Categorical Data is incorrectly colored in the legend when plotting #214

Description

@srivarra

When using pl.render_labels with the color and palette parameter, the legends are incorrectly colored.

Example Plot:
NBL-25-R2C8--Diagnosis--incorrect

Here we see that the Dot plot from scanpy counts 1.1K cells in the cluster NBL_9 and colors them with pastel green (correct color). However on the spatialdata plots, cluster NBL_11 is pastel green, when it should be NBL_9. The colors on the spatialdata image itself are not wrong, it is the colors on the legend which are incorrect.

This issue is occurs in pl.utils._get_palette, where the values in thecategories gets mapped to the colors of the palette. However in scanpy it's the categories of the DataFrame which get mapped to the colors.

By adjusting the following line from

returndict(zip(categories, palette))

to dict(zip(categories.categories, palette)) we get the correct legend-color mapping.

NBL-25-R2C8--Diagnosis--correct

Reproducible Example - MIBITOF dataset

importspatialdataassdimportspatialdata_plotimportmatplotlib.pyplotaspltfrompathlibimportPathmibitof_sd=sd.read_zarr(Path("~/Downloads/data.zarr").expanduser())
fig, axes=plt.subplots(nrows=1, ncols=2, figsize=(18, 8), layout="tight")
mibitof_sd.pp.get_elements("point8_labels").pl.render_labels(color="Cluster").pl.show(
ax=axes[0]
)
mibitof_sd.pp.get_elements("point8_labels").pl.render_labels(
color="Cluster", palette=["blue"], groups=["Epithelial"]
).pl.show(ax=axes[1])
fig

Generated Plot: Here Imm_other in the legend actually represents the Epithelial cells.
point8_labels

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    Skip to content

    Categorical Data is incorrectly colored in the legend when plotting #214

    Description

    @srivarra

    When using pl.render_labels with the color and palette parameter, the legends are incorrectly colored.

    Example Plot:
    NBL-25-R2C8--Diagnosis--incorrect

    Here we see that the Dot plot from scanpy counts 1.1K cells in the cluster NBL_9 and colors them with pastel green (correct color). However on the spatialdata plots, cluster NBL_11 is pastel green, when it should be NBL_9. The colors on the spatialdata image itself are not wrong, it is the colors on the legend which are incorrect.

    This issue is occurs in pl.utils._get_palette, where the values in thecategories gets mapped to the colors of the palette. However in scanpy it's the categories of the DataFrame which get mapped to the colors.

    By adjusting the following line from

    returndict(zip(categories, palette))

    to dict(zip(categories.categories, palette)) we get the correct legend-color mapping.

    NBL-25-R2C8--Diagnosis--correct

    Reproducible Example - MIBITOF dataset

    importspatialdataassdimportspatialdata_plotimportmatplotlib.pyplotaspltfrompathlibimportPathmibitof_sd=sd.read_zarr(Path("~/Downloads/data.zarr").expanduser())
    fig, axes=plt.subplots(nrows=1, ncols=2, figsize=(18, 8), layout="tight")
    mibitof_sd.pp.get_elements("point8_labels").pl.render_labels(color="Cluster").pl.show(
    ax=axes[0]
    )
    mibitof_sd.pp.get_elements("point8_labels").pl.render_labels(
    color="Cluster", palette=["blue"], groups=["Epithelial"]
    ).pl.show(ax=axes[1])
    fig

    Generated Plot: Here Imm_other in the legend actually represents the Epithelial cells.
    point8_labels

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      Skip to content

      Categorical Data is incorrectly colored in the legend when plotting #214

      Description

      @srivarra

      When using pl.render_labels with the color and palette parameter, the legends are incorrectly colored.

      Example Plot:
      NBL-25-R2C8--Diagnosis--incorrect

      Here we see that the Dot plot from scanpy counts 1.1K cells in the cluster NBL_9 and colors them with pastel green (correct color). However on the spatialdata plots, cluster NBL_11 is pastel green, when it should be NBL_9. The colors on the spatialdata image itself are not wrong, it is the colors on the legend which are incorrect.

      This issue is occurs in pl.utils._get_palette, where the values in thecategories gets mapped to the colors of the palette. However in scanpy it's the categories of the DataFrame which get mapped to the colors.

      By adjusting the following line from

      returndict(zip(categories, palette))

      to dict(zip(categories.categories, palette)) we get the correct legend-color mapping.

