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monitor_rdiag.py
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#!/usr/bin/env python
# coding: utf-8
import os
import random
import intake
import hvplot.pandas
import pandas as pd
import panel as pn
#import os
#import xarray as xr
#import hvplot.xarray
#import hvplot.pandas
#import pandas as pd
#import panel as pn
#import intake
#import cartopy.crs as ccrs
#import cartopy.feature as cfeature
#import geoviews as gv
#import geopandas as gpd
#import holoviews as hvs
#from datetime import datetime
#from holoviews.operation.datashader import rasterize
#import spatialpandas as spd
from datetime import datetime
from monitor_texts import MonitoringAppTexts
from monitor_dates import MonitoringAppDates
pn.extension()
monitor_app_texts = MonitoringAppTexts()
catalog_diag_conv_01 = intake.open_catalog('http://ftp1.cptec.inpe.br/pesquisa/das/carlos.bastarz/SMNAMonitoringApp/rdiag/catalog_diag_conv_01.yml')
catalog_diag_conv_03 = intake.open_catalog('http://ftp1.cptec.inpe.br/pesquisa/das/carlos.bastarz/SMNAMonitoringApp/rdiag/catalog_diag_conv_03.yml')
monitoring_app_dates = MonitoringAppDates()
sdate = monitoring_app_dates.getDates()[0].strip()
edate = monitoring_app_dates.getDates()[1].strip()
start_date = datetime(int(sdate[0:4]), int(sdate[4:6]), int(sdate[6:8]), int(sdate[8:10]))
end_date = datetime(int(edate[0:4]), int(edate[4:6]), int(edate[6:8]), int(edate[8:10]))
date_range = [d.strftime('%Y%m%d%H') for d in pd.date_range(start_date, end_date, freq='6h')][::-1]
date = pn.widgets.Select(name='Date', value=date_range[3], options=date_range)
loop = pn.widgets.Select(name='Loop', value='01', options=['01', '03'])
Tiles = ['CartoDark', 'CartoLight', 'EsriImagery', 'EsriNatGeo', 'EsriUSATopo',
'EsriTerrain', 'EsriStreet', 'EsriReference', 'OSM', 'OpenTopoMap']
tile = pn.widgets.Select(name='Tiles', value=Tiles[8], options=Tiles)
# From the catalogs, assemble a dictionary with all the kx values:
variable_list = ['q', 'ps', 't', 'uv', 'gps']
zlevs = [1000.0, 900.0, 800.0, 700.0, 600.0, 500.0, 400.0, 300.0, 250.0, 200.0, 150.0, 100.0, 50.0, 0.0]
_kx_values = {'q': [181, 120, 187, 180, 183],
'ps': [181, 180, 120, 187, 183],
't': [181, 180, 120, 187, 183, 130, 126],
'uv': [257, 258, 281, 280, 253, 243, 254, 220, 287, 221, 284, 230, 244, 259, 252, 242, 250, 210, 229, 224, 282],
'gps': [42, 269, 5, 44, 43, 3, 754, 752, 755, 753, 751, 750]}
_kx_valuesn = _kx_values.copy()
_kx_valuess = _kx_values.copy()
varn = pn.widgets.Select(name='Variable', value=variable_list[0], options=variable_list)
kxn = pn.widgets.MultiChoice(name='kx', value=_kx_values[varn.value], options=_kx_values[varn.value], solid=False)
@pn.depends(varn.param.value, watch=True)
def _update_kx_valuesn(select_varn):
kx_valuesn = _kx_valuesn[select_varn]
kxn.options = kx_valuesn
kxn.value = kx_valuesn
vars = pn.widgets.Select(name='Variable', value=variable_list[0], options=variable_list)
kxs = pn.widgets.MultiChoice(name='kx', value=_kx_values[vars.value], options=_kx_values[vars.value], solid=False)
@pn.depends(vars.param.value, watch=True)
def _update_kx_valuess(select_vars):
kx_valuess = _kx_valuess[select_vars]
kxs.options = kx_valuess
kxs.value = kx_valuess
level = pn.widgets.Select(name='Level', value=zlevs[0], options=zlevs)
iuse = pn.widgets.Select(name='iuse', value=1, options=[-1, 1])
by_level = pn.widgets.Toggle(name='by Level', value=False, button_type='success')
by_kx = pn.widgets.Toggle(name='by kx', value=False, button_type='success')
@pn.cache
def loadData(lfname, loop):
try:
if loop == '01':
ax = catalog_diag_conv_01[lfname].read()
elif loop == '03':
ax = catalog_diag_conv_03[lfname].read()
except:
ax = monitor_app_texts.warnings_rdiag(lfname + ' (loadData)')
return ax
@pn.depends(vars, kxs, level, iuse, date, loop, tile)
def plotPtmap(vars, kxs, level, iuse, date, loop, tile):
try:
lfname = str(vars) + '_diag_conv_' + str(loop) + '_' + str(date)
#print(lfname)
obsInfo = loadData(lfname, loop)
df = obsInfo
maskl = df['press'] == level
dffl = df[maskl]
maski = dffl['iuse'] == iuse
dffi = dffl[maski]
instr = getVarInfo(kxs, vars, 'instrument')
label = '\n'.join(wrap(vars + '-' + str(kxs) + ' | ' + instr,30))
ax = dffi.hvplot(global_extent=True,
grid=True,
tiles=tile,
title=label,
frame_height=750)
except:
ax = monitor_app_texts.warnings_rdiag(lfname + ' (plotPtmap)')
return pn.Column(ax)
@pn.depends(vars, kxs, level, iuse, date, loop, tile)
def plotPtmapMulti(vars, kxs, level, iuse, date, loop, tile):
