def test_skewt_shade_area_kwargs(test_profile):
"""Test shading areas on a SkewT plot with kwargs."""
p, t, tp = test_profile
fig = plt.figure(figsize=(9, 9))
skew = SkewT(fig)
skew.plot(p, t, 'r')
skew.plot(p, tp, 'k')
skew.shade_area(p, t, tp, facecolor='m')
return fig
def test_skewt_shade_area_invalid(test_profile):
"""Test shading areas on a SkewT plot."""
p, t, tp = test_profile
fig = plt.figure(figsize=(9, 9))
skew = SkewT(fig)
skew.plot(p, t, 'r')
skew.plot(p, tp, 'k')
with pytest.raises(ValueError):
skew.shade_area(p, t, tp, which='positve')
def test_skewt_shade_area(test_profile):
"""Test shading areas on a SkewT plot."""
p, t, tp = test_profile
fig = plt.figure(figsize=(9, 9))
skew = SkewT(fig)
skew.plot(p, t, 'r')
skew.plot(p, tp, 'k')
skew.shade_area(p, t, tp)
return fig
def test_skewt_shade_area_invalid(test_profile):
"""Test shading areas on a SkewT plot."""
p, t, tp = test_profile
fig = plt.figure(figsize=(9, 9))
skew = SkewT(fig)
skew.plot(p, t, 'r')
skew.plot(p, tp, 'k')
with pytest.raises(ValueError):
skew.shade_area(p, t, tp, which='positve')
def test_skewt_shade_area(test_profile):
"""Test shading areas on a SkewT plot."""
p, t, tp = test_profile
fig = plt.figure(figsize=(9, 9))
skew = SkewT(fig)
skew.plot(p, t, 'r')
skew.plot(p, tp, 'k')
skew.shade_area(p, t, tp)
skew.ax.set_xlim(-50, 50)
return fig
def test_skewt_shade_area_kwargs(test_profile):
"""Test shading areas on a SkewT plot with kwargs."""
p, t, tp = test_profile
with matplotlib.rc_context({'axes.autolimit_mode': 'data'}):
fig = plt.figure(figsize=(9, 9))
skew = SkewT(fig)
skew.plot(p, t, 'r')
skew.plot(p, tp, 'k')
skew.shade_area(p, t, tp, facecolor='m')
skew.ax.set_xlim(-50, 50)
return fig
def test_skewt_shade_area_kwargs(test_profile):
"""Test shading areas on a SkewT plot with kwargs."""
p, t, tp = test_profile
with matplotlib.rc_context({'axes.autolimit_mode': 'data'}):
fig = plt.figure(figsize=(9, 9))
skew = SkewT(fig)
skew.plot(p, t, 'r')
skew.plot(p, tp, 'k')
skew.shade_area(p, t, tp, facecolor='m')
skew.ax.set_xlim(-50, 50)
return fig
def test_skewt_shade_area(test_profile):
"""Test shading areas on a SkewT plot."""
p, t, tp = test_profile
with matplotlib.rc_context({'axes.autolimit_mode': 'data'}):
fig = plt.figure(figsize=(9, 9))
skew = SkewT(fig, aspect='auto')
skew.plot(p, t, 'r')
skew.plot(p, tp, 'k')
skew.shade_area(p, t, tp)
skew.ax.set_xlim(-50, 50)
skew.ax.set_ylim(1000, 100)
return fig
def test_skewt_shade_area_kwargs(test_profile):
"""Test shading areas on a SkewT plot with kwargs."""
