seo是做网站,最新新闻热点事件2023年4月,论医院网站的建设,开放平台设计这是使用scipy.optimize.curve_fit拟合表面的示例Python代码,它使原始数据生成3D散点图,对错误进行3D散点图绘制,绘制表面图和轮廓图.更改它以使用您自己的数据和功能,您应该已完成.
import numpy, scipy
import scipy.optimize
import matplotlib
from mpl_toolkits.mplot3d i…这是使用scipy.optimize.curve_fit拟合表面的示例Python代码,它使原始数据生成3D散点图,对错误进行3D散点图绘制,绘制表面图和轮廓图.更改它以使用您自己的数据和功能,您应该已完成.
import numpy, scipy
import scipy.optimize
import matplotlib
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm # to colormap 3D surfaces from blue to red
import matplotlib.pyplot as plt
graphWidth 800 # units are pixels
graphHeight 600 # units are pixels
# 3D contour plot lines
numberOfContourLines 16
def SurfacePlot(equationFunc, data, params):
f plt.figure(figsize(graphWidth/100.0, graphHeight/100.0), dpi100)
matplotlib.pyplot.grid(True)
axes Axes3D(f)
x_data data[0]
y_data data[1]
z_data data[2]
xModel numpy.linspace(min(x_data), max(x_data), 20)
yModel numpy.linspace(min(y_data), max(y_data), 20)
X, Y numpy.meshgrid(xModel, yModel)
Z equationFunc(numpy.array([X, Y]), *params)
axes.plot_surface(X, Y, Z, rstride1, cstride1, cmapcm.coolwarm, linewidth1, antialiasedTrue)
axes.scatter(x_data, y_data, z_data) # show data along with plotted surface
axes.set_title(Surface Plot (click-drag with mouse)) # add a title for surface plot
axes.set_xlabel(X Data) # X axis data label
axes.set_ylabel(Y Data) # Y axis data label
axes.set_zlabel(Z Data) # Z axis data label
plt.show()
plt.close(all) # clean up after using pyplot or else thaere can be memory and process problems
def ContourPlot(equationFunc, data, params):
f plt.figure(figsize(graphWidth/100.0, graphHeight/100.0), dpi100)
axes f.add_subplot(111)
x_data data[0]
y_data data[1]
z_data data[2]
xModel numpy.linspace(min(x_data), max(x_data), 20)
yModel numpy.linspace(min(y_data), max(y_data), 20)
X, Y numpy.meshgrid(xModel, yModel)
Z equationFunc(numpy.array([X, Y]), *params)
axes.plot(x_data, y_data, o)
axes.set_title(Contour Plot) # add a title for contour plot
axes.set_xlabel(X Data) # X axis data label
axes.set_ylabel(Y Data) # Y axis data label
CS matplotlib.pyplot.contour(X, Y, Z, numberOfContourLines, colorsk)
matplotlib.pyplot.clabel(CS, inline1, fontsize10) # labels for contours
plt.show()
plt.close(all) # clean up after using pyplot or else thaere can be memory and process problems
def ScatterPlot(data, title):
f plt.figure(figsize(graphWidth/100.0, graphHeight/100.0), dpi100)
matplotlib.pyplot.grid(True)
axes Axes3D(f)
x_data data[0]
y_data data[1]
z_data data[2]
axes.scatter(x_data, y_data, z_data, depthshadeFalse, colork)
axes.set_title(title)
axes.set_xlabel(X Data)
axes.set_ylabel(Y Data)
axes.set_zlabel(Z Data)
plt.show()
plt.close(all) # clean up after using pyplot or else thaere can be memory and process problems
def EquationFunc(data, *params):
p0 params[0]
p1 params[1]
return p0 numpy.sqrt(data[0]) numpy.cos(data[1] / p1)
if __name__ __main__:
# raw data
xData numpy.array([1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0])
yData numpy.array([11.0, 12.1, 13.0, 14.1, 15.0, 16.1, 17.0, 18.1, 90.0])
zData numpy.array([1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.0, 9.9])
pInitial (1.0, 1.0)
popt, pcov scipy.optimize.curve_fit(EquationFunc,(xData,yData),zData, p0pInitial)
dataForPlotting [xData, yData, zData]
ScatterPlot([xData, yData, zData], Data Scatter Plot (click-drag with mouse))
SurfacePlot(EquationFunc, [xData, yData, zData], popt)
ContourPlot(EquationFunc, [xData, yData, zData], popt)
absError zData - EquationFunc((xData,yData), *popt)
ScatterPlot([xData, yData, absError], Error Scatter Plot (click-drag with mouse))
