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)
df_fit = dEXP.fit_ridges(df_f, rmvOutliers=True) # fit ridges on filtered data
# pEXP.plot_ridges_sources(df_fit, ax=ax, z_max_source=-max_elevation*1.2,
# ridge_type=[0,1,2],ridge_nb=None)
pEXP.plot_ridges_sources(df_fit,
ax=ax,
z_max_source=-6000,
ridge_type=[0, 1, 2],
ridge_nb=None)
square([x1, x2, -z1, -z2])
plt.annotate(dens, [(x1 + x2) / 2, -(z1 + z2) / 2])
#%%
# ridges analysis
z0 = -2000
#%% ------------------------------- 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)