p, t, _, tp = test_profile
with matplotlib.rc_context({'axes.autolimit_mode': 'data'}):
fig = plt.figure(figsize=(9, 9))
skew = SkewT(fig, aspect='auto')
skew.plot(p, t, 'r')
skew.plot(p, tp, 'k')
skew.shade_area(p, t, tp, facecolor='m')
skew.ax.set_xlim(-50, 50)
skew.ax.set_ylim(1000, 100)
# This works around the fact that newer pint versions default to degrees_Celsius
skew.ax.set_xlabel('degC')
return fig
# automatically added
fig = plt.figure(figsize=(9, 9))
# The rotation keyword changes how skewed the temperature lines are. MetPy has
# a default skew of 30 degrees
skew = SkewT(fig, rotation=45)
ax = skew.ax
# Shade every other section between isotherms
x1 = np.linspace(-100, 40, 8) # The starting x values for the shaded regions
x2 = np.linspace(-90, 50, 8) # The ending x values for the shaded regions
y = [1050, 100] # The range of y values that the shades regions should cover
for i in range(0, 8):
skew.shade_area(y=y,
x1=x1[i],
x2=x2[i],
color='limegreen',
alpha=0.25,
zorder=1)
# Choose starting temperatures in Kelvin for the dry adiabats
t0 = units.K * np.arange(243.15, 444.15, 10)
skew.plot_dry_adiabats(t0=t0, linestyles='solid', colors='tan', linewidths=1.5)
# Choose starting temperatures in Kelvin for the moist adiabats
t0 = units.K * np.arange(281.15, 306.15, 4)
skew.plot_moist_adiabats(t0=t0,
linestyles='solid',
colors='lime',
linewidth=1.5)
# Choose mixing ratios
def core_ens(p, T, Td, u, v, p2, T2, Td2, **kwargs):
#from IPython import embed; embed()
T = T.to(units.K)
Td = Td.to(units.K)
Tmean = T.mean(axis=0)
Tdmean = Td.mean(axis=0)
pmean = p.mean(axis=0)
umean, vmean = u.mean(axis=0), v.mean(axis=0)
Tstd = np.std(T.data, axis=0) * units.K
Tdstd = np.std(Td.data, axis=0) * units.K
# Calculate the parcel profile.
parcel_prof = mpcalc.parcel_profile(pmean, Tmean[0], Tdmean[0]).to('degC')
# Create a new figure. The dimensions here give a good aspect ratio
fig = plt.figure(figsize=(8, 8))
skew = SkewT(fig, rotation=45)
# Plot a zero degree isotherm
skew.ax.axvline(0, color='k', linestyle='--', linewidth=1)
# Add the relevant special lines
skew.plot_dry_adiabats(lw=.5)
skew.plot_moist_adiabats(lw=.5)
skew.plot_mixing_lines(lw=.5)
# Plot the data using normal plotting functions, in this case using
# log scaling in Y, as dictated by the typical meteorological plot
skew.shade_area(pmean,
Tmean - Tstd,
Tmean + Tstd,
color='r',
label='std$_{ens}$ mean$_{dom}$ T$_{fc}$')
skew.shade_area(pmean,
Tdmean - Tdstd,
Tdmean + Tdstd,
color='g',
label='std$_{ens}$ mean$_{dom}$ Td$_{fc}$')
#skew.plot(p, Tmean+np.std(T), '-', color='grey', lw=1, label='p.999(T)')
skew.plot(pmean,
Tmean,
'r:',
ms=3,
lw=1,
label='mean$_{ens, dom}$ T$_{fc}$')
skew.plot(pmean,
Tdmean,
'g:',
ms=3,
lw=1,
label='mean$_{ens, dom}$ Td$_{fc}$')
skew.plot_barbs(pmean, umean, vmean)
# Plot the parcel profile as a black line
skew.plot(pmean, parcel_prof, 'k', linewidth=.5)
# Shade areas of CAPE and CIN
skew.shade_cin(pmean, Tmean, parcel_prof, alpha=0.2)
skew.shade_cape(pmean, Tmean, parcel_prof, alpha=0.2)
# nature
skew.plot(p2,
T2,
'r.-',
ms=5,
lw=2,
label='mean$_{ens, dom}$ T$_{nature}$')
skew.plot(p2,
Td2,
'g.-',
ms=5,
lw=2,
label='mean$_{ens, dom}$ Td$_{nature}$')
skew.ax.set_ylim(1000, 180)
skew.ax.set_xlim(-20, 40)
plt.legend(loc='lower left')
plt.title(kwargs.get('title'))
fname = kwargs.get('saveto', 'profile.png')
fig.savefig(fname)
print(fname, 'saved.')
plt.close()
