# How to extract transformed polygons from sdata.shapes?

**URL:** <https://discourse.scverse.org/t/how-to-extract-transformed-polygons-from-sdata-shapes/2458>\
**Category:** spatialdata\
**Created:** [August 18, 2024, 4:01pm UTC](https://discourse.scverse.org/t/how-to-extract-transformed-polygons-from-sdata-shapes/2458 "2024-08-18T16:01:04Z")\
**Posts on this page:** 4\
**Page:** 1

<div class="post-metadata">

**Author:** ![liz-is](https://yyz1.discourse-cdn.com/flex035/user_avatar/discourse.scverse.org/liz-is/32/1141_2.png) [@liz-is](https://discourse.scverse.org/u/liz-is)\
**Post date:** [August 18, 2024, 4:01pm UTC](https://discourse.scverse.org/t/how-to-extract-transformed-polygons-from-sdata-shapes/2458/1 "2024-08-18T16:01:04Z")

</div>

I have some segmentations (of structures larger than cells) that were performed on an H&E image, that I have imported, added to my spatialdata object containing my Xenium data, and then applied the appropriate XeniumExplorer transformation matrix to.

I’d now like to find, for each polygon in the new segmentations, the IDs of the cells where the centroid falls inside the polygon.

I thought I’d be able to do this using the [contains](https://shapely.readthedocs.io/en/stable/manual.html#object.contains) method of the Polygon object, but when I access the segmentation polygons using `sdata.shapes['new_polygons']`, the coordinates in the `geometry` column are the same as in my un-transformed input, and I don’t find any overlapping cells when I check the first couple of polygons.

Is it possible to extract/export the transformed coordinates of the polygons/points in `sdata.shapes`?

Or do you have another suggestion of how to do this?

I’ve looked at the `polygon_query` [example](https://spatialdata.scverse.org/en/latest/tutorials/notebooks/notebooks/examples/spatial_query.html#polygon-query), but I don’t follow what’s going on there - there’s clearly some kind of transformation happening between the polygon plotted by itself and the polygon plotted on top of the Visium data, but it’s not explained.

I tried that anyway, but I get an error, which I think is for the same reason as above - the untransformed polygon coords are being used for the query, so no cells overlap:

```auto
poly_cropped = polygon_query(
    sdata,
    polygon=sdata.shapes['tubule_polygons'].iloc[1,]["geometry"],
    target_coordinate_system="global",
)
File /mnt/storage/vaquerizas/liz/spatial/xenium/python_analysis/py3.10/lib/python3.10/site-packages/spatialdata/_core/query/relational_query.py:168, in _filter_table_by_elements(table, elements_dict, match_rows)
    166 assert set(elements_dict.keys()).issubset({"images", "labels", "shapes", "points"})
    167 assert len(elements_dict) > 0, "elements_dict must not be empty"
--> 168 assert any(
    169 len(elements) > 0 for elements in elements_dict.values()
    170 ), "elements_dict must contain at least one dict which contains at least one element"
    171 if table is None:
    172 return None

AssertionError: elements_dict must contain at least one dict which contains at least one element

```

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<div class="post-metadata">

**Author:** ![LucaMarconato](https://yyz1.discourse-cdn.com/flex035/user_avatar/discourse.scverse.org/lucamarconato/32/661_2.png) [@LucaMarconato](https://discourse.scverse.org/u/LucaMarconato)\
**Post date:** [August 19, 2024, 9:34am UTC](https://discourse.scverse.org/t/how-to-extract-transformed-polygons-from-sdata-shapes/2458/2 "2024-08-19T09:34:31Z")

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Hi @liz-is, what you experiences is the expected behavior: we store the raw coordinates paired with lightweight transformation metadata and we keep the raw coordinates raw unless the user explicitly wants to transform them.

The solution in your case is to use [transform()](https://spatialdata.scverse.org/en/latest/generated/spatialdata.transform.html#spatialdata.transform) in both elements that you want to transform and then use the `geopandas` APIs (such as `contains()`). Please notice that you need to specify the same `to_coordinate_system` parameter for both calls, or leave the default value `'global'`.

You may also find [get\_centroids()](https://spatialdata.scverse.org/en/latest/generated/spatialdata.get_centroids.html) useful.

Two more hints:

- if one of your segmentation data is raster, you can derive the polygons/multipolygons using [to\_polygons()](https://spatialdata.scverse.org/en/latest/generated/spatialdata.to_polygons.html).

Finally, after you filter the cells you may want to also filter the table (which annotates the cells). For this we have the function [match\_table\_to\_element](https://spatialdata.scverse.org/en/latest/generated/spatialdata.match_table_to_element.html) (for more control you can use [join\_spatialelement\_table()](https://spatialdata.scverse.org/en/latest/generated/spatialdata.join_spatialelement_table.html).

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<div class="post-metadata">

**Author:** ![liz-is](https://yyz1.discourse-cdn.com/flex035/user_avatar/discourse.scverse.org/liz-is/32/1141_2.png) [@liz-is](https://discourse.scverse.org/u/liz-is)\
**Post date:** [August 29, 2024, 7:51pm UTC](https://discourse.scverse.org/t/how-to-extract-transformed-polygons-from-sdata-shapes/2458/3 "2024-08-29T19:51:24Z")

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Thanks! I knew there had to be a simple way to do it.

I found the documentation for `transform()` slightly confusing, but I got it working! I think it’d be really helpful to have an example of using this function added to the [tutorial on transformations](https://spatialdata.scverse.org/en/latest/tutorials/notebooks/notebooks/examples/transformations.html#) at some point.

One remaining question - when I select and print a single polygon after transformation, its orientation doesn’t match how it’s plotted with `sdata.pl.render_shapes()` - is this expected?

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<div class="post-metadata">

**Author:** ![LucaMarconato](https://yyz1.discourse-cdn.com/flex035/user_avatar/discourse.scverse.org/lucamarconato/32/661_2.png) [@LucaMarconato](https://discourse.scverse.org/u/LucaMarconato)\
**Post date:** [September 2, 2024, 9:44am UTC](https://discourse.scverse.org/t/how-to-extract-transformed-polygons-from-sdata-shapes/2458/4 "2024-09-02T09:44:26Z")

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Great to hear that you solved your problem, and thanks for the feedback on the documentation. I tracked it [here](https://github.com/scverse/spatialdata/issues/631#issuecomment-2324292124).

Finally, the different orientation is expected as some plotting frameworks differ in how they orient the y axis; but you can quickly adjust this, for instance by plotting on a specific `ax`, and then using [matplotlib APIs](https://matplotlib.org/stable/api/_as_gen/matplotlib.axes.Axes.invert_yaxis.html).