Datashader Heatmap Visualization Function #330
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Add layer information in histogram title
…he import of unneccesary libraries
georgezakinih
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georgezakinih
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@LizaShch @ThomasSheeley , Thanks for the PR. I left few comments.
src/spac/visualization.py
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| for i, cat in enumerate(categories): | ||
| subset = coords[coords["labels"] == cat] | ||
| canvas = ds.Canvas( |
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@LizaShch, consider combining this the code at line 133 using the "partial" construct in python. This way, when you edit it, it will be edited once.
| # Fixed categorical labels to ensure representation of each category | ||
| fixed_labels = ['A', 'B', 'C', 'A', 'B', 'C', 'A', 'B', 'C', 'A'] | ||
| self.labels_categorical = pd.Series(fixed_labels, dtype="category") | ||
| self.labels_continuous = pd.Series(np.random.rand(10)) |
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@LizaShch , what do you do with teh continuous labels?
| heatmap_datashader(self.x, self.y, labels=wrong_labels) | ||
| self.assertIn("Labels length should match x and y length", str(context_manager.exception)) | ||
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| def test_valid_input_returns_figure(self): |
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@LizaShch, would you please add a case with number of labels not multiple of 3?
| # There should be as many subplots as unique labels (3 in this case) | ||
| num_axes = len(fig.axes) | ||
| expected_axes = self.labels_categorical.nunique() | ||
| self.assertEqual(num_axes, expected_axes) |
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@LizaShch, any other assertion you can add to make sure the plot got generated correctly besides the number of axes? For example, the content of the plot?
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| def heatmap_datashader(x, y, labels=None, theme=None, | ||
| x_axis_title="Component 1", y_axis_title="Component 2", | ||
| plot_title=None, **kwargs): |
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@LizaShch, can we use kwargs to pass optional arguments to ds.Canvas to control the figure? This way, you don't need to explicty control only for plot width and plot height, but for all other input argument that function would tak.
ying39purdue
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ying39purdue
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@georgezakinih I added a few formatting additions and Liza's previous commit resolved the previous comments
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Summary:
This pull request includes changes to src/spac/visualization.py file to creating a new heatmap function using the package datashader. There is an option to facet plots by annotation as well. A rest file tests/test_visualization/test_datashader.py was added as well to ensure proper functionality.
Changes: