def draw_vvel_high(uwind,
vwind,
wwind,
lon,
lat,
gh=None,
skip_vector=None,
map_region=None,
title_kwargs={},
outfile=None):
"""
Draw high vertical velocity.
Args:
uwind (np.array): u wind component, 2D array, [nlat, nlon]
vwind (np.array): v wind component, 2D array, [nlat, nlon]
wwind (np.array): w wind component, 2D array, [nlat, nlon]
lon (np.array): longitude, 1D array, [nlon]
lat (np.array): latitude, 1D array, [nlat]
gh (np.array): geopotential height, 2D array, [nlat, nlon]
skip_vector (integer): skip grid number for vector plot
map_region (list or tuple): the map region limit, [lonmin, lonmax, latmin, latmax]
title_kwargs (dictionaly, optional): keyword arguments for _get_title function.
"""
# check default parameters
if skip_vector is None:
skip_vector = util.get_skip_vector(lon, lat, map_region)
# put data into fields
wind_field = util.minput_2d_vector(uwind,
vwind,
lon,
lat,
skip=skip_vector)
vvel_field = util.minput_2d(wwind, lon, lat, {
'long_name': 'vertical velocity',
'units': 'Pa/s'
})
if gh is not None:
gh_feild = util.minput_2d(gh, lon, lat, {
'long_name': 'height',
'units': 'gpm'
})
#
# set up visual parameters
#
plots = []
# Setting the coordinates of the geographical area
if map_region is None:
china_map = map_set.get_mmap(name='CHINA_CYLINDRICAL',
subpage_frame_thickness=5)
else:
china_map = map_set.get_mmap(name='CHINA_REGION_CYLINDRICAL',
map_region=map_region,
subpage_frame_thickness=5)
plots.append(china_map)
# Background Coaslines
coastlines = map_set.get_mcoast(name='COAST_FILL')
plots.append(coastlines)
# Define the shading contour
vvel_contour = magics.mcont(legend='on',
contour_level_selection_type='level_list',
contour_level_list=[
-60, -30, -10, -5, -2.5, -1, -0.5, -0.2,
0.2, 0.5, 1, 2.5, 5, 10, 30
],
contour_shade='on',
contour="off",
contour_shade_method='area_fill',
contour_shade_colour_method='list',
contour_shade_colour_list=[
'#9D0001', '#C90101', '#F10202', '#FF3333',
'#FF8585', '#FFBABA', '#FEDDDD', '#FFFFFF',
'#E1E1FF', '#BABAFF', '#8484FF', '#2C2CF7',
'#0404F1', '#0101C8', '#020299'
],
contour_reference_level=0,
contour_highlight='off',
contour_hilo='off',
contour_label='off')
plots.extend([vvel_field, vvel_contour])
# Define the wind vector
wind_vector = common._get_wind_flags()
plots.extend([wind_field, wind_vector])
# Define the simple contouring for gh
if gh is not None:
gh_contour = common._get_gh_contour()
plots.extend([gh_feild, gh_contour])
# Add a legend
legend = common._get_legend(china_map, title="Vertical Velocity [Pa/s]")
plots.append(legend)
# Add the title
title_kwargs = check_kwargs(title_kwargs, 'head',
"700hPa Vertical Velocity | Wind | GH")
title = common._get_title(**title_kwargs)
plots.append(title)
# Add china province
china_coastlines = map_set.get_mcoast(name='PROVINCE')
plots.append(china_coastlines)
# final plot
return util.magics_plot(plots, outfile)
def draw_vort_high(uwind,
vwind,
lon,
lat,
vort=None,
gh=None,
skip_vector=None,
smooth_factor=1.0,
map_region=None,
title_kwargs={},
outfile=None):
"""
Draw high vorticity.
