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-rw-r--r--account/__init__.py0
-rw-r--r--account/quick_deduction.py22
-rw-r--r--dl/__init__.py0
-rw-r--r--dl/bn/__init__.py0
-rw-r--r--dl/bn/np_demo.py28
-rw-r--r--matrix/__init__.py0
-rw-r--r--matrix/rank.py7
-rw-r--r--ml/__init__.py0
-rw-r--r--ml/gbdt+lr/__init__.py0
-rw-r--r--network/__init__.py0
-rw-r--r--network/logic_gates.py13
-rw-r--r--network/lstm_add.py138
-rw-r--r--oop/MethodTest.py42
-rw-r--r--oop/TestProperrty.py22
-rw-r--r--oop/__init__.py0
-rw-r--r--oop/dp/Decorator.py59
-rw-r--r--oop/dp/__init__.py0
-rw-r--r--ordemo/polygon.py45
-rw-r--r--ordemo/send_more_money.py4
-rw-r--r--ordemo/two_sum.py36
-rw-r--r--sat/__init__.py0
-rw-r--r--sat/color.py1561
22 files changed, 1975 insertions, 2 deletions
diff --git a/account/__init__.py b/account/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/account/__init__.py
diff --git a/account/quick_deduction.py b/account/quick_deduction.py
new file mode 100644
index 0000000..a12fb64
--- /dev/null
+++ b/account/quick_deduction.py
@@ -0,0 +1,22 @@
+
+
+def deduction(x):
+ if x < 36000:
+ return x*0.03
+ if x < 144000:
+ return 36000*0.03 - 36000*0.1
+ if x < 300000:
+ return 36000*0.03 + (144000 - 36000)*0.1 - 144000*0.2
+ if x < 420000:
+ return 36000*0.03 + (144000 - 36000)*0.1 + (300000 - 144000)*0.2 - 300000*0.25
+ if x < 660000:
+ return 36000*0.03 + (144000 - 36000)*0.1 + (300000 - 144000)*0.2 + (420000 - 300000)*0.25 - 420000*0.3
+ if x < 960000:
+ return 36000 * 0.03 + (144000 - 36000) * 0.1 + (300000 - 144000) * 0.2 + (420000 - 300000) * 0.25 + (660000 - 420000) * 0.3 - 660000*0.35
+ return 36000 * 0.03 + (144000 - 36000) * 0.1 + (300000 - 144000) * 0.2 + (420000 - 300000) * 0.25 + (660000 - 420000) * 0.3 + (960000 - 660000)*0.35 - 960000*0.45
+
+
+if __name__ == '__main__':
+ for x in [10000, 100000, 200000, 300000, 400000, 500000, 600000, 700000, 800000, 900000, 10000000]:
+ print(x, deduction(x))
+
diff --git a/dl/__init__.py b/dl/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/dl/__init__.py
diff --git a/dl/bn/__init__.py b/dl/bn/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/dl/bn/__init__.py
diff --git a/dl/bn/np_demo.py b/dl/bn/np_demo.py
new file mode 100644
index 0000000..9cd6296
--- /dev/null
+++ b/dl/bn/np_demo.py
@@ -0,0 +1,28 @@
+
+import numpy as np
+import matplotlib.pyplot as plt
+
+
+batch = np.zeros([2, 3, 3, 3])
+batch[0, :, :, 0] = np.asarray([[2.4, 0.3, 5.6],
+ [7.2, 0.0, 2.1],
+ [1.9, 7.4, 4.1]])
+batch[0, :, :, 1] = np.asarray([[1.0, 2.1, 3.8],
+ [9.6, 2.0, 4.4],
+ [9.3, 3.9, 1.4]])
+batch[0, :, :, 2] = np.asarray([[2.6, 8.1, 9.0],
+ [2.2, 6.6, 0.2],
+ [6.3, 6.0, 0.1]])
+
+batch[1, :, :, 0] = np.asarray([[5.1, 9.0, 6.9],
+ [9.7, 2.9, 2.4],
+ [6.2, 0.7, 4.3]])
+batch[1, :, :, 1] = np.asarray([[3.3, 7.9, 4.8],
+ [3.7, 2.0, 9.4],
+ [4.9, 2.1, 7.8]])
+
+batch[1, :, :, 2] = np.asarray([[2.8, 5.4, 0.0],
+ [6.4, 1.8, 6.8],
+ [3.7, 5.6, 5.6]])
+print(batch[:, :, :, 0].mean())
+print(batch[:, :, :, 0].var()) \ No newline at end of file