try:
lfname = str(vars) + '_diag_conv_' + str(loop) + '_' + str(date)
#print(lfname)
obsInfo = loadData(lfname, loop)
df = obsInfo.loc[kxs]
maskl = df['press'] == level
dffl = df[maskl]
maski = dffl['iuse'] == iuse
dffi = dffl[maski]
color = [random.choice(['b', 'g', 'r', 'c', 'm', 'y', 'k']) for _ in range(len(_kx_values[str(vars)]))]
for count, i in enumerate(kxs):
if count == 0:
ax = dffi.hvplot.points(x='lon',
y='lat',
geo=True,
color=color,
tiles=tile,
#responsive=True,
frame_height=600,
frame_width=800,
title=str(vars) + ' | kx = ' + str(kxs) + ' | ' + str(level) + ' hPa | iuse = ' + str(iuse) + ' | loop = ' + str(loop) + ' | valid for ' + str(date))
else:
ax *= dffi.hvplot.points(x='lon',
y='lat',
geo=True,
color=color,
tiles=tile,
#responsive=True,
frame_height=600,
frame_width=800,
title=str(vars) + ' | kx = ' + str(kxs) + ' | ' + str(level) + ' hPa | iuse = ' + str(iuse) + ' | loop = ' + str(loop) + ' | valid for ' + str(date))
except:
ax = monitor_app_texts.warnings_rdiag(lfname + ' (plotPtmapMulti)')
return pn.Column(ax)
@pn.depends(varn, kxn, by_level, date, loop)
def plotPcount(varn, kxn, by_level, date, loop):
try:
lfname = str(varn) + '_diag_conv_' + str(loop) + '_' + str(date)
obsInfo = loadData(lfname, loop)
if by_level:
df = obsInfo.loc[kxn].groupby('press').size()
ax = df.hvplot.bar(x='press',
grid=True,
rot=45,
width=1000,
height=600,
ylabel='Number of Observations',
title=str(varn) + '| kx = ' + str(kxn) + ' | loop = ' + str(loop) + ' | valid for ' + str(date))
else:
df = obsInfo.groupby(level=0).size()
ax = df.hvplot.bar(x='kx',
grid=True,
rot=45,
width=1000,
height=600,
ylabel='Number of Observations',
title=str(varn) + '| all levels | loop = ' + str(loop) + ' | valid for ' + str(date))
except:
ax = monitor_app_texts.warnings_rdiag(lfname + ' (plotPcount)')
return pn.Column(ax)
@pn.depends(varn, kxn, by_level, by_kx, date, loop)
def plotPcount2(varn, kxn, by_level, by_kx, date, loop):
try:
lfname = str(varn) + '_diag_conv_' + str(loop) + '_' + str(date)
#print(lfname)
obsInfo = loadData(lfname, loop)
if by_level:
df = obsInfo.loc[kxn].groupby('press').size()
#df = obsInfo.groupby(['press', 'kx']).size()
ax = df.hvplot.bar(stacked=True,
legend="top_left",
rot=45,
#width=1000,
height=600,
ylabel='Number of Observations',
responsive=True,
title=str(varn) + ' | kx = ' + str(kxn) + ' | loop = ' + str(loop) + ' | valid for ' + str(date))
elif by_kx:
df = obsInfo.drop(kxn).groupby(['press', 'kx']).size()
ax = df.hvplot.barh(stacked=True,
legend="bottom_right",
rot=45,
#width=1000,
height=600,
ylabel='Number of Observations',
responsive=True,
title=str(varn) + ' | loop = ' + str(loop) + ' | valid for ' + str(date))
ax.opts(invert_yaxis=True)
else:
df = obsInfo.groupby(level=0).size()
ax = df.hvplot.bar(x='kx',
grid=True,
rot=45,
#width=1000,
height=600,
ylabel='Number of Observations',
responsive=True,
title=str(varn) + ' | all levels | loop = ' + str(loop) + ' | valid for ' + str(date))
except:
ax = monitor_app_texts.warnings_rdiag(lfname + ' (plotPcount2)')
return pn.Column(ax)
@pn.depends(varn, kxn, by_level, date, loop)
def getTable(varn, kxn, by_level, date, loop):
try:
lfname = str(varn) + '_diag_conv_' + str(loop) + '_' + str(date)
#print(lfname)
obsInfo = loadData(lfname, loop)
if by_level:
ax = obsInfo[varn].head(50)#[varn].loc[kxn]#.loc[kxn].groupby('press')#.size()
#ax = pn.widgets.Tabulator(df)
else:
ax = obsInfo[varn].groupby(level=0)#.size()
#ax = pn.widgets.Tabulator(df)
except:
ax = monitor_app_texts.warnings_rdiag(lfname + ' (getTable)')
return pn.Column(ax)
def LayoutSidebarRdiag():
card_parameters = pn.Card(date,
pn.Card(varn, loop, by_level, kxn, by_kx, title='Number of Observations', collapsed=False),
#pn.Card(varn, by_level, kxn, title='Table', collapsed=True),
pn.Card(vars, loop, tile, kxs, level, iuse, title='Spatial Distribution', collapsed=True),
title='Parameters', collapsed=False)
return pn.Column(card_parameters)
def LayoutMainRdiag():
main_text = pn.Column("""
# Analysis Diagnostics
Set the parameters on the left to update the map below and explore our analysis features.
""")
return pn.Column(main_text, pn.Tabs(('NUMBER OF OBSERVATIONS', pn.Column('Number of Observations for a variable by level and type (kx).', plotPcount2)),
#('Table', pn.Column('Table.', getTable)),
('SPATIAL DISTRIBUTION', pn.Column('Spatial distribution of observations by level and type (kx).', plotPtmapMulti)), dynamic=True),
sizing_mode="stretch_both")