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plot_disdrometer.py
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# -*- coding: cp1252 -*-
import matplotlib as mpl
mpl.use('Agg')
import numpy
from pylab import figure, ylim, show, savefig, plot_date, date2num,twinx,contour,legend,colorbar
#from Scientific.IO.NetCDF import NetCDFFile as NCDataset
from netCDF4 import Dataset as NCDataset
from matplotlib.dates import YearLocator, MonthLocator,DayLocator,HourLocator,MinuteLocator,DateFormatter
from matplotlib.ticker import AutoLocator, MultipleLocator, FixedLocator
#from matplotlib.colors import LogNorm
from numpy import *
#import array
import datetime as dt
import time as tm
from sys import exit, argv
import os
import math
import argparse
def get_unix_time(year,month,day,hour,minute,second):
unixtime = dt.datetime(year,month,day,hour,minute,second)
return unixtime.replace(tzinfo=dt.timezone.utc).timestamp()
def get_nc_files(folders,s_unix, e_unix):
s_time=tm.localtime(s_unix)
e_time=tm.localtime(e_unix)
s_date=dt.date(s_time[0],s_time[1], s_time[2])
e_date=dt.date(e_time[0],e_time[1], e_time[2])
ncfiles = []
thistime = s_unix
for n in range( (e_date-s_date).days+1 ):
t = s_date+dt.timedelta(n)
s_year = str(t.year).zfill(4)
s_month = str(t.month).zfill(2)
s_day = str(t.day).zfill(2)
ncfile = folders['datafolder']+s_year+'/'+s_year+s_month+s_day+'_disdrometer.nc'
if os.path.exists(ncfile):
ncfiles.append(ncfile)
#print ncfiles
return ncfiles
def append_data(thisvar,newvar):
n_dim=len(thisvar.shape)
if n_dim == 1:
return numpy.append(thisvar,newvar)
if n_dim == 2:
thisvar=numpy.concatenate((thisvar,newvar), axis=0)
return thisvar
def get_nc_data(ncfiles, varname):
requested_var = None
for thisfile in ncfiles:
ncfile = NCDataset(thisfile,'r')
var = ncfile.variables[varname]
if requested_var != None:
requested_var=append_data(requested_var,var[:])
else:
requested_var=var[:]
return requested_var
def get_xtick_interval(xmin,xmax):
nticks = 8
deltat = (xmax-xmin)*24.
#delta_h = int(math.ceil(deltat/nticks))
delta_h = deltat/nticks
if delta_h > 0.5:
return ('hour',int(math.ceil(delta_h)),)
if delta_h <= 0.5:
return ('minute',int(math.ceil(deltat*60)/nticks),)
#print 'delta_h in get_xtick_interval: ', delta_h
#return delta_h
def plot2d (x,y,xmin,xmax,xtitle,ytitle,varname):
#x: unixtime
#d = [dt.datetime.fromtimestamp(tm.mktime(tm.localtime(i))) for i in x]
#d = mpl.dates.date2num(d)
fig = figure(figsize=(10,3.5),dpi=80,facecolor='w',edgecolor='k')
ax = fig.add_subplot(111)
delta_h=get_xtick_interval(x[0],x[-1])
if delta_h[0] == 'minute':
major = MinuteLocator(range(0,60,delta_h[1]))
minor = MinuteLocator()
if delta_h[0] == 'hour':
major = HourLocator(range(0,24,delta_h[1]))
minor = MinuteLocator(interval=30)
daysFmt = DateFormatter('%d.%m.%y\n%H:%M UT')
ax.xaxis.set_minor_locator(minor)
ax.xaxis.set_major_locator(major)
ax.xaxis.set_major_formatter(daysFmt)
ylocator=AutoLocator()
ax.set_ylabel(ytitle)
font={'family': 'sans-serif',
'weight': 'bold',
'size': 10}
mpl.rc('font',**font)
ax.yaxis.grid(True)
ax.xaxis.grid(True)
ax.plot_date(x,y,'-')#,tz='local')
ax.yaxis.set_major_locator(ylocator)
y_major = ax.yaxis.get_majorticklocs()
dy_minor = (y_major[-1]-y_major[0])/(len(y_major)-1)/5.
ax.yaxis.set_minor_locator(MultipleLocator(dy_minor))
#fig.show()
fig.savefig(folders['imagefolder']+varname+'.png')
def plotcontour (x,y,z,xmin,xmax,xtitle,ytitle,varname):
z=transpose(z)
if varname == 'number_concentration':
z=z[0:len(y)-1,:]
y=y[0:len(y)-1]
y_max=0
for i in range(len(y)):
if y[i] > y_max:
y_max=y[i]
z_max=0
i_max=0
for i in range(len(z[:,0])):
for j in range(len(z[i,:])):
if z[i,j] > z_max:
z_max=z[i,j]
if z[i,j] <= 0:
z[i,j]=float('NaN')
if z[i,j] > 0:
if i > i_max:
i_max=i
if i_max == 0:
i_max=len(y)-1
if z_max == 0:
z_max=0.1
y_max = y[i_max]
z = z[0:i_max,:]
y = y[0:i_max]
#d = [dt.datetime.fromtimestamp(tm.mktime(tm.localtime(i))) for i in x]
#d = mpl.dates.date2num(d)
fig = figure(figsize=(10,3.5),dpi=80,facecolor='w',edgecolor='k')
if varname == 'number_concentration':
title='number concentration'
cb_label='log(1/(m^3 mm))'
if varname == 'fall_velocity':
title='velocity distribution'
cb_label='m/s'
ax = fig.add_subplot(111,title=title)
delta_h=get_xtick_interval(x[0],x[-1])
if delta_h[0] == 'minute':
major = MinuteLocator(range(0,60,delta_h[1]))
minor = MinuteLocator()
daysFmt = DateFormatter('%d.%m.%y\n%H:%M UT')
if delta_h[0] == 'hour':
major = HourLocator(range(0,24,delta_h[1]))
minor = MinuteLocator(interval=30)
daysFmt = DateFormatter('%d.%m.%y\n%H:%M UT')
ax.xaxis.set_minor_locator(minor)
ax.xaxis.set_major_locator(major)
ax.xaxis.set_major_formatter(daysFmt)
ylocator=AutoLocator()
ax.set_ylabel(ytitle)
font={'family': 'sans-serif',
'weight': 'bold',
'size': 10}
mpl.rc('font',**font)
ax.yaxis.grid(True)
ax.xaxis.grid(True)
levels=[]
n_levels=8
z_min=0
for i in range(n_levels):
levels.append(z_min+i*z_max/n_levels)
ax.set_ylim([0,y_max])
#ax.yaxis.set_major_locator(ylocator)
#y_major = ax.yaxis.get_majorticklocs()
#dy_minor = (y_major[-1]-y_major[0])/(len(y_major)-1)/5.
#ax.yaxis.set_minor_locator(MultipleLocator(dy_minor))
#levels=[0,0.5,1,1.5,2,2.5,3]
if varname == 'number_concentration':
CS=ax.contourf(x,y,z,levels)
if varname == 'fall_velocity':
CS=ax.contourf(x,y,z,levels)
CS.cmap.set_under('white')
CS.cmap.set_over('red')
cb=fig.colorbar(CS)
cb.ax.set_ylabel(cb_label)
#fig.show()
fig.savefig(folders['imagefolder']+varname+'.png')
def get_and_plot_data(ncfiles,Unix_time,plot_time,var,start,end):
diameters=[0.062,0.187,0.312,0.437,0.562,0.687,0.812,0.937,1.062,1.187,1.375,
1.625,1.875,2.125,2.375,2.750,3.250,3.750,4.250,4.750,5.500,6.500,
7.500,8.500,9.500,11.000,13.000,15.000,17.000,19.000,21.500,24.500]
velocities=[0.05,0.15,0.23,0.35,0.45,0.55,0.65,0.75,0.85,0.95,1.1,1.3,1.5,1.7,
1.9,2.2,2.6,3.0,3.4,3.8,4.4,5.2,6.0,6.8,7.6,8.8,10.4,12.0,13.6,15.2,
17.6,20.8]
data = get_nc_data(ncfiles,var)
if var == 'rainfall_rate':
data=data*1000*3600 # Convert from m/s to mm/s to mm/hr
#if var == 'number_concentration':
# ytitle='Drop Diameter [mm]'
if var == 'fall_velocity':
ytitle='Hydrometeor Diameter [mm]'
if var == 'rainfall_rate':
ytitle='Precipitation Rate [mm/h]'
if var == 'radar_reflectivity':
ytitle='Equivalent Radar Reflectivity [dBz]'
if var == 'n_particles':
ytitle='Number of Detected Particles'
if var == 'number_concentration':
ytitle='Hydrometeor Diameter [mm]'
if var == 'rainfall_rate' or var == 'radar_reflectivity' or var == 'n_particles':
plot2d(plot_time,data[start:end],0,0,'Time',ytitle,var)
if var == 'number_concentration' or var == 'fall_velocity':
plotcontour(plot_time,diameters, data[start:end,:],0,0,'Time',ytitle,var)
return data
def get_xrange(args):
#no starting time
if not args.timestamp_s:
#print "No start timestamp given."
