Repository: single-cell-data/TileDB-SOMA (language: python)

Issue:
[python/r/c++] Revisit `shape` for component arrays
## PRs

**Merged PRs:**

<details>

* #2909 `kerl/schevo-timestamp-methodize`
* #2913 `kerl/name-neaten`
* #2908 `kerl/ut-soma-exc-simplify`
* #2910 `kerl/test-common-parameterize`
* #2918 `kerl/cpp-test-deadstrip`
* #2919 `kerl/minor-unit-test-helper-mod`
* #2936 `kerl/cpp-ut-helper-neaten`
* #2938 `kerl/more-cur-dom-parameterize`
* #2915 `kerl/cpp-strict-int64-shape`
* #2911 `kerl/arrow-util-current-domain-optional`
* #2939 `kerl/step-two-temp`
* #2947 `kerl/cpp-ndarray-resize-testing`
* #2945 `kerl/dataframe-test-fixture`
* #2944 `kerl/cpp-variant-indexed-dataframes`
* #2916 `kerl/sdf-shape`
* #2917 `kerl/cpp-resizes`
* #2948 `kerl/upgrade-shape-int64`
* #2951 `kerl/sdf-test-accessors`
* #2953 `kerl/py-r-accessor-plumbing`
* #2957 `kerl/sdf-domain-accessors`
* #2960 `kerl/dense-link`
* #2963 `kerl/nightly-fix`
* #2970 `kerl/dense-writeable-after-create`
* #2968 `kerl/minor-trim`
* #2969 `kerl/more-py-domain-name-neaten`
* #2972 `kerl/libtiledbsoma-env-logging-level`
* #2962 `kerl/py-r-creation-paths`
* #2950 `kerl/py-r-test-2`
* #2994 `kerl/nanoarrow-helpers`
* #3011 `kerl/polydom3`
* #3017 `kerl/polydom5`
* #3018 `kerl/polydom6`
* #2990 `kerl/variant-nnz-bug`
* #3019 `kerl/index-swap`
* #3020 `kerl/ut-max-shape`
* #3012 `kerl/polydom4`
* #3025 `kerl/fix-3020-merge`
* #3026 `kerl/one-more-rename`
* #3028 `kerl/ff-not`
* #3029 `kerl/ut-vg`
* #3030 `kerl/table-utils-memory`
* #3067 `kerl/improve-sdf-test-field-names`
* #3068 `kerl/ut-generate`
* #3069 `kerl/cpp-sdf-domain-at-create`
* #3027 `kerl/hll-domainish`
* #3088 `kerl/max-domain-int64`
* #3090 `kerl/maybe-resize-soma-joinid-cpp-tweak`
* #3032 `kerl/sdf-domain-at-create` -- fixes #2967
* #3091 `kerl/maybe-resize-soma-joinid-py-r`
* #3095 `kerl/cpp-exp-resize-prep`
* #3089 `kerl/r-dataframe-shapeable`
* https://github.com/single-cell-data/SOMA/pull/233
* #3125 `kerl/cpp-ut-name-shortens`
* #3127 `kerl/helper-rename`
* #3130 `kerl/cpp-can-resizers-names`
* #3132 `kerl/cpp-dataframe-sizing-helpers`
* #3139 `kerl/cpp-dataframe-upgrade-test`
* #3140 `kerl/py-resizer-connects`
* #3151 `kerl/py-can-upgrade-shape`
* #3152 `kerl/registration-shape-acceessors`
* #3156 `kerl/py-exp-shaping`
* #3157 `kerl/py-exp-shaping2`
* #3148 `kerl/py-exp-resize`
* #3191 `kerl/py-domain-at-create-ut-1`
* #3190 `kerl/py-domain-at-create-ut-2`
* #3192 `kerl/py-domain-at-create-ut-3`
* #3193 `kerl/py-domain-at-create-ut-4`
* #3194 `kerl/py-domain-at-create-ut-5`
* #3203 `kerl/min-size-2`
* #3208 `kerl/r-min-sizing`
* #3211 `kerl/cpp-ugr-dom`
* #3232 `kerl/ff-interop`
* #3230 `kerl/ffon`
* #3234 `kerl/docstring-prune`
* #3236 `kerl/prefixing`
* #3241 `kerl/fix-bad-merge`
* #3235 `kerl/py-r-ugr-dom`
* #3237 `kerl/py-r-ugr-dom-2`
* #3238 `kerl/py-r-ugr-dom-3`
* #3253 `kerl/set-coords-rename`
* #3261 `kerl/pybind11-nda-sizing`
* #3265 `kerl/dense-227-a`
* #3263 `kerl/dense-range-trim`
* #3268 `kerl/dim-explosion`
* #3269 `kerl/python-227-dense-ned-read`
* #3270 `kerl/r-227-dense-fixes`
* #3280 `kerl/r-dense-227-more`
* #3286 `kerl/more-fn4m`
* #3283 `kerl/readthedocs-pre-1.15`
* #3288 `kerl/dense-ugrsh`
* #3289 `kerl/notebook-shape-upgrade`
* #3285 `kerl/new-shape-doc-updates`
* #3295 `kerl/notebook-data-refresh`
* #3290 `kerl/notebook-new-shape-refresh`
* #3301 `kerl/ffena`
* #3303 `kerl/r-data-refresh`
* #3300 `kerl/sdf-sjid-lower-zero`
* #3296 `kerl/dense-example-data-refresh`
* #3294 `kerl/new-shape-notebook-and-vignette`
* #3308 `kerl/upgrade-experiment-resources`
* #3309 `kerl/fix-notebook-merge`
* #3321 `kerl/more-use-shape`
* #3358 `kerl/revert-3300`
* #3368 `kerl/227a`
* #3369 `kerl/ucd1`
* #3370 `kerl/ucd2`
* #3371 `kerl/ucd3`
* #3372 `kerl/ucd4`
* #3396 `kerl/domain-at-create-docstrings`
* #3302 `kerl/new-shape-vignette`
* https://github.com/single-cell-data/SOMA/pull/250
* #3399 `kerl/new-shape-more-docstrings`
* #3400 `kerl/check-only-r`
* https://github.com/TileDB-Inc/somacore-feedstock/pull/27

