Matplotlib 表函数中的图例颜色?

发布于 2024-10-28 19:12:47 字数 295 浏览 5 评论 0原文

有谁知道是否可以在 Matplotlib 的图例函数中采用标准颜色框,并将这些框放入表格的行中?

例如,查看此图表:

http://www.winplanet.com/img /screenshots/excel-datatable.gif

在底部的表格中,您将看到行项目旁边的小彩色框。

这可以用 Matplotlib 来做吗?

Does anyone know if it's possible to take the standard color boxes in the legend function in Matplotlib, and put those boxes in the rows of a table?

For example, look at this chart:

http://www.winplanet.com/img/screenshots/excel-datatable.gif

In the table at the bottom, you will see the small colored boxes next to the row items.

Is that possible to do with Matplotlib?

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南街九尾狐 2024-11-04 19:12:47

有点,但我不确定你是否可以做到这一点,这样你也可以调整窗口的大小(除了在所有绘图之前)。

我改编了 http://matplotlib.sourceforge.net/users/screenshots.html 中的“表格”示例。它使用一个跨越整个图形的单独轴,并在正确的位置添加自定义矩形补丁。正确的地点就是通过反复试验来确定正确的地点。

#!/usr/bin/env python
import matplotlib

from pylab import *
from matplotlib.colors import colorConverter


#Some simple functions to generate colours.
def pastel(colour, weight=2.4):
    """ Convert colour into a nice pastel shade"""
    rgb = asarray(colorConverter.to_rgb(colour))
    # scale colour
    maxc = max(rgb)
    if maxc < 1.0 and maxc > 0:
        # scale colour
        scale = 1.0 / maxc
        rgb = rgb * scale
    # now decrease saturation
    total = sum(rgb)
    slack = 0
    for x in rgb:
        slack += 1.0 - x

    # want to increase weight from total to weight
    # pick x s.t.  slack * x == weight - total
    # x = (weight - total) / slack
    x = (weight - total) / slack

    rgb = [c + (x * (1.0-c)) for c in rgb]

    return rgb

def get_colours(n):
    """ Return n pastel colours. """
    base = asarray([[1,0,0], [0,1,0], [0,0,1]])

    if n <= 3:
        return base[0:n]

    # how many new colours to we need to insert between
    # red and green and between green and blue?
    needed = (((n - 3) + 1) / 2, (n - 3) / 2)

    colours = []
    for start in (0, 1):
        for x in linspace(0, 1, needed[start]+2):
            colours.append((base[start] * (1.0 - x)) +
                           (base[start+1] * x))

    return [pastel(c) for c in colours[0:n]]


figure(1)
clf()
ax = axes([0.2, 0.2, 0.7, 0.6])   # leave room below the axes for the table

data = [[  66386,  174296,   75131,  577908,   32015],
        [  58230,  381139,   78045,   99308,  160454],
        [  89135,   80552,  152558,  497981,  603535],
        [  78415,   81858,  150656,  193263,   69638],
        [ 139361,  331509,  343164,  781380,   52269]]

colLabels = ('Freeze', 'Wind', 'Flood', 'Quake', 'Hail')
rowLabels = ['    %d year' % x for x in (100, 50, 20, 10, 5)]

# Get some pastel shades for the colours
colours = get_colours(len(colLabels))
colours.reverse()
rows = len(data)

ind = arange(len(colLabels)) + 0.3  # the x locations for the groups
cellText = []
width = 0.4     # the width of the bars
yoff = array([0.0] * len(colLabels)) # the bottom values for stacked bar chart
for row in xrange(rows):
    bar(ind, data[row], width, bottom=yoff, color=colours[row])
    yoff = yoff + data[row]
    cellText.append(['%1.1f' % (x/1000.0) for x in yoff])

# Add a table at the bottom of the axes
colours.reverse()
cellText.reverse()
the_table = table(cellText=cellText,
                  rowLabels=rowLabels,
                  colLabels=colLabels,
                  loc='bottom')


ylabel("Loss $1000's")
vals = arange(0, 2500, 500)
yticks(vals*1000, ['%d' % val for val in vals])
xticks([])
title('Loss by Disaster')

ax2 = axes([0,0,1,1], frameon=False)
ax2.xaxis.set_visible(False)
ax2.yaxis.set_visible(False)

for ind, k in enumerate(colours):
    rect = matplotlib.patches.Rectangle((.07, -.0278*ind+.15), .015, .015, fill=True, fc = k, ec = '.0')
    ax2.add_patch(rect)                     

show()

Sort of, but I'm not sure if you can make it so you can also resize the window (except before all the plotting).