      NBL-25-R2C8--Diagnosis--correct

      Reproducible Example - MIBITOF dataset

      importspatialdataassdimportspatialdata_plotimportmatplotlib.pyplotaspltfrompathlibimportPathmibitof_sd=sd.read_zarr(Path("~/Downloads/data.zarr").expanduser())
      fig, axes=plt.subplots(nrows=1, ncols=2, figsize=(18, 8), layout="tight")
      mibitof_sd.pp.get_elements("point8_labels").pl.render_labels(color="Cluster").pl.show(
      ax=axes[0]
      )
      mibitof_sd.pp.get_elements("point8_labels").pl.render_labels(
      color="Cluster", palette=["blue"], groups=["Epithelial"]
      ).pl.show(ax=axes[1])
      fig

      Generated Plot: Here Imm_other in the legend actually represents the Epithelial cells.
      point8_labels

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        Skip to content

        Categorical Data is incorrectly colored in the legend when plotting #214

        Description

        @srivarra

        When using pl.render_labels with the color and palette parameter, the legends are incorrectly colored.

        Example Plot:
        NBL-25-R2C8--Diagnosis--incorrect

        Here we see that the Dot plot from scanpy counts 1.1K cells in the cluster NBL_9 and colors them with pastel green (correct color). However on the spatialdata plots, cluster NBL_11 is pastel green, when it should be NBL_9. The colors on the spatialdata image itself are not wrong, it is the colors on the legend which are incorrect.

        This issue is occurs in pl.utils._get_palette, where the values in thecategories gets mapped to the colors of the palette. However in scanpy it's the categories of the DataFrame which get mapped to the colors.

        By adjusting the following line from

        returndict(zip(categories, palette))

        to dict(zip(categories.categories, palette)) we get the correct legend-color mapping.

        NBL-25-R2C8--Diagnosis--correct

        Reproducible Example - MIBITOF dataset

        importspatialdataassdimportspatialdata_plotimportmatplotlib.pyplotaspltfrompathlibimportPathmibitof_sd=sd.read_zarr(Path("~/Downloads/data.zarr").expanduser())
        fig, axes=plt.subplots(nrows=1, ncols=2, figsize=(18, 8), layout="tight")
        mibitof_sd.pp.get_elements("point8_labels").pl.render_labels(color="Cluster").pl.show(
        ax=axes[0]
        )
        mibitof_sd.pp.get_elements("point8_labels").pl.render_labels(
        color="Cluster", palette=["blue"], groups=["Epithelial"]
        ).pl.show(ax=axes[1])
        fig

        Generated Plot: Here Imm_other in the legend actually represents the Epithelial cells.
        point8_labels

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          Skip to content

          Categorical Data is incorrectly colored in the legend when plotting #214

          Description

          @srivarra

          When using pl.render_labels with the color and palette parameter, the legends are incorrectly colored.

          Example Plot:
          NBL-25-R2C8--Diagnosis--incorrect

          Here we see that the Dot plot from scanpy counts 1.1K cells in the cluster NBL_9 and colors them with pastel green (correct color). However on the spatialdata plots, cluster NBL_11 is pastel green, when it should be NBL_9. The colors on the spatialdata image itself are not wrong, it is the colors on the legend which are incorrect.

          This issue is occurs in pl.utils._get_palette, where the values in thecategories gets mapped to the colors of the palette. However in scanpy it's the categories of the DataFrame which get mapped to the colors.

          By adjusting the following line from

          returndict(zip(categories, palette))

          to dict(zip(categories.categories, palette)) we get the correct legend-color mapping.

          NBL-25-R2C8--Diagnosis--correct

          Reproducible Example - MIBITOF dataset

          importspatialdataassdimportspatialdata_plotimportmatplotlib.pyplotaspltfrompathlibimportPathmibitof_sd=sd.read_zarr(Path("~/Downloads/data.zarr").expanduser())
          fig, axes=plt.subplots(nrows=1, ncols=2, figsize=(18, 8), layout="tight")
          mibitof_sd.pp.get_elements("point8_labels").pl.render_labels(color="Cluster").pl.show(
          ax=axes[0]
          )
          mibitof_sd.pp.get_elements("point8_labels").pl.render_labels(
          color="Cluster", palette=["blue"], groups=["Epithelial"]
          ).pl.show(ax=axes[1])
          fig

          Generated Plot: Here Imm_other in the legend actually represents the Epithelial cells.
          point8_labels

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            Skip to content

            Categorical Data is incorrectly colored in the legend when plotting #214

            Description

            @srivarra

            When using pl.render_labels with the color and palette parameter, the legends are incorrectly colored.

            Example Plot:
            NBL-25-R2C8--Diagnosis--incorrect

            Here we see that the Dot plot from scanpy counts 1.1K cells in the cluster NBL_9 and colors them with pastel green (correct color). However on the spatialdata plots, cluster NBL_11 is pastel green, when it should be NBL_9. The colors on the spatialdata image itself are not wrong, it is the colors on the legend which are incorrect.

