westonpace commented on issue #35508:
URL: https://github.com/apache/arrow/issues/35508#issuecomment-1540932823
> Is it possible to alter the scale function used in the implementation? I'm
not sure which scale function you have implemented but it would be nice to have
some control over this!
I don't know enough about tdigest to answer this. Here are the current
options:
```
Help on function tdigest in module pyarrow.compute:
tdigest(array, /, q=0.5, *, delta=100, buffer_size=500, skip_nulls=True,
min_count=0, options=None, memory_pool=None)
Approximate quantiles of a numeric array with T-Digest algorithm.
By default, 0.5 quantile (median) is returned.
Nulls and NaNs are ignored.
An array of nulls is returned if there is no valid data point.
Parameters
----------
array : Array-like
Argument to compute function.
q : double or sequence of double, default 0.5
Quantiles to approximate. All values must be in [0, 1].
delta : int, default 100
Compression parameter for the T-digest algorithm.
buffer_size : int, default 500
Buffer size for the T-digest algorithm.
skip_nulls : bool, default True
Whether to skip (ignore) nulls in the input.
If False, any null in the input forces the output to null.
min_count : int, default 0
Minimum number of non-null values in the input. If the number
of non-null values is below `min_count`, the output is null.
options : pyarrow.compute.TDigestOptions, optional
Alternative way of passing options.
memory_pool : pyarrow.MemoryPool, optional
If not passed, will allocate memory from the default memory pool.
```
If that isn't enough then you could probably open a separate issue to
request a configurable scale.
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