In [1]:

    

%matplotlib inline

import linecache
import sys
import gc
import pdb

import matplotlib
import matplotlib.pyplot as plt
import matplotlib.mlab as ml
from matplotlib.colors import from_levels_and_colors
import datetime
from dateutil.relativedelta import relativedelta
import re
import numpy as np
from math import *
import scipy.interpolate


    

In [2]:

    

# Exception handling, with line number and stuff

def PrintException():
    exc_type, exc_obj, tb = sys.exc_info()
    f = tb.tb_frame
    lineno = tb.tb_lineno
    filename = f.f_code.co_filename
    linecache.checkcache(filename)
    line = linecache.getline(filename, lineno, f.f_globals)
    print 'EXCEPTION IN ({}, LINE {} "{}"): {}'.format(filename, lineno, line.strip(), exc_obj)


    

In [9]:

    

def rotate_u_v_wind_array(u_wind, v_wind, brng):
    '''
    Rotate winds with given angle (which is a maths angle - positive counter-clockwise from positive x to positive y)
    Returns roated u and v masked array 
    '''
  
  #nan_mask_u_wind = np.ma.masked_array(np.array(u_wind[:,i,0:-1:10], dtype=float).flatten(), np.isnan(np.array(u_wind[:,i,0:-1:10], dtype=float).flatten()))
  #nan_mask_v_wind = np.ma.masked_array(np.array(v_wind[:,i,0:-1:10], dtype=float).flatten(), np.isnan(np.array(v_wind[:,i,0:-1:10], dtype=float).flatten()))
    nan_mask_u_wind = np.ma.masked_array(np.array(u_wind, dtype=float).flatten(), np.isnan(np.array(u_wind, dtype=float).flatten()))
    nan_mask_v_wind = np.ma.masked_array(np.array(v_wind, dtype=float).flatten(), np.isnan(np.array(v_wind, dtype=float).flatten()))
    
    #print nan_mask
 
    u_rot = nan_mask_u_wind * cos(brng) + nan_mask_v_wind * sin(brng)
    v_rot = -nan_mask_u_wind * sin(brng) + nan_mask_v_wind * cos(brng)
    
    return u_rot,v_rot

def u_v_winds(wind_direction, wind_speed):
    wind_rad = np.radians(wind_direction)
    u_wind=-((wind_speed)*np.sin(wind_rad))
    v_wind=-((wind_speed)*np.cos(wind_rad))
    return u_wind,v_wind

def grid_data_cs(pressure, distance, param):
    xi=np.linspace(0, max(distance), 200) 
 #yi=np.linspace(np.nanmin(pressure), np.nanmax(pressure), 500) 
    yi=np.linspace(5000, 100000, 50) # Points for pressure interpolation
    
    try:
        zi = ml.griddata(distance, pressure,param,xi, yi, interp='linear')
        #zi = scipy.interpolate.griddata((distance, pressure),  param, (xi[None,:],yi[:,None]), method='linear')
    except Exception, e:
        PrintException()
    return xi,yi,zi 
    

    

def station_info_search(stat):
    for line in station_metadata:
         if "%s" % stat in line: 
             st = line[2].lower().title().replace('_',' ')
             lo = float(line[3])
             la = float(line[4])
    return st,la,lo

def calculate_distance_from_first_station(stat, first_station_lon, first_station_lat, station_lat, station_lon):

    fslat_rad = radians(first_station_lat)
    fslon_rad = radians(first_station_lon)
    lat_rad = radians(station_lat)
    lon_rad = radians(station_lon)

 #Haversine Formula
    
    a = sin((lat_rad-fslat_rad)/2)**2 + cos(lat_rad) * cos(fslat_rad) * sin((lon_rad-fslon_rad)/2)**2
    c = 2 * atan2(sqrt(a), sqrt(1-a))
    d = 6371 * c

    return d

def variable_name_index_match(variable, variable_list):
    for key, value in variable_list.iteritems():   # iter on both keys and values
        if key.startswith('%s' % variable) and key.endswith('%s' % variable):
            arr_index_var=value 
    return arr_index_var

def variable_cat(var_index, station_list_cs):
    '''
    Load date binned radiosonde data, saved as output for each station from previous script, and gather
    info of stations in line, calculate dist from first station and concatente station data
    '''
    
    var_cat=[]
    distances=[]
    date_min_max=[]
    
    for stat in station_list_cs:
        load_file = np.load('/nfs/a90/eepdw/Data/Observations/Radiosonde_Numpy/Radiosonde_Cross_Section_'
                           'IND_SOUNDING_INTERP_MEAN_Climat_%s_%s_%s_%s.npz' 
                           % (date_min.strftime('%Y%m%d'), date_max.strftime('%Y%m%d'), delta, stat))
  
         #print load_file['date_bin_mean_all_dates_one_station'].shape

        if date_min_max ==[]:
            date_min_max=np.empty(load_file['min_max_date_bin'].shape)
        
        station_title, station_lon, station_lat = station_info_search(stat)
    
        dist_from_first_station = calculate_distance_from_first_station(stat, first_station_lon, first_station_lat, station_lat, station_lon)
    
        var_cat.append(load_file['date_bin_mean_all_dates_one_station'][:,var_index,:])
        distances.append(dist_from_first_station)
    
        date_min_max = np.where((load_file['min_max_date_bin']>date_min) & (load_file['min_max_date_bin']<date_max), load_file['min_max_date_bin'], date_min_max )
        
    dates_savefig_name=load_file['dates_for_plotting']
  
    return np.array(var_cat), np.array(distances, dtype=float), date_min_max, dates_savefig_name

def variable_cat_line(var_index, station_list_cs):
    var_cat=[]
    distances=[]
    date_min_max=[]
    
    for stat in station_list_cs:
     load_file = np.load('/nfs/a90/eepdw/Data/Observations/Radiosonde_Numpy/Radiosonde_Cross_Section_'
                        'IND_SOUNDING_INTERP_MEAN_Climat_%s_%s_%s_%s.npz' 
                        % (date_min.strftime('%Y%m%d'), date_max.strftime('%Y%m%d'), delta, stat))
  
     #print load_file['date_bin_mean_all_dates_one_station'].shape

     if date_min_max ==[]:
      date_min_max=np.empty(load_file['min_max_date_bin'].shape)
        
     station_title, station_lon, station_lat = station_info_search(stat)
    
     dist_from_first_station = calculate_distance_from_first_station(stat, first_station_lon, first_station_lat, station_lat, station_lon)
    
     #print dist_from_first_station
     #print load_file['date_bin_mean_all_dates_one_station'][:,var_index,:].shape
     var_cat.append(load_file['date_bin_mean_all_dates_one_station_single'][i,0,var_index])
     distances.append(dist_from_first_station)
     #pdb.set_trace()
     #if load_file['min_max_date_bin'].any() != np.NAN:
     #date_min_max=np.ma.masked_outside(load_file['min_max_date_bin'], date_min, date_max ).data
     date_min_max = np.where((load_file['min_max_date_bin']>date_min) & (load_file['min_max_date_bin']<date_max), load_file['min_max_date_bin'], date_min_max )
    #print np.array(var_cat).shape
    #print date_min_max
    return np.array(var_cat), np.array(distances, dtype=float), date_min_max

def plot_rad_cs_winds(i, xi,yi,zi, min_contour, max_contour, xiw, yiw, uiw, viw, cmap):
    
    num_cols=32
   
    plt.figure(figsize=(14,8.5))
       
    clevs = np.linspace(min_contour, max_contour, num_cols)
    ticks = (np.arange(min_contour, max_contour+tick_interval,tick_interval))
    