Args:
uwind (np.array): u wind component, 2D array, [nlat, nlon]
vwind (np.array): v wind component, 2D array, [nlat, nlon]
lon (np.array): longitude, 1D array, [nlon]
lat (np.array): latitude, 1D array, [nlat]
vort (np.array, optional): vorticity component, 2D array, [nlat, nlon]
gh (np.array): geopotential height, 2D array, [nlat, nlon]
skip_vector (integer): skip grid number for vector plot
smooth_factor (float): smooth factor for vorticity, larger for smoother.
map_region (list or tuple): the map region limit, [lonmin, lonmax, latmin, latmax]
title_kwargs (dictionaly, optional): keyword arguments for _get_title function.
"""
# check default parameters
if skip_vector is None:
skip_vector = util.get_skip_vector(lon, lat, map_region)
# put data into fields
wind_field = util.minput_2d_vector(uwind,
vwind,
lon,
lat,
skip=skip_vector)
if vort is None:
dx, dy = calc.lat_lon_grid_deltas(lon, lat)
vort = calc.vorticity(uwind * units.meter / units.second,
vwind * units.meter / units.second, dx, dy)
vort = ndimage.gaussian_filter(vort, sigma=smooth_factor,
order=0) * 10**5
vort_field = util.minput_2d(vort, lon, lat, {
'long_name': 'vorticity',
'units': 's-1'
})
if gh is not None:
gh_feild = util.minput_2d(gh, lon, lat, {
'long_name': 'height',
'units': 'gpm'
})
#
# set up visual parameters
#
plots = []
# Setting the coordinates of the geographical area
if map_region is None:
china_map = map_set.get_mmap(name='CHINA_CYLINDRICAL',
subpage_frame_thickness=5)
else:
china_map = map_set.get_mmap(name='CHINA_REGION_CYLINDRICAL',
map_region=map_region,
subpage_frame_thickness=5)
plots.append(china_map)
# Background Coaslines
coastlines = map_set.get_mcoast(name='COAST_FILL')
plots.append(coastlines)
# Define the shading contour
vort_contour = magics.mcont(
legend='on',
contour_level_selection_type='level_list',
contour_level_list=[
-200.0, -100.0, -75.0, -50.0, -30.0, -20.0, -15.0, -13.0, -11.0,
-9.0, -7.0, -5.0, -3.0, -1.0, 1.0, 3.0, 5.0, 7.0, 9.0, 11.0, 13.0,
15.0, 20.0, 30.0, 50.0, 75.0, 100.0, 200.0
],
contour_shade='on',
contour="off",
contour_shade_method='area_fill',
contour_shade_colour_method='list',
contour_shade_colour_list=[
"rgb(0,0,0.3)", "rgb(0,0,0.5)", "rgb(0,0,0.7)", "rgb(0,0,0.9)",
"rgb(0,0.15,1)", "rgb(0,0.3,1)", "rgb(0,0.45,1)", "rgb(0,0.6,1)",
"rgb(0,0.75,1)", "rgb(0,0.85,1)", "rgb(0.2,0.95,1)",
"rgb(0.45,1,1)", "rgb(0.75,1,1)", "none", "rgb(1,1,0)",
"rgb(1,0.9,0)", "rgb(1,0.8,0)", "rgb(1,0.7,0)", "rgb(1,0.6,0)",
"rgb(1,0.5,0)", "rgb(1,0.4,0)", "rgb(1,0.3,0)", "rgb(1,0.15,0)",
"rgb(0.9,0,0)", "rgb(0.7,0,0)", "rgb(0.5,0,0)", "rgb(0.3,0,0)"
],
contour_reference_level=8.,
contour_highlight='off',
contour_hilo='off',
contour_label='off')
plots.extend([vort_field, vort_contour])
# Define the wind vector
wind_vector = common._get_wind_flags()
plots.extend([wind_field, wind_vector])
# Define the simple contouring for gh
if gh is not None:
gh_contour = common._get_gh_contour()
plots.extend([gh_feild, gh_contour])
# Add a legend
legend = common._get_legend(china_map, title="Vorticity [s^-1]")
plots.append(legend)
# Add the title
title_kwargs = check_kwargs(title_kwargs, 'head',
"500hPa Relative vorticity | Wind | GH")
title = common._get_title(**title_kwargs)
plots.append(title)
# Add china province
china_coastlines = map_set.get_mcoast(name='PROVINCE')
plots.append(china_coastlines)
# final plot
return util.magics_plot(plots, outfile)
def draw_ivt(iqu,
iqv,
lon,
lat,
mslp=None,
skip_vector=None,
map_region=None,
title_kwargs={},
outfile=None):
"""
Draw integrated Water Vapor Transport (IVT) .
