ( "TelluricContext context not exists" ) else : log . debug ( "Got a copy of context %r options" , local_context . _options ) return local_context . _options . copy ( )
Get a mapping of current options .
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def set_context ( ** options ) : if not local_context . _options : raise TelluricContextError ( "TelluricContext context not exists" ) else : local_context . _options . update ( options ) log . debug ( "Updated existing %r with options %r" , local_context . _options , options )
Set options in the existing context .
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def transform_properties ( properties , schema ) : new_properties = properties . copy ( ) for prop_value , ( prop_name , prop_type ) in zip ( new_properties . values ( ) , schema [ "properties" ] . items ( ) ) : if prop_value is None : continue elif prop_type == "time" : new_properties [ prop_name ] = parse_date ( prop...
Transform properties types according to a schema .
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def serialize_properties ( properties ) : new_properties = properties . copy ( ) for attr_name , attr_value in new_properties . items ( ) : if isinstance ( attr_value , datetime ) : new_properties [ attr_name ] = attr_value . isoformat ( ) elif not isinstance ( attr_value , ( dict , list , tuple , str , int , float , b...
Serialize properties .
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def from_record ( cls , record , crs , schema = None ) : properties = cls . _to_properties ( record , schema ) vector = GeoVector ( shape ( record [ 'geometry' ] ) , crs ) if record . get ( 'raster' ) : assets = { k : dict ( type = RASTER_TYPE , product = 'visual' , ** v ) for k , v in record . get ( 'raster' ) . items...
Create GeoFeature from a record .
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def copy_with ( self , geometry = None , properties = None , assets = None ) : def copy_assets_object ( asset ) : obj = asset . get ( "__object" ) if hasattr ( "copy" , obj ) : new_obj = obj . copy ( ) if obj : asset [ "__object" ] = new_obj geometry = geometry or self . geometry . copy ( ) new_properties = copy . deep...
Generate a new GeoFeature with different geometry or preperties .
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def from_raster ( cls , raster , properties , product = 'visual' ) : footprint = raster . footprint ( ) assets = raster . to_assets ( product = product ) return cls ( footprint , properties , assets )
Initialize a GeoFeature object with a GeoRaster
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def has_raster ( self ) : return any ( asset . get ( 'type' ) == RASTER_TYPE for asset in self . assets . values ( ) )
True if any of the assets is type raster .
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def transform ( shape , source_crs , destination_crs = None , src_affine = None , dst_affine = None ) : if destination_crs is None : destination_crs = WGS84_CRS if src_affine is not None : shape = ops . transform ( lambda r , q : ~ src_affine * ( r , q ) , shape ) shape = generate_transform ( source_crs , destination_c...
Transforms shape from one CRS to another .
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def simple_plot ( feature , * , mp = None , ** map_kwargs ) : from telluric . collections import BaseCollection if mp is None : mp = folium . Map ( tiles = "Stamen Terrain" , ** map_kwargs ) if feature . is_empty : warnings . warn ( "The geometry is empty." ) else : if isinstance ( feature , BaseCollection ) : feature ...
Plots a GeoVector in a simple Folium map .
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def zoom_level_from_geometry ( geometry , splits = 4 ) : from telluric . vectors import generate_tile_coordinates levels = [ ] for chunk in generate_tile_coordinates ( geometry , ( splits , splits ) ) : levels . append ( mercantile . bounding_tile ( * chunk . get_shape ( WGS84_CRS ) . bounds ) . z ) return median_low (...
Generate optimum zoom level for geometry .
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def layer_from_element ( element , style_function = None ) : from telluric . collections import BaseCollection if isinstance ( element , BaseCollection ) : styled_element = element . map ( lambda feat : style_element ( feat , style_function ) ) else : styled_element = style_element ( element , style_function ) return G...
Return Leaflet layer from shape .
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def plot ( feature , mp = None , style_function = None , ** map_kwargs ) : map_kwargs . setdefault ( 'basemap' , basemaps . Stamen . Terrain ) if feature . is_empty : warnings . warn ( "The geometry is empty." ) mp = Map ( ** map_kwargs ) if mp is None else mp else : if mp is None : center = feature . envelope . centro...
Plots a GeoVector in an ipyleaflet map .
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def tileserver_optimized_raster ( src , dest ) : src_raster = tl . GeoRaster2 . open ( src ) bounding_box = src_raster . footprint ( ) . get_shape ( tl . constants . WGS84_CRS ) . bounds tile = mercantile . bounding_tile ( * bounding_box ) dest_resolution = mercator_upper_zoom_level ( src_raster ) bounds = tl . GeoVect...
This method converts a raster to a tileserver optimized raster . The method will reproject the raster to align to the xyz system in resolution and projection It will also create overviews And finally it will arragne the raster in a cog way . You could take the dest file upload it to a web server that supports ranges an...
