/
kharif_model_output_processor.py
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/
kharif_model_output_processor.py
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import csv
import itertools
from collections import OrderedDict
import numpy as np
from constants_dicts_lookups import *
from kharif_model_calculator import *
from qgis.core import QgsVectorLayer, QgsFeature, QgsField, QgsMapLayerRegistry, QgsSymbolV2, QgsRendererRangeV2, QgsGraduatedSymbolRendererV2, QgsVectorFileWriter
class KharifModelOutputProcessor:
def output_point_results_to_csv(self, output_grid_points, pointwise_output_csv_filepath, crops):
"""
#~ <all_crops> includes actual (selected) crops and also pseudo-crops
"""
parameters = ['PET-AET', 'Soil Moisture', 'Infiltration', 'Runoff', 'GW Recharge']
csvwrite = open(pointwise_output_csv_filepath,'w+b')
writer = csv.writer(csvwrite)
writer.writerow(['X', 'Y'] + [crops[i]+'-'+parameter+'-'+duration for i in range(len(crops)) for parameter in parameters for duration in ['Monsoon end', 'Crop end']] + ['Vegetation-'+parameter+'-'+duration for parameter in parameters for duration in ['Monsoon end', 'Crop end']])
for point in output_grid_points:
#~ if not point.zone_polygon: continue
if point.lulc_type in ['agriculture', 'fallow land']:
writer.writerow([point.qgsPoint.x(), point.qgsPoint.y()] +
list(itertools.chain(*[
[
point.budget.runoff_monsoon_end[i], point.budget.runoff_crop_end[i],
point.budget.sm_monsoon_end[i], point.budget.sm_crop_end[i],
point.budget.infil_monsoon_end[i], point.budget.infil_crop_end[i],
point.budget.PET_minus_AET_monsoon_end[i], point.budget.PET_minus_AET_crop_end[i],
point.budget.GW_rech_monsoon_end[i], point.budget.GW_rech_crop_end[i]
]
for i in range(len(crops))
])) +
['']*10
)
else:
writer.writerow([point.qgsPoint.x(), point.qgsPoint.y()] +
['']*(10*len(crops)) +
[
point.budget.runoff_monsoon_end[0], point.budget.runoff_crop_end[0],
point.budget.sm_monsoon_end[0], point.budget.sm_crop_end[0],
point.budget.infil_monsoon_end[0], point.budget.infil_crop_end[0],
point.budget.PET_minus_AET_monsoon_end[0], point.budget.PET_minus_AET_crop_end[0],
point.budget.GW_rech_monsoon_end[0], point.budget.GW_rech_crop_end[0]
]
)
csvwrite.close()
def compute_zonewise_budget(self, zone_points_dict):
zonewise_budgets = OrderedDict()
for zone_id in zone_points_dict:
zone_points = zone_points_dict[zone_id]
no_of_zone_points = len(zone_points)
if no_of_zone_points == 0: continue
zonewise_budgets[zone_id] = {}
all_agricultural_points = filter(lambda p: p.lulc_type in ['agriculture', 'fallow land'], zone_points)
non_agricultural_points_dict = {lulc_type: filter(lambda p: p.lulc_type == lulc_type, zone_points) for lulc_type in dict_LULC_pseudo_crop}
no_of_agricultural_points = len(all_agricultural_points)
zb = zonewise_budgets[zone_id]['agricultural'] = Budget()
zb.runoff_monsoon_end = np.sum([p.budget.runoff_monsoon_end for p in all_agricultural_points], 0) / no_of_agricultural_points
zb.sm_crop_end = np.sum([p.budget.sm_crop_end for p in all_agricultural_points], 0) / no_of_agricultural_points
