


'''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


__A		=pytest.mark.integration


@require_faiss
class 						_snake_case   (       a__		):




						def 			snake_case__  ( self):
									UpperCAmelCase__					:   Tuple       				=       Dataset.from_dict({"""filename""": ["""my_name-train""" + """_""" + str(_lowerCamelCase) for x in np.arange(30).tolist()]})
									return dset




						def 			snake_case__  ( self):
									import faiss

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




						def 			snake_case__  ( self):
									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=_lowerCamelCase) 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__					:   str       				=       dset.get_nearest_examples("""vecs2"""							,							np.ones(5							,							dtype=np.floataa))
									self.assertEqual(examples["""filename"""][0]							,							"""my_name-train_29""")




						def 			snake_case__  ( self):
									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(_lowerCamelCase							,							partial(dset.get_nearest_examples							,							"""vecs2"""							,							np.ones(5							,							dtype=np.floataa)))




						def 			snake_case__  ( self):
									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__					:   List[Any]       				=       {"acknowledged": True}
												mocked_bulk.return_value([(True, None)] * 30)
												UpperCAmelCase__					:   str       				=       {"hits": {"hits": [{"_score": 1, "_id": 29}]}}
												UpperCAmelCase__					:   Optional[Any]       				=       Elasticsearch()

												dset.add_elasticsearch_index("""filename"""							,							es_client=_lowerCamelCase)
												UpperCAmelCase__					:   Dict       				=       dset.get_nearest_examples("""filename"""							,							"""my_name-train_29""")
												self.assertEqual(examples["""filename"""][0]							,							"""my_name-train_29""")


@require_faiss
class 						_snake_case   (       a__		):




						def 			snake_case__  ( self):
									import faiss

									UpperCAmelCase__					:   Any       				=       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__					:   Union[str, Any]       				=       np.zeros(5							,							dtype=np.floataa)
									UpperCAmelCase__					:   Dict       				=       1
									UpperCAmelCase__					:   int       				=       index.search(_lowerCamelCase)
									self.assertRaises(_lowerCamelCase							,							index.search							,							query.reshape(-1							,							1))
									self.assertGreater(scores[0]							,							0)
									self.assertEqual(indices[0]							,							1)

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




						def 			snake_case__  ( self):
									import faiss

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




						def 			snake_case__  ( self):
									import faiss

									UpperCAmelCase__					:   Dict       				=       faiss.IndexFlat(5)
									UpperCAmelCase__					:   str       				=       FaissIndex(custom_index=_lowerCamelCase)
									index.add_vectors(np.eye(5							,							dtype=np.floataa))
									self.assertIsInstance(index.faiss_index							,							faiss.IndexFlat)




						def 			snake_case__  ( self):
									import faiss

									UpperCAmelCase__					:   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=_lowerCamelCase) as tmp_file:
												index.save(tmp_file.name)
												UpperCAmelCase__					:   List[str]       				=       FaissIndex.load(tmp_file.name)
									os.unlink(tmp_file.name)

									UpperCAmelCase__					:   Union[str, Any]       				=       np.zeros(5							,							dtype=np.floataa)
									UpperCAmelCase__					:   List[Any]       				=       1
									UpperCAmelCase__					:   Union[str, Any]       				=       index.search(_lowerCamelCase)
									self.assertGreater(scores[0]							,							0)
									self.assertEqual(indices[0]							,							1)







@require_faiss
def       _UpperCamelCase (						UpperCamelCase__   ):
			import faiss

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

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

			UpperCAmelCase__					:   Optional[Any]       				=       np.zeros(5	, dtype=np.floataa   )
			UpperCAmelCase__					:   Optional[Any]       				=       1
			UpperCAmelCase__					:   Optional[Any]       				=       index.search(_lowerCamelCase   )
			assert scores[0] > 0
			assert indices[0] == 1


@require_elasticsearch
class 						_snake_case   (       a__		):




						def 			snake_case__  ( self):
									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__					:   Dict       				=       Elasticsearch()
												UpperCAmelCase__					:   Optional[Any]       				=       {"acknowledged": True}
												UpperCAmelCase__					:   Optional[int]       				=       ElasticSearchIndex(es_client=_lowerCamelCase)
												mocked_bulk.return_value([(True, None)] * 3)
												index.add_documents(["""foo""", """bar""", """foobar"""])

												# single query
												UpperCAmelCase__					:   List[Any]       				=       "foo"
												UpperCAmelCase__					:   List[str]       				=       {"hits": {"hits": [{"_score": 1, "_id": 0}]}}
												UpperCAmelCase__					:   Optional[int]       				=       index.search(_lowerCamelCase)
												self.assertEqual(scores[0]							,							1)
												self.assertEqual(indices[0]							,							0)

												# single query with timeout
												UpperCAmelCase__					:   Union[str, Any]       				=       "foo"
												UpperCAmelCase__					:   int       				=       {"hits": {"hits": [{"_score": 1, "_id": 0}]}}
												UpperCAmelCase__					:   Tuple       				=       index.search(_lowerCamelCase							,							request_timeout=30)
												self.assertEqual(scores[0]							,							1)
												self.assertEqual(indices[0]							,							0)

												# batched queries
												UpperCAmelCase__					:   str       				=       ["foo", "bar", "foobar"]
												UpperCAmelCase__					:   List[Any]       				=       {"hits": {"hits": [{"_score": 1, "_id": 1}]}}
												UpperCAmelCase__					:   Optional[Any]       				=       index.search_batch(_lowerCamelCase)
												UpperCAmelCase__					:   int       				=       [scores[0] for scores in total_scores]
												UpperCAmelCase__					:   List[str]       				=       [indices[0] for indices in total_indices]
												self.assertGreater(np.min(_lowerCamelCase)							,							0)
												self.assertListEqual([1, 1, 1]							,							_lowerCamelCase)

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



'''simple docstring'''



import colorsys

from PIL import Image  # type: ignore







def       _UpperCamelCase (						UpperCamelCase__	, UpperCamelCase__	, UpperCamelCase__   ):
			UpperCAmelCase__					:   Optional[Any]       				=       x
			UpperCAmelCase__					:   Optional[int]       				=       y
			for step in range(UpperCamelCase__   ):  # noqa: B007
						UpperCAmelCase__					:   List[str]       				=       a * a - b * b + x
						UpperCAmelCase__					:   Optional[int]       				=       2 * a * b + y
						UpperCAmelCase__					:   int       				=       a_new

						# divergence happens for all complex number with an absolute value
						# greater than 4
						if a * a + b * b > 4:
									break
			return step / (max_step - 1)







def       _UpperCamelCase (						UpperCamelCase__   ):
			if distance == 1:
						return (0, 0, 0)
			else:
						return (2_5_5, 2_5_5, 2_5_5)







def       _UpperCamelCase (						UpperCamelCase__   ):
			if distance == 1:
						return (0, 0, 0)
			else:
						return tuple(round(i * 2_5_5   ) for i in colorsys.hsv_to_rgb(UpperCamelCase__	, 1	, 1   )   )







def       _UpperCamelCase (						UpperCamelCase__ = 8_0_0	, UpperCamelCase__ = 6_0_0	, UpperCamelCase__ = -0.6	, UpperCamelCase__ = 0	, UpperCamelCase__ = 3.2	, UpperCamelCase__ = 5_0	, UpperCamelCase__ = True	, ):
			UpperCAmelCase__					:   str       				=       Image.new("""RGB"""	, (image_width, image_height)   )
			UpperCAmelCase__					:   Optional[int]       				=       img.load()

			# loop through the image-coordinates
			for image_x in range(UpperCamelCase__   ):
						for image_y in range(UpperCamelCase__   ):
									# determine the figure-coordinates based on the image-coordinates
									UpperCAmelCase__					:   Union[str, Any]       				=       figure_width / image_width * image_height
									UpperCAmelCase__					:   Union[str, Any]       				=       figure_center_x + (image_x / image_width - 0.5) * figure_width
									UpperCAmelCase__					:   Tuple       				=       figure_center_y + (image_y / image_height - 0.5) * figure_height

									UpperCAmelCase__					:   List[str]       				=       get_distance(UpperCamelCase__	, UpperCamelCase__	, UpperCamelCase__   )

									# color the corresponding pixel based on the selected coloring-function
									if use_distance_color_coding:
												UpperCAmelCase__					:   Any       				=       get_color_coded_rgb(UpperCamelCase__   )
									else:
												UpperCAmelCase__					:   Tuple       				=       get_black_and_white_rgb(UpperCamelCase__   )

			return img


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		# colored version, full figure
		__A		=get_image()

		# uncomment for colored version, different section, zoomed in
		# img = get_image(figure_center_x = -0.6, figure_center_y = -0.4,
		# figure_width = 0.8)

		# uncomment for black and white version, full figure
		# img = get_image(use_distance_color_coding = False)

		# uncomment to save the image
		# img.save("mandelbrot.png")

		img.show()