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def get_dimension ( geometry ) : coordinates = geometry [ "coordinates" ] type_ = geometry [ "type" ] if type_ in ( 'Point' , ) : return len ( coordinates ) elif type_ in ( 'LineString' , 'MultiPoint' ) : return len ( coordinates [ 0 ] ) elif type_ in ( 'Polygon' , 'MultiLineString' ) : return len ( coordinates [ 0 ] [...
Gets the dimension of a Fiona - like geometry element .
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def from_geojson ( cls , filename ) : with open ( filename ) as fd : geometry = json . load ( fd ) if 'type' not in geometry : raise TypeError ( "%s is not a valid geojson." % ( filename , ) ) return cls ( to_shape ( geometry ) , WGS84_CRS )
Load vector from geojson .
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def to_geojson ( self , filename ) : with open ( filename , 'w' ) as fd : json . dump ( self . to_record ( WGS84_CRS ) , fd )
Save vector as geojson .
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def from_bounds ( cls , xmin , ymin , xmax , ymax , crs = DEFAULT_CRS ) : return cls ( Polygon . from_bounds ( xmin , ymin , xmax , ymax ) , crs )
Creates GeoVector object from bounds .
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def from_xyz ( cls , x , y , z ) : bb = xy_bounds ( x , y , z ) return cls . from_bounds ( xmin = bb . left , ymin = bb . bottom , xmax = bb . right , ymax = bb . top , crs = WEB_MERCATOR_CRS )
Creates GeoVector from Mercator slippy map values .
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def cascaded_union ( cls , vectors , dst_crs , prevalidate = False ) : try : shapes = [ geometry . get_shape ( dst_crs ) for geometry in vectors ] if prevalidate : if not all ( [ sh . is_valid for sh in shapes ] ) : warnings . warn ( "Some invalid shapes found, discarding them." ) except IndexError : crs = DEFAULT_CRS ...
Generate a GeoVector from the cascade union of the impute vectors .
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def from_record ( cls , record , crs ) : if 'type' not in record : raise TypeError ( "The data isn't a valid record." ) return cls ( to_shape ( record ) , crs )
Load vector from record .
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def get_bounding_box ( self , crs ) : return self . from_bounds ( * self . get_bounds ( crs ) , crs = crs )
Gets bounding box as GeoVector in a specified CRS .
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def polygonize ( self , width , cap_style_line = CAP_STYLE . flat , cap_style_point = CAP_STYLE . round ) : shape = self . _shape if isinstance ( shape , ( LineString , MultiLineString ) ) : return self . __class__ ( shape . buffer ( width / 2 , cap_style = cap_style_line ) , self . crs ) elif isinstance ( shape , ( Po...
Turns line or point into a buffered polygon .
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def tiles ( self , zooms , truncate = False ) : west , south , east , north = self . get_bounds ( WGS84_CRS ) return tiles ( west , south , east , north , zooms , truncate )
Iterator over the tiles intersecting the bounding box of the vector
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def _join_masks_from_masked_array ( data ) : if not isinstance ( data . mask , np . ndarray ) : mask = np . empty ( data . data . shape , dtype = np . bool ) mask . fill ( data . mask ) return mask mask = data . mask [ 0 ] . copy ( ) for i in range ( 1 , len ( data . mask ) ) : mask = np . logical_or ( mask , data . ma...
Union of masks .
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def _creation_options_for_cog ( creation_options , source_profile , blocksize ) : if not ( creation_options ) : creation_options = { } creation_options [ "blocksize" ] = blocksize creation_options [ "tiled" ] = True defaults = { "nodata" : None , "compress" : "lzw" } for key in [ "nodata" , "compress" ] : if key not in...
it uses the profile of the source raster override anything using the creation_options and guarantees we will have tiled raster and blocksize
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def convert_to_cog ( source_file , destination_file , resampling = rasterio . enums . Resampling . gauss , blocksize = 256 , overview_blocksize = 256 , creation_options = None ) : with rasterio . open ( source_file ) as src : source_profile = src . profile creation_options = _creation_options_for_cog ( creation_options...
Convert source file to a Cloud Optimized GeoTiff new file .
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def warp ( source_file , destination_file , dst_crs = None , resolution = None , dimensions = None , src_bounds = None , dst_bounds = None , src_nodata = None , dst_nodata = None , target_aligned_pixels = False , check_invert_proj = True , creation_options = None , resampling = Resampling . cubic , ** kwargs ) : with r...
Warp a raster dataset .
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def build_overviews ( source_file , factors = None , minsize = 256 , external = False , blocksize = 256 , interleave = 'pixel' , compress = 'lzw' , resampling = Resampling . gauss , ** kwargs ) : with rasterio . open ( source_file , 'r+' ) as dst : if factors is None : factors = _calc_overviews_factors ( SimpleNamespac...
Build overviews at one or more decimation factors for all bands of the dataset .
