Skip to content

Commit

Permalink
Merge pull request #97 from osundwajeff/water-sanitation
Browse files Browse the repository at this point in the history 
Water sanitation
  • Loading branch information
@osundwajeff
osundwajeff authored Aug 7, 2024
2 parents d81a166 + bc936ec commit ad39807
Show file tree
Hide file tree
Showing 3 changed files with 757 additions and 468 deletions.
Binary file modified gender_indicator_tool.zip
View file
Binary file not shown.
216 changes: 195 additions & 21 deletions gender_indicator_tool/gender_indicator_tool.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -351,6 +351,9 @@ def run(self):
###### TAB 4.6 - Facility, conflict, and violence
#self.dlg.FCV_Set_PB.clicked.connect(lambda: self.RasterizeSet(5))
self.dlg.FCV_Execute_PB.clicked.connect(lambda: self.Rasterize(6))

###### TAB 4.7 - Water and Sanitation
self.dlg.WAS_Execute_PB.clicked.connect(lambda: self.Rasterize(7))

###### TAB 4.7 - Aggregate
self.dlg.WLK_Aggregate_TB.clicked.connect(lambda: self.getFile(11))
Expand All @@ -359,12 +362,13 @@ def run(self):
self.dlg.ENV_Aggregate_TB.clicked.connect(lambda: self.getFile(21))
self.dlg.EDU_Aggregate_TB.clicked.connect(lambda: self.getFile(0))
self.dlg.FCV_Aggregate_TB.clicked.connect(lambda: self.getFile(26))
self.dlg.WAS_Aggregate_TB.clicked.connect(lambda: self.getFile(27))
self.dlg.PlaceCharacterization_AggregateExecute_PB.clicked.connect(
self.placeCharacterizationAggregation
)

## TAB 5 - Dimension Aggregation ************************************************************************
self.dlg.ID_Aggregate_TB.clicked.connect(lambda: self.getFile(22))
#self.dlg.ID_Aggregate_TB.clicked.connect(lambda: self.getFile(22))
self.dlg.CD_Aggregate_TB.clicked.connect(lambda: self.getFile(23))
self.dlg.AD_Aggregate_TB.clicked.connect(lambda: self.getFile(24))
self.dlg.PD_Aggregate_TB.clicked.connect(lambda: self.getFile(25))
Expand Down Expand Up @@ -452,6 +456,9 @@ def getFile(self, button_num):

elif button_num == 26:
self.dlg.FCV_Aggregate_Field.setText(response[0])

elif button_num == 27:
self.dlg.WAS_Aggregate_Field.setText(response[0])

def getFolder(self, button_num):
"""
Expand All @@ -476,7 +483,7 @@ def RasterizeSet(self, factor_no):
Contextual Dimension
- Workplace Discrimination
- Regulatory Frameworks(RF)
- Access to Finance
- Financial Inclusion
Place Characterization Dimension
- Education
- Safety
Expand Down Expand Up @@ -627,10 +634,9 @@ def Rasterize(self, factor_no):
- Financial Inclusion
Place Characterization Dimension
- Education
- Security
- Income Level
- Fragility, conflict, and violence(FCV)
- Digital Inclusion
- Water and Sanitation (WAS)
"""
current_script_path = os.path.dirname(os.path.abspath(__file__))
workingDir = self.dlg.workingDir_Field.text()
Expand Down Expand Up @@ -705,13 +711,23 @@ def Rasterize(self, factor_no):

elif factor_no == 6:
csvFile = self.dlg.FCV_Input_Field.filePath()
csvFile = f"file://{csvFile}?delimiter=,&yField=latitude&xField=longitude"
csvFile = f"file:///{csvFile.replace(os.sep, '/')}?type=csv&maxFields=10000&detectTypes=yes&xField=longitude&yField=latitude&crs=EPSG:4326&spatialIndex=no&subsetIndex=no&watchFile=no"
rasField = "rasField"
self.dlg.FCV_status.setText("Variables Set")
self.dlg.FCV_status.repaint()
time.sleep(0.5)
self.dlg.FCV_status.setText("Processing...")
self.dlg.FCV_status.repaint()

elif factor_no == 7:
pointlayer = self.dlg.WAS_Input_Field.filePath()
#rasField = self.dlg.WAS_rasField_CB.currentText()
rasField = "rasField"
self.dlg.WAS_status.setText("Variables Set")
self.dlg.WAS_status.repaint()
time.sleep(0.5)
self.dlg.WAS_status.setText("Processing...")
self.dlg.WAS_status.repaint()

# Convert countryLayer data to UTM CRS
self.convertCRS(countryLayer, UTM_crs)
Expand Down Expand Up @@ -744,11 +760,14 @@ def Rasterize(self, factor_no):
self.convertCRS(polygonlayer, UTM_crs)
else:
pass
elif factor_no in [7]:
self.convertCRS(pointlayer, UTM_crs)
else:
self.convertCRS(polygonlayer, UTM_crs)

if rasField not in shp_utm.columns:
shp_utm[rasField] = [0]
shp_utm[rasField] = [0] * len(shp_utm)

shp_utm[rasField] = shp_utm[rasField].astype(float)