 #cmap=plt.cm.RdBu_r
    
    cont = plt.contourf(xi,yi/100, zi, clevs, cmap=cmap, extend='both')
 
    cont_wind = plt.barbs(xiw,yiw/100, uiw, viw)
 #plt.clabel(cont_wind, fontsize=9, inline=1, fmt='%1d')
  
    cbar = plt.colorbar(cont, orientation='vertical', pad=0.05, extend='both')
 #cbar.set_label('$W m^{-2}$') 
    cbar.set_ticks(np.arange(min_contour, max_contour+tick_interval,tick_interval))
    cbar.set_ticklabels([cbar_number_format % i for i in ticks])
 
    plt.xlim(np.min(xi)-200,np.max(xi)+200)
    plt.gca().invert_yaxis()
    plt.gca().invert_xaxis()
    plt.ylabel('Pressure (hPa)')
    plt.xlabel('km from first station')
    
    return cont,cbar

def plot_rad_cs_winds_normalize(i, xi,yi,zi, min_contour, max_contour, xiw, yiw, uiw, viw, cmap):
   
    num_cols=32
    
    plt.figure(figsize=(14,8))
   
    clevs = np.linspace(min_contour, max_contour, num_cols)
    ticks = (np.arange(min_contour, max_contour+tick_interval,tick_interval))
    
 #cmap=plt.cm.RdBu_r
    
    midpoint=0
    midp = np.mean(np.c_[clevs[:-1], clevs[1:]], axis=1)
    vals = np.interp(midp, [min_contour, midpoint, max_contour], [0, 0.5, 1])
    cols = cmap(vals)
    clevs_extend = np.linspace(min_contour, max_contour,num_cols-2)
    cmap, norm = from_levels_and_colors(clevs_extend, cols, extend='both')

    cont = plt.contourf(xi,yi/100, zi, clevs, cmap=cmap, extend='both')
 
    cont_wind = plt.barbs(xiw,yiw/100, uiw, viw)
 #plt.clabel(cont_wind, fontsize=9, inline=1, fmt='%1d')
  
    cbar = plt.colorbar(cont, orientation='vertical', pad=0.05, extend='both')
 #cbar.set_label('$W m^{-2}$') 
    cbar.set_ticks(np.arange(min_contour, max_contour+tick_interval,tick_interval))
    cbar.set_ticklabels([cbar_number_format % i for i in ticks])
 
    plt.xlim(np.min(xi)-200,np.max(xi)+200)
    plt.gca().invert_yaxis()
    plt.gca().invert_xaxis()
    plt.ylabel('Pressure (hPa)')
    plt.xlabel('km from first station')
    
    return cont,cbar


def plot_rad_cs_winds_rot_and_unrot(i, xi,yi,zi, min_contour, max_contour, xiw, yiw, uiw, viw, uiw_rot, viw_rot, cmap, cbar_number_format):
    
    num_cols=32
   
    plt.figure(figsize=(14,8.5))
       
    clevs = np.linspace(min_contour, max_contour, num_cols)
    ticks = (np.arange(min_contour, max_contour+tick_interval,tick_interval))
    
 #cmap=plt.cm.RdBu_r
    
    cont = plt.contourf(xi,yi/100, zi, clevs, cmap=cmap, extend='both')
 
    cont_wind = plt.barbs(xiw,yiw/100, uiw, viw)
    
    cont_wind_rot = plt.quiver(xiw,yiw/100, uiw_rot, viw_rot,
               scale_units='inches',
               angles='uv',
               scale=40,
               headlength=1,
               headaxislength=1,
               width=0.004,
               alpha=0.8)
 #plt.clabel(cont_wind, fontsize=9, inline=1, fmt='%1d')
  
    cbar = plt.colorbar(cont, orientation='vertical', pad=0.05, extend='both')
 #cbar.set_label('$W m^{-2}$') 
    cbar.set_ticks(np.arange(min_contour, max_contour+tick_interval,tick_interval))
    cbar.set_ticklabels([cbar_number_format % i for i in ticks])
 
    plt.xlim(np.min(xi)-200,np.max(xi)+200)
    plt.gca().invert_yaxis()
    plt.gca().invert_xaxis()
    plt.ylabel('Pressure (hPa)')
    plt.xlabel('km from first station')
    
    return cont,cbar

def plot_rad_cs_winds_rot_and_unrot_normalize(i, xi,yi,zi, min_contour, max_contour, xiw, yiw, uiw, viw, uiw_rot, viw_rot, cmap, cbar_number_format):
    
    num_cols=32
   
    plt.figure(figsize=(14,8.5))
       
    clevs = np.linspace(min_contour, max_contour, num_cols)
    ticks = (np.arange(min_contour, max_contour+tick_interval,tick_interval))
    
 #cmap=plt.cm.RdBu_r
    
    midpoint=0
    midp = np.mean(np.c_[clevs[:-1], clevs[1:]], axis=1)
    vals = np.interp(midp, [min_contour, midpoint, max_contour], [0, 0.5, 1])
    cols = cmap(vals)
    clevs_extend = np.linspace(min_contour, max_contour,num_cols-2)
    cmap, norm = from_levels_and_colors(clevs_extend, cols, extend='both')
 #cmap=plt.cm.RdBu_r
    
    cont = plt.contourf(xi,yi/100, zi, clevs, cmap=cmap, extend='both')
 
    cont_wind = plt.barbs(xiw,yiw/100, uiw, viw)
    
    cont_wind_rot = plt.quiver(xiw,yiw/100, uiw_rot, viw_rot,
               scale_units='inches',
               angles='uv',
               scale=40,
               headlength=1,
               headaxislength=1,
               width=0.004,
               alpha=0.8)
 #plt.clabel(cont_wind, fontsize=9, inline=1, fmt='%1d')
  
    cbar = plt.colorbar(cont, orientation='vertical', pad=0.05, extend='both')
 #cbar.set_label('$W m^{-2}$') 
    cbar.set_ticks(np.arange(min_contour, max_contour+tick_interval,tick_interval))
    cbar.set_ticklabels([cbar_number_format % i for i in ticks])
 
    plt.xlim(np.min(xi)-200,np.max(xi)+200)
    plt.gca().invert_yaxis()
    plt.gca().invert_xaxis()
    plt.ylabel('Pressure (hPa)')
    plt.xlabel('km from first station')
    
    return cont,cbar


import re

station_list_search='/nfs/a90/eepdw/Data/Observations/Radiosonde_downloaded_from_NOAA_GUAN/igra-stations.txt'
station_metadata=[]
f = open(station_list_search,'r')
for line in f:
     line = line.strip()
     line=re.sub(r'([A-Z])\s([A-Z])', r'\1_\2',line)
     line=re.sub(r'([A-Z])\s\s([A-Z])', r'\1_\2',line)
     station_metadata.append(line.split())
f.close()

def LinePlots(variable_list_line, station_list_cs, distances):
        legendEntries=[]
        legendtext=[]
    
        variable='surface_pressure'
        var_index = variable_name_index_match(variable, variable_list_line)
        surface_pressure, distances, date_min_max = variable_cat_line(var_index, station_list_cs)
        l, = plt.plot(distances, surface_pressure/100, color='k', linewidth=2.)
        
        legendEntries.append(l)
        legendtext.append('Surface Pressure')
        
        variable='T_eq_0'
        var_index = variable_name_index_match(variable, variable_list_line)
        T_eq_0, distances_line, date_min_max_line = variable_cat_line(var_index, station_list_cs)
        l, = plt.plot(distances, T_eq_0/100, color='red', linewidth=2., linestyle='-')
  
        legendEntries.append(l)
        legendtext.append('T=0')   
  
        variable='lcl_vpt'

        var_index = variable_name_index_match(variable, variable_list_line)
        lcl_vpt, distances_line, date_min_max_line = variable_cat_line(var_index, station_list_cs)
        l, = plt.plot(distances, lcl_vpt/100, color='k', linewidth=2., linestyle=':')
  
        legendEntries.append(l)
        legendtext.append('LCL')   
  
        variable='pbl_pressure'

        var_index = variable_name_index_match(variable, variable_list_line)
        pbl_pressure, distances_line, date_min_max_line = variable_cat_line(var_index, station_list_cs)
        l,= plt.plot(distances, pbl_pressure/100, color='k', linewidth=2., linestyle='--')
   
        legendEntries.append(l)
        legendtext.append('PBL')

        l0=plt.legend(legendEntries, legendtext,title='', loc='upper left', bbox_to_anchor=(1.2, 1.05),
                      ncol=3, fancybox=True, shadow=True )


    

In [11]:

