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편집 파일: function_base.cpython-37.pyc
B ��FdH/ � @ s� d dl mZmZmZ d dlZd dlZddlmZ ddlm Z m Z m Z m Z m Z mZ dddgZdd d �Zddd�Zddd�Zddd�ZdS )� )�division�absolute_import�print_functionN� )�numeric)� result_type�NaN� shares_memory�MAY_SHARE_BOUNDS� TooHardError� asanyarray�logspace�linspace� geomspace� c C sV yt �| �} W nB tk rP d�t| ��}t| �} |d7 }tj|t|d� Y nX | S )Nz=object of type {} cannot be safely interpreted as an integer.r )� stacklevel) �operator�index� TypeError�format�type�int�warnings�warn�DeprecationWarning)�ir �msg� r �K/opt/alt/python37/lib64/python3.7/site-packages/numpy/core/function_base.py�_index_deprecate s r �2 TFc C s� t |�}|dk r td| ��|r(|d n|}t| �d } t|�d }t| |t|��}|dkr`|}tjd||d�}|| } |dkr�| | } | dkr�|| }|| }q�|| }n t} || }|| 7 }|r�|dkr�||d< |r�|j|dd �| fS |j|dd �S dS ) a� Return evenly spaced numbers over a specified interval. Returns `num` evenly spaced samples, calculated over the interval [`start`, `stop`]. The endpoint of the interval can optionally be excluded. Parameters ---------- start : scalar The starting value of the sequence. stop : scalar The end value of the sequence, unless `endpoint` is set to False. In that case, the sequence consists of all but the last of ``num + 1`` evenly spaced samples, so that `stop` is excluded. Note that the step size changes when `endpoint` is False. num : int, optional Number of samples to generate. Default is 50. Must be non-negative. endpoint : bool, optional If True, `stop` is the last sample. Otherwise, it is not included. Default is True. retstep : bool, optional If True, return (`samples`, `step`), where `step` is the spacing between samples. dtype : dtype, optional The type of the output array. If `dtype` is not given, infer the data type from the other input arguments. .. versionadded:: 1.9.0 Returns ------- samples : ndarray There are `num` equally spaced samples in the closed interval ``[start, stop]`` or the half-open interval ``[start, stop)`` (depending on whether `endpoint` is True or False). step : float, optional Only returned if `retstep` is True Size of spacing between samples. See Also -------- arange : Similar to `linspace`, but uses a step size (instead of the number of samples). logspace : Samples uniformly distributed in log space. Examples -------- >>> np.linspace(2.0, 3.0, num=5) array([ 2. , 2.25, 2.5 , 2.75, 3. ]) >>> np.linspace(2.0, 3.0, num=5, endpoint=False) array([ 2. , 2.2, 2.4, 2.6, 2.8]) >>> np.linspace(2.0, 3.0, num=5, retstep=True) (array([ 2. , 2.25, 2.5 , 2.75, 3. ]), 0.25) Graphical illustration: >>> import matplotlib.pyplot as plt >>> N = 8 >>> y = np.zeros(N) >>> x1 = np.linspace(0, 10, N, endpoint=True) >>> x2 = np.linspace(0, 10, N, endpoint=False) >>> plt.plot(x1, y, 'o') [<matplotlib.lines.Line2D object at 0x...>] >>> plt.plot(x2, y + 0.5, 'o') [<matplotlib.lines.Line2D object at 0x...>] >>> plt.ylim([-0.5, 1]) (-0.5, 1) >>> plt.show() r z,Number of samples, %s, must be non-negative.r g �?N)�dtype���F)�copy) r � ValueErrorr r �float�_nxZaranger �astype) �start�stop�num�endpointZretstepr! Zdiv�dt�y�delta�stepr r r r s2 L � $@c C s6 t | |||d�}|dkr$t�||�S t�||��|�S )a� Return numbers spaced evenly on a log scale. In linear space, the sequence starts at ``base ** start`` (`base` to the power of `start`) and ends with ``base ** stop`` (see `endpoint` below). Parameters ---------- start : float ``base ** start`` is the starting value of the sequence. stop : float ``base ** stop`` is the final value of the sequence, unless `endpoint` is False. In that case, ``num + 1`` values are spaced over the interval in log-space, of which all but the last (a sequence of length `num`) are returned. num : integer, optional Number of samples to generate. Default is 50. endpoint : boolean, optional If true, `stop` is the last sample. Otherwise, it is not included. Default is True. base : float, optional The base of the log space. The step size between the elements in ``ln(samples) / ln(base)`` (or ``log_base(samples)``) is uniform. Default is 10.0. dtype : dtype The type of the output array. If `dtype` is not given, infer the data type from the other input arguments. Returns ------- samples : ndarray `num` samples, equally spaced on a log scale. See Also -------- arange : Similar to linspace, with the step size specified instead of the number of samples. Note that, when