from __future__ import annotations

import re
import sys
from datetime import date, datetime, time
from decimal import Decimal
from enum import Enum
from typing import Any, ClassVar, Dict, List, Literal, Optional, Union

import numpy as np
from numpydantic import NDArray, Shape
from pydantic import BaseModel, ConfigDict, Field, RootModel, field_validator

from ...core.v2_2_0.core_nwb_base import (
    NWBContainer,
    TimeSeries,
    TimeSeriesStartingTime,
    TimeSeriesSync,
)
from ...core.v2_2_0.core_nwb_device import Device


metamodel_version = "None"
version = "2.2.0"


class ConfiguredBaseModel(BaseModel):
    model_config = ConfigDict(
        validate_assignment=True,
        validate_default=True,
        extra="allow",
        arbitrary_types_allowed=True,
        use_enum_values=True,
        strict=False,
    )
    hdf5_path: Optional[str] = Field(
        None, description="The absolute path that this object is stored in an NWB file"
    )
    object_id: Optional[str] = Field(None, description="Unique UUID for each object")

    def __getitem__(self, val: Union[int, slice]) -> Any:
        """Try and get a value from value or "data" if we have it"""
        if hasattr(self, "value") and self.value is not None:
            return self.value[val]
        elif hasattr(self, "data") and self.data is not None:
            return self.data[val]
        else:
            raise KeyError("No value or data field to index from")

    @field_validator("*", mode="wrap")
    @classmethod
    def coerce_value(cls, v: Any, handler) -> Any:
        """Try to rescue instantiation by using the value field"""
        try:
            return handler(v)
        except Exception as e1:
            try:
                return handler(v.value)
            except AttributeError:
                try:
                    return handler(v["value"])
                except (IndexError, KeyError, TypeError):
                    raise e1

    @field_validator("*", mode="before")
    @classmethod
    def coerce_subclass(cls, v: Any, info) -> Any:
        """Recast parent classes into child classes"""
        if isinstance(v, BaseModel):
            annotation = cls.model_fields[info.field_name].annotation
            while hasattr(annotation, "__args__"):
                annotation = annotation.__args__[0]
            try:
                if issubclass(annotation, type(v)) and annotation is not type(v):
                    v = annotation(**{**v.__dict__, **v.__pydantic_extra__})
            except TypeError:
                # fine, annotation is a non-class type like a TypeVar
                pass
        return v


class LinkMLMeta(RootModel):
    root: Dict[str, Any] = {}
    model_config = ConfigDict(frozen=True)

    def __getattr__(self, key: str):
        return getattr(self.root, key)

    def __getitem__(self, key: str):
        return self.root[key]

    def __setitem__(self, key: str, value):
        self.root[key] = value

    def __contains__(self, key: str) -> bool:
        return key in self.root


NUMPYDANTIC_VERSION = "1.2.1"
linkml_meta = LinkMLMeta(
    {
        "annotations": {
            "is_namespace": {"tag": "is_namespace", "value": False},
            "namespace": {"tag": "namespace", "value": "core"},
        },
        "default_prefix": "core.nwb.ogen/",
        "id": "core.nwb.ogen",
        "imports": ["core.nwb.base", "core.nwb.device", "core.nwb.language"],
        "name": "core.nwb.ogen",
    }
)


class OptogeneticSeries(TimeSeries):
    """
    An optogenetic stimulus.
    """

    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta(
        {"from_schema": "core.nwb.ogen", "tree_root": True}
    )

    name: str = Field(...)
    data: NDArray[Shape["* num_times"], float] = Field(
        ...,
        description="""Applied power for optogenetic stimulus, in watts.""",
        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
    )
    site: Union[OptogeneticStimulusSite, str] = Field(
        ...,
        json_schema_extra={
            "linkml_meta": {
                "annotations": {"source_type": {"tag": "source_type", "value": "link"}},
                "any_of": [{"range": "OptogeneticStimulusSite"}, {"range": "string"}],
            }
        },
    )
    description: Optional[str] = Field(
        "no description",
        description="""Description of the time series.""",
        json_schema_extra={"linkml_meta": {"ifabsent": "string(no description)"}},
    )
    comments: Optional[str] = Field(
        "no comments",
        description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""",
        json_schema_extra={"linkml_meta": {"ifabsent": "string(no comments)"}},
    )
    starting_time: Optional[TimeSeriesStartingTime] = Field(
        None,
        description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""",
    )
    timestamps: Optional[NDArray[Shape["* num_times"], float]] = Field(
        None,
        description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""",
        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
    )
    control: Optional[NDArray[Shape["* num_times"], int]] = Field(
        None,
        description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""",
        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
    )
    control_description: Optional[NDArray[Shape["* num_control_values"], str]] = Field(
        None,
        description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""",
        json_schema_extra={
            "linkml_meta": {"array": {"dimensions": [{"alias": "num_control_values"}]}}
        },
    )
    sync: Optional[TimeSeriesSync] = Field(
        None,
        description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""",
    )


class OptogeneticStimulusSite(NWBContainer):
    """
    A site of optogenetic stimulation.
    """

    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta(
        {"from_schema": "core.nwb.ogen", "tree_root": True}
    )

    name: str = Field(...)
    description: str = Field(..., description="""Description of stimulation site.""")
    excitation_lambda: float = Field(..., description="""Excitation wavelength, in nm.""")
    location: str = Field(
        ...,
        description="""Location of the stimulation site. Specify the area, layer, comments on estimation of area/layer, stereotaxic coordinates if in vivo, etc. Use standard atlas names for anatomical regions when possible.""",
    )
    device: Union[Device, str] = Field(
        ...,
        json_schema_extra={
            "linkml_meta": {
                "annotations": {"source_type": {"tag": "source_type", "value": "link"}},
                "any_of": [{"range": "Device"}, {"range": "string"}],
            }
        },
    )


# Model rebuild
# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
OptogeneticSeries.model_rebuild()
OptogeneticStimulusSite.model_rebuild()
