@@ -8,7 +8,8 @@ def __init__(self, dataframe, demand_col=None, demand_name=None, supply_name=Non
88 """
99 An object that stores the relationship between a set of demand locations and a set of supply locations.
1010 Use this initializer if the coverage matrix has already been created, otherwise this can be created from two
11- geodataframes using the :meth:`~allagash.coverage.Coverage.from_geodataframes` factory method.
11+ geodataframes using the :meth:`~allagash.coverage.Coverage.from_geodataframes` or
12+ :meth:`~allagash.coverage.Coverage.from_spatially_enabled_dataframes` factory methods.
1213
1314 .. code-block:: python
1415
@@ -115,7 +116,9 @@ def from_geodataframes(cls, demand_df, supply_df, demand_id_col, supply_id_col,
115116 locations. Required if generating partial coverage.
116117 :param str coverage_type: (optional) The type of coverage this represents. If not supplied, the default is
117118 "binary". Options are "binary" and "partial".
118- :return:
119+
120+ :return: The coverage
121+ :rtype: ~allagash.coverage.Coverage
119122 """
120123 cls ._validate_from_geodataframes (coverage_type , demand_col , demand_df , demand_id_col , demand_name , supply_df ,
121124 supply_id_col )
@@ -147,6 +150,61 @@ def from_geodataframes(cls, demand_df, supply_df, demand_id_col, supply_id_col,
147150 supply_name = supply_name ,
148151 coverage_type = coverage_type )
149152
153+ @classmethod
154+ def from_spatially_enabled_dataframes (cls , demand_df , supply_df , demand_id_col , supply_id_col , demand_name = None ,
155+ supply_name = None , demand_col = None , coverage_type = "binary" ,
156+ demand_geometry_col = 'SHAPE' , supply_geometry_col = 'SHAPE' ):
157+ """
158+ Creates a new Coverage from two spatially enabled (arcgis) dataframes representing the demand and supply locations.
159+ The coverage is determined by intersecting the two dataframes.
160+
161+ :param ~pandas.DataFrame demand_df: The spatially enabled dataframe containing the demand locations
162+ :param ~pandas.DataFrame supply_df: The spatially enavled dataframe containing the supply locations
163+ :param str demand_id_col: The name of the column that has unique identifiers for the demand locations
164+ :param str supply_id_col: The name of the column that has unique identifiers for the supply locations
165+ :param str demand_name: (optional) The name of the demand to use. If not supplied, a random name is generated.
166+ :param str supply_name: (optional) The name of the supply to use. If not supplied, a random name is generated.
167+ :param str demand_col: (optional) The name of the column that stores the amount of demand for the demand
168+ locations. Required if generating partial coverage.
169+ :param str coverage_type: (optional) The type of coverage this represents. If not supplied, the default is
170+ "binary". Options are "binary" and "partial".
171+ :param str demand_geometry_col: (optional) The name of the field storing the geometry in the demand dataframe.
172+ If not supplied, the default is "SHAPE".
173+ :param str supply_geometry_col: (optional) The name of the field storing the geometry in the supply dataframe.
174+ If not supplied, the default is "SHAPE".
175+ :return: The coverage
176+ :rtype: ~allagash.coverage.Coverage
177+ """
178+
179+ cls ._validate_from_spatially_enabled_dataframes (coverage_type , demand_col , demand_df , demand_id_col , demand_name , supply_df ,
180+ supply_id_col , demand_geometry_col , supply_geometry_col )
181+ data = []
182+ if coverage_type .lower () == 'binary' :
183+ for index , row in demand_df .iterrows ():
184+ contains = supply_df [supply_geometry_col ].geom .contains (row [demand_geometry_col ]).tolist ()
185+ if demand_col :
186+ contains .insert (0 , row [demand_col ])
187+ data .append (contains )
188+ elif coverage_type .lower () == 'partial' :
189+ for index , row in demand_df .iterrows ():
190+ demand_area = row [demand_geometry_col ].area
191+ intersection_area = supply_df [supply_geometry_col ].geom .intersect (row [demand_geometry_col ]).geom .area
192+ partial_coverage = ((intersection_area / demand_area ) * row [demand_col ]).tolist ()
193+ if demand_col :
194+ partial_coverage .insert (0 , row [demand_col ])
195+ data .append (partial_coverage )
196+ else :
197+ raise ValueError (f"Invalid coverage type '{ coverage_type } )
198+ columns = supply_df [supply_id_col ].tolist ()
199+ if demand_col :
200+ columns .insert (0 , demand_col )
201+ df = pd .DataFrame .from_records (data , index = demand_df [demand_id_col ], columns = columns )
202+ return Coverage (df ,
203+ demand_col = demand_col ,
204+ demand_name = demand_name ,
205+ supply_name = supply_name ,
206+ coverage_type = coverage_type )
207+
150208 @classmethod
151209 def _validate_from_geodataframes (cls , coverage_type , demand_col , demand_df , demand_id_col , demand_name , supply_df ,
152210 supply_id_col ):
@@ -172,3 +230,33 @@ def _validate_from_geodataframes(cls, coverage_type, demand_col, demand_df, dema
172230 raise ValueError (f"Invalid coverage type '{ coverage_type } )
173231 if coverage_type .lower () == "partial" and demand_col is None :
174232 raise ValueError (f"demand_col is required when generating partial coverage" )
233+
234+ @classmethod
235+ def _validate_from_spatially_enabled_dataframes (cls , coverage_type , demand_col , demand_df , demand_id_col , demand_name , supply_df ,
236+ supply_id_col , demand_geometry_col , supply_geometry_col ):
237+ if not isinstance (demand_df , pd .DataFrame ):
238+ raise TypeError (f"Expected 'Dataframe' type for demand_df, got '{ type (demand_df )} )
239+ if not isinstance (supply_df , pd .DataFrame ):
240+ raise TypeError (f"Expected 'Dataframe' type for supply_df, got '{ type (supply_df )} )
241+ if not isinstance (demand_id_col , str ):
242+ raise TypeError (f"Expected 'str' type for demand_id_col, got '{ type (demand_id_col )} )
243+ if not isinstance (supply_id_col , str ):
244+ raise TypeError (f"Expected 'str' type for demand_id_col, got '{ type (supply_id_col )} )
245+ if not isinstance (demand_name , str ) and demand_name is not None :
246+ raise TypeError (f"Expected 'str' type for demand_name, got '{ type (demand_name )} )
247+ if not isinstance (coverage_type , str ):
248+ raise TypeError (f"Expected 'str' type for coverage_type, got '{ type (coverage_type )} )
249+ if demand_col and demand_col not in demand_df .columns :
250+ raise ValueError (f"'{ demand_col } )
251+ if demand_id_col and demand_id_col not in demand_df .columns :
252+ raise ValueError (f"'{ demand_id_col } )
253+ if supply_id_col and supply_id_col not in supply_df .columns :
254+ raise ValueError (f"'{ supply_id_col } )
255+ if demand_geometry_col and demand_geometry_col not in demand_df .columns :
256+ raise ValueError (f"'{ demand_geometry_col } )
257+ if supply_geometry_col and supply_geometry_col not in supply_df .columns :
258+ raise ValueError (f"'{ supply_geometry_col } )
259+ if coverage_type .lower () not in "binary" , "partial" ):
260+ raise ValueError (f"Invalid coverage type '{ coverage_type } )
261+ if coverage_type .lower () == "partial" and demand_col is None :
262+ raise ValueError (f"demand_col is required when generating partial coverage" )
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