    

Cross_Section_Title = 'Bombay_to_Nagpur'
station_list_cs=[42867, 43014, 43003]
first_station=station_list_cs[0]

maths_bearing_to_rotate_winds=19.5456998888 # See 'Radiosonde Location Map of Picked Sites' notebook for calculation

date_min=datetime.datetime(1960,5,1,0,0,0)
date_max=datetime.datetime(2014,10,1,0,0,0)

delta = relativedelta(weeks=+1)

variable_list={'pressures': 0, 'temps':1, 'dewpoints':2, 'winddirs':3, 'windspeeds':4, 'pot_temp':5, 
               'sat_vap_pres':6, 'vap_press':7, 'rel_hum':8, 'wvmr':9, 'sp_hum':10, 'sat_temp':11, 
               'theta_e':12, 'theta_e_sat':13, 'theta_e_minus_theta_e_sat':14}
variable_list_line={'lcl_temp': 0, 'lcl_vpt':1, 'pbl_pressure':2, 'surface_pressure':3, 'T_eq_0':4, 
                    'CAPE':5, 'CIN':6, 'lclp':7, 'lclt':8, 'lfcp':9, 'equil_level':10}

first_station_title, first_station_lon, first_station_lat = station_info_search(first_station)

# Create plot arrays for pressure, winds etc

variable='pressures'

var_index = variable_name_index_match(variable, variable_list)
pressures, distances, date_min_max,dates_savefig = variable_cat(var_index, station_list_cs)

variable='windspeeds'

var_index = variable_name_index_match(variable, variable_list)
wind_speed, distances, date_min_max,dates_savefig = variable_cat(var_index, station_list_cs)

variable='winddirs'

var_index = variable_name_index_match(variable, variable_list)
wind_direction, distances, date_min_max,dates_savefig = variable_cat(var_index, station_list_cs)

u_wind,v_wind = u_v_winds(wind_direction, wind_speed)


    

In [5]:

    

#Weekly Climatology with pbl and lcl, ROTATED winds

max_contour=100
min_contour=0
tick_interval=10

cmap=plt.cm.jet


variable_to_plot='rel_hum' # From variable_list

var_index = variable_name_index_match(variable_to_plot, variable_list)
concat_plot_variable, distances, date_min_max,dates_savefig = variable_cat(var_index, station_list_cs)

cbar_number_format = '$%d$'
# For each time bin

for i, date_bin in enumerate(dates_savefig):

# Rotate winds
            
    try:    
   
# Grid data
        u_rot,v_rot = rotate_u_v_wind_array(u_wind[:,i,0:-1:10], v_wind[:,i,0:-1:10], radians(maths_bearing_to_rotate_winds))
        nan_mask = np.ma.masked_array(np.array(concat_plot_variable[:,i,:], dtype=float).flatten(), np.isnan(np.array(concat_plot_variable[:,i,:], dtype=float).flatten()))
        if nan_mask.mask.all() == False:
            xi,yi,zi = grid_data_cs(np.array(pressures[:,i,:], dtype=float).flatten(), np.repeat(distances, concat_plot_variable[:,i,:].shape[1]).flatten(), nan_mask) 
            
# Contour plot
            
            cont,cbar = plot_rad_cs_winds_rot_and_unrot(i, xi, yi, zi, min_contour, max_contour, np.repeat(distances, concat_plot_variable[:,i,0:-1:10].shape[1]).flatten(),
                                  np.array(pressures[:,i,0:-1:10], dtype=float).flatten(), u_wind[:,i,0:-1:10], v_wind[:,i,0:-1:10], u_rot, v_rot, cmap, cbar_number_format = '$%d$')
            #station_name_plot(station_list_cs, first_station, yi)


# Line plots
        legendEntries=[]
        legendtext=[]
    
        variable='surface_pressure'
        var_index = variable_name_index_match(variable, variable_list_line)
        surface_pressure, distances, date_min_max = variable_cat_line(var_index, station_list_cs)
        l, = plt.plot(distances, surface_pressure/100, color='k', linewidth=2.)
        
        legendEntries.append(l)
        legendtext.append('Surface Pressure')
        
        variable='T_eq_0'
        var_index = variable_name_index_match(variable, variable_list_line)
        T_eq_0, distances_line, date_min_max_line = variable_cat_line(var_index, station_list_cs)
        l, = plt.plot(distances, T_eq_0/100, color='red', linewidth=2., linestyle='-')
  
        legendEntries.append(l)
        legendtext.append('T=0')   
  
        variable='lcl_vpt'

        var_index = variable_name_index_match(variable, variable_list_line)
        lcl_vpt, distances_line, date_min_max_line = variable_cat_line(var_index, station_list_cs)
        l, = plt.plot(distances, lcl_vpt/100, color='k', linewidth=2., linestyle=':')
  
        legendEntries.append(l)
        legendtext.append('LCL')   
  
        variable='pbl_pressure'

        var_index = variable_name_index_match(variable, variable_list_line)
        pbl_pressure, distances_line, date_min_max_line = variable_cat_line(var_index, station_list_cs)
        l,= plt.plot(distances, pbl_pressure/100, color='k', linewidth=2., linestyle='--')
   
        legendEntries.append(l)
        legendtext.append('PBL')

        l0=plt.legend(legendEntries, legendtext,title='', loc='upper left', bbox_to_anchor=(1.2, 1.05),
                      ncol=3, fancybox=True, shadow=True )  
    
        cbar.set_label('\%', rotation=90)
    
# Plot station names and vertical lines at their location

        y_offset_text=0
        first_station_title, first_station_lon, first_station_lat = station_info_search(first_station)
    
        for stat in station_list_cs: 
     
            station_title, station_lon, station_lat = station_info_search(stat)
    
            dist_from_first_station = calculate_distance_from_first_station(stat, first_station_lon, first_station_lat, station_lat, station_lon)
            
            plt.axvline(x=dist_from_first_station, ymin=0, ymax=1, label=station_title, color='k')
            plt.text(dist_from_first_station+0.1,max(yi)/100+20,station_title,rotation=-45)

            y_offset_text=+1 
        
  
        #plt.title('Week Beg.%s %s Cross-Section of Relative Humidity and Winds along Cross-Section Plane from Radiosonde Soundings' % (date_bin.strftime("%d %B"), Cross_Section_Title.replace('_',' ') ))
        plt.title('Week Beg.%s %s Relative Humidity' % (date_bin.strftime("%d %B"), Cross_Section_Title.replace('_',' ') ))

        #plt.show()
        plt.savefig('/nfs/a90/eepdw/Figures/Radiosonde/Cross_Sections/%s_%s_%s_Relative_Humidity_No_Title.png' % (Cross_Section_Title, date_bin.strftime("%y"), date_bin.strftime("%d_%B")),  format='png', bbox_inches='tight')

    except Exception, e:
        PrintException()
  
 # plt.savefig('/nfs/a90/eepdw/Figures/Radiosonde/Cross_Sections/%s_%s_%s_Relative_Humidity_V_Wind.png' % (Cross_Section_Title, date_bin.strftime("%y"), date_bin.strftime("%d_%B")),  format='png', bbox_inches='tight')
 # plt.close()
 # plt.clf()
 # gc.collect()


    

    




EXCEPTION IN (<ipython-input-5-ef822e37254e>, LINE 78 "cbar.set_label('\%', rotation=90)"): name 'cbar' is not defined






    




---------------------------------------------------------------------------
KeyboardInterrupt                         Traceback (most recent call last)
<ipython-input-5-ef822e37254e> in <module>()
     99 
    100         #plt.show()
--> 101         plt.savefig('/nfs/a90/eepdw/Figures/Radiosonde/Cross_Sections/%s_%s_%s_Relative_Humidity_No_Title.png' % (Cross_Section_Title, date_bin.strftime("%y"), date_bin.strftime("%d_%B")),  format='png', bbox_inches='tight')
    102 
    103     except Exception, e:

