+ /if XRt^RItR RltR RltR RltR RltR RltR RltR Rlt R#) z- Functions for acting on a axis of an array. Nc\R4.VP,p\WV4WT&V\V4,pV#)aTake 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 -------- >>> import numpy as np >>> from scipy.signal._arraytools import axis_slice >>> a = np.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 exactly 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)slicendimtuple)astartstopstepaxisa_slicebs&&&&& V/var/www/html/photoedit/myenv/lib/python3.14/site-packages/scipy/signal/_arraytools.py axis_slicers:HT{maff$G%t,GM %.A Hc\VRVR7#)z]Reverse the 1-D slices of `a` along axis `axis`. Returns axis_slice(a, step=-1, axis=axis). )r r )r)rr s&&r axis_reverser1s abt ,,rcV^8dV#WPV,^, 8d,\RWPV,^, 3,4h\V^^VR7p\W^RVR7p\VRVR7p\VRV^,)RVR7p\P!^V,V, V^V,V, 3VR7pV#)a 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 -------- >>> import numpy as np >>> 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(np.arange(-40, 140), b, 'b', lw=1, label='odd extension') >>> plt.plot(np.arange(100), a, 'r', lw=2, label='original') >>> plt.legend(loc='best') >>> plt.show() rrr rrr r rr r XThe extension length n (%d) is too big. It must not exceed x.shape[axis]-1, which is %d.rshape ValueErrorrnp concatenate)xnr left_endleft_ext right_end right_extexts&&& r odd_extr&9sH 1u774=1 Lwwt}q0123 3!1148H!12DAH1BT2I1Bq1uXBTJI ..!h,1i-)35# $C Jrc.V^8dV#WPV,^, 8d,\RWPV,^, 3,4h\W^RVR7p\VRV^,)RVR7p\P!VVV3VR7pV#)a Even extension at the boundaries of an array Generate a new ndarray by making an even extension of `x` along an axis. Parameters ---------- x : ndarray The array to be extended. n : int The number of elements by which to extend `x` at each end of the axis. axis : int, optional The axis along which to extend `x`. Default is -1. Examples -------- >>> import numpy as np >>> from scipy.signal._arraytools import even_ext >>> a = np.array([[1, 2, 3, 4, 5], [0, 1, 4, 9, 16]]) >>> even_ext(a, 2) array([[ 3, 2, 1, 2, 3, 4, 5, 4, 3], [ 4, 1, 0, 1, 4, 9, 16, 9, 4]]) Even extension is a "mirror image" at the boundaries of the original array: >>> t = np.linspace(0, 1.5, 100) >>> a = 0.9 * np.sin(2 * np.pi * t**2) >>> b = even_ext(a, 40) >>> import matplotlib.pyplot as plt >>> plt.plot(np.arange(-40, 140), b, 'b', lw=1, label='even extension') >>> plt.plot(np.arange(100), a, 'r', lw=2, label='original') >>> plt.legend(loc='best') >>> plt.show() rrrrrr)rr r r"r$r%s&&& r even_extr(nsF 1u774=1 Lwwt}q0123 3!12DAH1Bq1uXBTJI ..(#%# $C JrcV^8dV#\V^^VR7p^.VP,pWV&\P!W@PR7pWS,p\VRVR7pWW,p\P !VVV3VR7p V #)a7 Constant extension at the boundaries of an array Generate a new ndarray that is a constant extension of `x` along an axis. The extension repeats the values at the first and last element of the axis. Parameters ---------- x : ndarray The array to be extended. n : int The number of elements by which to extend `x` at each end of the axis. axis : int, optional The axis along which to extend `x`. Default is -1. Examples -------- >>> import numpy as np >>> from scipy.signal._arraytools import const_ext >>> a = np.array([[1, 2, 3, 4, 5], [0, 1, 4, 9, 16]]) >>> const_ext(a, 2) array([[ 1, 1, 1, 2, 3, 4, 5, 5, 5], [ 0, 0, 0, 1, 4, 9, 16, 16, 16]]) Constant extension continues with the same values as the endpoints of the array: >>> t = np.linspace(0, 1.5, 100) >>> a = 0.9 * np.sin(2 * np.pi * t**2) >>> b = const_ext(a, 40) >>> import matplotlib.pyplot as plt >>> plt.plot(np.arange(-40, 140), b, 'b', lw=1, label='constant extension') >>> plt.plot(np.arange(100), a, 'r', lw=2, label='original') >>> plt.legend(loc='best') >>> plt.show() rdtyperrr)rrronesr+r) rr r r! ones_shaper,r"r#r$r%s &&& r const_extr.sN 1u!1148HqvvJt 77:WW -DH1BT2I I ..(#%# $C JrcV^8dV#\VP4pWV&\P!W0PR7p\P !W@V3VR7pV#)a^ Zero padding at the boundaries of an array Generate a new ndarray that is a zero-padded 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 -------- >>> import numpy as np >>> 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]]) r*r)listrrzerosr+r)rr r zeros_shaper1r%s&&& r zero_extr3sQ4 1uqww-K HH[ 0E ..%E* 6C JrcVfV'g \R4hV#\P!V4'g \R4h\V4pV#)z Check if the given sampling frequency is a scalar and raises an exception otherwise. If allow_none is False, also raises an exception for none sampling rates. Returns the sampling frequency as float or none if the input is none. z#Sampling frequency can not be none.z.Sampling frequency fs must be a single scalar.)rrisscalarfloat)fs allow_nones&&r _validate_fsr9sM zBC C I{{2MN N 2Y Ir)NNNr)r)T) __doc__numpyrrrr&r(r.r3r9rr r=s7' T-2j/d4n Fr