Datagrid Slices¶
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import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import LinearLocator
from mpl_toolkits.mplot3d import axes3d
import s3dlib.surface as s3d
#.. Datagrid surface and xySlice line set plot
# 1. Define function to examine .....................................
z=np.load('data/jacksboro_fault_dem.npz')['elevation']
datagrid = np.flip( z[5:50, 5:50], 0 )
# 2. Setup and map surfaces .........................................
rez=6
line = s3d.ParametricLine(rez, cmap='gist_earth', name='jacksboro_fault_dem')
line.map_xySlice_from_datagrid(datagrid, yset=50,xset=2).shade(0.7)
# 3. Construct figure, add surface, plot ............................
fig = plt.figure()
ax = plt.axes(projection='3d')
fig.text(0.975,0.975,str(line), ha='right', va='top', fontsize='smaller')
fig.text(0.025,0.025,line.cname, ha='left', va='bottom', fontsize='smaller')
ax.set_title( line.name )
ax.set(xlim=(-1,1), ylim=(-1,1), zlim=(0,1) )
ax.xaxis.set_major_locator(LinearLocator(5))
ax.yaxis.set_major_locator(LinearLocator(5))
ax.zaxis.set_major_locator(LinearLocator(5))
ax.add_collection3d(line)
plt.show()
Vertical Colorization¶
The referenced matplotlib example uses a cmap applied to the vertical location of the surface. This can also be easily constructed similar to Vertical Colorization of the surface with the resulting plot shown below.
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import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import LinearLocator
from mpl_toolkits.mplot3d import axes3d
import s3dlib.surface as s3d
#.. Datagrid xySlice line set plot
# 1. Define function to examine .....................................
with np.load('data/jacksboro_fault_dem.npz') as dem :
z = dem['elevation']
nrows, ncols = z.shape
x = np.linspace(dem['xmin'], dem['xmax'], ncols)
y = np.linspace(dem['ymin'], dem['ymax'], nrows)
x, y = np.meshgrid(x, y)
region = np.s_[5:50, 5:50]
x, y, z = x[region], y[region], z[region]
datagrid = np.flip(z,0)
# 2. Setup and map surfaces .........................................
rez=6
line = s3d.ParametricLine(rez, cmap='gist_earth', name='jacksboro_fault_dem')
line.map_xySlice_from_datagrid(datagrid, yset=50,xset=2)
line.map_cmap_from_op(lambda xyz: xyz[2], cname='elevation').shade(0.7)
line.scale_dataframe(x,y,datagrid)
# 3. Construct figure, add surface, plot ............................
fig = plt.figure()
ax = plt.axes(projection='3d')
fig.text(0.975,0.975,str(line), ha='right', va='top', fontsize='smaller')
fig.text(0.025,0.025,line.cname, ha='left', va='bottom', fontsize='smaller')
ax.set_title( line.name )
ax.set(xlim=(-84.415,-84.375), ylim=(36.690,36.740), zlim=(350,700) )
ax.xaxis.set_major_locator(LinearLocator(5))
ax.yaxis.set_major_locator(LinearLocator(6))
ax.zaxis.set_major_locator(LinearLocator(8))
ax.set_xlabel('X axis')
ax.set_ylabel('Y axis')
ax.add_collection3d(line)
plt.show()