# Set variables required to conduct standardization of values
Expand Down Expand Up @@ -1476,6 +1495,157 @@ def Rasterize(self, factor_no):
self.dlg.FCV_status.setText("Processing has been completed!")
self.dlg.FCV_status.repaint()

elif factor_no == 7:
shp_utm[rasField] = 99
shp_utm[rasField] = (shp_utm[rasField] - Rmin) / (Rmax - Rmin) * m_max
pointUTM = QgsVectorLayer(shp_utm.to_json(), "pointUTM", "ogr")
#
#shp_utm[rasField] = [0]

#for i in roadType_Score:
# shp_utm.loc[shp_utm[roadTypeField] == i[0], "Score"] = i[1]

#shp_utm[rasField] = shp_utm[rasField].astype(int)
gridExtent = countryUTMLayerBuf.extent()
grid_params = {
'TYPE': 2, # Rectangle (polygon)
'EXTENT': gridExtent,
'HSPACING': 100, # Horizontal spacing
'VSPACING': 100, # Vertical spacing
'CRS': UTM_crs,
'OUTPUT': "memory:"
}

grid_result = processing.run('native:creategrid', grid_params)
grid_layer = grid_result['OUTPUT']

field_name = 'reclass_va'
if not grid_layer.fields().indexFromName(field_name) >= 0:
grid_layer.dataProvider().addAttributes([QgsField(field_name, QVariant.Int)])
grid_layer.updateFields()

self.dlg.WAS_status.setText("Processing...")
self.dlg.WAS_status.repaint()

#dif_out = f"{workingDir}/temp/tempBuf.shp"

Buffer = processing.run(
"native:buffer",
{
"INPUT": pointUTM,
"DISTANCE": 250,
"SEGMENTS": 5,
"END_CAP_STYLE": 0,
"JOIN_STYLE": 0,
"MITER_LIMIT": 2,
"DISSOLVE": False,
"SEPARATE_DISJOINT": False,
"OUTPUT": "memory:",
},
)

# Count the number of buffers within each grid cell
buffer_layer = Buffer['OUTPUT']
index = QgsSpatialIndex(buffer_layer.getFeatures())
reclass_vals = {}

for grid_feat in grid_layer.getFeatures():
intersecting_ids = index.intersects(grid_feat.geometry().boundingBox())
num_waterpoints = len(intersecting_ids)

if num_waterpoints > 2:
reclass_val = 5
elif num_waterpoints == 1:
reclass_val = 3
else:
reclass_val = 0

reclass_vals[grid_feat.id()] = reclass_val

grid_layer.startEditing()
for grid_feat in grid_layer.getFeatures():
grid_layer.changeAttributeValue(grid_feat.id(), grid_layer.fields().indexFromName(field_name),
reclass_vals[grid_feat.id()])
grid_layer.commitChanges()

#dif_out = f"{workingDir}/{tempDir}/Dif.shp"

Difference = processing.run(
"native:difference",
{
"INPUT": countryUTMLayerBuf,
"OVERLAY": grid_layer,
"OUTPUT": "memory:",
"GRID_SIZE": None,
},
)

difference = Difference["OUTPUT"]

Merge = processing.run(
"native:mergevectorlayers",
{"LAYERS": [grid_layer, difference], "CRS": UTM_crs, "OUTPUT": "memory:"},
)

merge = Merge["OUTPUT"]

mergeClip = processing.run(
"native:clip",
{
"INPUT": merge,
"OVERLAY": countryUTMLayerBuf,
"OUTPUT": "memory:",
}
)

mergeOutput = mergeClip["OUTPUT"]

# Get the width and height of the extent
extent = mergeOutput.extent()
raster_width = int(extent.width() / pixelSize)
raster_height = int(extent.height() / pixelSize)

Dimension = "Place Characterization"
if os.path.exists(Dimension):
os.chdir(Dimension)
else:
os.mkdir(Dimension)
os.chdir(Dimension)

rasOutput = self.dlg.WAS_Output_Field.text()

rasterize = processing.run(
"gdal:rasterize",
{
"INPUT": mergeOutput,
"FIELD": field_name,
"BURN": 0,
"USE_Z": False,
"UNITS": 0,
"WIDTH": raster_width,
"HEIGHT": raster_height,
"EXTENT": None,
"NODATA": None,
"OPTIONS": "",
"DATA_TYPE": 5,
"INIT": None,
"INVERT": False,
"EXTRA": "",
"OUTPUT": rasOutput,
},
)

