Spaces:
Running
Running
Commit
·
16e804d
1
Parent(s):
9ecd5cd
Minor Tweak to Filter Shchool Subsets
Browse files
app.py
CHANGED
@@ -1048,7 +1048,19 @@ def run_model(model_name):
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# -------------------------------------------------------------------------
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# 4. Cálculo de distancias y scatter plot: Distance vs F1 (usando PC1 y PC2 globales)
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model_options = [
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model_options_with_default = [""]
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model_options_with_default.extend(model_options)
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@@ -1269,13 +1281,15 @@ def run_model(model_name):
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'label': df_heatmap['name']
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})
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invisible_renderer = heatmap_fig.circle('x', 'y', size=10, source=source_points, fill_alpha=0, line_alpha=0.5)
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-
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if select_extra_dataset_hm != "-":
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df_extra = df_all["synthetic"][df_all["synthetic"]["source"] == select_extra_dataset_hm].copy()
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df_extra["x"] = df_extra[x_comp]
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df_extra["y"] = df_extra[y_comp]
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if 'name' not in df_extra.columns:
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df_extra["name"] = df_extra["img"].apply(lambda x: x.split("/")[-1].replace(".png", "") if isinstance(x, str) else x)
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source_extra_points = ColumnDataSource(data={
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'x': df_extra['x'],
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'y': df_extra['y'],
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# -------------------------------------------------------------------------
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# 4. Cálculo de distancias y scatter plot: Distance vs F1 (usando PC1 y PC2 globales)
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model_options = [
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"es-digital-paragraph-degradation-seq",
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"es-digital-line-degradation-seq",
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"es-digital-seq",
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"es-digital-rotation-degradation-seq",
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"es-digital-zoom-degradation-seq",
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"es-render-seq",
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"es-digital-seq_filtered_deus",
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"es-digital-seq_filtered_liceo",
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"es-digital-seq_filtered_lusitano",
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"es-digital-seq_filtered_monterraso",
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"es-digital-seq_filtered_patria"
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]
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model_options_with_default = [""]
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model_options_with_default.extend(model_options)
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'label': df_heatmap['name']
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})
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invisible_renderer = heatmap_fig.circle('x', 'y', size=10, source=source_points, fill_alpha=0, line_alpha=0.5)
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# school = "patria"
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if select_extra_dataset_hm != "-":
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df_extra = df_all["synthetic"][df_all["synthetic"]["source"] == select_extra_dataset_hm].copy()
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df_extra["x"] = df_extra[x_comp]
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df_extra["y"] = df_extra[y_comp]
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if 'name' not in df_extra.columns:
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df_extra["name"] = df_extra["img"].apply(lambda x: x.split("/")[-1].replace(".png", "") if isinstance(x, str) else x)
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# mask = df_extra["name"].str.contains(school, case=False, na=False)
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# df_extra = df_extra[mask].copy()
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source_extra_points = ColumnDataSource(data={
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'x': df_extra['x'],
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'y': df_extra['y'],
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