def OverlayMaps(self, Path, BaseMapF, ExcludedValue, OccupiedCellsOnly, SavePath):
"""
==================================================================
OverlayMaps(self, Path, BaseMapF, ExcludedValue, OccupiedCellsOnly, SavePath)
==================================================================
OverlayMaps method reads all the maps in the folder given by Path
input and overlay them with the basemap and for each value in the basemap
it create a dictionary with the intersected values from all maps
Inputs:
1-Path
[String] a path to the folder includng the maps.
2-BaseMapF:
[String] a path includng the name of the ASCII and extention like
path="data/cropped.asc"
3-ExcludedValue:
[Numeric] values you want to exclude from exteacted values
5-OccupiedCellsOnly:
[Bool] if you want to count only cells that is not ExcludedValue.
6-SavePath:
[String] a path to the folder to save a text file for each
value in the base map including all the intersected values
from other maps.
Outputs:
1- ExtractedValues:
[Dict] dictonary with a list of values in the basemap as keys
and for each key a list of all the intersected values in the
maps from the path
2- NonZeroCells:
[dataframe] dataframe with the first column as the "file" name
and the second column is the number of cells in each map
"""
self.DepthValues, NonZeroCells = Raster.OverlayMaps(Path, BaseMapF, self.DepthPrefix,
ExcludedValue, self.Compressed,OccupiedCellsOnly)
# NonZeroCells dataframe with the first column as the "file" name and the second column
# is the number of cells in each map
NonZeroCells['days'] = [int(i[len(self.DepthPrefix):-4]) for i in NonZeroCells['files'].tolist()]
# get the numbe of inundated cells in the Event index data frame
self.EventIndex['cells'] = 0
for i in range(len(NonZeroCells)):
# get the location in the EventIndex dataframe
try:
loc = np.where(NonZeroCells.loc[i,'days'] == self.EventIndex.loc[:,"id"] )[0][0]
except IndexError:
# if it does not find the event in the eventindex table ignore
continue
# store number of cells
self.EventIndex.loc[loc,'cells'] = NonZeroCells.loc[i,'cells']
# save depths of each sub-basin
inundatedSubs = list(self.DepthValues.keys())
for i in range(len(inundatedSubs)):
np.savetxt(SavePath +"/" + str(inundatedSubs[i]) + ".txt",
self.DepthValues[inundatedSubs[i]],fmt="%4.2f")
"""
# import os
import numpy as np
from Hapi.raster import Raster as R
Path = "data/GIS/ZonalStatistics/"
SavePath = Path
BaseMapF = Path + "Polygons.tif"
ExcludedValue = 0
Compressed = True
OccupiedCellsOnly = False
# one map
ExtractedValues, NonZeroCells = R.OverlayMap(Path + "data/Map1.zip", BaseMapF,
ExcludedValue, Compressed,
OccupiedCellsOnly)
MapPrefix = "Map"
# several maps
ExtractedValues, NonZeroCells = R.OverlayMaps(Path + "data", BaseMapF,
MapPrefix, ExcludedValue,
Compressed, OccupiedCellsOnly)
# save extracted values in different files
Polygons = list(ExtractedValues.keys())
for i in range(len(Polygons)):
np.savetxt(SavePath + "/" + str(Polygons[i]) + ".txt",
ExtractedValues[Polygons[i]],
fmt="%4.2f")
