



"""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


lowercase__		:    Optional[int]				   =     pytest.mark.integration







@require_faiss
class 				UpperCamelCase__       (     lowercase_  ):




      """simple docstring"""




      def 					SCREAMING_SNAKE_CASE__			(				self    :				Union[str, Any]	):
        lowerCAmelCase_       :    str								=			Dataset.from_dict({'filename': ['my_name-train' + '_' + str(SCREAMING_SNAKE_CASE_	) for x in np.arange(3_0	).tolist()]}	)
        return dset



      def 					SCREAMING_SNAKE_CASE__			(				self    :				List[Any]	):
        import faiss

        lowerCAmelCase_       :    Dataset								=			self._create_dummy_dataset()
        lowerCAmelCase_       :    Any								=			dset.map(
            lambda SCREAMING_SNAKE_CASE_   ,      SCREAMING_SNAKE_CASE_	: {"vecs": i * np.ones(5   ,      dtype=np.floataa	)}   ,      with_indices=SCREAMING_SNAKE_CASE_   ,      keep_in_memory=SCREAMING_SNAKE_CASE_	)
        lowerCAmelCase_       :    List[Any]								=			dset.add_faiss_index('vecs'   ,      batch_size=1_0_0   ,      metric_type=faiss.METRIC_INNER_PRODUCT	)
        lowerCAmelCase_						,lowerCAmelCase_       :    str								=			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 					SCREAMING_SNAKE_CASE__			(				self    :				Optional[int]	):
        import faiss

        lowerCAmelCase_       :    Dataset								=			self._create_dummy_dataset()
        dset.add_faiss_index_from_external_arrays(
            external_arrays=np.ones((3_0, 5)	) * np.arange(3_0	).reshape(-1   ,      1	)   ,      index_name='vecs'   ,      batch_size=1_0_0   ,      metric_type=faiss.METRIC_INNER_PRODUCT   ,      )
        lowerCAmelCase_						,lowerCAmelCase_       :    Optional[Any]								=			dset.get_nearest_examples('vecs'   ,      np.ones(5   ,      dtype=np.floataa	)	)
        self.assertEqual(examples['filename'][0]   ,      'my_name-train_29'	)



      def 					SCREAMING_SNAKE_CASE__			(				self    :				Union[str, Any]	):
        import faiss

        lowerCAmelCase_       :    Dataset								=			self._create_dummy_dataset()
        dset.add_faiss_index_from_external_arrays(
            external_arrays=np.ones((3_0, 5)	) * np.arange(3_0	).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=SCREAMING_SNAKE_CASE_	) as tmp_file:
          dset.save_faiss_index('vecs'   ,      tmp_file.name	)
          dset.load_faiss_index('vecs2'   ,      tmp_file.name	)
        os.unlink(tmp_file.name	)

        lowerCAmelCase_						,lowerCAmelCase_       :    int								=			dset.get_nearest_examples('vecs2'   ,      np.ones(5   ,      dtype=np.floataa	)	)
        self.assertEqual(examples['filename'][0]   ,      'my_name-train_29'	)



      def 					SCREAMING_SNAKE_CASE__			(				self    :				Any	):
        lowerCAmelCase_       :    Dataset								=			self._create_dummy_dataset()
        dset.add_faiss_index_from_external_arrays(
            external_arrays=np.ones((3_0, 5)	) * np.arange(3_0	).reshape(-1   ,      1	)   ,      index_name='vecs'	)
        dset.drop_index('vecs'	)
        self.assertRaises(SCREAMING_SNAKE_CASE_   ,      partial(dset.get_nearest_examples   ,      'vecs2'   ,      np.ones(5   ,      dtype=np.floataa	)	)	)





      def 					SCREAMING_SNAKE_CASE__			(				self    :				Dict	):
        from elasticsearch import Elasticsearch

        lowerCAmelCase_       :    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:
          lowerCAmelCase_       :    Any								=			{'acknowledged': True}
          mocked_bulk.return_value([(True, None)] * 3_0	)
          lowerCAmelCase_       :    List[str]								=			{'hits': {'hits': [{'_score': 1, '_id': 2_9}]}}
          lowerCAmelCase_       :    Union[str, Any]								=			Elasticsearch()

          dset.add_elasticsearch_index('filename'   ,      es_client=SCREAMING_SNAKE_CASE_	)
          lowerCAmelCase_						,lowerCAmelCase_       :    Union[str, Any]								=			dset.get_nearest_examples('filename'   ,      'my_name-train_29'	)
          self.assertEqual(examples['filename'][0]   ,      'my_name-train_29'	)







@require_faiss
class 				UpperCamelCase__       (     lowercase_  ):




      """simple docstring"""




      def 					SCREAMING_SNAKE_CASE__			(				self    :				str	):
        import faiss

        lowerCAmelCase_       :    Tuple								=			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   ,      1_0	)

