ORIGINAL: Python script for plotting Doppler Lidar data share by Dr. Oliver...

#!/usr/bin/env python3

# -*- coding: utf-8 -*-

import matplotlib

matplotlib.use('Agg') # use non gui backend

import numpy as np

#from netCDF4 import Dataset

import os

from datetime import datetime, timedelta

#import matplotlib.pyplot as plt

from matplotlib import pylab as plt

import sys

import datetime

from datetime import datetime

from datetime import timedelta 

import matplotlib.dates as mdates

import matplotlib.pyplot as plt

from numpy import meshgrid

import matplotlib.colors as mc

from matplotlib.colors import ListedColormap, LinearSegmentedColormap 

from mpl_toolkits.axes_grid1.axes_divider import make_axes_locatable

#function imports .hpl file and stores information in dictionary data_temp

def hpl2dict(file_path):

    #import hpl files into intercal storage

    with open(file_path, 'r') as text_file:

        lines=text_file.readlines()

    #write lines into Dictionary

    data_temp=dict()

    header_n=17 #length of header

    data_temp['filename']=lines[0].split()[-1]

    data_temp['system_id']=int(lines[1].split()[-1])

    data_temp['number_of_gates']=int(lines[2].split()[-1])

    data_temp['range_gate_length_m']=float(lines[3].split()[-1])

    data_temp['gate_length_pts']=int(lines[4].split()[-1])

    data_temp['pulses_per_ray']=int(lines[5].split()[-1])

    data_temp['number_of_waypoints_in_file']=int(lines[6].split()[-1])

    rays_n=(len(lines)-header_n)/(data_temp['number_of_gates']+1)

    if not rays_n.is_integer():

        raise Exception('Number of lines does not match expected format')

    data_temp['no_of_rays_in_file']=int(rays_n)

    data_temp['scan_type']=' '.join(lines[7].split()[2:])

    data_temp['focus_range']=lines[8].split()[-1]

    data_temp['start_time']=' '.join(lines[9].split()[-2:])

    data_temp['resolution']=('%s %s' % (lines[10].split()[-1],'m s-1'))

    data_temp['range_gates']=np.arange(0,data_temp['number_of_gates'])

    data_temp['center_of_gates']=(data_temp['range_gates']+0.5)*data_temp['range_gate_length_m']

    #dimensions of data set

    gates_n=data_temp['number_of_gates']

    rays_n=data_temp['no_of_rays_in_file']

    #keys for measurement variables are predefined as symetric numpy arrays filled with NaN values

    data_temp['radial_velocity']=np.full([gates_n,rays_n],np.nan) #m/s

    data_temp['intensity']=np.full([gates_n,rays_n],np.nan) #SNR+1

    data_temp['beta']=np.full([gates_n,rays_n],np.nan) #m-1 sr-1

    data_temp['elevation']=np.full(rays_n,np.nan) #degrees

    data_temp['azimuth']=np.full(rays_n,np.nan) #degrees

    data_temp['decimal_time']=np.full(rays_n,np.nan) #hours

    data_temp['pitch']=np.full(rays_n,np.nan) #degrees

    data_temp['roll']=np.full(rays_n,np.nan) #degrees

    for ri in range(0,rays_n): #loop through rays

        lines_temp=lines[header_n+(ri*gates_n)+ri+1:header_n+(ri*gates_n)+gates_n+ri+1]

        header_temp=np.asarray(lines[header_n+(ri*gates_n)+ri].split(),dtype=float)

        data_temp['decimal_time'][ri]=header_temp[0]

        data_temp['azimuth'][ri]=header_temp[1]

        data_temp['elevation'][ri]=header_temp[2]

        data_temp['pitch'][ri]=header_temp[3]

        data_temp['roll'][ri]=header_temp[4]

        for gi in range(0,gates_n): #loop through range gates

            line_temp=np.asarray(lines_temp[gi].split(),dtype=float)

            data_temp['radial_velocity'][gi,ri]=line_temp[1]

            data_temp['intensity'][gi,ri]=line_temp[2]

            data_temp['beta'][gi,ri]=line_temp[3]    

    return data_temp

'''

