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Radar2Catchment_Windows.py
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Radar2Catchment_Windows.py
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#
# Radar to Catchment v3.3 for Windows
#
# Copyright Ruben Imhoff
#
# Contact: Ruben Imhoff (ruben.imhoff@wur.nl)
# Aart Overeem (aart.overeem@wur.nl)
#
#######################################################################################
print("This script requires some Python packages in order to run. If one of these packages is not yet installed, it is recommended to install them prior to running the script. For most systems, this is a matter of typing the following text in a command window: pip install [name of package] ")
import h5py
import numpy as np
import shapefile
import urllib
import ftplib
from osgeo import gdal
from osgeo import gdal_array
from osgeo import ogr, osr
import os
import sys
import osgeo.gdal
import subprocess
from osgeo import gdal, gdalnumeric, ogr, osr
from PIL import Image, ImageDraw
from subprocess import call
import tkinter
from tkinter import filedialog
from tkinter import *
import inspect
from numpy import *
import matplotlib
import matplotlib.pyplot as plt
from numpy import linspace
from numpy import meshgrid
from osgeo import gdalconst
from PIL import Image
from netCDF4 import Dataset
import netCDF4
import csv
import glob
from datetime import datetime
startTime = datetime.now()
# Ask what the user wants to do
while True:
root = Tk()
FirstQues = IntVar()
FirstQues.set(1)
options = [
("Get precipitation values for a pixel", 1),
("Get precipitation values for an area / a catchment", 2)
]
def ShowChoice():
print(FirstQues.get())
root.quit()
Label(root, text="""What would you like to do? Click on your choice and close the window.""", justify = LEFT, padx = 20).pack()
for txt, val in options:
Radiobutton(root, text=txt, padx = 20, variable = FirstQues, command = ShowChoice, value=val,tristatevalue=0).pack(anchor=W)
mainloop()
FirstQues = FirstQues.get()
break
if FirstQues == 1:
def safe():
print(e1.get())
DataQuestion = e1.get()
root2.quit()
root2 = Tk()
root2.title("Indicate which type of dataset will be supplied. Fill out the number of your choice and click on enter.")
Label(root2, text = "1 NLRadarhdf5_NL25", justify = LEFT).grid(row=0)
Label(root2, text = "2 NLRadarhdf5_NL21", justify = LEFT).grid(row=1)
Label(root2, text = "3 DERadar_Radolan", justify = LEFT).grid(row=2)
Label(root2, text = "4 NL KDC data in NETCDF", justify = LEFT).grid(row=3)
Label(root2, text = "5 OPERA - Radar Europe", justify = LEFT).grid(row=4)
Label(root2, text = "6 NASA GPM IMERG_HQprecipitation level 3", justify = LEFT).grid(row=5)
e1 = Entry(root2)
e1.grid(row=2, column=3)
Button(root2, text = "Enter", command = safe).grid(row=3,column=3,sticky=W,pady=4)
mainloop()
DataQuestion = e1.get()
print(DataQuestion)
if DataQuestion == "1":
########################################################
# Open the hdf5-files for the Netherlands, in this case the NL_25 dataset.
########################################################
root = tkinter.Tk()
root.withdraw()
dirpath = filedialog.askdirectory(parent=root, title='Open the main folder with hdf5-files and press OK')
list = []
for root, dirnames, filenames in os.walk(dirpath):
for filename in filenames:
if filename.endswith('.h5'):
list.append(os.path.join(root,filename))
########################################################
# It is time to start the 'For Loop'
########################################################
while True:
def safe():
print(e1.get())
print(e2.get())
Col = e1.get()
Row = e2.get()
master.quit()
master = Tk()
Label(master, text = "Column number of the target cell", justify = LEFT).grid(row=0)
Label(master, text = "Row number of the target cell", justify = LEFT).grid(row=1)
e1 = Entry(master)
e2 = Entry(master)
e1.grid(row=0, column=1)
e2.grid(row=1, column=1)
Button(master, text = "Enter", command = safe).grid(row=3,column=1,sticky=W,pady=4)
mainloop()
Col = e1.get()
Row = e2.get()
