drought/disaster/views.py

import datetime
from urllib.parse import unquote

import httplib2
from django.db.models import Count
from django.http import JsonResponse, HttpResponse, HttpResponseNotAllowed
from django.shortcuts import render
from django.views.decorators.csrf import csrf_exempt

from .util.utils import *
from .radar.process import *
from .spi.process import *
from dashboard.models import Spi

PROXY_FORMAT = 'http://%s:%d%s' % ('210.77.68.250', 8080, '%s')

def index(request):
	month = request.GET.get('month', '1')
	months = range(1, 13)
	spis = Spi.objects.filter(month=month)
	return render(request, 'disaster/index.html', {'month': month, 'months': months, 'spis': spis})



def hail(request):
	return render(request, 'disaster/hail.html')

## 冰雹相关
'''取出冰雹范围'''
@csrf_exempt
def hailstones(request):
	# csv_path = '../data/radar/radar-bj.csv'
	csv_path = handle_uploaded_file(request.FILES['file_path']) # 冰雹雷达数据
	'''
	读取csv文件中的雷达数据
	code,position,seq,time,yangjiao,no.,X,Y,huibo,dinggao,field_11
	:param csv_path: 包含上述title的csv文件，主要是X,Y,huibo三个字段
	'''
	hailstones_data = get_hailstones(csv_path)
	return JsonResponse(hailstones_data.to_json(), safe=False)


def get_type_path(type):
	'''
	if type == '棉花':
		type = 'cotton'
	elif type == '玉米':
		type = 'corn'
	elif type == '小麦':
		type = 'wheat'
	elif type == '人口':
		type = 'population'
	elif type == 'GDP':
		type = 'gdp'
	'''
	return DATA_BASE_PATH + 'raster/%s_3857.tif' % type


'''计算冰雹的影响'''
@csrf_exempt
def calc_hailstones_impact(request):
	type = request.POST['type']
	county = request.POST['county'] # 是否划分县域 1 or 0
	calc_dem = request.POST['dem'] # 是否计算dem  1 or 0
	csv_path = handle_uploaded_file(request.FILES['file_path']) # 冰雹雷达数据

	hailstones_data = get_hailstones(csv_path)
	if county == 1:
		hailstones_data = intersection_xzqh(hailstones_data)

	tif_path = get_type_path(type)
	if calc_dem == 0:
		sum = agg_raster_by_gdf_value(tif_path, hailstones_data)
	else:
		sum = agg_raster_by_gdf_area_and_aspect_slope(tif_path, get_type_path('aspect'), get_type_path('slope'),
		                                              hailstones_data)
	res = {}
	res['agg'] = sum
	res['geo'] = hailstones_data.to_json()
	return JsonResponse(res, safe=False)


def prevent_hailstones_data():
	prevent_data = read_xls(DATA_BASE_PATH + 'fbd/fbd.xlsx')
	return get_buffer_data(prevent_data, dis=10000)


'''防雹点分布情况'''
@csrf_exempt
def prevent_hailstones(request):
	prevent_data = prevent_hailstones_data()
	return JsonResponse(prevent_data.to_json(), safe=False)


'''计算防雹点范围内冰雹的影响情况'''
@csrf_exempt
def calc_prevent_impact(request):
	csv_path = handle_uploaded_file(request.FILES['file_path']) # 冰雹雷达数据

	prevent_data = prevent_hailstones_data()

	hailstones_data = get_hailstones(csv_path)
	prevent_intersection_disater_data = intersection(prevent_data, hailstones_data)
	print(prevent_intersection_disater_data)
	agg = agg_gdf_by_gdf_area(prevent_data, prevent_intersection_disater_data)
	# print(res)  # 单个点的面积
	# print(res.sum())  # 总面积
	res = {}
	res['agg'] = agg
	res['sum'] = agg.sum()
	res['geo'] = prevent_intersection_disater_data.to_json()
	return JsonResponse(res, safe=False)


## SPI 相关
'''获取SPI或者SPEI分布情况'''
@csrf_exempt
def get_spi_region(request):
	spi_type = request.POST['spi_type']  # spi.spei
	month = request.POST['month'] # 几月
	file_path = handle_uploaded_file(request.FILES['file_path'])  # 上传文件，   name, rain, temp
	station_buffer = get_station_polygon()
	spi_gdf = get_spi_dataframe(station_buffer, file_path, int(month))
	spi_disaster = get_disaster_gdf(spi_gdf, spi_type)
	return JsonResponse(spi_disaster.to_json(), safe=False)


'''计算spi或spei对各种因素的影响'''
@csrf_exempt
def calc_spi_diaster(request):
	spi_type = request.POST['spi_type']  # spi.spei
	county = request.POST['county'] # 是否划分县域 1 or 0
	type = request.POST['type'] # 栅格种类
	month = request.POST['month'] # 几月
	file_path = handle_uploaded_file(request.FILES['file_path'])  # name, rain, temp

	station_buffer = get_station_polygon()
	spi_gdf = get_spi_dataframe(station_buffer, file_path, int(month))

	spi_disaster = get_disaster_gdf(spi_gdf, spi_type)

	if county:
		spi_disaster = intersection_xzqh(spi_disaster)

	res_spi = agg_raster_by_gdf_value(get_type_path(type), spi_disaster)
	res = {}
	res['geo'] = spi_disaster.to_json()
	res['agg'] = res_spi
	return JsonResponse(res, safe=False)



def handle_uploaded_file(f):
	from django.conf import settings
	file_name = f.name
	# _, ext = os.path.splitext(file_name)
	# id = str(uuid.uuid4())
	media_root = settings.MEDIA_ROOT
	if not os.path.exists(media_root):
		os.mkdir(media_root)

	path = '%s\%s' % (media_root, file_name)
	print(path)
	with open(path, 'wb+') as destination:
		for chunk in f.chunks():
			destination.write(chunk)

	return path