#%%
# 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
points, fit, SI, EXTnb = dEXP.scalFUN(dfI_f, EXTnb=[1], z0=z0)
pEXP.plot_scalFUN(points, fit, z0=z0)
# z0 = -2000
# points, fit, SI, EXTnb = dEXP.scalFUN(dfI_f,EXTnb=[3],z0=z0)
# pEXP.plot_scalFUN(points, fit, z0=z0)
#%% ------------------------------- 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)
DF_F.append(df_f)
DF_FIT.append(df_fit)
XXZZ.append(xxzz)
CTm.append(CT)
#%%
plt.figure()
ax = plt.gca()
i = 0
pEXP.plot_xy(MESH[i], label=LABEL[i], ax=ax) #, ldg=)
dfI_f, dfII_f, dfIII_f = DF_F[i]
pEXP.plot_ridges_harmonic(dfI_f, dfII_f, dfIII_f, ax=ax, label=False)
pEXP.plot_ridges_sources(DF_FIT[i],
ax=ax,
z_max_source=-max_elevation * 1.2,
ridge_type=[0, 1, 2],
ridge_nb=None)
x1, x2, z1, z2 = XXZZ[i]
square([x1, x2, z1, z2])
plt.annotate(CTm[i], [(x1 + x2) / 2, (z1 + z2) / 2])
plt.figure()
ax = plt.gca()
i = 1
pEXP.plot_xy(MESH[i], label=LABEL[i], ax=ax) #, ldg=)
dfI_f, dfII_f, dfIII_f = DF_F[i]
pEXP.plot_ridges_harmonic(dfI_f, dfII_f, dfIII_f, ax=ax, label=False)
pEXP.plot_ridges_sources(DF_FIT[i],
ax=ax,
# pEXP.plot_xy(mesh, label=label_prop, ax=ax) #, ldg=)
# pEXP.slice_mesh(xp, yp, mesh, label_prop, p1, p2,
# interp=True, ax=ax, Xaxis='y')
pEXP.plot_xy(mesh, label=label_prop, Xaxis=x_axis, p1p2=p, 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*2,
# ridge_type=[0,1,2],ridge_nb=None)
pEXP.plot_ridges_sources(df_fit,
ax=ax,
z_max_source=-max_elevation * 2,
ridge_type=[0, 1, 2],
ridge_nb=None,
xmin=5.036e6 + 50,
xmax=5.036e6 + 400)
#%% DEXP ratio
qratio = [1, 0]
mesh_dexp, label_dexp = dEXP.dEXP_ratio(xp,
yp,
zp,
U,
shape,
zmin=0,
zmax=max_elevation,
nlayers=nlay,