break
# Ask if the user wants to change reflectivities into mm.
def safe():
print(e1.get())
CalcQues = e1.get()
master.quit()
master = Tk()
Label(master, text = "Do you want to convert reflectivities [dBZ] into [mm] of rain? Note: only use this").grid(row=0)
Label(master, text = "tool when the provided data has reflectivities in dBZ. Please give the number of your answer: [1] Yes, [2] No and press enter").grid(row=1)
e1 = Entry(master)
e1.grid(row=0, column=1)
Button(master, text = "Enter", command = safe).grid(row=3,column=1,sticky=W,pady=4)
mainloop()
CalcQues = e1.get()
if CalcQues == "1":
def safe():
print(e1.get())
NumMin = e1.get()
master.quit()
master = Tk()
Label(master, text = "What is the temporal resolution of your data (e.g. 5 min. data)? Please give the amount in minutes.").grid(row=0)
e1 = Entry(master)
e1.grid(row=0, column=1)
Button(master, text = "Enter", command = safe).grid(row=3,column=1,sticky=W,pady=4)
mainloop()
NumMin = e1.get()
NumMin = float(NumMin)
else:
print("No conversion will take place.")
########################################################
# It is time to start the 'For Loop'
########################################################
Outfile = os.path.join(dirpath,'Results','PixelPrec.csv')
outcsv = open(Outfile,"w")
writer = csv.writer(outcsv, delimiter = ",")
writer.writerow(['Name','Precipitation [mm]'])
for x in range(0, len(list)):
hdf5filename = list[x]
file = h5py.File(list[x],'r+')
filedata = file['/image1/image_data'][()] # Open "image1" dataset under the root group,
# this dataset consists of the accumulated 5 min precipitation amounts.
if CalcQues == "1":
filedata = 0.5 * filedata - 32
filedata = ((10.**((filedata-23)/16))/(60/NumMin))
if CalcQues == "2":
filedata = filedata * 0.01
basename = os.path.basename(hdf5filename)
basenametxt = os.path.splitext(basename)[0]
print(basenametxt)
# Multiply the data with 0.01 to get mm.
filedata = filedata * 0.01
Value = filedata[Row,Col]
writer.writerow([basenametxt, Value])
print("End of this script.")
if DataQuestion == "2":
########################################################
# Open the hdf5-files for the Netherlands, in this case the NL_21 dataset.
########################################################
root = tkinter.Tk()
root.withdraw()
dirpath = filedialog.askdirectory(parent=root, title='Open the main folder with hdf5-files and press OK')
list = []
for root, dirnames, filenames in os.walk(dirpath):
for filename in filenames:
if filename.endswith('.h5'):
list.append(os.path.join(root,filename))
########################################################
# It is time to start the 'For Loop'
########################################################
while True:
def safe():
print(e1.get())
print(e2.get())
Col = e1.get()
Row = e2.get()
master.quit()
master = Tk()
Label(master, text = "Column number of the target cell", justify = LEFT).grid(row=0)
Label(master, text = "Row number of the target cell", justify = LEFT).grid(row=1)
e1 = Entry(master)
e2 = Entry(master)
e1.grid(row=0, column=1)
e2.grid(row=1, column=1)
Button(master, text = "Enter", command = safe).grid(row=3,column=1,sticky=W,pady=4)
mainloop()
Col = e1.get()
Row = e2.get()
