from ..utils import PrepareTapeData, PathHandler, hdf5Loader
import pickle as pkl
from tensorflow.keras.utils import HDF5Matrix
from typing import TypeVar, Type, Union, Dict
import numpy as np
T = TypeVar('T', bound='Tape2Prosit')


class Tape2Prosit(PrepareTapeData, PathHandler, hdf5Loader):
    """Convert Tape result into Prsoit HDF5"""
    def __init__(self, prosit_hdf5_data: HDF5Matrix, tape_result: dict)->None:
        PrepareTapeData.__init__(self, prosit_hdf5_data, tape_result)
        PathHandler.__init__(self)
        hdf5Loader.__init__(self)
        
    @classmethod
    def fromPath(cls: Type[T], prositHDF5path: str, tapeOutPath: str)->T:
        """Init from Tape2Prosit"""
        if not PathHandler.isFile(prositHDF5path):
                raise RuntimeError(f"Path {prositHDF5path} to prosit hdf5-file don't exist.")
        if not PathHandler.isFile(tapeOutPath):
                raise RuntimeError(f"Path {tapeOutPath} to tape output-file don't exist.")

        prositHDF5data = cls.from_hdf5(prositHDF5path)
        tapeOutData = np.load(tapeOutPath)

        return cls(prositHDF5data, tapeOutData)

    def convert(self, out_path: str)->None:
        """Convert Tape result into Prosit hdf5-file"""
        tape_data_hdf5 = self.createTapeHDF5Dict()
        
        self.deleteFile(out_path)
        self.to_hdf5(tape_data_hdf5, out_path)
        print("HDF5 file has been successfully saved at {}".format(out_path))

    def get_sa(self):
        tape_data_hdf5 = self.createTapeHDF5Dict()
        return tape_data_hdf5["spectral_angle"]

0f565d052f1927415225fe4274849ed0694c56fb
<mask token>


class Tape2Prosit(PrepareTapeData, PathHandler, hdf5Loader):
    <mask token>

    def __init__(self, prosit_hdf5_data: HDF5Matrix, tape_result: dict) ->None:
        PrepareTapeData.__init__(self, prosit_hdf5_data, tape_result)
        PathHandler.__init__(self)
        hdf5Loader.__init__(self)

    @classmethod
    def fromPath(cls: Type[T], prositHDF5path: str, tapeOutPath: str) ->T:
        """Init from Tape2Prosit"""
        if not PathHandler.isFile(prositHDF5path):
            raise RuntimeError(
                f"Path {prositHDF5path} to prosit hdf5-file don't exist.")
        if not PathHandler.isFile(tapeOutPath):
            raise RuntimeError(
                f"Path {tapeOutPath} to tape output-file don't exist.")
        prositHDF5data = cls.from_hdf5(prositHDF5path)
        tapeOutData = np.load(tapeOutPath)
        return cls(prositHDF5data, tapeOutData)

    def convert(self, out_path: str) ->None:
        """Convert Tape result into Prosit hdf5-file"""
        tape_data_hdf5 = self.createTapeHDF5Dict()
        self.deleteFile(out_path)
        self.to_hdf5(tape_data_hdf5, out_path)
        print('HDF5 file has been successfully saved at {}'.format(out_path))

    def get_sa(self):
        tape_data_hdf5 = self.createTapeHDF5Dict()
        return tape_data_hdf5['spectral_angle']

<mask token>


class Tape2Prosit(PrepareTapeData, PathHandler, hdf5Loader):
    """Convert Tape result into Prsoit HDF5"""

    def __init__(self, prosit_hdf5_data: HDF5Matrix, tape_result: dict) ->None:
        PrepareTapeData.__init__(self, prosit_hdf5_data, tape_result)
        PathHandler.__init__(self)
        hdf5Loader.__init__(self)

    @classmethod
    def fromPath(cls: Type[T], prositHDF5path: str, tapeOutPath: str) ->T:
        """Init from Tape2Prosit"""
        if not PathHandler.isFile(prositHDF5path):
            raise RuntimeError(
                f"Path {prositHDF5path} to prosit hdf5-file don't exist.")
        if not PathHandler.isFile(tapeOutPath):
            raise RuntimeError(
                f"Path {tapeOutPath} to tape output-file don't exist.")
        prositHDF5data = cls.from_hdf5(prositHDF5path)
        tapeOutData = np.load(tapeOutPath)
        return cls(prositHDF5data, tapeOutData)

    def convert(self, out_path: str) ->None:
        """Convert Tape result into Prosit hdf5-file"""
        tape_data_hdf5 = self.createTapeHDF5Dict()
        self.deleteFile(out_path)
        self.to_hdf5(tape_data_hdf5, out_path)
        print('HDF5 file has been successfully saved at {}'.format(out_path))

    def get_sa(self):
        tape_data_hdf5 = self.createTapeHDF5Dict()
        return tape_data_hdf5['spectral_angle']

