





'''simple docstring'''




import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union

import pandas as pd
import pyarrow as pa

import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datasets.utils.py_utils import Literal


_SCREAMING_SNAKE_CASE							     =			datasets.utils.logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE							     =			["names", "prefix"]
_SCREAMING_SNAKE_CASE							     =			["warn_bad_lines", "error_bad_lines", "mangle_dupe_cols"]
_SCREAMING_SNAKE_CASE							     =			["encoding_errors", "on_bad_lines"]
_SCREAMING_SNAKE_CASE							     =			["date_format"]
@dataclass
class 			_lowerCAmelCase		(			datasets.BuilderConfig	):






     """simple docstring"""






     snake_case_						      =   ","
     snake_case_						      =   None
     snake_case_						      =   "infer"
     snake_case_						      =   None
     snake_case_						      =   None
     snake_case_						      =   None
     snake_case_						      =   None
     snake_case_						      =   None
     snake_case_						      =   True
     snake_case_						      =   None
     snake_case_						      =   None
     snake_case_						      =   None
     snake_case_						      =   None
     snake_case_						      =   False
     snake_case_						      =   None
     snake_case_						      =   None
     snake_case_						      =   None
     snake_case_						      =   True
     snake_case_						      =   True
     snake_case_						      =   False
     snake_case_						      =   True
     snake_case_						      =   None
     snake_case_						      =   "."
     snake_case_						      =   None
     snake_case_						      =   '"'
     snake_case_						      =   0
     snake_case_						      =   None
     snake_case_						      =   None
     snake_case_						      =   None
     snake_case_						      =   None
     snake_case_						      =   True
     snake_case_						      =   True
     snake_case_						      =   0
     snake_case_						      =   True
     snake_case_						      =   False
     snake_case_						      =   None
     snake_case_						      =   1_0000
     snake_case_						      =   None
     snake_case_						      =   "strict"
     snake_case_						      =   "error"
     snake_case_						      =   None



     def      lowerCAmelCase			(   self							:			str						)->	Any:
        if self.delimiter is not None:
           snake_case 						=   self.delimiter
        if self.column_names is not None:
           snake_case 						=   self.column_names



     @property
     def      lowerCAmelCase			(   self							:			Any						)->	Any:
        snake_case 						=   {
            """sep""": self.sep,
            """header""": self.header,
            """names""": self.names,
            """index_col""": self.index_col,
            """usecols""": self.usecols,
            """prefix""": self.prefix,
            """mangle_dupe_cols""": self.mangle_dupe_cols,
            """engine""": self.engine,
            """converters""": self.converters,
            """true_values""": self.true_values,
            """false_values""": self.false_values,
            """skipinitialspace""": self.skipinitialspace,
            """skiprows""": self.skiprows,
            """nrows""": self.nrows,
            """na_values""": self.na_values,
            """keep_default_na""": self.keep_default_na,
            """na_filter""": self.na_filter,
            """verbose""": self.verbose,
            """skip_blank_lines""": self.skip_blank_lines,
            """thousands""": self.thousands,
            """decimal""": self.decimal,
            """lineterminator""": self.lineterminator,
            """quotechar""": self.quotechar,
            """quoting""": self.quoting,
            """escapechar""": self.escapechar,
            """comment""": self.comment,
            """encoding""": self.encoding,
            """dialect""": self.dialect,
            """error_bad_lines""": self.error_bad_lines,
            """warn_bad_lines""": self.warn_bad_lines,
            """skipfooter""": self.skipfooter,
            """doublequote""": self.doublequote,
            """memory_map""": self.memory_map,
            """float_precision""": self.float_precision,
            """chunksize""": self.chunksize,
            """encoding_errors""": self.encoding_errors,
            """on_bad_lines""": self.on_bad_lines,
            """date_format""": self.date_format,
        }

