np.linspace、 np.arange、np.logspace三个函数的对比分析--python学习笔记24

np.linspace
np.linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None)

import numpy as np
x1=np.linspace(1,100,endpoint=True,retstep=True);
x2=np.linspace(1,100,num=100,endpoint=True,retstep=True);
x3=np.linspace(1,100,,endpoint=False,retstep=True);
x4=np.linspace(1,100,endpoint=True,retstep=False);

np.arange(3)
array([0, 1, 2])
np.arange(3.0)
array([ 0.,  1.,  2.])
np.arange(3,7)
array([3, 4, 5, 6])
np.arange(3,7,2)
array([3, 5])
'''
Signature: np.linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None)
Docstring:
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
    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()
'''
'''
'''
'''
Signature: np.logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None)
Docstring:
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.
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()
File:      c:\program files (x86)\python35-32\lib\site-packages\numpy\core\function_base.py
Type:      function
'''
'''
Docstring:
arange([start,] stop[, step,], dtype=None)
Return evenly spaced values within a given interval.
Values are generated within the half-open interval ``[start, stop)``
(in other words, the interval including `start` but excluding `stop`).
For integer arguments the function is equivalent to the Python built-in
`range <http://docs.python.org/lib/built-in-funcs.html>`_ function,
but returns an ndarray rather than a list.
When using a non-integer step, such as 0.1, the results will often not
be consistent.  It is better to use ``linspace`` for these cases.
Parameters
----------
start : number, optional
    Start of interval.  The interval includes this value.  The default
    start value is 0.
stop : number
    End of interval.  The interval does not include this value, except
    in some cases where `step` is not an integer and floating point
    round-off affects the length of `out`.
step : number, optional
    Spacing between values.  For any output `out`, this is the distance
    between two adjacent values, ``out[i+1] - out[i]``.  The default
    step size is 1.  If `step` is specified, `start` must also be given.
dtype : dtype
    The type of the output array.  If `dtype` is not given, infer the data
    type from the other input arguments.
Returns
-------
arange : ndarray
    Array of evenly spaced values.
    For floating point arguments, the length of the result is
    ``ceil((stop - start)/step)``.  Because of floating point overflow,
    this rule may result in the last element of `out` being greater
    than `stop`.
See Also
--------
linspace : Evenly spaced numbers with careful handling of endpoints.
ogrid: Arrays of evenly spaced numbers in N-dimensions.
mgrid: Grid-shaped arrays of evenly spaced numbers in N-dimensions.
Examples
--------
np.arange(3)
array([0, 1, 2])
np.arange(3.0)
array([ 0.,  1.,  2.])
np.arange(3,7)
array([3, 4, 5, 6])
np.arange(3,7,2)
array([3, 5])
'''