設置顏色條
對於圖形中由彩色的點、線、面構成的連續標簽，用顏色條來表示的效果比較好，在Matplotlib中，顏色條是一個獨立的坐標軸。
可視圖形的顏色選擇可參考matplotlib配色方案。
Choosing Colormaps — Matplotlib 1.4.1 documentation
重點關注的配色方案
- 順序配色方案：由一組連續的顏色構成的配色方案（例如binary 或 viridis）。
- 互逆配色方案：通常有兩種互補的顏色構成，表示正反兩種含義（例如RdBu 或 PuOr）
- 定性配色方案：隨機順序的一組顏色（例如rainbow 或 jet）
plt.imshow(
X,
cmap=None,
norm=None,
aspect=None,
interpolation=None,
alpha=None,
vmin=None,
vmax=None,
origin=None,
extent=None,
shape=<deprecated parameter>,
filternorm=1,
filterrad=4.0,
imlim=<deprecated parameter>,
resample=None,
url=None,
*,
data=None,
**kwargs,
)
Docstring:
Display an image, i.e. data on a 2D regular raster.
Parameters
----------
X : array-like or PIL image
The image data. Supported array shapes are:
- (M, N): an image with scalar data. The data is visualized
using a colormap.
- (M, N, 3): an image with RGB values (0-1 float or 0-255 int).
- (M, N, 4): an image with RGBA values (0-1 float or 0-255 int),
i.e. including transparency.
The first two dimensions (M, N) define the rows and columns of
the image.
Out-of-range RGB(A) values are clipped.
cmap : str or `~matplotlib.colors.Colormap`, optional
The Colormap instance or registered colormap name used to map
scalar data to colors. This parameter is ignored for RGB(A) data.
Defaults to :rc:`image.cmap`.
norm : `~matplotlib.colors.Normalize`, optional
The `Normalize` instance used to scale scalar data to the [0, 1]
range before mapping to colors using *cmap*. By default, a linear
scaling mapping the lowest value to 0 and the highest to 1 is used.
This parameter is ignored for RGB(A) data.
aspect : {'equal', 'auto'} or float, optional
Controls the aspect ratio of the axes. The aspect is of particular
relevance for images since it may distort the image, i.e. pixel
will not be square.
This parameter is a shortcut for explicitly calling
`.Axes.set_aspect`. See there for further details.
- 'equal': Ensures an aspect ratio of 1. Pixels will be square
(unless pixel sizes are explicitly made non-square in data
coordinates using *extent*).
- 'auto': The axes is kept fixed and the aspect is adjusted so
that the data fit in the axes. In general, this will result in
non-square pixels.
If not given, use :rc:`image.aspect` (default: 'equal').
interpolation : str, optional
The interpolation method used. If *None*
:rc:`image.interpolation` is used, which defaults to 'nearest'.
Supported values are 'none', 'nearest', 'bilinear', 'bicubic',
'spline16', 'spline36', 'hanning', 'hamming', 'hermite', 'kaiser',
'quadric', 'catrom', 'gaussian', 'bessel', 'mitchell', 'sinc',
'lanczos'.
If *interpolation* is 'none', then no interpolation is performed
on the Agg, ps, pdf and svg backends. Other backends will fall back
to 'nearest'. Note that most SVG renders perform interpolation at
rendering and that the default interpolation method they implement
may differ.
See
:doc:`/gallery/images_contours_and_fields/interpolation_methods`
for an overview of the supported interpolation methods.
Some interpolation methods require an additional radius parameter,
which can be set by *filterrad*. Additionally, the antigrain image
resize filter is controlled by the parameter *filternorm*.
alpha : scalar, optional
The alpha blending value, between 0 (transparent) and 1 (opaque).
This parameter is ignored for RGBA input data.
vmin, vmax : scalar, optional
When using scalar data and no explicit *norm*, *vmin* and *vmax*
define the data range that the colormap covers. By default,
the colormap covers the complete value range of the supplied
data. *vmin*, *vmax* are ignored if the *norm* parameter is used.
origin : {'upper', 'lower'}, optional
Place the [0,0] index of the array in the upper left or lower left
corner of the axes. The convention 'upper' is typically used for
matrices and images.
If not given, :rc:`image.origin` is used, defaulting to 'upper'.
Note that the vertical axes points upward for 'lower'
but downward for 'upper'.
See the :doc:`/tutorials/intermediate/imshow_extent` tutorial for
examples and a more detailed description.
extent : scalars (left, right, bottom, top), optional
The bounding box in data coordinates that the image will fill.
The image is stretched individually along x and y to fill the box.
The default extent is determined by the following conditions.
Pixels have unit size in data coordinates. Their centers are on
integer coordinates, and their center coordinates range from 0 to
columns-1 horizontally and from 0 to rows-1 vertically.
Note that the direction of the vertical axis and thus the default
values for top and bottom depend on *origin*:
- For ``origin == 'upper'`` the default is
``(-0.5, numcols-0.5, numrows-0.5, -0.5)``.
- For ``origin == 'lower'`` the default is
``(-0.5, numcols-0.5, -0.5, numrows-0.5)``.