diff --git a/matrix/__init__.py b/matrix/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/matrix/__init__.py
diff --git a/matrix/rank.py b/matrix/rank.py
new file mode 100644
index 0000000..6ade71b
--- /dev/null
+++ b/matrix/rank.py
@@ -0,0 +1,7 @@
+
+import numpy as np
+from numpy.linalg import matrix_rank
+
+if __name__ == '__main__':
+ m = np.asarray([[1, 2, 3], [4, 5, 6], [5, 7, 9]])
+ matrix_rank(m) \ No newline at end of file
diff --git a/ml/__init__.py b/ml/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/ml/__init__.py
diff --git a/ml/gbdt+lr/__init__.py b/ml/gbdt+lr/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/ml/gbdt+lr/__init__.py
diff --git a/network/__init__.py b/network/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/network/__init__.py
diff --git a/network/logic_gates.py b/network/logic_gates.py
new file mode 100644
index 0000000..2a33d16
--- /dev/null
+++ b/network/logic_gates.py
@@ -0,0 +1,13 @@
+import torch
+
+
+def and_gate():
+ and_weights = torch.tensor([1, 1, -2])
+
+
+if __name__ == '__main__':
+ # x1, x2, b
+ X = torch.tensor([(0, 0, 1), (0, 1, 1), (1, 0, 1), (1, 1, 1)], dtype=torch.double)
+
+ print(X)
+ pass
diff --git a/network/lstm_add.py b/network/lstm_add.py
new file mode 100644
index 0000000..1eeb4f9
--- /dev/null
+++ b/network/lstm_add.py
@@ -0,0 +1,138 @@
+from random import seed
+from random import randint
+from numpy import array
+from math import ceil
+from math import log10
+from math import sqrt
+from numpy import argmax
+from keras.models import Sequential
+from keras.layers import Dense
+from keras.layers import LSTM
+from keras.layers import TimeDistributed
+from keras.layers import RepeatVector
+
+
+# generate lists of random integers and their sum
+def random_sum_pairs(n_examples, n_numbers, largest):
+ X, y = list(), list()
+ for i in range(n_examples):
+ in_pattern = [randint(1, largest) for _ in range(n_numbers)]
+ out_pattern = sum(in_pattern)
+ X.append(in_pattern)
+ y.append(out_pattern)
+ return X, y
+
+
+# convert data to strings
+def to_string(X, y, n_numbers, largest):
+ max_length = n_numbers * ceil(log10(largest + 1)) + n_numbers - 1
+ Xstr = list()
+ for pattern in X:
+ strp = '+'.join([str(n) for n in pattern])
+ strp = ''.join([' ' for _ in range(max_length - len(strp))]) + strp
+ Xstr.append(strp)
+ max_length = ceil(log10(n_numbers * (largest + 1)))
+ ystr = list()
+ for pattern in y:
+ strp = str(pattern)
+ strp = ''.join([' ' for _ in range(max_length - len(strp))]) + strp
+ ystr.append(strp)
+ return Xstr, ystr
+
+
+# integer encode strings
+def integer_encode(X, y, alphabet):
+ char_to_int = dict((c, i) for i, c in enumerate(alphabet))
+ Xenc = list()
+ for pattern in X:
+ integer_encoded = [char_to_int[char] for char in pattern]
+ Xenc.append(integer_encoded)
+ yenc = list()
+ for pattern in y:
+ integer_encoded = [char_to_int[char] for char in pattern]
+ yenc.append(integer_encoded)
+ return Xenc, yenc
+
+
+# one hot encode
+def one_hot_encode(X, y, max_int):
+ Xenc = list()
+ for seq in X:
+ pattern = list()
+ for index in seq:
+ vector = [0 for _ in range(max_int)]