#=======================

# select data files

#=======================

# print count of specified arguments

print("Sie haben %d Argument(e) angegeben." % len(sys.argv))

# repeat for each argument

for argument in sys.argv:

  # print current argument

  print(argument)

'''

def file2plot(datetime_now, hour_in, loop_start):

    #hour_in = int(12)

    #hour_in = int(sys.argv[1])

#    datetime_now = datetime(year=2020, month=7, day=1, hour=hour_in, minute=3, second=23)

    #datetime_now = datetime(year=2020, month=7, day=1, hour=12, minute=3, second=23)

    print('Now:   ', datetime_now)

    #/ipmserver/ag_fernerkundung/Projekte/LAFO/DL/DL_UAE

    #/data/data_shared/DopplerLidar/DL_UAE/Proc/

    #/data/data_shared/DopplerLidar/DL_UAE/Quicklooks

    #/data/data_personal/quicklooks/DL/metek_server

    path1=os.path.join('/data/data_shared/DopplerLidar/DL_156/Proc', (datetime_now - timedelta(hours=3)).strftime("%Y"), (datetime_now - timedelta(hours=3)).strftime("%Y%m"), (datetime_now - timedelta(hours=3)).strftime("%Y%m%d"))

    file1 = 'Stare_156_' + (datetime_now - timedelta(hours=3)).strftime("%Y%m%d_%H") + '.hpl'

    file_path1 = os.path.join(path1, file1)

    path2=os.path.join('/data/data_shared/DopplerLidar/DL_156/Proc', (datetime_now - timedelta(hours=2)).strftime("%Y"), (datetime_now - timedelta(hours=2)).strftime("%Y%m"), (datetime_now - timedelta(hours=2)).strftime("%Y%m%d"))

    file2 = 'Stare_156_' + (datetime_now - timedelta(hours=2)).strftime("%Y%m%d_%H") + '.hpl'

    file_path2 = os.path.join(path2, file2)

    path3=os.path.join('/data/data_shared/DopplerLidar/DL_156/Proc', (datetime_now - timedelta(hours=1)).strftime("%Y"), (datetime_now - timedelta(hours=1)).strftime("%Y%m"), (datetime_now - timedelta(hours=1)).strftime("%Y%m%d"))

    file3 = 'Stare_156_' + (datetime_now - timedelta(hours=1)).strftime("%Y%m%d_%H") + '.hpl'

    file_path3 = os.path.join(path3, file3)

    path_out1=os.path.join('/data/data_personal/quicklooks/DL', datetime_now.strftime("%Y"), datetime_now.strftime("%Y%m"), datetime_now.strftime("%Y%m%d"))

    file_out1='LAFO_'+datetime_now.strftime("%Y%m%d_%H")+'_DLw.png'

    file_path_out1 = os.path.join(path_out1, file_out1)

    #path_out2=os.path.join('/data/data_shared/DopplerLidar/DL_UAE/Quicklooks', datetime_now.strftime("%Y"), datetime_now.strftime("%m%d"))

    path_out2=os.path.join('/data/data_personal/quicklooks/DL/metek_server', datetime_now.strftime("%Y"), datetime_now.strftime("%m%d"))

    file_out2=datetime_now.strftime("%H")+'01.LAFO_DLw.png'

    file_path_out2 = os.path.join(path_out2, file_out2)

    file_out3=datetime_now.strftime("%H")+'01.LAFO_DLbeta.png'

    file_path_out3 = os.path.join(path_out2, file_out3)

    file_out4=datetime_now.strftime("%H")+'01.LAFO_DLsnr.png'

    file_path_out4 = os.path.join(path_out2, file_out4)