break
# Ask if the user wants to change reflectivities into mm.
def safe():
print(e1.get())
CalcQues = e1.get()
master.quit()
master = Tk()
Label(master, text = "Do you want to convert reflectivities [dBZ] into [mm] of rain? Note: only use this").grid(row=0)
Label(master, text = "tool when the provided data has reflectivities in dBZ. Please give the number of your answer: [1] Yes, [2] No and press enter").grid(row=1)
e1 = Entry(master)
e1.grid(row=0, column=1)
Button(master, text = "Enter", command = safe).grid(row=3,column=1,sticky=W,pady=4)
mainloop()
CalcQues = e1.get()
if CalcQues == "1":
def safe():
print(e1.get())
NumMin = e1.get()
master.quit()
master = Tk()
Label(master, text = "What is the temporal resolution of your data (e.g. 5 min. data)? Please give the amount in minutes.").grid(row=0)
e1 = Entry(master)
e1.grid(row=0, column=1)
Button(master, text = "Enter", command = safe).grid(row=3,column=1,sticky=W,pady=4)
mainloop()
NumMin = e1.get()
NumMin = float(NumMin)
else:
print("No conversion will take place.")
########################################################
# It is time to start the 'For Loop'
########################################################
Outfile = os.path.join(dirpath,'Results','PixelPrec.csv')
outcsv = open(Outfile,"wb")
writer = csv.writer(outcsv, delimiter = ",")
writer.writerow(['Name','Precipitation [mm]'])
for x in range(0, len(list)):
hdf5filename = list[x]
file = h5py.File(list[x],'r+')
filedata = file['/image1/image_data'][()] # Open "image1" dataset under the root group,
# this dataset consists of the accumulated 5 min precipitation amounts.
if CalcQues == "1":
filedata = 0.5 * filedata - 32
filedata = ((10.**((filedata-23)/16))/(60/NumMin))
if CalcQues == "2":
filedata = filedata * 0.01
basename = os.path.basename(hdf5filename)
basenametxt = os.path.splitext(basename)[0]
print(basenametxt)
# Multiply the data with 0.01 to get mm.
filedata = filedata * 0.01
Value = filedata[Row,Col]
writer.writerow([basenametxt, Value])
print("End of this script.")
if DataQuestion == "3":
########################################################
# Open the radolan radar dataset for Germany.
########################################################
root = tkinter.Tk()
root.withdraw()
dirpath = filedialog.askdirectory(parent=root, title='Open the main folder with ASCII-files and press OK')
radolanlist = []
for root, dirnames, filenames in os.walk(dirpath):
for filename in filenames:
if filename.endswith('.asc'):
radolanlist.append(os.path.join(root,filename))
########################################################
# It is time to start the 'For Loop'
########################################################
Outfile = os.path.join(dirpath,'Results','PixelPrec.csv')
outcsv = open(Outfile,"wb")
writer = csv.writer(outcsv, delimiter = ",")
writer.writerow(['Name','Precipitation [mm]'])
while True:
def safe():
print(e1.get())
print(e2.get())
Col = e1.get()
Row = e2.get()
master.quit()
master = Tk()
Label(master, text = "Column number of the target cell", justify = LEFT).grid(row=0)
Label(master, text = "Row number of the target cell", justify = LEFT).grid(row=1)
e1 = Entry(master)
e2 = Entry(master)
e1.grid(row=0, column=1)
e2.grid(row=1, column=1)
Button(master, text = "Enter", command = safe).grid(row=3,column=1,sticky=W,pady=4)
mainloop()
Col = e1.get()
Row = e2.get()
break
for x in range(0, len(radolanlist)):
radolanfilename = radolanlist[x]
filedata = np.loadtxt(radolanlist[x], skiprows=6)
basename = os.path.basename(radolanfilename)
basenametxt = os.path.splitext(basename)[0]
print(basenametxt)
Value = filedata[Row,Col]
writer.writerow([basenametxt, Value])
print("End of this script.")
if DataQuestion == "4":
########################################################
# Open the NETCDF-files for the Netherlands. In this case that is the monthly averaged precipitation, but it could also be hourly or five minute data.
