def lulc(request, landcover=None, period=None):
import datasets as ds
ds.LoadRawData()
ds.LoadPeriod()
# lc_name = "Select landcover" if request.LANGUAGE_CODE == "en" else "Pilih tutupan lahan"
landcover_list = np.append(
{
"value": "",
"name_en": "Select landcover",
"name_id": "Pilih tutupan lahan"
}, ds.LANDCOVER)
period_list = np.append([""], ds.PERIOD_LIST)
if landcover == None:
landcover_name = "Land cover" if request.LANGUAGE_CODE == "en" else "Tutupan lahan"
ds.CalculateArea("", "")
# print("yg ini kosong")
else:
landcover_name = landcover_list[next(
index for (index, d) in enumerate(landcover_list)
if d["value"] == landcover)]["name_" + request.LANGUAGE_CODE]
ds.CalculateArea(landcover, period)
# print("--> " + landcover + " -- " + period)
periods = ["", ""] if (landcover == None) else period.split("-")
#generate geojson data
geojson_data1 = pg.load(filepath=settings.BASE_DIR +
"/main/static/data/geojson/batas_admin.geojson")
geojson_data2 = pg.load(filepath=settings.BASE_DIR +
"/main/static/data/geojson/batas_admin.geojson")
for feat in geojson_data1:
nama_kec = feat.properties["KABKOTA"]
if nama_kec in ds.AREA_PERIOD_BEGIN_ADMIN.index:
feat.properties["DATA"] = ds.AREA_PERIOD_BEGIN_ADMIN.loc[nama_kec][
"COUNT"] / 1000.00
else:
feat.properties["DATA"] = -1
for feat in geojson_data2:
nama_kec = feat.properties["KABKOTA"]
if nama_kec in ds.AREA_PERIOD_END_ADMIN.index:
feat.properties["DATA"] = ds.AREA_PERIOD_END_ADMIN.loc[nama_kec][
"COUNT"] / 1000.00
else:
feat.properties["DATA"] = -1
stat_data = {
'area1': round(ds.AREA_PERIOD_BEGIN / 1000000.00, 2),
'area2': round(ds.AREA_PERIOD_END / 1000000.00, 2),
'growth': round(ds.AREA_GROWTH, 2),
'num_district': ds.AREA_ADMIN_TOTAL,
'max_district': ds.AREA_ADMIN_LARGEST,
'fast_district': ds.AREA_ADMIN_FASTEST,
'period1': periods[0],
'period2': periods[1]
}
context = {
'landcover_list': landcover_list,
'selected_landcover': landcover,
'period': period_list,
'selected_period': period,
'landcover_title': landcover_name,
'map_data1': geojson_data1,
'map_data2': geojson_data2,
'stat_data': stat_data,
'peat_data': ds.AREA_PEAT,
'landcover_data': ds.AREA_LANDCOVER,
'landcover_plan': ds.AREA_LANDCOVER_PLAN,
'landchanges': ds.AREA_PERIOD,
'landchange_plan': ds.AREA_CHANGES_PLAN
}
#return render(request, request.LANGUAGE_CODE +'_bau_lulc.html', context)
return render(request, 'bau_lulc.html', context)
def process_carbon(request, period, template, carbon_type, map_field):
import datasets as ds
ds.LoadRawData()
ds.LoadPeriod()
period_list = np.append([""], ds.PERIOD_LIST)
if period == None:
ds.CalculateDataEnv("", carbon_type)
else:
ds.CalculateDataEnv(period, carbon_type)
map_data = ds.PEAT_DATA_ADMIN if carbon_type == "p" else ds.DATA_DISTRICT
geojson_data1 = pg.load(filepath=settings.BASE_DIR +
"/main/static/data/geojson/batas_admin.geojson")
for feat in geojson_data1:
nama_kec = feat.properties["KABKOTA"]
if nama_kec in map_data.index:
feat.properties["DATA"] = map_data.loc[nama_kec][map_field]
else:
feat.properties["DATA"] = -1
stat_data = {}
if carbon_type != "p":
stat_data["total"] = round(ds.TOTAL_DATA / 1000.00, 2)
stat_data["rate"] = round(ds.TOTAL_RATE, 4)
stat_data["max_district"] = ds.DATA_DISTRICT_MAX_DATA
stat_data["min_district"] = ds.DATA_DISTRICT_MIN_DATA
stat_data["fast_district"] = ds.DATA_DISTRICT_MAX_RATE
context = {
'period': period_list,
'selected_period': period,
'map_data1': geojson_data1
}
if carbon_type == "p":
context[
"peat_data1"] = ds.PEAT_DATA_ADMIN if period == None else ds.PEAT_DATA_ADMIN.sort_values(
"DATA", ascending=False)
context[
"peat_data2"] = ds.PEAT_DATA_ZONE if period == None else ds.PEAT_DATA_ZONE.sort_values(
"DATA", ascending=False)
else:
main_index = [] if period == None else ds.DATA_PERIOD_PEAT.index.get_level_values(
level=0).unique()
sub_index = [] if period == None else ds.DATA_PERIOD_PEAT.index.get_level_values(
level=1).unique()
period_data = []
for idx in main_index:
item = {"label": idx, "data": ds.DATA_PERIOD_PEAT.loc[idx]}
period_data.append(item)
context["stat_data"] = stat_data
context["peat_data"] = ds.DATA_PERIOD
context["peat_period_index"] = main_index
context["peat_period_sub_index"] = sub_index
context["peat_period_data"] = period_data
context["district_data"] = ds.DATA_DISTRICT_TOP
context["zone_data"] = ds.DATA_ZONE_TOP
return render(request, template, context)