    file_out5=datetime_now.strftime("%H")+'01.LAFO_DLw_4km.png'

    file_path_out5 = os.path.join(path_out2, file_out5)

    file_out6=datetime_now.strftime("%H")+'01.LAFO_DLbeta_4km.png'

    file_path_out6 = os.path.join(path_out2, file_out6)

    print('file1: ', file_path1)

    print('file2: ', file_path2)

    print('file3: ', file_path3)

    print('file_out1: ', file_path_out1)

    print('file_out2: ', file_path_out2)

    print('file_out3: ', file_path_out3)

    print('file_out4: ', file_path_out4)

    print('file_out5: ', file_path_out5)

    print('file_out6: ', file_path_out6)

    # quit python script

    #sys.exit(0)

    file_exists = 1

    if not os.path.exists(file_path1):

        #raise Exception('%s cannot be found' %os.path.basename(file_path1))

        file_exists = 0

        print('%s cannot be found' %os.path.basename(file_path1))

    if not os.path.exists(file_path2):

        #raise Exception('%s cannot be found' %os.path.basename(file_path2))

        file_exists = 0

        print('%s cannot be found' %os.path.basename(file_path2))

    if not os.path.exists(file_path3):

        #raise Exception('%s cannot be found' %os.path.basename(file_path3))

        file_exists = 0

        print('%s cannot be found' %os.path.basename(file_path3))

    if file_exists == 1:

        if not os.path.isdir(path_out1):

            #raise Exception('%s cannot be found' %os.path.basename(file_path2))

            print('Folder does not exist.')

            os.makedirs(path_out1)

            print('Quicklook folder created: %s' %os.path.basename(path_out1))

        if not os.path.isdir(path_out2):

            #raise Exception('%s cannot be found' %os.path.basename(file_path2))

            print('Folder does not exist.')

            os.makedirs(path_out2)

            print('Quicklook folder created: %s' %os.path.basename(path_out2))

        # read data from files

        data_temp1=hpl2dict(file_path1)

        print(data_temp1['filename'] + ' loaded.')

        data_temp2=hpl2dict(file_path2)

        print(data_temp2['filename'] + ' loaded.')

        data_temp3=hpl2dict(file_path3)

        print(data_temp3['filename'] + ' loaded.')

        # merge data_temp1, data_temp2, and date_temp3

        gates_n1=data_temp1['number_of_gates']

        rays_n1=data_temp1['no_of_rays_in_file']

        gates_n2=data_temp2['number_of_gates']

        rays_n2=data_temp2['no_of_rays_in_file']

        gates_n3=data_temp3['number_of_gates']

        rays_n3=data_temp3['no_of_rays_in_file']

        data_12=dict()

        data_12['filename']='Stare_115_' + (datetime_now - timedelta(hours=3)).strftime("%Y%m%d_%H") + '-' + (datetime_now - timedelta(hours=1)).strftime("%H") + '.hpl'

        data_12['system_id']=data_temp1['system_id']

        data_12['number_of_gates']=data_temp1['number_of_gates']

        data_12['range_gate_length_m']=data_temp1['range_gate_length_m']

        data_12['gate_length_pts']=data_temp1['gate_length_pts']

        data_12['pulses_per_ray']=data_temp1['pulses_per_ray']

        data_12['number_of_waypoints_in_file']=data_temp1['number_of_waypoints_in_file']

        data_12['no_of_rays_in_file']=int(rays_n1+rays_n2+rays_n3)

        data_12['scan_type']=data_temp1['scan_type']

        data_12['focus_range']=data_temp1['focus_range']

        data_12['start_time']=data_temp1['start_time']

        data_12['resolution']=data_temp1['resolution']

        data_12['range_gates']=np.arange(0,data_temp1['number_of_gates'])

        data_12['center_of_gates']=(data_temp1['range_gates']+0.5)*data_temp1['range_gate_length_m']