I adapted the 'table' example from http://matplotlib.sourceforge.net/users/screenshots.html. It uses a separate axis that spans the whole figure and adds custom rectangle patches in the right spot. The right spot is simply what trial and error defines the right spot to be.

#!/usr/bin/env python
import matplotlib

from pylab import *
from matplotlib.colors import colorConverter


#Some simple functions to generate colours.
def pastel(colour, weight=2.4):
    """ Convert colour into a nice pastel shade"""
    rgb = asarray(colorConverter.to_rgb(colour))
    # scale colour
    maxc = max(rgb)
    if maxc < 1.0 and maxc > 0:
        # scale colour
        scale = 1.0 / maxc
        rgb = rgb * scale
    # now decrease saturation
    total = sum(rgb)
    slack = 0
    for x in rgb:
        slack += 1.0 - x

    # want to increase weight from total to weight
    # pick x s.t.  slack * x == weight - total
    # x = (weight - total) / slack
    x = (weight - total) / slack

    rgb = [c + (x * (1.0-c)) for c in rgb]

    return rgb

def get_colours(n):
    """ Return n pastel colours. """
    base = asarray([[1,0,0], [0,1,0], [0,0,1]])

    if n <= 3:
        return base[0:n]

    # how many new colours to we need to insert between
    # red and green and between green and blue?
    needed = (((n - 3) + 1) / 2, (n - 3) / 2)

    colours = []
    for start in (0, 1):
        for x in linspace(0, 1, needed[start]+2):
            colours.append((base[start] * (1.0 - x)) +
                           (base[start+1] * x))

    return [pastel(c) for c in colours[0:n]]


figure(1)
clf()
ax = axes([0.2, 0.2, 0.7, 0.6])   # leave room below the axes for the table

data = [[  66386,  174296,   75131,  577908,   32015],
        [  58230,  381139,   78045,   99308,  160454],
        [  89135,   80552,  152558,  497981,  603535],
        [  78415,   81858,  150656,  193263,   69638],
        [ 139361,  331509,  343164,  781380,   52269]]

colLabels = ('Freeze', 'Wind', 'Flood', 'Quake', 'Hail')
rowLabels = ['    %d year' % x for x in (100, 50, 20, 10, 5)]

# Get some pastel shades for the colours
colours = get_colours(len(colLabels))
colours.reverse()
rows = len(data)

ind = arange(len(colLabels)) + 0.3  # the x locations for the groups
cellText = []
width = 0.4     # the width of the bars
yoff = array([0.0] * len(colLabels)) # the bottom values for stacked bar chart
for row in xrange(rows):
    bar(ind, data[row], width, bottom=yoff, color=colours[row])
    yoff = yoff + data[row]
    cellText.append(['%1.1f' % (x/1000.0) for x in yoff])

# Add a table at the bottom of the axes
colours.reverse()
cellText.reverse()
the_table = table(cellText=cellText,
                  rowLabels=rowLabels,
                  colLabels=colLabels,
                  loc='bottom')


ylabel("Loss $1000's")
vals = arange(0, 2500, 500)
yticks(vals*1000, ['%d' % val for val in vals])
xticks([])
title('Loss by Disaster')

ax2 = axes([0,0,1,1], frameon=False)
ax2.xaxis.set_visible(False)
ax2.yaxis.set_visible(False)

for ind, k in enumerate(colours):
    rect = matplotlib.patches.Rectangle((.07, -.0278*ind+.15), .015, .015, fill=True, fc = k, ec = '.0')
    ax2.add_patch(rect)                     

show()
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