我正在尝试使用Python和matplotlib定义一个自定义类，
产生一个复杂的数字。但是，我在获取
箱形图正确打印-它们不出现晶须或
标记中间值的线。我无法嵌入示例图像，但是您可以see one here。
我的自定义类定义如下：
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.ticker import FixedLocator
from matplotlib.gridspec import GridSpec
from matplotlib.figure import Figure
from matplotlib.backends.backend_svg import FigureCanvasSVG as FigureCanvas
import numpy as np
import scipy as sp
import scipy.optimize
class DotDashHist(Figure):
"""A Tufte-style dot-dash plot with histograms along the x- and y-axes."""
def __init__(self, the_vals):
# Actually inherit all the attributes and methods of parent class
super(DotDashHist, self).__init__()
# Process incoming data
self.vals = the_vals
self.xvals, self.yvals = zip(*self.vals)
self.xvals_uniq = list(set(self.xvals))
self.yvals_uniq = list(set(self.yvals))
self.xmax = float(max(self.xvals_uniq))
self.xpadding = float(self.xmax / 50)
self.ymax = float(max(self.yvals_uniq))
self.ypadding = float(self.ymax / 50)
self.xlims = [-1 * self.xpadding, self.xmax + self.xpadding]
self.ylims = [-1 * self.ypadding, self.ymax + self.ypadding]
self.lims = [-1 * self.xpadding, self.xmax + self.xpadding,
-1 * self.ypadding, self.ymax + self.ypadding]
# Set some matplotlib default behavior
mpl.rcParams['backend'] = 'SVG'
mpl.rcParams['lines.antialiased'] = True
mpl.rcParams['font.family'] = 'sans-serif'
mpl.rcParams['font.sans-serif'] = 'Gill Sans MT Pro, Lucida Grande, Helvetica, sans-serif'
mpl.rcParams['axes.titlesize'] = 'large'
mpl.rcParams['axes.labelsize'] = 'xx-small'
mpl.rcParams['xtick.major.size'] = 2
mpl.rcParams['xtick.minor.size'] = 0.5
mpl.rcParams['xtick.labelsize'] = 'xx-small'
mpl.rcParams['ytick.major.size'] = 2
mpl.rcParams['ytick.minor.size'] = 0.5
mpl.rcParams['ytick.labelsize'] = 'xx-small'
def _makeskel(self):
# Set up the framework in which the figure will be drawn
# Define the canvas for the figure
self.canvas = FigureCanvas(self)
self.set_canvas(self.canvas)
# Place subplots on a 6x6 grid
gs = GridSpec(6,6)
# Add the main subplot, override weird axis and tick defaults
self.main = self.add_subplot(gs[1:, :-1])
self.main.set_frame_on(False)
self.main.get_xaxis().tick_bottom()
self.main.get_yaxis().tick_left()
self.main.axis(self.lims)
# Add the x-value histogram, override weird axis and tick defaults
self.xhist = self.add_subplot(gs[0, :-1])
self.xhist.set_xticks([])
self.xhist.set_yticks([])
self.xhist.set_frame_on(False)
self.xhist.get_xaxis().tick_bottom()
self.xhist.get_yaxis().tick_left()
self.xhist.set_xlim(self.xlims)
# Add the y-value histogram, override weird axis and tick defaults
self.yhist = self.add_subplot(gs[1:, -1])
self.yhist.set_xticks([])
self.yhist.set_yticks([])
self.yhist.set_frame_on(False)
self.yhist.get_xaxis().tick_bottom()
self.yhist.get_yaxis().tick_left()
self.yhist.set_ylim(self.ylims)
def _makehist(self):
# Draw the x- and y-value histograms
self.xhist.hist(self.xvals, normed=1, bins=min([50, self.xmax + 1]),
range=[0, self.xmax + self.xpadding])
self.yhist.hist(self.yvals, normed=1, bins=min([50, self.ymax + 1]),
range=[0, self.ymax + self.ypadding],
orientation='horizontal')
def makebox(self):
self._makeskel()
self._makehist()
# Aggregate to make boxplots
box_dict = {}
for point in self.vals:
if point[0] <= self.xmax and point[1] <= self.ymax:
box_dict.setdefault(round(float(point[0]), 0),
[]).append(point[1])
self.main.boxplot(box_dict.values(), positions=box_dict.keys(),
whis=1.0, sym='ro')
self.main.set_xticks(np.arange(0, self.xmax + 1, 12))
self.main.xaxis.set_minor_locator(FixedLocator(self.xvals_uniq))
self.main.yaxis.set_minor_locator(FixedLocator(self.yvals_uniq))
此测试代码显示了问题：
from numpy.random import randn
import mycustomfigures as hf
test_x = np.arange(0, 25, 0.01)
test_y = test_x + randn(2500)
test_data = zip(test_x, test_y)
test_fig = hf.DotDashHist(test_data)
test_fig.makebox()
test_fig.suptitle('Test Figure')
test_fig.savefig('testing.svg')
我定义DotDashHist的方式有什么问题？我可以使用MATLAB样式的有状态语法生成晶须状线图，但是这种方法在绘制多个图形时会生成大量代码。
最佳答案
对于我来说，晶须在您的原始绘图中，只是被您绘制的异常点所遮盖。
无论如何，我将继续执行以下操作：
import collections
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec
import numpy as np
def main():
x = np.arange(0, 25, 0.01)
y = x + np.random.randn(x.size)
plot = DotDashHist(figsize=(10, 8))
plot.plot(x, y, whis=1.0, sym='r.')
plot.title('This is a Test')
plt.show()
class DotDashHist(object):
def __init__(self, **kwargs):
self.fig = plt.figure(**kwargs)
gs = GridSpec(6, 6)
self.ax = self.fig.add_subplot(gs[1:, :-1])
self.topax = self.fig.add_subplot(gs[0, :-1], sharex=self.ax)
self.rightax = self.fig.add_subplot(gs[1:, -1], sharey=self.ax)
for ax in [self.topax, self.rightax]:
ax.set_axis_off()
def plot(self, x, y, **kwargs):
_, _, self.topbars = self.topax.hist(x, normed=1, bins=50)
_, _, self.rightbars = self.rightax.hist(y, normed=1, bins=50,
orientation='horizontal')
boxes = collections.defaultdict(list)
for X, Y in zip(x, y):
boxes[int(X)].append(Y)
kwargs.pop('positions', None)
self.boxes = self.ax.boxplot(boxes.values(), **kwargs)
def title(self, *args, **kwargs):
self.topax.set_title(*args, **kwargs)
if __name__ == '__main__':
main()
关于python - 面向对象的matplotlib用法神秘地产生没有晶须或中间线的箱形图，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/8888901/