def draw_cumulated_precip(
rain=None,
map_extent=(50, 150, 0, 65),
add_china=True,city=True,south_China_sea=True,add_background=True,
output_dir=None,Global=False):
initTime = pd.to_datetime(rain.attrs['initTime']).replace(tzinfo=None).to_pydatetime()
fcstTime1 = initTime + timedelta(hours=int(rain.attrs['fhour1']-rain.attrs['t_gap']))
fcstTime2 = initTime + timedelta(hours=int(rain.attrs['fhour2']))
title = '[{}] {}到{}时效累积降水'.format(rain.attrs['model'],int(rain.attrs['fhour1']-rain.attrs['t_gap']),int(rain.attrs['fhour2']))
forcast_info = '起报时间: {0:%Y}年{0:%m}月{0:%d}日{0:%H}时\n起始时间: {1:%Y}年{1:%m}月{1:%d}日{1:%H}时\n终止时间: {2:%Y}年{2:%m}月{2:%d}日{2:%H}时\nwww.nmc.cn'.format(initTime, fcstTime1, fcstTime2)
fig, ax, map_extent = GF.pallete_set.Horizontal_Pallete((18, 9),map_extent=map_extent, title=title, forcast_info=forcast_info,info_zorder=4,
add_china=add_china, add_city=city, add_background=add_background, south_China_sea=south_China_sea)
if rain is not None:
x, y = np.meshgrid(rain['lon'], rain['lat'])
z=np.squeeze(rain['data'].values)
z[z<0.1]=np.nan
cmap,norm=dk_ctables.cm_qpf_nws(atime=24)
plots={}
cmap.set_under(color=[0,0,0,0],alpha=0.0)
plots['rain'] = ax.pcolormesh(
x,y,z, norm=norm,
cmap=cmap, zorder=1,transform=ccrs.PlateCarree(),alpha=0.5)
l, b, w, h = ax.get_position().bounds
# add color bar
cax=plt.axes([l,b-0.04,w,.02])
cb = plt.colorbar(plots['rain'], cax=cax, orientation='horizontal')
cb.ax.tick_params(labelsize='x-large')
cb.set_label('Precipitation (mm)',size=20)
if(output_dir is not None):
plt.savefig(output_dir+
'起报时间_{0:%Y}年{0:%m}月{0:%d}日{0:%H}时_起始时间_{1:%Y}年{1:%m}月{1:%d}日{1:%H}时_终止时间_{1:%Y}年{1:%m}月{1:%d}日{1:%H}时'.format(initTime, fcstTime1, fcstTime2)+'.png', dpi=200,bbox_inches='tight')
plt.close()
else:
plt.show()
def draw_cumulated_precip(
rain=None,
map_extent=(50, 150, 0, 65),
regrid_shape=20,
add_china=True,city=True,south_China_sea=True,
output_dir=None,Global=False):
# set font
plt.rcParams['font.sans-serif'] = ['SimHei'] # 步骤一（替换sans-serif字体）
plt.rcParams['axes.unicode_minus'] = False # 步骤二（解决坐标轴负数的负号显示问题）
# set figure
fig = plt.figure(figsize=(9,14))
camera = Camera(fig)
nframe=rain['data'].shape[0]
plotcrs = ccrs.AlbersEqualArea(central_latitude=(map_extent[2]+map_extent[3])/2.,
central_longitude=(map_extent[0]+map_extent[1])/2., standard_parallels=[30., 60.])