Args:
iqu (np.array): u * q transport, 2D array, [nlat, nlon]
iqv (np.array): v * q transport, 2D array, [nlat, nlon]
lon (np.array): longitude, 1D array, [nlon]
lat (np.array): latitude, 1D array, [nlat]
mslp (np.array): mean sea level pressure, 2D array, [nlat, nlon]
skip_vector (integer): skip grid number for vector plot
map_region (list or tuple): the map region limit, [lonmin, lonmax, latmin, latmax]
title_kwargs (dictionaly, optional): keyword arguments for _get_title function.
"""
# check default parameters
if skip_vector is None:
skip_vector = util.get_skip_vector(lon, lat, map_region)
# put data into fields
ivt_field = util.minput_2d_vector(iqu, iqv, lon, lat, skip=skip_vector)
ivt_mag_field = util.minput_2d(np.sqrt(iqu * iqu + iqv * iqv), lon, lat, {
'long_name': 'Integrated Water Vapor Transport',
'units': 'kg/m/s'
})
mslp_field = util.minput_2d(mslp, lon, lat, {
'long_name': 'mean sea level pressure',
'units': 'mb'
})
#
# set up visual parameters
#
plots = []
# Setting the coordinates of the geographical area
if map_region is None:
china_map = map_set.get_mmap(name='CHINA_CYLINDRICAL',
subpage_frame_thickness=5)
else:
china_map = map_set.get_mmap(name='CHINA_REGION_CYLINDRICAL',
map_region=map_region,
subpage_frame_thickness=5)
plots.append(china_map)
# Background Coaslines
coastlines = map_set.get_mcoast(name='COAST_FILL')
plots.append(coastlines)
# Define the shading for the wind speed
ivt_mag_contour = magics.mcont(
legend='on',
contour="off",
contour_level_selection_type="level_list",
contour_level_list=[i * 50.0 + 150 for i in range(3)] +
[i * 100.0 + 300 for i in range(17)],
contour_shade='on',
contour_shade_method='area_fill',
contour_shade_colour_method="list",
contour_shade_colour_list=[
'#fdd6c4', '#fcae92', '#fc8363', '#f6573e', '#de2b25', '#b81419',
'#840711', '#fbb1ba', '#f98cae', '#f25e9f', '#dc3296', '#b40781',
'#890179', '#600070', '#787878', '#8c8c8c', '#a0a0a0', '#b4b4b4',
'#c8c8c8', '#dcdcdc'
],
contour_highlight='off',
contour_hilo='off',
contour_label='off')
plots.extend([ivt_mag_field, ivt_mag_contour])
# Define the wind vector
if ivt_field is not None:
ivt_vector = magics.mwind(legend='off',
wind_field_type='arrows',
wind_arrow_head_shape=1,
wind_arrow_head_ratio=0.5,
wind_arrow_thickness=2,
wind_arrow_unit_velocity=1000.0,
wind_arrow_min_speed=150.0,
wind_arrow_calm_below=150,
wind_arrow_colour='#31043a')
plots.extend([ivt_field, ivt_vector])
# Define the simple contouring for gh
if mslp_field is not None:
interval = check_region_to_contour(map_region, 4, 2, thred=600)
mslp_contour = common._get_mslp_contour(interval=interval)
plots.extend([mslp_field, mslp_contour])
# Add a legend
legend = common._get_legend(
china_map, title="Integrated Water Vapor Transport [kg/m/s]")
plots.append(legend)
# Add the title
title_kwargs = check_kwargs(title_kwargs, 'head',
"Integrated Water Vapor Transport | MSLP")
title = common._get_title(**title_kwargs)
plots.append(title)
# Add china province
china_province_coastlines = map_set.get_mcoast(
name='PROVINCE',
map_user_layer_thickness=2,
map_user_layer_colour='black')
plots.append(china_province_coastlines)
china_river_coastlines = map_set.get_mcoast(
name='RIVER',
map_user_layer_thickness=2,
map_user_layer_colour='#71b2fd')
plots.append(china_river_coastlines)
# final plot
return util.magics_plot(plots, outfile)
def draw_wind_high(uwind,
vwind,
lon,
lat,
gh=None,
skip_vector=None,
map_region=None,
title_kwargs={},
outfile=None):
"""
Draw high wind speed and flags.
