ace.smoother module

Scatterplot smoother with a fixed span.

Takes x,y scattered data and returns a set of (x,s) points that form a smoother curve fitting the data with moving least squares estimates. Similar to a moving average, but with better characteristics. The fundamental issue with this smoother is that the choice of span (window size) is not known in advance. The SuperSmoother uses these smoothers to figure out which span is optimal.

This is a Python port of J. Friedman’s 1982 fixed-span Smoother [Friedman82]

Example:

s = Smoother()
s.specify_data_set(x, y, sort_data = True)
s.set_span(0.05)
s.compute()
smoothed_y = s.smooth_result

class ace.smoother.Smoother[source]

Bases: object

Smoother that accepts data and produces smoother curves that fit the data.

add_data_point_xy(x, y)[source]: Add a new data point to the data set to be smoothed.

specify_data_set(x_input, y_input, sort_data=False)[source]

Fully define data by lists of x values and y values.

This will sort them by increasing x but remember how to unsort them for providing results.

Parameters:

x_inputiterable: list of floats that represent x
y_inputiterable: list of floats that represent y(x) for each x
sort_databool, optional: If true, the data will be sorted by increasing x values.

set_span(span)[source]

Set the window-size for computing the least squares fit.

Parameters:

spanfloat: Fraction on data length N to be considered in smoothing

compute()[source]: Perform the smoothing operations.

plot(fname=None)[source]

Plot the input data and resulting smooth.

Parameters:

fnamestr, optional: name of file to produce. If none, will show interactively.

class ace.smoother.BasicFixedSpanSmoother[source]

Bases: Smoother

A basic fixed-span smoother.

Simple least-squares linear local smoother.

Uses fast updates of means, variances.

compute()[source]: Perform the smoothing operations.

class ace.smoother.BasicFixedSpanSmootherSlowUpdate[source]

Bases: BasicFixedSpanSmoother

Use slow means and variances at each step. Used to validate fast updates.

ace.smoother.DEFAULT_BASIC_SMOOTHER: alias of BasicFixedSpanSmoother

ace.smoother.perform_smooth(x_values, y_values, span=None, smoother_cls=None)[source]

Run the basic smoother (convenience function).

Parameters:

x_valuesiterable: List of x value observations
y_ valuesiterable: list of y value observations
spanfloat, optional: Fraction of data to use as the window
smoother_clsClass: The class of smoother to use to smooth the data

Returns:

smootherobject: The smoother object with results stored on it.