</details>

**Closed/abandoned PRs:**

<details>

* #2785 -- This was only dogfooding for the core 2.25 release -- not to be merged
* #2952 `kerl/feature-flag-temp` -- folded into 2962
* #2995 `kerl/polydom`
* #2964 `kerl/tiledbsoma-io-test`
* #3189 `kerl/min-size`
* #3220 `kerl/cpp-ugr-dom-2`
* #3244 `kerl/dense-227-fixes`
* #3276 `kerl/dataframe-shape`

</details>

**Issues which are related but non-blocking:**

* https://github.com/single-cell-data/SOMA/pull/216
* https://github.com/TileDB-Inc/TileDB/pull/5303
* #2966
* #3081
* Note: R append mode does not exist yet -- see #1630 -- so an experiment-level resizer is not a priority in R
* #3271 
* #3272
* #3273

**See also:** [[sc-51048]](https://app.shortcut.com/tiledb-inc/story/51048).

## Problem to be solved

Users want to know the `shape` of an array, in the SciPy sense:

* Reads and writes are bounds-checked against the shape
* This retains its value regardless of which values of a sparse array are or are not actually occupied
* Users can `resize`.
  * Some users need the ability to grow their datasets later, using either `tiledbsoma.io`'s append mode, or subsequent writes using the `tiledbsoma` API.
  * Note that the cellxgene census doesn't need this: eact week's published census has fixed shape, and any updates will happen in new storage, on a new week.

Using TileDB-SOMA up until the present:

* The TIleDB `domain` is immutable after array creation
  * This does bounds-checking for reads and writes, which is good
  * To leverage this to function as a `shape`, users would need to set the `domain` at array-creation time. However, users lose the ability to grow their datasets later.
* There is a `non_empty_domain` accessor
  * This only indicates min/max coordinates _at which data exists_. Consider an `X` array for 100 cells and 200 genes. If non-zero expression counts exist only for cell join IDs 2-17, then the `non_empty_domain` will indicate `(2,17)` along `soma_dim_0`.
  * Consider an `obms["X_pca"]` within the same experiment. This may be 100 cells by 50 PCA components: we need a placd to store the number 50.
  * Therefore users cannot leverage this to function as a `shape` accessor.
* We have offered a `used_shape` accessor since TileDB-SOMA 1.5.
  * This functions as a `shape` accessor, in the SciPy sense, but it is not multi-writer safe.

New feature for TileDB-SOMA 1.15:

* Arrays will have a  `shape`
* Reads and writes are bounds-checked against the shape
* This retains its value regardless of which values of a sparse array are or are not actually occupied
* Users can `resize`
* The `used_shape` accessor will be deprecated in TileDB-SOMA 1.13, and slated for removal in TileDB-SOMA 1.14.

Compatiblity:

This will now require users to do an explicit `resize` before appending/growing TileDB-SOMA Experiments. Guidance in the form of example notebooks will be provided.

##  Tracking

See also: [[sc-41074]](https://app.shortcut.com/tiledb-inc/story/41074) and [[sc-51048]](https://app.shortcut.com/tiledb-inc/story/51048).

## Scheduling

Support arrives in TileDB Core 2.25. Deprecations for TileDB-SOMA will be released with 1.13. Full support within TileDB-SOMA will be release in 1.14.

## Details

SOMA API mods as we've discussed in a Google doc are as follows.

### `SOMADataFrame`

* `create`: Retain the `domain` argument
  * Issue:
    * Core has a `(lo, hi)` tuple per dim, e.g. `(0,99)` or `(10,19)`
    * SOMA has count per dim, with 0 implicit: e.g. 100 or 20
    * For `SparseNDArray` and `DenseNDArray` core can have `(lo, hi)` and SOMA can have `count`
    * For `DataFrame` there can be multiple dims --- default is a single `soma_joinid`
    * That could be treated either in `(lo, hi)` fashion or `count` fashion
    * However additional dims (e.g. `cell_type`) can be on any type, including strings, floats, etc. where there is no implicit lo=0
    * Therefore we need to keep the current SOMA API wherein `DataFrame` takes a `domain` argument (in `(lo, hi)` fashion) and not a `shape` argument (in `count` fashion)

### `SparseNDArray and DenseNDArray`

* `create`
  * Have an optional shape argument which is of type `Tuple[Int,...]` where each element is the cell count of the corresponding dimension
    * If unsupplied, or if supplied but None in any slot: use the minimum 0 in each slot – nothing larger makes sense since we will not support downsize
  * User guidance should make clear that it will not be possible to create an ‘old’ style array with the ‘new style’ API. (See also the upgrade logic below.)

