ó ˽÷Xc@`sƒdZddlmZmZmZddlZddddd„Zdd„Z dd„Z dd„Z dd „Z dd „Z dS( s- Functions for acting on a axis of an array. i(tdivisiontprint_functiontabsolute_importNiÿÿÿÿcC`s:tdƒg|j}t|||ƒ||<||}|S(sÛTake a slice along axis 'axis' from 'a'. Parameters ---------- a : numpy.ndarray The array to be sliced. start, stop, step : int or None The slice parameters. axis : int, optional The axis of `a` to be sliced. Examples -------- >>> a = array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) >>> axis_slice(a, start=0, stop=1, axis=1) array([[1], [4], [7]]) >>> axis_slice(a, start=1, axis=0) array([[4, 5, 6], [7, 8, 9]]) Notes ----- The keyword arguments start, stop and step are used by calling slice(start, stop, step). This implies axis_slice() does not handle its arguments the exacty the same as indexing. To select a single index k, for example, use axis_slice(a, start=k, stop=k+1) In this case, the length of the axis 'axis' in the result will be 1; the trivial dimension is not removed. (Use numpy.squeeze() to remove trivial axes.) N(tslicetNonetndim(tatstarttstoptsteptaxista_slicetb((s7/tmp/pip-build-7oUkmx/scipy/scipy/signal/_arraytools.pyt axis_slice s" cC`st|ddd|ƒS(seReverse the 1-d slices of `a` along axis `axis`. Returns axis_slice(a, step=-1, axis=axis). R iÿÿÿÿR (R (RR ((s7/tmp/pip-build-7oUkmx/scipy/scipy/signal/_arraytools.pyt axis_reverse1sc C`s|dkr|S||j|dkrOtdd||j|dfƒ‚nt|ddddd|ƒ}t|d|dddd d|ƒ}t|dd d|ƒ}t|dd d|d  dd d|ƒ}tjd |||d ||fd|ƒ}|S( s, Odd extension at the boundaries of an array Generate a new ndarray by making an odd extension of `x` along an axis. Parameters ---------- x : ndarray The array to be extended. n : int The number of elements by which to extend `x` at each end of the axis. axis : int, optional The axis along which to extend `x`. Default is -1. Examples -------- >>> from scipy.signal._arraytools import odd_ext >>> a = np.array([[1, 2, 3, 4, 5], [0, 1, 4, 9, 16]]) >>> odd_ext(a, 2) array([[-1, 0, 1, 2, 3, 4, 5, 6, 7], [-4, -1, 0, 1, 4, 9, 16, 23, 28]]) Odd extension is a "180 degree rotation" at the endpoints of the original array: >>> t = np.linspace(0, 1.5, 100) >>> a = 0.9 * np.sin(2 * np.pi * t**2) >>> b = odd_ext(a, 40) >>> import matplotlib.pyplot as plt >>> plt.plot(arange(-40, 140), b, 'b', lw=1, label='odd extension') >>> plt.plot(arange(100), a, 'r', lw=2, label='original') >>> plt.legend(loc='best') >>> plt.show() is(The extension length n (%d) is too big. s0It must not exceed x.shape[axis]-1, which is %d.RiRR R iÿÿÿÿiþÿÿÿi(tshapet ValueErrorR tnpt concatenate(txtnR tleft_endtleft_extt right_endt right_exttext((s7/tmp/pip-build-7oUkmx/scipy/scipy/signal/_arraytools.pytodd_ext9s# $) c C`s¾|dkr|S||j|dkrOtdd||j|dfƒ‚nt|d|ddddd |ƒ}t|dd d|d  ddd |ƒ}tj|||fd |ƒ}|S( s) Even extension at the boundaries of an array Generate a new ndarray by making an even extension of `x` along an axis. Parameters ---------- x : ndarray The array to be extended. n : int The number of elements by which to extend `x` at each end of the axis. axis : int, optional The axis along which to extend `x`. Default is -1. Examples -------- >>> from scipy.signal._arraytools import even_ext >>> a = np.array([[1, 2, 3, 4, 5], [0, 1, 4, 9, 16]]) >>> even_ext(a, 2) array([[ 3, 2, 1, 2, 3, 4, 5, 4, 3], [ 4, 1, 0, 1, 4, 9, 16, 9, 4]]) Even extension is a "mirror image" at the boundaries of the original array: >>> t = np.linspace(0, 1.5, 100) >>> a = 0.9 * np.sin(2 * np.pi * t**2) >>> b = even_ext(a, 40) >>> import matplotlib.pyplot as plt >>> plt.plot(arange(-40, 140), b, 'b', lw=1, label='even extension') >>> plt.plot(arange(100), a, 'r', lw=2, label='original') >>> plt.legend(loc='best') >>> plt.show() is(The extension length n (%d) is too big. s0It must not exceed x.shape[axis]-1, which is %d.RRiR iÿÿÿÿR iþÿÿÿi(RRR RR(RRR RRR((s7/tmp/pip-build-7oUkmx/scipy/scipy/signal/_arraytools.pyteven_extms" $)   c C`s®|dkr|St|ddddd|ƒ}dg|j}|||>> from scipy.signal._arraytools import const_ext >>> a = np.array([[1, 2, 3, 4, 5], [0, 1, 4, 9, 16]]) >>> const_ext(a, 2) array([[ 1, 1, 1, 2, 3, 4, 5, 5, 5], [ 0, 0, 0, 1, 4, 9, 16, 16, 16]]) Constant extension continues with the same values as the endpoints of the array: >>> t = np.linspace(0, 1.5, 100) >>> a = 0.9 * np.sin(2 * np.pi * t**2) >>> b = const_ext(a, 40) >>> import matplotlib.pyplot as plt >>> plt.plot(arange(-40, 140), b, 'b', lw=1, label='constant extension') >>> plt.plot(arange(100), a, 'r', lw=2, label='original') >>> plt.legend(loc='best') >>> plt.show() iRiRR tdtypeiÿÿÿÿ(R RRtonesRR( RRR Rt ones_shapeRRRRR((s7/tmp/pip-build-7oUkmx/scipy/scipy/signal/_arraytools.pyt const_extžs&       cC`sc|dkr|St|jƒ}|||>> from scipy.signal._arraytools import zero_ext >>> a = np.array([[1, 2, 3, 4, 5], [0, 1, 4, 9, 16]]) >>> zero_ext(a, 2) array([[ 0, 0, 1, 2, 3, 4, 5, 0, 0], [ 0, 0, 0, 1, 4, 9, 16, 0, 0]]) iRR (tlistRRtzerosRR(RRR t zeros_shapeR!R((s7/tmp/pip-build-7oUkmx/scipy/scipy/signal/_arraytools.pytzero_extÔs  (t__doc__t __future__RRRtnumpyRRR RRRRR#(((s7/tmp/pip-build-7oUkmx/scipy/scipy/signal/_arraytools.pyts (  4 1 6