used with a float endpoint, the endpoint may or may not be included. linspace : Similar to logspace, but with the samples uniformly distributed in linear space, instead of log space. geomspace : Similar to logspace, but with endpoints specified directly. Notes ----- Logspace is equivalent to the code >>> y = np.linspace(start, stop, num=num, endpoint=endpoint) ... # doctest: +SKIP >>> power(base, y).astype(dtype) ... # doctest: +SKIP Examples -------- >>> np.logspace(2.0, 3.0, num=4) array([ 100. , 215.443469 , 464.15888336, 1000. ]) >>> np.logspace(2.0, 3.0, num=4, endpoint=False) array([ 100. , 177.827941 , 316.22776602, 562.34132519]) >>> np.logspace(2.0, 3.0, num=4, base=2.0) array([ 4. , 5.0396842 , 6.34960421, 8. ]) Graphical illustration: >>> import matplotlib.pyplot as plt >>> N = 10 >>> x1 = np.logspace(0.1, 1, N, endpoint=True) >>> x2 = np.logspace(0.1, 1, N, endpoint=False) >>> y = np.zeros(N) >>> plt.plot(x1, y, 'o') [<matplotlib.lines.Line2D object at 0x...>] >>> plt.plot(x2, y + 0.5, 'o') [<matplotlib.lines.Line2D object at 0x...>] >>> plt.ylim([-0.5, 1]) (-0.5, 1) >>> plt.show() )r* r+ N)r r& �powerr' )r( r) r* r+ �baser! r- r r r r � s N c C s | dks|dkrt d��t| |t|��}|dkr6|}n t�|�}d}| j|j kr\dkrvn n| j|j } }d| }t�| �t�|� kr�dkr�n n| | } }| }| || } || | }t�|t �r�| d } |d }t� | �}t� |�}|t ||||d|d � } | � |�S ) a� Return numbers spaced evenly on a log scale (a geometric progression). This is similar to `logspace`, but with endpoints specified directly. Each output sample is a constant multiple of the previous. Parameters ---------- start : scalar The starting value of the sequence. stop : scalar The final value of the sequence, unless `endpoint` is False. In that case, ``num + 1`` values are spaced over the interval in log-space, of which all but the last (a sequence of length `num`) are returned. num : integer, optional Number of samples to generate. Default is 50. endpoint : boolean, optional If true, `stop` is the last sample. Otherwise, it is not included. Default is True. dtype : dtype The type of the output array. If `dtype` is not given, infer the data type from the other input arguments. Returns ------- samples : ndarray `num` samples, equally spaced on a log scale. See Also -------- logspace : Similar to geomspace, but with endpoints specified using log and base. linspace : Similar to geomspace, but with arithmetic instead of geometric progression. arange : Similar to linspace, with the step size specified instead of the number of samples. Notes ----- If the inputs or dtype are complex, the output will follow a logarithmic spiral in the complex plane. (There are an infinite number of spirals passing through two points; the output will follow the shortest such path.) Examples -------- >>> np.geomspace(1, 1000, num=4) array([ 1., 10., 100., 1000.]) >>> np.geomspace(1, 1000, num=3, endpoint=False) array([ 1., 10., 100.]) >>> np.geomspace(1, 1000, num=4, endpoint=False) array([ 1. , 5.62341325, 31.6227766 , 177.827941 ]) >>> np.geomspace(1, 256, num=9) array([ 1., 2., 4., 8., 16., 32., 64., 128., 256.]) Note that the above may not produce exact integers: >>> np.geomspace(1, 256, num=9, dtype=int) array([ 1, 2, 4, 7, 16, 32, 63, 127, 256]) >>> np.around(np.geomspace(1, 256, num=9)).astype(int) array([ 1, 2, 4, 8, 16, 32, 64, 128, 256]) Negative, decreasing, and complex inputs are allowed: >>> np.geomspace(1000, 1, num=4) array([ 1000., 100., 10., 1.]) >>> np.geomspace(-1000, -1, num=4) array([-1000., -100., -10., -1.]) >>> np.geomspace(1j, 1000j, num=4) # Straight line array([ 0. +1.j, 0. +10.j, 0. +100.j, 0.+1000.j]) >>> np.geomspace(-1+0j, 1+0j, num=5) # Circle array([-1.00000000+0.j , -0.70710678+0.70710678j, 0.00000000+1.j , 0.70710678+0.70710678j, 1.00000000+0.j ]) Graphical illustration of ``endpoint`` parameter: >>> import matplotlib.pyplot as plt >>> N = 10 >>> y = np.zeros(N) >>> plt.semilogx(np.geomspace(1, 1000, N, endpoint=True), y + 1, 'o') >>> plt.semilogx(np.geomspace(1, 1000, N, endpoint=False), y + 2, 'o') >>> plt.axis([0.5, 2000, 0, 3]) >>> plt.grid(True, color='0.7', linestyle='-', which='both', axis='both') >>> plt.show() r z&Geometric sequence cannot include zeroNr y �?r" y g $@)r* r+ r2 r! ) r$ r r% r& r! �real�imag�signZ issubdtype�complex�log10r r' ) r( r) r* r+ r! r, Zout_signZ log_startZlog_stop�resultr r r r � s. 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