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def build_vrt ( source_file , destination_file , ** kwargs ) : with rasterio . open ( source_file ) as src : vrt_doc = boundless_vrt_doc ( src , ** kwargs ) . tostring ( ) with open ( destination_file , 'wb' ) as dst : dst . write ( vrt_doc ) return destination_file
Make a VRT XML document and write it in file .
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def stretch_histogram ( img , dark_clip_percentile = None , bright_clip_percentile = None , dark_clip_value = None , bright_clip_value = None , ignore_zero = True ) : if ( dark_clip_percentile is not None and dark_clip_value is not None ) or ( bright_clip_percentile is not None and bright_clip_value is not None ) : rai...
Stretch img histogram .
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def _distribution_info ( self ) : print ( 'Gathering information...' ) system = platform . system ( ) system = 'cygwin' if 'CYGWIN' in system else system processor = platform . processor ( ) machine = '64bit' if sys . maxsize > 2 ** 32 else '32bit' print ( 'SYSTEM: ' , system ) print ( 'PROCESSOR:' , processor ) prin...
Creates the distribution name and the expected extension for the CSPICE package and returns it .
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def _download ( self ) : if ssl . OPENSSL_VERSION < 'OpenSSL 1.0.1g' : import urllib3 . contrib . pyopenssl urllib3 . contrib . pyopenssl . inject_into_urllib3 ( ) import certifi import urllib3 try : proxies = { } for key , value in os . environ . items ( ) : if '_proxy' in key . lower ( ) : proxies [ key . lower ( ) ....
Support function that encapsulates the OpenSSL transfer of the CSPICE package to the self . _local io . ByteIO stream .
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def _unpack ( self ) : if self . _ext == 'zip' : with ZipFile ( self . _local , 'r' ) as archive : archive . extractall ( self . _root ) else : cmd = 'gunzip | tar xC ' + self . _root proc = subprocess . Popen ( cmd , shell = True , stdin = subprocess . PIPE ) proc . stdin . write ( self . _local . read ( ) ) self . _l...
Unpacks the CSPICE package on the given root directory . Note that Package could either be the zipfile . ZipFile class for Windows platforms or tarfile . TarFile for other platforms .
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def spiceErrorCheck ( f ) : @ functools . wraps ( f ) def with_errcheck ( * args , ** kwargs ) : try : res = f ( * args , ** kwargs ) checkForSpiceError ( f ) return res except : raise return with_errcheck
Decorator for spiceypy hooking into spice error system . If an error is detected an output similar to outmsg
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def spiceFoundExceptionThrower ( f ) : @ functools . wraps ( f ) def wrapper ( * args , ** kwargs ) : res = f ( * args , ** kwargs ) if config . catch_false_founds : found = res [ - 1 ] if isinstance ( found , bool ) and not found : raise stypes . SpiceyError ( "Spice returns not found for function: {}" . format ( f . ...
Decorator for wrapping functions that use status codes
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def appndc ( item , cell ) : assert isinstance ( cell , stypes . SpiceCell ) if isinstance ( item , list ) : for c in item : libspice . appndc_c ( stypes . stringToCharP ( c ) , cell ) else : item = stypes . stringToCharP ( item ) libspice . appndc_c ( item , cell )
Append an item to a character cell .
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def appndd ( item , cell ) : assert isinstance ( cell , stypes . SpiceCell ) if hasattr ( item , "__iter__" ) : for d in item : libspice . appndd_c ( ctypes . c_double ( d ) , cell ) else : item = ctypes . c_double ( item ) libspice . appndd_c ( item , cell )
Append an item to a double precision cell .
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def appndi ( item , cell ) : assert isinstance ( cell , stypes . SpiceCell ) if hasattr ( item , "__iter__" ) : for i in item : libspice . appndi_c ( ctypes . c_int ( i ) , cell ) else : item = ctypes . c_int ( item ) libspice . appndi_c ( item , cell )
Append an item to an integer cell .
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def axisar ( axis , angle ) : axis = stypes . toDoubleVector ( axis ) angle = ctypes . c_double ( angle ) r = stypes . emptyDoubleMatrix ( ) libspice . axisar_c ( axis , angle , r ) return stypes . cMatrixToNumpy ( r )
Construct a rotation matrix that rotates vectors by a specified angle about a specified axis .
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def badkpv ( caller , name , comp , insize , divby , intype ) : caller = stypes . stringToCharP ( caller ) name = stypes . stringToCharP ( name ) comp = stypes . stringToCharP ( comp ) insize = ctypes . c_int ( insize ) divby = ctypes . c_int ( divby ) intype = ctypes . c_char ( intype . encode ( encoding = 'UTF-8' ) )...
Determine if a kernel pool variable is present and if so that it has the correct size and type .
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def bltfrm ( frmcls , outCell = None ) : frmcls = ctypes . c_int ( frmcls ) if not outCell : outCell = stypes . SPICEINT_CELL ( 1000 ) libspice . bltfrm_c ( frmcls , outCell ) return outCell
Return a SPICE set containing the frame IDs of all built - in frames of a specified class .