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How to use to_column method in pandera

Best Python code snippet using pandera_python

candidate.py

Source:candidate.py

1import numpy2import random3Nd = 9  # number of digits4class Candidate(object):5    def __init__(self):6        self.values = numpy.zeros((Nd, Nd), dtype=int) # Set the 9x9 Sudoku into 0s7        self.fitness = None8        return9    def update_fitness(self):10        row_count = numpy.zeros(Nd,dtype=int)11        column_count = numpy.zeros(Nd,dtype=int)12        block_count = numpy.zeros(Nd,dtype=int)13        row_sum = 014        column_sum = 015        block_sum = 016        17        print('--------------Row Sum--------------------')18        for i in range(0, Nd):  # For each row...19            for j in range(0, Nd):  # For each number within it...20                # ...Update list with occurrence of a particular number.21                row_count[self.values[i][j]-1] += 122            row_sum += (1.0/len(set(row_count)))/Nd23            print(f'{row_sum} += (1.0/{len(set(row_count))})/{Nd}')24            row_count = numpy.zeros(Nd)25        26        print('-------------Column Sum------------------')27        for i in range(0, Nd):  # For each column...28            for j in range(0, Nd):  # For each number within it...29                # ...Update list with occurrence of a particular number.30                column_count[self.values[j][i]-1] += 131            column_sum += (1.0 / len(set(column_count)))/Nd32            print(f'{column_sum} += (1.0/{len(set(column_count))})/{Nd}')33            column_count = numpy.zeros(Nd)34        35        print('-------------Block Sum--------------------')36        # For each block...37        for i in range(0, Nd, 3):38            for j in range(0, Nd, 3):39                block_count[self.values[i][j]-1] += 140                block_count[self.values[i][j+1]-1] += 141                block_count[self.values[i][j+2]-1] += 142                block_count[self.values[i+1][j]-1] += 143                block_count[self.values[i+1][j+1]-1] += 144                block_count[self.values[i+1][j+2]-1] += 145                block_count[self.values[i+2][j]-1] += 146                block_count[self.values[i+2][j+1]-1] += 147                block_count[self.values[i+2][j+2]-1] += 148                block_sum += (1.0/len(set(block_count)))/Nd49                print(f'{block_sum} += (1.0/{len(set(block_count))})/{Nd}')50                block_count = numpy.zeros(Nd)51        52        print('------------Overall Fitness--------------------')53        # Calculate overall fitness.54        if (int(row_sum) == 1 and int(column_sum) == 1 and int(block_sum) == 1):55            fitness = 1.056            print(f'Row Sum = {row_sum} Column Sum = {column_sum} Block Sum = {block_sum} Fitness = {fitness}')57        else:58            fitness = column_sum * block_sum59            print('Fitness =\t\t Column Sum\t * Block Sum')60            print(f'{fitness} = {column_sum} * {block_sum}')61        self.fitness = fitness62        return63    def mutate(self, mutation_rate, given):64        """ Mutate a candidate by picking a row, and then picking two values within that row to swap. """65        r = random.uniform(0, 1.1)66        while(r > 1): # Outside [0, 1] boundary - choose another67            r = random.uniform(0, 1.1)68            print(f'r = {r}')69    70        success = False71        if (r < mutation_rate):  # Mutate.72            while(not success):73                row1 = random.randint(0, 8)74                row2 = random.randint(0, 8)75                row2 = row176                print(f'row1 = {row1} row2 = {row2}')77                78                from_column = random.randint(0, 8)79                to_column = random.randint(0, 8)80                while(from_column == to_column):81                    from_column = random.randint(0, 8)82                    to_column = random.randint(0, 8)   83                # Check if the two places are free...84                if(given[row1][from_column] == 0 and given[row1][to_column] == 0):85                    # ...and that we are not causing a duplicate in the rows' columns.86                    if self.is_column_duplicate(to_column, self.values[row1][from_column]): return87                    if self.is_column_duplicate(from_column, self.values[row2][to_column]): return88                    if self.is_block_duplicate(row2, to_column, self.values[row1][from_column]): return89                    if self.is_block_duplicate(row1, from_column, self.values[row2][to_column]): return90                    # Swap values.91                    temp = self.values[row2][to_column]92                    self.values[row2][to_column] = self.values[row1][from_column]93                    self.values[row1][from_column] = temp94                    success = True95    96        return success97    def is_row_duplicate(self, row, value):98        """ Check whether there is a duplicate of a fixed/given value in a row. """99        for column in range(0, Nd):100            if(self.values[row][column] == value):101                return True102        return False103    def is_column_duplicate(self, column, value):104        """ Check whether there is a duplicate of a fixed/given value in a column. """105        for row in range(0, Nd):106            if(self.values[row][column] == value):107                return True108        return False109    def is_block_duplicate(self, row, column, value):110        """ Check whether there is a duplicate of a fixed/given value in a 3 x 3 block. """111        i = 3*(int(row/3))112        j = 3*(int(column/3))113        if((self.values[i][j] == value)114            or (self.values[i][j+1] == value)115            or (self.values[i][j+2] == value)116            or (self.values[i+1][j] == value)117            or (self.values[i+1][j+1] == value)118            or (self.values[i+1][j+2] == value)119            or (self.values[i+2][j] == value)120            or (self.values[i+2][j+1] == value)121            or (self.values[i+2][j+2] == value)):122            return True123        else:...

