Add longitudinal trends for subset of subjects #64
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melhemr
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AbdulkadirA
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@melhemr Thanks for the updates. I recommend not to compute DXsimple in the toolbox as this is too specific. Instead, pick a column and plot that one. Could also simply be Diagnosis_nearest_2.0 for now. Make sure to remove unused categories.
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BrainChart/plotcanvas.py
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| palette = dict(MCI="orangered", AD="crimson",CN="indigo",none="slategrey",other="gold") | ||
| ax = sns.scatterplot(x='Age',y=currentROI,hue=currentHue,ax=self.axes,edgecolor=data_sample["DX_simple"].map(palette),linewidth=1.5,s=50,data=data_sample) |
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| palette = dict(MCI="orangered", AD="crimson",CN="indigo",none="slategrey",other="gold") | |
| ax = sns.scatterplot(x='Age',y=currentROI,hue=currentHue,ax=self.axes,edgecolor=data_sample["DX_simple"].map(palette),linewidth=1.5,s=50,data=data_sample) | |
| ax = sns.scatterplot(x='Age',y=currentROI,hue=currentHue,ax=self.axes, linewidth=1.5,s=50,data=data_sample) |
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How would I show diagnosis on the plot if these are not included?
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The line with the scatterplot will still be included, but the edge color is not fixed.
README.md
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| @@ -3,7 +3,7 @@ | |||
| After proper installation, the tools can be used as follows | |||
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| ```shell | |||
| python -m BrainChart.main --data_file istaging.pkl.gz --harmonization_model_file MUSE_harmonization_model.pkl | |||
| python -m BrainChart.main --data_file reduced_istaging.pkl.gz --harmonization_model_file MUSE_harmonization_model_sprint_in.pkl | |||
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Please undo this change to keep the default at the full data set and the default harmonization model.
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BrainChart/plotcanvas.py
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| markers = [plt.Line2D([0,0],[0,0],color=color, marker='o', linestyle='') for color in palette.values()] | ||
| dx_legend = ax.legend(markers, palette.keys(), numpoints=1,loc='lower right') | ||
| ax.add_artist(dx_legend) |
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AbdulkadirA
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