datacrs = ccrs.PlateCarree()
ax = plt.axes([0.01,0.1,.98,.84], projection=plotcrs)
map_extent2=utl.adjust_map_ratio(ax,map_extent=map_extent,datacrs=datacrs)
# define return plots
plots = {}
# draw mean sea level pressure
if rain is not None:
x, y = np.meshgrid(rain['lon'], rain['lat'])
z=np.squeeze(rain['data'].values)
z[z<0.1]=np.nan
znan=np.zeros(shape=x.shape)
znan[:]=np.nan
# cmap,norm=dk_ctables.cm_qpf_nws(atime=None,
# pos=np.concatenate((
# np.array([0, 0.1, 0.5, 1]), np.arange(2.5, 25, 2.5),
# np.arange(25, 50, 5), np.arange(50, 150, 10),
# np.arange(150, 800, 50))))
cmap,norm=dk_ctables.cm_qpf_nws(atime=24)
cmap.set_under(color=[0,0,0,0],alpha=0.0)
plots['rain'] = ax.pcolormesh(
x,y,znan, norm=norm,
cmap=cmap, zorder=1,transform=datacrs,alpha=0.5)
#additional information
plt.title('['+rain.attrs['model']+'] '+
str(int(rain.coords['forecast_period'].values[0]))+'至'+str(int(rain.coords['forecast_period'].values[-1]))+'时效累积降水预报',
loc='left', fontsize=30)
ax.add_feature(cfeature.OCEAN)
utl.add_china_map_2cartopy_public(
ax, name='coastline', edgecolor='gray', lw=0.8, zorder=3,alpha=0.5)
if add_china:
utl.add_china_map_2cartopy_public(
ax, name='province', edgecolor='gray', lw=0.5, zorder=3)
utl.add_china_map_2cartopy_public(
ax, name='nation', edgecolor='black', lw=0.8, zorder=3)
utl.add_china_map_2cartopy_public(
ax, name='river', edgecolor='#74b9ff', lw=0.8, zorder=3,alpha=0.5)
# grid lines
gl = ax.gridlines(
crs=datacrs, linewidth=2, color='gray', alpha=0.5, linestyle='--', zorder=1)
gl.xlocator = mpl.ticker.FixedLocator(np.arange(0, 360, 15))
gl.ylocator = mpl.ticker.FixedLocator(np.arange(-90, 90, 15))
utl.add_cartopy_background(ax,name='RD')
l, b, w, h = ax.get_position().bounds
#forecast information
initTime = pd.to_datetime(
str(rain.coords['forecast_reference_time'].values)).replace(tzinfo=None).to_pydatetime()
#发布时间
if(sys.platform[0:3] == 'lin'):
locale.setlocale(locale.LC_CTYPE, 'zh_CN.utf8')
if(sys.platform[0:3] == 'win'):
locale.setlocale(locale.LC_CTYPE, 'chinese')
# add color bar
cax=plt.axes([l,b-0.04,w,.02])
cb = plt.colorbar(plots['rain'], cax=cax, orientation='horizontal')
cb.ax.tick_params(labelsize='x-large')
cb.set_label('Precipitation (mm)',size=20)
fcst_time=initTime+timedelta(hours=rain.coords['forecast_period'].values[0])
bax=plt.axes([l,b+h-0.07,.45,.07])
bax.set_yticks([])
bax.set_xticks([])
bax.axis([0, 10, 0, 10])
fcst_time1=initTime+timedelta(hours=rain.coords['forecast_period'].values[0]-6)
bax.text(2.5, 7.5,'起始时间: '+fcst_time1.strftime("%Y年%m月%d日%H时"),size=15)
bax.text(2.5, 0.5,'www.nmc.cn',size=15)
valid_fhour=bax.text(2.5, 5,'截至时间: ',size=15)
txt_fhour=bax.text(2.5, 2.5,'预报时效: ',size=15)
utl.add_logo_extra_in_axes(pos=[l-0.0,b+h-0.085,.1,.1],which='nmc', size='Xlarge')
# add south China sea
if south_China_sea:
utl.add_south_China_sea(pos=[l+w-0.091,b,.1,.2])
small_city=False
if(map_extent2[1]-map_extent2[0] < 25):
small_city=True
if city:
utl.add_city_on_map(ax,map_extent=map_extent2,transform=datacrs,zorder=2,size=13,small_city=small_city)
fcst_time2=initTime+timedelta(hours=rain.coords['forecast_period'].values[-1])
valid_fhour.set_text('截至时间: '+fcst_time2.strftime("%Y年%m月%d日%H时"))
txt_fhour.set_text('预报时效: '+str(int(rain.coords['forecast_period'].values[-1]))+'小时')
ax.pcolormesh(
x,y,np.squeeze(z[-1,:,:]), norm=norm,
cmap=cmap, zorder=1,transform=datacrs,alpha=0.5)
# plt.draw()
plt.savefig(output_dir+
'起报时间_'+initTime.strftime("%Y年%m月%d日%H时")+
'预报时效_'+str(int(rain.coords['forecast_period'].values[-1]))+'小时_'+rain.attrs['model']+'.png', dpi=200,bbox_inches='tight')
def draw_cumulated_precip_evo(
rain=None,
map_extent=(50, 150, 0, 65),
regrid_shape=20,
add_china=True,city=True,south_China_sea=True,
output_dir=None,Global=False):
# set font
plt.rcParams['font.sans-serif'] = ['SimHei'] # 步骤一（替换sans-serif字体）
plt.rcParams['axes.unicode_minus'] = False # 步骤二（解决坐标轴负数的负号显示问题）
# set figure
fig = plt.figure(figsize=(16,9))
plotcrs = ccrs.AlbersEqualArea(central_latitude=(map_extent[2]+map_extent[3])/2.,
central_longitude=(map_extent[0]+map_extent[1])/2., standard_parallels=[30., 60.])
