'''simple docstring'''






import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch

import numpy as np
import pytest

from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex

from .utils import require_elasticsearch, require_faiss


SCREAMING_SNAKE_CASE_	   =			pytest.mark.integration




@require_faiss
class    a (       __lowerCAmelCase				):



  """simple docstring"""







  def    lowercase_  (							self					):

    '''simple docstring'''







    __UpperCAmelCase:					int		= Dataset.from_dict({"""filename""": ["""my_name-train""" + """_""" + str(UpperCamelCase_					) for x in np.arange(30					).tolist()]}					)
    return dset







  def    lowercase_  (							self					):

    '''simple docstring'''







    import faiss

    __UpperCAmelCase:					Dataset		= self._create_dummy_dataset()
    __UpperCAmelCase:					Union[str, Any]		= dset.map(
        lambda snake_case_   ,    snake_case_					: {"vecs": i * np.ones(5   ,    dtype=np.floataa					)}   ,    with_indices=UpperCamelCase_   ,    keep_in_memory=UpperCamelCase_					)
    __UpperCAmelCase:					List[str]		= dset.add_faiss_index("""vecs"""   ,    batch_size=100   ,    metric_type=faiss.METRIC_INNER_PRODUCT					)
    __UpperCAmelCase:					Any		= dset.get_nearest_examples("""vecs"""   ,    np.ones(5   ,    dtype=np.floataa					)					)
    self.assertEqual(examples["""filename"""][0]   ,    """my_name-train_29"""					)
    dset.drop_index("""vecs"""					)







  def    lowercase_  (							self					):

    '''simple docstring'''







    import faiss

    __UpperCAmelCase:					Dataset		= self._create_dummy_dataset()
    dset.add_faiss_index_from_external_arrays(
        external_arrays=np.ones((30, 5)					) * np.arange(30					).reshape(-1   ,    1					)   ,    index_name="""vecs"""   ,    batch_size=100   ,    metric_type=faiss.METRIC_INNER_PRODUCT   ,    )
    __UpperCAmelCase:					Tuple		= dset.get_nearest_examples("""vecs"""   ,    np.ones(5   ,    dtype=np.floataa					)					)
    self.assertEqual(examples["""filename"""][0]   ,    """my_name-train_29"""					)







  def    lowercase_  (							self					):

    '''simple docstring'''







    import faiss

    __UpperCAmelCase:					Dataset		= self._create_dummy_dataset()
    dset.add_faiss_index_from_external_arrays(
        external_arrays=np.ones((30, 5)					) * np.arange(30					).reshape(-1   ,    1					)   ,    index_name="""vecs"""   ,    metric_type=faiss.METRIC_INNER_PRODUCT   ,    )

    # Setting delete=False and unlinking manually is not pretty... but it is required on Windows to
    # ensure somewhat stable behaviour. If we don't, we get PermissionErrors. This is an age-old issue.
    # see https://bugs.python.org/issue14243 and
    # https://stackoverflow.com/questions/23212435/permission-denied-to-write-to-my-temporary-file/23212515
    with tempfile.NamedTemporaryFile(delete=UpperCamelCase_					) as tmp_file:
      dset.save_faiss_index("""vecs"""   ,    tmp_file.name					)
      dset.load_faiss_index("""vecs2"""   ,    tmp_file.name					)
    os.unlink(tmp_file.name					)

    __UpperCAmelCase:					Optional[Any]		= dset.get_nearest_examples("""vecs2"""   ,    np.ones(5   ,    dtype=np.floataa					)					)
    self.assertEqual(examples["""filename"""][0]   ,    """my_name-train_29"""					)







  def    lowercase_  (							self					):

    '''simple docstring'''







    __UpperCAmelCase:					Dataset		= self._create_dummy_dataset()
    dset.add_faiss_index_from_external_arrays(
        external_arrays=np.ones((30, 5)					) * np.arange(30					).reshape(-1   ,    1					)   ,    index_name="""vecs"""					)
    dset.drop_index("""vecs"""					)
    self.assertRaises(UpperCamelCase_   ,    partial(dset.get_nearest_examples   ,    """vecs2"""   ,    np.ones(5   ,    dtype=np.floataa					)					)					)







  def    lowercase_  (							self					):