/nfs/see-fs-01_users/eepdw/.local/lib/python2.7/site-packages/matplotlib-1.4.0-py2.7-linux-x86_64.egg/matplotlib/pyplot.pyc in savefig(*args, **kwargs)
    574 def savefig(*args, **kwargs):
    575     fig = gcf()
--> 576     res = fig.savefig(*args, **kwargs)
    577     draw()   # need this if 'transparent=True' to reset colors
    578     return res

/nfs/see-fs-01_users/eepdw/.local/lib/python2.7/site-packages/matplotlib-1.4.0-py2.7-linux-x86_64.egg/matplotlib/figure.pyc in savefig(self, *args, **kwargs)
   1468             self.set_frameon(frameon)
   1469 
-> 1470         self.canvas.print_figure(*args, **kwargs)
   1471 
   1472         if frameon:

/nfs/see-fs-01_users/eepdw/.local/lib/python2.7/site-packages/matplotlib-1.4.0-py2.7-linux-x86_64.egg/matplotlib/backend_bases.pyc in print_figure(self, filename, dpi, facecolor, edgecolor, orientation, format, **kwargs)
   2190                 orientation=orientation,
   2191                 bbox_inches_restore=_bbox_inches_restore,
-> 2192                 **kwargs)
   2193         finally:
   2194             if bbox_inches and restore_bbox:

/nfs/see-fs-01_users/eepdw/.local/lib/python2.7/site-packages/matplotlib-1.4.0-py2.7-linux-x86_64.egg/matplotlib/backends/backend_agg.pyc in print_png(self, filename_or_obj, *args, **kwargs)
    511 
    512     def print_png(self, filename_or_obj, *args, **kwargs):
--> 513         FigureCanvasAgg.draw(self)
    514         renderer = self.get_renderer()
    515         original_dpi = renderer.dpi

/nfs/see-fs-01_users/eepdw/.local/lib/python2.7/site-packages/matplotlib-1.4.0-py2.7-linux-x86_64.egg/matplotlib/backends/backend_agg.pyc in draw(self)
    459 
    460         try:
--> 461             self.figure.draw(self.renderer)
    462         finally:
    463             RendererAgg.lock.release()

/nfs/see-fs-01_users/eepdw/.local/lib/python2.7/site-packages/matplotlib-1.4.0-py2.7-linux-x86_64.egg/matplotlib/artist.pyc in draw_wrapper(artist, renderer, *args, **kwargs)
     57     def draw_wrapper(artist, renderer, *args, **kwargs):
     58         before(artist, renderer)
---> 59         draw(artist, renderer, *args, **kwargs)
     60         after(artist, renderer)
     61 

/nfs/see-fs-01_users/eepdw/.local/lib/python2.7/site-packages/matplotlib-1.4.0-py2.7-linux-x86_64.egg/matplotlib/figure.pyc in draw(self, renderer)
   1077         dsu.sort(key=itemgetter(0))
   1078         for zorder, a, func, args in dsu:
-> 1079             func(*args)
   1080 
   1081         renderer.close_group('figure')

/nfs/see-fs-01_users/eepdw/.local/lib/python2.7/site-packages/matplotlib-1.4.0-py2.7-linux-x86_64.egg/matplotlib/artist.pyc in draw_wrapper(artist, renderer, *args, **kwargs)
     57     def draw_wrapper(artist, renderer, *args, **kwargs):
     58         before(artist, renderer)
---> 59         draw(artist, renderer, *args, **kwargs)
     60         after(artist, renderer)
     61 

/nfs/see-fs-01_users/eepdw/.local/lib/python2.7/site-packages/matplotlib-1.4.0-py2.7-linux-x86_64.egg/matplotlib/axes/_base.pyc in draw(self, renderer, inframe)
   2090 
   2091         for zorder, a in dsu:
-> 2092             a.draw(renderer)
   2093 
   2094         renderer.close_group('axes')

/nfs/see-fs-01_users/eepdw/.local/lib/python2.7/site-packages/matplotlib-1.4.0-py2.7-linux-x86_64.egg/matplotlib/artist.pyc in draw_wrapper(artist, renderer, *args, **kwargs)
     57     def draw_wrapper(artist, renderer, *args, **kwargs):
     58         before(artist, renderer)
---> 59         draw(artist, renderer, *args, **kwargs)
     60         after(artist, renderer)
     61 

/nfs/see-fs-01_users/eepdw/.local/lib/python2.7/site-packages/matplotlib-1.4.0-py2.7-linux-x86_64.egg/matplotlib/axis.pyc in draw(self, renderer, *args, **kwargs)
   1103         ticks_to_draw = self._update_ticks(renderer)
   1104         ticklabelBoxes, ticklabelBoxes2 = self._get_tick_bboxes(ticks_to_draw,
-> 1105                                                                 renderer)
   1106 
   1107         for tick in ticks_to_draw:

/nfs/see-fs-01_users/eepdw/.local/lib/python2.7/site-packages/matplotlib-1.4.0-py2.7-linux-x86_64.egg/matplotlib/axis.pyc in _get_tick_bboxes(self, ticks, renderer)
   1055                 ticklabelBoxes.append(extent)
   1056             if tick.label2On and tick.label2.get_visible():
-> 1057                 extent = tick.label2.get_window_extent(renderer)
   1058                 ticklabelBoxes2.append(extent)
   1059         return ticklabelBoxes, ticklabelBoxes2

/nfs/see-fs-01_users/eepdw/.local/lib/python2.7/site-packages/matplotlib-1.4.0-py2.7-linux-x86_64.egg/matplotlib/text.pyc in get_window_extent(self, renderer, dpi)
    739             raise RuntimeError('Cannot get window extent w/o renderer')
    740 
--> 741         bbox, info, descent = self._get_layout(self._renderer)
    742         x, y = self.get_position()
    743         x, y = self.get_transform().transform_point((x, y))

/nfs/see-fs-01_users/eepdw/.local/lib/python2.7/site-packages/matplotlib-1.4.0-py2.7-linux-x86_64.egg/matplotlib/text.pyc in _get_layout(self, renderer)
    318                 w, h, d = renderer.get_text_width_height_descent(clean_line,
    319                                                         self._fontproperties,
--> 320                                                         ismath=ismath)
    321             else:
    322                 w, h, d = 0, 0, 0

/nfs/see-fs-01_users/eepdw/.local/lib/python2.7/site-packages/matplotlib-1.4.0-py2.7-linux-x86_64.egg/matplotlib/backends/backend_agg.pyc in get_text_width_height_descent(self, s, prop, ismath)
    218         if ismath:
    219             ox, oy, width, height, descent, fonts, used_characters = \
--> 220                 self.mathtext_parser.parse(s, self.dpi, prop)
    221             return width, height, descent
    222 

/nfs/see-fs-01_users/eepdw/.local/lib/python2.7/site-packages/matplotlib-1.4.0-py2.7-linux-x86_64.egg/matplotlib/mathtext.pyc in parse(self, s, dpi, prop)
   3003             self.__class__._parser = Parser()
   3004 
-> 3005         box = self._parser.parse(s, font_output, fontsize, dpi)
   3006         font_output.set_canvas_size(box.width, box.height, box.depth)
   3007         result = font_output.get_results(box)

/nfs/see-fs-01_users/eepdw/.local/lib/python2.7/site-packages/matplotlib-1.4.0-py2.7-linux-x86_64.egg/matplotlib/mathtext.pyc in parse(self, s, fonts_object, fontsize, dpi)
   2331         self._em_width_cache = {}
   2332         try:
-> 2333             result = self._expression.parseString(s)
   2334         except ParseBaseException as err:
   2335             raise ValueError("\n".join([

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in parseString(self, instring, parseAll)
   1099             instring = instring.expandtabs()
   1100         try:
-> 1101             loc, tokens = self._parse( instring, 0 )
   1102             if parseAll:
   1103                 loc = self.preParse( instring, loc )

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in _parseCache(self, instring, loc, doActions, callPreParse)
   1030         else:
   1031             try:
-> 1032                 value = self._parseNoCache( instring, loc, doActions, callPreParse )
   1033                 ParserElement._exprArgCache[ lookup ] = (value[0],value[1].copy())
   1034                 return value

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in _parseNoCache(self, instring, loc, doActions, callPreParse)
    973             if self.mayIndexError or loc >= len(instring):
    974                 try:
--> 975                     loc,tokens = self.parseImpl( instring, preloc, doActions )
    976                 except IndexError:
    977                     raise ParseException( instring, len(instring), self.errmsg, self )

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in parseImpl(self, instring, loc, doActions)
   2609     def parseImpl( self, instring, loc, doActions=True ):
   2610         if self.expr is not None:
-> 2611             return self.expr._parse( instring, loc, doActions, callPreParse=False )
   2612         else:
   2613             raise ParseException("",loc,self.errmsg,self)

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in _parseCache(self, instring, loc, doActions, callPreParse)
   1030         else:
   1031             try:
-> 1032                 value = self._parseNoCache( instring, loc, doActions, callPreParse )
   1033                 ParserElement._exprArgCache[ lookup ] = (value[0],value[1].copy())
   1034                 return value

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in _parseNoCache(self, instring, loc, doActions, callPreParse)
    973             if self.mayIndexError or loc >= len(instring):
    974                 try:
--> 975                     loc,tokens = self.parseImpl( instring, preloc, doActions )
    976                 except IndexError:
    977                     raise ParseException( instring, len(instring), self.errmsg, self )

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in parseImpl(self, instring, loc, doActions)
   2363                     raise ParseSyntaxException( ParseException(instring, len(instring), self.errmsg, self) )
   2364             else:
-> 2365                 loc, exprtokens = e._parse( instring, loc, doActions )
   2366             if exprtokens or exprtokens.haskeys():
   2367                 resultlist += exprtokens

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in _parseCache(self, instring, loc, doActions, callPreParse)
   1030         else:
   1031             try:
-> 1032                 value = self._parseNoCache( instring, loc, doActions, callPreParse )
   1033                 ParserElement._exprArgCache[ lookup ] = (value[0],value[1].copy())
   1034                 return value

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in _parseNoCache(self, instring, loc, doActions, callPreParse)
    973             if self.mayIndexError or loc >= len(instring):
    974                 try:
--> 975                     loc,tokens = self.parseImpl( instring, preloc, doActions )
    976                 except IndexError:
    977                     raise ParseException( instring, len(instring), self.errmsg, self )

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in parseImpl(self, instring, loc, doActions)
   2717         tokens = []
   2718         try:
-> 2719             loc, tokens = self.expr._parse( instring, loc, doActions, callPreParse=False )
   2720             hasIgnoreExprs = ( len(self.ignoreExprs) > 0 )
   2721             while 1:

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in _parseCache(self, instring, loc, doActions, callPreParse)
   1030         else:
   1031             try:
-> 1032                 value = self._parseNoCache( instring, loc, doActions, callPreParse )
   1033                 ParserElement._exprArgCache[ lookup ] = (value[0],value[1].copy())
   1034                 return value

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in _parseNoCache(self, instring, loc, doActions, callPreParse)
    973             if self.mayIndexError or loc >= len(instring):
    974                 try:
--> 975                     loc,tokens = self.parseImpl( instring, preloc, doActions )
    976                 except IndexError:
    977                     raise ParseException( instring, len(instring), self.errmsg, self )

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in parseImpl(self, instring, loc, doActions)
   2346         # pass False as last arg to _parse for first element, since we already
   2347         # pre-parsed the string as part of our And pre-parsing
-> 2348         loc, resultlist = self.exprs[0]._parse( instring, loc, doActions, callPreParse=False )
   2349         errorStop = False
   2350         for e in self.exprs[1:]:

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in _parseCache(self, instring, loc, doActions, callPreParse)
   1030         else:
   1031             try:
-> 1032                 value = self._parseNoCache( instring, loc, doActions, callPreParse )
   1033                 ParserElement._exprArgCache[ lookup ] = (value[0],value[1].copy())
   1034                 return value

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in _parseNoCache(self, instring, loc, doActions, callPreParse)
    999             else:
   1000                 for fn in self.parseAction:
-> 1001                     tokens = fn( instring, tokensStart, retTokens )
   1002                     if tokens is not None:
   1003                         retTokens = ParseResults( tokens,

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in wrapper(*args)
    763         while 1:
    764             try:
--> 765                 ret = func(*args[limit[0]:])
    766                 foundArity[0] = True
    767                 return ret

/nfs/see-fs-01_users/eepdw/.local/lib/python2.7/site-packages/matplotlib-1.4.0-py2.7-linux-x86_64.egg/matplotlib/mathtext.pyc in math_string(self, s, loc, toks)
   2402     def math_string(self, s, loc, toks):
   2403         # print "math_string", toks[0][1:-1]
-> 2404         return self._math_expression.parseString(toks[0][1:-1])
   2405 
   2406     def math(self, s, loc, toks):

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in parseString(self, instring, parseAll)
   1099             instring = instring.expandtabs()
   1100         try:
-> 1101             loc, tokens = self._parse( instring, 0 )
   1102             if parseAll:
   1103                 loc = self.preParse( instring, loc )

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in _parseCache(self, instring, loc, doActions, callPreParse)
   1030         else:
   1031             try:
-> 1032                 value = self._parseNoCache( instring, loc, doActions, callPreParse )
   1033                 ParserElement._exprArgCache[ lookup ] = (value[0],value[1].copy())
   1034                 return value

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in _parseNoCache(self, instring, loc, doActions, callPreParse)
    973             if self.mayIndexError or loc >= len(instring):
    974                 try:
--> 975                     loc,tokens = self.parseImpl( instring, preloc, doActions )
    976                 except IndexError:
    977                     raise ParseException( instring, len(instring), self.errmsg, self )

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in parseImpl(self, instring, loc, doActions)
   2609     def parseImpl( self, instring, loc, doActions=True ):
   2610         if self.expr is not None:
-> 2611             return self.expr._parse( instring, loc, doActions, callPreParse=False )
   2612         else:
   2613             raise ParseException("",loc,self.errmsg,self)

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in _parseCache(self, instring, loc, doActions, callPreParse)
   1030         else:
   1031             try:
-> 1032                 value = self._parseNoCache( instring, loc, doActions, callPreParse )
   1033                 ParserElement._exprArgCache[ lookup ] = (value[0],value[1].copy())
   1034                 return value

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in _parseNoCache(self, instring, loc, doActions, callPreParse)
    973             if self.mayIndexError or loc >= len(instring):
    974                 try:
--> 975                     loc,tokens = self.parseImpl( instring, preloc, doActions )
    976                 except IndexError:
    977                     raise ParseException( instring, len(instring), self.errmsg, self )

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in parseImpl(self, instring, loc, doActions)
   2759                 else:
   2760                     preloc = loc
-> 2761                 loc, tmptokens = self.expr._parse( instring, preloc, doActions )
   2762                 if tmptokens or tmptokens.haskeys():
   2763                     tokens += tmptokens

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in _parseCache(self, instring, loc, doActions, callPreParse)
   1030         else:
   1031             try:
-> 1032                 value = self._parseNoCache( instring, loc, doActions, callPreParse )
   1033                 ParserElement._exprArgCache[ lookup ] = (value[0],value[1].copy())
   1034                 return value

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in _parseNoCache(self, instring, loc, doActions, callPreParse)
    973             if self.mayIndexError or loc >= len(instring):
    974                 try:
--> 975                     loc,tokens = self.parseImpl( instring, preloc, doActions )
    976                 except IndexError:
    977                     raise ParseException( instring, len(instring), self.errmsg, self )

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in parseImpl(self, instring, loc, doActions)
   2609     def parseImpl( self, instring, loc, doActions=True ):
   2610         if self.expr is not None:
-> 2611             return self.expr._parse( instring, loc, doActions, callPreParse=False )
   2612         else:
   2613             raise ParseException("",loc,self.errmsg,self)

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in _parseCache(self, instring, loc, doActions, callPreParse)
   1030         else:
   1031             try:
-> 1032                 value = self._parseNoCache( instring, loc, doActions, callPreParse )
   1033                 ParserElement._exprArgCache[ lookup ] = (value[0],value[1].copy())
   1034                 return value

