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more texts. Fix coercion with ndarrays and vectordata, incl numpydantic 1.3.3 making ndarray types callable

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sneakers-the-rat 2024-08-13 23:38:53 -07:00
parent 980db25b15
commit 43ff3503dc
Signed by untrusted user who does not match committer: jonny
GPG key ID: 6DCB96EF1E4D232D
4 changed files with 241 additions and 165 deletions
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nwb_linkml/pdm.lock
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@ -5,7 +5,7 @@
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@ -102,7 +102,7 @@ name = "blinker"
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@ -219,7 +219,7 @@ name = "click"
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@ -364,7 +372,7 @@ files = [
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@ -1046,8 +1034,8 @@ dependencies = [
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name = "setuptools" name = "setuptools"
version = "72.1.0" version = "72.2.0"
requires_python = ">=3.8" requires_python = ">=3.8"
summary = "Easily download, build, install, upgrade, and uninstall Python packages" summary = "Easily download, build, install, upgrade, and uninstall Python packages"
groups = ["dev", "plot", "tests"] groups = ["plot"]
files = [ files = [
{file = "setuptools-72.1.0-py3-none-any.whl", hash = "sha256:5a03e1860cf56bb6ef48ce186b0e557fdba433237481a9a625176c2831be15d1"}, {file = "setuptools-72.2.0-py3-none-any.whl", hash = "sha256:f11dd94b7bae3a156a95ec151f24e4637fb4fa19c878e4d191bfb8b2d82728c4"},
{file = "setuptools-72.1.0.tar.gz", hash = "sha256:8d243eff56d095e5817f796ede6ae32941278f542e0f941867cc05ae52b162ec"}, {file = "setuptools-72.2.0.tar.gz", hash = "sha256:80aacbf633704e9c8bfa1d99fa5dd4dc59573efcf9e4042c13d3bcef91ac2ef9"},
] ]
[[package]] [[package]]
@ -1987,7 +1946,7 @@ name = "tenacity"
version = "9.0.0" version = "9.0.0"
requires_python = ">=3.8" requires_python = ">=3.8"
summary = "Retry code until it succeeds" summary = "Retry code until it succeeds"
groups = ["dev", "plot", "tests"] groups = ["plot"]
files = [ files = [
{file = "tenacity-9.0.0-py3-none-any.whl", hash = "sha256:93de0c98785b27fcf659856aa9f54bfbd399e29969b0621bc7f762bd441b4539"}, {file = "tenacity-9.0.0-py3-none-any.whl", hash = "sha256:93de0c98785b27fcf659856aa9f54bfbd399e29969b0621bc7f762bd441b4539"},
{file = "tenacity-9.0.0.tar.gz", hash = "sha256:807f37ca97d62aa361264d497b0e31e92b8027044942bfa756160d908320d73b"}, {file = "tenacity-9.0.0.tar.gz", hash = "sha256:807f37ca97d62aa361264d497b0e31e92b8027044942bfa756160d908320d73b"},
@ -2135,7 +2094,7 @@ name = "werkzeug"
version = "3.0.3" version = "3.0.3"
requires_python = ">=3.8" requires_python = ">=3.8"
summary = "The comprehensive WSGI web application library." summary = "The comprehensive WSGI web application library."
groups = ["dev", "plot", "tests"] groups = ["plot"]
dependencies = [ dependencies = [
"MarkupSafe>=2.1.1", "MarkupSafe>=2.1.1",
] ]
@ -2190,7 +2149,7 @@ name = "zipp"
version = "3.20.0" version = "3.20.0"
requires_python = ">=3.8" requires_python = ">=3.8"
summary = "Backport of pathlib-compatible object wrapper for zip files" summary = "Backport of pathlib-compatible object wrapper for zip files"
groups = ["dev", "plot", "tests"] groups = ["plot"]
files = [ files = [
{file = "zipp-3.20.0-py3-none-any.whl", hash = "sha256:58da6168be89f0be59beb194da1250516fdaa062ccebd30127ac65d30045e10d"}, {file = "zipp-3.20.0-py3-none-any.whl", hash = "sha256:58da6168be89f0be59beb194da1250516fdaa062ccebd30127ac65d30045e10d"},
{file = "zipp-3.20.0.tar.gz", hash = "sha256:0145e43d89664cfe1a2e533adc75adafed82fe2da404b4bbb6b026c0157bdb31"}, {file = "zipp-3.20.0.tar.gz", hash = "sha256:0145e43d89664cfe1a2e533adc75adafed82fe2da404b4bbb6b026c0157bdb31"},

2
nwb_linkml/pyproject.toml
View file

@ -20,7 +20,7 @@ dependencies = [
"pydantic-settings>=2.0.3", "pydantic-settings>=2.0.3",
"tqdm>=4.66.1", "tqdm>=4.66.1",
'typing-extensions>=4.12.2;python_version<"3.11"', 'typing-extensions>=4.12.2;python_version<"3.11"',
"numpydantic>=1.3.1", "numpydantic>=1.3.3",
"black>=24.4.2", "black>=24.4.2",
"pandas>=2.2.2", "pandas>=2.2.2",
] ]