    '''simple docstring'''







    from elasticsearch import Elasticsearch

    __UpperCAmelCase:					Dataset		= self._create_dummy_dataset()
    with patch("""elasticsearch.Elasticsearch.search"""					) as mocked_search, patch(
        """elasticsearch.client.IndicesClient.create"""					) as mocked_index_create, patch("""elasticsearch.helpers.streaming_bulk"""					) as mocked_bulk:
      __UpperCAmelCase:					Optional[int]		= {'acknowledged': True}
      mocked_bulk.return_value([(True, None)] * 30					)
      __UpperCAmelCase:					Union[str, Any]		= {'hits': {'hits': [{'_score': 1, '_id': 29}]}}
      __UpperCAmelCase:					str		= Elasticsearch()

      dset.add_elasticsearch_index("""filename"""   ,    es_client=UpperCamelCase_					)
      __UpperCAmelCase:					int		= dset.get_nearest_examples("""filename"""   ,    """my_name-train_29"""					)
      self.assertEqual(examples["""filename"""][0]   ,    """my_name-train_29"""					)




@require_faiss
class    a (       __lowerCAmelCase				):



  """simple docstring"""







  def    lowercase_  (							self					):

    '''simple docstring'''







    import faiss

    __UpperCAmelCase:					List[str]		= FaissIndex(metric_type=faiss.METRIC_INNER_PRODUCT					)

    # add vectors
    index.add_vectors(np.eye(5   ,    dtype=np.floataa					)					)
    self.assertIsNotNone(index.faiss_index					)
    self.assertEqual(index.faiss_index.ntotal   ,    5					)
    index.add_vectors(np.zeros((5, 5)   ,    dtype=np.floataa					)					)
    self.assertEqual(index.faiss_index.ntotal   ,    10					)

    # single query
    __UpperCAmelCase:					List[str]		= np.zeros(5   ,    dtype=np.floataa					)
    __UpperCAmelCase:					int		= 1
    __UpperCAmelCase:					Optional[Any]		= index.search(UpperCamelCase_					)
    self.assertRaises(UpperCamelCase_   ,    index.search   ,    query.reshape(-1   ,    1					)					)
    self.assertGreater(scores[0]   ,    0					)
    self.assertEqual(indices[0]   ,    1					)

    # batched queries
    __UpperCAmelCase:					Any		= np.eye(5   ,    dtype=np.floataa					)[::-1]
    __UpperCAmelCase:					Tuple		= index.search_batch(UpperCamelCase_					)
    self.assertRaises(UpperCamelCase_   ,    index.search_batch   ,    queries[0]					)
    __UpperCAmelCase:					List[Any]		= [scores[0] for scores in total_scores]
    __UpperCAmelCase:					Tuple		= [indices[0] for indices in total_indices]
    self.assertGreater(np.min(UpperCamelCase_					)   ,    0					)
    self.assertListEqual([4, 3, 2, 1, 0]   ,    UpperCamelCase_					)







  def    lowercase_  (							self					):

    '''simple docstring'''







    import faiss

    __UpperCAmelCase:					List[Any]		= FaissIndex(string_factory="""Flat"""					)
    index.add_vectors(np.eye(5   ,    dtype=np.floataa					)					)
    self.assertIsInstance(index.faiss_index   ,    faiss.IndexFlat					)
    __UpperCAmelCase:					int		= FaissIndex(string_factory="""LSH"""					)
    index.add_vectors(np.eye(5   ,    dtype=np.floataa					)					)
    self.assertIsInstance(index.faiss_index   ,    faiss.IndexLSH					)
    with self.assertRaises(UpperCamelCase_					):
      __UpperCAmelCase:					Union[str, Any]		= FaissIndex(string_factory="""Flat"""   ,    custom_index=faiss.IndexFlat(5					)					)







  def    lowercase_  (							self					):

    '''simple docstring'''







    import faiss

    __UpperCAmelCase:					Tuple		= faiss.IndexFlat(5					)
    __UpperCAmelCase:					List[Any]		= FaissIndex(custom_index=UpperCamelCase_					)
    index.add_vectors(np.eye(5   ,    dtype=np.floataa					)					)
    self.assertIsInstance(index.faiss_index   ,    faiss.IndexFlat					)







  def    lowercase_  (							self					):

