"""
Generic Writer class
"""


import os
from abc import abstractmethod
from typing import Any, Dict

import imageio
import numpy as np
import torch
from omegaconf import DictConfig
from torch.utils.tensorboard import SummaryWriter
from torchtyping import TensorType

import mattport.utils.writer
from mattport.utils import comms
from mattport.utils.decorators import check_main_thread, decorate_all

to8b = lambda x: (255 * torch.clamp(x, min=0, max=1)).to(torch.uint8)
EVENT_WRITERS = []


def write_event(args: Dict[str, Any]):
    """write out values for all the event writers"""
    assert comms.is_main_process(), "Writing out with process other than main"
    for writer in EVENT_WRITERS:
        if "x" in args:
            writer.write_image(**args)
        elif "scalar" in args:
            writer.write_scalar(**args)
        elif "scalar_dict" in args:
            writer.write_scalar_dict(**args)
        else:
            raise NotImplementedError


def setup_event_writers(config: DictConfig) -> None:
    """Initialization of all event writers specified in config"""
    if comms.is_main_process():
        for writer_type in config:
            curr_writer = getattr(mattport.utils.writer, writer_type)
            EVENT_WRITERS.append(curr_writer(config[writer_type].save_dir))


def get_tensorboard_name(name: str, group: str = None, prefix: str = None):
    """Returns a string for tensorboard with an optional group and prefix.
    Where tensorboard_name has the form `group/prefix-name`.
    """
    group_string = f"{group}/" if group else ""
    prefix_string = f"{prefix}" if prefix else ""
    tensorboard_name = f"{group_string}{prefix_string}{name}"
    return tensorboard_name


class Writer:
    """Writer class"""

    def __init__(self, save_dir: str):
        self.save_dir = save_dir

    @abstractmethod
    def write_image(
        self, name: str, x: TensorType["H", "W", "C"], step: int, group: str = None, prefix: str = None
    ) -> None:
        """_summary_

        Args:
            name (str): data identifier
            x (TensorType["H", "W", "C"]): rendered image to write
            step (int): the time step to log
            group (str): the group e.g., "Loss", "Accuracy", "Time"
            prefix (str): the prefix e.g., "train-", "test-"
        """
        raise NotImplementedError

    @abstractmethod
    def write_scalar(self, name: str, scalar: float, step: int, group: str = None, prefix: str = None) -> None:
        """Required method to write a single scalar value to the logger

        Args:
            name (str): data identifier
            step (int): the time step to log
            group (str): the group e.g., "Loss", "Accuracy", "Time"
            prefix (str): the prefix e.g., "train-", "test-"
        """
        raise NotImplementedError

    @check_main_thread
    def write_scalar_dict(
        self, scalar_dict: Dict[str, float], step: int, group: str = None, prefix: str = None
    ) -> None:
        """Function that writes out all scalars from a given dictionary to the logger

        Args:
            scalar_dict (dict): dictionary containing all scalar values with key names and quantities
            step (int): the time step to log
            group (str): the group e.g., "Loss", "Accuracy", "Time"
            prefix (str): the prefix e.g., "train-", "test-"
        """
        for name, scalar in scalar_dict.items():
            self.write_scalar(name, scalar, step, group=group, prefix=prefix)


@decorate_all([check_main_thread])
class TensorboardWriter(Writer):
    """Tensorboard Writer Class"""

    def __init__(self, save_dir: str):
        super().__init__(save_dir)
        self.tb_writer = SummaryWriter(log_dir=self.save_dir)

    def write_image(
        self, name: str, x: TensorType["H", "W", "C"], step: int, group: str = None, prefix: str = None
    ) -> None:
        """_summary_

        Args:
            name (str): data identifier
            x (TensorType["H", "W", "C"]): rendered image to write
        """
        x = to8b(x)
        tensorboard_name = get_tensorboard_name(name, group=group, prefix=prefix)
        self.tb_writer.add_image(tensorboard_name, x, step, dataformats="HWC")

    def write_scalar(self, name: str, scalar: float, step: int, group: str = None, prefix: str = None) -> None:
        """Tensorboard method to write a single scalar value to the logger

        Args:
            name (str): data identifier
            x (float): x value to write
            y (float): y value to write
            group (str)): a prefix to group tensorboard scalars
        """
        tensorboard_name = get_tensorboard_name(name, group=group, prefix=prefix)
        self.tb_writer.add_scalar(tensorboard_name, scalar, step)


@decorate_all([check_main_thread])
class LocalWriter(Writer):
    """Local Writer Class"""

    def write_image(
        self, name: str, x: TensorType["H", "W", "C"], step: int, group: str = None, prefix: str = None
    ) -> None:
        x = to8b(x)
        image_path = os.path.join(self.save_dir, f"{name}.jpg")
        imageio.imwrite(image_path, np.uint8(x.cpu().numpy() * 255.0))

    def write_scalar(self, name: str, scalar: float, step: int, group: str = None, prefix: str = None) -> None:
        raise NotImplementedError