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kharif_model.py
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kharif_model.py
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# -*- coding: utf-8 -*-
"""
/***************************************************************************
KharifModel
A QGIS plugin
Generates kharif season vulnerability map
-------------------
begin : 2017-11-18
git sha : $Format:%H$
copyright : (C) 2017 by IITB
email : sohoni@cse.iitb.ac.in
***************************************************************************/
/***************************************************************************
* *
* This program is free software; you can redistribute it and/or modify *
* it under the terms of the GNU General Public License as published by *
* the Free Software Foundation; either version 2 of the License, or *
* (at your option) any later version. *
* *
***************************************************************************/
"""
from PyQt4.QtCore import QSettings, QTranslator, qVersion, QCoreApplication, QDate, QTimer
from PyQt4.QtGui import QAction, QIcon, QFileDialog, QColor
# Initialize Qt resources from file resources.py
import resources
import time
# Import the code for the dialog
from kharif_model_dialog import KharifModelDialog
from kharif_model_output_processor import KharifModelOutputProcessor
import os.path, csv
# Import code for the calculation
from kharif_model_calculator import KharifModelCalculator
from qgis.core import QgsMapLayerRegistry, QgsVectorLayer, QgsSymbolV2, QgsRendererRangeV2, QgsGraduatedSymbolRendererV2, QgsVectorFileWriter
from constants_dicts_lookups import *
from configuration import *
from collections import OrderedDict
class KharifModel:
"""QGIS Plugin Implementation."""
def __init__(self, iface):
"""Constructor.
:param iface: An interface instance that will be passed to this class
which provides the hook by which you can manipulate the QGIS
application at run time.
:type iface: QgsInterface
"""
# Save reference to the QGIS interface
self.iface = iface
# initialize plugin directory
self.plugin_dir = os.path.dirname(__file__)
# initialize locale
locale = QSettings().value('locale/userLocale')[0:2]
locale_path = os.path.join(
self.plugin_dir,
'i18n',
'KharifModel_{}.qm'.format(locale))
if os.path.exists(locale_path):
self.translator = QTranslator()
self.translator.load(locale_path)
if qVersion() > '4.3.3':
QCoreApplication.installTranslator(self.translator)
# Declare instance attributes
self.actions = []
self.menu = self.tr(u'&Kharif Model - all crop - all year - zone only')
# TODO: We are going to let the user set this up in a future iteration
self.toolbar = self.iface.addToolBar(u'KharifModelMulticrop')
self.toolbar.setObjectName(u'KharifModelMulticrop')
# noinspection PyMethodMayBeStatic
def tr(self, message):
"""Get the translation for a string using Qt translation API.
We implement this ourselves since we do not inherit QObject.
:param message: String for translation.
:type message: str, QString
:returns: Translated version of message.
:rtype: QString
"""
# noinspection PyTypeChecker,PyArgumentList,PyCallByClass
return QCoreApplication.translate('KharifModelMulticrop', message)
def add_action(
self,
icon_path,
text,
callback,
enabled_flag=True,
add_to_menu=True,
add_to_toolbar=True,
status_tip=None,
whats_this=None,
parent=None):
"""Add a toolbar icon to the toolbar.
:param icon_path: Path to the icon for this action. Can be a resource
path (e.g. ':/plugins/foo/bar.png') or a normal file system path.
:type icon_path: str
:param text: Text that should be shown in menu items for this action.
:type text: str
:param callback: Function to be called when the action is triggered.
:type callback: function
:param enabled_flag: A flag indicating if the action should be enabled
by default. Defaults to True.
:type enabled_flag: bool
:param add_to_menu: Flag indicating whether the action should also
be added to the menu. Defaults to True.
:type add_to_menu: bool
:param add_to_toolbar: Flag indicating whether the action should also
be added to the toolbar. Defaults to True.
:type add_to_toolbar: bool
:param status_tip: Optional text to show in a popup when mouse pointer
hovers over the action.
:type status_tip: str
:param parent: Parent widget for the new action. Defaults None.
:type parent: QWidget
:param whats_this: Optional text to show in the status bar when the
mouse pointer hovers over the action.
:returns: The action that was created. Note that the action is also
added to self.actions list.
:rtype: QAction
"""
# Create the dialog (after translation) and keep reference
self.dlg = KharifModelDialog(crops=dict_crop.keys())
icon = QIcon(icon_path)
action = QAction(icon, text, parent)
action.triggered.connect(callback)
action.setEnabled(enabled_flag)
if status_tip is not None:
action.setStatusTip(status_tip)
if whats_this is not None:
action.setWhatsThis(whats_this)
if add_to_toolbar:
self.toolbar.addAction(action)
if add_to_menu:
self.iface.addPluginToMenu(
self.menu,
action)
self.actions.append(action)
return action
def initGui(self):
"""Create the menu entries and toolbar icons inside the QGIS GUI."""
icon_path = ':/plugins/KharifModelMulticrop/icon.png'
self.add_action(
icon_path,
text=self.tr(u'Kharif Model - all crop - all year - zone only'),
callback=self.run,
parent=self.iface.mainWindow())
def unload(self):
"""Removes the plugin menu item and icon from QGIS GUI."""
for action in self.actions:
self.iface.removePluginMenu(
self.tr(u'&Kharif Model - all crop - all year - zone only'),
action)
self.iface.removeToolBarIcon(action)
# remove the toolbar
del self.toolbar
def run(self):
"""Run method that performs all the real work"""
start_time = time.time()
if PLUGIN_MODE == 'DEBUG':
if not os.path.exists(DEBUG_BASE_FOLDER_PATH): raise Exception('Set DEBUG_BASE_FOLDER_PATH for the debug dataset')
paths = [DEBUG_BASE_FOLDER_PATH]
elif PLUGIN_MODE == 'REAL':
paths = ['']
else:
if not os.path.exists(TEST_SUITE_BASE_FOLDER_PATH): raise Exception('Set TEST_SUITE_BASE_FOLDER_PATH for the debug dataset')
paths = [os.path.join(TEST_SUITE_BASE_FOLDER_PATH, base_path) for base_path in os.listdir(TEST_SUITE_BASE_FOLDER_PATH)]
filter(lambda p: os.path.isdir(p), paths)
path_num = 0
for path in paths:
path_num += 1
# if os.path.basename(path) == '503_ptp-1_03': continue
if not os.path.exists(os.path.join(path, 'Zones.shp')): continue
if self.fetch_inputs(path) is False: return
# return
print 'cluster', os.path.basename(path)
# print self.rain['2013'].keys(); return
year_num = 0
print 'years', self.rain.keys()
for year in self.rain:
# if year_num > 0: break
year_num += 1
print 'checking whether already processed for year', year
if os.path.exists(os.path.join(path, year + '_' + ZONEWISE_BUDGET_CSV_FILENAME)): continue
print 'initializing calculations'
self.modelCalculator = KharifModelCalculator(self.path, self.et0, **self.input_layers)
rain_input_dict = {circle: {'daily_rain':self.rain[year][circle]} for circle in self.rain[year]}
rain_sum_input_dict = {circle: {'year': year, 'sum': self.rain_sum_monsoon[year][circle]} for circle in self.rain_sum_monsoon[year]}
self.modelCalculator.calculate(
rain_input_dict,
self.crop_names,
self.sowing_threshold,
monsoon_end_date_index=self.monsoon_end_date_index,
cluster=str(path_num) + '/' + str(len(paths)-1),
year=str(year_num) + '/' + str(len(self.rain.keys()))
)
pointwise_output_csv_filepath = os.path.join(self.base_path, year + '_' + POINTWISE_OUTPUT_CSV_FILENAME)
op = KharifModelOutputProcessor()
# Removed for urgent case of zone-level outputs only
# op.output_point_results_to_csv (
# self.modelCalculator.output_grid_points,
# pointwise_output_csv_filepath,
# crops=[crop.name for crop in self.modelCalculator.crops]
# )
zonewise_budgets = op.compute_zonewise_budget (
self.modelCalculator.zone_points_dict ,
self.modelCalculator.zone_points_dict_ag_missing, #removed for urgent village charts (17-11-2018)
self.modelCalculator.zone_points_dict_current_fallow,
self.modelCalculator.zone_points_dict_non_ag_missing_LU,
self.modelCalculator.zones_layer
)
print self.circle_avg_year_dict
village_avg_year_dict = {
feature['VIL_NAME']: self.circle_avg_year_dict[feature['Circle'].lower()]
for feature in self.modelCalculator.zones_layer.feature_dict.values()
}
print village_avg_year_dict
op.output_zonewise_budget_to_csv (
zonewise_budgets,
self.modelCalculator.crops,
self.rabi_crop_names,
self.modelCalculator.currnet_fallow,
self.modelCalculator.LULC_pseudo_crops.values(),
os.path.join(self.base_path, year + '_' + ZONEWISE_BUDGET_CSV_FILENAME ),
rain_sum_input_dict,
year,
village_avg_year_dict
)
# Removed for urgent case of zone-level outputs only
# op.compute_and_output_cadastral_vulnerability_to_csv(
# self.crop_names,
# self.modelCalculator.output_cadastral_points,
# os.path.join(self.base_path, year + '_' + CADESTRAL_VULNERABILITY_CSV_FILENAME)
# )
# kharif_model_crop_end_output_layer = \
# op.render_and_save_pointwise_output_layer(
# pointwise_output_csv_filepath,
# 'Kharif Model Crop End Output',
# 'Crop duration PET-AET',
# self.output_configuration['graduated_rendering_interval_points'],
# shapefile_path=os.path.join(self.base_path, 'kharif_crop_duration_et_deficit.shp')
# )
# if(crop in long_kharif_crops):
# kharif_model_monsoon_end_output_layer = \
# op.render_and_save_pointwise_output_layer(
# pointwise_output_csv_filepath,
# 'Kharif Model Monsoon End Output',
# 'Monsoon PET-AET',
# self.output_configuration['graduated_rendering_interval_points'],
# shapefile_path=os.path.join(self.base_path, 'kharif_monsoon_et_deficit.shp')
# )
# Removed for urgent case of zone-level outputs only
# for i in range(len(self.crop_names)):
# op.compute_and_display_cadastral_vulnerability(
# self.modelCalculator.cadastral_layer,
# self.modelCalculator.output_grid_points,
# self.modelCalculator.output_cadastral_points,
# i,
# self.crop_names[i],
# self.path
# )
QgsMapLayerRegistry.instance().removeMapLayers([
self.input_layers['zones_layer'].id(),
self.input_layers['soil_layer'].id(),
self.input_layers['lulc_layer'].id(),
self.input_layers['slope_layer'].id(),
# self.input_layers['cadastral_layer'].id()
])
print("KM--- %s seconds ---" % (time.time() - start_time))
print self.plugin_dir
# self.iface.actionHideAllLayers().trigger()
# self.iface.legendInterface().setLayerVisible(self.input_layers['zones_layer'], True)
# if 'drainage_layer' in locals(): self.iface.legendInterface().setLayerVisible(self.input_layers['drainage_layer'], True)
# if (crop in long_kharif_crops): self.iface.legendInterface().setLayerVisible(kharif_model_monsoon_end_output_layer, True)
# self.iface.legendInterface().setLayerVisible(kharif_model_crop_end_output_layer, True)
# self.iface.mapCanvas().setExtent(self.input_layers['zones_layer'].extent())
# self.iface.mapCanvas().mapRenderer().setDestinationCrs(self.input_layers['zones_layer'].crs())
#~ if self.dlg.save_image_group_box.isChecked():
#~ QTimer.singleShot(1000, lambda : self.iface.mapCanvas().saveAsImage(self.dlg.save_image_filename.text()))
def fetch_inputs(self, path):
def set_et0_from_et0_file_data(et0_file_data):
et0 = []
