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lagrangian_animation.py
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lagrangian_animation.py
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from matplotlib import pyplot as plt
from tracking.core import cell_tracking as ct
from datetime import datetime
from find_storms import parse_date_string
import pandas as pd
import numpy as np
import pyart
import gc
from matplotlib.ticker import Formatter as formatter
from matplotlib import pyplot as plt
import matplotlib.animation
import matplotlib as mpl
import cartopy.feature as cfeature
import cartopy.crs as ccrs
out_dir = ''
tracks_path = '/Users/Mark/argonne/houston/combined_storms.csv'
tracks = pd.read_csv(tracks_path)
tracks.set_index(['storm_id', 'uid'], inplace=True)
cells = tracks.groupby(level=['storm_id', 'uid'])
tracks['life_iso'] = cells.apply(lambda x: np.all(x['isolated']))
tracks['nscans'] = cells.size()
ideal_cell = tracks.loc[tracks[tracks.life_iso]['nscans'].argmax()].copy()
ideal_cell['time'] = ideal_cell['time'].apply(parse_date_string)
config_grid = pyart.io.read_grid(ideal_cell['file'].iloc[0])
grid_size = ct.get_grid_size(config_grid)
box_size = 50
a = 0
stepsize = 6
title_font = 20
axes_font = 18
mpl.rcParams['xtick.labelsize'] = 16
mpl.rcParams['ytick.labelsize'] = 16
for ind, row in ideal_cell.iterrows():
grid = pyart.io.read_grid(row['file'])
display = pyart.graph.GridMapDisplay(grid)
# Box Size
tx = row['grid_x']
ty = row['grid_y']
lvxlim = np.array([tx - box_size, tx + box_size]) * grid_size[1]
lvylim = np.array([ty - box_size, ty + box_size]) * grid_size[2]
lat = grid.point_latitude['data'][0, int(ty), int(tx)]
lon = grid.point_longitude['data'][0, int(ty), int(tx)]
bsx = tx-grid.fields['reflectivity']['data'].shape[1]/2
bsy = ty-grid.fields['reflectivity']['data'].shape[1]/2
xlim = np.array([bsx - box_size, bsx + box_size]) * grid_size[1]/1000
ylim = np.array([bsy - box_size, bsy + box_size]) * grid_size[2]/1000
fig = plt.figure(figsize=(25,18))
plt.title('Lagrangian View', fontsize=22)
plt.axis('off')
#Lagrangian View
ax1 = fig.add_subplot(3, 2, (1, 3))
display.plot_grid('reflectivity', level=ct.get_gs_alt(grid_size, 3000),
vmin=-8, vmax=64, mask_outside = False,
cmap=pyart.graph.cm.NWSRef,
ax = ax1, colorbar_flag = False, linewidth=4)
display.plot_crosshairs(lon=lon, lat=lat, line_style='k--', linewidth=3)
ax1.set_xlim(lvxlim[0], lvxlim[1])
ax1.set_ylim(lvylim[0], lvylim[1])
ax1.set_xticks(np.arange(lvxlim[0], lvxlim[1], (stepsize * 1000)))
ax1.set_yticks(np.arange(lvylim[0], lvylim[1], (stepsize * 1000)))
ax1.set_xticklabels(np.round((np.arange(xlim[0], xlim[1], stepsize)), 2))
ax1.set_yticklabels(np.round((np.arange(ylim[0], ylim[1], stepsize)), 2))
ax1.set_title('Top-Down View', fontsize = title_font)
ax1.set_xlabel('East West Distance From Origin (km)' + '\n',
fontsize=axes_font)
ax1.set_ylabel('North South Distance From Origin (km)',
fontsize=axes_font)
#Latitude Cross Section
ax2 = fig.add_subplot(3, 2, 2)
display.plot_latitude_slice('reflectivity', lon=lon, lat=lat,
title_flag=False,
colorbar_flag=False, edges=False,
vmin=-8, vmax=64, mask_outside = False,
cmap=pyart.graph.cm.NWSRef,
ax = ax2)
shift = 6
ax2.set_xlim(xlim[0], xlim[1])
ax2.set_xticks(np.arange(xlim[0], xlim[1], stepsize))
ax2.set_xticklabels(np.round((np.arange(xlim[0], xlim[1], stepsize)), 2))
ax2.set_title('Latitude Cross Section', fontsize = title_font)
ax2.set_xlabel('East West Distance From Origin (km)' + '\n',
fontsize=axes_font)
ax2.set_ylabel('Distance Above Origin (km)', fontsize=axes_font)
ax2.set_aspect(aspect = 1.4)
#Longitude Cross Section
ax3 = fig.add_subplot(3,2,4)
display.plot_longitude_slice('reflectivity', lon=lon, lat=lat,
title_flag=False,
colorbar_flag=False, edges=False,
vmin=-8, vmax=64, mask_outside = False,
cmap=pyart.graph.cm.NWSRef,
ax = ax3)
ax3.set_xlim(ylim[0], ylim[1])
ax3.set_xticks(np.arange(ylim[0], ylim[1], stepsize))
ax3.set_xticklabels(np.round((np.arange(ylim[0], ylim[1], stepsize)), 2))
ax3.set_title('Longitudinal Cross Section', fontsize = title_font)
ax3.set_xlabel('North South Distance From Origin (km)', fontsize=axes_font)
ax3.set_ylabel('Distance Above Origin (km)', fontsize=axes_font)
ax3.set_aspect(aspect = 1.4)
#Statistics
# Data
maxref = ideal_cell['max']
maxalt = ideal_cell['max_alt']
# Time Calculation
trackdatetime = ideal_cell['time']
timeindex = trackdatetime.index
plttime = []
for t in trackdatetime.index:
hour = (trackdatetime[t].hour)*100
minute = trackdatetime[t].minute
timecalc = hour + minute
plttime.append(int(timecalc))
# Plot
ax4 = fig.add_subplot(3,2,(5,6))
#ax4.plot(plttime, vol[timeindex])
ax4.plot(plttime, maxref[timeindex], color='b', linewidth=3)
#ax4.plot(plttime, maxalt[timeindex], color='g')
ax4.axvline(x=plttime[a], linewidth=4, color='r')
ax4.set_title('Time Series', fontsize = title_font)
ax4.set_xlabel('Time (UTC) \n Lagrangian Viewer Time (vertical line, red)',
fontsize=axes_font)
ax4.set_ylabel('Maximum Reflectivity (dBZ, blue)', fontsize=axes_font)
ax4.set_aspect(aspect = 5)
a = a+1
#plot and save figure
fig.savefig(outdir + 'scan_' + str(row['scan']) + '.png')
plt.clf()
del grid
gc.collect()