        #dimensions of data set

        gates_n=data_12['number_of_gates']

        rays_n=data_12['no_of_rays_in_file']

        #keys for measurement variables are predefined as symetric numpy arrays filled with NaN values

        data_12['radial_velocity']=np.full([gates_n,rays_n],np.nan) #m/s

        data_12['intensity']=np.full([gates_n,rays_n],np.nan) #SNR+1

        data_12['beta']=np.full([gates_n,rays_n],np.nan) #m-1 sr-1

        data_12['elevation']=np.full(rays_n,np.nan) #degrees

        data_12['azimuth']=np.full(rays_n,np.nan) #degrees

        data_12['decimal_time']=np.full(rays_n,np.nan) #hours

        data_12['date']=np.full(rays_n,np.nan) #date string

        data_12['pitch']=np.full(rays_n,np.nan) #degrees

        data_12['roll']=np.full(rays_n,np.nan) #degrees

        data_12['elevation'][0:rays_n1]=data_temp1['elevation'] #degrees

        data_12['elevation'][rays_n1:rays_n1+rays_n2]=data_temp2['elevation'] #degrees

        data_12['elevation'][rays_n1+rays_n2:]=data_temp3['elevation'] #degrees

        data_12['azimuth'][0:rays_n1]=data_temp1['azimuth'] #degrees

        data_12['azimuth'][rays_n1:rays_n1+rays_n2]=data_temp2['azimuth'] #degrees

        data_12['azimuth'][rays_n1+rays_n2:]=data_temp3['azimuth'] #degrees

        data_12['decimal_time'][0:rays_n1]=data_temp1['decimal_time'] #hours

        data_12['decimal_time'][rays_n1:rays_n1+rays_n2]=data_temp2['decimal_time'] #hours

        data_12['decimal_time'][rays_n1+rays_n2:]=data_temp3['decimal_time'] #hours

        data_12['pitch'][0:rays_n1]=data_temp1['pitch'] #degrees

        data_12['pitch'][rays_n1:rays_n1+rays_n2]=data_temp2['pitch'] #degrees

        data_12['pitch'][rays_n1+rays_n2:]=data_temp3['pitch'] #degrees

        data_12['roll'][0:rays_n1]=data_temp1['roll'] #degrees

        data_12['roll'][rays_n1:rays_n1+rays_n2]=data_temp2['roll'] #degrees

        data_12['roll'][rays_n1+rays_n2:]=data_temp3['roll'] #degrees

        data_12['radial_velocity'][:,0:rays_n1]=data_temp1['radial_velocity'] #m/s

        data_12['radial_velocity'][:,rays_n1:rays_n1+rays_n2]=data_temp2['radial_velocity'] #m/s

        data_12['radial_velocity'][:,rays_n1+rays_n2:]=data_temp3['radial_velocity'] #m/s

        data_12['intensity'][:,0:rays_n1]=data_temp1['intensity'] #m/s

        data_12['intensity'][:,rays_n1:rays_n1+rays_n2]=data_temp2['intensity'] #m/s

        data_12['intensity'][:,rays_n1+rays_n2:]=data_temp3['intensity'] #m/s

        data_12['beta'][:,0:rays_n1]=data_temp1['beta'] #m/s

        data_12['beta'][:,rays_n1:rays_n1+rays_n2]=data_temp2['beta'] #m/s

        data_12['beta'][:,rays_n1+rays_n2:]=data_temp3['beta'] #m/s

        #=======================

        # PLOTTING

        #=======================

        cmap = LinearSegmentedColormap.from_list("mycmap", ["lime","blue", "white", "red", "yellow"])

#        plt.rc('font', **{'family': 'serif', 'serif': ['Computer Modern']})

#        plt.rc('text', usetex=True)

#        plt.rc('text')

#        plt.rc('axes', labelsize=14)

#        plt.rc('xtick', labelsize=14)

#        plt.rc('ytick', labelsize=14)

        # masks data

        data_12['radial_velocity'] = np.ma.masked_less(data_12['radial_velocity'], -3)

        data_12['radial_velocity'] = np.ma.masked_greater(data_12['radial_velocity'], 3)

        data_12['beta'] = np.ma.masked_less(data_12['beta'], 1e-7)

        data_12['beta'] = np.ma.masked_greater(data_12['beta'], 1e-4)

        data_12['intensity'] = np.ma.masked_less(data_12['intensity'], 0.8)

        data_12['intensity'] = np.ma.masked_greater(data_12['intensity'], 1.6)

        temp1 = [data_temp1['start_time']]*len(data_temp1['decimal_time'])

        temp2 = [data_temp2['start_time']]*len(data_temp2['decimal_time'])

        temp3 = [data_temp3['start_time']]*len(data_temp3['decimal_time'])

        temp= temp1+temp2+temp3

        t_start = data_12['start_time'][:4]+'-' + data_12['start_time'][4:6] +\

                    '-' + data_12['start_time'][6:8]

        time = data_12['decimal_time']

        height = data_12['center_of_gates']

        Hours = time

        Minutes = 60 * (Hours % 1)

        Seconds = 60 * (Minutes % 1)

        timestamps = []

        for n in range(len(time)):

            day = temp[n][:4]+'-' + temp[n][4:6] +'-' + temp[n][6:8]+"%d:%02d:%02d" % (Hours[n], Minutes[n], Seconds[n])

            day1 = temp[n][:4]+'-' + temp[n][4:6] +'-' + temp[n][6:8]+"%d:%02d:%02d" % (Hours[0], Minutes[0], Seconds[0])

#            day = t_start+"%d:%02d:%02d" % (Hours[n], Minutes[n], Seconds[n])

#            day1 = t_start+"%d:%02d:%02d" % (Hours[0], Minutes[0], Seconds[0])

#            timestamps.append(datetime.datetime.strptime(day, '%Y-%m-%d%H:%M:%S'))

            timestamps.append(datetime.strptime(day, '%Y-%m-%d%H:%M:%S'))

        # plotting

        fig = plt.figure(figsize=[10, 6.2], dpi=100)

#        fig = plt.figure(figsize=[10, 6.2], dpi=75)

        xx, yy = meshgrid(timestamps, height)

        data_doppler = data_12['radial_velocity']

        data_beta = data_12['beta']

        data_snr = data_12['intensity']

        pc = plt.pcolormesh(xx, yy/1000, data_doppler, cmap=cmap)

        plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))

#        plt.yticks(ticks=[0, 2, 4, 6, 8, 10], labels=['0', '2', '4', '6', '8', '10'])	# 'ticks' and 'labels' in new python version not allowed any more

        plt.yticks([0, 2, 4, 6, 8, 10], ['0', '2', '4', '6', '8', '10'])

        plt.tick_params('both', length=8, width=0.5, which='major')

        plt.ylabel('Range (km)')

        plt.xlabel('Time (UTC)')

        ax2_divider = make_axes_locatable(plt.gca())

        cax2 = ax2_divider.append_axes("top", size=0.12, pad="20%")

        clb = fig.colorbar(pc, cax=cax2, orientation="horizontal")

        clb.ax.set_title('Doppler Wind Velocity, m/s', size=24)

#        plt.gcf().text(0.1, 0.78, 'Date:'+'\t'+'\t'+t_start, fontsize=14)

#        plt.gcf().text(0.3, 0.78, 'Time:'+'\t'+'\t'+day1[10:15] + '\t' + '\t' + 'to' +

#                       '\t' + '\t'+day[0:10]+' '+day[9:15], fontsize=14)

        plt.gcf().text(0.1, 0.78, t_start+' '+day1[10:15], fontsize=14)

        plt.gcf().text(0.3, 0.78, 'to'+' '+day[0:10]+' '+day[10:15], fontsize=14)

        plt.gcf().text(0.75, 0.78, 'Az = '+str(int(data_12['azimuth'][0])),

                       fontsize=14)

        plt.gcf().text(0.9, 0.78, 'El = '+str(int(data_12['elevation'][0])),

                       fontsize=14)

        plt.tight_layout()

