diff fitted_model_eval.py @ 9:364234f65507 draft

planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb

--- a/fitted_model_eval.py	Thu Aug 11 09:22:41 2022 +0000
+++ b/fitted_model_eval.py	Wed Aug 09 13:28:32 2023 +0000
@@ -3,11 +3,11 @@
 import warnings
 
 import pandas as pd
-from galaxy_ml.utils import get_scoring, load_model, read_columns
+from galaxy_ml.model_persist import load_model_from_h5
+from galaxy_ml.utils import clean_params, get_scoring, read_columns
 from scipy.io import mmread
-from sklearn.metrics.scorer import _check_multimetric_scoring
+from sklearn.metrics._scorer import _check_multimetric_scoring
 from sklearn.model_selection._validation import _score
-from sklearn.pipeline import Pipeline
 
 
 def _get_X_y(params, infile1, infile2):
@@ -75,7 +75,12 @@
         loaded_df[df_key] = infile2
 
     y = read_columns(
-        infile2, c=c, c_option=column_option, sep="\t", header=header, parse_dates=True
+        infile2,
+        c=c,
+        c_option=column_option,
+        sep="\t",
+        header=header,
+        parse_dates=True,
     )
     if len(y.shape) == 2 and y.shape[1] == 1:
         y = y.ravel()
@@ -83,14 +88,7 @@
     return X, y
 
 
-def main(
-    inputs,
-    infile_estimator,
-    outfile_eval,
-    infile_weights=None,
-    infile1=None,
-    infile2=None,
-):
+def main(inputs, infile_estimator, outfile_eval, infile1=None, infile2=None):
     """
     Parameter
     ---------
@@ -103,9 +101,6 @@
     outfile_eval : str
         File path to save the evalulation results, tabular
 
-    infile_weights : str
-        File path to weights input
-
     infile1 : str
         File path to dataset containing features
 
@@ -120,40 +115,20 @@
     X_test, y_test = _get_X_y(params, infile1, infile2)
 
     # load model
-    with open(infile_estimator, "rb") as est_handler:
-        estimator = load_model(est_handler)
-
-    main_est = estimator
-    if isinstance(estimator, Pipeline):
-        main_est = estimator.steps[-1][-1]
-    if hasattr(main_est, "config") and hasattr(main_est, "load_weights"):
-        if not infile_weights or infile_weights == "None":
-            raise ValueError(
-                "The selected model skeleton asks for weights, "
-                "but no dataset for weights was provided!"
-            )
-        main_est.load_weights(infile_weights)
+    estimator = load_model_from_h5(infile_estimator)
+    estimator = clean_params(estimator)
 
     # handle scorer, convert to scorer dict
-    # Check if scoring is specified
     scoring = params["scoring"]
-    if scoring is not None:
-        # get_scoring() expects secondary_scoring to be a comma separated string (not a list)
-        # Check if secondary_scoring is specified
-        secondary_scoring = scoring.get("secondary_scoring", None)
-        if secondary_scoring is not None:
-            # If secondary_scoring is specified, convert the list into comman separated string
-            scoring["secondary_scoring"] = ",".join(scoring["secondary_scoring"])
-
     scorer = get_scoring(scoring)
-    scorer, _ = _check_multimetric_scoring(estimator, scoring=scorer)
+    if not isinstance(scorer, (dict, list)):
+        scorer = [scoring["primary_scoring"]]
+    scorer = _check_multimetric_scoring(estimator, scoring=scorer)
 
     if hasattr(estimator, "evaluate"):
-        scores = estimator.evaluate(
-            X_test, y_test=y_test, scorer=scorer, is_multimetric=True
-        )
+        scores = estimator.evaluate(X_test, y_test=y_test, scorer=scorer)
     else:
-        scores = _score(estimator, X_test, y_test, scorer, is_multimetric=True)
+        scores = _score(estimator, X_test, y_test, scorer)
 
     # handle output
     for name, score in scores.items():
@@ -167,7 +142,6 @@
     aparser = argparse.ArgumentParser()
     aparser.add_argument("-i", "--inputs", dest="inputs", required=True)
     aparser.add_argument("-e", "--infile_estimator", dest="infile_estimator")
-    aparser.add_argument("-w", "--infile_weights", dest="infile_weights")
     aparser.add_argument("-X", "--infile1", dest="infile1")
     aparser.add_argument("-y", "--infile2", dest="infile2")
     aparser.add_argument("-O", "--outfile_eval", dest="outfile_eval")
@@ -177,7 +151,6 @@
         args.inputs,
         args.infile_estimator,
         args.outfile_eval,
-        infile_weights=args.infile_weights,
         infile1=args.infile1,
         infile2=args.infile2,
     )