def test_plot_Soares(sim_data):
"""
plot Soares profiles
"""
data_to_plot = pls.read_data_avg(sim_data, n_steps=100)
pls.plot_mean(data_to_plot, "Soares_quicklook.pdf")
pls.plot_drafts(data_to_plot, "Soares_quicklook_drafts.pdf")
def test_plot_var_covar_Soares(sim_data):
"""
plot Soares var covar profiles
"""
data_to_plot = pls.read_data_avg(sim_data, n_steps=100, var_covar=True)
pls.plot_var_covar_mean(data_to_plot, "Soares_var_covar_mean.pdf")
pls.plot_var_covar_components(data_to_plot, "Soares_var_covar_comp.pdf")
def test_plot_GATE_III(sim_data):
"""
plot GATE_III profiles
"""
data_to_plot = pls.read_data_avg(sim_data, n_steps=100)
pls.plot_mean(data_to_plot, "GATE_III_quicklook.pdf")
pls.plot_drafts(data_to_plot, "GATE_III_quicklook_drafts.pdf")
def test_plot_Tan2018(sim_data):
"""
plot Tan2018 profiles
"""
data_to_plot = pls.read_data_avg(sim_data, n_steps=100)
pls.plot_mean(data_to_plot, "Tan2018_quicklook.pdf")
pls.plot_drafts(data_to_plot, "Tan2018_quicklook_drafts.pdf")
def test_plot_Rico(sim_data):
"""
plot Rico profiles
"""
data_to_plot = pls.read_data_avg(sim_data, n_steps=100)
pls.plot_mean(data_to_plot, "Rico_quicklook.pdf")
pls.plot_drafts(data_to_plot, "Rico_quicklook_drafts.pdf")
def test_plot_TRMM_LBA(sim_data):
"""
plot TRMM_LBA profiles
"""
data_to_plot = pls.read_data_avg(sim_data, n_steps=100)
pls.plot_mean(data_to_plot, "TRMM_LBA_quicklook.pdf")
pls.plot_drafts(data_to_plot, "TRMM_LBA_quicklook_drafts.pdf")
def test_plot_var_covar_DYCOMS_RF01(sim_data):
"""
plot DYCOMS_RF01 quicklook profiles
"""
data_to_plot = pls.read_data_avg(sim_data, n_steps=100, var_covar=True)
pls.plot_var_covar_mean(data_to_plot, "DYCOMS_RF01_var_covar_mean.pdf")
pls.plot_var_covar_components(data_to_plot, "DYCOMS_RF01_var_covar_components.pdf")
def test_plot_DYCOMS_RF01(sim_data):
"""
plot DYCOMS_RF01 quicklook profiles
"""
data_to_plot = pls.read_data_avg(sim_data, n_steps=100)
pls.plot_mean(data_to_plot, "DYCOMS_RF01_quicklook.pdf")
pls.plot_drafts(data_to_plot, "DYCOMS_RF01_quicklook_drafts.pdf")
def test_plot_var_covar_Bomex(sim_data):
"""
plot Bomex var covar
"""
data_to_plot = pls.read_data_avg(sim_data, n_steps=100, var_covar=True)
pls.plot_var_covar_mean(data_to_plot, "Bomex_var_covar_mean.pdf")
pls.plot_var_covar_components(data_to_plot, "Bomex_var_covar_components.pdf")
def test_plot_Bomex(sim_data):
"""
plot Bomex profiles
"""
data_to_plot = pls.read_data_avg(sim_data, n_steps=100)
pls.plot_mean(data_to_plot, "Bomex_quicklook.pdf")
pls.plot_drafts(data_to_plot, "Bomex_quicklook_drafts.pdf")
def test_plot_var_covar_GATE_III(sim_data):
"""
plot GATE III var covar
"""
data_to_plot = pls.read_data_avg(sim_data, n_steps=100, var_covar=True)
pls.plot_var_covar_mean(data_to_plot, "GATE_III_var_covar_mean.pdf")
pls.plot_var_covar_components(data_to_plot,
"GATE_III_var_covar_components.pdf")
def test_plot_var_covar_Tan2018(sim_data):
"""
plot Tan2018 var covar
"""
data_to_plot = pls.read_data_avg(sim_data, n_steps=100, var_covar=True)
pls.plot_var_covar_mean(data_to_plot, "Tan2018_var_covar_mean.pdf")
pls.plot_var_covar_components(data_to_plot,
"Tan2018_var_covar_components.pdf")
def test_plot_var_covar_Rico(sim_data):
"""
plot Rico variance and covariance of H and QT profiles
"""
data_to_plot = pls.read_data_avg(sim_data, n_steps=100, var_covar=True)
pls.plot_var_covar_mean(data_to_plot, "Rico_var_covar_mean.pdf")
pls.plot_var_covar_components(data_to_plot,
"Rico_var_covar_components.pdf")
def test_plot_var_covar_TRMM_LBA(sim_data):
"""
plot TRMM LBA var covar
"""
data_to_plot = pls.read_data_avg(sim_data, n_steps=100, var_covar=True)
pls.plot_var_covar_mean(data_to_plot, "TRMM_LBA_var_covar_mean.pdf")
pls.plot_var_covar_components(data_to_plot,
"TRMM_LBA_var_covar_components.pdf")
def test_DYCOMS_RF01_radiation(sim_data):
"""
plots DYCOMS_RF01
"""
import matplotlib as mpl
mpl.use('Agg') # Must be before importing matplotlib.pyplot or pylab!
import matplotlib.pyplot as plt
fig = plt.figure(1)
fig.set_figheight(12)
fig.set_figwidth(14)
mpl.rcParams.update({'font.size': 18})
mpl.rc('lines', linewidth=4, markersize=10)
plt_data = pls.read_data_avg(sim_data, n_steps=100, var_covar=False)
rad_data = pls.read_rad_data_avg(sim_data, n_steps=100)
plots = []
# loop over simulation and reference data for t=0 and t=-1
x_lab = ['longwave radiative flux [W/m2]', 'dTdt [K/day]', 'QT [g/kg]', 'QL [g/kg]']
legend = ["lower right", "lower left", "lower left", "lower right"]
line = ['--', '--', '-', '-']
plot_y = [rad_data["rad_flux"], rad_data["rad_dTdt"], plt_data["qt_mean"], plt_data["ql_mean"]]
plot_x = [rad_data["z"], plt_data["z_half"], plt_data["z_half"], plt_data["z_half"]]
color = ["palegreen", "forestgreen"]
label = ["ini", "end" ]
for plot_it in range(4):
plots.append(plt.subplot(2,2,plot_it+1))
#(rows, columns, number)
for it in range(2):
plots[plot_it].plot(plot_y[plot_it][it], plot_x[plot_it], '.-', color=color[it], label=label[it])
plots[plot_it].legend(loc=legend[plot_it])
plots[plot_it].set_xlabel(x_lab[plot_it])
plots[plot_it].set_ylabel('z [m]')
plots[2].set_xlim([1, 10])
plots[3].set_xlim([-0.1, 0.5])
plt.savefig("plots/output/DYCOMS_RF01_radiation.pdf")
plt.clf()
