我已经得到了一系列的(x,y)值,我想用python的matplotlib绘制一个二维直方图。使用hexbin,我得到的结果如下所示:
但我正在寻找这样的东西:
示例代码:
from matplotlib import pyplot as plt
import random
foo = lambda : random.gauss(0.0,1.0)
x = [foo() for i in xrange(5000)]
y = [foo() for i in xrange(5000)]
pairs = zip(x,y)
#using hexbin I supply the x,y series and it does the binning for me
hexfig = plt.figure()
hexplt = hexfig.add_subplot(1,1,1)
hexplt.hexbin(x, y, gridsize = 20)
#to use imshow I have to bin the data myself
def histBin(pairsData,xbins,ybins=None):
if (ybins == None): ybins = xbins
xdata, ydata = zip(*pairsData)
xmin,xmax = min(xdata),max(xdata)
xwidth = xmax-xmin
ymin,ymax = min(ydata),max(ydata)
ywidth = ymax-ymin
def xbin(xval):
xbin = int(xbins*(xval-xmin)/xwidth)
return max(min(xbin,xbins-1),0)
def ybin(yval):
ybin = int(ybins*(yval-ymin)/ywidth)
return max(min(ybin,ybins-1),0)
hist = [[0 for x in xrange(xbins)] for y in xrange(ybins)]
for x,y in pairsData:
hist[ybin(y)][xbin(x)] += 1
extent = (xmin,xmax,ymin,ymax)
return hist,extent
#plot using imshow
imdata,extent = histBin(pairs,20)
imfig = plt.figure()
implt = imfig.add_subplot(1,1,1)
implt.imshow(imdata,extent = extent, interpolation = 'nearest')
plt.draw()
plt.show()
似乎已经有一种方法可以做到这一点,而不需要编写我自己的“装箱”方法和使用imshow。
发布于 2010-01-15 23:57:16
Numpy有一个名为histogram2d的函数,它的文档字符串还向您展示了如何使用Matplotlib可视化它。将interpolation=nearest
添加到imshow调用以禁用插值。
发布于 2012-06-02 01:22:59
我意识到有一个补丁提交给matplotlib,但我采用了其他示例中的代码,以满足我的一些需求。
现在直方图是从左下角绘制的,就像传统的数学(而不是计算)一样。
此外,超出装箱范围的值将被忽略,并且我对二维数组使用2dnumpy数组
我将数据输入从成对改为两个一维数组,因为这是将数据提供给scatter(x,y)和类似函数的方式
def histBin(x,y,x_range=(0.0,1.0),y_range=(0.0,1.0),xbins=10,ybins=None):
""" Helper function to do 2D histogram binning
x, y are lists / 2D arrays
x_range and yrange define the range of the plot similar to the hist(range=...)
xbins,ybins are the number of bins within this range.
"""
pairsData = zip(x,y)
if (ybins == None):
ybins = xbins
xdata, ydata = zip(*pairsData)
xmin,xmax = x_range
xmin = float(xmin)
xmax = float(xmax)
xwidth = xmax-xmin
ymin,ymax = y_range
ymin = float(ymin)
ymax = float(ymax)
ywidth = ymax-ymin
def xbin(xval):
return floor(xbins*(xval-xmin)/xwidth) if xmin <= xval < xmax else xbins-1 if xval ==xmax else None
def ybin(yval):
return floor(ybins*(yval-ymin)/ywidth) if ymin <= yval < ymax else ybins-1 if yval ==ymax else None
hist = numpy.zeros((xbins,ybins))
for x,y in pairsData:
i_x,i_y = xbin(x),ybin(ymax-y)
if i_x is not None and i_y is not None:
hist[i_y,i_x] += 1
extent = (xmin,xmax,ymin,ymax)
return hist,extent
发布于 2012-03-29 05:28:59
我刚刚提交了此https://github.com/matplotlib/matplotlib/pull/805的拉取请求。希望它能被接受。
https://stackoverflow.com/questions/2030970
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