'''simple docstring'''
from random import shuffle

import tensorflow as tf
from numpy import array







def  _UpperCamelCase (     _a	:	Optional[int]				,     _a	:	str			):




    """simple docstring"""



    __UpperCamelCase	:	Tuple		    =  int(_a			)
    assert noofclusters < len(_a			)

    # Find out the dimensionality
    __UpperCamelCase	:	Dict		    =  len(vectors[0]			)

    # Will help select random centroids from among the available vectors
    __UpperCamelCase	:	List[Any]		    =  list(range(len(_a			)			)			)
    shuffle(_a			)

    # GRAPH OF COMPUTATION
    # We initialize a new graph and set it as the default during each run
    # of this algorithm. This ensures that as this function is called
    # multiple times, the default graph doesn't keep getting crowded with
    # unused ops and Variables from previous function calls.

    __UpperCamelCase	:	int		    =  tf.Graph()

    with graph.as_default():
        # SESSION OF COMPUTATION

        __UpperCamelCase	:	Optional[int]		    =  tf.Session()

        ##CONSTRUCTING THE ELEMENTS OF COMPUTATION

        ##First lets ensure we have a Variable vector for each centroid,
        ##initialized to one of the vectors from the available data points
        __UpperCamelCase	:	Optional[int]		    =  [
            tf.Variable(vectors[vector_indices[i]]			) for i in range(_a			)
        ]
        ##These nodes will assign the centroid Variables the appropriate
        ##values
        __UpperCamelCase	:	Dict		    =  tf.placeholder('float64'				,     [dim]			)
        __UpperCamelCase	:	Tuple		    =  []
        for centroid in centroids:
            cent_assigns.append(tf.assign(_a				,     _a			)			)

        ##Variables for cluster assignments of individual vectors(initialized
        ##to 0 at first)
        __UpperCamelCase	:	int		    =  [tf.Variable(0			) for i in range(len(_a			)			)]
        ##These nodes will assign an assignment Variable the appropriate
        ##value
        __UpperCamelCase	:	List[Any]		    =  tf.placeholder('int32'			)
        __UpperCamelCase	:	Optional[Any]		    =  []
        for assignment in assignments:
            cluster_assigns.append(tf.assign(_a				,     _a			)			)

        ##Now lets construct the node that will compute the mean
        # The placeholder for the input
        __UpperCamelCase	:	List[Any]		    =  tf.placeholder('float'				,     [None, dim]			)
        # The Node/op takes the input and computes a mean along the 0th
        # dimension, i.e. the list of input vectors
        __UpperCamelCase	:	Union[str, Any]		    =  tf.reduce_mean(_a				,     0			)

        ##Node for computing Euclidean distances
        # Placeholders for input
        __UpperCamelCase	:	Any		    =  tf.placeholder('float'				,     [dim]			)
        __UpperCamelCase	:	Union[str, Any]		    =  tf.placeholder('float'				,     [dim]			)
        __UpperCamelCase	:	str		    =  tf.sqrt(tf.reduce_sum(tf.pow(tf.sub(_a				,     _a			)				,     2			)			)			)

        ##This node will figure out which cluster to assign a vector to,
        ##based on Euclidean distances of the vector from the centroids.
        # Placeholder for input
        __UpperCamelCase	:	List[Any]		    =  tf.placeholder('float'				,     [noofclusters]			)
        __UpperCamelCase	:	Dict		    =  tf.argmin(_a				,     0			)

        ##INITIALIZING STATE VARIABLES

        ##This will help initialization of all Variables defined with respect
        ##to the graph. The Variable-initializer should be defined after
        ##all the Variables have been constructed, so that each of them
        ##will be included in the initialization.
        __UpperCamelCase	:	Any		    =  tf.initialize_all_variables()