+ vector[index] = 1
+ pattern.append(vector)
+ Xenc.append(pattern)
+ yenc = list()
+ for seq in y:
+ pattern = list()
+ for index in seq:
+ vector = [0 for _ in range(max_int)]
+ vector[index] = 1
+ pattern.append(vector)
+ yenc.append(pattern)
+ return Xenc, yenc
+
+
+# generate an encoded dataset
+def generate_data(n_samples, n_numbers, largest, alphabet):
+ # generate pairs
+ X, y = random_sum_pairs(n_samples, n_numbers, largest)
+ # convert to strings
+ X, y = to_string(X, y, n_numbers, largest)
+ # integer encode
+ X, y = integer_encode(X, y, alphabet)
+ # one hot encode
+ X, y = one_hot_encode(X, y, len(alphabet))
+ # return as numpy arrays
+ X, y = array(X), array(y)
+ return X, y
+
+
+# invert encoding
+def invert(seq, alphabet):
+ int_to_char = dict((i, c) for i, c in enumerate(alphabet))
+ strings = list()
+ for pattern in seq:
+ string = int_to_char[argmax(pattern)]
+ strings.append(string)
+ return ''.join(strings)
+
+
+# define dataset
+seed(1)
+n_samples = 5000
+n_numbers = 2
+largest = 100
+alphabet = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '+', ' ']
+n_chars = len(alphabet)
+n_in_seq_length = n_numbers * ceil(log10(largest + 1)) + n_numbers - 1
+n_out_seq_length = ceil(log10(n_numbers * (largest + 1)))
+# define LSTM configuration
+n_batch = 10
+n_epoch = 50
+# create LSTM
+model = Sequential()
+# n_in_seq_length: 7, n_chars: 12
+model.add(LSTM(100, input_shape=(n_in_seq_length, n_chars)))
+model.add(RepeatVector(n_out_seq_length))
+model.add(LSTM(50, return_sequences=True))
+model.add(TimeDistributed(Dense(n_chars, activation='softmax')))
+model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
+print(model.summary())
+# train LSTM
+for i in range(n_epoch):
+ X, y = generate_data(n_samples, n_numbers, largest, alphabet)
+ print(i)
+ model.fit(X, y, epochs=1, batch_size=n_batch)
+
+# evaluate on some new patterns
+X, y = generate_data(n_samples, n_numbers, largest, alphabet)
+result = model.predict(X, batch_size=n_batch, verbose=0)
+# calculate error
+expected = [invert(x, alphabet) for x in y]
+predicted = [invert(x, alphabet) for x in result]
+# show some examples
+for i in range(20):
+ print('Expected=%s, Predicted=%s' % (expected[i], predicted[i]))
diff --git a/oop/MethodTest.py b/oop/MethodTest.py
new file mode 100644
index 0000000..67fdf57
--- /dev/null
+++ b/oop/MethodTest.py
@@ -0,0 +1,42 @@
+
+from datetime import datetime
+
+class Test:
+ alias = 'wudaokou nash'
+
+ @staticmethod
+ def static_mode(language):
+ print(f'static method, {Test.alias} codes in {language}')
+
+ @classmethod
+ def class_mode(cls, language):
+ print(f'class method, {cls.alias} codes in {language}')
+
+
+class Repr:
+
+ def __init__(self, name):
+ self.name = name
+
+ def __repr__(self):
+ return f'{self.__class__.__module__}.{self.__class__.__qualname__}(name={self.name})'
+
+ def __str__(self):
+ return f'{self.name}'
+
+
+if __name__ == '__main__':
+ t = Test()
+ t.static_mode('chinese')
+ t.class_mode('english')
+
+ r = Repr('zhang')
+ print(r)
+ print(repr(r))
+ print(str(r))
+
