added streamlit utils for streamlit sake

iderare_pheno/streamlit_utils.py

@@ -0,0 +1,78 @@
+import os
+from datetime import datetime
+
+import pandas as pd
+import scipy.cluster
+import yaml
+from matplotlib import pyplot as plt
+
+iderare_template = os.path.join(os.path.dirname(__file__), "templates", "template_iderare.yml")
+
+
+# Fill template_iderare.yml with the given phenotype
+def generate_yml(hpo_sets):
+    with open(iderare_template, "r") as f:
+        y = yaml.safe_load(f)
+        y["analysis"]["hpo_ids"] = hpo_sets
+
+    yaml_str = yaml.dump(y, default_flow_style=False, sort_keys=False)
+    return yaml_str
+
+
+# Convert data(s) to dataframe
+def list2tsv(
+    term_id,
+    name,
+    sim_score=None,
+):
+    if sim_score is None:
+        data = {"id": term_id, "name": name}
+    else:
+        rank = [i + 1 for i in range(len(name))]
+        data = {"rank": rank, "id": term_id, "name": name, "score": sim_score}
+    df = pd.DataFrame(data)
+    return df.to_csv(index=False, sep="\t")
+
+
+# Print the dendrogram tree
+def linkage_dendrogram(linkage, labels, title="Similarity", threshold=0.3, path_to_save=None):
+    if len(linkage) == 0:
+        print("Linkage is empty. The data not possible due to blank linkage information.")
+        return
+    plt.figure(figsize=(20, len(linkage)))
+    scipy.cluster.hierarchy.dendrogram(
+        linkage,
+        labels=labels,
+        show_contracted=True,
+        leaf_font_size=plt.rcParams["font.size"] * 1.5,
+        color_threshold=threshold,
+        orientation="right",
+    )
+    plt.title(title, fontsize=plt.rcParams["font.size"] * 2)
+
+    plt.axvline(x=threshold, c="r", lw=2, linestyle="--")
+    plt.text(
+        threshold,
+        0,
+        "Similarity Threshold",
+        fontsize=plt.rcParams["font.size"] * 1.5,
+        va="bottom",
+        ha="center",
+        color="r",
+    )
+    plt.xlim(0, 1.0)
+    plt.xlabel("Distance", fontsize=plt.rcParams["font.size"] * 2)
+    plt.ylabel("Disease", fontsize=plt.rcParams["font.size"] * 2)
+    plt.tight_layout()
+
+    if not os.path.exists("output"):
+        os.makedirs("output")
+        print("Folder output created.")
+    else:
+        print("Folder output already exists.")
+
+    if path_to_save is None:
+        path_to_save = "output/{date_time}_{title}.png".format(
+            date_time=datetime.now().strftime("%Y%m%d_%H%M%S"), title=title[0:30]
+        )
+    plt.savefig(path_to_save)

iderare_pheno/version.py

@@ -1,5 +1,5 @@
 _MAJOR = "0"
-_MINOR = "4"
+_MINOR = "5"
 # On main and in a nightly release the patch should be one ahead of the last
 # released build.
 _PATCH = "0"

pyproject.toml

@@ -9,7 +9,7 @@ dynamic = ["version"]
 readme = "README.md"
 classifiers = [
     "Intended Audience :: Science/Research",
-    "Development Status :: 4 - Beta",
+    "Development Status :: 5 - Production/Stable",
     "License :: OSI Approved :: BSD License",
     "Programming Language :: Python :: 3",
     "Topic :: Scientific/Engineering :: Medical Science Apps.",