########################################################
root = tkinter.Tk()
root.withdraw()
dirpath = filedialog.askdirectory(parent=root, title='Open the main folder with NETCDF-files and press OK')
list = []
for root, dirnames, filenames in os.walk(dirpath):
for filename in filenames:
if filename.endswith('.nc'):
list.append(os.path.join(root,filename))
########################################################
# It is time to start the 'For Loop'
########################################################
while True:
def safe():
print(e1.get())
print(e2.get())
Col = e1.get()
Row = e2.get()
master.quit()
master = Tk()
Label(master, text = "Column number of the target cell", justify = LEFT).grid(row=0)
Label(master, text = "Row number of the target cell", justify = LEFT).grid(row=1)
e1 = Entry(master)
e2 = Entry(master)
e1.grid(row=0, column=1)
e2.grid(row=1, column=1)
Button(master, text = "Enter", command = safe).grid(row=3,column=1,sticky=W,pady=4)
mainloop()
Col = e1.get()
Row = e2.get()
break
Outfile = os.path.join(dirpath,'Results','PixelPrec.csv')
outcsv = open(Outfile,"wb")
writer = csv.writer(outcsv, delimiter = ",")
writer.writerow(['Name','Precipitation [mm]'])
for x in range(0, len(list)):
netcdffilename = list[x]
file = Dataset(list[x],'r')
values = file.variables['prediction'][:,:]
# Get the name of the file path and the file itself
dirname = os.path.dirname(netcdffilename)
basename = os.path.basename(netcdffilename)
basenametxt = os.path.splitext(basename)[0]
print(basename)
# The data has to be converted into numpy arrays to make them ready for use.
np_data = np.array(values)
np_data = np_data.flatten()
np_data = np_data[::-1]
New = np_data.reshape(315,266)
New = np.fliplr(New)
Value = New[Row,Col]
writer.writerow([basenametxt, Value])
print("End of this script.")
if DataQuestion == "5":
########################################################
# Open the hdf5-files for the OPERA-dataset of Europe.
########################################################
root = tkinter.Tk()
root.withdraw()
dirpath = filedialog.askdirectory(parent=root, title='Open the main folder with hdf5-files and press OK')
list = []
for root, dirnames, filenames in os.walk(dirpath):
for filename in filenames:
if filename.endswith('.h5'):
list.append(os.path.join(root,filename))
########################################################
# It is time to start the 'For Loop'
########################################################
while True:
def safe():
print(e1.get())
print(e2.get())
Col = e1.get()
Row = e2.get()
master.quit()
master = Tk()
Label(master, text = "Column number of the target cell", justify = LEFT).grid(row=0)
Label(master, text = "Row number of the target cell", justify = LEFT).grid(row=1)
e1 = Entry(master)
e2 = Entry(master)
e1.grid(row=0, column=1)
e2.grid(row=1, column=1)
Button(master, text = "Enter", command = safe).grid(row=3,column=1,sticky=W,pady=4)
mainloop()
Col = e1.get()
Row = e2.get()
break
# Ask if the user wants to change reflectivities into mm.
def safe():
print(e1.get())
CalcQues = e1.get()
master.quit()
master = Tk()
Label(master, text = "Do you want to convert reflectivities [dBZ] into [mm] of rain? Note: only use this").grid(row=0)
Label(master, text = "tool when the provided data has reflectivities in dBZ. Please give the number of your answer: [1] Yes, [2] No and press enter").grid(row=1)
e1 = Entry(master)
e1.grid(row=0, column=1)
Button(master, text = "Enter", command = safe).grid(row=3,column=1,sticky=W,pady=4)
mainloop()
CalcQues = e1.get()
if CalcQues == "1":
def safe():
print(e1.get())
NumMin = e1.get()
master.quit()
master = Tk()
Label(master, text = "What is the temporal resolution of your data (e.g. 5 min. data)? Please give the amount in minutes.").grid(row=0)
e1 = Entry(master)
e1.grid(row=0, column=1)
Button(master, text = "Enter", command = safe).grid(row=3,column=1,sticky=W,pady=4)
mainloop()
NumMin = e1.get()
NumMin = float(NumMin)
else:
print("No conversion will take place.")