zb.infil_monsoon_end = np.sum([p.budget.infil_monsoon_end for p in all_agricultural_points], 0) / no_of_agricultural_points
zb.AET_crop_end = np.sum([p.budget.AET_crop_end for p in all_agricultural_points], 0) / no_of_agricultural_points
zb.GW_rech_monsoon_end = np.sum([p.budget.GW_rech_monsoon_end for p in all_agricultural_points], 0) / no_of_agricultural_points
zb.PET_minus_AET_monsoon_end = np.sum([p.budget.PET_minus_AET_monsoon_end for p in all_agricultural_points], 0) / no_of_agricultural_points
zb.PET_minus_AET_crop_end = np.sum([p.budget.PET_minus_AET_crop_end for p in all_agricultural_points], 0) / no_of_agricultural_points
no_of_non_ag_lulc_type_points = {}
for lulc_type in non_agricultural_points_dict:
lulc_type_points = non_agricultural_points_dict[lulc_type]
no_of_non_ag_lulc_type_points[lulc_type] = len(lulc_type_points)
if no_of_non_ag_lulc_type_points[lulc_type] == 0: continue
zb = zonewise_budgets[zone_id][lulc_type] = Budget()
zb.sm_crop_end = np.sum([p.budget.sm_crop_end for p in lulc_type_points], 0) / no_of_non_ag_lulc_type_points[lulc_type]
zb.runoff_monsoon_end = np.sum([p.budget.runoff_monsoon_end for p in lulc_type_points], 0) / no_of_non_ag_lulc_type_points[lulc_type]
zb.infil_monsoon_end = np.sum([p.budget.infil_monsoon_end for p in lulc_type_points], 0) / no_of_non_ag_lulc_type_points[lulc_type]
zb.AET_crop_end = np.sum([p.budget.AET_crop_end for p in lulc_type_points], 0) / no_of_non_ag_lulc_type_points[lulc_type]
zb.GW_rech_monsoon_end = np.sum([p.budget.GW_rech_monsoon_end for p in lulc_type_points], 0) / no_of_non_ag_lulc_type_points[lulc_type]
zb.PET_minus_AET_monsoon_end = np.sum([p.budget.PET_minus_AET_monsoon_end for p in lulc_type_points], 0) / no_of_non_ag_lulc_type_points[lulc_type]
zb.PET_minus_AET_crop_end = np.sum([p.budget.PET_minus_AET_crop_end for p in lulc_type_points], 0) / no_of_non_ag_lulc_type_points[lulc_type]
#~ zb = Budget()
#~ zb.sm_crop_end = sum([p.budget.sm_crop_end for p in zone_points]) / no_of_zone_points
#~ zb.runoff_monsoon_end = sum([p.budget.runoff_monsoon_end for p in zone_points]) / no_of_zone_points
#~ zb.infil_monsoon_end = sum([p.budget.infil_monsoon_end for p in zone_points]) / no_of_zone_points
#~ zb.AET_crop_end = sum([p.budget.AET_crop_end for p in zone_points]) / no_of_zone_points
#~ zb.GW_rech_monsoon_end = sum([p.budget.GW_rech_monsoon_end for p in zone_points]) / no_of_zone_points
#~ zb.PET_minus_AET_monsoon_end = sum([p.budget.PET_minus_AET_monsoon_end for p in zone_points]) / no_of_zone_points
#~ zb.PET_minus_AET_crop_end = sum([p.budget.PET_minus_AET_crop_end for p in zone_points]) / no_of_zone_points
#~ zonewise_budgets[zone_id]['zone'] = {'overall':zb} # dict {'overall':zb} assigned instead of simple zb for convenience in iterating with ag and non-ag
return zonewise_budgets
def output_zonewise_budget_to_csv(self, zonewise_budgets, crops, pseudo_crops, zonewise_budget_csv_filepath, rain_sum):
csvwrite = open(zonewise_budget_csv_filepath,'wb')
writer = csv.writer(csvwrite)
writer.writerow(['']
+ ['zone-'+str(ID)+'-'+crop.name for ID in zonewise_budgets for crop in crops]
+ ['zone-'+str(ID)+'-'+pseudo_crop.name for ID in zonewise_budgets for pseudo_crop in pseudo_crops if pseudo_crop.name in zonewise_budgets[ID]]
)
writer.writerow(['Rainfall']
+ [rain_sum for ID in zonewise_budgets for i in range(len(crops))]
+ [rain_sum for ID in zonewise_budgets for pseudo_crop in pseudo_crops if pseudo_crop.name in zonewise_budgets[ID]]
)
writer.writerow(['Runoff in Monsoon']
+ [zonewise_budgets[ID]['agricultural'].runoff_monsoon_end[i] for ID in zonewise_budgets for i in range(len(crops))]
+ [zonewise_budgets[ID][pseudo_crop.name].runoff_monsoon_end[0] for ID in zonewise_budgets for pseudo_crop in pseudo_crops if pseudo_crop.name in zonewise_budgets[ID]]
)
writer.writerow(['Infiltration in Monsoon']
+ [zonewise_budgets[ID]['agricultural'].infil_monsoon_end[i] for ID in zonewise_budgets for i in range(len(crops))]
+ [zonewise_budgets[ID][pseudo_crop.name].infil_monsoon_end[0] for ID in zonewise_budgets for pseudo_crop in pseudo_crops if pseudo_crop.name in zonewise_budgets[ID]]
)
writer.writerow(['Soil Moisture Crop end']
+ [zonewise_budgets[ID]['agricultural'].sm_crop_end[i] for ID in zonewise_budgets for i in range(len(crops))]
+ [zonewise_budgets[ID][pseudo_crop.name].sm_crop_end[0] for ID in zonewise_budgets for pseudo_crop in pseudo_crops if pseudo_crop.name in zonewise_budgets[ID]]
)
writer.writerow(['GW Recharge in Monsoon']
+ [zonewise_budgets[ID]['agricultural'].GW_rech_monsoon_end[i] for ID in zonewise_budgets for i in range(len(crops))]
+ [zonewise_budgets[ID][pseudo_crop.name].GW_rech_monsoon_end[0] for ID in zonewise_budgets for pseudo_crop in pseudo_crops if pseudo_crop.name in zonewise_budgets[ID]]
)
writer.writerow(['AET']
+ [zonewise_budgets[ID]['agricultural'].AET_crop_end[i] for ID in zonewise_budgets for i in range(len(crops))]
+ [zonewise_budgets[ID][pseudo_crop.name].AET_crop_end[0] for ID in zonewise_budgets for pseudo_crop in pseudo_crops if pseudo_crop.name in zonewise_budgets[ID]]
)
writer.writerow(['PET']
+ [crop.PET_sum_cropend for ID in zonewise_budgets for crop in crops]
+ [pseudo_crop.PET_sum_cropend for ID in zonewise_budgets for pseudo_crop in pseudo_crops if pseudo_crop.name in zonewise_budgets[ID]]
)
writer.writerow(['Monsoon Deficit(PET-AET)']
+ [zonewise_budgets[ID]['agricultural'].PET_minus_AET_monsoon_end[i] for ID in zonewise_budgets for i in range(len(crops))]
+ [zonewise_budgets[ID][pseudo_crop.name].PET_minus_AET_monsoon_end[0] for ID in zonewise_budgets for pseudo_crop in pseudo_crops if pseudo_crop.name in zonewise_budgets[ID]]
)
writer.writerow(['Crop duration Deficit(PET-AET)']
+ [zonewise_budgets[ID]['agricultural'].PET_minus_AET_crop_end[i] for ID in zonewise_budgets for i in range(len(crops))]
+ [zonewise_budgets[ID][pseudo_crop.name].PET_minus_AET_crop_end[0] for ID in zonewise_budgets for pseudo_crop in pseudo_crops if pseudo_crop.name in zonewise_budgets[ID]]
)
csvwrite.close()
def render_and_save_pointwise_output_layer(self,
pointwise_output_csv_filepath,
output_layer_name,
on_values_of_attribute,
graduated_rendering_interval_points,
shapefile_path=''
):
uri = 'file:///' + pointwise_output_csv_filepath + \
'?delimiter=%s&crs=epsg:32643&xField=%s&yField=%s' % (',', 'X', 'Y')