        #       plt.show()

        #       plt.savefig('Matplotlib_save_plot-2.png')

        # plt.savefig(file_path_out1)

        # print('Quicklook created: ' + file_path_out1)

        plt.savefig(file_path_out2)

        print('Quicklook created: ' + file_path_out2)

        print('Doppler Quicklook created: ', datetime.utcnow())

#       plot beta data

        fig = plt.figure(figsize=[10, 6.2], dpi=100)

#        fig = plt.figure(figsize=[10, 6.2], dpi=75)

        pc = plt.pcolormesh(xx, yy/1000, data_beta, cmap=plt.get_cmap('rainbow'))

        plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))

#        plt.yticks(ticks=[0, 2, 4, 6, 8, 10], labels=['0', '2', '4', '6', '8', '10'])	# 'ticks' and 'labels' in new python version not allowed any more

        plt.yticks([0, 2, 4, 6, 8, 10], ['0', '2', '4', '6', '8', '10'])

        plt.tick_params('both', length=8, width=0.5, which='major')

        plt.ylabel('Range (km)')

        plt.xlabel('Time (UTC)')

        ax2_divider = make_axes_locatable(plt.gca())

        cax2 = ax2_divider.append_axes("top", size=0.12, pad="20%")

        clb = fig.colorbar(pc, cax=cax2, orientation="horizontal")

        clb.ax.set_title('Backscatter Signal', size=24)

        plt.gcf().text(0.1, 0.78, t_start+' '+day1[10:15], fontsize=14)

        plt.gcf().text(0.3, 0.78, 'to'+' '+day[0:10]+' '+day[10:15], fontsize=14)

        plt.gcf().text(0.75, 0.78, 'Az = '+str(int(data_12['azimuth'][0])),

                       fontsize=14)

        plt.gcf().text(0.9, 0.78, 'El = '+str(int(data_12['elevation'][0])),

                       fontsize=14)

        plt.tight_layout()

        plt.savefig(file_path_out3)

        print('Quicklook created: ' + file_path_out3)

        print('beta    Quicklook created: ', datetime.utcnow())

#       plot snr data

        fig = plt.figure(figsize=[10, 6.2], dpi=100)

#        fig = plt.figure(figsize=[10, 6.2], dpi=75)

        pc = plt.pcolormesh(xx, yy/1000, data_snr, cmap=plt.get_cmap('rainbow'))

        plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))

#        plt.yticks(ticks=[0, 2, 4, 6, 8, 10], labels=['0', '2', '4', '6', '8', '10'])	# 'ticks' and 'labels' in new python version not allowed any more

        plt.yticks([0, 2, 4, 6, 8, 10], ['0', '2', '4', '6', '8', '10'])

        plt.tick_params('both', length=8, width=0.5, which='major')

        plt.ylabel('Range (km)')

        plt.xlabel('Time (UTC)')

        ax2_divider = make_axes_locatable(plt.gca())

        cax2 = ax2_divider.append_axes("top", size=0.12, pad="20%")

        clb = fig.colorbar(pc, cax=cax2, orientation="horizontal")

        clb.ax.set_title('SNR+1', size=24)

        plt.gcf().text(0.1, 0.78, t_start+' '+day1[10:15], fontsize=14)

        plt.gcf().text(0.3, 0.78, 'to'+' '+day[0:10]+' '+day[10:15], fontsize=14)

        plt.gcf().text(0.75, 0.78, 'Az = '+str(int(data_12['azimuth'][0])),

                       fontsize=14)

        plt.gcf().text(0.9, 0.78, 'El = '+str(int(data_12['elevation'][0])),

                       fontsize=14)

        plt.tight_layout()

        plt.savefig(file_path_out4)

        print('Quicklook created: ' + file_path_out4)

        print('snr     Quicklook created: ', datetime.utcnow())