+ now = datetime.now()
+ print(now.__str__())
+ print(now.__repr__())
+
+
diff --git a/oop/TestProperrty.py b/oop/TestProperrty.py
new file mode 100644
index 0000000..de43e17
--- /dev/null
+++ b/oop/TestProperrty.py
@@ -0,0 +1,22 @@
+
+class Screen(object):
+ @property
+ def width(self):
+ return self._width
+
+ @width.setter
+ def width(self, value):
+ self._width = value
+
+ @property
+ def height(self):
+ return self._height
+
+ @height.setter
+ def height(self, value):
+ self._height = value
+
+ @property
+ def resolution(self):
+ return self._height*self._width
+
diff --git a/oop/__init__.py b/oop/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/oop/__init__.py
diff --git a/oop/dp/Decorator.py b/oop/dp/Decorator.py
new file mode 100644
index 0000000..390935a
--- /dev/null
+++ b/oop/dp/Decorator.py
@@ -0,0 +1,59 @@
+
+from abc import ABCMeta, abstractmethod
+
+
+class Person(metaclass=ABCMeta):
+ def __init__(self, name):
+ self._name = name
+
+ @abstractmethod
+ def wear(self):
+ print('着装: ')
+
+
+class Engineer(Person):
+
+ def __init__(self, name, skill):
+ super().__init__(name)
+ self._skill = skill
+
+ def wear(self):
+ print(f'我是 {self._name} 工程师, 我会 {self._skill}')
+ super().wear()
+
+
+class ClothingDecorator(Person):
+ def __init__(self, person: Person):
+ self._decoratored = person
+
+ def wear(self):
+ self._decoratored.wear()
+ self.decorate()
+
+ @abstractmethod
+ def decorate(self):
+ pass
+
+
+class CasualPantDecorator(ClothingDecorator):
+ def __init__(self, person: Person):
+ super().__init__(person)
+ def decorate(self):
+ print('一条卡其色裤子')
+
+
+class BeltDecorator(ClothingDecorator):
+ def __init__(self, person: Person):
+ super().__init__(person)
+
+ def decorate(self):
+ print('一条黑色腰带')
+
+if __name__ == '__main__':
+ tony = Engineer('Tony', '算法')
+ pant = CasualPantDecorator(tony)
+ belt = BeltDecorator(pant)
+ belt.wear()
+
+
+
diff --git a/oop/dp/__init__.py b/oop/dp/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/oop/dp/__init__.py
diff --git a/ordemo/polygon.py b/ordemo/polygon.py
new file mode 100644
index 0000000..6a157f4
--- /dev/null
+++ b/ordemo/polygon.py
@@ -0,0 +1,45 @@
+from ortools.linear_solver import pywraplp
+
+
+def main():
+ # Create the mip solver with the SCIP backend.
+ solver = pywraplp.Solver.CreateSolver('SCIP')
+
+ infinity = solver.infinity()
+ # x and y are integer non-negative variables.
+ x = solver.IntVar(3, infinity, 'x')
+ y = solver.IntVar(0, infinity, 'y')
+ t = solver.IntVar(0, infinity, 't')
+
+ print('Number of variables =', solver.NumVariables())
+
+ solver.Add(t == x-2)
+ # x + 7 * y <= 17.5.
+ solver.Add(y == 2*x/t)
+
+ # x <= 3.5.
+ # solver.Add(x <= 3.5)
+
+ print('Number of constraints =', solver.NumConstraints())
+
+ # Maximize x + 10 * y.
+ solver.Maximize(0)
+
+ status = solver.Solve()
+
+ if status == pywraplp.Solver.OPTIMAL:
+ print('Solution:')
+ print('Objective value =', solver.Objective().Value())
+ print('x =', x.solution_value())
+ print('y =', y.solution_value())
+ else:
+ print('The problem does not have an optimal solution.')
