Lukas Prause
2 years ago
2 changed files with 2 additions and 2 deletions
+ 1
- 1
plot_single_transmission_timeline.py
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| cmap = matplotlib.cm.get_cmap("Set3") | cmap = matplotlib.cm.get_cmap("Set3") | ||||
| unique_cells = transmission_df["cell_color"].unique() | unique_cells = transmission_df["cell_color"].unique() | ||||
| color_list = cmap * (round(len(unique_cells) / len(cmap)) + 1) | |||||
| color_list = cmap.colors * (round(len(unique_cells) / len(cmap.colors)) + 1) | |||||
| for c in transmission_df["cell_color"].unique(): | for c in transmission_df["cell_color"].unique(): | ||||
| bounds = transmission_df[["index", "cell_color"]].groupby("cell_color").agg(["min", "max"]).loc[c] | bounds = transmission_df[["index", "cell_color"]].groupby("cell_color").agg(["min", "max"]).loc[c] |
+ 1
- 1
plot_transmission_timeline.py
View File
| cmap = matplotlib.cm.get_cmap("Set3") | cmap = matplotlib.cm.get_cmap("Set3") | ||||
| unique_cells = transmission_df["cell_color"].unique() | unique_cells = transmission_df["cell_color"].unique() | ||||
| color_list = cmap * (round(len(unique_cells) / len(cmap)) + 1) | |||||
| color_list = cmap.colors * (round(len(unique_cells) / len(cmap.colors)) + 1) | |||||
| for c in transmission_df["cell_color"].unique(): | for c in transmission_df["cell_color"].unique(): | ||||
| bounds = transmission_df[["index", "cell_color"]].groupby("cell_color").agg(["min", "max"]).loc[c] | bounds = transmission_df[["index", "cell_color"]].groupby("cell_color").agg(["min", "max"]).loc[c] |
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