### All three of `SOMADataFrame`, `SparseNDArray`, `DenseNDArray`

* `write`
  * For new arrays, created with the new shape feature:
    * Core will bounds-check that coordinates provided at `write` time are within the current shape
    * Core will raise `tiledb.cc.TileDBError` to TileDB-SOMA, which will catch and raise `IndexError`, and R-standard behavior on the R side
  * For old arrays created before this feature:
    * Core will not bounds-check that coordinates provided at write time are within the current shape
* Existing `used_shape` accessor
  * TileDB-SOMA will deprecate this over a release cycle.
  * For new arrays: raise `NotImplementedError`
  * For old arrays: return what’s currently returned, with a deprecation warning.
  * Mechanism for determining old vs. new: `array.schema.version` (the core storage version).
* Existing `shape` accessor
  * For new arrays:
    * Have this return the new shape as proposed by core, no longer returning the TileDB domain.
  * For old arrays created before this feature:
    * Return the TileDB domain as now.
* Existing `non_empty_domain` accessor
  * Same behavior for old and new arrays (unaffected by this proposal).
  * Keep this accessor supported, but, with user notes that it’s generally non-useful
  * This should return None (or R equivalent) when there is a schema but no data have been written.
* New `maxshape` accessor
  * Maps the core-level `(lo, hi)` accessor for domain to count-style accessor hi+1. E.g. if the core domain is either `(0,99)` or `(50,99)` then TileDB-SOMA `maxshape` will say 100.
  * Same behavior for old and new arrays.
  * Let users query for what the TileDB domain is, with user notes that it’s the maximum that users can reshape to.
  * Issac suggests: maybe `domain` or `maxshape` (see h5py).
* New `resize` mutator
  * Note: `reshape` means something else in the community (numpy, zarr, h5py), e.g. a 5x20 (total 100 cells) being reinterpreted as 4x25 (still 100 cells). The standard name for changing cell-count is `resize`.
  * For old arrays created before this feature: raise `NotImplementedError`.
  * For new arrays:
    * Will raise `ValueError` if the new shape is smaller on any dim than currently in storage
    * Regardless of whether any data have been written whatsoever
    * Will raise `ValueError` if the new shape exceeds the TileDB domain from create time, which will serve TileDB-SOMA in a role of “max possible shape the user can reshape to”
    * Otherwise, any calls to write from this point will bounds-check writes within this new shape
    * **We don’t expect resize to be multi-writer safe with regard to write ; user notes must be clear on this point**
* New `tiledbsoma_upgrade_shape` method for SparseNDArray and DenseNDArray
  * This will leverage `array.schema.version` to see if an upgrade is needed
  * Leverage core support for storage-version updates
  * This will take a shape argument as in `create`
  * For arrays created with “just-right” size: this will succeed
  * For arrays created with “room-for-growth” / “two billion-ish” size: this will succeed
  * If the user passes a shape which exceeds the current TileDB domain: this will fail
* New `tiledbsoma_upgrade_domain method` for `DataFrame`
  * Same as for `SparseNDArray`/`DenseNDArray` except it will take a domain at the SOMA-API level just as `DataFrame`'s create method

### `tiledbsoma.io`

* The user-facing API has no shape arguments and thus won’t need changing.
* Internally to `tiledbsoma.io`, we’ll still ask the tiledbsoma API for the “big domain” (2 billionish)
* Append mode:
  * Will need a new `resize` method at the `Experiment` level
  * Users will need to:
    * Register as now
    * Call the experiment-level `resize`
      * Could be `exp.resize(...)`, or (better) this could be `tiledbsoma.io.reshape_experiment`
  * In either case: this method will take the new `obs` and `var` counts as inputs:
    * `exp.obs.reshape` to new `obs` count
    * `exp.ms[name].var.reshape` to new `var` count
    * `exp.ms[name].X[name].reshape` to new `obs` count x `var` count
    * `exp.ms[name].obsm[name].reshape` to new `obs` count x same width
    * `exp.ms[name].obsp[name].reshape` to new `obs` count x `obs` count
    * `exp.ms[name].varm[name].reshape` to new `var` count x same width
    * `exp.ms[name].varp[name].reshape` to new `var` count x `var` count
  * Do the individual append-mode writes as now

[packaging] Core 2.27 release items [tracking]
This is just a central spot for tracking things related to the 2.27 release, including its preliminary release-candidate series.
[python/r/c++] Revisit `shape` for component arrays
## PRs

**Merged PRs:**

<details>

* #2909 `kerl/schevo-timestamp-methodize`
* #2913 `kerl/name-neaten`
* #2908 `kerl/ut-soma-exc-simplify`
* #2910 `kerl/test-common-parameterize`
* #2918 `kerl/cpp-test-deadstrip`
* #2919 `kerl/minor-unit-test-helper-mod`
* #2936 `kerl/cpp-ut-helper-neaten`
* #2938 `kerl/more-cur-dom-parameterize`
* #2915 `kerl/cpp-strict-int64-shape`
* #2911 `kerl/arrow-util-current-domain-optional`
* #2939 `kerl/step-two-temp`
* #2947 `kerl/cpp-ndarray-resize-testing`
* #2945 `kerl/dataframe-test-fixture`
* #2944 `kerl/cpp-variant-indexed-dataframes`
* #2916 `kerl/sdf-shape`
* #2917 `kerl/cpp-resizes`
* #2948 `kerl/upgrade-shape-int64`
* #2951 `kerl/sdf-test-accessors`
* #2953 `kerl/py-r-accessor-plumbing`
* #2957 `kerl/sdf-domain-accessors`
* #2960 `kerl/dense-link`
* #2963 `kerl/nightly-fix`
* #2970 `kerl/dense-writeable-after-create`
* #2968 `kerl/minor-trim`
* #2969 `kerl/more-py-domain-name-neaten`
* #2972 `kerl/libtiledbsoma-env-logging-level`
* #2962 `kerl/py-r-creation-paths`
* #2950 `kerl/py-r-test-2`
* #2994 `kerl/nanoarrow-helpers`
* #3011 `kerl/polydom3`
* #3017 `kerl/polydom5`
* #3018 `kerl/polydom6`
* #2990 `kerl/variant-nnz-bug`
* #3019 `kerl/index-swap`
* #3020 `kerl/ut-max-shape`
* #3012 `kerl/polydom4`
* #3025 `kerl/fix-3020-merge`
* #3026 `kerl/one-more-rename`
* #3028 `kerl/ff-not`
* #3029 `kerl/ut-vg`
* #3030 `kerl/table-utils-memory`
* #3067 `kerl/improve-sdf-test-field-names`
* #3068 `kerl/ut-generate`
* #3069 `kerl/cpp-sdf-domain-at-create`
* #3027 `kerl/hll-domainish`
* #3088 `kerl/max-domain-int64`
* #3090 `kerl/maybe-resize-soma-joinid-cpp-tweak`
* #3032 `kerl/sdf-domain-at-create` -- fixes #2967
* #3091 `kerl/maybe-resize-soma-joinid-py-r`
* #3095 `kerl/cpp-exp-resize-prep`
* #3089 `kerl/r-dataframe-shapeable`
* https://github.com/single-cell-data/SOMA/pull/233
* #3125 `kerl/cpp-ut-name-shortens`
* #3127 `kerl/helper-rename`
* #3130 `kerl/cpp-can-resizers-names`
* #3132 `kerl/cpp-dataframe-sizing-helpers`
* #3139 `kerl/cpp-dataframe-upgrade-test`
* #3140 `kerl/py-resizer-connects`
* #3151 `kerl/py-can-upgrade-shape`
* #3152 `kerl/registration-shape-acceessors`
* #3156 `kerl/py-exp-shaping`
* #3157 `kerl/py-exp-shaping2`
* #3148 `kerl/py-exp-resize`
* #3191 `kerl/py-domain-at-create-ut-1`
* #3190 `kerl/py-domain-at-create-ut-2`
* #3192 `kerl/py-domain-at-create-ut-3`
* #3193 `kerl/py-domain-at-create-ut-4`
* #3194 `kerl/py-domain-at-create-ut-5`
* #3203 `kerl/min-size-2`
* #3208 `kerl/r-min-sizing`
* #3211 `kerl/cpp-ugr-dom`
* #3232 `kerl/ff-interop`
* #3230 `kerl/ffon`
* #3234 `kerl/docstring-prune`
* #3236 `kerl/prefixing`
* #3241 `kerl/fix-bad-merge`
* #3235 `kerl/py-r-ugr-dom`
* #3237 `kerl/py-r-ugr-dom-2`
* #3238 `kerl/py-r-ugr-dom-3`
* #3253 `kerl/set-coords-rename`
* #3261 `kerl/pybind11-nda-sizing`
* #3265 `kerl/dense-227-a`
* #3263 `kerl/dense-range-trim`
* #3268 `kerl/dim-explosion`
* #3269 `kerl/python-227-dense-ned-read`
* #3270 `kerl/r-227-dense-fixes`
* #3280 `kerl/r-dense-227-more`
* #3286 `kerl/more-fn4m`
* #3283 `kerl/readthedocs-pre-1.15`
* #3288 `kerl/dense-ugrsh`
* #3289 `kerl/notebook-shape-upgrade`
* #3285 `kerl/new-shape-doc-updates`
* #3295 `kerl/notebook-data-refresh`
* #3290 `kerl/notebook-new-shape-refresh`
* #3301 `kerl/ffena`
* #3303 `kerl/r-data-refresh`
* #3300 `kerl/sdf-sjid-lower-zero`
* #3296 `kerl/dense-example-data-refresh`
* #3294 `kerl/new-shape-notebook-and-vignette`
* #3308 `kerl/upgrade-experiment-resources`
* #3309 `kerl/fix-notebook-merge`
* #3321 `kerl/more-use-shape`
* #3358 `kerl/revert-3300`
* #3368 `kerl/227a`
* #3369 `kerl/ucd1`
* #3370 `kerl/ucd2`
* #3371 `kerl/ucd3`
* #3372 `kerl/ucd4`
* #3396 `kerl/domain-at-create-docstrings`
* #3302 `kerl/new-shape-vignette`
* https://github.com/single-cell-data/SOMA/pull/250
* #3399 `kerl/new-shape-more-docstrings`
* #3400 `kerl/check-only-r`
* https://github.com/TileDB-Inc/somacore-feedstock/pull/27

