qbiocode.data_generation.make_s_curve module#

Summary#

Functions:

my_make_s_curve

This function generates a series of 'S-curve' data sets.

Reference#

my_make_s_curve(n_samples=[100, 120, 140, 160, 180, 200, 220, 240, 260, 280], noise=[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9], save_path=None)[source]#

This function generates a series of ‘S-curve’ data sets. It uses itertools to generate a range of input arguments to pass into the sklearn make_s_curve function. A data set is generated for each set of input arguments, which allows the function to produce a variety of different S-curves based on varying number of samples (n_samples) and noise.

Parameters:

  • n_samples – list of integers The number of sample points on the Swiss Roll.

  • noise – list of floats The standard deviation of the gaussian noise.

Returns:

Dataset in pandas dataframe with samples in the first column, features in the middle columns, and

labels in the last column.

Return type:

df (pandas.DataFrame)