# https://github.com/cgre-aachen/gempy/blob/master/notebooks/tutorials/ch1-3-Grids.ipynb) # # %% geo_model.set_centered_grid(xy_ravel, resolution=[10, 10, 15], radius=5000) # %% geo_model.grid.centered_grid.kernel_centers # %% # Now we need to compute the component tz (see # https://github.com/cgre-achen/gempy/blob/master/notebooks/tutorials/ch2-2-Cell_selection.ipynb) # # %% g = GravityPreprocessing(geo_model.grid.centered_grid) # %% tz = g.set_tz_kernel() # %% tz # %% # Compiling the gravity graph # ~~~~~~~~~~~~~~~~~~~~~~~~~~~ # # If geo_model has already a centered grid, the calculation of tz happens # automatically. This theano graph will return gravity # as well as the lithologies. In addition we need either to pass the density # block (see below). Or the position of density on the surface(in the
# %%
# Importing gempy
from gempy.assets.geophysics import GravityPreprocessing
# Aux imports
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
np.random.seed(1515)
pd.set_option('precision', 2)
# %%
g = GravityPreprocessing()
# %%
kernel_centers, kernel_dxyz_left, kernel_dxyz_right = g.create_irregular_grid_kernel(
resolution=[10, 10, 20], radius=100)
# %%
# ``create_irregular_grid_kernel`` will create a constant kernel around
# the point 0,0,0. This kernel will be what we use for each device.
#
# %%
kernel_centers
# %%
# :math:`t_z` is only dependent on distance and therefore we can use the
def calculate_tz(self, centered_grid):
from gempy.assets.geophysics import GravityPreprocessing
g = GravityPreprocessing(centered_grid)
return g.set_tz_kernel()