</details>

**Closed/abandoned PRs:**

<details>

* #2785 -- This was only dogfooding for the core 2.25 release -- not to be merged
* #2952 `kerl/feature-flag-temp` -- folded into 2962
* #2995 `kerl/polydom`
* #2964 `kerl/tiledbsoma-io-test`
* #3189 `kerl/min-size`
* #3220 `kerl/cpp-ugr-dom-2`
* #3244 `kerl/dense-227-fixes`
* #3276 `kerl/dataframe-shape`

</details>

**Issues which are related but non-blocking:**

* https://github.com/single-cell-data/SOMA/pull/216
* https://github.com/TileDB-Inc/TileDB/pull/5303
* #2966
* #3081
* Note: R append mode does not exist yet -- see #1630 -- so an experiment-level resizer is not a priority in R
* #3271 
* #3272
* #3273

**See also:** [[sc-51048]](https://app.shortcut.com/tiledb-inc/story/51048).

## Problem to be solved

Users want to know the `shape` of an array, in the SciPy sense:

* Reads and writes are bounds-checked against the shape
* This retains its value regardless of which values of a sparse array are or are not actually occupied
* Users can `resize`.
  * Some users need the ability to grow their datasets later, using either `tiledbsoma.io`'s append mode, or subsequent writes using the `tiledbsoma` API.
  * Note that the cellxgene census doesn't need this: eact week's published census has fixed shape, and any updates will happen in new storage, on a new week.

Using TileDB-SOMA up until the present:

* The TIleDB `domain` is immutable after array creation
  * This does bounds-checking for reads and writes, which is good
  * To leverage this to function as a `shape`, users would need to set the `domain` at array-creation time. However, users lose the ability to grow their datasets later.
* There is a `non_empty_domain` accessor
  * This only indicates min/max coordinates _at which data exists_. Consider an `X` array for 100 cells and 200 genes. If non-zero expression counts exist only for cell join IDs 2-17, then the `non_empty_domain` will indicate `(2,17)` along `soma_dim_0`.
  * Consider an `obms["X_pca"]` within the same experiment. This may be 100 cells by 50 PCA components: we need a placd to store the number 50.
  * Therefore users cannot leverage this to function as a `shape` accessor.
* We have offered a `used_shape` accessor since TileDB-SOMA 1.5.
  * This functions as a `shape` accessor, in the SciPy sense, but it is not multi-writer safe.

New feature for TileDB-SOMA 1.15:

* Arrays will have a  `shape`
* Reads and writes are bounds-checked against the shape
* This retains its value regardless of which values of a sparse array are or are not actually occupied
* Users can `resize`
* The `used_shape` accessor will be deprecated in TileDB-SOMA 1.13, and slated for removal in TileDB-SOMA 1.14.

Compatiblity:

This will now require users to do an explicit `resize` before appending/growing TileDB-SOMA Experiments. Guidance in the form of example notebooks will be provided.

##  Tracking

See also: [[sc-41074]](https://app.shortcut.com/tiledb-inc/story/41074) and [[sc-51048]](https://app.shortcut.com/tiledb-inc/story/51048).

## Scheduling

Support arrives in TileDB Core 2.25. Deprecations for TileDB-SOMA will be released with 1.13. Full support within TileDB-SOMA will be release in 1.14.

## Details

SOMA API mods as we've discussed in a Google doc are as follows.

### `SOMADataFrame`

* `create`: Retain the `domain` argument
  * Issue:
    * Core has a `(lo, hi)` tuple per dim, e.g. `(0,99)` or `(10,19)`
    * SOMA has count per dim, with 0 implicit: e.g. 100 or 20
    * For `SparseNDArray` and `DenseNDArray` core can have `(lo, hi)` and SOMA can have `count`
    * For `DataFrame` there can be multiple dims --- default is a single `soma_joinid`
    * That could be treated either in `(lo, hi)` fashion or `count` fashion
    * However additional dims (e.g. `cell_type`) can be on any type, including strings, floats, etc. where there is no implicit lo=0
    * Therefore we need to keep the current SOMA API wherein `DataFrame` takes a `domain` argument (in `(lo, hi)` fashion) and not a `shape` argument (in `count` fashion)

### `SparseNDArray and DenseNDArray`

* `create`
  * Have an optional shape argument which is of type `Tuple[Int,...]` where each element is the cell count of the corresponding dimension
    * If unsupplied, or if supplied but None in any slot: use the minimum 0 in each slot – nothing larger makes sense since we will not support downsize
  * User guidance should make clear that it will not be possible to create an ‘old’ style array with the ‘new style’ API. (See also the upgrade logic below.)

