#!/usr/bin/env python # coding: utf-8 import os import xarray as xr import hvplot.xarray import pandas as pd import panel as pn import intake import cartopy.crs as ccrs import cartopy.feature as cfeature import holoviews as hvs from datetime import datetime from monitor_texts import MonitoringAppTexts from monitor_dates import MonitoringAppDates hvplot.extension("matplotlib") monitor_app_texts = MonitoringAppTexts() catalog_anl = intake.open_catalog('http://ftp1.cptec.inpe.br/pesquisa/das/carlos.bastarz/GSIMonitor/anls/catalog_anl.yml') catalog_bkg = intake.open_catalog('http://ftp1.cptec.inpe.br/pesquisa/das/carlos.bastarz/GSIMonitor/anls/catalog_bkg.yml') variable_list = [ 'TOPOGRAPHY', 'LAND SEA ICE MASK', 'LN SURFACE PRESSURE', 'DIVERGENCE', 'VORTICITY', 'SPECIFIC HUMIDITY', 'VIRTUAL TEMPERATURE', 'ROUGHNESS LENGTH', 'SURFACE TEMPERATURE', 'DEEP SOIL TEMPERATURE', 'STORAGE ON CANOPY', 'STORAGE ON GROUND', 'SOIL WETNESS OF SURFACE', 'SOIL WETNESS OF ROOT ZONE', 'SOIL WETNESS OF DRAINAGE ZONE', 'TEMPERATURE AT 2-M FROM SURFACE', 'SPECIFIC HUMIDITY AT 2-M FROM SURFACE', 'ZONAL WIND AT 10-M FROM SURFACE', 'MERID WIND AT 10-M FROM SURFACE', 'MASK VEGETATION', 'MASK SOIL TEXTURE CLASSES', 'PARTIAL OXYGEN DENSITY', 'SURFACE SOIL TEMPERATURE', 'VEGETATION COVER', 'SNOW DEPTH', 'LIQ MIXING RATIO PROGNOSTIC', 'ICE MIXING RATIO PROGNOSTIC', 'CLOUD TOTAL PROGNOSTIC', ] variable = pn.widgets.Select(name='Variable', value=variable_list[0], options=variable_list) vcoord_levels = [1.0000000e+03, 9.9467389e+02, 9.8864404e+02, 9.8182812e+02, 9.7413733e+02, 9.6547662e+02, 9.5574554e+02, 9.4483936e+02, 9.3265070e+02, 9.1907172e+02, 9.0399707e+02, 8.8732709e+02, 8.6897253e+02, 8.4885895e+02, 8.2693237e+02, 8.0316449e+02, 7.7755896e+02, 7.5015576e+02, 7.2103583e+02, 6.9032397e+02, 6.5818927e+02, 6.2484418e+02, 5.9053998e+02, 5.5556073e+02, 5.2021417e+02, 4.8482129e+02, 4.4970471e+02, 4.1517715e+02, 3.8153036e+02, 3.4902579e+02, 3.1788751e+02, 2.8829736e+02, 2.6039276e+02, 2.3426695e+02, 2.0997141e+02, 1.8751950e+02, 1.6689160e+02, 1.4804048e+02, 1.3089703e+02, 1.1537564e+02, 1.0137925e+02, 8.8803711e+01, 7.7541557e+01, 6.7485062e+01, 5.8528511e+01, 5.0570110e+01, 4.3513206e+01, 3.7267128e+01, 3.1747662e+01, 2.6877260e+01, 2.2585030e+01, 1.8806541e+01, 1.5483560e+01, 1.2563700e+01, 1.0000000e+01, 7.7563500e+00, 5.8265901e+00, 4.2146201e+00, 2.9185901e+00, 1.9237399e+00, 1.1999500e+00, 7.0422000e-01, 3.8661000e-01, 1.9740000e-01] level = pn.widgets.Select(name='Level', value=vcoord_levels[0], options=vcoord_levels) monitoring_app_dates = MonitoringAppDates() sdate = monitoring_app_dates.getDates()[0] edate = monitoring_app_dates.getDates()[1] 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[0], options=date_range) colormaps = ['nipy_spectral', 'Blues', 'BrBG', 'BuGn', 'BuPu', 'CMRmap', 'Dark2', 'GnBu', 'Greens', 'Greys', 'OrRd', 'Oranges', 'PRGn', 'Paired', 'Pastel1', 'Pastel2', 'PiYG', 'PuBu', 'PuBuGn', 'PuOr', 'PuRd', 'Purples', 'RdBu', 'RdGy', 'RdPu', 'RdYlBu', 'RdYlGn', 'Reds', 'Set1', 'Set2', 'Set3', 'Spectral', 'Wistia', 'YlGn', 'YlGnBu', 'YlOrBr', 'YlOrRd', 'afmhot', 'autumn', 'binary', 'bone', 'brg', 'bwr', 'cividis', 'cool', 'Accent', 'copper', 'crest', 'cubehelix', 'flag', 'flare', 'gist_earth', 'gist_gray', 'gist_heat', 'gist_ncar', 'gist_stern', 'gist_yarg', 'gnuplot', 'gnuplot2', 'gray', 'hot', 'hsv', 'icefire', 'inferno', 'jet', 'magma', 'mako', 'coolwarm', 'ocean', 'pink', 'plasma', 'prism', 'rainbow', 'rocket', 'seismic', 'spring', 'summer', 'tab10', 'tab20', 