31
nwb_linkml/src/nwb_linkml/includes/hdmf.py
View file

@ -49,7 +49,7 @@ class DynamicTableMixin(BaseModel):
""" """
model_config = ConfigDict(extra="allow") model_config = ConfigDict(extra="allow")
__pydantic_extra__: Dict[str, Union[list, "NDArray", "VectorDataMixin"]] __pydantic_extra__: Dict[str, Union["VectorDataMixin", "VectorIndexMixin", "NDArray", list]]
NON_COLUMN_FIELDS: ClassVar[tuple[str]] = ( NON_COLUMN_FIELDS: ClassVar[tuple[str]] = (
"name", "name",
"colnames", "colnames",
@ -249,8 +249,9 @@ class DynamicTableMixin(BaseModel):
model["colnames"] = colnames model["colnames"] = colnames
return model return model
@model_validator(mode="after") @model_validator(mode="before")
def cast_extra_columns(self) -> "DynamicTableMixin": @classmethod
def cast_extra_columns(cls, model: Dict[str, Any]) -> Dict:
""" """
If extra columns are passed as just lists or arrays, cast to VectorData If extra columns are passed as just lists or arrays, cast to VectorData
before we resolve targets for VectorData and VectorIndex pairs. before we resolve targets for VectorData and VectorIndex pairs.
@ -258,22 +259,20 @@ class DynamicTableMixin(BaseModel):
See :meth:`.cast_specified_columns` for handling columns in the class specification See :meth:`.cast_specified_columns` for handling columns in the class specification
""" """
# if columns are not in the specification, cast to a generic VectorData # if columns are not in the specification, cast to a generic VectorData
for key, val in self.__pydantic_extra__.items(): for key, val in model.items():
if key in cls.model_fields:
continue
if not isinstance(val, (VectorData, VectorIndex)): if not isinstance(val, (VectorData, VectorIndex)):
try: try:
if key.endswith("_index"): if key.endswith("_index"):
self.__pydantic_extra__[key] = VectorIndex( model[key] = VectorIndex(name=key, description="", value=val)
name=key, description="", value=val
)
else: else:
self.__pydantic_extra__[key] = VectorData( model[key] = VectorData(name=key, description="", value=val)
name=key, description="", value=val
)
except ValidationError as e: except ValidationError as e:
raise ValidationError( raise ValidationError(
f"field {key} cannot be cast to VectorData from {val}" f"field {key} cannot be cast to VectorData from {val}"
) from e ) from e
return self return model
@model_validator(mode="after") @model_validator(mode="after")
def resolve_targets(self) -> "DynamicTableMixin": def resolve_targets(self) -> "DynamicTableMixin":
@ -285,6 +284,8 @@ class DynamicTableMixin(BaseModel):
# find an index # find an index
idx = None idx = None
for field_name in self.model_fields_set: for field_name in self.model_fields_set:
if field_name in self.NON_COLUMN_FIELDS or field_name == key:
continue
# implicit name-based index # implicit name-based index
field = getattr(self, field_name) field = getattr(self, field_name)
if isinstance(field, VectorIndex) and ( if isinstance(field, VectorIndex) and (
@ -323,10 +324,14 @@ class DynamicTableMixin(BaseModel):
""" """
try: try:
return handler(val) return handler(val)
except ValidationError: except ValidationError as e:
annotation = cls.model_fields[info.field_name].annotation annotation = cls.model_fields[info.field_name].annotation
if type(annotation).__name__ == "_UnionGenericAlias": if type(annotation).__name__ == "_UnionGenericAlias":
annotation = annotation.__args__[0] annotation = annotation.__args__[0]
try:
# should pass if we're supposed to be a VectorData column
# don't want to override intention here by insisting that it is
# *actually* a VectorData column in case an NDArray has been specified for now
return handler( return handler(
annotation( annotation(
val, val,
@ -334,6 +339,8 @@ class DynamicTableMixin(BaseModel):
description=cls.model_fields[info.field_name].description, description=cls.model_fields[info.field_name].description,
) )
) )
except Exception:
raise e
class VectorDataMixin(BaseModel, Generic[T]): class VectorDataMixin(BaseModel, Generic[T]):