########################################################
# It is time to start the 'For Loop'
########################################################
Outfile = os.path.join(dirpath,'Results','PixelPrec.csv')
outcsv = open(Outfile,"wb")
writer = csv.writer(outcsv, delimiter = ",")
writer.writerow(['Name','Precipitation [mm]'])
for x in range(0, len(list)):
hdf5filename = list[x]
file = h5py.File(list[x],'r+')
filedata = file['/image1/image_data'][()] # Open "image1" dataset under the root group,
# this dataset consists of the accumulated 5 min precipitation amounts.
if CalcQues == "1":
filedata = 0.5 * filedata - 32
filedata = ((10.**((filedata-23)/16))/(60/NumMin))
if CalcQues == "2":
filedata = filedata * 0.01
basename = os.path.basename(hdf5filename)
basenametxt = os.path.splitext(basename)[0]
print(basenametxt)
# Multiply the data with 0.01 to get mm.
filedata = filedata * 0.01
Value = filedata[Row,Col]
writer.writerow([basenametxt, Value])
print("End of this script.")
if DataQuestion == "6":
########################################################
# Open the hdf5-files of the NASA GPM IMERG High Quality Precipitation level 3 dataset.
########################################################
dirpath = filedialog.askdirectory(parent=root, title='Open the main folder with hdf5-files and press OK')
list = []
for root, dirnames, filenames in os.walk(dirpath):
for filename in filenames:
if filename.endswith('.HDF5'):
list.append(os.path.join(root,filename))
root = tkinter.Tk()
root.withdraw()
########################################################
# It is time to start the 'For Loop'
########################################################
while True:
def safe():
print(e1.get())
print(e2.get())
Col = e1.get()
Row = e2.get()
master.quit()
master = Tk()
Label(master, text = "Column number of the target cell", justify = LEFT).grid(row=0)
Label(master, text = "Row number of the target cell", justify = LEFT).grid(row=1)
e1 = Entry(master)
e2 = Entry(master)
e1.grid(row=0, column=1)
e2.grid(row=1, column=1)
Button(master, text = "Enter", command = safe).grid(row=3,column=1,sticky=W,pady=4)
mainloop()
Col = e1.get()
Row = e2.get()
break
Outfile = os.path.join(dirpath,'Results','PixelPrec.csv')
outcsv = open(Outfile,"wb")
writer = csv.writer(outcsv, delimiter = ",")
writer.writerow(['Name','Precipitation [mm]'])
for x in range(0, len(list)):
hdf5filename = list[x]
file = h5py.File(list[x],'r+')
filedata = file['/Grid/HQprecipitation'][()] # Open "image1" dataset under the root group,
# this dataset consists of the accumulated 5 min precipitation amounts.
filedata = filedata * 0.5 # The units are mm/h, while the temporal resolution is 30 min.
# Get the name of the file path and the file itself
dirname = os.path.dirname(hdf5filename)
basename = os.path.basename(hdf5filename)
basenametxt = os.path.splitext(basename)[0]
print(basename)
Value = filedata[Row,Col]
writer.writerow([basenametxt, Value])
print("End of this script.")
if FirstQues == 2:
#########################################################
# Time to read the shapefile
#########################################################
root = tkinter.Tk()
root.withdraw()
filename = filedialog.askopenfilename(parent=root,filetypes=[("ESRI Shapefile","*.shp"),("all files","*.*")],title='Choose a Shapefile of your study area')
sf = shapefile.Reader(filename)
#########################################################
# Get the projection of the shapefiles
##########################################################
driver = ogr.GetDriverByName('ESRI Shapefile')
dataset = driver.Open(filename)
# from Layer
layer = dataset.GetLayer()
spatialRef = layer.GetSpatialRef()
# from Geometry
feature = layer.GetNextFeature()
geom = feature.GetGeometryRef()
spatialRef = geom.GetSpatialReference()
print(spatialRef)
#########################################################
# Indicate which type of data set will be supplied
#########################################################
def safe():
print(e1.get())
DataQuestion = e1.get()
root2.quit()
root2 = Tk()
root2.title("Indicate which type of dataset will be supplied. Fill out the number of your choice and click on enter.")