Args:
uwind (np.array): u wind component, 2D array, [nlat, nlon]
vwind (np.array): v wind component, 2D array, [nlat, nlon]
lon (np.array): longitude, 1D array, [nlon]
lat (np.array): latitude, 1D array, [nlat]
gh (np.array): geopotential height, 2D array, [nlat, nlon]
skip_vector (integer): skip grid number for vector plot
map_region (list or tuple): the map region limit, [lonmin, lonmax, latmin, latmax]
title_kwargs (dictionaly, optional): keyword arguments for _get_title function.
"""
# check default parameters
if skip_vector is None:
skip_vector = util.get_skip_vector(lon, lat, map_region)
# put data into fields
wind_field = util.minput_2d_vector(uwind,
vwind,
lon,
lat,
skip=skip_vector)
wspeed_field = util.minput_2d(np.sqrt(uwind * uwind + vwind * vwind), lon,
lat, {
'long_name': 'Wind Speed',
'units': 'm/s'
})
if gh is not None:
gh_field = util.minput_2d(gh, lon, lat, {
'long_name': 'height',
'units': 'gpm'
})
#
# set up visual parameters
#
plots = []
# Setting the coordinates of the geographical area
if map_region is None:
china_map = map_set.get_mmap(name='CHINA_CYLINDRICAL',
subpage_frame_thickness=5)
else:
china_map = map_set.get_mmap(name='CHINA_REGION_CYLINDRICAL',
map_region=map_region,
subpage_frame_thickness=5)
plots.append(china_map)
# Background Coaslines
coastlines = map_set.get_mcoast(name='COAST_FILL')
plots.append(coastlines)
# Define the shading for the wind speed
wspeed_contour = magics.mcont(
legend='on',
contour_level_selection_type='interval',
contour_shade_max_level=44.,
contour_shade_min_level=8.,
contour_interval=4.,
contour_shade='on',
contour="off",
contour_shade_method='area_fill',
contour_shade_colour_method='palette',
contour_shade_palette_name='eccharts_rainbow_blue_purple_9',
contour_reference_level=8.,
contour_highlight='off',
contour_hilo='hi',
contour_hilo_format='(F3.0)',
contour_hilo_height=0.6,
contour_hilo_type='number',
contour_hilo_window_size=10,
contour_label='off')
plots.extend([wspeed_field, wspeed_contour])
# Define the wind vector
wind_vector = common._get_wind_flags()
plots.extend([wind_field, wind_vector])
# Define the simple contouring for gh
if gh is not None:
gh_contour = common._get_gh_contour()
plots.extend([gh_field, gh_contour])
# Add a legend
legend = common._get_legend(china_map, title="Wind Speed [m/s]")
plots.append(legend)
# Add the title
title_kwargs = check_kwargs(title_kwargs, 'head',
"850hPa Wind | 500hPa GH")
title = common._get_title(**title_kwargs)
plots.append(title)
# Add china province
china_coastlines = map_set.get_mcoast(name='PROVINCE')
plots.append(china_coastlines)
# final plot
return util.magics_plot(plots, outfile)
def draw_rh_high(uwind,
vwind,
rh,
lon,
lat,
gh=None,
skip_vector=None,
map_region=None,
title_kwargs={},
outfile=None):
"""
Draw high relative humidity.