### All three of `SOMADataFrame`, `SparseNDArray`, `DenseNDArray`

* `write`
  * For new arrays, created with the new shape feature:
    * Core will bounds-check that coordinates provided at `write` time are within the current shape
    * Core will raise `tiledb.cc.TileDBError` to TileDB-SOMA, which will catch and raise `IndexError`, and R-standard behavior on the R side
  * For old arrays created before this feature:
    * Core will not bounds-check that coordinates provided at write time are within the current shape
* Existing `used_shape` accessor
  * TileDB-SOMA will deprecate this over a release cycle.
  * For new arrays: raise `NotImplementedError`
  * For old arrays: return what’s currently returned, with a deprecation warning.
  * Mechanism for determining old vs. new: `array.schema.version` (the core storage version).
* Existing `shape` accessor
  * For new arrays:
    * Have this return the new shape as proposed by core, no longer returning the TileDB domain.
  * For old arrays created before this feature:
    * Return the TileDB domain as now.
* Existing `non_empty_domain` accessor
  * Same behavior for old and new arrays (unaffected by this proposal).
  * Keep this accessor supported, but, with user notes that it’s generally non-useful
  * This should return None (or R equivalent) when there is a schema but no data have been written.
* New `maxshape` accessor
  * Maps the core-level `(lo, hi)` accessor for domain to count-style accessor hi+1. E.g. if the core domain is either `(0,99)` or `(50,99)` then TileDB-SOMA `maxshape` will say 100.
  * Same behavior for old and new arrays.
  * Let users query for what the TileDB domain is, with user notes that it’s the maximum that users can reshape to.
  * Issac suggests: maybe `domain` or `maxshape` (see h5py).
* New `resize` mutator
  * Note: `reshape` means something else in the community (numpy, zarr, h5py), e.g. a 5x20 (total 100 cells) being reinterpreted as 4x25 (still 100 cells). The standard name for changing cell-count is `resize`.
  * For old arrays created before this feature: raise `NotImplementedError`.
  * For new arrays:
    * Will raise `ValueError` if the new shape is smaller on any dim than currently in storage
    * Regardless of whether any data have been written whatsoever
    * Will raise `ValueError` if the new shape exceeds the TileDB domain from create time, which will serve TileDB-SOMA in a role of “max possible shape the user can reshape to”
    * Otherwise, any calls to write from this point will bounds-check writes within this new shape
    * **We don’t expect resize to be multi-writer safe with regard to write ; user notes must be clear on this point**
* New `tiledbsoma_upgrade_shape` method for SparseNDArray and DenseNDArray
  * This will leverage `array.schema.version` to see if an upgrade is needed
  * Leverage core support for storage-version updates
  * This will take a shape argument as in `create`
  * For arrays created with “just-right” size: this will succeed
  * For arrays created with “room-for-growth” / “two billion-ish” size: this will succeed
  * If the user passes a shape which exceeds the current TileDB domain: this will fail
* New `tiledbsoma_upgrade_domain method` for `DataFrame`
  * Same as for `SparseNDArray`/`DenseNDArray` except it will take a domain at the SOMA-API level just as `DataFrame`'s create method

### `tiledbsoma.io`

* The user-facing API has no shape arguments and thus won’t need changing.
* Internally to `tiledbsoma.io`, we’ll still ask the tiledbsoma API for the “big domain” (2 billionish)
* Append mode:
  * Will need a new `resize` method at the `Experiment` level
  * Users will need to:
    * Register as now
    * Call the experiment-level `resize`
      * Could be `exp.resize(...)`, or (better) this could be `tiledbsoma.io.reshape_experiment`
  * In either case: this method will take the new `obs` and `var` counts as inputs:
    * `exp.obs.reshape` to new `obs` count
    * `exp.ms[name].var.reshape` to new `var` count
    * `exp.ms[name].X[name].reshape` to new `obs` count x `var` count
    * `exp.ms[name].obsm[name].reshape` to new `obs` count x same width
    * `exp.ms[name].obsp[name].reshape` to new `obs` count x `obs` count
    * `exp.ms[name].varm[name].reshape` to new `var` count x same width
    * `exp.ms[name].varp[name].reshape` to new `var` count x `var` count
  * Do the individual append-mode writes as now

[c++] Apply subarrays for dense reads and writes
**Issue and/or context:** As tracked on issue #2407 / [[sc-51048]](https://app.shortcut.com/tiledb-inc/story/51048). See also #3364.

Note that the intended Python and R API changes are all agreed on and finalized as described in #2407.

**Changes:**

As found on #3244:

* The main context of #3244 is:
  * For dense arrays only
  * If any dim's subarray range isn't specified, core uses the core domain
  * With new-shape feature-flag enabled, and with core 2.27 where dense arrays _can_ have current domain (they couldn't in 2.26), we are indeed using data-sized core current domain and huge core domain
  * Put those together and we get these problems
  * Note there are a few other issues on this PR, and a few _not_ yet included in this PR, other than that -- and those should be split out into separate PRs
* On this PR I've ben finding callsites, for write and for read, for Python and R, and touching up the ranges which end up being core subarrays on each dim slot
  * This is tedious and error-prone
* What we should do instead is:
  * In one place -- in `libtiledbsoma`, in `ManagedQuery`, before `submit_query`
  * If any dim's range has not been set up to this point, and if the array has a current domain, simply set the ranges on that dim to be the current domain's `(lo, hi)`
  * We know (for a fact) that core will go ahead and use the too-big domain anyway so this is safe

**Notes for Reviewer:**



Discussion / hints:
#2785 is a quick-and-dirty concept-prover -- its sole function is to flush out any API misunderstandings we might have, in prep for 2.25.0 core release.

#2785 is a quick-and-dirty concept-prover -- its sole function is to flush out any API misunderstandings we might have, in prep for 2.25.0 core release.
## [Codecov](https://app.codecov.io/gh/single-cell-data/TileDB-SOMA/pull/3263?dropdown=coverage&src=pr&el=h1&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=single-cell-data) Report
Attention: Patch coverage is `84.61538%` with `2 lines` in your changes missing coverage. Please review.
> Project coverage is 83.81%. Comparing base [(`130ccc6`)](https://app.codecov.io/gh/single-cell-data/TileDB-SOMA/commit/130ccc60007a3df1d40fb5e8902db027443fe728?dropdown=coverage&el=desc&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=single-cell-data) to head [(`febaa7a`)](https://app.codecov.io/gh/single-cell-data/TileDB-SOMA/commit/febaa7a740d7e9c37d635c0910a8cb53ff9d4d6f?dropdown=coverage&el=desc&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=single-cell-data).

<details><summary>Additional details and impacted files</summary>


```diff
@@            Coverage Diff             @@
##             main    #3263      +/-   ##
==========================================
+ Coverage   83.79%   83.81%   +0.01%     
==========================================
  Files          51       51              
  Lines        5567     5578      +11     
==========================================
+ Hits         4665     4675      +10     
- Misses        902      903       +1     
```

| [Flag](https://app.codecov.io/gh/single-cell-data/TileDB-SOMA/pull/3263/flags?src=pr&el=flags&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=single-cell-data) | Coverage Δ | |
|---|---|---|
| [python](https://app.codecov.io/gh/single-cell-data/TileDB-SOMA/pull/3263/flags?src=pr&el=flag&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=single-cell-data) | `83.81% <84.61%> (+0.01%)` | :arrow_up: |

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| [Components](https://app.codecov.io/gh/single-cell-data/TileDB-SOMA/pull/3263/components?src=pr&el=components&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=single-cell-data) | Coverage Δ | |
|---|---|---|
| [python_api](https://app.codecov.io/gh/single-cell-data/TileDB-SOMA/pull/3263/components?src=pr&el=component&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=single-cell-data) | `83.81% <84.61%> (+0.01%)` | :arrow_up: |
| [libtiledbsoma](https://app.codecov.io/gh/single-cell-data/TileDB-SOMA/pull/3263/components?src=pr&el=component&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=single-cell-data) | `∅ <ø> (∅)` | |

</details>
@nguyenv ready for review 🙏 

Fix patch:
diff --git a/apis/python/src/tiledbsoma/_common_nd_array.py b/apis/python/src/tiledbsoma/_common_nd_array.py
index 8a21d7bc03..83853ab082 100644
--- a/apis/python/src/tiledbsoma/_common_nd_array.py
+++ b/apis/python/src/tiledbsoma/_common_nd_array.py
@@ -122,6 +122,7 @@ def _dim_capacity_and_extent(
         cls,
         dim_name: str,
         dim_shape: Optional[int],
+        ndim: int,
         create_options: TileDBCreateOptions,
     ) -> Tuple[int, int]:
         raise NotImplementedError("must be implemented by child class.")
diff --git a/apis/python/src/tiledbsoma/_dense_nd_array.py b/apis/python/src/tiledbsoma/_dense_nd_array.py
index 95d90a411a..7a8bfff7ba 100644
--- a/apis/python/src/tiledbsoma/_dense_nd_array.py
+++ b/apis/python/src/tiledbsoma/_dense_nd_array.py
@@ -101,6 +101,7 @@ def create(
 
         index_column_schema = []
         index_column_data = {}
+        ndim = len(shape)
 
         for dim_idx, dim_shape in enumerate(shape):
             dim_name = f"soma_dim_{dim_idx}"
@@ -128,6 +129,7 @@ def create(
                     # which is taken from the max ranges for the dim datatype.
                     # We pass None here to detect those.
                     None,
+                    ndim,
                     TileDBCreateOptions.from_platform_config(platform_config),
                 )
 
@@ -146,6 +148,7 @@ def create(
                 dim_capacity, dim_extent = cls._dim_capacity_and_extent(
                     dim_name,
                     dim_shape,
+                    ndim,
                     TileDBCreateOptions.from_platform_config(platform_config),
                 )
 
@@ -357,6 +360,7 @@ def _dim_capacity_and_extent(
         cls,
         dim_name: str,
         dim_shape: Optional[int],
+        ndim: int,
         create_options: TileDBCreateOptions,
     ) -> Tuple[int, int]:
         """Given a user-specified shape (maybe ``None``) along a particular dimension,
@@ -365,9 +369,48 @@ def _dim_capacity_and_extent(
         int64 is returned for the capacity -- which is particularly suitable for
         maxdomain.
         """
+
+        # Old news: for dense n-dimensional arrays, the number of bytes for each
+        # core cell is the product of the following:
+        #
+        # * element size (e.g. 4 for float32, 8 for float64)
+        # * extent for dim 0
+        # * extent for dim 1
+        # * ...
+        # * extent for dim n
+        #
+        # With float64 and extent 2048, this memory requirement for n = 1,2,3,4
+        # multiplies out to:
+        #
+        # * n=1: ~10**4
+        # * n=2: ~10**8
+        # * n=3: ~10**11
+        # * n=4: ~10**14
+        #
+        # New news: before core 2.27 we didn't have current-domain support for
+        # dense arrays and so we made the core domain fit the shape -- and we of
+        # course cap each dim slot's extent at the slotwise domain. So if the
+        # array is 3D with shape = (10,20,30) we got tile extents 10, 20, 30.
+        #
+        # But as of core 2.27 we do have current-domain support for dense
+        # arrays, and we make the core domain huge. (Core domain is immutable;
+        # core current domain is upward-resizeable up to the limit which is the
+        # core domain.) This means a default extent of 2048 blows up fast at
+        # higher dimensions.
+        if ndim == 1:
+            default_extent = 2048
+        elif ndim == 2:
+            default_extent = 512
+        elif ndim == 3:
+            default_extent = 128
+        elif ndim >= 4:
+            default_extent = 4
+
         if dim_shape is None:
             dim_capacity = 2**63 - 1
-            dim_extent = min(dim_capacity, create_options.dim_tile(dim_name, 2048))
+            dim_extent = min(
+                dim_capacity, create_options.dim_tile(dim_name, default_extent)
+            )
             # For core: "domain max expanded to multiple of tile extent exceeds max value
             # representable by domain type. Reduce domain max by 1 tile extent to allow for
             # expansion."
@@ -378,6 +421,8 @@ def _dim_capacity_and_extent(
                     "SOMASparseNDArray shape must be a non-zero-length tuple of positive ints or Nones"
                 )
             dim_capacity = dim_shape
-            dim_extent = min(dim_shape, create_options.dim_tile(dim_name, 2048))
+            dim_extent = min(
+                dim_shape, create_options.dim_tile(dim_name, default_extent)
+            )
 
