Question

我有一个问题。

我使用Matplotlib绘制了一个图形，如下所示：

from matplotlib import pyplot
import numpy
from scipy.interpolate import spline

widths = numpy.array([0, 30, 60, 90, 120, 150, 180])
heights = numpy.array([26, 38.5, 59.5, 82.5, 120.5, 182.5, 319.5])

xnew = numpy.linspace(widths.min(),widths.max(),300)
heights_smooth = spline(widths,heights,xnew)

pyplot.plot(xnew,heights_smooth)
pyplot.show()

现在我想使用宽度值作为参数查询高度值。我似乎无法找到如何做到这一点。请帮忙！提前谢谢！

Answer 1

plot()会返回一个有用的对象：[<matplotlib.lines.Line2D object at 0x38c9910>]
由此我们可以获得x轴和y轴值：

import matplotlib.pyplot as plt, numpy as np
...
line2d = plt.plot(xnew,heights_smooth)
xvalues = line2d[0].get_xdata()
yvalues = line2d[0].get_ydata()

然后我们可以获得其中一个宽度值的索引：

idx = np.where(xvalues==xvalues[-2]) # this is 179.3979933110368
# idx is a tuple of array(s) containing index where value was found
# in this case -> (array([298]),)

和相应的高度：

yvalues[idx]
# -> array([ 315.53469])

要检查我们是否可以使用get_xydata()：

>>> xy = line2d[0].get_xydata()
>>> xy[-2]
array([ 179.39799331,  315.53469   ])

Answer 2

您可以将数组转换为列表：

>>> heights[list(widths).index(30)]
38.5

用于插值结果：

s = xnew[56] 
print s, heights_smooth[list(xnew).index(s)]
33.7123745819, 40.9547542163

由于xnew是一个有序列表，您可以使用bisect module查找查询宽度的最接近宽度值，然后以类似的方式找到相应的高度：

....
import bisect
pyplot.plot(xnew,heights_smooth)
#33.1222 is a queried value which does not exist in xnew.
index_of_nearest_width = bisect.bisect_left(xnew, 33.1222) 
width_val = xnew[index_of_closest_width]
print width_val, heights_smooth[list(xnew).index(width_val)]
#prints the nearest width to 33.1222 then the corresponding height.
33.7123745819 40.9547542163

Answer 3

如果您愿意使用不同的样条函数，这是另一个选项：

from matplotlib import pyplot
import numpy
from scipy import interpolate

widths = numpy.array([0, 30, 60, 90, 120, 150, 180])
heights = numpy.array([26, 38.5, 59.5, 82.5, 120.5, 182.5, 319.5])

xnew = numpy.linspace(widths.min(),widths.max(),300)
heights_smooth = interpolate.splrep(widths,heights) #Use splrep instead of spline

#Select desired width values
width_vals = [0, 80.5, 38.98743]   

#splev returns the value of your spline evaluated at the width values.    
heights = interpolate.splev(width_vals, heights_smooth)

然后

In[]:  heights
Out[]: array([ 26.        ,  74.1721985 ,  44.47929453])

或者评估一下：

w = 167.2
heights = interpolate.splev(w, heights_smooth)
height = heights.item()

In[]:  height
Out[]: 247.8396196684303

.item()功能是必需的，因为splev会返回array()

如何从图中提取点？

3 个答案: