Stats.Moment

Stats.Moment#

Stats.Moment.py

Copyright (c) 2024-2025, SAXS Team, KEK-PF

compute_meanstd(x, y)#

Compute the mean and standard deviation of a distribution defined by x and y.

Parameters:

  • x (array-like) – The x-values of the distribution.

  • y (array-like) – The y-values of the distribution.

Returns:

  • M1 (float) – The mean of the distribution.

  • std (float) – The standard deviation of the distribution.

class Moment(x, y)#

Bases: object

A class to represent the moment of a distribution defined by x and y. .. attribute:: x

The x-values of the distribution.

type:

array-like

y#

The y-values of the distribution.

Type:

array-like

y_#

The processed y-values of the distribution. If None, it has not been computed yet.

Type:

array-like or None

M#

The mean of the distribution. If None, it has not been computed yet.

Type:

float or None

std#

The standard deviation of the distribution. If None, it has not been computed yet.

Type:

float or None

lpm_percent#

The estimated percentage of low-q plateau in the distribution. If None, it has not been computed yet.

Type:

float or None

Initialize the Moment object. :param x: The x-values of the distribution. :type x: array-like :param y: The y-values of the distribution. :type y: array-like

get_y_(**kwargs)#
Get the processed y-values of the distribution.

If y_ is None, it will be computed using the provided processing function.

Parameters:

**kwargs (keyword arguments) – Additional keyword arguments to pass to the processing function.

Returns:

y_ – The processed y-values of the distribution.

Return type:

array-like

debug_plot(ax)#

Plot the original and processed y-values for debugging purposes.

Parameters:

ax (matplotlib.axes.Axes) – The axes to plot on.

get_meanstd()#
Get the mean and standard deviation of the distribution.

If M and std are None, they will be computed using the processed y-values.

Returns:

  • M (float) – The mean of the distribution.

  • std (float) – The standard deviation of the distribution.

is_in_nsigma(n, px)#

Check if a given x-value is within n standard deviations from the mean.

Parameters:

  • n (float) – The number of standard deviations.

  • px (float) – The x-value to check.

Returns:

True if px is within n standard deviations from the mean, False otherwise.

Return type:

bool

get_nsigma_points(n)#

Get the indices of the x-values that are within n standard deviations from the mean.

Parameters:

n (float) – The number of standard deviations.

Returns:

(i, j) – The indices of the first and last x-values within n standard deviations from the mean. If no such points exist, returns (None, None).

Return type:

tuple of int

get_lpm_percent(debug=True)#

Estimate the percentage of low-q plateau in the distribution.

Parameters:

debug (bool, optional) – If True, enables debug mode for more verbose output, by default True.

Returns:

lpm_percent – The estimated percentage of low-q plateau in the distribution.

Return type:

float

Contents