for i in range (0,len(et0_file_data)):
if (i in [0,3,5,10]): et0.extend([et0_file_data[i]]*30)
elif i == 8: et0.extend([et0_file_data[i]]*28)
else: et0.extend([et0_file_data[i]]*31)
return et0
self.rain=OrderedDict()
if path != '':
self.base_path = self.path = path
self.input_layers = {}
self.input_layers['zones_layer'] = self.iface.addVectorLayer(os.path.join(path, 'Zones.shp'), 'Zones', 'ogr')
self.input_layers['soil_layer'] = self.iface.addVectorLayer(os.path.join(path, 'Soil.shp'), 'Soil Cover', 'ogr')
self.input_layers['lulc_layer'] = self.iface.addVectorLayer(os.path.join(path, 'LULC.shp'), 'Land-Use-Land-Cover', 'ogr')
# self.input_layers['cadastral_layer'] = self.iface.addVectorLayer(os.path.join(path, 'Cadastral.shp'), 'Cadastral Map', 'ogr')
self.input_layers['slope_layer'] = self.iface.addRasterLayer(os.path.join(path, 'Slope.tif'), 'Slope')
#~ self.input_layers['drainage_layer'] = self.iface.addRasterLayer(os.path.join(path, 'Drainage.shp'), 'Drainage', 'ogr')
data_dir = os.path.join(self.plugin_dir,'Data')
# self.input_layers['soil_layer'] = self.iface.addVectorLayer(os.path.join(data_dir, 'soil utm.shp'), 'Soil Cover', 'ogr')
# self.input_layers['lulc_layer'] = self.iface.addVectorLayer(os.path.join(data_dir, 'lulc utm.shp'), 'Land-Use-Land-Cover', 'ogr')
# csvreader=csv.reader(open(os.path.join(path, RAINFALL_CSV_FILENAME)))
with open(os.path.join(path, 'Rainfall.csv')) as f:
csvreader_for_avg_year = csv.DictReader(f)
self.circle_avg_year_dict = {row['Circle'].lower(): row['Year'] for row in csvreader_for_avg_year}
print self.circle_avg_year_dict
csvreader = csv.reader(open(os.path.join(TEST_SUITE_BASE_FOLDER_PATH, 'Rainfall_all.csv'))) # FOR urgent village charts (17-11-2018)
next(csvreader)
# self.rain = OrderedDict((row[0].lower(),{'year': row[1],'daily_rain':[float(val) for val in row[2:]]}) for row in csvreader)
# self.rain['0'] = self.rain[next(iter(self.rain.keys()))]
###For multiple rainfall years use the following###
self.rain = {}; years = []; dist_taluka_year_tuples = set([])
for row in csvreader:
# print row
if row[3] not in self.rain:
years += [row[3]]
self.rain[row[3]] = {}
# self.rain[row[1]][row[0].lower()] = [float(val) for val in row[2:]]
self.rain[row[3]][(row[0].lower(), row[1].lower(), row[2].lower())] = [float(val) for val in row[4:]]
dist_taluka_year_tuples.add((row[0].lower(), row[1].lower(), row[3]))
for dty in dist_taluka_year_tuples:
for k in self.rain[dty[2]]:
if (k[0], k[1]) == (dty[0], dty[1]):
# print zc[3], zc[0], zc[1]
self.rain[dty[2]][(dty[0], dty[1], '0')] = self.rain[dty[2]][(k[0], k[1], k[2])]
break
# return
et0_file_data = [float(row["ET0"]) for row in csv.DictReader(open(os.path.join(path, ET0_CSV_FILENAME)))]
self.et0 = set_et0_from_et0_file_data(et0_file_data)
self.sowing_threshold = DEFAULT_SOWING_THRESHOLD
self.monsoon_end_date_index = MONSOON_END_DATE_INDEX
self.rain_sum_monsoon = {
year: {
circle: sum(self.rain[year][circle][START_DATE_INDEX: self.monsoon_end_date_index + 1])
for circle in self.rain[year].keys()
} for year in self.rain.keys()
}
# self.rain_sum_monsoon={key:{'year':self.rain[key]['year'],'sum':sum(self.rain[key]['daily_rain'][START_DATE_INDEX : self.monsoon_end_date_index+1])} for key in self.rain.keys()}
# if not OVERRIDE_FILECROPS_BY_DEBUG_OR_TEST_CROPS and os.path.exists(os.path.join(path, CROPS_FILENAME)):
# self.crop_names = open(os.path.join(path, CROPS_FILENAME), 'r').read().split(',')
# print (self.crop_names)
# if len(self.crop_names) == 0 : raise Exception('No crop selected')
# else:
# self.crop_names = DEBUG_OR_TEST_CROPS
# self.rabi_crop_names = DEBUG_OR_TEST_RABI_CROPS
self.crop_names = dict_crop
self.rabi_crop_names = dict_rabi_crop
self.output_configuration = {}
# self.output_configuration['graduated_rendering_interval_points'] = DEBUG_OR_TEST_GRADUATED_RENDERING_INTERVAL_POINTS
else:
self.dlg.show()
if self.dlg.exec_() == QFileDialog.Rejected: return False
path = self.path = self.base_path = self.dlg.folder_path.text()
self.input_layers = {}
self.input_layers['zones_layer'] = self.iface.addVectorLayer(self.dlg.zones_layer_filename.text(), 'Zones', 'ogr')
self.input_layers['soil_layer'] = self.iface.addVectorLayer(self.dlg.soil_layer_filename.text(), 'Soil Cover', 'ogr')
self.input_layers['lulc_layer'] = self.iface.addVectorLayer(self.dlg.lulc_layer_filename.text(), 'Land-Use-Land-Cover', 'ogr')
self.input_layers['cadastral_layer'] = self.iface.addVectorLayer(self.dlg.cadastral_layer_filename.text(), 'Cadastral Map', 'ogr')
self.input_layers['slope_layer'] = self.iface.addRasterLayer(self.dlg.slope_layer_filename.text(), 'Slope')
if self.dlg.drainage_layer_filename.text() != '':
self.drainage_layer = self.iface.addVectorLayer(self.dlg.drainage_layer_filename.text(), 'Drainage', 'ogr')
csvreader=csv.reader(open(str(self.dlg.rainfall_csv_filename.text())))
next(csvreader)
# self.rain = OrderedDict((row[0].lower(),{'year': row[1],'daily_rain':[float(val) for val in row[2:]]}) for row in csvreader)
# self.rain['0'] = self.rain[next(iter(self.rain.keys()))]
###For multiple rainfall years use the following###
self.rain = {}; years = []
for row in csvreader:
if row[1] not in self.rain:
years += row[1]
self.rain[row[1]] = {}
self.rain[row[1]][row[0].lower()] = [float(val) for val in row[2:]]
for y in years: self.rain[y]['0'] = self.rain[y][next(iter(self.rain[y].keys()))]
# self.rain = OrderedDict(
# (row[1].lower(), {row[0].lower(): [float(val) for val in row[2:]]}) for row in csvreader
# )
# print 'circles', self.rain['2013'].keys()
# self.rain['0'] = self.rain[next(iter(self.rain.keys()))]
et0_file_data = [float(row["ET0"]) for row in csv.DictReader(open(os.path.join(path, ET0_CSV_FILENAME)))]
self.et0 = set_et0_from_et0_file_data(et0_file_data)
self.sowing_threshold = self.dlg.sowing_threshold.value()
self.monsoon_end_date_index = self.dlg.monsoon_end.value()+122
self.rain_sum_monsoon = {
year: {
circle: sum(self.rain[year][circle][START_DATE_INDEX : self.monsoon_end_date_index+1])
for circle in self.rain[year].keys()
} for year in self.rain.keys()
}
# 'year':self.rain[key]['year'],'sum':sum(self.rain[key]['daily_rain'][START_DATE_INDEX : self.monsoon_end_date_index+1])} for circle in self.rain.keys()}
# self.crop_names = self.dlg.crops
# self.rabi_crop_names = self.dlg.rabi_crops
# for urgent requirement of all crops
self.crop_names = dict_crop
self.rabi_crop_names = dict_rabi_crop
if len(self.crop_names) == 0: raise Exception('No crop selected')
self.output_configuration = {}
# self.output_configuration['graduated_rendering_interval_points'] = [
# int(self.dlg.colour_code_intervals_list_widget.item(i).text().split('-')[0])
# for i in range(1,self.dlg.colour_code_intervals_list_widget.count())
# ]