    '''simple docstring'''







    import faiss

    __UpperCAmelCase:					List[Any]		= FaissIndex(metric_type=faiss.METRIC_INNER_PRODUCT					)
    index.add_vectors(np.eye(5   ,    dtype=np.floataa					)					)

    # Setting delete=False and unlinking manually is not pretty... but it is required on Windows to
    # ensure somewhat stable behaviour. If we don't, we get PermissionErrors. This is an age-old issue.
    # see https://bugs.python.org/issue14243 and
    # https://stackoverflow.com/questions/23212435/permission-denied-to-write-to-my-temporary-file/23212515
    with tempfile.NamedTemporaryFile(delete=UpperCamelCase_					) as tmp_file:
      index.save(tmp_file.name					)
      __UpperCAmelCase:					List[Any]		= FaissIndex.load(tmp_file.name					)
    os.unlink(tmp_file.name					)

    __UpperCAmelCase:					Dict		= np.zeros(5   ,    dtype=np.floataa					)
    __UpperCAmelCase:					List[str]		= 1
    __UpperCAmelCase:					Dict		= index.search(UpperCamelCase_					)
    self.assertGreater(scores[0]   ,    0					)
    self.assertEqual(indices[0]   ,    1					)






@require_faiss
def  UpperCamelCase__					(					_lowercase    :				List[str]     )							->	Optional[int]:
  import faiss

  __UpperCAmelCase:					Optional[int]		= FaissIndex(metric_type=faiss.METRIC_INNER_PRODUCT     )
  index.add_vectors(np.eye(5   ,    dtype=np.floataa     )     )

  __UpperCAmelCase:					str		= 'index.faiss'
  __UpperCAmelCase:					List[Any]		= F'''mock://{index_name}'''
  index.save(_lowercase   ,    storage_options=mockfs.storage_options     )
  __UpperCAmelCase:					Any		= FaissIndex.load(_lowercase   ,    storage_options=mockfs.storage_options     )

  __UpperCAmelCase:					Any		= np.zeros(5   ,    dtype=np.floataa     )
  __UpperCAmelCase:					Optional[int]		= 1
  __UpperCAmelCase:					Tuple		= index.search(_lowercase     )
  assert scores[0] > 0
  assert indices[0] == 1







@require_elasticsearch
class    a (       __lowerCAmelCase				):



  """simple docstring"""







  def    lowercase_  (							self					):

    '''simple docstring'''







    from elasticsearch import Elasticsearch

    with patch("""elasticsearch.Elasticsearch.search"""					) as mocked_search, patch(
        """elasticsearch.client.IndicesClient.create"""					) as mocked_index_create, patch("""elasticsearch.helpers.streaming_bulk"""					) as mocked_bulk:
      __UpperCAmelCase:					Tuple		= Elasticsearch()
      __UpperCAmelCase:					Optional[int]		= {'acknowledged': True}
      __UpperCAmelCase:					List[Any]		= ElasticSearchIndex(es_client=UpperCamelCase_					)
      mocked_bulk.return_value([(True, None)] * 3					)
      index.add_documents(["""foo""", """bar""", """foobar"""]					)

      # single query
      __UpperCAmelCase:					Optional[Any]		= 'foo'
      __UpperCAmelCase:					Optional[Any]		= {'hits': {'hits': [{'_score': 1, '_id': 0}]}}
      __UpperCAmelCase:					Dict		= index.search(UpperCamelCase_					)
      self.assertEqual(scores[0]   ,    1					)
      self.assertEqual(indices[0]   ,    0					)

      # single query with timeout
      __UpperCAmelCase:					Optional[Any]		= 'foo'
      __UpperCAmelCase:					int		= {'hits': {'hits': [{'_score': 1, '_id': 0}]}}
      __UpperCAmelCase:					Optional[int]		= index.search(UpperCamelCase_   ,    request_timeout=30					)
      self.assertEqual(scores[0]   ,    1					)
      self.assertEqual(indices[0]   ,    0					)

