From c921334481a34a608cced85887ef1aef3c610736 Mon Sep 17 00:00:00 2001 From: Zargham Ahmad Date: Tue, 31 Oct 2023 14:18:21 +0100 Subject: [PATCH] updated boxplot --- .../chemical_composition_boxplot.ipynb | 55 ++++++------------- 1 file changed, 18 insertions(+), 37 deletions(-) diff --git a/analysis/Python_scripts/chemical_composition_boxplot.ipynb b/analysis/Python_scripts/chemical_composition_boxplot.ipynb index 04ab0fc..162da33 100644 --- a/analysis/Python_scripts/chemical_composition_boxplot.ipynb +++ b/analysis/Python_scripts/chemical_composition_boxplot.ipynb @@ -21,7 +21,7 @@ "metadata": {}, "outputs": [], "source": [ - "top5 = pd.read_csv(\"../data/output_matching/matchms/matchms_tol_0.01_1%I_top5.tsv\", sep='\\t')" + "top5 = pd.read_csv(\"../data/output_matching/matchms/matchms_tol_0.01_1%I_top5_with_0s.tsv\", sep='\\t')" ] }, { @@ -33,20 +33,19 @@ "name": "stderr", "output_type": "stream", "text": [ - "[14:23:27] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", - "[14:23:27] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", - "[14:23:27] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", - "[14:23:27] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", - "[14:23:28] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", - "[14:23:28] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", - "[14:23:28] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", - "[14:23:28] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", - "[14:23:29] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", - "[14:23:29] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", - "[14:23:29] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", - "[14:23:29] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", - "[14:23:30] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", - "[14:23:30] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n" + "[14:03:57] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", + "[14:03:57] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", + "[14:03:57] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", + "[14:03:57] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", + "[14:03:57] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", + "[14:03:57] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", + "[14:03:57] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", + "[14:03:57] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", + "[14:03:58] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", + "[14:03:58] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", + "[14:03:58] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", + "[14:03:58] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n", + "[14:03:58] Skipping unrecognized collection type at line 48576: MDLV30/STERAC1 BONDS=(1 7)\n" ] } ], @@ -64,27 +63,9 @@ "execution_count": 4, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/hechth/micromamba/envs/rms/lib/python3.10/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n", - " if pd.api.types.is_categorical_dtype(vector):\n", - "/home/hechth/micromamba/envs/rms/lib/python3.10/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n", - " if pd.api.types.is_categorical_dtype(vector):\n", - "/home/hechth/micromamba/envs/rms/lib/python3.10/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n", - " if pd.api.types.is_categorical_dtype(vector):\n", - "/home/hechth/micromamba/envs/rms/lib/python3.10/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n", - " if pd.api.types.is_categorical_dtype(vector):\n", - "/home/hechth/micromamba/envs/rms/lib/python3.10/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n", - " if pd.api.types.is_categorical_dtype(vector):\n", - "/home/hechth/micromamba/envs/rms/lib/python3.10/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n", - " if pd.api.types.is_categorical_dtype(vector):\n" - ] - }, { "data": { - "image/png": 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", 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" ] @@ -134,9 +115,9 @@ "ax.xaxis.labelpad = 10\n", "\n", "# Add x-axis labels with group sizes\n", - "grouped_df = merged_top5_same.groupby('true_names')['query'].apply(list).reset_index(name='queries')\n", - "xticklabels = [f\"{group} ({len(x)})\" for group, x in grouped_df.values]\n", - "ax.set_xticklabels(xticklabels, rotation=90, ha='right')\n", + "#grouped_df = merged_top5_same.groupby('true_names')['query'].apply(list).reset_index(name='queries')\n", + "#xticklabels = [f\"{group} ({len(x)})\" for group, x in grouped_df.values]\n", + "#ax.set_xticklabels(xticklabels, rotation=90, ha='right')\n", "\n", "ax2.legend_.remove()\n", "ax2.set_ylim([0, 1.2]) # Set y-axis limits\n",