def plot_ilag(en, lag, ilag, lagS=None, ilagS=None, figsize=None):
"""plot the results of lag_en_pipeline, with simulations if given"""
doindv = False
try:
_,nindv,_,nfq = ilag.shape
doindv = True
except:
nfq, nindv = lag.shape[-1], 1
if figsize is None: figsize=(14,3*nfq)
fig = plt.figure(figsize=figsize)
for ifq in range(nfq):
if not lagS is None:
lm, ls = lagS[:,:,1,ifq].mean(0), lagS[:,:,1,ifq].std(0)
for il in range(nindv):
if nindv < 10:
ax = plt.subplot(nfq, nindv, il+ifq*nfq+1)
else:
ax = plt.subplot(nfq*2, nindv//2+1, il+ifq*nfq+1)
ax.set_xscale('log')
ax.set_ylim([-2,2])
ax.set_xticks([3,6])
ax.xaxis.set_major_formatter(plt.ScalarFormatter())
ax.xaxis.set_minor_formatter(plt.NullFormatter())
ax.errorbar(en, lag[:,1,ifq]/1e3, lag[:,2,ifq]/1e3, fmt='o-', alpha=0.5)
if doindv:
ax.errorbar(en, ilag[:,il,1,ifq]/1e3, ilag[:,il,2,ifq]/1e3, fmt='s-')
# simulations #
if not lagS is None:
ax.fill_between(en, (lm-ls)/1e3, (lm+ls)/1e3, alpha=0.3)
if doindv:
ilm, ils = ilagS[:,:,il,1,ifq].mean(0), ilagS[:,:,il,1,ifq].std(0)
ax.fill_between(en, (ilm-ils)/1e3, (ilm+ils)/1e3, alpha=0.3)
plt.tight_layout(pad=0)
imshow_grid(mgrid, iz-mz, vmin=-120, vmax=120, cmap='RdBu_r')
# slope
plt.sca(axarr[2,0])
plt.text(0.2, 0.9, 'Slope', color='w', ha='center', va='center', transform=axarr[2,0].transAxes)
imshow_grid(grid, grid['node']['topographic__steepest_slope'], vmin=0, vmax=1.2, cmap='plasma_r')
plt.sca(axarr[2,1])
imshow_grid(mgrid, mgrid['node']['topographic__steepest_slope'], vmin=0, vmax=1.2, cmap='plasma_r')
for ni in range(2):
for nj in range(3):
axarr[nj,ni].set_aspect('equal')
axarr[nj,ni].set_xlabel('')
axarr[nj,ni].set_ylabel('')
axarr[nj,ni].xaxis.set_major_formatter(plt.NullFormatter())
axarr[nj,ni].yaxis.set_major_formatter(plt.NullFormatter())
plt.tight_layout()
plt.savefig(os.path.join('comparison_figures', model + '.png'), dpi=300)
#plt.savefig(os.path.join('comparison_figures', model + '.pdf')) # pdfs take about 3 minutes to render and 10
df = pd.DataFrame(outputs).T
output_filepath = ['work', 'WVDP_EWG_STUDY3', 'study3py', 'result_tables', 'calibration', 'sew', 'sew.calibration.summary.csv']
df.to_csv(os.path.join(os.sep, *output_filepath), float_format='%.3e')
#%%
cat_df = pd.DataFrame(cat_diff).T
cat_of = np.sum(np.square(cat_df), axis=1)
#%%
def AXIS(axis,
xlabel=None,
ylabel=None,
remove_xticks=False,
remove_yticks=False,
remove_ticks_all=False,
tickscolor="k"):
plt.setp(axis.get_yticklabels(), rotation='vertical',
fontsize=10) #,visible=False)
plt.setp(axis.get_xticklabels(), fontsize=10)
axis.spines['bottom'].set_color(tickscolor)
axis.spines['top'].set_color(tickscolor)
axis.spines['left'].set_color(tickscolor)
axis.spines['right'].set_color(tickscolor)
axis.minorticks_on()
axis.tick_params('both',
length=6.5,
width=0.7,
which='major',
direction='in',
color=tickscolor,
bottom=1,
top=1,
left=1,
right=1)
axis.tick_params('both',
length=3.5,
width=0.7,
which='minor',
direction='in',
color=tickscolor,
bottom=1,
top=1,
left=1,
right=1)
axis.tick_params(axis='x', colors='k', pad=1)
axis.tick_params(axis='y', colors='k', pad=1)
axis.tick_params(axis='both', direction='in', color=tickscolor)
axis.xaxis.major.locator.set_params(nbins=3)
axis.yaxis.major.locator.set_params(nbins=3)
if xlabel != None:
axis.set_xlabel('%s' % ylabel, fontsize=10)
if ylabel != None:
axis.set_xlabel('%s' % xlabel, fontsize=10)
#
# Remove x,y label ticks
#
if remove_xticks == True:
axis.xaxis.set_major_formatter(plt.NullFormatter())
if remove_yticks == True:
axis.yaxis.set_major_formatter(plt.NullFormatter())
# remove all from the axis (both ticks and xy ticks labels)
if remove_ticks_all == True:
axis.yaxis.set_major_locator(plt.NullLocator())
axis.xaxis.set_major_locator(plt.NullLocator())
axis.set_facecolor('#e8ebf2')
for p in range(0, 16):
gs = gridspec.GridSpec(6, 1)
res_dir = database_dir + '/' + d # e.g. /raid8/srvx1/federico/odb_netCDF/$New_Results/1759/
res_name = os.listdir(res_dir)[0].replace('u.nc', '').replace(
'v.nc', '').replace('t.nc', '')
ax0 = plt.subplot(gs[0])
netCDF_file = netCDF(database_dir, d, res_name, hour=h, plevel=p)
netCDF_file.load()
Plot = Plotter(netCDF_file, var='temp')
Plot.plotter(out_dir=out_dir, save=False, xlabel=False)
plt.tight_layout()
ax0.xaxis.set_major_formatter(plt.NullFormatter())
ax1 = plt.subplot(gs[1])
netCDF_file.load()
Plot = Plotter(netCDF_file, var='uwind')
Plot.plotter(out_dir=out_dir, save=False, xlabel=False)
plt.tight_layout()
ax1.xaxis.set_major_formatter(plt.NullFormatter())
ax2 = plt.subplot(gs[2])
netCDF_file.load()
Plot = Plotter(netCDF_file, var='vwind')
Plot.plotter(out_dir=out_dir, save=False, xlabel=False)
plt.tight_layout()
ax2.xaxis.set_major_formatter(plt.NullFormatter())