        # some kwargs must not be passed if they don't have a default value
        # some others are deprecated and we can also not pass them if they are the default value
        for pd_read_csv_parameter in _PANDAS_READ_CSV_NO_DEFAULT_PARAMETERS + _PANDAS_READ_CSV_DEPRECATED_PARAMETERS:
           if pd_read_csv_kwargs[pd_read_csv_parameter] == getattr(CsvConfig()   ,       lowerCAmelCase_						):
              del pd_read_csv_kwargs[pd_read_csv_parameter]

        # Remove 2.0 new arguments
        if not (datasets.config.PANDAS_VERSION.major >= 2):
           for pd_read_csv_parameter in _PANDAS_READ_CSV_NEW_2_0_0_PARAMETERS:
              del pd_read_csv_kwargs[pd_read_csv_parameter]

        # Remove 1.3 new arguments
        if not (datasets.config.PANDAS_VERSION.major >= 1 and datasets.config.PANDAS_VERSION.minor >= 3):
           for pd_read_csv_parameter in _PANDAS_READ_CSV_NEW_1_3_0_PARAMETERS:
              del pd_read_csv_kwargs[pd_read_csv_parameter]

        return pd_read_csv_kwargs




class 			_lowerCAmelCase		(			datasets.ArrowBasedBuilder	):






     """simple docstring"""






     snake_case_						      =   CsvConfig



     def      lowerCAmelCase			(   self							:			List[Any]						)->	Union[str, Any]:
        return datasets.DatasetInfo(features=self.config.features						)



     def      lowerCAmelCase			(   self							:			Tuple   ,       __snake_case							:			List[str]						)->	str:
        if not self.config.data_files:
           raise ValueError(f'''At least one data file must be specified, but got data_files={self.config.data_files}'''						)
        snake_case 						=   dl_manager.download_and_extract(self.config.data_files						)
        if isinstance(lowerCAmelCase_   ,       (str, list, tuple)						):
           snake_case 						=   data_files
           if isinstance(lowerCAmelCase_   ,       lowerCAmelCase_						):
              snake_case 						=   [files]
           snake_case 						=   [dl_manager.iter_files(lowerCAmelCase_						) for file in files]
           return [datasets.SplitGenerator(name=datasets.Split.TRAIN   ,       gen_kwargs={"""files""": files}						)]
        snake_case 						=   []
        for split_name, files in data_files.items():
           if isinstance(lowerCAmelCase_   ,       lowerCAmelCase_						):
              snake_case 						=   [files]
           snake_case 						=   [dl_manager.iter_files(lowerCAmelCase_						) for file in files]
           splits.append(datasets.SplitGenerator(name=lowerCAmelCase_   ,       gen_kwargs={"""files""": files}						)						)
        return splits



     def      lowerCAmelCase			(   self							:			Dict   ,       __snake_case							:			pa.Table						)->	pa.Table:
        if self.config.features is not None:
           snake_case 						=   self.config.features.arrow_schema
           if all(not require_storage_cast(lowerCAmelCase_						) for feature in self.config.features.values()						):
              # cheaper cast
              snake_case 						=   pa.Table.from_arrays([pa_table[field.name] for field in schema]   ,       schema=lowerCAmelCase_						)
           else:
              # more expensive cast; allows str <-> int/float or str to Audio for example
              snake_case 						=   table_cast(lowerCAmelCase_   ,       lowerCAmelCase_						)
        return pa_table



