#%%
# Plot ridges over continuated section
# fig = plt.figure()
# ax = plt.gca()
# pEXP.plot_xy(mesh, label=label_prop, ax=ax) #, ldg=)
# pEXP.plot_ridges_harmonic(dfI,dfII,dfIII,ax=ax)
#%%
# Filter ridges (regionally constrainsted)
dfI_f, dfII_f, dfIII_f = dEXP.filter_ridges(dfI,
dfII,
dfIII,
minDepth=minAlt_ridge,
maxDepth=maxAlt_ridge,
minlength=3,
rmvNaN=True)
df_f = dfI_f, dfII_f, dfIII_f
#%%
# plot ridges fitted over continuated section
# fig = plt.figure()
# ax = plt.gca()
# pEXP.plot_xy(mesh, label=label_prop, ax=ax) #, ldg=)
# pEXP.plot_ridges_harmonic(dfI_f,dfII_f,dfIII_f,ax=ax,label=True)
df_fit = dEXP.fit_ridges(df_f,
#%%
# Plot ridges over continuated section
fig = plt.figure()
ax = plt.gca()
pEXP.plot_xy(mesh, label=label_prop, ax=ax, Xaxis=x_axis)
pEXP.plot_ridges_harmonic(dfI, dfII, dfIII, ax=ax)
#%%
# Filter ridges regionally constrainsted)
dfI_f, dfII_f, dfIII_f = dEXP.filter_ridges(dfI,
dfII,
dfIII,
minDepth=1000,
maxDepth=3000,
minlength=3,
rmvNaN=True)
df_f = dfI_f, dfII_f, dfIII_f
# df_f = dfI, dfII, dfIII
#%%
# Plot ridges fitted over continuated section
fig = plt.figure()
ax = plt.gca()
pEXP.plot_xy(mesh, label=label_prop, ax=ax) #, ldg=)
pEXP.plot_ridges_harmonic(dfI_f, dfII_f, dfIII_f, ax=ax, label=True)
#%%
# Plot ridges over continuated section
fig = plt.figure()
ax = plt.gca()
pEXP.plot_xy(mesh, label=label_prop, ax=ax, Xaxis=x_axis)
pEXP.plot_ridges_harmonic(dfI, dfII, dfIII, ax=ax)
#%%
# Filter ridges regionally constrainsted)
D_f = dEXP.filter_ridges(dfI,
dfII,
dfIII,
minDepth=1000,
maxDepth=3000,
minlength=3,
rmvNaN=True,
heights=[hI, hII, hIII])
dfI_f, dfII_f, dfIII_f = D_f[0:3]
hI_f, hII_f, hIII_f = D_f[3:6]
df_f = D_f[0:3]
#%%
# Plot ridges fitted over continuated section
fig = plt.figure()
ax = plt.gca()
pEXP.plot_xy(mesh, label=label_prop, ax=ax) #, ldg=)
#%%
# filter ridges using a minimum length criterium and and filter for a specific range of altitude
# a =2.25
# if x_axis=='y':
# xf_min = a*x1
# xf_max = a*x2
# else:
# xf_min = a*y1
# xf_max = a*y2
D_f = dEXP.filter_ridges(dfI,
dfII,
dfIII,
minDepth=500,
maxDepth=5000,
minlength=8,
rmvNaN=True,
xmin=1000,
xmax=19000,
heights=[hI, hII, hIII])
dfI_f, dfII_f, dfIII_f = D_f[0:3]
hI_f, hII_f, hIII_f = D_f[3:6]
df_f = D_f[0:3]
#%%
# plot filtered ridges fitted over continuated section
fig = plt.figure()
ax = plt.gca()
label=label_prop,
method_peak='find_peaks')
#%% ------------------------------- plot ridges over continuated section
fig = plt.figure()
ax = plt.gca()
pEXP.plot_xy(mesh, label=label_prop, ax=ax) #, ldg=)
pEXP.plot_ridges_harmonic(dfI,dfII,dfIII,ax=ax)
#%% ------------------------------- filter ridges regionally constrainsted)
dfI_f,dfII_f, dfIII_f = dEXP.filter_ridges(dfI,dfII,dfIII,
1,maxAlt_ridge,
minlength=8,rmvNaN=True)
df_f = dfI_f, dfII_f, dfIII_f
#%% ------------------------------- plot ridges fitted over continuated section
fig = plt.figure()
ax = plt.gca()