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in _parseNoCache(self, instring, loc, doActions, callPreParse)
    973             if self.mayIndexError or loc >= len(instring):
    974                 try:
--> 975                     loc,tokens = self.parseImpl( instring, preloc, doActions )
    976                 except IndexError:
    977                     raise ParseException( instring, len(instring), self.errmsg, self )

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in parseImpl(self, instring, loc, doActions)
   2468         for e in self.exprs:
   2469             try:
-> 2470                 ret = e._parse( instring, loc, doActions )
   2471                 return ret
   2472             except ParseException as err:

/apps/canopy-1.4.1/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pyparsing.py in _parseCache(self, instring, loc, doActions, callPreParse)
   1030         else:
   1031             try:
-> 1032                 value = self._parseNoCache( instring, loc, doActions, callPreParse )
   1033                 ParserElement._exprArgCache[ lookup ] = (value[0],value[1].copy())
   1034                 return value

KeyboardInterrupt: 





    













    













    













    













    













    

In [19]:

    

dates_savefig[i]


    

    
Out[19]:





datetime.datetime(2011, 6, 26, 0, 0)

In [16]:

    

date_min_max[:,0].shape


    

    
Out[16]:





(22,)

In [20]:

    

# Weekly Climatology theta_e_minus_theta_e_sat  with pbl and lcl, ROTATED winds

max_contour=315
min_contour=215
tick_interval=20

#variable='theta_e_minus_theta_e_sat'
variable='pot_temp'

cbar_number_format = '$%d$'

var_index = variable_name_index_match(variable, variable_list)
concat_plot_variable, distances, date_min_max,dates_savefig = variable_cat(var_index, station_list_cs)

cmap=plt.cm.jet

# For each time bin

for i, date_bin in enumerate(dates_savefig):

# Rotate winds
            
    try:    
   
# Grid data
        u_rot,v_rot = rotate_u_v_wind_array(u_wind[:,i,0:-1:10], v_wind[:,i,0:-1:10], radians(maths_bearing_to_rotate_winds))
        nan_mask = np.ma.masked_array(np.array(concat_plot_variable[:,i,:], dtype=float).flatten(), np.isnan(np.array(concat_plot_variable[:,i,:], dtype=float).flatten()))
        if nan_mask.mask.all() == False:
            xi,yi,zi = grid_data_cs(np.array(pressures[:,i,:], dtype=float).flatten(), np.repeat(distances, concat_plot_variable[:,i,:].shape[1]).flatten(), nan_mask) 
            
# Contour plot


            cont,cbar = plot_rad_cs_winds_rot_and_unrot(i, xi, yi, zi, min_contour, max_contour, np.repeat(distances, concat_plot_variable[:,i,0:-1:10].shape[1]).flatten(),
                                  np.array(pressures[:,i,0:-1:10], dtype=float).flatten(), u_wind[:,i,0:-1:10], v_wind[:,i,0:-1:10], u_rot, v_rot, cmap, cbar_number_format)
            
           # station_name_plot(station_list_cs, first_station, yi)


# Line plots
        LinePlots(variable_list_line, station_list_cs, distances) 
    
        cbar.set_label('\%', rotation=90)
    
# Plot station names and vertical lines at their location

        y_offset_text=0
        first_station_title, first_station_lon, first_station_lat = station_info_search(first_station)
    
        for stat in station_list_cs: 
     
            station_title, station_lon, station_lat = station_info_search(stat)
    
            dist_from_first_station = calculate_distance_from_first_station(stat, first_station_lon, first_station_lat, station_lat, station_lon)
            
            plt.axvline(x=dist_from_first_station, ymin=0, ymax=1, label=station_title, color='k')
            plt.text(dist_from_first_station+0.1,max(yi)/100+20,station_title,rotation=-45)

            y_offset_text=+1 
         
        plt.title('Week Beg.%s %s Cross-Section of Relative Humidity and Winds along Cross-Section Plane from Radiosonde Soundings' % (date_bin.strftime("%d %B"), Cross_Section_Title.replace('_',' ') ))

        plt.show()
    
    except Exception, e:
        PrintException()
  
 # plt.savefig('/nfs/a90/eepdw/Figures/Radiosonde/Cross_Sections/%s_%s_%s_Relative_Humidity_V_Wind.png' % (Cross_Section_Title, date_bin.strftime("%y"), date_bin.strftime("%d_%B")),  format='png', bbox_inches='tight')
 # plt.close()
 # plt.clf()
 # gc.collect()


    

    






<matplotlib.figure.Figure at 0x1a926d10>






    













    













    













    













    













    













    













    













    













    













    













    













    













    













    













    













    













    













    













    













    

In [9]:

    

load_file['date_bin_mean_all_dates_one_station_single']


    

    




---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-9-919d7a718bc4> in <module>()
----> 1 load_file['date_bin_mean_all_dates_one_station_single']

NameError: name 'load_file' is not defined

In [13]:

    

grid=[]

date_min_month_bin=datetime.datetime(2011,5,1,0,0,0)
date_max_month_bin=datetime.datetime(2011,10,1,0,0,0)
delta = relativedelta(weeks=+1)

d = date_min_month_bin
while (d <= date_max_month_bin): 
 grid.append(d.timetuple().tm_yday)
 d += delta
    

for stat in station_list_cs:

  load_file = np.load('/nfs/a90/eepdw/Data/Observations/Radiosonde_Numpy/Radiosonde_Cross_Section_'
                        'IND_SOUNDING_INTERP_MEAN_Climat_%s_%s_%s_%s.npz' 
                        % (date_min.strftime('%Y%m%d'), date_max.strftime('%Y%m%d'), delta, stat))
  load_file['date_bin_mean_all_dates_one_station_single'][:,0,1]

  date_plot = [datetime.datetime.fromordinal(d).replace(year=2011) for d in grid]
    
  station_name,la,lo=station_info_search(stat)
  
  variable='CAPE'
  var_index = variable_name_index_match(variable, variable_list_line)
  plt.plot_date(date_plot[1:], load_file['date_bin_mean_all_dates_one_station_single'][1:,0,var_index], fmt="-", label=variable)  
  
  variable='CIN'
  var_index = variable_name_index_match(variable, variable_list_line)
  plt.plot_date(date_plot[1:], load_file['date_bin_mean_all_dates_one_station_single'][1:,0,var_index], fmt="-", label=variable)  
  
  plt.legend()
  plt.title('%s' % station_name)
  #plt.gca().invert_yaxis()
  plt.show()


    

In [10]:

    

grid=[]

date_min_month_bin=datetime.datetime(2011,5,1,0,0,0)
date_max_month_bin=datetime.datetime(2011,10,1,0,0,0)
delta = relativedelta(weeks=+1)

d = date_min_month_bin
while (d <= date_max_month_bin): 
 grid.append(d.timetuple().tm_yday)
 d += delta
    

for stat in station_list_cs:

  load_file = np.load('/nfs/a90/eepdw/Data/Observations/Radiosonde_Numpy/Radiosonde_Cross_Section_'
                        'IND_SOUNDING_INTERP_MEAN_Climat_%s_%s_%s_%s.npz' 
                        % (date_min.strftime('%Y%m%d'), date_max.strftime('%Y%m%d'), delta, stat))
  load_file['date_bin_mean_all_dates_one_station_single'][:,0,1]

  date_plot = [datetime.datetime.fromordinal(d).replace(year=2011) for d in grid]
    
  station_name,la,lo=station_info_search(stat)
  
  variable='pbl_pressure'
  var_index = variable_name_index_match(variable, variable_list_line)
  plt.plot_date(date_plot[1:], load_file['date_bin_mean_all_dates_one_station_single'][1:,0,var_index], fmt="-", label='PBL')
    
  variable='lcl_vpt'
  var_index = variable_name_index_match(variable, variable_list_line)
  plt.plot_date(date_plot[1:], load_file['date_bin_mean_all_dates_one_station_single'][1:,0,var_index], fmt="-", label='LCL')  
  
  variable='surface_pressure'
  var_index = variable_name_index_match(variable, variable_list_line)
  plt.plot_date(date_plot[1:], load_file['date_bin_mean_all_dates_one_station_single'][1:,0,var_index], fmt="-", label='SP')  


  variable='T_eq_0'
  var_index = variable_name_index_match(variable, variable_list_line)
  plt.plot_date(date_plot[1:], load_file['date_bin_mean_all_dates_one_station_single'][1:,0,var_index], fmt="-", label='T_eq_0')
  
  plt.legend()
  plt.title('%s' % station_name)
  plt.gca().invert_yaxis()
  plt.show()