+
+ print('\nAdvanced usage:')
+ print('Problem solved in %f milliseconds' % solver.wall_time())
+ print('Problem solved in %d iterations' % solver.iterations())
+ print('Problem solved in %d branch-and-bound nodes' % solver.nodes())
+
+
+if __name__ == '__main__':
+ main() \ No newline at end of file
diff --git a/ordemo/send_more_money.py b/ordemo/send_more_money.py
index 77fddda..d8e10fa 100644
--- a/ordemo/send_more_money.py
+++ b/ordemo/send_more_money.py
@@ -50,5 +50,5 @@ solver.parameters.enumerate_all_solutions = True
solver.Solve(model, solution_printer)
-print(
- f" {solver.Value(S)}{solver.Value(E)}{solver.Value(N)}{solver.Value(D)}\n+ {solver.Value(M)}{solver.Value(O)}{solver.Value(R)}{solver.Value(E)}\n={solver.Value(M)}{solver.Value(O)}{solver.Value(N)}{solver.Value(E)}{solver.Value(Y)}")
+# print(
+# f" {solver.Value(S)}{solver.Value(E)}{solver.Value(N)}{solver.Value(D)}\n+ {solver.Value(M)}{solver.Value(O)}{solver.Value(R)}{solver.Value(E)}\n={solver.Value(M)}{solver.Value(O)}{solver.Value(N)}{solver.Value(E)}{solver.Value(Y)}")
diff --git a/ordemo/two_sum.py b/ordemo/two_sum.py
new file mode 100644
index 0000000..5652998
--- /dev/null
+++ b/ordemo/two_sum.py
@@ -0,0 +1,36 @@
+from ortools.sat.python import cp_model
+
+
+class VarArraySolutionPrinter(cp_model.CpSolverSolutionCallback):
+ """Print intermediate solutions."""
+
+ def __init__(self, variables):
+ cp_model.CpSolverSolutionCallback.__init__(self)
+ self.__variables = variables
+ self.__solution_count = 0
+
+ def on_solution_callback(self):
+ self.__solution_count += 1
+ for v in self.__variables:
+ print('%s=%i' % (v, self.Value(v)), end=' ')
+ print()
+
+ def solution_count(self):
+ return self.__solution_count
+
+
+l = [2, 7, 1, 3, 6, 9, 10, -1, 12, 22]
+target = 9
+
+model = cp_model.CpModel()
+
+xs = [model.NewBoolVar(str(i)) for i in range(len(l))]
+
+model.Add(sum(xs) == 2)
+
+model.Add(sum([xs[i]*l[i] for i in range(len(l))]) == target)
+solver = cp_model.CpSolver()
+solution_printer = VarArraySolutionPrinter(xs)
+solver.parameters.enumerate_all_solutions = True
+solver.Solve(model, solution_printer)
+
diff --git a/sat/__init__.py b/sat/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/sat/__init__.py
diff --git a/sat/color.py b/sat/color.py
new file mode 100644
index 0000000..094370d
--- /dev/null
+++ b/sat/color.py
@@ -0,0 +1,1561 @@