#       plot Doppler data up to 4 km

        fig = plt.figure(figsize=[10, 6.2], dpi=100)

#        fig = plt.figure(figsize=[10, 6.2], dpi=75)

        pc = plt.pcolormesh(xx[0:150,:], yy[0:150,:]/1000, data_doppler[0:150,:], cmap=cmap)

        plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))

#        plt.yticks(ticks=[0, 1, 2, 3, 4], labels=['0', '1', '2', '3', '4'])	# 'ticks' and 'labels' in new python version not allowed any more

        plt.yticks([0, 1, 2, 3, 4], ['0', '1', '2', '3', '4'])

        plt.tick_params('both', length=8, width=0.5, which='major')

        plt.ylabel('Range (km)')

        plt.xlabel('Time (UTC)')

        ax2_divider = make_axes_locatable(plt.gca())

        cax2 = ax2_divider.append_axes("top", size=0.12, pad="20%")

        clb = fig.colorbar(pc, cax=cax2, orientation="horizontal")

        clb.ax.set_title('Doppler Wind Velocity, m/s', size=24)

        plt.gcf().text(0.1, 0.78, t_start+' '+day1[10:15], fontsize=14)

        plt.gcf().text(0.3, 0.78, 'to'+' '+day[0:10]+' '+day[10:15], fontsize=14)

        plt.gcf().text(0.75, 0.78, 'Az = '+str(int(data_12['azimuth'][0])),

                       fontsize=14)

        plt.gcf().text(0.9, 0.78, 'El = '+str(int(data_12['elevation'][0])),

                       fontsize=14)

        plt.tight_layout()

        plt.savefig(file_path_out5)

        print('Quicklook created: ' + file_path_out5)

        print('Doppler Quicklook created: ', datetime.utcnow())

#       plot beta data up to 4 km

        fig = plt.figure(figsize=[10, 6.2], dpi=100)

#        fig = plt.figure(figsize=[10, 6.2], dpi=75)

        pc = plt.pcolormesh(xx[0:150,:], yy[0:150,:]/1000, data_beta[0:150,:], cmap=plt.get_cmap('rainbow'))

        plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))

#        plt.yticks(ticks=[0, 1, 2, 3, 4], labels=['0', '1', '2', '3', '4'])	# 'ticks' and 'labels' in new python version not allowed any more

        plt.yticks([0, 1, 2, 3, 4], ['0', '1', '2', '3', '4'])

        plt.tick_params('both', length=8, width=0.5, which='major')

        plt.ylabel('Range (km)')

        plt.xlabel('Time (UTC)')

        ax2_divider = make_axes_locatable(plt.gca())

        cax2 = ax2_divider.append_axes("top", size=0.12, pad="20%")

        clb = fig.colorbar(pc, cax=cax2, orientation="horizontal")

        clb.ax.set_title('Backscatter Signal', size=24)

        plt.gcf().text(0.1, 0.78, t_start+' '+day1[10:15], fontsize=14)

        plt.gcf().text(0.3, 0.78, 'to'+' '+day[0:10]+' '+day[10:15], fontsize=14)

        plt.gcf().text(0.75, 0.78, 'Az = '+str(int(data_12['azimuth'][0])),

                       fontsize=14)

        plt.gcf().text(0.9, 0.78, 'El = '+str(int(data_12['elevation'][0])),

                       fontsize=14)

        plt.tight_layout()

        plt.savefig(file_path_out6)

        print('Quicklook created: ' + file_path_out6)

        print('beta    Quicklook created: ', datetime.utcnow())

    return

# crontab -e

# 3 * * * * python3 /ipmserver/ag_fernerkundung/Projekte/LAFO/DL/DL_UAE/hpl2plot_time3h.py