         return (dim_capacity, dim_extent)
diff --git a/apis/python/src/tiledbsoma/_sparse_nd_array.py b/apis/python/src/tiledbsoma/_sparse_nd_array.py
index 585ab90bce..f48747f3ca 100644
--- a/apis/python/src/tiledbsoma/_sparse_nd_array.py
+++ b/apis/python/src/tiledbsoma/_sparse_nd_array.py
@@ -169,6 +169,7 @@ def create(
                     # which is taken from the max ranges for the dim datatype.
                     # We pass None here to detect those.
                     None,
+                    len(shape),
                     TileDBCreateOptions.from_platform_config(platform_config),
                 )
 
@@ -192,6 +193,7 @@ def create(
                 dim_capacity, dim_extent = cls._dim_capacity_and_extent(
                     dim_name,
                     dim_shape,
+                    len(shape),
                     TileDBCreateOptions.from_platform_config(platform_config),
                 )
                 index_column_data[pa_field.name] = [0, dim_capacity - 1, dim_extent]
@@ -498,6 +500,7 @@ def _dim_capacity_and_extent(
         cls,
         dim_name: str,
         dim_shape: Optional[int],
+        ndim: int,  # not needed for sparse
         create_options: TileDBCreateOptions,
     ) -> Tuple[int, int]:
         """Given a user-specified shape (maybe ``None``) along a particular dimension,
diff --git a/libtiledbsoma/src/soma/managed_query.h b/libtiledbsoma/src/soma/managed_query.h
index a1cb26feff..c33d78e519 100644
--- a/libtiledbsoma/src/soma/managed_query.h
+++ b/libtiledbsoma/src/soma/managed_query.h
@@ -439,8 +439,8 @@ class ManagedQuery {
      *
      * The other is a combination of several things. Firstly, is current-domain
      * support which we have for sparse arrays as of core 2.26, and for dense as
-     * of 2.27. Secondly, without current-domain support, we had small domains; with
-     * it, we have huge core domains (2^63-ish) which are immutable, and
+     * of 2.27. Secondly, without current-domain support, we had small domains;
+     * with it, we have huge core domains (2^63-ish) which are immutable, and
      * small current domains which are upward-mutable. (The soma domain and
      * maxdomain, respectively, are core current domain and domain.) Thirdly,
      * if a query doesn't have a subarray set on any


Test patch:
diff --git a/apis/python/tests/test_dense_nd_array.py b/apis/python/tests/test_dense_nd_array.py
index 87b7c29415..d347f95625 100644
--- a/apis/python/tests/test_dense_nd_array.py
+++ b/apis/python/tests/test_dense_nd_array.py
@@ -400,8 +400,8 @@ def test_tile_extents(tmp_path):
             "tiledb": {
                 "create": {
                     "dims": {
-                        "soma_dim_0": {"tile": 2048},
-                        "soma_dim_1": {"tile": 2048},
+                        "soma_dim_0": {"tile": 512},
+                        "soma_dim_1": {"tile": 512},
                     }
                 }
             }
@@ -410,8 +410,17 @@ def test_tile_extents(tmp_path):
 
     with soma.DenseNDArray.open(tmp_path.as_posix()) as A:
         dim_info = json.loads(A.config_options_from_schema().dims)
-        assert int(dim_info["soma_dim_0"]["tile"]) == 100
-        assert int(dim_info["soma_dim_1"]["tile"]) == 2048
+        if soma._flags.DENSE_ARRAYS_CAN_HAVE_CURRENT_DOMAIN:
+            # With new-shape, core current domain is (100,10000) but core domain
+            # is huge, and therefore dim 0 does not get its extent squashed down
+            # to 100.
+            assert int(dim_info["soma_dim_0"]["tile"]) == 512
+            assert int(dim_info["soma_dim_1"]["tile"]) == 512
+        else:
+            # This assumes core domain is (100,10000) and therefore dim 0
+            # gets its extent squashed down to 100.
+            assert int(dim_info["soma_dim_0"]["tile"]) == 100
+            assert int(dim_info["soma_dim_1"]["tile"]) == 512
 
 
 def test_timestamped_ops(tmp_path):