Label(root2, text = "1 NLRadarhdf5_NL25", justify = LEFT).grid(row=0)
Label(root2, text = "2 NLRadarhdf5_NL21", justify = LEFT).grid(row=1)
Label(root2, text = "3 DERadar_Radolan", justify = LEFT).grid(row=2)
Label(root2, text = "4 NL KDC data in NETCDF", justify = LEFT).grid(row=3)
Label(root2, text = "5 OPERA - Radar Europe", justify = LEFT).grid(row=4)
Label(root2, text = "6 NASA GPM IMERG_HQprecipitation level 3", justify = LEFT).grid(row=5)
e1 = Entry(root2)
e1.grid(row=2, column=3)
Button(root2, text = "Enter", command = safe).grid(row=3,column=3,sticky=W,pady=4)
mainloop()
DataQuestion = e1.get()
print(DataQuestion)
#########################################################
# Reproject the geometry of the shapefile
#########################################################
# set file names
infile = filename
dirname = os.path.dirname(filename)
basename = os.path.basename(filename)
basenametxt = os.path.splitext(basename)[0]
outfile = os.path.join(dirname, basenametxt+'_Reprojected.shp')
# The projection will be based on the projection of the given data set
if DataQuestion == "1":
ShapefileProj = '+proj=stere +lat_0=90 +lon_0=0.0 +lat_ts=60.0 +a=6378.137 +b=6356.752 +x_0=0 +y_0=0'
if DataQuestion == "2":
ShapefileProj = '+proj=stere +lat_0=90 +lon_0=0.0 +lat_ts=60.0 +a=6378.137 +b=6356.752 +x_0=0 +y_0=0'
if DataQuestion == "3":
ShapefileProj = '+proj=stere +lat_0=90.0 +lat_ts=60.0 +lon_0=10.0 +a=6370040 +b=6370040 +units=m'
if DataQuestion == "4":
ShapefileProj = '+proj=sterea +lat_0=52.15616055555555 +lon_0=5.38763888888889 +k=0.9999079 +x_0=155000 +y_0=463000 +ellps=bessel +units=m +no_defs'
if DataQuestion == "5":
ShapefileProj = '+proj=stere +lat_0=90 +lon_0=0.0 +lat_ts=60.0 +a=6378.137 +b=6356.752 +x_0=0 +y_0=0'
if DataQuestion == "6":
ShapefileProj = '+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs'
subprocess.call(['ogr2ogr', '-t_srs', ShapefileProj, outfile, infile])
#########################################################
# Define the new, reprojected shapefile as sfnew
# We are going to rasterize this shapefile, since the resulting radar raster (after
# rasterizing the hdf5-dataset) should be exactly the same as this raster of this shapefile
#########################################################
sfnew = shapefile.Reader(outfile)
# 1. Define pixel_size and NoData value of new raster
NoData_value = -9999
# Let's ask for the cell size and use that for the xres, yres and pixel_size
def safe():
print(e1.get())
Res = e1.get()
master.quit()
master = Tk()
Label(master, text = "Please give the desired pixel resolution in km or", justify = LEFT).grid(row=0)
Label(master, text = "in degrees, depending on the provided data set.", justify = LEFT).grid(row=1)
e1 = Entry(master)
e1.grid(row=0, column=1)
Button(master, text = "Enter", command = safe).grid(row=3,column=1,sticky=W,pady=4)
mainloop()
Res = e1.get()
Res = float(Res)
if DataQuestion == "3":
Res = Res * 1000
if DataQuestion == "4":
Res = Res * 1000
#Res = input("Please give the desired pixel resolution in km2")
x_res = Res
y_res = Res
Pixel_size = Res
# 2. Filenames for in- and output
_out = os.path.join(dirname, basenametxt+'_Reprojected.tiff')
# 3. Open Shapefile
driver = ogr.GetDriverByName('ESRI Shapefile')
shapefile = driver.Open(outfile)
source_layer = shapefile.GetLayer()
# Obtain xmin, xmax, ymin and ymax as floats
x_min, x_max, y_min, y_max = source_layer.GetExtent()