     def      lowerCAmelCase			(   self							:			Any   ,       __snake_case							:			str						)->	Dict:
        snake_case 						=   self.config.features.arrow_schema if self.config.features else None
        # dtype allows reading an int column as str
        snake_case 						=   (
            {
                name: dtype.to_pandas_dtype() if not require_storage_cast(lowerCAmelCase_						) else object
                for name, dtype, feature in zip(schema.names   ,       schema.types   ,       self.config.features.values()						)
            }
            if schema is not None
            else None
        )
        for file_idx, file in enumerate(itertools.chain.from_iterable(lowerCAmelCase_						)						):
           snake_case 						=   pd.read_csv(lowerCAmelCase_   ,       iterator=lowerCAmelCase_   ,       dtype=lowerCAmelCase_   ,       **self.config.pd_read_csv_kwargs						)
           try:
              for batch_idx, df in enumerate(lowerCAmelCase_						):
                 snake_case 						=   pa.Table.from_pandas(lowerCAmelCase_						)
                 # Uncomment for debugging (will print the Arrow table size and elements)
                 # logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
                 # logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
                 yield (file_idx, batch_idx), self._cast_table(lowerCAmelCase_						)
           except ValueError as e:
              logger.error(f'''Failed to read file \'{file}\' with error {type(lowerCAmelCase_						)}: {e}'''						)
              raise





'''simple docstring'''





from __future__ import annotations

import math

UpperCAmelCase__  			=				'''2020.9.26'''
UpperCAmelCase__  			=				'''xcodz-dot, cclaus, dhruvmanila'''






def 						UpperCAmelCase__(				_SCREAMING_SNAKE_CASE					: float,_SCREAMING_SNAKE_CASE					: float,_SCREAMING_SNAKE_CASE					: float,_SCREAMING_SNAKE_CASE					: float,_SCREAMING_SNAKE_CASE					: float ):






			"""simple docstring"""




			if not all(isinstance(_SCREAMING_SNAKE_CASE,(float, int) ) for val in locals().values() ):
						__A=	f"""Input values must either be float or int: {list(locals().values() )}"""
						raise TypeError(_SCREAMING_SNAKE_CASE )
			__A=	((x * distance) / (z + distance)) * scale
			__A=	((y * distance) / (z + distance)) * scale
			return projected_x, projected_y






def 						UpperCAmelCase__(				_SCREAMING_SNAKE_CASE					: float,_SCREAMING_SNAKE_CASE					: float,_SCREAMING_SNAKE_CASE					: float,_SCREAMING_SNAKE_CASE					: str,_SCREAMING_SNAKE_CASE					: float ):






			"""simple docstring"""




			if not isinstance(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE ):
						raise TypeError('Axis must be a str' )
			__A=	locals()
			del input_variables["axis"]
			if not all(isinstance(_SCREAMING_SNAKE_CASE,(float, int) ) for val in input_variables.values() ):
						__A=	(
						    'Input values except axis must either be float or int: '
						    f"""{list(input_variables.values() )}"""
						)
						raise TypeError(_SCREAMING_SNAKE_CASE )
			__A=	(angle % 360) / 450 * 180 / math.pi
			if axis == "z":
						__A=	x * math.cos(_SCREAMING_SNAKE_CASE ) - y * math.sin(_SCREAMING_SNAKE_CASE )
						__A=	y * math.cos(_SCREAMING_SNAKE_CASE ) + x * math.sin(_SCREAMING_SNAKE_CASE )
						__A=	z
			elif axis == "x":
						__A=	y * math.cos(_SCREAMING_SNAKE_CASE ) - z * math.sin(_SCREAMING_SNAKE_CASE )
						__A=	z * math.cos(_SCREAMING_SNAKE_CASE ) + y * math.sin(_SCREAMING_SNAKE_CASE )
						__A=	x
			elif axis == "y":
						__A=	x * math.cos(_SCREAMING_SNAKE_CASE ) - z * math.sin(_SCREAMING_SNAKE_CASE )
						__A=	z * math.cos(_SCREAMING_SNAKE_CASE ) + x * math.sin(_SCREAMING_SNAKE_CASE )
						__A=	y
			else:
						raise ValueError('not a valid axis, choose one of \'x\', \'y\', \'z\'' )

			return new_x, new_y, new_z


if __name__ == "__main__":
					import doctest

					doctest.testmod()
					print(F"""{convert_to_ad(1.0, 2.0, 3.0, 10.0, 10.0) = }""")
					print(F"""{rotate(1.0, 2.0, 3.0, 'y', 90.0) = }""")