datacrs = ccrs.PlateCarree()
ax = plt.axes([0.01,0.1,.98,.84], projection=plotcrs)
map_extent2=utl.adjust_map_ratio(ax,map_extent=map_extent,datacrs=datacrs)
# define return plots
plots = {}
# draw mean sea level pressure
if rain is not None:
x, y = np.meshgrid(rain['lon'], rain['lat'])
z=np.squeeze(rain['data'].values)
z[z<0.1]=np.nan
znan=np.zeros(shape=x.shape)
znan[:]=np.nan
cmap,norm=dk_ctables.cm_qpf_nws(atime=24)
cmap.set_under(color=[0,0,0,0],alpha=0.0)
plots['rain'] = ax.pcolormesh(
x,y,znan, norm=norm,
cmap=cmap, zorder=1,transform=datacrs,alpha=0.5)
#additional information
plt.title('['+rain.attrs['model']+'] '+
str(int(rain.coords['forecast_period'].values[0])-rain.attrs['t_gap'])+
'至'+str(int(rain.coords['forecast_period'].values[-1]))+'时效累积降水预报',
loc='left', fontsize=25)
ax.add_feature(cfeature.OCEAN)
utl.add_china_map_2cartopy_public(
ax, name='coastline', edgecolor='gray', lw=0.8, zorder=3,alpha=0.5)
if add_china:
utl.add_china_map_2cartopy_public(
ax, name='province', edgecolor='gray', lw=0.5, zorder=3)
utl.add_china_map_2cartopy_public(
ax, name='nation', edgecolor='black', lw=0.8, zorder=3)
utl.add_china_map_2cartopy_public(
ax, name='river', edgecolor='#74b9ff', lw=0.8, zorder=3,alpha=0.5)
# grid lines
gl = ax.gridlines(
crs=datacrs, linewidth=2, color='gray', alpha=0.5, linestyle='--', zorder=1)
gl.xlocator = mpl.ticker.FixedLocator(np.arange(0, 360, 15))
gl.ylocator = mpl.ticker.FixedLocator(np.arange(-90, 90, 15))
utl.add_cartopy_background(ax,name='RD')
l, b, w, h = ax.get_position().bounds
#forecast information
initTime = pd.to_datetime(
str(rain.coords['forecast_reference_time'].values)).replace(tzinfo=None).to_pydatetime()
#发布时间
if(sys.platform[0:3] == 'lin'):
locale.setlocale(locale.LC_CTYPE, 'zh_CN.utf8')
if(sys.platform[0:3] == 'win'):
locale.setlocale(locale.LC_CTYPE, 'chinese')
# add color bar
cax=plt.axes([l,b-0.04,w,.02])
cb = plt.colorbar(plots['rain'], cax=cax, orientation='horizontal')
cb.ax.tick_params(labelsize='x-large')
cb.set_label('Precipitation (mm)',size=20)
fcst_time=initTime+timedelta(hours=rain.coords['forecast_period'].values[0])
bax=plt.axes([l,b+h-0.1,.25,.1])
bax.set_yticks([])
bax.set_xticks([])
bax.axis([0, 10, 0, 10])
fcst_time1=initTime+timedelta(hours=rain.coords['forecast_period'].values[0]-6)