Args:
uwind (np.array): u wind component, 2D array, [nlat, nlon]
vwind (np.array): v wind component, 2D array, [nlat, nlon]
rh (np.array): relative humidity wind component, 2D array, [nlat, nlon]
lon (np.array): longitude, 1D array, [nlon]
lat (np.array): latitude, 1D array, [nlat]
gh (np.array): geopotential height, 2D array, [nlat, nlon]
skip_vector (integer): skip grid number for vector plot
map_region (list or tuple): the map region limit, [lonmin, lonmax, latmin, latmax]
title_kwargs (dictionaly, optional): keyword arguments for _get_title function.
"""
# check default parameters
if skip_vector is None:
skip_vector = util.get_skip_vector(lon, lat, map_region)
# put data into fields
wind_field = util.minput_2d_vector(uwind,
vwind,
lon,
lat,
skip=skip_vector)
rh_field = util.minput_2d(rh, lon, lat, {
'long_name': 'Relative Humidity',
'units': '%'
})
gh_field = util.minput_2d(gh, lon, lat, {
'long_name': 'height',
'units': 'gpm'
})
#
# set up visual parameters
#
plots = []
# Setting the coordinates of the geographical area
if map_region is None:
china_map = map_set.get_mmap(name='CHINA_CYLINDRICAL',
subpage_frame_thickness=5)
else:
china_map = map_set.get_mmap(name='CHINA_REGION_CYLINDRICAL',
map_region=map_region,
subpage_frame_thickness=5)
plots.append(china_map)
# Background Coaslines
coastlines = map_set.get_mcoast(name='COAST_FILL')
plots.append(coastlines)
# Define the shading for the specific humidity
rh_contour = magics.mcont(legend='on',
contour_level_selection_type='level_list',
contour_level_list=[
0, 1., 5., 10, 20, 30, 40, 50, 60, 65, 70,
75, 80, 85, 90, 99, 100.
],
contour_shade='on',
contour="off",
contour_shade_method='area_fill',
contour_shade_colour_method='list',
contour_shade_colour_list=[
'#644228', '#7f5330', '#9b6238', '#ab754b',
'#b78a60', '#d0b494', '#decab2', '#e0dac8',
'#bdcbab', '#adc59c', '#88bd89', '#6ba48d',
'#506c93', '#4d6393', '#5c5692', '#6b4b92',
'#7a3e94'
],
contour_reference_level=60.,
contour_highlight='off',
contour_hilo='hi',
contour_hilo_format='(F3.0)',
contour_hilo_height=0.6,
contour_hilo_type='number',
contour_hilo_window_size=10,
contour_label='off')
plots.extend([rh_field, rh_contour])
# Define the wind vector
wind_vector = common._get_wind_flags()
plots.extend([wind_field, wind_vector])
# Define the simple contouring for gh
if gh is not None:
gh_contour = common._get_gh_contour()
plots.extend([gh_field, gh_contour])
# Add a legend
legend = common._get_legend(china_map, title="Relative Humidity[%]")
plots.append(legend)
# Add the title
title_kwargs = check_kwargs(title_kwargs, 'head',
"Relative Humidity | Wind | 500hPa GH")
title = common._get_title(**title_kwargs)
plots.append(title)
# Add china province
china_coastlines = map_set.get_mcoast(name='PROVINCE')
plots.append(china_coastlines)
# final plot
return util.magics_plot(plots, outfile)