#self.dlg.WLK_Output_Field_2.setText(f"{workingDir}{Dimension}/{rasOutput}")

styleTemplate = f"{current_script_path}/Style/{Dimension}.qml"
styleFileDestination = f"{workingDir}{Dimension}/"
styleFile = f"{rasOutput.split('.')[0]}.qml"

shutil.copy(styleTemplate, os.path.join(styleFileDestination, styleFile))

self.dlg.WAS_status.setText("Processing Complete!")
self.dlg.WAS_status.repaint()

def ServiceArea(self, factor_no):
"""
This function is used to conduct a service area network analysis facilitated using Openrouteservices' (ORS) isochrones service. Isochrones are derived from the OpenStreetMap (OSM) road network
Expand Down Expand Up @@ -5047,6 +5217,7 @@ def placeCharacterizationAggregation(self):
ENV_ras = self.dlg.ENV_Aggregate_Field.text().strip(" ")
EDU_ras = self.dlg.EDU_Aggregate_Field.text().strip(" ")
FCV_ras = self.dlg.FCV_Aggregate_Field.text().strip(" ")
WAS_ras = self.dlg.WAS_Aggregate_Field.text().strip(" ")

WLK_weight = self.dlg.WLK_Aggregate_SB.value()
# CYC_weight = self.dlg.CYC_Aggregate_SB.value()
Expand All @@ -5055,6 +5226,7 @@ def placeCharacterizationAggregation(self):
ENV_weight = self.dlg.ENV_Aggregate_SB.value()
EDU_weight = self.dlg.EDU_Aggregate_SB.value()
FCV_weight = self.dlg.FCV_Aggregate_SB.value()
WAS_weight = self.dlg.WAS_Aggregate_SB.value()

# OUTPUT
aggregation = self.dlg.PlaceCharacterization_AggregateOutput_Field.text()
Expand All @@ -5066,6 +5238,7 @@ def placeCharacterizationAggregation(self):
ENV_ras,
EDU_ras,
FCV_ras,
WAS_ras,
]
factorWeighting = [
WLK_weight,
Expand All @@ -5074,6 +5247,7 @@ def placeCharacterizationAggregation(self):
ENV_weight,
EDU_weight,
FCV_weight,
WAS_weight,
]
non_empty_count = sum(1 for item in rasLayers if item != "")

Expand Down Expand Up @@ -5122,6 +5296,10 @@ def placeCharacterizationAggregation(self):
with rasterio.open(rasLayers[5]) as src:
FCV_ras = src.read(1)
FCV_weight = factorWeighting[5]

with rasterio.open(rasLayers[6]) as src:
WAS_ras = src.read(1)
WAS_weight = factorWeighting[6]

# Raster Calculation

Expand All @@ -5132,6 +5310,7 @@ def placeCharacterizationAggregation(self):
+ (ENV_ras * ENV_weight / 100)
+ (EDU_ras * EDU_weight / 100)
+ (FCV_ras * FCV_weight / 100)
+ (WAS_ras * WAS_weight / 100)
)

meta1.update(dtype=rasterio.float32)
Expand Down Expand Up @@ -5202,21 +5381,21 @@ def dimesnionsAggregation(self):
os.chdir(workingDir)

# INPUT
ID_ras = self.dlg.ID_Aggregate_Field.text().strip(" ")
#ID_ras = self.dlg.ID_Aggregate_Field.text().strip(" ")
CD_ras = self.dlg.CD_Aggregate_Field.text().strip(" ")
AD_ras = self.dlg.AD_Aggregate_Field.text().strip(" ")
PD_ras = self.dlg.PD_Aggregate_Field.text().strip(" ")

ID_weight = self.dlg.ID_Aggregate_SB.value()
#ID_weight = self.dlg.ID_Aggregate_SB.value()
CD_weight = self.dlg.CD_Aggregate_SB.value()
AD_weight = self.dlg.AD_Aggregate_SB.value()
PD_weight = self.dlg.PD_Aggregate_SB.value()

# OUTPUT
aggregation = self.dlg.Dimensions_AggregateOutput_Field.text()

rasLayers = [ID_ras, CD_ras, AD_ras, PD_ras]
dimensionWeighting = [ID_weight, CD_weight, AD_weight, PD_weight]
rasLayers = [CD_ras, AD_ras, PD_ras]
dimensionWeighting = [CD_weight, AD_weight, PD_weight]

weightingSum = round(sum(dimensionWeighting))

Expand All @@ -5240,27 +5419,22 @@ def dimesnionsAggregation(self):
if weightingSum == 100:

with rasterio.open(rasLayers[0]) as src:
ID_ras = src.read(1)
ID_weight = dimensionWeighting[0]
CD_ras = src.read(1)
CD_weight = dimensionWeighting[0]
meta1 = src.meta

with rasterio.open(rasLayers[1]) as src:
CD_ras = src.read(1)
CD_weight = dimensionWeighting[1]

with rasterio.open(rasLayers[2]) as src:
AD_ras = src.read(1)
AD_weight = dimensionWeighting[2]
AD_weight = dimensionWeighting[1]

with rasterio.open(rasLayers[3]) as src:
with rasterio.open(rasLayers[2]) as src:
PD_ras = src.read(1)
PD_weight = dimensionWeighting[3]
PD_weight = dimensionWeighting[2]

# Raster Calculation

result = (
(ID_ras * ID_weight / 100)
+ (CD_ras * CD_weight / 100)
(CD_ras * CD_weight / 100)
+ (AD_ras * AD_weight / 100)
+ (PD_ras * PD_weight / 100)
)
Expand Down
Loading

0 comments on commit ad39807

Please sign in to comment.