使用histogram2d python找到平均bin值

发布时间：2020-12-20 11:36:40 所属栏目：Python 来源：网络整理

导读：参见英文答案 binning data in python with scipy/numpy????????????????????????????????????6个如何在python中使用2D直方图计算容器的平均值？我有x轴和y轴的温度范围,我试图用相应温度的箱子绘制闪电概率.我正在读取csv文件中的数据,我的代码是这样的：

参见英文答案 > binning data in python with scipy/numpy????????????????????????????????????6个
如何在python中使用2D直方图计算容器的平均值？我有x轴和y轴的温度范围,我试图用相应温度的箱子绘制闪电概率.我正在读取csv文件中的数据,我的代码是这样的：

filename = 'Random_Events_All_Sorted_85GHz.csv'
df = pd.read_csv(filename)

min37 = df.min37
min85 = df.min85
verification = df.five_min_1

#Numbers
x = min85
y = min37
H = verification

#Estimate the 2D histogram
nbins = 4
H,xedges,yedges = np.histogram2d(x,y,bins=nbins)

#Rotate and flip H
H = np.rot90(H) 
H = np.flipud(H)

#Mask zeros
Hmasked = np.ma.masked_where(H==0,H)

#Plot 2D histogram using pcolor
fig1 = plt.figure()
plt.pcolormesh(xedges,yedges,Hmasked)
plt.xlabel('min 85 GHz PCT (K)')
plt.ylabel('min 37 GHz PCT (K)')
cbar = plt.colorbar()
cbar.ax.set_ylabel('Probability of Lightning (%)')

plt.show()

这样可以产生漂亮的绘图,但绘制的数据是计数或落入每个bin的样本数.验证变量是一个包含1和0的数组,其中1表示闪电,0表示没有闪电.我希望绘图中的数据是基于验证变量数据的给定bin的闪电概率 – 因此我需要bin_mean * 100才能获得此百分比.

我尝试使用类似于此处所示的方法(binning data in python with scipy/numpy),但我很难将其用于2D直方图.

解决方法

这至少可以通过以下方法实现

# xedges,yedges as returned by 'histogram2d'

# create an array for the output quantities
avgarr = np.zeros((nbins,nbins))

# determine the X and Y bins each sample coordinate belongs to
xbins = np.digitize(x,xedges[1:-1])
ybins = np.digitize(y,yedges[1:-1])

# calculate the bin sums (note,if you have very many samples,this is more
# effective by using 'bincount',but it requires some index arithmetics
for xb,yb,v in zip(xbins,ybins,verification):
    avgarr[yb,xb] += v

# replace 0s in H by NaNs (remove divide-by-zero complaints)
# if you do not have any further use for H after plotting,the
# copy operation is unnecessary,and this will the also take care
# of the masking (NaNs are plotted transparent)
divisor = H.copy()
divisor[divisor==0.0] = np.nan

# calculate the average
avgarr /= divisor

# now 'avgarr' contains the averages (NaNs for no-sample bins)

如果您事先知道bin边缘,则可以通过添加一行来完成相同的直方图部分.

（编辑：李大同）

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