本文整理汇总了Python中diffpy.srfit.fitbase.FitContribution.A方法的典型用法代码示例。如果您正苦于以下问题：Python FitContribution.A方法的具体用法？Python FitContribution.A怎么用？Python FitContribution.A使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类diffpy.srfit.fitbase.FitContribution的用法示例。
在下文中一共展示了FitContribution.A方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: show
# 需要导入模块: from diffpy.srfit.fitbase import FitContribution [as 别名]
# 或者: from diffpy.srfit.fitbase.FitContribution import A [as 别名]
# SrFit objects can be examined by calling their show() function. SrFit
# parses the model equation and finds two parameters A, B at independent
# variable x. The values of parameters A, B are at this stage undefined.
linefit.show()
# <demo> --- stop ---
# We can set A and B to some specific values and calculate model
# observations. The x and y attributes of the FitContribution are
# the observed values, which may be re-sampled or truncated to a shorter
# fitting range.
linefit.A
linefit.A = 3
linefit.B = 5
print(linefit.A, linefit.A.value)
print(linefit.B, linefit.B.value)
# <demo> --- stop ---
# linefit.evaluate() returns the modeled values and linefit.residual
# the difference between observed and modeled data scaled by estimated
# standard deviations.
print("linefit.evaluate() =", linefit.evaluate())
print("linefit.residual() =", linefit.residual())
plt.plot(xobs, yobs, 'x', linedata.x, linefit.evaluate(), '-')
plt.title('Line simulated at A=3, B=5')