<mask token>
T = TypeVar('T', bound='Tape2Prosit')


class Tape2Prosit(PrepareTapeData, PathHandler, hdf5Loader):
    """Convert Tape result into Prsoit HDF5"""

    def __init__(self, prosit_hdf5_data: HDF5Matrix, tape_result: dict) ->None:
        PrepareTapeData.__init__(self, prosit_hdf5_data, tape_result)
        PathHandler.__init__(self)
        hdf5Loader.__init__(self)

    @classmethod
    def fromPath(cls: Type[T], prositHDF5path: str, tapeOutPath: str) ->T:
        """Init from Tape2Prosit"""
        if not PathHandler.isFile(prositHDF5path):
            raise RuntimeError(
                f"Path {prositHDF5path} to prosit hdf5-file don't exist.")
        if not PathHandler.isFile(tapeOutPath):
            raise RuntimeError(
                f"Path {tapeOutPath} to tape output-file don't exist.")
        prositHDF5data = cls.from_hdf5(prositHDF5path)
        tapeOutData = np.load(tapeOutPath)
        return cls(prositHDF5data, tapeOutData)

    def convert(self, out_path: str) ->None:
        """Convert Tape result into Prosit hdf5-file"""
        tape_data_hdf5 = self.createTapeHDF5Dict()
        self.deleteFile(out_path)
        self.to_hdf5(tape_data_hdf5, out_path)
        print('HDF5 file has been successfully saved at {}'.format(out_path))

    def get_sa(self):
        tape_data_hdf5 = self.createTapeHDF5Dict()
        return tape_data_hdf5['spectral_angle']

from ..utils import PrepareTapeData, PathHandler, hdf5Loader
import pickle as pkl
from tensorflow.keras.utils import HDF5Matrix
from typing import TypeVar, Type, Union, Dict
import numpy as np
T = TypeVar('T', bound='Tape2Prosit')


class Tape2Prosit(PrepareTapeData, PathHandler, hdf5Loader):
    """Convert Tape result into Prsoit HDF5"""

    def __init__(self, prosit_hdf5_data: HDF5Matrix, tape_result: dict) ->None:
        PrepareTapeData.__init__(self, prosit_hdf5_data, tape_result)
        PathHandler.__init__(self)
        hdf5Loader.__init__(self)

    @classmethod
    def fromPath(cls: Type[T], prositHDF5path: str, tapeOutPath: str) ->T:
        """Init from Tape2Prosit"""
        if not PathHandler.isFile(prositHDF5path):
            raise RuntimeError(
                f"Path {prositHDF5path} to prosit hdf5-file don't exist.")
        if not PathHandler.isFile(tapeOutPath):
            raise RuntimeError(
                f"Path {tapeOutPath} to tape output-file don't exist.")
        prositHDF5data = cls.from_hdf5(prositHDF5path)
        tapeOutData = np.load(tapeOutPath)
        return cls(prositHDF5data, tapeOutData)

    def convert(self, out_path: str) ->None:
        """Convert Tape result into Prosit hdf5-file"""
        tape_data_hdf5 = self.createTapeHDF5Dict()
        self.deleteFile(out_path)
        self.to_hdf5(tape_data_hdf5, out_path)
        print('HDF5 file has been successfully saved at {}'.format(out_path))

    def get_sa(self):
        tape_data_hdf5 = self.createTapeHDF5Dict()
        return tape_data_hdf5['spectral_angle']

from ..utils import PrepareTapeData, PathHandler, hdf5Loader
import pickle as pkl
from tensorflow.keras.utils import HDF5Matrix
from typing import TypeVar, Type, Union, Dict
import numpy as np
T = TypeVar('T', bound='Tape2Prosit')


class Tape2Prosit(PrepareTapeData, PathHandler, hdf5Loader):
    """Convert Tape result into Prsoit HDF5"""
    def __init__(self, prosit_hdf5_data: HDF5Matrix, tape_result: dict)->None:
        PrepareTapeData.__init__(self, prosit_hdf5_data, tape_result)
        PathHandler.__init__(self)
        hdf5Loader.__init__(self)
        
    @classmethod
    def fromPath(cls: Type[T], prositHDF5path: str, tapeOutPath: str)->T:
        """Init from Tape2Prosit"""
        if not PathHandler.isFile(prositHDF5path):
                raise RuntimeError(f"Path {prositHDF5path} to prosit hdf5-file don't exist.")
        if not PathHandler.isFile(tapeOutPath):
                raise RuntimeError(f"Path {tapeOutPath} to tape output-file don't exist.")

        prositHDF5data = cls.from_hdf5(prositHDF5path)
        tapeOutData = np.load(tapeOutPath)

        return cls(prositHDF5data, tapeOutData)

    def convert(self, out_path: str)->None:
        """Convert Tape result into Prosit hdf5-file"""
        tape_data_hdf5 = self.createTapeHDF5Dict()
        
        self.deleteFile(out_path)
        self.to_hdf5(tape_data_hdf5, out_path)
        print("HDF5 file has been successfully saved at {}".format(out_path))

    def get_sa(self):
        tape_data_hdf5 = self.createTapeHDF5Dict()
        return tape_data_hdf5["spectral_angle"]