130
nwb_linkml/tests/test_includes/test_hdmf.py
View file

@ -1,6 +1,8 @@
import numpy as np import numpy as np
import pandas as pd import pandas as pd
import pytest
from numpydantic import NDArray, Shape from numpydantic import NDArray, Shape
from pydantic import ValidationError
from nwb_linkml.includes import hdmf from nwb_linkml.includes import hdmf
from nwb_linkml.includes.hdmf import DynamicTableMixin, VectorDataMixin, VectorIndexMixin from nwb_linkml.includes.hdmf import DynamicTableMixin, VectorDataMixin, VectorIndexMixin
@ -289,17 +291,125 @@ def test_dynamictable_mixin_getattr():
""" """
class MyDT(DynamicTableMixin): class MyDT(DynamicTableMixin):
existing_col: NDArray[Shape["* col"], int] existing_col: hdmf.VectorData[NDArray[Shape["* col"], int]]
class AModel(DynamicTableMixin):
col: hdmf.VectorData[NDArray[Shape["3, 3"], int]]
col = hdmf.VectorData(value=np.arange(10)) col = hdmf.VectorData(value=np.arange(10))
inst = MyDT(existing_col=col) inst = MyDT(existing_col=col)
# regular lookup for attrs that exist
# pdb.set_trace() # regular lookup for attrs that exist
# inst.existing_col assert isinstance(inst.existing_col, hdmf.VectorData)
# assert inst.existing_col == col assert all(inst.existing_col.value == col.value)
# df lookup otherwise
# inst.columns # df lookup for thsoe that don't
assert isinstance(inst.columns, pd.Index)
def test_dynamictable_coercion():
"""
Dynamictable should coerce arrays into vectordata objects for known and unknown cols
"""
class MyDT(DynamicTableMixin):
existing_col: hdmf.VectorData[NDArray[Shape["* col"], int]]
cols = {
"existing_col": np.arange(10),
"new_col_1": np.arange(10),
}
inst = MyDT(**cols)
assert isinstance(inst.existing_col, hdmf.VectorData)
assert isinstance(inst.new_col_1, hdmf.VectorData)
assert all(inst.existing_col.value == np.arange(10))
assert all(inst.new_col_1.value == np.arange(10))
def test_dynamictable_create_id():
class MyDT(DynamicTableMixin):
existing_col: hdmf.VectorData[NDArray[Shape["* col"], int]]
cols = {
"existing_col": np.arange(10),
}
inst = MyDT(**cols)
assert all(inst.id == np.arange(10))
def test_dynamictable_resolve_index():
"""
Dynamictable should resolve and connect data to indices, explicit and implicit
"""
class MyDT(DynamicTableMixin):
existing_col: hdmf.VectorData[NDArray[Shape["* col"], int]]
cols = {
"existing_col": np.arange(10),
"new_col_1": hdmf.VectorData(value=np.arange(10)),
"new_col_2": hdmf.VectorData(value=np.arange(10)),
}
# explicit index with mismatching name
cols["weirdname_index"] = hdmf.VectorIndex(value=np.arange(10), target=cols["new_col_1"])
# implicit index with matching name
cols["new_col_2_index"] = hdmf.VectorIndex(value=np.arange(10))
inst = MyDT(**cols)
assert inst.weirdname_index.target is inst.new_col_1
assert inst.new_col_2_index.target is inst.new_col_2
assert inst.new_col_1._index is inst.weirdname_index
assert inst.new_col_2._index is inst.new_col_2_index
def dynamictable_assert_equal_length():
"""
Dynamictable validates that columns are of equal length
"""
class MyDT(DynamicTableMixin):
existing_col: NDArray[Shape["* col"], int]
cols = {
"existing_col": np.arange(10),
"new_col_1": hdmf.VectorData(value=np.arange(11)),
}
with pytest.raises(ValidationError, pattern="Columns are not of equal length"):
_ = MyDT(**cols)
cols = {
"existing_col": np.arange(11),
"new_col_1": hdmf.VectorData(value=np.arange(10)),
}
with pytest.raises(ValidationError, pattern="Columns are not of equal length"):
_ = MyDT(**cols)
# wrong lengths are fine as long as the index is good
cols = {
"existing_col": np.arange(10),
"new_col_1": hdmf.VectorData(value=np.arange(100)),
"new_col_1_index": hdmf.VectorIndex(value=np.arange(0, 100, 10) + 10),
}
_ = MyDT(**cols)
# but not fine if the index is not good
cols = {
"existing_col": np.arange(10),
"new_col_1": hdmf.VectorData(value=np.arange(100)),
"new_col_1_index": hdmf.VectorIndex(value=np.arange(0, 100, 5) + 5),
}
with pytest.raises(ValidationError, pattern="Columns are not of equal length"):
_ = MyDT(**cols)
def test_vectordata_generic_numpydantic_validation():
"""
Using VectorData as a generic with a numpydantic array annotation should still validate
Simple test here because numpydantic validation is tested in numpydantic itself,
we just want to check that the annotations work as validation and it doesn't just
"""
class MyDT(DynamicTableMixin):
existing_col: NDArray[Shape["3 col"], int]
with pytest.raises(ValidationError):
_ = MyDT(existing_col=np.zeros((4, 5, 6), dtype=int))