Wordcloud integration (#43)

* wordcloud integration

* linting

* lint

* lint

bin/create_wordcloud.py

@@ -0,0 +1,83 @@
+#!/usr/bin/env python
+
+import argparse
+
+import matplotlib.pyplot as plt
+import numpy as np
+import pandas as pd
+from PIL import Image
+from wordcloud import WordCloud
+
+
+def get_wordcloud(community_tool_path: str, mask_figure: str, stats_column: str, wordcloud_output_path: str) -> None:
+    """
+    Generate a wordcloud based on the counts for each Galaxy wrapper id
+
+    :param community_tool_path: Dataframe that must
+        have the columns "Galaxy wrapper id" and `stats_column`
+    :param mask_figure: a figure that is used to render the wordcloud
+        E.g. a nice shape to highlight your community
+    :param stats_column: Column name of the
+        column with usage statistics in the table
+    :param wordcloud_output_path: Path to store the wordcloud
+    """
+
+    community_tool_stats = pd.read_csv(community_tool_path, sep="\t")
+
+    assert (
+        stats_column in community_tool_stats
+    ), f"Stats column: {stats_column} not found in table!"  # check if the stats column is there
+
+    # create the word cloud
+    frec = pd.Series(
+        community_tool_stats[stats_column].values, index=community_tool_stats["Galaxy wrapper id"]
+    ).to_dict()
+
+    mask = np.array(Image.open(mask_figure))
+    mask[mask == 0] = 255  # set 0 in array to 255 to work with wordcloud
+
+    wc = WordCloud(
+        mask=mask,
+        background_color="rgba(255, 255, 255, 0)",
+        random_state=42,
+    )
+
+    wc.generate_from_frequencies(frec)
+
+    fig, ax = plt.subplots(figsize=(13, 5))
+    ax.imshow(wc)
+
+    plt.axis("off")
+    plt.tight_layout(pad=0)
+
+    plt.savefig(wordcloud_output_path)
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description="Create wordcloud from \
+            TSV file based on Galaxy usage statistics"
+    )
+    parser.add_argument(
+        "--table",
+        "-ta",
+        required=True,
+        help="Path to TSV file with tools and stats",
+    )
+    parser.add_argument(
+        "--stats_column",
+        "-sc",
+        required=True,
+        help="Name of the column with usage statistics",
+    )
+    parser.add_argument(
+        "--output",
+        "-out",
+        required=True,
+        help="Path to HTML output",
+    )
+
+    parser.add_argument("--wordcloud_mask", "-wcm", required=False, help="Mask figure to generate the wordcloud")
+
+    args = parser.parse_args()
+    get_wordcloud(args.table, args.wordcloud_mask, args.stats_column, args.output)

bin/extract_all_tools_downstream.sh

@@ -5,4 +5,10 @@ mkdir -p 'results/'
 python bin/create_interactive_table.py \
         --table "results/all_tools.tsv" \
         --template "data/interactive_table_template.html" \
-        --output "results/index.html"
+        --output "results/index.html"
+
+python bin/create_wordcloud.py \
+        --table "results/all_tools.tsv" \
+        --wordcloud_mask "data/usage_stats/wordcloud_mask.png" \
+        --output "results/all_tools_wordcloud.png" \
+        --stats_column "https://usegalaxy.eu usage"

bin/get_community_tools.sh

@@ -35,5 +35,11 @@ for com_data_fp in data/communities/* ; do
                         --template "data/interactive_table_template.html" \
                         --output "results/$community/index.html"
 
+                python bin/create_wordcloud.py \
+                        --table  "results/$community/tools.tsv" \
+                        --wordcloud_mask "data/usage_stats/wordcloud_mask.png" \
+                        --output "results/$community/tools_wordcloud.png" \
+                        --stats_column "https://usegalaxy.eu usage"
+
   fi;
 done

requirements.txt

@@ -1,3 +1,7 @@
 pandas
 PyGithub
-pyyaml
+pyyaml
+numpy
+PIL
+matplotlib
+wordcloud