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87 lines
2.0 KiB
87 lines
2.0 KiB
#
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# Created: 20140207
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# Wirawan Purwanto
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#
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"""
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wpylib.array_tools
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Various tools for arrays (mainly, numpy array objects).
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"""
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import numpy
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def array_indices_cond_1d(arr, cond):
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"""Get the ordered list of array indices whose corresponding elements satisfy
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a given condition.
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Useful for conditional assignment or evaluation.
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The input `cond' argument can be an ufunc-like function that evaluates
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a logical expression in bulk for each of the arr's element.
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Or it can be an array of logical values that has the same length as arr.
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Example use case:
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r = numpy.linspace(1.97, 3.5, num=150)
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i_select = cond_indices_1d(r, r <= 2.5)
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# ... then we can do something with r[i_select]
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# for conditional assignment or value extraction.
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"""
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arr = numpy.asarray(arr)
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assert len(arr.shape) == 1
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if callable(cond):
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cond = cond(arr)
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# otherwise, assume cond is already a good array
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return numpy.array(xrange(len(arr)))[ cond ]
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def array_hstack(arrays):
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"""Creates a 2D array by horizontally stacking many arrays together
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(along the array's second dimension).
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Each of the input arrays can be a 1D or 2D array.
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This function is similar to numpy.hstack.
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"""
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from numpy import asarray, hstack
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stk = []
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for a1 in arrays:
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a = asarray(a1)
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dim = len(a.shape)
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if dim == 1:
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a = a.reshape((len(a),1))
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elif dim == 2:
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pass
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else:
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raise ValueError, "Won't take 3D, 4D, ... arrays"
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stk.append(a)
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return hstack(stk)
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def array_vstack(arrays):
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"""Creates a 2D array by vertically stacking many arrays together
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(along the array's first dimension).
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Each of the input arrays can be a 1D or 2D array.
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This function is similar to numpy.vstack.
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"""
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from numpy import asarray, vstack
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stk = []
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for a1 in arrays:
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a = asarray(a1)
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dim = len(a.shape)
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if dim == 1:
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a = a.reshape((1,len(a)))
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elif dim == 2:
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pass
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else:
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raise ValueError, "Won't take 3D, 4D, ... arrays"
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stk.append(a)
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return vstack(stk)
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