# HG changeset patch
# User bgruening
# Date 1695400223 0
# Node ID d37a7f17e35d797d83b78237fed0e95b664606e6
# Parent 1ddf415cb3491937927ff7723ebd049f1c146f79
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 3c1e6c72303cfd8a5fd014734f18402b97f8ecb5
diff -r 1ddf415cb349 -r d37a7f17e35d ml_visualization_ex.py
--- a/ml_visualization_ex.py Wed Aug 09 13:33:12 2023 +0000
+++ b/ml_visualization_ex.py Fri Sep 22 16:30:23 2023 +0000
@@ -15,6 +15,7 @@
from sklearn.metrics import (
auc,
average_precision_score,
+ confusion_matrix,
precision_recall_curve,
roc_curve,
)
@@ -258,6 +259,30 @@
os.rename(os.path.join(folder, "output.svg"), os.path.join(folder, "output"))
+def get_dataframe(file_path, plot_selection, header_name, column_name):
+ header = "infer" if plot_selection[header_name] else None
+ column_option = plot_selection[column_name]["selected_column_selector_option"]
+ if column_option in [
+ "by_index_number",
+ "all_but_by_index_number",
+ "by_header_name",
+ "all_but_by_header_name",
+ ]:
+ col = plot_selection[column_name]["col1"]
+ else:
+ col = None
+ _, input_df = read_columns(
+ file_path,
+ c=col,
+ c_option=column_option,
+ return_df=True,
+ sep="\t",
+ header=header,
+ parse_dates=True,
+ )
+ return input_df
+
+
def main(
inputs,
infile_estimator=None,
@@ -271,6 +296,10 @@
targets=None,
fasta_path=None,
model_config=None,
+ true_labels=None,
+ predicted_labels=None,
+ plot_color=None,
+ title=None,
):
"""
Parameter
@@ -311,6 +340,18 @@
model_config : str, default is None
File path to dataset containing JSON config for neural networks
+
+ true_labels : str, default is None
+ File path to dataset containing true labels
+
+ predicted_labels : str, default is None
+ File path to dataset containing true predicted labels
+
+ plot_color : str, default is None
+ Color of the confusion matrix heatmap
+
+ title : str, default is None
+ Title of the confusion matrix heatmap
"""
warnings.simplefilter("ignore")
@@ -534,6 +575,36 @@
return 0
+ elif plot_type == "classification_confusion_matrix":
+ plot_selection = params["plotting_selection"]
+ input_true = get_dataframe(
+ true_labels, plot_selection, "header_true", "column_selector_options_true"
+ )
+ header_predicted = "infer" if plot_selection["header_predicted"] else None
+ input_predicted = pd.read_csv(
+ predicted_labels, sep="\t", parse_dates=True, header=header_predicted
+ )
+ true_classes = input_true.iloc[:, -1].copy()
+ predicted_classes = input_predicted.iloc[:, -1].copy()
+ axis_labels = list(set(true_classes))
+ c_matrix = confusion_matrix(true_classes, predicted_classes)
+ fig, ax = plt.subplots(figsize=(7, 7))
+ im = plt.imshow(c_matrix, cmap=plot_color)
+ for i in range(len(c_matrix)):
+ for j in range(len(c_matrix)):
+ ax.text(j, i, c_matrix[i, j], ha="center", va="center", color="k")
+ ax.set_ylabel("True class labels")
+ ax.set_xlabel("Predicted class labels")
+ ax.set_title(title)
+ ax.set_xticks(axis_labels)
+ ax.set_yticks(axis_labels)
+ fig.colorbar(im, ax=ax)
+ fig.tight_layout()
+ plt.savefig("output.png", dpi=125)
+ os.rename("output.png", "output")
+
+ return 0
+
# save pdf file to disk
# fig.write_image("image.pdf", format='pdf')
# fig.write_image("image.pdf", format='pdf', width=340*2, height=226*2)
@@ -553,6 +624,10 @@
aparser.add_argument("-t", "--targets", dest="targets")
aparser.add_argument("-f", "--fasta_path", dest="fasta_path")
aparser.add_argument("-c", "--model_config", dest="model_config")
+ aparser.add_argument("-tl", "--true_labels", dest="true_labels")
+ aparser.add_argument("-pl", "--predicted_labels", dest="predicted_labels")
+ aparser.add_argument("-pc", "--plot_color", dest="plot_color")
+ aparser.add_argument("-pt", "--title", dest="title")
args = aparser.parse_args()
main(
@@ -568,4 +643,8 @@
targets=args.targets,
fasta_path=args.fasta_path,
model_config=args.model_config,
+ true_labels=args.true_labels,
+ predicted_labels=args.predicted_labels,
+ plot_color=args.plot_color,
+ title=args.title,
)
diff -r 1ddf415cb349 -r d37a7f17e35d pdb70_cs219.ffdata
--- a/pdb70_cs219.ffdata Wed Aug 09 13:33:12 2023 +0000
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,189 +0,0 @@
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