        # Initialize all variables
        sess.run(_a			)

        ##CLUSTERING ITERATIONS

        # Now perform the Expectation-Maximization steps of K-Means clustering
        # iterations. To keep things simple, we will only do a set number of
        # iterations, instead of using a Stopping Criterion.
        __UpperCamelCase	:	Dict		    =  1_0_0
        for _ in range(_a			):
            ##EXPECTATION STEP
            ##Based on the centroid locations till last iteration, compute
            ##the _expected_ centroid assignments.
            # Iterate over each vector
            for vector_n in range(len(_a			)			):
                __UpperCamelCase	:	str		    =  vectors[vector_n]
                # Compute Euclidean distance between this vector and each
                # centroid. Remember that this list cannot be named
                #'centroid_distances', since that is the input to the
                # cluster assignment node.
                __UpperCamelCase	:	Optional[int]		    =  [
                    sess.run(_a				,     feed_dict={va: vect, va: sess.run(_a			)}			)
                    for centroid in centroids
                ]
                # Now use the cluster assignment node, with the distances
                # as the input
                __UpperCamelCase	:	Optional[int]		    =  sess.run(
                    _a				,     feed_dict={centroid_distances: distances}			)
                # Now assign the value to the appropriate state variable
                sess.run(
                    cluster_assigns[vector_n]				,     feed_dict={assignment_value: assignment}			)

            ##MAXIMIZATION STEP
            # Based on the expected state computed from the Expectation Step,
            # compute the locations of the centroids so as to maximize the
            # overall objective of minimizing within-cluster Sum-of-Squares
            for cluster_n in range(_a			):
                # Collect all the vectors assigned to this cluster
                __UpperCamelCase	:	Tuple		    =  [
                    vectors[i]
                    for i in range(len(_a			)			)
                    if sess.run(assignments[i]			) == cluster_n
                ]
                # Compute new centroid location
                __UpperCamelCase	:	Optional[int]		    =  sess.run(
                    _a				,     feed_dict={mean_input: array(_a			)}			)
                # Assign value to appropriate variable
                sess.run(
                    cent_assigns[cluster_n]				,     feed_dict={centroid_value: new_location}			)

        # Return centroids and assignments
        __UpperCamelCase	:	Optional[Any]		    =  sess.run(_a			)
        __UpperCamelCase	:	Optional[Any]		    =  sess.run(_a			)
        return centroids, assignments




'''simple docstring'''
import unittest

from .lib import (
    Matrix,
    Vector,
    axpy,
    square_zero_matrix,
    unit_basis_vector,
    zero_vector,
)






class 			__lowercase		(						unittest.TestCase						):







     """simple docstring"""






     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Dict		    =  Vector([1, 2, 3]    )
         self.assertEqual(x.component(0    )     ,			1    )
         self.assertEqual(x.component(2    )     ,			3    )
         __UpperCamelCase	:	Dict		    =  Vector()







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	str		    =  Vector([0, 0, 0, 0, 0, 1]    )
         self.assertEqual(str(_lowerCamelCase    )     ,			'(0,0,0,0,0,1)'    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Dict		    =  Vector([1, 2, 3, 4]    )
         self.assertEqual(len(_lowerCamelCase    )     ,			4    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Any		    =  Vector([1, 2]    )
         __UpperCamelCase	:	Optional[int]		    =  Vector([1, 2, 3, 4, 5]    )
         __UpperCamelCase	:	Optional[Any]		    =  Vector([0, 0, 0, 0, 0, 0, 0, 0, 0, 0]    )
         __UpperCamelCase	:	List[str]		    =  Vector([1, -1, 1, -1, 2, -3, 4, -5]    )
         self.assertAlmostEqual(x.euclidean_length()     ,			2.2_3_6     ,			3    )
         self.assertAlmostEqual(y.euclidean_length()     ,			7.4_1_6     ,			3    )
         self.assertEqual(z.euclidean_length()     ,			0    )
         self.assertAlmostEqual(w.euclidean_length()     ,			7.6_1_6     ,			3    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	int		    =  Vector([1, 2, 3]    )
         __UpperCamelCase	:	List[str]		    =  Vector([1, 1, 1]    )
         self.assertEqual((x + y).component(0    )     ,			2    )
         self.assertEqual((x + y).component(1    )     ,			3    )
         self.assertEqual((x + y).component(2    )     ,			4    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Optional[Any]		    =  Vector([1, 2, 3]    )
         __UpperCamelCase	:	Dict		    =  Vector([1, 1, 1]    )
         self.assertEqual((x - y).component(0    )     ,			0    )
         self.assertEqual((x - y).component(1    )     ,			1    )
         self.assertEqual((x - y).component(2    )     ,			2    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Dict		    =  Vector([1, 2, 3]    )
         __UpperCamelCase	:	int		    =  Vector([2, -1, 4]    )  # for test of dot product
         __UpperCamelCase	:	int		    =  Vector([1, -2, -1]    )
         self.assertEqual(str(x * 3.0    )     ,			'(3.0,6.0,9.0)'    )
         self.assertEqual((a * b)     ,			0    )