output_layer = QgsVectorLayer(uri, output_layer_name, 'delimitedtext')
if 'Crop' in on_values_of_attribute:
ET_D_max = max([point.budget.PET_minus_AET_crop_end for point in model_calculator.output_grid_points])
elif 'Monsoon' in on_values_of_attribute:
ET_D_max = max([point.budget.PET_minus_AET_monsoon_end for point in model_calculator.output_grid_points])
graduated_symbol_renderer_range_list = []
opacity = 1
intervals_count = len(graduated_rendering_interval_points)
for i in range(intervals_count):
interval_min = 0 if graduated_rendering_interval_points[i] == 0 else (graduated_rendering_interval_points[i]*ET_D_max/100.0 + 0.01)
interval_max = (graduated_rendering_interval_points*ET_D_max/100.0)
label = "{0:.2f} - {1:.2f}".format(interval_min, interval_max)
colour = QColor(int(255*(1-(i+1.0)/(intervals_count+1.0))), 0, 0) # +1 done to tackle boundary cases
symbol = QgsSymbolV2.defaultSymbol(output_layer.geometryType())
symbol.setColor(colour)
symbol.setAlpha(opacity)
interval_range = QgsRendererRangeV2(interval_min, interval_max, symbol, label)
graduated_symbol_renderer_range_list.append(interval_range)
renderer = QgsGraduatedSymbolRendererV2('', graduated_symbol_renderer_range_list)
renderer.setMode(QgsGraduatedSymbolRendererV2.EqualInterval)
renderer.setClassAttribute(on_values_of_attribute)
output_layer.setRendererV2(renderer)
QgsMapLayerRegistry.instance().addMapLayer(output_layer)
if shapefile_path != '':
QgsVectorFileWriter.writeAsVectorFormat(output_layer, shapefile_path, "utf-8", None, "ESRI Shapefile")
return output_layer
def compute_and_output_cadastral_vulnerability_to_csv(self, crop_names, output_cadastral_points, cadastral_vulnerability_csv_filepath):
plot_vulnerability_dict = {
p.cadastral_polygon.id():
[
(
p.budget.PET_minus_AET_crop_end[i],
p.budget.PET_minus_AET_monsoon_end[i]
)
for i in range(len(crop_names))
]
for p in output_cadastral_points
if p.lulc_type in ['agriculture', 'fallow land']
}
sorted_keys = sorted(plot_vulnerability_dict.keys(), key=lambda ID: plot_vulnerability_dict[ID], reverse=True)
csvwrite = open(cadastral_vulnerability_csv_filepath, 'w+b')
writer = csv.writer(csvwrite)
writer.writerow(['Plot ID'] +
list(itertools.chain(*[
[
crop + ' Crop end Deficit',
crop + ' Crop end Deficit Waterings',
crop + ' Monsoon end Deficit',
crop + ' Monsoon end Deficit Waterings'
]
for crop in crop_names
])
)
)
for key in sorted_keys:
writer.writerow([key] +
list(itertools.chain(*[
[
'{0:.2f}'.format(plot_vulnerability_dict[key][i][0]),
round((plot_vulnerability_dict[key][i][0]) / 50),
'{0:.2f}'.format(plot_vulnerability_dict[key][i][1]),
round((plot_vulnerability_dict[key][i][1]) / 50)
]
for i in range(len(crop_names))
])
)
)
csvwrite.close()
def compute_and_display_cadastral_vulnerability(self, cadastral_layer, output_grid_points, output_cadastral_points, crop_index, crop_name, base_path):
cadastral_points_per_plot = {}
for p in (output_grid_points + output_cadastral_points):
if p.cadastral_polygon is None: continue
if p.lulc_type not in ['agriculture', 'fallow land']: continue
if p.cadastral_polygon.id() in cadastral_points_per_plot:
