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30 lines
1.1 KiB
Python
30 lines
1.1 KiB
Python
from __future__ import division, print_function, absolute_import
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from CDTools.tools import initializers
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from CDTools.tools import cmath
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import numpy as np
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import torch as t
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def test_gaussian():
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# Generate gaussian as a numpy array (square array)
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shape = [10, 10]
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sigma = [2.5, 2.5]
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center = ((shape[0]-1)/2, (shape[1]-1)/2)
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y, x = np.mgrid[:shape[0], :shape[1]]
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np_result = 10*np.exp(-0.5*((x-center[1])/sigma[1])**2
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-0.5*((y-center[0])/sigma[0])**2)
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init_result = cmath.torch_to_complex(initializers.gaussian([10, 10], 10, [2.5, 2.5]))
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assert np.allclose(init_result, np_result)
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# Generate gaussian as a numpy array (rectangular array)
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shape = [10, 5]
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sigma = [2.5, 2.5]
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center = ((shape[0]-1)/2, (shape[1]-1)/2)
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y, x = np.mgrid[:shape[0], :shape[1]]
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np_result = 10*np.exp(-0.5*((x-center[1])/sigma[1])**2
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-0.5*((y-center[0])/sigma[0])**2)
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init_result = cmath.torch_to_complex(initializers.gaussian([10, 5], 10, [2.5, 2.5]))
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assert np.allclose(init_result, np_result)
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