From 5976e85e28995bb7e69634eab8371a699f07b263 Mon Sep 17 00:00:00 2001
From: Alex Rubinsteyn <alex.rubinsteyn@gmail.com>
Date: Thu, 23 Jun 2016 16:15:42 -0400
Subject: [PATCH] added missing plotting module
---
mhcflurry/plotting.py | 85 +++++++++++++++++++++++++++++++++++++++++++
1 file changed, 85 insertions(+)
create mode 100644 mhcflurry/plotting.py
diff --git a/mhcflurry/plotting.py b/mhcflurry/plotting.py
new file mode 100644
index 00000000..6be12a41
--- /dev/null
+++ b/mhcflurry/plotting.py
@@ -0,0 +1,85 @@
+# Copyright (c) 2015-2016. Mount Sinai School of Medicine
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import seaborn
+from matplotlib import pyplot
+from matplotlib import rc
+import numpy as np
+
+def plot_nsamples_vs_metrics_with_imputation(
+ results_df,
+ base_filename,
+ metrics=["auc", "f1", "tau"],
+ titles={
+ "tau": "Kendall's $\\tau$",
+ "auc": "AUC",
+ "f1": "$F_1$ score",
+ },
+ figsize=(6.5, 3.5),
+ groupby_columns=["num_samples", "impute"],
+ dpi=None):
+
+ pyplot.figure(figsize=figsize)
+ seaborn.set_style("whitegrid")
+
+ for (j, score_name) in enumerate(metrics):
+ ax = pyplot.subplot2grid((1, 4), (0, j))
+ groups = results_df.groupby(groupby_columns)
+ groups_score = groups[score_name].mean().to_frame().reset_index()
+ groups_score["std_error"] = \
+ groups[score_name].std().to_frame().reset_index()[score_name]
+
+ for impute in [True, False]:
+ sub = groups_score[groups_score.impute == impute]
+ color = seaborn.get_color_cycle()[0] if impute else seaborn.get_color_cycle()[1]
+ pyplot.errorbar(
+ x=sub.num_samples.values,
+ y=sub[score_name].values,
+ yerr=sub.std_error.values,
+ label=("with" if impute else "without") + " imputation",
+ color=color)
+ if j == 1:
+ pyplot.xlabel("Training set size")
+ pyplot.xscale("log")
+ pyplot.title(titles[score_name])
+
+ if score_name == "auc":
+ pyplot.ylim(ymin=0.5, ymax=1.0)
+ if score_name == "f1":
+ pyplot.ylim(ymin=0, ymax=1)
+ if score_name == "tau":
+ pyplot.ylim(ymin=0, ymax=0.6)
+ pyplot.yticks(np.arange(0, 0.61, 0.15))
+
+ pyplot.legend(
+ bbox_to_anchor=(1.1, 1),
+ loc=2,
+ borderaxespad=0.,
+ fancybox=True,
+ frameon=True,
+ fontsize="small")
+
+ pyplot.tight_layout()
+
+ if dpi:
+ rc("savefig", dpi=dpi)
+
+ # Put the legend out of the figure
+ image_filename = base_filename + ".png"
+ print("Writing PNG to %s" % image_filename)
+ pyplot.savefig(image_filename)
+
+ pdf_filename = base_filename + ".pdf"
+ print("Writing PDF to %s" % pdf_filename)
+ pyplot.savefig(pdf_filename)
--
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