      # batched queries
      __UpperCAmelCase:					Dict		= ['foo', 'bar', 'foobar']
      __UpperCAmelCase:					List[Any]		= {'hits': {'hits': [{'_score': 1, '_id': 1}]}}
      __UpperCAmelCase:					Tuple		= index.search_batch(UpperCamelCase_					)
      __UpperCAmelCase:					Union[str, Any]		= [scores[0] for scores in total_scores]
      __UpperCAmelCase:					str		= [indices[0] for indices in total_indices]
      self.assertGreater(np.min(UpperCamelCase_					)   ,    0					)
      self.assertListEqual([1, 1, 1]   ,    UpperCamelCase_					)

      # batched queries with timeout
      __UpperCAmelCase:					List[str]		= ['foo', 'bar', 'foobar']
      __UpperCAmelCase:					Optional[int]		= {'hits': {'hits': [{'_score': 1, '_id': 1}]}}
      __UpperCAmelCase:					Tuple		= index.search_batch(UpperCamelCase_   ,    request_timeout=30					)
      __UpperCAmelCase:					Optional[Any]		= [scores[0] for scores in total_scores]
      __UpperCAmelCase:					Any		= [indices[0] for indices in total_indices]
      self.assertGreater(np.min(UpperCamelCase_					)   ,    0					)
      self.assertListEqual([1, 1, 1]   ,    UpperCamelCase_					)


'''simple docstring'''






from __future__ import annotations

import matplotlib.pyplot as plt  # type: ignore
import numpy

# initial triangle of Koch snowflake
SCREAMING_SNAKE_CASE_	   =			numpy.array([0, 0])
SCREAMING_SNAKE_CASE_	   =			numpy.array([0.5, 0.866_0254])
SCREAMING_SNAKE_CASE_	   =			numpy.array([1, 0])
SCREAMING_SNAKE_CASE_	   =			[VECTOR_1, VECTOR_2, VECTOR_3, VECTOR_1]






def  UpperCamelCase__					(					_lowercase    :				list[numpy.ndarray]   ,    _lowercase    :				int     )							->	list[numpy.ndarray]:
  __UpperCAmelCase:					int		= initial_vectors
  for _ in range(_lowercase     ):
    __UpperCAmelCase:					Any		= iteration_step(_lowercase     )
  return vectors






def  UpperCamelCase__					(					_lowercase    :				list[numpy.ndarray]     )							->	list[numpy.ndarray]:
  __UpperCAmelCase:					Optional[int]		= []
  for i, start_vector in enumerate(vectors[:-1]     ):
    __UpperCAmelCase:					Union[str, Any]		= vectors[i + 1]
    new_vectors.append(_lowercase     )
    __UpperCAmelCase:					Optional[int]		= end_vector - start_vector
    new_vectors.append(start_vector + difference_vector / 3     )
    new_vectors.append(
        start_vector + difference_vector / 3 + rotate(difference_vector / 3   ,    6_0     )     )
    new_vectors.append(start_vector + difference_vector * 2 / 3     )
  new_vectors.append(vectors[-1]     )
  return new_vectors






def  UpperCamelCase__					(					_lowercase    :				numpy.ndarray   ,    _lowercase    :				float     )							->	numpy.ndarray:
  __UpperCAmelCase:					Tuple		= numpy.radians(_lowercase     )
  __UpperCAmelCase, __UpperCAmelCase:					Optional[Any]		= numpy.cos(_lowercase     ), numpy.sin(_lowercase     )
  __UpperCAmelCase:					Tuple		= numpy.array(((c, -s), (s, c))     )
  return numpy.dot(_lowercase   ,    _lowercase     )






def  UpperCamelCase__					(					_lowercase    :				list[numpy.ndarray]     )							->	None:
  __UpperCAmelCase:					Union[str, Any]		= plt.gca()
  axes.set_aspect("""equal"""     )

  # matplotlib.pyplot.plot takes a list of all x-coordinates and a list of all
  # y-coordinates as inputs, which are constructed from the vector-list using
  # zip()
  __UpperCAmelCase, __UpperCAmelCase:					Dict		= zip(*_lowercase     )
  plt.plot(_lowercase   ,    _lowercase     )
  plt.show()


if __name__ == "__main__":
    import doctest

    doctest.testmod()

    SCREAMING_SNAKE_CASE_	   =			iterate(INITIAL_VECTORS, 5)
    plot(processed_vectors)