(a, axis=None, keepdims=False, split_every=None, out=None)
| 264 | |
| 265 | @derived_from(np) |
| 266 | def nanmin(a, axis=None, keepdims=False, split_every=None, out=None): |
| 267 | if np.isnan(a.size): |
| 268 | raise ValueError(f"Arrays chunk sizes are unknown. {unknown_chunk_message}") |
| 269 | if a.size == 0: |
| 270 | raise ValueError( |
| 271 | "zero-size array to reduction operation fmin which has no identity" |
| 272 | ) |
| 273 | return reduction( |
| 274 | a, |
| 275 | _nanmin_skip, |
| 276 | _nanmin_skip, |
| 277 | axis=axis, |
| 278 | keepdims=keepdims, |
| 279 | dtype=a.dtype, |
| 280 | split_every=split_every, |
| 281 | out=out, |
| 282 | ) |
| 283 | |
| 284 | |
| 285 | def _nanmin_skip(x_chunk, axis, keepdims): |
nothing calls this directly
no test coverage detected