Mutation.py

Source:Mutation.py

12import numpy as np3import random4import operator5import setup as v6from past.builtins import range78class Mutation(object):9    10    11    def __init__(self):12        return13    14    15###############################################################################################16def swap_mutation(self, mutation_rate, given):17   1819    r = random.uniform(0, 1.1)20    while r > 1:  21        r = random.uniform(0, 1.1)2223    success = False24    if r < mutation_rate:  25        while not success:26            row1 = random.randint(0, 8)27            row2 = random.randint(0, 8)28            2930            from_column = random.randint(0, 8)31            to_column = random.randint(0, 8)32            while from_column == to_column:33                from_column = random.randint(0, 8)34                to_column = random.randint(0, 8)3536                37            if given.values[row1][from_column] == 0 and given.values[row1][to_column] == 0:38                39                if not given.is_column_duplicate(to_column, self.values[row1][from_column]) and not given.is_column_duplicate(from_column, self.values[row2][to_column]) and not given.is_block_duplicate(row2, to_column, self.values[row1][from_column]) and not given.is_block_duplicate(row1, from_column, self.values[row2][to_column]):40                    41                    temp = self.values[row2][to_column]42                    self.values[row2][to_column] = self.values[row1][from_column]43                    self.values[row1][from_column] = temp44                    success = True4546    return success4748###############################################################################################49def inversion_mutation(self, mutation_rate, given):5051    r = random.uniform(0, 1.1)52    while r > 1:  53        r = random.uniform(0, 1.1)5455    success = False56    if r < mutation_rate:  57        while not success:58            row1 = random.randint(0, 8)59            row2 = random.randint(0, 8)60            6162            from_column = random.randint(0, 8)63            to_column = random.randint(0, 8)64            while from_column == to_column:65                from_column = random.randint(0, 8)66                to_column = random.randint(0, 8)6768               69            if given.values[row1][from_column] == 0 and given.values[row1][to_column] == 0:70            71                if not given.is_column_duplicate(to_column, self.values[row1][from_column]) and not given.is_column_duplicate(from_column, self.values[row2][to_column]) and not given.is_block_duplicate(row2, to_column, self.values[row1][from_column]) and not given.is_block_duplicate(row1, from_column, self.values[row2][to_column]):72                    73                    reversed(self.values[row1:row2][from_column:to_column])74                    75                    success = True76    77    return True7879###############################################################################################80def scramble_mutation(self, mutation_rate, given):8182    r = random.uniform(0, 1.1)83    while r > 1:  84        r = random.uniform(0, 1.1)8586        success = False87        if r < mutation_rate:  88            while not success:89                row1 = random.randint(0, 8)90                row2 = random.randint(0, 8)91                9293                from_column = random.randint(0, 8)94                to_column = random.randint(0, 8)95                while from_column == to_column:96                    from_column = random.randint(0, 8)97                    to_column = random.randint(0, 8)9899                    100                if given.values[row1][from_column] == 0 and given.values[row1][to_column] == 0:101                    102                    if not given.is_column_duplicate(to_column, self.values[row1][from_column]) and not given.is_column_duplicate(from_column, self.values[row2][to_column]) and not given.is_block_duplicate(row2, to_column, self.values[row1][from_column]) and not given.is_block_duplicate(row1, from_column, self.values[row2][to_column]):103                        104                        random.shuffle(self.values[row1:row2][from_column:to_column])105                        106                        107                        success = True108                        109    110    return True
...

test_column_format.py

Source:test_column_format.py

2import pytest3from json2db.core import ColumnFormat, FrameworkNotSupport4def test_not_support():5    with pytest.raises(FrameworkNotSupport):6        ColumnFormat.to_column("test", "NotSupportFormat")7def test_to_camel():8    assert "abcAbc" == ColumnFormat.to_column("abc_abc", ColumnFormat.CAMEL)9    assert "abcAbcId" == ColumnFormat.to_column("abc_abc", ColumnFormat.CAMEL, "id")10    assert "abcAbcEfg" == ColumnFormat.to_column("abc_abc_efg", ColumnFormat.CAMEL, "")11    assert "abcAbcEfgId" == ColumnFormat.to_column("abc_abc_efg", ColumnFormat.CAMEL, "id")12    assert "AbcAbc" == ColumnFormat.to_column("AbcAbc", ColumnFormat.CAMEL)13    assert "AbcAbcFakeId" == ColumnFormat.to_column("AbcAbc", ColumnFormat.CAMEL, "fake_id")14def test_to_underline():15    assert "abc_abc" == ColumnFormat.to_column("abcAbc", ColumnFormat.UNDERLINE)16    assert "abc_abc_id" == ColumnFormat.to_column("abcAbc", ColumnFormat.UNDERLINE, 'id')17    assert "abc_Abc_id" == ColumnFormat.to_column("abc_Abc", ColumnFormat.UNDERLINE, 'id')18def test_to_default():19    assert "abcAbc" == ColumnFormat.to_column("abcAbc", ColumnFormat.DEFAULT)20    assert "abcAbcid" == ColumnFormat.to_column("abcAbc", ColumnFormat.DEFAULT, 'id')21def test_column_object_camel():22    fmt = ColumnFormat(ColumnFormat.CAMEL)23    assert fmt.rename("abcABC") == "abcABC"24    assert fmt.rename("abcABC", "id") == "abcABCId"25    assert fmt.rename("abc_aBC", "id") == "abcABCId"26def test_column_object_default():27    fmt = ColumnFormat()28    assert fmt.rename("abcABC") == "abcABC"29    assert fmt.rename("abcABC", "id") == "abcABCid"30    assert fmt.rename("abc_aBC", "id") == "abc_aBCid"31def test_column_object_underline():32    fmt = ColumnFormat(ColumnFormat.UNDERLINE)33    assert fmt.rename("abcABC") == "abc_aBC"34    assert fmt.rename("abcABC", "id") == "abc_aBC_id"...

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