mpa.EvaluateModel¶
Usage¶
>>> import mpathic as mpa
>>> model = mpa.io.load_model("./mpathic/data/sortseq/full-0/crp_model.txt")
>>> dataset = mpa.io.load_dataset("./mpathic/data/sortseq/full-0/data.txt")
>>> mpa.EvaluateModel(dataset_df = dataset, model_df = model)
Example Input and Output¶
Example Input Table:
pos val_A val_C val_G val_T
3 -0.070101 -0.056502 0.184170 -0.057568
4 -0.045146 -0.042017 0.172377 -0.085214
5 -0.035447 0.006974 0.059453 -0.030979
6 -0.037837 -0.000299 0.079747 -0.041611
7 -0.110627 -0.054740 0.066257 0.099110
...
Example Output Table:
output:
0 0.348108
1 -0.248134
2 0.009507
3 0.238852
4 -0.112121
5 -0.048588
...
Class Details¶
-
class
evaluate_model.
EvaluateModel
(**kwargs)¶ Parameters: - dataset_df: (pandas dataframe)
Input dataset data frame
- model_df: (pandas dataframe)
Model dataframe
- left: (int)
Seq position at which to align the left-side of the model.
Defaults to position determined by model dataframe.
- right: (int)
Seq position at which to align the right-side of the model.
Defaults to position determined by model dataframe.