See the :doc:`/tutorials/intermediate/imshow_extent` tutorial for
examples and a more detailed description.
filternorm : bool, optional, default: True
A parameter for the antigrain image resize filter (see the
antigrain documentation). If *filternorm* is set, the filter
normalizes integer values and corrects the rounding errors. It
doesn't do anything with the source floating point values, it
corrects only integers according to the rule of 1.0 which means
that any sum of pixel weights must be equal to 1.0. So, the
filter function must produce a graph of the proper shape.
filterrad : float > 0, optional, default: 4.0
The filter radius for filters that have a radius parameter, i.e.
when interpolation is one of: 'sinc', 'lanczos' or 'blackman'.
resample : bool, optional
When *True*, use a full resampling method. When *False*, only
resample when the output image is larger than the input image.
url : str, optional
Set the url of the created `.AxesImage`. See `.Artist.set_url`.
Returns
-------
image : `~matplotlib.image.AxesImage`
Other Parameters
----------------
**kwargs : `~matplotlib.artist.Artist` properties
These parameters are passed on to the constructor of the
`.AxesImage` artist.
See also
--------
matshow : Plot a matrix or an array as an image.
**X:**
圖像數據。支持的數組形狀是：
（M，N） ：帶有標量數據的圖像。數據可視化使用色彩圖。
（M，N，3） ：具有RGB值的圖像（float或uint8）。
（M，N，4） ：具有RGBA值的圖像（float或uint8），即包括透明度。
前兩個維度（M，N）定義了行和列圖片，即圖片的高和寬；
RGB（A）值應該在浮點數[0, ..., 1]的范圍內,或者
整數[0, ... ,255]。超出范圍的值將被剪切為這些界限。
**cmap:**
將標量數據映射到色彩圖
顏色默認為：rc：image.cmap。
**norm :**
~matplotlib.colors.Normalize
如果使用scalar data ，則Normalize會對其進行縮放[0,1]的數據值內。
默認情況下，數據范圍使用線性縮放映射到顏色條范圍。 RGB（A）數據忽略該參數。
**aspect:**
{'equal'，'auto'}或float，可選
控制軸的縱橫比。該參數可能使圖像失真，即像素不是方形的。
equal：確保寬高比為1,像素將為正方形。（除非像素大小明確地在數據中變為非正方形,坐標使用 extent ）。
auto: 更改圖像寬高比以匹配軸的寬高比。通常，這將導致非方形像素。
**interpolation:**
str
使用的插值方法
支持的值有：'none', 'nearest', 'bilinear', 'bicubic','spline16', 'spline36', 'hanning', 'hamming', 'hermite', 'kaiser',
'quadric', 'catrom', 'gaussian', 'bessel', 'mitchell', 'sinc','lanczos'.
如果interpolation = 'none'，則不執行插值
**alpha:**
alpha值，介於0（透明）和1（不透明）之間。RGBA輸入數據忽略此參數。
**vmin, vmax : scalar,**
如果使用* norm 參數，則忽略 vmin ， vmax *。
vmin,vmax與norm結合使用以標准化亮度數據。
**origin : {'upper', 'lower'}**
將數組的[0,0]索引放在軸的左上角或左下角。
'upper'通常用於矩陣和圖像。
請注意，垂直軸向上指向“下”但向下指向“上”。
**extent：(left, right, bottom, top）**
數據坐標中左下角和右上角的位置。 如果為“無”，則定位圖像使得像素中心落在基於零的（行，列）索引上。
import matplotlib.pyplot as plt
import numpy as np
np.random.seed(123456789)
data = np.random.rand(25).reshape(5, 5)
#plt.imshow()繪制一組矩陣或數組圖像
#cmap設置配色方案，origin設置數組的索引方向，aspect設置坐標軸縱橫比，vmin和vmax設置顯示的值范圍，
#alpha設置透明度，interpolation設置插值方法（默認為None)
plt.imshow(data,cmap='viridis', origin='lower', aspect='auto',vmin=-0.8, vmax=0.8, alpha=0.7, interpolation='None')
#plt.colorbar()繪制簡單顏色條
plt.colorbar()
#xlim,ylim設置x軸和y軸的坐標范圍
plt.imshow(data,cmap='viridis', origin='lower', aspect='auto',vmin=-0.8, vmax=0.8, alpha=0.7, interpolation='None')
plt.xlim(-1,5)
plt.ylim(5,-1)
plt.colorbar()
#interpolation用於設置插值方法
inter_list = ['nearest', 'bilinear', 'bicubic','spline16', 'spline36', 'hanning', 'hamming', 'hermite', 'kaiser',
'quadric', 'catrom', 'gaussian', 'bessel', 'mitchell', 'sinc','lanczos']
fig = plt.figure()
fig.subplots_adjust(hspace=0.6, wspace=0.2)
for i,itype in zip(range(1,17),inter_list):
ax = fig.add_subplot(4,4,i)
ax.imshow(data, cmap='viridis', origin='lower', interpolation=itype)
ax.set_title(itype)
