英语好的童鞋们,直接看后面的英文官方解释,我就不班门弄斧了。英文不好的,可以看下我的中文解释。
首先:np.linspace
np.linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None)
参数解释:start,stop是开始,结束的数字,num是生成多少个数字,默认50个;endpoint是最后一个stop数字是否包含进去,默认包含;retstep,是两个数字间的间距,默认不显示;dtype默认。
小栗子:对比分析
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);
其次,np.logspace,跟np.linspace很相似,多了一个base
np.logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None)
参数解释:base意思是取对数的时候log的下标;retstep这个参数没有了;
最后,np.arange
这个是比较常用的:
eg:
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')
[
plt.plot(x2, y + 0.5, 'o')
[
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')
[
plt.plot(x2, y + 0.5, 'o')
[
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
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])
'''