+N = 120
+# X(G) = 9
+COLORS = 8
+# M = 1276
+EDGES = [
+ [1, 16],
+ [1, 20],
+ [1, 94],
+ [1, 80],
+ [1, 57],
+ [1, 62],
+ [1, 89],
+ [1, 113],
+ [1, 5],
+ [1, 21],
+ [1, 15],
+ [2, 24],
+ [2, 30],
+ [2, 77],
+ [2, 92],
+ [2, 41],
+ [2, 55],
+ [2, 6],
+ [2, 54],
+ [3, 100],
+ [3, 44],
+ [3, 105],
+ [3, 91],
+ [3, 42],
+ [3, 103],
+ [3, 90],
+ [3, 22],
+ [3, 67],
+ [3, 31],
+ [3, 115],
+ [3, 71],
+ [4, 38],
+ [4, 85],
+ [4, 49],
+ [4, 50],
+ [4, 61],
+ [4, 63],
+ [4, 99],
+ [4, 96],
+ [4, 84],
+ [4, 107],
+ [4, 12],
+ [5, 56],
+ [5, 26],
+ [5, 72],
+ [5, 38],
+ [5, 32],
+ [5, 85],
+ [5, 76],
+ [5, 1],
+ [5, 34],
+ [5, 53],
+ [6, 11],
+ [6, 87],
+ [6, 13],
+ [6, 14],
+ [6, 41],
+ [6, 24],
+ [6, 55],
+ [6, 92],
+ [6, 2],
+ [6, 60],
+ [7, 66],
+ [7, 83],
+ [7, 21],
+ [7, 118],
+ [7, 48],
+ [7, 10],
+ [7, 120],
+ [7, 25],
+ [7, 75],
+ [7, 64],
+ [7, 28],
+ [7, 51],
+ [8, 73],
+ [8, 18],
+ [8, 53],
+ [8, 86],
+ [8, 71],
+ [8, 104],
+ [8, 98],
+ [8, 38],
+ [8, 46],
+ [8, 100],
+ [9, 33],
+ [9, 31],
+ [9, 69],
+ [9, 58],
+ [9, 116],
+ [9, 17],
+ [9, 51],
+ [9, 70],
+ [9, 101],
+ [9, 119],
+ [9, 38],
+ [10, 25],
+ [10, 75],
+ [10, 48],
+ [10, 83],
+ [10, 21],
+ [10, 7],
+ [10, 64],
+ [10, 35],
+ [10, 120],
+ [10, 36],
+ [10, 118],
+ [11, 6],
+ [11, 55],
+ [11, 14],
+ [11, 41],
+ [11, 60],
+ [11, 87],
+ [11, 30],
+ [11, 54],
+ [11, 13],
+ [12, 117],
+ [12, 19],
+ [12, 43],
+ [12, 102],
+ [12, 23],
+ [12, 88],
+ [12, 35],
+ [12, 97],
+ [12, 68],
+ [12, 29],
+ [12, 4],
+ [13, 60],
+ [13, 41],
+ [13, 6],
+ [13, 87],
+ [13, 55],
+ [13, 14],
+ [13, 54],
+ [13, 77],
+ [13, 30],
+ [13, 11],
+ [14, 55],
+ [14, 60],
+ [14, 11],
+ [14, 6],
+ [14, 87],
+ [14, 13],
+ [14, 77],
+ [14, 54],
+ [14, 24],
+ [14, 41],
+ [15, 53],
+ [15, 95],
+ [15, 52],
+ [15, 65],
+ [15, 59],
+ [15, 108],
+ [15, 39],
+ [15, 66],
+ [15, 37],
+ [15, 112],
+ [15, 88],
+ [15, 1],
+ [16, 65],
+ [16, 1],
+ [16, 62],
+ [16, 80],
+ [16, 94],
+ [16, 47],
+ [16, 57],
+ [16, 113],
+ [16, 89],
+ [16, 26],
+ [16, 27],
+ [16, 34],
+ [17, 31],
+ [17, 34],
+ [17, 28],
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+ [113, 33],
+ [113, 20],
+ [113, 80],
+ [113, 57],
+ [113, 47],
+ [113, 94],
+ [113, 89],
+ [113, 16],
+ [113, 1],
+ [113, 49],
+ [113, 108],
+ [113, 27],
+ [114, 115],
+ [114, 32],
+ [114, 64],
+ [114, 82],
+ [114, 62],
+ [114, 102],
+ [114, 48],