            This issue is occurs in pl.utils._get_palette, where the values in thecategories gets mapped to the colors of the palette. However in scanpy it's the categories of the DataFrame which get mapped to the colors.

            By adjusting the following line from

            returndict(zip(categories, palette))

            to dict(zip(categories.categories, palette)) we get the correct legend-color mapping.

            NBL-25-R2C8--Diagnosis--correct

            Reproducible Example - MIBITOF dataset

            importspatialdataassdimportspatialdata_plotimportmatplotlib.pyplotaspltfrompathlibimportPathmibitof_sd=sd.read_zarr(Path("~/Downloads/data.zarr").expanduser())
            fig, axes=plt.subplots(nrows=1, ncols=2, figsize=(18, 8), layout="tight")
            mibitof_sd.pp.get_elements("point8_labels").pl.render_labels(color="Cluster").pl.show(
            ax=axes[0]
            )
            mibitof_sd.pp.get_elements("point8_labels").pl.render_labels(
            color="Cluster", palette=["blue"], groups=["Epithelial"]
            ).pl.show(ax=axes[1])
            fig

            Generated Plot: Here Imm_other in the legend actually represents the Epithelial cells.
            point8_labels

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              Skip to content

              Categorical Data is incorrectly colored in the legend when plotting #214

              Description

              @srivarra

              When using pl.render_labels with the color and palette parameter, the legends are incorrectly colored.

              Example Plot:
              NBL-25-R2C8--Diagnosis--incorrect

              Here we see that the Dot plot from scanpy counts 1.1K cells in the cluster NBL_9 and colors them with pastel green (correct color). However on the spatialdata plots, cluster NBL_11 is pastel green, when it should be NBL_9. The colors on the spatialdata image itself are not wrong, it is the colors on the legend which are incorrect.

              This issue is occurs in pl.utils._get_palette, where the values in thecategories gets mapped to the colors of the palette. However in scanpy it's the categories of the DataFrame which get mapped to the colors.

              By adjusting the following line from

              returndict(zip(categories, palette))

              to dict(zip(categories.categories, palette)) we get the correct legend-color mapping.

              NBL-25-R2C8--Diagnosis--correct

              Reproducible Example - MIBITOF dataset

              importspatialdataassdimportspatialdata_plotimportmatplotlib.pyplotaspltfrompathlibimportPathmibitof_sd=sd.read_zarr(Path("~/Downloads/data.zarr").expanduser())
              fig, axes=plt.subplots(nrows=1, ncols=2, figsize=(18, 8), layout="tight")
              mibitof_sd.pp.get_elements("point8_labels").pl.render_labels(color="Cluster").pl.show(
              ax=axes[0]
              )
              mibitof_sd.pp.get_elements("point8_labels").pl.render_labels(
              color="Cluster", palette=["blue"], groups=["Epithelial"]
              ).pl.show(ax=axes[1])
              fig

              Generated Plot: Here Imm_other in the legend actually represents the Epithelial cells.
              point8_labels

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                Skip to content

                Categorical Data is incorrectly colored in the legend when plotting #214

                Description

                @srivarra

                When using pl.render_labels with the color and palette parameter, the legends are incorrectly colored.

                Example Plot:
                NBL-25-R2C8--Diagnosis--incorrect

                Here we see that the Dot plot from scanpy counts 1.1K cells in the cluster NBL_9 and colors them with pastel green (correct color). However on the spatialdata plots, cluster NBL_11 is pastel green, when it should be NBL_9. The colors on the spatialdata image itself are not wrong, it is the colors on the legend which are incorrect.

                This issue is occurs in pl.utils._get_palette, where the values in thecategories gets mapped to the colors of the palette. However in scanpy it's the categories of the DataFrame which get mapped to the colors.

                By adjusting the following line from

                returndict(zip(categories, palette))

                to dict(zip(categories.categories, palette)) we get the correct legend-color mapping.

                NBL-25-R2C8--Diagnosis--correct

                Reproducible Example - MIBITOF dataset

                importspatialdataassdimportspatialdata_plotimportmatplotlib.pyplotaspltfrompathlibimportPathmibitof_sd=sd.read_zarr(Path("~/Downloads/data.zarr").expanduser())
                fig, axes=plt.subplots(nrows=1, ncols=2, figsize=(18, 8), layout="tight")
                mibitof_sd.pp.get_elements("point8_labels").pl.render_labels(color="Cluster").pl.show(
                ax=axes[0]
                )
                mibitof_sd.pp.get_elements("point8_labels").pl.render_labels(
                color="Cluster", palette=["blue"], groups=["Epithelial"]
                ).pl.show(ax=axes[1])
                fig

                Generated Plot: Here Imm_other in the legend actually represents the Epithelial cells.
                point8_labels

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