pEXP.plot_xy(mesh, label=label_prop, ax=ax) #, ldg=)
pEXP.plot_ridges_harmonic(dfI_f,dfII_f,dfIII_f,ax=ax,label=True)
df_fit = dEXP.fit_ridges(df_f) # fit ridges on filtered data
pEXP.plot_ridges_sources(df_fit, ax=ax, z_max_source=-max_elevation*2,
ridge_type=[0,1,2],ridge_nb=None)
#%%
# Plot ridges over continuated section
# fig = plt.figure()
# ax = plt.gca()
# pEXP.plot_xy(mesh, label=label_prop, ax=ax) #, ldg=)
# pEXP.plot_ridges_harmonic(dfI,dfII,dfIII,ax=ax)
#%%
# Filter ridges (regionally constrainsted)
dfI_f, dfII_f, dfIII_f = dEXP.filter_ridges(dfI,
dfII,
dfIII,
minDepth=minAlt_ridge,
maxDepth=maxAlt_ridge,
minlength=7,
rmvNaN=True,
xmin=100,
xmax=300)
df_f = dfI_f, dfII_f, dfIII_f
# dfI_f,dfII_f, dfIII_f = dEXP.filter_ridges(dfI,dfII,dfIII,
# minDepth=minAlt_ridge,maxDepth=maxAlt_ridge,
# minlength=7,rmvNaN=True)
# df_f = dfI_f, dfII_f, dfIII_f
# k=['EX_xpos1', 'EX_xpos2', 'EX_xpos3', 'EX_xpos4']
# minx = xmin
# dfI.columns[1:]
# import numpy as np
Vminmax=[0, 0.35],
p1p2=p)
cbar = plt.colorbar(cmap, shrink=0.25, pad=0.04)
cbar.set_label('upwc voltage (V)')
plt.tight_layout()
pEXP.plot_ridges_harmonic(dfI, dfII, dfIII, ax=ax)
plt.xlim([200, 600])
plt.savefig('ridges_raw_' + str(file) + '.png', dpi=450)
#%% ------------------------------- filter ridges regionally constrainsted)
dfI_f, dfII_f, dfIII_f = dEXP.filter_ridges(dfI,
dfII,
dfIII,
minDepth=minAlt_ridge,
maxDepth=maxAlt_ridge,
minlength=5,
rmvNaN=True,
xmin=100,
xmax=700,
Xaxis=x_axis)
df_f = dfI_f, dfII_f, dfIII_f
#%% ------------------------------- plot ridges fitted over continuated section
fig = plt.figure()
ax = plt.gca()
plt, cmap = pEXP.plot_xy(mesh,
label=label_prop,
ax=ax,
fig = plt.figure()
ax = plt.gca()
pEXP.plot_xy(mesh, label=label_prop, ax=ax, Xaxis=x_axis)
pEXP.plot_ridges_harmonic(dfI, dfII, dfIII, ax=ax)
#%% ------------------------------- filter ridges regionally constrainsted)
# dfI_f,dfII_f, dfIII_f = dEXP.filter_ridges(dfI,dfII,dfIII,
# minAlt_ridge,maxAlt_ridge,
# minlength=5,rmvNaN=True)
dfI_f, dfII_f, dfIII_f = dEXP.filter_ridges(dfI,
dfII,
dfIII,
minAlt_ridge,
maxAlt_ridge,
minlength=8,
rmvNaN=True,
xmin=150,
xmax=450,
Xaxis=x_axis)
# dfI_f,dfII_f, dfIII_f = dEXP.filter_ridges(dfI,dfII,dfIII,
# minAlt_ridge,maxAlt_ridge,
# minlength=5,rmvNaN=True,
# xmin=284200)
df_f = dfI_f, dfII_f, dfIII_f
#%% ------------------------------- plot ridges fitted over continuated section
fig = plt.figure()
#%%
# filter ridges using a minimum length criterium and and filter for a specific range of altitude
a = 2.25
if x_axis == 'y':
xf_min = a * x1
xf_max = a * x2
else:
xf_min = -5800
xf_max = a * x2
D_f = dEXP.filter_ridges(dfI,
dfII,
dfIII,
minDepth=200,
maxDepth=2000,
minlength=8,
rmvNaN=True,
xmin=xf_min,
xmax=xf_max,
heights=[hI, hII, hIII])
D_f = D
dfI_f, dfII_f, dfIII_f = D_f[0:3]
hI_f, hII_f, hIII_f = D_f[3:6]
df_f = D_f[0:3]
#%%
# plot filtered ridges fitted over continuated section
fig = plt.figure()
ax = plt.gca()