#no ending time
if not args.timestamp_e:
#print "No end timestamp given."
#no duration
if not args.duration:
#print "No duration given. Using standard value: 12"
args.duration = default_duration
#set ending time to current time
args.timestamp_e = tm.time()
#ending time is available
else:
args.timestamp_e=get_unix_time(int(args.timestamp_e[0:4]),int(args.timestamp_e[4:6]),
int(args.timestamp_e[6:8]),int(args.timestamp_e[8:10])
,int(args.timestamp_e[10:12]),0)
#no duration available
if not args.duration:
#print "No duration given. Using standard value: 12"
args.duration = default_duration
#set starting time to current time - duration
args.timestamp_s = args.timestamp_e-args.duration*3600.
else:
args.timestamp_s=get_unix_time(int(args.timestamp_s[0:4]),int(args.timestamp_s[4:6]),
int(args.timestamp_s[6:8]),int(args.timestamp_s[8:10])
,int(args.timestamp_s[10:12]),0)
#print args.timestamp_s
#no ending time available
if not args.timestamp_e:
#no duration available
if not args.duration:
args.duration = default_duration
#print args.duration
args.timestamp_e = args.timestamp_s+args.duration*3600.
else:
args.timestamp_e=get_unix_time(int(args.timestamp_e[0:4]),int(args.timestamp_e[4:6]),
int(args.timestamp_e[6:8]),int(args.timestamp_e[8:10])
,int(args.timestamp_e[10:12]),0)
args.duration=args.timestamp_e-args.timestamp_s
return args
def define_parser(argv):
parser = argparse.ArgumentParser()
parser.add_argument('-e', action='store', dest='timestamp_e',
help='end time yyyymmddhhmm')
parser.add_argument('-s', action='store', dest='timestamp_s',
help='starting time yyyymmddhhmm')
parser.add_argument('-d', action='store', dest='duration', type=float,
help='time interval to display in hours')
return parser
'''*********************'''
'''START OF MAIN PROGRAM'''
'''*********************'''
#-s 201202170200 -d 10
#provide input variables
#datafolder='C:\\Users\\Vaio\\Desktop\\PlotParsivel\\'
#datafolder='G:\\Programme\\Python\\PlotParsivel\\'
#datafolder='/home/cloudnet/data/meteo/'
datafolder='/home/disdrometer/data/'
imagefolder='/home/disdrometer/tmp/'
folders={'datafolder':datafolder, 'imagefolder':imagefolder}
default_duration=12
# process command line arguments
parser = define_parser(argv)
# extract argument structure from parser
args = parser.parse_args()
# determine start time (xmin) and end time (xmax) of plot
times = get_xrange(args)
ncfiles = get_nc_files(folders,times.timestamp_s, times.timestamp_e)
print(ncfiles)
Unix_time = get_nc_data(ncfiles, 'time')*1.
#reduce data
start = where(Unix_time >= times.timestamp_s)
if len(start[0]) == 0:
print('Start time not found in data...exiting')
exit()
start = start[0][0]
end = where(Unix_time >= times.timestamp_e)
if len(end[0]) == 0:
end = len(Unix_time)-1
else:
end = end[0][0]
plot_time = [dt.datetime.fromtimestamp(tm.mktime(tm.localtime(i))) for i in Unix_time[start:end]]
plot_time = mpl.dates.date2num(plot_time)
RR = get_and_plot_data(ncfiles,Unix_time,plot_time,'rainfall_rate',start,end)
Ze = get_and_plot_data(ncfiles,Unix_time,plot_time,'radar_reflectivity',start,end)
N = get_and_plot_data(ncfiles,Unix_time,plot_time,'n_particles',start,end)
N_Field = get_and_plot_data(ncfiles,Unix_time,plot_time,'number_concentration',start,end)
V_Field = get_and_plot_data(ncfiles,Unix_time,plot_time,'fall_velocity',start,end)
time_interval=get_nc_data(ncfiles, 'interval')*1.
rr = RR.copy()
rr[rr<0] = 0
R = numpy.cumsum(rr*time_interval/3600.)
#for i in range(1,len(RR)):
# print(R[i], rr[i], time_interval[i])
ytitle='Accumulated precip. [mm]'
var='acc_precip'
plot2d(plot_time,R[start:end],0,0,'Time',ytitle,var)