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'''
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Created on 20. jan. 2011
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@author: pab
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'''
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import numpy as np
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from numpy import exp, meshgrid
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__all__ = ['peaks', 'humps', 'magic']
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def magic(n):
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'''
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Return magic square for n of any orders > 2.
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A magic square has the property that the sum of every row and column,
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as well as both diagonals, is the same number.
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Examples
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--------
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>>> np.allclose(magic(3),
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... [[8, 1, 6],
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... [3, 5, 7],
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... [4, 9, 2]])
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True
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>>> np.allclose(magic(4),
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... [[16, 2, 3, 13],
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... [ 5, 11, 10, 8],
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... [ 9, 7, 6, 12],
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... [ 4, 14, 15, 1]])
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True
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>>> np.allclose(magic(6),
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... [[35, 1, 6, 26, 19, 24],
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... [ 3, 32, 7, 21, 23, 25],
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... [31, 9, 2, 22, 27, 20],
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... [ 8, 28, 33, 17, 10, 15],
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... [30, 5, 34, 12, 14, 16],
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... [ 4, 36, 29, 13, 18, 11]])
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True
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'''
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if (n < 3):
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raise ValueError('n must be greater than 2.')
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if np.mod(n, 2) == 1: # odd order
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ix = np.arange(n) + 1
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J, I = np.meshgrid(ix, ix)
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A = np.mod(I + J - (n + 3) / 2, n)
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B = np.mod(I + 2 * J - 2, n)
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M = n * A + B + 1
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elif np.mod(n, 4) == 0: # doubly even order
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M = np.arange(1, n * n + 1).reshape(n, n)
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ix = np.mod(np.arange(n) + 1, 4) // 2
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J, I = np.meshgrid(ix, ix)
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iz = np.flatnonzero(I == J)
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M.put(iz, n * n + 1 - M.flat[iz])
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else: # singly even order
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p = n // 2
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M0 = magic(p)
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M = np.hstack((np.vstack((M0, M0 + 3 * p * p)),
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np.vstack((M0 + 2 * p * p, M0 + p * p))))
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if n > 2:
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k = (n - 2) // 4
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Jvec = np.hstack((np.arange(k), np.arange(n - k + 1, n)))
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for i in range(p):
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for j in Jvec:
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temp = M[i][j]
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M[i][j] = M[i + p][j]
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M[i + p][j] = temp
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i = k
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j = 0
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temp = M[i][j]
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M[i][j] = M[i + p][j]
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M[i + p][j] = temp
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j = i
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temp = M[i + p][j]
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M[i + p][j] = M[i][j]
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M[i][j] = temp
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return M
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def peaks(x=None, y=None, n=51):
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'''
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Return the "well" known MatLab (R) peaks function
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evaluated in the [-3,3] x,y range
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Example
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-------
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>>> import matplotlib.pyplot as plt
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>>> x,y,z = peaks()
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h = plt.contourf(x,y,z)
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'''
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if x is None:
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x = np.linspace(-3, 3, n)
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if y is None:
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y = np.linspace(-3, 3, n)
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[x1, y1] = meshgrid(x, y)
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z = (3 * (1 - x1) ** 2 * exp(-(x1 ** 2) - (y1 + 1) ** 2) -
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10 * (x1 / 5 - x1 ** 3 - y1 ** 5) * exp(-x1 ** 2 - y1 ** 2) -
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1. / 3 * exp(-(x1 + 1) ** 2 - y1 ** 2))
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return x1, y1, z
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def humps(x=None):
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'''
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Computes a function that has three roots, and some humps.
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Example
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-------
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>>> import matplotlib.pyplot as plt
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>>> x = np.linspace(0,1)
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>>> y = humps(x)
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h = plt.plot(x,y)
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'''
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if x is None:
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y = np.linspace(0, 1)
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else:
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y = np.asarray(x)
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return 1.0 / ((y - 0.3) ** 2 + 0.01) + 1.0 / ((y - 0.9) ** 2 + 0.04) + \
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2 * y - 5.2
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if __name__ == '__main__':
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from wafo.testing import test_docstrings
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test_docstrings(__file__)
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