cadastral_points_per_plot[p.cadastral_polygon.id()].append(
p.budget.PET_minus_AET_crop_end[crop_index])
else:
cadastral_points_per_plot[p.cadastral_polygon.id()] = [
p.budget.PET_minus_AET_crop_end[crop_index]]
for k, v in cadastral_points_per_plot.items():
if len(v) > 0:
cadastral_points_per_plot[k] = sum(v) / len(v)
else:
del cadastral_points_per_plot[k]
# print cadastral_points_per_plot
# Create duplicate cadastral layer in memory
memory_cadastral_layer = QgsVectorLayer('Polygon?crs=epsg:32643', crop_name + ' Cadastral Level Vulnerability', 'memory')
memory_cadastral_layer.startEditing()
memory_cadastral_layer.dataProvider().addAttributes(
cadastral_layer.qgsLayer.dataProvider().fields().toList())
memory_cadastral_layer.updateFields()
dict_new_feature_id_to_old_feature_id = {}
for old_plot_id in cadastral_points_per_plot:
result, output_features = memory_cadastral_layer.dataProvider().addFeatures(
[cadastral_layer.feature_dict[old_plot_id]])
dict_new_feature_id_to_old_feature_id[output_features[0].id()] = old_plot_id
memory_cadastral_layer.dataProvider().addAttributes([QgsField('Deficit', QVariant.Double)])
memory_cadastral_layer.updateFields()
for new_feature in memory_cadastral_layer.getFeatures():
new_feature['Deficit'] = cadastral_points_per_plot[
dict_new_feature_id_to_old_feature_id[new_feature.id()]]
memory_cadastral_layer.updateFeature(new_feature)
memory_cadastral_layer.commitChanges()
# Graduated Rendering
graduated_symbol_renderer_range_list = []
ET_D_max = max(cadastral_points_per_plot.values())
opacity = 1
geometry_type = memory_cadastral_layer.geometryType()
intervals_count = CADASTRAL_VULNERABILITY_DISPLAY_COLOUR_INTERVALS_COUNT
dict_interval_colour = CADASTRAL_VULNERABILITY_DISPLAY_COLOURS_DICT
for i in range(intervals_count):
interval_min = 0 if i == 0 else (ET_D_max * float(
i) / intervals_count) + 0.01
interval_max = ET_D_max * float(i + 1) / intervals_count
label = "{0:.2f} - {1:.2f}".format(interval_min, interval_max)
colour = QColor(*dict_interval_colour[i])
symbol = QgsSymbolV2.defaultSymbol(geometry_type)
symbol.setColor(colour)
symbol.setAlpha(opacity)
interval_range = QgsRendererRangeV2(interval_min, interval_max, symbol, label)
graduated_symbol_renderer_range_list.append(interval_range)
renderer = QgsGraduatedSymbolRendererV2('', graduated_symbol_renderer_range_list)
renderer.setMode(QgsGraduatedSymbolRendererV2.EqualInterval)
renderer.setClassAttribute('Deficit')
memory_cadastral_layer.setRendererV2(renderer)
QgsMapLayerRegistry.instance().addMapLayer(memory_cadastral_layer)
memory_cadastral_layer.setCustomProperty('labeling', 'pal')
memory_cadastral_layer.setCustomProperty('labeling/enabled', 'true')
memory_cadastral_layer.setCustomProperty('labeling/fieldName', 'Number')
memory_cadastral_layer.setCustomProperty('labeling/fontSize', '10')
memory_cadastral_layer.setCustomProperty('labeling/placement', '0')
memory_cadastral_layer.dataProvider().forceReload()
memory_cadastral_layer.triggerRepaint()
QgsVectorFileWriter.writeAsVectorFormat(memory_cadastral_layer,
base_path + '/kharif_'+crop_name+'_cadastral_level_vulnerability.shp', "utf-8", None,
"ESRI Shapefile")