bax.text(2.5, 7.5,'起始时间: '+fcst_time1.strftime("%Y年%m月%d日%H时"),size=15)
bax.text(2.5, 0.5,'www.nmc.cn',size=15)
valid_fhour=bax.text(2.5, 5,'截至时间: ',size=15)
txt_fhour=bax.text(2.5, 2.5,'预报时效: ',size=15)
utl.add_logo_extra_in_axes(pos=[l-0.02,b+h-0.1,.1,.1],which='nmc', size='Xlarge')
# add south China sea
if south_China_sea:
utl.add_south_China_sea(pos=[l+w-0.091,b,.1,.2])
small_city=False
if(map_extent2[1]-map_extent2[0] < 25):
small_city=True
if city:
utl.add_city_on_map(ax,map_extent=map_extent2,transform=datacrs,zorder=2,size=13,small_city=small_city)
def update(frame_number):
fcst_time2=initTime+timedelta(hours=rain.coords['forecast_period'].values[frame_number])
valid_fhour.set_text('截至时间: '+fcst_time2.strftime("%Y年%m月%d日%H时"))
txt_fhour.set_text('预报时效: '+str(int(rain.coords['forecast_period'].values[frame_number]))+'小时')
return ax.pcolormesh(
x,y,np.squeeze(z[frame_number,:,:]), norm=norm,
cmap=cmap, zorder=1,transform=datacrs,alpha=0.5)
nframes=rain['data'].shape[0]
animation1 = FuncAnimation(fig, update, frames=nframes,interval=1000)
# ffmpegpath = os.path.abspath(r"C:\Users\HEYGY\Desktop\ffmpeg-20200824-3477feb-win64-static\bin\ffmpeg.exe")
# import matplotlib
# matplotlib.rcParams["animation.ffmpeg_path"] = ffmpegpath
# writer = animation.FFMpegWriter()
# show figure
plt.subplots_adjust(top=1, bottom=0, right=0.93, left=0, hspace=0, wspace=0)
plt.margins(0, 0)
if(output_dir != None):
animation1.save(output_dir+'累积降水演变_'+
'起报时间_'+initTime.strftime("%Y年%m月%d日%H时")+
'预报时效_'+str(int(rain.coords['forecast_period'].values[-1]))+'小时_'+
'['+rain.attrs['model']+'] '+'.gif',writer='pillow')
if(output_dir == None):
#animation.save('rain.gif', fps=75, writer='imagemagick')
plt.show()
def draw_gh_rain(gh=None, rain=None,
map_extent=(50, 150, 0, 65),
regrid_shape=20,
add_china=True,city=True,south_China_sea=True,
output_dir=None,Global=False):
# set font
plt.rcParams['font.sans-serif'] = ['SimHei'] # 步骤一（替换sans-serif字体）
plt.rcParams['axes.unicode_minus'] = False # 步骤二（解决坐标轴负数的负号显示问题）
# set figure
plt.figure(figsize=(16,9))
if(Global == True):
plotcrs = ccrs.Robinson(central_longitude=115.)
else:
plotcrs = ccrs.AlbersEqualArea(central_latitude=(map_extent[2]+map_extent[3])/2.,
central_longitude=(map_extent[0]+map_extent[1])/2., standard_parallels=[30., 60.])