     def lowerCAmelCase     (		self    ):
         self.assertEqual(str(zero_vector(1_0    )    ).count('0'    )     ,			1_0    )







     def lowerCAmelCase     (		self    ):
         self.assertEqual(str(unit_basis_vector(3     ,			1    )    )     ,			'(0,1,0)'    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Optional[int]		    =  Vector([1, 2, 3]    )
         __UpperCamelCase	:	Union[str, Any]		    =  Vector([1, 0, 1]    )
         self.assertEqual(str(axpy(2     ,			_lowerCamelCase     ,			_lowerCamelCase    )    )     ,			'(3,4,7)'    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	List[str]		    =  Vector([1, 0, 0, 0, 0, 0]    )
         __UpperCamelCase	:	Optional[Any]		    =  x.copy()
         self.assertEqual(str(_lowerCamelCase    )     ,			str(_lowerCamelCase    )    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	List[str]		    =  Vector([1, 0, 0]    )
         x.change_component(0     ,			0    )
         x.change_component(1     ,			1    )
         self.assertEqual(str(_lowerCamelCase    )     ,			'(0,1,0)'    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Tuple		    =  Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]     ,			3     ,			3    )
         self.assertEqual('|1,2,3|\n|2,4,5|\n|6,7,8|\n'     ,			str(_lowerCamelCase    )    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Optional[int]		    =  Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]     ,			3     ,			3    )
         __UpperCamelCase	:	List[str]		    =  [[-3, -1_4, -1_0], [-5, -1_0, -5], [-2, -1, 0]]
         for x in range(a.height()    ):
             for y in range(a.width()    ):
                 self.assertEqual(minors[x][y]     ,			a.minor(_lowerCamelCase     ,			_lowerCamelCase    )    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	int		    =  Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]     ,			3     ,			3    )
         __UpperCamelCase	:	List[str]		    =  [[-3, 1_4, -1_0], [5, -1_0, 5], [-2, 1, 0]]
         for x in range(a.height()    ):
             for y in range(a.width()    ):
                 self.assertEqual(cofactors[x][y]     ,			a.cofactor(_lowerCamelCase     ,			_lowerCamelCase    )    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Any		    =  Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]     ,			3     ,			3    )
         self.assertEqual(-5     ,			a.determinant()    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	int		    =  Matrix([[1, 2, 3], [4, 5, 6], [7, 8, 9]]     ,			3     ,			3    )
         __UpperCamelCase	:	Union[str, Any]		    =  Vector([1, 2, 3]    )
         self.assertEqual('(14,32,50)'     ,			str(a * x    )    )
         self.assertEqual('|2,4,6|\n|8,10,12|\n|14,16,18|\n'     ,			str(a * 2    )    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Union[str, Any]		    =  Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]     ,			3     ,			3    )
         a.change_component(0     ,			2     ,			5    )
         self.assertEqual('|1,2,5|\n|2,4,5|\n|6,7,8|\n'     ,			str(_lowerCamelCase    )    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	int		    =  Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]     ,			3     ,			3    )
         self.assertEqual(7     ,			a.component(2     ,			1    )     ,			0.0_1    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	List[str]		    =  Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]     ,			3     ,			3    )
         __UpperCamelCase	:	Optional[Any]		    =  Matrix([[1, 2, 7], [2, 4, 5], [6, 7, 1_0]]     ,			3     ,			3    )
         self.assertEqual('|2,4,10|\n|4,8,10|\n|12,14,18|\n'     ,			str(a + b    )    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Optional[int]		    =  Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]     ,			3     ,			3    )
         __UpperCamelCase	:	Optional[int]		    =  Matrix([[1, 2, 7], [2, 4, 5], [6, 7, 1_0]]     ,			3     ,			3    )
         self.assertEqual('|0,0,-4|\n|0,0,0|\n|0,0,-2|\n'     ,			str(a - b    )    )







     def lowerCAmelCase     (		self    ):
         self.assertEqual(
             '|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n'     ,			str(square_zero_matrix(5    )    )     ,			)


if __name__ == "__main__":
  unittest.main()