+ [114, 19],
+ [115, 114],
+ [115, 101],
+ [115, 69],
+ [115, 111],
+ [115, 58],
+ [115, 36],
+ [115, 32],
+ [115, 3],
+ [115, 17],
+ [116, 94],
+ [116, 58],
+ [116, 110],
+ [116, 101],
+ [116, 70],
+ [116, 9],
+ [116, 79],
+ [116, 106],
+ [116, 36],
+ [116, 38],
+ [116, 33],
+ [116, 119],
+ [117, 12],
+ [117, 35],
+ [117, 97],
+ [117, 43],
+ [117, 102],
+ [117, 19],
+ [117, 23],
+ [117, 39],
+ [117, 94],
+ [117, 45],
+ [117, 105],
+ [118, 120],
+ [118, 21],
+ [118, 25],
+ [118, 7],
+ [118, 75],
+ [118, 48],
+ [118, 94],
+ [118, 83],
+ [118, 10],
+ [118, 82],
+ [119, 46],
+ [119, 45],
+ [119, 66],
+ [119, 40],
+ [119, 71],
+ [119, 81],
+ [119, 74],
+ [119, 82],
+ [119, 64],
+ [119, 9],
+ [119, 116],
+ [120, 118],
+ [120, 25],
+ [120, 75],
+ [120, 48],
+ [120, 83],
+ [120, 21],
+ [120, 7],
+ [120, 28],
+ [120, 10],
+ [120, 64],
+ [120, 109],
+]
+
+# N = 47
+# # X(G) = 6
+# COLORS = 5
+# # M = 236
+# EDGES = [
+# [1, 2],
+# [1, 4],
+# [1, 7],
+# [1, 9],
+# [1, 13],
+# [1, 15],
+# [1, 18],
+# [1, 20],
+# [1, 25],
+# [1, 27],
+# [1, 30],
+# [1, 32],
+# [1, 36],
+# [1, 38],
+# [1, 41],
+# [1, 43],
+# [2, 3],
+# [2, 6],
+# [2, 8],
+# [2, 12],
+# [2, 14],
+# [2, 17],
+# [2, 19],
+# [2, 24],
+# [2, 26],
+# [2, 29],
+# [2, 31],
+# [2, 35],
+# [2, 37],
+# [2, 40],
+# [2, 42],
+# [3, 5],
+# [3, 7],
+# [3, 10],
+# [3, 13],
+# [3, 16],
+# [3, 18],
+# [3, 21],
+# [3, 25],
+# [3, 28],
+# [3, 30],
+# [3, 33],
+# [3, 36],
+# [3, 39],
+# [3, 41],
+# [3, 44],
+# [4, 5],
+# [4, 6],
+# [4, 10],
+# [4, 12],
+# [4, 16],
+# [4, 17],
+# [4, 21],
+# [4, 24],
+# [4, 28],
+# [4, 29],
+# [4, 33],
+# [4, 35],
+# [4, 39],
+# [4, 40],
+# [4, 44],
+# [5, 8],
+# [5, 9],
+# [5, 14],
+# [5, 15],
+# [5, 19],
+# [5, 20],
+# [5, 26],
+# [5, 27],
+# [5, 31],
+# [5, 32],
+# [5, 37],
+# [5, 38],
+# [5, 42],
+# [5, 43],
+# [6, 11],
+# [6, 13],
+# [6, 15],
+# [6, 22],
+# [6, 25],
+# [6, 27],
+# [6, 34],
+# [6, 36],
+# [6, 38],
+# [6, 45],
+# [7, 11],
+# [7, 12],
+# [7, 14],
+# [7, 22],
+# [7, 24],
+# [7, 26],
+# [7, 34],
+# [7, 35],
+# [7, 37],
+# [7, 45],
+# [8, 11],
+# [8, 13],
+# [8, 16],
+# [8, 22],
+# [8, 25],
+# [8, 28],
+# [8, 34],
+# [8, 36],
+# [8, 39],
+# [8, 45],
+# [9, 11],
+# [9, 12],
+# [9, 16],
+# [9, 22],
+# [9, 24],
+# [9, 28],
+# [9, 34],
+# [9, 35],
+# [9, 39],
+# [9, 45],
+# [10, 11],
+# [10, 14],
+# [10, 15],
+# [10, 22],
+# [10, 26],
+# [10, 27],