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

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



      def 					SCREAMING_SNAKE_CASE__			(				self    :				Union[str, Any]	):
        import faiss

        lowerCAmelCase_       :    Tuple								=			FaissIndex(string_factory='Flat'	)
        index.add_vectors(np.eye(5   ,      dtype=np.floataa	)	)
        self.assertIsInstance(index.faiss_index   ,      faiss.IndexFlat	)
        lowerCAmelCase_       :    Optional[Any]								=			FaissIndex(string_factory='LSH'	)
        index.add_vectors(np.eye(5   ,      dtype=np.floataa	)	)
        self.assertIsInstance(index.faiss_index   ,      faiss.IndexLSH	)
        with self.assertRaises(SCREAMING_SNAKE_CASE_	):
          lowerCAmelCase_       :    Dict								=			FaissIndex(string_factory='Flat'   ,      custom_index=faiss.IndexFlat(5	)	)



      def 					SCREAMING_SNAKE_CASE__			(				self    :				Dict	):
        import faiss

        lowerCAmelCase_       :    List[str]								=			faiss.IndexFlat(5	)
        lowerCAmelCase_       :    int								=			FaissIndex(custom_index=SCREAMING_SNAKE_CASE_	)
        index.add_vectors(np.eye(5   ,      dtype=np.floataa	)	)
        self.assertIsInstance(index.faiss_index   ,      faiss.IndexFlat	)





      def 					SCREAMING_SNAKE_CASE__			(				self    :				str	):
        import faiss

        lowerCAmelCase_       :    List[str]								=			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=SCREAMING_SNAKE_CASE_	) as tmp_file:
          index.save(tmp_file.name	)
          lowerCAmelCase_       :    List[Any]								=			FaissIndex.load(tmp_file.name	)
        os.unlink(tmp_file.name	)

        lowerCAmelCase_       :    Optional[int]								=			np.zeros(5   ,      dtype=np.floataa	)
        lowerCAmelCase_       :    str								=			1
        lowerCAmelCase_						,lowerCAmelCase_       :    List[Any]								=			index.search(SCREAMING_SNAKE_CASE_	)
        self.assertGreater(scores[0]   ,      0	)
        self.assertEqual(indices[0]   ,      1	)




@require_faiss
def     UpperCamelCase_   (   lowerCAmelCase__				:    int						)						->       Tuple:

  """simple docstring"""




  import faiss

  lowerCAmelCase_       :    Any								=			FaissIndex(metric_type=faiss.METRIC_INNER_PRODUCT						)
  index.add_vectors(np.eye(5   ,       dtype=np.floataa						)						)

  lowerCAmelCase_       :    List[str]								=			'index.faiss'
  lowerCAmelCase_       :    Union[str, Any]								=			f"mock://{index_name}"
  index.save(lowerCAmelCase__   ,       storage_options=mockfs.storage_options						)
  lowerCAmelCase_       :    int								=			FaissIndex.load(lowerCAmelCase__   ,       storage_options=mockfs.storage_options						)

  lowerCAmelCase_       :    str								=			np.zeros(5   ,       dtype=np.floataa						)
  lowerCAmelCase_       :    List[str]								=			1
  lowerCAmelCase_						,lowerCAmelCase_       :    int								=			index.search(lowerCAmelCase__						)
  assert scores[0] > 0
  assert indices[0] == 1







@require_elasticsearch
class 				UpperCamelCase__       (     lowercase_  ):




      """simple docstring"""




      def 					SCREAMING_SNAKE_CASE__			(				self    :				Dict	):
        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:
          lowerCAmelCase_       :    Union[str, Any]								=			Elasticsearch()
          lowerCAmelCase_       :    Dict								=			{'acknowledged': True}
          lowerCAmelCase_       :    str								=			ElasticSearchIndex(es_client=SCREAMING_SNAKE_CASE_	)
          mocked_bulk.return_value([(True, None)] * 3	)
          index.add_documents(['foo', 'bar', 'foobar']	)

          # single query
          lowerCAmelCase_       :    int								=			'foo'
          lowerCAmelCase_       :    Optional[int]								=			{'hits': {'hits': [{'_score': 1, '_id': 0}]}}
          lowerCAmelCase_						,lowerCAmelCase_       :    int								=			index.search(SCREAMING_SNAKE_CASE_	)
          self.assertEqual(scores[0]   ,      1	)
          self.assertEqual(indices[0]   ,      0	)

          # single query with timeout
          lowerCAmelCase_       :    Dict								=			'foo'
          lowerCAmelCase_       :    Union[str, Any]								=			{'hits': {'hits': [{'_score': 1, '_id': 0}]}}
          lowerCAmelCase_						,lowerCAmelCase_       :    Dict								=			index.search(SCREAMING_SNAKE_CASE_   ,      request_timeout=3_0	)
          self.assertEqual(scores[0]   ,      1	)
          self.assertEqual(indices[0]   ,      0	)

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

          # batched queries with timeout
          lowerCAmelCase_       :    Tuple								=			['foo', 'bar', 'foobar']
          lowerCAmelCase_       :    Optional[int]								=			{'hits': {'hits': [{'_score': 1, '_id': 1}]}}
          lowerCAmelCase_						,lowerCAmelCase_       :    Any								=			index.search_batch(SCREAMING_SNAKE_CASE_   ,      request_timeout=3_0	)
          lowerCAmelCase_       :    Optional[int]								=			[scores[0] for scores in total_scores]
          lowerCAmelCase_       :    int								=			[indices[0] for indices in total_indices]
          self.assertGreater(np.min(SCREAMING_SNAKE_CASE_	)   ,      0	)
          self.assertListEqual([1, 1, 1]   ,      SCREAMING_SNAKE_CASE_	)










"""simple docstring"""







def     UpperCamelCase_   (   lowerCAmelCase__				:    Optional[Any]   ,       lowerCAmelCase__				:    str						)						->       List[Any]:

  """simple docstring"""




  return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2

def     UpperCamelCase_   (   lowerCAmelCase__				:    List[Any]   ,       lowerCAmelCase__				:    str=0						)						->       Union[str, Any]:

  """simple docstring"""




  return sorted(lowerCAmelCase__   ,       key=lambda lowerCAmelCase__						: x[column]						)

def     UpperCamelCase_   (   lowerCAmelCase__				:    Dict   ,       lowerCAmelCase__				:    Optional[int]   ,       lowerCAmelCase__				:    Optional[Any]=float('inf'						)						)						->       Optional[int]:

  """simple docstring"""




  for i in range(points_counts - 1						):
    for j in range(i + 1   ,       lowerCAmelCase__						):
      lowerCAmelCase_       :    Union[str, Any]								=			euclidean_distance_sqr(points[i]   ,       points[j]						)
      if current_dis < min_dis:
        lowerCAmelCase_       :    Optional[int]								=			current_dis
  return min_dis

def     UpperCamelCase_   (   lowerCAmelCase__				:    List[Any]   ,       lowerCAmelCase__				:    Dict   ,       lowerCAmelCase__				:    Union[str, Any]=float('inf'						)						)						->       Dict:

  """simple docstring"""




  for i in range(min(6   ,       points_counts - 1						)   ,       lowerCAmelCase__						):
    for j in range(max(0   ,       i - 6						)   ,       lowerCAmelCase__						):
      lowerCAmelCase_       :    Any								=			euclidean_distance_sqr(points[i]   ,       points[j]						)
      if current_dis < min_dis:
        lowerCAmelCase_       :    Union[str, Any]								=			current_dis
  return min_dis

def     UpperCamelCase_   (   lowerCAmelCase__				:    Dict   ,       lowerCAmelCase__				:    int   ,       lowerCAmelCase__				:    Optional[int]						)						->       Dict:

  """simple docstring"""




  if points_counts <= 3:
    return dis_between_closest_pair(lowerCAmelCase__   ,       lowerCAmelCase__						)

  # recursion
  lowerCAmelCase_       :    int								=			points_counts // 2
  lowerCAmelCase_       :    Optional[Any]								=			closest_pair_of_points_sqr(
      lowerCAmelCase__   ,       points_sorted_on_y[:mid]   ,       lowerCAmelCase__						)
  lowerCAmelCase_       :    Optional[Any]								=			closest_pair_of_points_sqr(
      lowerCAmelCase__   ,       points_sorted_on_y[mid:]   ,       points_counts - mid						)
  lowerCAmelCase_       :    Any								=			min(lowerCAmelCase__   ,       lowerCAmelCase__						)
  lowerCAmelCase_       :    str								=			[]
  for point in points_sorted_on_x:
    if abs(point[0] - points_sorted_on_x[mid][0]						) < closest_pair_dis:
      cross_strip.append(lowerCAmelCase__						)

  lowerCAmelCase_       :    List[Any]								=			dis_between_closest_in_strip(
      lowerCAmelCase__   ,       len(lowerCAmelCase__						)   ,       lowerCAmelCase__						)
  return min(lowerCAmelCase__   ,       lowerCAmelCase__						)

def     UpperCamelCase_   (   lowerCAmelCase__				:    str   ,       lowerCAmelCase__				:    Tuple						)						->       List[Any]:

  """simple docstring"""




  lowerCAmelCase_       :    List[str]								=			column_based_sort(lowerCAmelCase__   ,       column=0						)
  lowerCAmelCase_       :    Dict								=			column_based_sort(lowerCAmelCase__   ,       column=1						)
  return (
      closest_pair_of_points_sqr(
          lowerCAmelCase__   ,       lowerCAmelCase__   ,       lowerCAmelCase__						)
  ) ** 0.5


if __name__ == "__main__":
     lowercase__		:    List[str]				   =     [(2, 3), (1_2, 3_0), (4_0, 5_0), (5, 1), (1_2, 1_0), (3, 4)]
     print("""Distance:""", closest_pair_of_points(points, len(points)))





