moocore.eaf

moocore.eaf(data, /, percentiles=[])

Compute the Empirical attainment function (EAF) in 2D or 3D.

Parameters:

• data (numpy array) – Numpy array of numerical values and set numbers, containing multiple sets. For example the output of the read_datasets() function

• percentiles (list, default: []) – List indicating which percentiles are computed. By default, all possible percentiles are calculated.

Returns:

numpy array – Returns a numpy array containing the EAF data points, with the same number of columns as the input argument, but a different number of rows. The last column represents the EAF percentile for that data point

Examples

>>> x = moocore.get_dataset("input1.dat")
>>> moocore.eaf(x)                                     
array([[  0.17470556,   8.89066343,  10.        ],
       [  0.20816431,   4.62275469,  10.        ],
       [  0.22997367,   1.11772205,  10.        ],
       [  0.58799475,   0.73891181,  10.        ],
       [  1.54506255,   0.38303122,  10.        ],
       [  8.57911868,   0.35169752,  10.        ],
       [  0.20816431,   8.89066343,  20.        ],
       [  0.2901393 ,   8.32259412,  20.        ],
       ...
       [  9.78758589,   2.8124162 ,  90.        ],
       [  1.13096306,   9.72645436, 100.        ],
       [  2.71891214,   8.84691923, 100.        ],
       [  3.34035397,   7.49376946, 100.        ],
       [  4.43498452,   6.94327481, 100.        ],
       [  4.96525837,   6.20957074, 100.        ],
       [  7.92511295,   3.92669598, 100.        ]])

>>> moocore.eaf(x, percentiles = [0, 50, 100])         
array([[  0.17470556,   8.89066343,   0.        ],
       [  0.20816431,   4.62275469,   0.        ],
       [  0.22997367,   1.11772205,   0.        ],
       [  0.58799475,   0.73891181,   0.        ],
       [  1.54506255,   0.38303122,   0.        ],
       [  8.57911868,   0.35169752,   0.        ],
       [  0.53173087,   9.73244829,  50.        ],
       [  0.62230271,   9.02211752,  50.        ],
       [  0.79293574,   8.89066343,  50.        ],
       [  0.9017068 ,   8.32259412,  50.        ],
       [  0.97468676,   7.65893644,  50.        ],
       [  1.06855707,   7.49376946,  50.        ],
       [  1.54506255,   6.7102429 ,  50.        ],
       [  1.5964888 ,   5.98825094,  50.        ],
       [  2.16315952,   4.7394435 ,  50.        ],
       [  2.85891341,   4.49240941,  50.        ],
       [  3.34035397,   2.89377444,  50.        ],
       [  4.61023932,   2.87955367,  50.        ],
       [  4.96525837,   2.29231998,  50.        ],
       [  7.04694467,   1.83484358,  50.        ],
       [  9.7398055 ,   1.00153569,  50.        ],
       [  1.13096306,   9.72645436, 100.        ],
       [  2.71891214,   8.84691923, 100.        ],
       [  3.34035397,   7.49376946, 100.        ],
       [  4.43498452,   6.94327481, 100.        ],
       [  4.96525837,   6.20957074, 100.        ],
       [  7.92511295,   3.92669598, 100.        ]])