    

In [14]:

    

def station_name_vertical_line(station_list_cs, first_station_lon, first_station_lat, date_bin, Cross_Section_Title):
    
    for stat in station_list_cs: 
     
        station_title, station_lon, station_lat = station_info_search(stat)
    
        dist_from_first_station = calculate_distance_from_first_station(stat, first_station_lon, first_station_lat, station_lat, station_lon)
            
        plt.axvline(x=dist_from_first_station, ymin=0, ymax=1, label=station_title, color='k')
        plt.text(dist_from_first_station+0.1,max(yi)/100+20,station_title,rotation=-45)

        y_offset_text=+1 
        
        
variable='pressures'

var_index = variable_name_index_match(variable, variable_list)
concat_plot_variable, distances, date_min_max,dates_savefig = variable_cat(var_index, station_list_cs)

variable='rel_hum'

var_index = variable_name_index_match(variable, variable_list)
concat_plot_variable, distances, date_min_max,dates_savefig = variable_cat(var_index, station_list_cs)

max_contour=100
min_contour=0
tick_interval=10

cbar_number_format = '$%d$'
cmap=plt.cm.jet
    
for i, date_bin in enumerate(dates_savefig):
        
 try:
  # Grid data
  u_rot,v_rot = rotate_u_v_wind_array(u_wind[:,i,0:-1:10], v_wind[:,i,0:-1:10], radians(maths_bearing_to_rotate_winds))
  nan_mask = np.ma.masked_array(np.array(concat_plot_variable[:,i,:], dtype=float).flatten(), np.isnan(np.array(concat_plot_variable[:,i,:], dtype=float).flatten()))
  if nan_mask.mask.all() == False:
      xi,yi,zi = grid_data_cs(np.array(pressures[:,i,:], dtype=float).flatten(), np.repeat(distances, concat_plot_variable[:,i,:].shape[1]).flatten(), nan_mask) 
            
# Contour plot
            
  cont,cbar = plot_rad_cs_winds_rot_and_unrot(i, xi, yi, zi, min_contour, max_contour, np.repeat(distances, concat_plot_variable[:,i,0:-1:10].shape[1]).flatten(),
                                  np.array(pressures[:,i,0:-1:10], dtype=float).flatten(), u_wind[:,i,0:-1:10], v_wind[:,i,0:-1:10], u_rot, v_rot, cmap, cbar_number_format)
           # station_name_plot(station_list_cs, first_station, yi)
        
  LinePlots(variable_list_line, station_list_cs, distances)
        
  cbar.set_label('\%', rotation=90)

  #print date_bin
  
  y_offset_text=0
  first_station_title, first_station_lon, first_station_lat = station_info_search(first_station)
  
  station_name_vertical_line(station_list_cs, first_station_lon, first_station_lat, date_bin, Cross_Section_Title)
    
  plt.title('%s %s Cross-Section of Relative Humidity from Radiosonde Soundings' % (date_bin.strftime("%d %B"), Cross_Section_Title.replace('_',' ') ))
    
  #plt.show()
  
  plt.savefig('/nfs/a90/eepdw/Figures/Radiosonde/Cross_Sections/%s_%s_%s_%s_Relative_Humidity.png' % (Cross_Section_Title,  date_min.strftime('%Y%m%d'), date_max.strftime('%Y%m%d'), date_bin.strftime("%d_%B")),  format='png', bbox_inches='tight')
  plt.close()
  plt.clf()
  gc.collect()
 except Exception, e:
   PrintException()
        
#Potential Temperature

variable='pot_temp'

var_index = variable_name_index_match(variable, variable_list)
concat_plot_variable, distances, date_min_max,dates_savefig = variable_cat(var_index, station_list_cs)

max_contour=315
min_contour=215
tick_interval=20
    
cbar_number_format = '$%d$'
cmap=plt.cm.jet

for i, date_bin in enumerate(dates_savefig):
        
 try:
  u_rot,v_rot = rotate_u_v_wind_array(u_wind[:,i,0:-1:10], v_wind[:,i,0:-1:10], radians(maths_bearing_to_rotate_winds))
  nan_mask = np.ma.masked_array(np.array(concat_plot_variable[:,i,:], dtype=float).flatten(), np.isnan(np.array(concat_plot_variable[:,i,:], dtype=float).flatten()))
  if nan_mask.mask.all() == False:
      xi,yi,zi = grid_data_cs(np.array(pressures[:,i,:], dtype=float).flatten(), np.repeat(distances, concat_plot_variable[:,i,:].shape[1]).flatten(), nan_mask) 
            
# Contour plot
            
  cont,cbar = plot_rad_cs_winds_rot_and_unrot(i, xi, yi, zi, min_contour, max_contour, np.repeat(distances, concat_plot_variable[:,i,0:-1:10].shape[1]).flatten(),
                                  np.array(pressures[:,i,0:-1:10], dtype=float).flatten(), u_wind[:,i,0:-1:10], v_wind[:,i,0:-1:10], u_rot, v_rot, cmap, cbar_number_format)
        
  LinePlots(variable_list_line, station_list_cs, distances) 
        
  cbar.set_label('\%', rotation=90)
  plt.title('Week beg. %s %s Cross-Section of Potential Temperature from Radiosonde Soundings' % (date_bin.strftime("%d %B"), Cross_Section_Title.replace('_',' ') ))

  station_name_vertical_line(station_list_cs, first_station_lon, first_station_lat, date_bin, Cross_Section_Title)
        
  #plt.show()
  plt.savefig('/nfs/a90/eepdw/Figures/Radiosonde/Cross_Sections/%s_%s_%s_%s_pottemp.png' % (Cross_Section_Title,  date_min.strftime('%Y%m%d'), date_max.strftime('%Y%m%d'), date_bin.strftime("%d_%B")),  format='png', bbox_inches='tight')
  plt.close()
  plt.clf()
  gc.collect()
 except Exception, e:
   PrintException()


#Theta E

variable='theta_e'

var_index = variable_name_index_match(variable, variable_list)
concat_plot_variable, distances, date_min_max,dates_savefig = variable_cat(var_index, station_list_cs)

max_contour=380
min_contour=320
tick_interval=10
    
cbar_number_format = '$%d$'
cmap=plt.cm.jet

for i, date_bin in enumerate(dates_savefig):
        
 try:
  u_rot,v_rot = rotate_u_v_wind_array(u_wind[:,i,0:-1:10], v_wind[:,i,0:-1:10], radians(maths_bearing_to_rotate_winds))
  nan_mask = np.ma.masked_array(np.array(concat_plot_variable[:,i,:], dtype=float).flatten(), np.isnan(np.array(concat_plot_variable[:,i,:], dtype=float).flatten()))
  if nan_mask.mask.all() == False:
      xi,yi,zi = grid_data_cs(np.array(pressures[:,i,:], dtype=float).flatten(), np.repeat(distances, concat_plot_variable[:,i,:].shape[1]).flatten(), nan_mask) 
            
# Contour plot
            
  cont,cbar = plot_rad_cs_winds_rot_and_unrot(i, xi, yi, zi, min_contour, max_contour, np.repeat(distances, concat_plot_variable[:,i,0:-1:10].shape[1]).flatten(),
                                  np.array(pressures[:,i,0:-1:10], dtype=float).flatten(), u_wind[:,i,0:-1:10], v_wind[:,i,0:-1:10], u_rot, v_rot, cmap, cbar_number_format)
        
  LinePlots(variable_list_line, station_list_cs, distances) 
        
  cbar.set_label('K', rotation=90)
  plt.title('Week beg. %s %s Cross-Section of Equivalent Potential Temperature from Radiosonde Soundings' % (date_bin.strftime("%d %B"), Cross_Section_Title.replace('_',' ') ))

  station_name_vertical_line(station_list_cs, first_station_lon, first_station_lat, date_bin, Cross_Section_Title)
    