# Round the values for xmin, xmax, ymin and ymax (make a rough rounding)
# in order to not get a too small extent. Finally, make integer values of it.
xmin = int(round(x_min, 0) - 1)
xmax = int(round(x_max, 0) + 1)
ymin = int(round(y_min, 0) - 1)
ymax = int(round(y_max, 0) + 1)
# 4. Create Target - TIFF
cols = int( (xmax - xmin) / x_res )
rows = int( (ymax - ymin) / y_res )
# Save raster
# TO DO: Make this an option, it's not necessary to save it in all cases.
_raster = gdal.GetDriverByName('GTiff').Create(_out, cols, rows, 1, gdal.GDT_Byte)
_raster.SetGeoTransform((xmin, x_res, 0, ymax, 0, -y_res))
projection = osr.SpatialReference()
projection.ImportFromProj4(ShapefileProj)
_raster.SetProjection(projection.ExportToWkt())
_band = _raster.GetRasterBand(1)
_band.SetNoDataValue(NoData_value)
# 5. Rasterize
gdal.RasterizeLayer(_raster, [1], source_layer, None, None, [1], ['ALL_TOUCHED=TRUE'])
inraster = _out
########################################################
# Open the dataset
########################################################
if DataQuestion == "1":
########################################################
# Open the hdf5-files for the Netherlands, in this case the NL_25 dataset.
########################################################
dirpath = filedialog.askdirectory(parent=root, title='Open the main folder with hdf5-files and press OK')
list = []
for root, dirnames, filenames in os.walk(dirpath):
for filename in filenames:
if filename.endswith('.h5'):
list.append(os.path.join(root,filename))
print(dirpath)
# Ask if the user wants to change reflectivities into mm.
def safe():
print(e1.get())
CalcQues = e1.get()
master.quit()
master = Tk()
Label(master, text = "Do you want to convert reflectivities [dBZ] into [mm] of rain? Note: only use this").grid(row=0)
Label(master, text = "tool when the provided data has reflectivities in dBZ. Please give the number of your answer: [1] Yes, [2] No and press enter").grid(row=1)
e1 = Entry(master)
e1.grid(row=0, column=1)
Button(master, text = "Enter", command = safe).grid(row=3,column=1,sticky=W,pady=4)
mainloop()
CalcQues = e1.get()
if CalcQues == "1":
def safe():
print(e1.get())
NumMin = e1.get()
master.quit()
master = Tk()
Label(master, text = "What is the temporal resolution of your data (e.g. 5 min. data)? Please give the amount in minutes.").grid(row=0)
e1 = Entry(master)
e1.grid(row=0, column=1)
Button(master, text = "Enter", command = safe).grid(row=3,column=1,sticky=W,pady=4)
mainloop()
NumMin = e1.get()
NumMin = float(NumMin)
else:
print("No conversion will take place.")
########################################################
# It is time to start the 'For Loop'
########################################################
for x in range(0, len(list)):
hdf5filename = list[x]
file = h5py.File(list[x],'r+')
filedata = file['/image1/image_data'][()] # Open "image1" dataset under the root group,