datacrs = ccrs.PlateCarree()
ax = plt.axes([0.01,0.1,.98,.84], projection=plotcrs)
map_extent2=utl.adjust_map_ratio(ax,map_extent=map_extent,datacrs=datacrs)
# define return plots
plots = {}
# draw mean sea level pressure
if rain is not None:
x, y = np.meshgrid(rain['lon'], rain['lat'])
z=np.squeeze(rain['data'].values)
z[z<0.1]=np.nan
cmap,norm=dk_ctables.cm_qpf_nws(atime=rain.attrs['atime'])
cmap.set_under(color=[0,0,0,0],alpha=0.0)
plots['rain'] = ax.pcolormesh(
x,y,z, norm=norm,
cmap=cmap, zorder=1,transform=datacrs,alpha=0.5)
# draw -hPa geopotential height
if gh is not None:
x, y = np.meshgrid(gh['lon'], gh['lat'])
clevs_gh = np.append(np.append(np.arange(0, 480, 4),np.append(np.arange(480, 584, 8), np.arange(580, 604, 4))), np.arange(604, 2000, 8))
plots['gh'] = ax.contour(
x, y, np.squeeze(gh['data']), clevs_gh, colors='black',
linewidths=2, transform=datacrs, zorder=3)
plt.clabel(plots['gh'], inline=2, fontsize=20, fmt='%.0f',colors='black')
#additional information
plt.title('['+gh.attrs['model']+'] '+
str(int(gh['level'].values[0]))+'hPa 位势高度场, '+
str(int(rain.attrs['atime']))+'小时降水',
loc='left', fontsize=30)
ax.add_feature(cfeature.OCEAN)
utl.add_china_map_2cartopy_public(
ax, name='coastline', edgecolor='gray', lw=0.8, zorder=3,alpha=0.5)
if add_china:
utl.add_china_map_2cartopy_public(
ax, name='province', edgecolor='gray', lw=0.5, zorder=3)
utl.add_china_map_2cartopy_public(
ax, name='nation', edgecolor='black', lw=0.8, zorder=3)
utl.add_china_map_2cartopy_public(
ax, name='river', edgecolor='#74b9ff', lw=0.8, zorder=3,alpha=0.5)
# grid lines
gl = ax.gridlines(
crs=datacrs, linewidth=2, color='gray', alpha=0.5, linestyle='--', zorder=1)
gl.xlocator = mpl.ticker.FixedLocator(np.arange(0, 360, 15))
gl.ylocator = mpl.ticker.FixedLocator(np.arange(-90, 90, 15))
utl.add_cartopy_background(ax,name='RD')
l, b, w, h = ax.get_position().bounds
#forecast information
bax=plt.axes([l,b+h-0.1,.25,.1],facecolor='#FFFFFFCC')
bax.set_yticks([])
bax.set_xticks([])
bax.axis([0, 10, 0, 10])
initTime = pd.to_datetime(
str(gh.coords['forecast_reference_time'].values)).replace(tzinfo=None).to_pydatetime()
fcst_time=initTime+timedelta(hours=gh.coords['forecast_period'].values[0])
#发布时间
if(sys.platform[0:3] == 'lin'):
locale.setlocale(locale.LC_CTYPE, 'zh_CN.utf8')
if(sys.platform[0:3] == 'win'):
locale.setlocale(locale.LC_CTYPE, 'chinese')
plt.text(2.5, 7.5,'起报时间: '+initTime.strftime("%Y年%m月%d日%H时"),size=15)
plt.text(2.5, 5,'预报时间: '+fcst_time.strftime("%Y年%m月%d日%H时"),size=15)
plt.text(2.5, 2.5,'预报时效: '+str(int(gh.coords['forecast_period'].values[0]))+'小时'+'(降水'+str(int(gh.coords['forecast_period'].values[0]+12))+'小时)',size=15)
plt.text(2.5, 0.5,'www.nmc.cn',size=15)
# add color bar
if(rain != None):
cax=plt.axes([l,b-0.04,w,.02])
cb = plt.colorbar(plots['rain'], cax=cax, orientation='horizontal')
cb.ax.tick_params(labelsize='x-large')
cb.set_label(str(int(rain.attrs['atime']))+'h precipitation (mm)',size=20)
# add south China sea
if south_China_sea:
utl.add_south_China_sea(pos=[l+w-0.091,b,.1,.2])
small_city=False
if(map_extent2[1]-map_extent2[0] < 25):
small_city=True
if city:
utl.add_city_on_map(ax,map_extent=map_extent2,transform=datacrs,zorder=2,size=13,small_city=small_city)
utl.add_logo_extra_in_axes(pos=[l-0.02,b+h-0.1,.1,.1],which='nmc', size='Xlarge')
# show figure
if(output_dir != None):
plt.savefig(output_dir+'高度场_降水_预报_'+
'起报时间_'+initTime.strftime("%Y年%m月%d日%H时")+
'预报时效_'+str(int(gh.coords['forecast_period'].values[0]))+'小时'+'.png', dpi=200)
if(output_dir == None):
plt.show()