  #plt.show()
  plt.savefig('/nfs/a90/eepdw/Figures/Radiosonde/Cross_Sections/%s_%s_%s_%s_thetae.png' % (Cross_Section_Title,  date_min.strftime('%Y%m%d'), date_max.strftime('%Y%m%d'), date_bin.strftime("%d_%B")),  format='png', bbox_inches='tight')
  plt.close()
  plt.clf()
  gc.collect()
 except Exception, e:
   PrintException()

#Theta Es

variable='theta_e_sat'

var_index = variable_name_index_match(variable, variable_list)
concat_plot_variable, distances, date_min_max,dates_savefig = variable_cat(var_index, station_list_cs)

max_contour=420
min_contour=330
tick_interval=10
    
cbar_number_format = '$%d$'
cmap=plt.cm.jet

for i, date_bin in enumerate(dates_savefig):
        
 try:
  u_rot,v_rot = rotate_u_v_wind_array(u_wind[:,i,0:-1:10], v_wind[:,i,0:-1:10], radians(maths_bearing_to_rotate_winds))
  nan_mask = np.ma.masked_array(np.array(concat_plot_variable[:,i,:], dtype=float).flatten(), np.isnan(np.array(concat_plot_variable[:,i,:], dtype=float).flatten()))
  if nan_mask.mask.all() == False:
      xi,yi,zi = grid_data_cs(np.array(pressures[:,i,:], dtype=float).flatten(), np.repeat(distances, concat_plot_variable[:,i,:].shape[1]).flatten(), nan_mask) 
            
# Contour plot
            
  cont,cbar = plot_rad_cs_winds_rot_and_unrot(i, xi, yi, zi, min_contour, max_contour, np.repeat(distances, concat_plot_variable[:,i,0:-1:10].shape[1]).flatten(),
                                  np.array(pressures[:,i,0:-1:10], dtype=float).flatten(), u_wind[:,i,0:-1:10], v_wind[:,i,0:-1:10], u_rot, v_rot, cmap, cbar_number_format)
        
  LinePlots(variable_list_line, station_list_cs, distances) 
        
  cbar.set_label('K', rotation=90)
  plt.title('Week beg. %s %s Cross-Section of Saturated Equivalent Potential Temperature from Radiosonde Soundings' % (date_bin.strftime("%d %B"), Cross_Section_Title.replace('_',' ') ))

  station_name_vertical_line(station_list_cs, first_station_lon, first_station_lat, date_bin, Cross_Section_Title)
    
  #plt.show()
  plt.savefig('/nfs/a90/eepdw/Figures/Radiosonde/Cross_Sections/%s_%s_%s_%s_thetaesat.png' % (Cross_Section_Title,  date_min.strftime('%Y%m%d'), date_max.strftime('%Y%m%d') , date_bin.strftime("%d_%B")),  format='png', bbox_inches='tight')
  plt.close()
  plt.clf()
  gc.collect()
 except Exception, e:
   PrintException()
        
        
# WVMR

variable = 'wvmr'

var_index = variable_name_index_match(variable, variable_list)
concat_plot_variable, distances, date_min_max,dates_savefig = variable_cat(var_index, station_list_cs)

max_contour=0.02
min_contour=0.
tick_interval=0.001

cbar_number_format = '$%.3f$'
cmap=plt.cm.jet

for i, date_bin in enumerate(dates_savefig):
        
 try:
  u_rot,v_rot = rotate_u_v_wind_array(u_wind[:,i,0:-1:10], v_wind[:,i,0:-1:10], radians(maths_bearing_to_rotate_winds))
  nan_mask = np.ma.masked_array(np.array(concat_plot_variable[:,i,:], dtype=float).flatten(), np.isnan(np.array(concat_plot_variable[:,i,:], dtype=float).flatten()))
  if nan_mask.mask.all() == False:
      xi,yi,zi = grid_data_cs(np.array(pressures[:,i,:], dtype=float).flatten(), np.repeat(distances, concat_plot_variable[:,i,:].shape[1]).flatten(), nan_mask) 
            
# Contour plot
            
  cont,cbar = plot_rad_cs_winds_rot_and_unrot(i, xi, yi, zi, min_contour, max_contour, np.repeat(distances, concat_plot_variable[:,i,0:-1:10].shape[1]).flatten(),
                                  np.array(pressures[:,i,0:-1:10], dtype=float).flatten(), u_wind[:,i,0:-1:10], v_wind[:,i,0:-1:10], u_rot, v_rot, cmap, cbar_number_format)
        
  LinePlots(variable_list_line, station_list_cs, distances) 
        
  cbar.set_label('', rotation=90)
  plt.title('Week beg. %s %s Cross-Section of WVMR from Radiosonde Soundings' % (date_bin.strftime("%d %B"), Cross_Section_Title.replace('_',' ') ))

  station_name_vertical_line(station_list_cs, first_station_lon, first_station_lat, date_bin, Cross_Section_Title)
    
    #plt.show()
  plt.savefig('/nfs/a90/eepdw/Figures/Radiosonde/Cross_Sections/%s_%s_%s_%s_wvmr.png' % (Cross_Section_Title,  date_min.strftime('%Y%m%d'), date_max.strftime('%Y%m%d'), date_bin.strftime("%d_%B")),  format='png', bbox_inches='tight')
  plt.close()
  plt.clf()
  gc.collect()
 except Exception, e:
   PrintException()



#Theta Es - Theta E - Buoyancy

variable='theta_e_minus_theta_e_sat'

var_index = variable_name_index_match(variable, variable_list)
concat_plot_variable, distances, date_min_max,dates_savefig = variable_cat(var_index, station_list_cs)

cbar_number_format = '$%d$'

cmap=plt.cm.RdBu_r

max_contour=10
min_contour=-50
tick_interval=10
for i, date_bin in enumerate(dates_savefig):
        
 try:
  u_rot,v_rot = rotate_u_v_wind_array(u_wind[:,i,0:-1:10], v_wind[:,i,0:-1:10], radians(maths_bearing_to_rotate_winds))
  nan_mask = np.ma.masked_array(np.array(concat_plot_variable[:,i,:], dtype=float).flatten(), np.isnan(np.array(concat_plot_variable[:,i,:], dtype=float).flatten()))
  if nan_mask.mask.all() == False:
      xi,yi,zi = grid_data_cs(np.array(pressures[:,i,:], dtype=float).flatten(), np.repeat(distances, concat_plot_variable[:,i,:].shape[1]).flatten(), nan_mask) 
            
# Contour plot
            
  cont,cbar = plot_rad_cs_winds_rot_and_unrot_normalize(i, xi, yi, zi, min_contour, max_contour, np.repeat(distances, concat_plot_variable[:,i,0:-1:10].shape[1]).flatten(),
                                  np.array(pressures[:,i,0:-1:10], dtype=float).flatten(), u_wind[:,i,0:-1:10], v_wind[:,i,0:-1:10], u_rot, v_rot, cmap, cbar_number_format)
        
  LinePlots(variable_list_line, station_list_cs, distances) 
        
        
  cbar.set_label('K', rotation=90)
  plt.title('Week beg. %s %s Cross-Section of Theta-e BL Minus Theta-es Local from Radiosonde Soundings' % (date_bin.strftime("%d %B"), Cross_Section_Title.replace('_',' ') ))

  station_name_vertical_line(station_list_cs, first_station_lon, first_station_lat, date_bin, Cross_Section_Title)
    
  #plt.show()
  plt.savefig('/nfs/a90/eepdw/Figures/Radiosonde/Cross_Sections/%s_%s_%s_%s_thetaeminthetaesat_buoy.png' % (Cross_Section_Title, date_min.strftime('%Y%m%d'), date_max.strftime('%Y%m%d'), date_bin.strftime("%d_%B")),  format='png', bbox_inches='tight')
  plt.close()
  plt.clf()
  gc.collect()
 except Exception, e:
   PrintException()