Created by Mauro Alberti
Last run: 2019-06-16
In [1]:
import numpy as np
In [2]:
a= np.array([[1, 2, 3, 4], [4, 6, 8, 10], [9, 11, 13, 15]])
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a
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In [4]:
np.gradient(a, axis=0) # along y axis
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np.gradient(a, axis=1) # along x axis
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In [6]:
from math import pi
from numpy import array
In [7]:
from pygsf.spatial.rasters.fields import *
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fld1 = array([
[1, 1, 1, 1],
[1, 1, 1, 1],
[1, 1, 1, 1]])
In [9]:
grad_j(fld1, cell_size_j=10)
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grad_i(fld1, cell_size_i=10)
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In [11]:
fld2 = array([
[10, 10, 10, 10],
[20, 20, 20, 20],
[30, 30, 30, 30]])
In [12]:
grad_j(fld2, cell_size_j=10)
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In [13]:
grad_i(fld2, cell_size_i=10)
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In [14]:
dir_deriv(fld2, cell_size_x=10, cell_size_y=10, direct_rad=pi*45.0/180.0)
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In [15]:
dir_deriv(fld2, cell_size_x=10, cell_size_y=10, direct_rad=pi*0.0/180.0)
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In [16]:
dir_deriv(fld2, cell_size_x=10, cell_size_y=10, direct_rad=pi*180.0/180.0)
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In [17]:
dir_deriv(fld2, cell_size_x=10, cell_size_y=10, direct_rad=pi*90.0/180.0)
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dir_deriv(fld2, cell_size_x=10, cell_size_y=10, direct_rad=pi*270.0/180.0)
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In [19]:
dir_deriv(fld2, cell_size_x=10, cell_size_y=10, direct_rad=pi*315.0/180.0)
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In [20]:
dir_deriv(fld2, cell_size_x=10, cell_size_y=10, direct_rad=pi*135.0/180.0)
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In [21]:
fld3 = array([
[10, 10, 10, 10],
[20, 20, 20, 20],
[30, 30, 30, 30]])
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fld4 = fld3
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orients_d(fld3, fld4)
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orients_d(fld3, -fld4)
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orients_d(-fld3, fld4)
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orients_d(-fld3, -fld4)
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In [27]:
orients_d(fld3, 0.0)
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In [28]:
orients_d(0, fld4)
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orients_d(0, -fld4)
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In [30]:
orients_d(-fld3, 0.0)
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