MPL_autoplot.py

# -*- coding: utf-8 -*-
"""
Created on Sun Jan 26 17:04:59 2014

@author: dashamstyr

Program to generate processed image of files from most recent 24 hour window in miniMPL data file.

"""

import os, sys

import pandas as pan
import datetime,time
import numpy as np
import glob
import matplotlib
matplotlib.use('Agg')
from matplotlib import pyplot as plt


lib = '/data/lv1/pcottle'
datalib = '/data/lv1/pcottle/MPLData'
figurelib = '/data/lv1/pcottle/MPLFigures'

try:
    sys.path.append(os.path.join(lib, 'MPLCode'))
    from MPLcode import MPLtools as mtools
    from MPLcode import MPL_plot as mplot   
except ImportError:
    
    try:
        import MPLtools as mtools
        import MPL_plot as mplot
    
    except ImportError:
        raise Exception('You havent specified where your modules are located!')

mplfiles = []

os.chdir(datalib)

# gather all mpl files from the data folder and sort them by name
for temp in glob.glob("*.mpl"):
    mplfiles.append(temp)

mplfiles.sort()

# mpl files are generated hourly so take last 24 entries from the list

mpl_selected = mplfiles[-24:]

# generate mpl class object from the selected files

#set altitude range and date step sizes

altrange = np.arange(150,15000,30)#meters
timestep = '60S' #seconds

#check to see if each file has been processed before and separate processed
#files into a new list


for f in mpl_selected:
    MPLdat_temp = mtools.MPL()
    MPLdat_temp.fromMPL(f)
    MPLdat_temp.alt_resample(altrange)

    try:
        MPLdat_event.append(MPLdat_temp)
    except NameError:
        MPLdat_event = MPLdat_temp
   
#sort by index to make certain data is in order then set date ranges to match
MPLdat_event.header.sort_index()

for n in range(MPLdat_event.header['numchans'][0]):
    data = MPLdat_event.data[n]
    data = data.sort_index()

MPLdat_event.time_resample(timestep)
MPLdat_event.range_cor()    
MPLdat_event.calculate_NRB(showplots = False)
MPLdat_event.calculate_depolrat()


#get current date and time
current_time = datetime.datetime.now()

try:
    os.chdir('Processed')
except OSError: # except WindowsError:
    os.makedirs('Processed')
    os.chdir('Processed')

newfile = True
#get list of existing processed files and if newest file is > 1 day old, make a new one
for temp in glob.glob("*.h5"):
    temptime = datetime.datetime.fromtimestamp(os.path.getctime(temp))
    
    if current_time-temptime < datetime.timedelta(1):
        newfile = False

if newfile:
    [path,startfile] = os.path.split(mpl_selected[0])
    [path,endfile] = os.path.split(mpl_selected[-1])
    filename = startfile.split('.')[0]+'-'+endfile.split('.')[0]
    
    MPLdat_event.save_to_HDF(filename+'_proc.h5')

#Now generate a new figure.
os.chdir(figurelib)

copol = MPLdat_event.NRB[0]
depol = MPLdat_event.depolrat[0]

copol_min = 0.0
copol_max = 1.0
copol_step = 5
copolticks = np.linspace(copol_min,copol_max,copol_step)

depol_min = 0.0
depol_max = 0.5
depol_step = 5
depolticks = np.linspace(depol_min,depol_max,depol_step)

alt = copol.columns
time_index = copol.index

hours = ['03','06','09','12','15','18','21']

fsize = 18 #baseline font size
ar = 2.0  #aspect ratio
figheight = 12 #inches


plt.rc('font', family='serif', size=fsize)


fig = plt.figure()

h_set = range(1,25)
h_set = map(str,h_set)

ax1 = fig.add_subplot(2,1,1)
im1 = mplot.backscatter_plot(fig, ax1, ar, time_index,alt[::-1],copol.T[::-1], (copol_min,copol_max), fsize = fsize)
cbar1 = fig.colorbar(im1, orientation = 'vertical', aspect = 6)
cbar1.set_ticks(copolticks)
cbar1.set_ticklabels(copolticks)
cbar1.ax.tick_params(labelsize = fsize)
cbar1.ax.set_ylabel('$[counts*km^{2}/(\mu s*\mu J)$')
mplot.dateticks(ax1, time_index, hours = hours, fsize = fsize, tcolor = 'w')
ax1.set_xticklabels([])
t1 = ax1.set_title('Normalized Relative Backscatter', fontsize = fsize+10)
t1.set_y(1.03)
        
ax2 = fig.add_subplot(2,1,2)
im2 = mplot.depol_plot(fig, ax2, ar, time_index,alt[::-1],depol.T[::-1], (depol_min,depol_max), fsize = fsize)
cbar2 = fig.colorbar(im2, orientation = 'vertical', aspect = 6)
cbar2.set_ticks(depolticks)
cbar2.set_ticklabels(depolticks)
cbar2.ax.tick_params(labelsize = fsize)
#set axis ranges and tickmarks based on data ranges
mplot.dateticks(ax2, time_index, hours = hours, fsize = fsize)
ax2.set_xlabel('Time [Local]',fontsize = fsize+4)
fig.autofmt_xdate()
t2 = ax2.set_title('Linear Depolarization Ratio',fontsize = fsize+10)
t2.set_y(1.03)    


fig.set_size_inches(figheight*ar,figheight) 

if newfile:
    plt.savefig(filename+'.png',dpi = 100, edgecolor = 'b', bbox_inches = 'tight')
else:
    plt.savefig('latest.png',dpi = 100, edgecolor = 'b', bbox_inches = 'tight')