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#!/usr/bin/env python3
import os
import json
import numpy as np
import matplotlib.pyplot as plt
import metpy.calc as mpcalc
import misc
HEIGHT = 13
def run(data, plots, output='.'):
misc.create_output_dir(output)
index = []
for plot in plots:
index.append(_plot(data, output, **plot))
return index
def _get_next_subplot(size, counter=0):
ret = (counter + 1, counter + size)
counter += size
return counter, ret
def _add_cloudcov(ax, data):
ax.set_ylabel('Pressure level [hPa]')
clc = ax.contourf(data.valid_time, data.isobaricInhPa, data.ccl.transpose(), cmap='clcov', vmin=0, vmax=100, levels=9)
# use Format parameter for n/8
plt.colorbar(clc, label='cloudcov', extendfrac=None, ticks=[100*n/8 for n in range(9)], format=lambda x,_: f'{int(x/12.5)}/8', pad=0.0, fraction=0.015)
cf = ax.contour(data.valid_time, data.isobaricInhPa, data.t.metpy.convert_units('degC').transpose())
ax.clabel(cf, inline=True, fontsize=10)
ax.barbs(
data.valid_time,
data.isobaricInhPa,
data.u.metpy.convert_units('kt').transpose(),
data.v.metpy.convert_units('kt').transpose()
)
ax.invert_yaxis()
def _add_temp_dewpoint(ax, data):
### Temp + Dewpoint
ax.plot(data.valid_time, data.t2m.metpy.convert_units('degC').transpose(), color='red', label='Temperature (2m)')
ax.plot(data.valid_time, mpcalc.dewpoint_from_relative_humidity(data.t2m, data.r2).transpose(), color='blue', label='Dewpoint (2m)')
ax.plot(data.valid_time, data.sel(isobaricInhPa=850.0).t.metpy.convert_units('degC').transpose(), color='grey', label='Tempreature (850hPa)')
ax.set_ylabel('Temperature [degC]')
ax.legend(loc='lower right')
def _add_mslp(ax, data):
ax.plot(data.valid_time, data.prmsl.metpy.convert_units('hPa').transpose(), color='black', label='Temperature (2m)')
ax.set_ylabel('Mean Sea Level Pressure [hPa]')
def _add_convective_clouds(ax, data):
# TODO: ADD HBAS_CON, HTOP_CON
# If none: -500m
ax.set_ylim(0, 14)
ax.set_ylabel('Convective Clouds Height [km]')
ax.bar(data.valid_time, alpha=0.5,
bottom=data.HBAS_CON.metpy.convert_units('km').transpose(),
height=(data.hcct.metpy.convert_units('km')-data.HBAS_CON.metpy.convert_units('km')).transpose(),
align='edge', width=np.timedelta64(3, 'h'))
def _add_precip(ax, data):
ax.set_ylabel('Total precipitation [mm]')
ax.set_ylim(0, 30)
ax.bar(data.valid_time[:-1], data.tp.diff('step').transpose(), width=np.timedelta64(3, 'h'),
align='edge', alpha=0.7, color='green')
ax_p = ax.twinx()
ax_p.set_ylabel('Snow depth [m]')
ax_p.set_ylim(bottom=0)
ax_p.plot(data.valid_time, data.sde.transpose(), color='blue')
def _add_surface_wind(ax, data):
ax.plot(data.valid_time, mpcalc.wind_speed(data.u10.transpose(), data.v10.transpose()), color='black', label='Wind (10m)')
ax.plot(data.valid_time, data.fg10.transpose(), color='red', label='Gust (10m)')
ax_b = ax.twinx()
ax_b.barbs(
data.valid_time,
[1 for _ in data.valid_time],
data.u10.metpy.convert_units('kt').transpose(),
data.v10.metpy.convert_units('kt').transpose()
)
ax_b.axis('off')
ax.set_ylabel('Wind Speed [m/s]')
ax.legend(loc='lower right')
def _plot(data, output, name, lat, lon):
data = data.sel(latitude=lat, longitude = lon, method='nearest')
fig = plt.figure(figsize=(12, 12), layout="constrained")
sp_cnt, spec = _get_next_subplot(4)
ax = fig.add_subplot(HEIGHT,1,spec)
_add_cloudcov(ax, data)
sp_cnt, spec2 = _get_next_subplot(2,sp_cnt)
ax2 = fig.add_subplot(HEIGHT,1,spec2,sharex=ax)
_add_temp_dewpoint(ax2, data)
sp_cnt, spec3 = _get_next_subplot(2,sp_cnt)
ax3 = fig.add_subplot(HEIGHT,1,spec3,sharex=ax)
#ax3.legend(loc='lower right')
_add_mslp(ax3, data)
ax4 = ax3.twinx()
_add_convective_clouds(ax4, data)
sp_cnt, spec4 = _get_next_subplot(2,sp_cnt)
ax5 = fig.add_subplot(HEIGHT,1,spec4,sharex=ax)
_add_precip(ax5, data)
sp_cnt, spec5 = _get_next_subplot(2,sp_cnt)
ax6 = fig.add_subplot(HEIGHT,1,spec5,sharex=ax)
_add_surface_wind(ax6, data)
### Info Lines
sp_cnt, spec5 = _get_next_subplot(1,sp_cnt)
ax_text = fig.add_subplot(HEIGHT, 1, spec5)
info_lines = []
init = misc.np_time_convert(data.time.values)
init_str = init.strftime('%d %b %Y - %HUTC')
init_for_filename = init.strftime('%Y-%m-%d-%HUTC')
info_lines.append(f'{name}')
info_lines.append(f"INIT : {init_str}")
info_lines.append(f"LAT {lat} LON {lon}")
if '_description' in data.attrs:
info_lines.append(data.attrs['_description'])
ax_text.text(0, 0, '\n'.join(info_lines), ha='left', va='center',
size=10, fontfamily='monospace')
ax_text.axis("off")
### Output
outname = f'{name}_{init_for_filename}.png'
plt.savefig(os.path.join(output, outname))
plt.close('all')
index = []
index.append(
{
'file': outname,
'init': init_str,
'valid': init_str,
'valid_offset': '00'
}
)
with open(os.path.join(output, f'{name}.index.json'), 'w') as f:
f.write(json.dumps(index, indent=4))
return { 'name': name, 'indexfile': f'{name}.index.json' }
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