# this dataset consists of the accumulated 5 min precipitation amounts.
if CalcQues == "1":
filedata = 0.5 * filedata - 32
filedata = ((10.**((filedata-23)/16))/(60/NumMin))
if CalcQues == "2":
filedata = filedata * 0.01
# Get the name of the file path and the file itself
dirname = os.path.dirname(hdf5filename)
basename = os.path.basename(hdf5filename)
basenametxt = os.path.splitext(basename)[0]
print(basename)
#########################################################
# Create a raster from the hdf5 file
#########################################################
# Make a raster out of the hdf5 dataset
# First convert the data into numpy arrays
np_data = np.array(filedata)
# Get the spatial extent of the data
num_cols = float(np_data.shape[1])
num_rows = float(np_data.shape[0])
xmin = 0
xmax = 699
ymin = 0
ymax = -3650 # offset is 3650
xres = (xmax - xmin)/num_cols
yres = (ymax - ymin)/num_rows
# Time to set up the transformation which is necessary to create the raster we want
geotransform = (xmin, xres, 0, ymin, 0, -yres)
# We are going to create the raster with the right coordinate encoding and projection
def array_to_raster(array, outfilename):
dst_filename = outfilename
x_pixels = 700
y_pixels = 765
pixel_size = 1
x_min = 0
y_max = -3650
driver = gdal.GetDriverByName('GTiff')
dataset = driver.Create(
dst_filename,
x_pixels,
y_pixels,
1,
gdal.GDT_Float32, )
dataset.SetGeoTransform((
x_min,
pixel_size,
0,
y_max,
0,
-pixel_size))
projection = osr.SpatialReference()
projection.ImportFromProj4('+proj=stere +lat_0=90 +lon_0=0.0 +lat_ts=60.0 +a=6378.137 +b=6356.752 +x_0=0 +y_0=0')
dataset.SetProjection(projection.ExportToWkt())
dataset.GetRasterBand(1).WriteArray(array)
dataset.FlushCache() # This is the way to write it to the disk
return dataset, dataset.GetRasterBand(1)
rasterfile = os.path.join(dirpath,'RasterIn', basenametxt+'.tiff')
print(rasterfile)
array_to_raster(np_data, rasterfile)
#########################################################
# Time to clip the raster with the rasterized shapefile
#########################################################
# inraster = _out --> This is already defined in the rasterizing of the shapefile.
outraster = os.path.join(dirpath,'RasterIn', basenametxt+'Reprojected.tiff') # Here, the clip is saved as an ASCII file, but a .tiff extension is also possible.
# Source
src_filename = rasterfile
src = gdal.Open(src_filename, gdalconst.GA_ReadOnly)
src_proj = src.GetProjection()
src_geotrans = src.GetGeoTransform()
# We want a section of source that matches this:
match_filename = inraster
match_ds = gdal.Open(match_filename, gdalconst.GA_ReadOnly)
match_proj = match_ds.GetProjection()
match_geotrans = match_ds.GetGeoTransform()
wide = match_ds.RasterXSize
high = match_ds.RasterYSize
# Output / destination
dst_filename = outraster
dst = gdal.GetDriverByName('GTiff').Create(dst_filename, wide, high, 1, gdalconst.GDT_Float32)
dst.SetGeoTransform( match_geotrans )
dst.SetProjection( match_proj)
# Do the work. Check whether the pixel resolution is the same as the hdf5 dataset
# resolution. If yes, use a nearest neighbour conversion. If not, use a cubic spline
# conversion for downscaling and averaging for upscaling to get the best possible
# reprojection on the new grid.
if Res == 1:
gdal.ReprojectImage(src, dst, src_proj, match_proj, gdalconst.GRA_NearestNeighbour)
elif Res > 1:
gdal.ReprojectImage(src, dst, src_proj, match_proj, gdalconst.GRA_Average)
else:
gdal.ReprojectImage(src, dst, src_proj, match_proj, gdalconst.GRA_CubicSpline)
# We do have the hdf5 dataset as GeoTiff in the correct raster grid and extent. Now, it's
# time to only keep the pixels that overlap with the rasterized shapefile.
Result = os.path.join(dirpath,'Results', basenametxt+'.tiff')
Catchment = gdal.Open(_out)
xSize = dst.RasterXSize
ySize = dst.RasterYSize
InputBand = dst.ReadAsArray(0,0,xSize,ySize)
if CalcQues == "1":
NDvalue = 0.5 * 255 - 32
NDvalue = ((10.**((NDvalue-23)/16))/(60/NumMin))
InputBand = np.where(InputBand < NDvalue, InputBand, -999)
if CalcQues == "2":
InputBand = np.where(InputBand < 655.35, InputBand, -999)
CatchmentBand = _raster.ReadAsArray(0,0,xSize,ySize)
OutputData = np.where(CatchmentBand > 0, InputBand, -999)