# Bio.phenotype.pm_fitting module

Growth curves fitting and parameters extraction for phenotype data.

This module provides functions to perform sigmoid functions fitting to Phenotype Microarray data. This module depends on scipy curve_fit function. If not available, a warning is raised.

Functions: logistic Logistic growth model. gompertz Gompertz growth model. richards Richards growth model. guess_plateau Guess the plateau point to improve sigmoid fitting. guess_lag Guess the lag point to improve sigmoid fitting. fit Sigmoid functions fit. get_area Calculate the area under the PM curve.

Bio.phenotype.pm_fitting.logistic(x, A, u, d, v, y0)

  Logistic growth model.

  Proposed in Zwietering et al., 1990 (PMID: 16348228)

Bio.phenotype.pm_fitting.gompertz(x, A, u, d, v, y0)

  Gompertz growth model.

  Proposed in Zwietering et al., 1990 (PMID: 16348228)

Bio.phenotype.pm_fitting.richards(x, A, u, d, v, y0)

  Richards growth model (equivalent to Stannard).

  Proposed in Zwietering et al., 1990 (PMID: 16348228)

Bio.phenotype.pm_fitting.guess_lag(x, y)

  Given two axes returns a guess of the lag point.

  The lag point is defined as the x point where the difference in y with the next point is higher then the mean differences between the points plus one standard deviation. If such point is not found or x and y have different lengths the function returns zero.

Bio.phenotype.pm_fitting.guess_plateau(x, y)

  Given two axes returns a guess of the plateau point.

  The plateau point is defined as the x point where the y point is near one standard deviation of the differences between the y points to the maximum y value. If such point is not found or x and y have different lengths the function returns zero.

Bio.phenotype.pm_fitting.fit(function, x, y)

  Fit the provided function to the x and y values.

  The function parameters and the parameters covariance.

Bio.phenotype.pm_fitting.get_area(y, x)

  Get the area under the curve.

Biopython v: 1.86

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