# Does Scanpy stores raw count as int or float?

**URL:** <https://discourse.scverse.org/t/does-scanpy-stores-raw-count-as-int-or-float/2177>\
**Category:** scanpy\
**Tags:** anndata\
**Created:** [March 24, 2024, 12:02am UTC](https://discourse.scverse.org/t/does-scanpy-stores-raw-count-as-int-or-float/2177 "2024-03-24T00:02:15Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![lwtan](https://avatars.discourse-cdn.com/v4/letter/l/97f17d/32.png) [@lwtan](https://discourse.scverse.org/u/lwtan)\
**Post date:** [March 24, 2024, 12:02am UTC](https://discourse.scverse.org/t/does-scanpy-stores-raw-count-as-int-or-float/2177/1 "2024-03-24T00:02:15Z")

</div>

Hi single-cell connoisseur,

I am curious if the default type for AnnData raw object is float or int?

For example:

```auto
raw_adata = adata.raw.to_adata()
raw_adata.X

```

Output:

```auto
<220752x29484 sparse matrix of type '<class 'numpy.float64'>'
	with 307103988 stored elements in Compressed Sparse Row format>

```

Of course, I got this object for a published dataset, and have to restore the raw count. Just curious if raw counts are stored by default as float?

The motivation for this question was because I saw this cute way of checking if the data is normalized:

```auto
if check_counts:
        # check if observations are unnormalized using first 10
        X_subset = adata.X[:10]
        norm_error = 'Make sure that the dataset (adata.X) contains unnormalized count data.'
        if sp.sparse.issparse(X_subset):
            assert (X_subset.astype(int) != X_subset).nnz == 0, norm_error
        else:
            assert np.all(X_subset.astype(int) == X_subset), norm_error

```

Certainly, my case would have failed this check, if the sparse matrix is not by default stored in int.

Thank you.

Wil

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<div class="post-metadata">

**Author:** ![ivirshup](https://yyz1.discourse-cdn.com/flex035/user_avatar/discourse.scverse.org/ivirshup/32/160_2.png) [@ivirshup](https://discourse.scverse.org/u/ivirshup)\
**Post date:** [March 25, 2024, 8:30pm UTC](https://discourse.scverse.org/t/does-scanpy-stores-raw-count-as-int-or-float/2177/2 "2024-03-25T20:30:26Z")

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Hi Wil,

Scanpy should be able to work with either, though inplace normalization requires floating point values. Data is typically stored as `float32`.

> Certainly, my case would have failed this check, if the sparse matrix is not by default stored in int.

I don’t think this is the case. For an example:

```python
import numpy as np

assert np.array_equal(
    np.arange(10, dtype=np.float64).astype(int),
    np.arange(10, dtype=np.float64)
)

```

If the numbers have a floating point type but are integer valued, this should be fine.