simpeg.utils.model_builder.create_random_model#
- simpeg.utils.model_builder.create_random_model(shape, random_seed=1000, anisotropy=None, its=100, bounds=None, **kwargs)[source]#
Create random model by convolving a kernel with a uniformly distributed random model.
- Parameters:
- shape
int
ortuple
of
int
Shape of the model. Can define a vector of size (n_cells) or define the dimensions of a tensor.
- random_seed
None
orRandomSeed
,optional
Random seed for random uniform model that is convolved with the kernel. It can either be an int, a predefined Numpy random number generator, or any valid input to
numpy.random.default_rng
.- anisotropy
numpy.ndarray
this is the (3, n) blurring kernel that is used.
- its
int
Number of smoothing iterations after convolutions
- bounds
list
of
float
Lower and upper bound for the model values
- seed
None
orRandomSeed
,optional
Deprecated since version 0.23.0: Argument
seed
is deprecated in favor ofrandom_seed
and will be removed in SimPEG v0.24.0.
- shape
- Returns:
numpy.ndarray
Physical property model
Examples
>>> import matplotlib.pyplot as plt >>> from simpeg.utils.model_builder import create_random_model >>> m = create_random_model((50,50), bounds=[-4,0]) >>> plt.colorbar(plt.imshow(m)) >>> plt.title('A very cool, yet completely random model.') >>> plt.show()
(
Source code
,png
,pdf
)
Galleries and Tutorials using simpeg.utils.model_builder.create_random_model
#
Maps: Mesh2Mesh