'tab20b', 'tab20c', 'terrain', 'turbo', 'twilight', 'twilight_shifted', 'viridis', 'vlag', 'winter'] colormap = pn.widgets.Select(name='Colormap', value=colormaps[0], options=colormaps) invert_colors = pn.widgets.Checkbox(name='Invert Colors', value=False) showdiff = pn.widgets.Checkbox(name='Show Difference', value=False) @pn.cache def loadDataAnl(lfname): return catalog_anl[lfname].to_dask() @pn.cache def loadDataBkg(lfname): return catalog_anl[lfname].to_dask() @pn.depends(variable, level, date, colormap, invert_colors, showdiff) def plotFields(variable, level, date, colormap, invert_colors, showdiff): lfname = date vars3d = ['DIVERGENCE', 'VORTICITY', 'SPECIFIC HUMIDITY', 'VIRTUAL TEMPERATURE', 'LIQ MIXING RATIO PROGNOSTIC', 'ICE MIXING RATIO PROGNOSTIC', 'CLOUD TOTAL PROGNOSTIC'] try: dfs_anl = loadDataAnl(lfname) dfs_bkg = loadDataBkg(lfname) cmin=dfs_anl[variable].min() cmax=dfs_anl[variable].max() frame_height=900 frame_height2=1800 height=450 width=1600 fontsize=10 if invert_colors == True: cmap = colormap + '_r' else: cmap = colormap if variable in vars3d: if showdiff: dfsdiff = dfs_anl[variable].sel(lev=level)-dfs_bkg[variable].sel(lev=level) ax = dfsdiff.hvplot.contourf(x="lon", y="lat", geo=True, coastline=True, frame_height=frame_height2, grid=True, cmap=cmap, rasterize=True, title="Analysis Minus Background of " + str(variable) + " @ level " + str(level) + " (valid for " + str(date) + ")", fontsize=fontsize) else: ax_anl = dfs_anl[variable].sel(lev=level).hvplot.contourf(x="lon", y="lat", geo=True, coastline=True, #frame_height=frame_height, #height=height, width=width, grid=True, cmap=cmap, rasterize=True, title="Analysis of " + str(variable) + " @ level " + str(level) + " (valid for " + str(date) + ")", fontsize=fontsize) ax_bkg = dfs_bkg[variable].sel(lev=level).hvplot.contourf(x="lon", y="lat", geo=True, coastline=True, #frame_height=frame_height, #height=height, width=width, grid=True, cmap=cmap, rasterize=True, title="Background of " + str(variable) + " @ level " + str(level) + " (valid for " + str(date) + ")", fontsize=fontsize) ax = hvs.Layout(ax_anl + ax_bkg).cols(2) else: if showdiff: dfsdiff = dfs_anl[variable]-dfs_bkg[variable] ax = dfsdiff.hvplot.contourf(x="lon", y="lat", geo=True, coastline=True, frame_height=frame_height2, grid=True, cmap=cmap, rasterize=True, title="Analysis Minus Background of " + str(variable) + " (valid for " + str(date) + ")", fontsize=fontsize) else: ax_anl = dfs_anl[variable].hvplot.contourf(x="lon", y="lat", geo=True, coastline=True, #frame_height=frame_height, #height=height, width=width, grid=True, cmap=cmap, rasterize=True, title="Analysis of " + str(variable) + " (valid for " + str(date) + ")", fontsize=fontsize) ax_bkg = dfs_bkg[variable].hvplot.contourf(x="lon", y="lat", geo=True, coastline=True, #frame_height=frame_height, #height=height, width=width, grid=True, cmap=cmap, rasterize=True, title="Background of " + str(variable) + " (valid for " + str(date) + ")", fontsize=fontsize) ax = hvs.Layout(ax_anl + ax_bkg).cols(2) except: ax = monitor_app_texts.warnings_anl(lfname) return pn.Column(ax, sizing_mode='stretch_width') def LayoutSidebarAnl(): card_parameters = pn.Card(date, variable, level, showdiff, colormap, invert_colors, title='Parameters', collapsed=False) return pn.Column(card_parameters) def LayoutMainAnl(): main_text = pn.Column(""" # Analysis Plots Set the parameters on the left to update the map below and explore our analysis features. """) return pn.Column(main_text, plotFields)