+# [10, 34],
+# [10, 37],
+# [10, 38],
+# [10, 45],
+# [11, 17],
+# [11, 18],
+# [11, 19],
+# [11, 20],
+# [11, 21],
+# [11, 29],
+# [11, 30],
+# [11, 31],
+# [11, 32],
+# [11, 33],
+# [11, 40],
+# [11, 41],
+# [11, 42],
+# [11, 43],
+# [11, 44],
+# [12, 23],
+# [12, 25],
+# [12, 27],
+# [12, 30],
+# [12, 32],
+# [12, 46],
+# [13, 23],
+# [13, 24],
+# [13, 26],
+# [13, 29],
+# [13, 31],
+# [13, 46],
+# [14, 23],
+# [14, 25],
+# [14, 28],
+# [14, 30],
+# [14, 33],
+# [14, 46],
+# [15, 23],
+# [15, 24],
+# [15, 28],
+# [15, 29],
+# [15, 33],
+# [15, 46],
+# [16, 23],
+# [16, 26],
+# [16, 27],
+# [16, 31],
+# [16, 32],
+# [16, 46],
+# [17, 23],
+# [17, 25],
+# [17, 27],
+# [17, 34],
+# [17, 46],
+# [18, 23],
+# [18, 24],
+# [18, 26],
+# [18, 34],
+# [18, 46],
+# [19, 23],
+# [19, 25],
+# [19, 28],
+# [19, 34],
+# [19, 46],
+# [20, 23],
+# [20, 24],
+# [20, 28],
+# [20, 34],
+# [20, 46],
+# [21, 23],
+# [21, 26],
+# [21, 27],
+# [21, 34],
+# [21, 46],
+# [22, 23],
+# [22, 29],
+# [22, 30],
+# [22, 31],
+# [22, 32],
+# [22, 33],
+# [22, 46],
+# [23, 35],
+# [23, 36],
+# [23, 37],
+# [23, 38],
+# [23, 39],
+# [23, 40],
+# [23, 41],
+# [23, 42],
+# [23, 43],
+# [23, 44],
+# [23, 45],
+# [24, 47],
+# [25, 47],
+# [26, 47],
+# [27, 47],
+# [28, 47],
+# [29, 47],
+# [30, 47],
+# [31, 47],
+# [32, 47],
+# [33, 47],
+# [34, 47],
+# [35, 47],
+# [36, 47],
+# [37, 47],
+# [38, 47],
+# [39, 47],
+# [40, 47],
+# [41, 47],
+# [42, 47],
+# [43, 47],
+# [44, 47],
+# [45, 47],
+# [46, 47]
+# ]
+
+import pycosat
+from timeit import default_timer as timer
+
+# x(v, c) <--> vertex v is set to color c
+def x(v, c):
+ return c*N + v
+
+# x(1,0) = 1, x(2,0) = 2, ..., x(n-1, 0) = n-1, x(1,1) = n, ...
+
+cnf = []
+
+# Constraint 1: every vertex gets a color
+for v in range(1, N+1):
+ cnf.append([x(v, c) for c in range(COLORS)])
+
+# Constraint 2: if (u, v) is an edge, then u and v have different colors
+for u, v in EDGES:
+ for c in range(COLORS):
+ cnf.append([-x(u, c), -x(v, c)])
+
+# Constraint 3: every vertex has at most one color
+for v in range(1, N+1):
+ for c1 in range(COLORS):
+ for c2 in range(c1+1, COLORS):
+ cnf.append([-x(v, c1), -x(v, c1)])
+
+# Symmetry breaking -- try solving the second graph for K=5 with and without these constraints!
+cnf.append([x(1, 0)])
+cnf.append([x(2, 1)])
+
+t = timer()
+soln = pycosat.solve(cnf)
+time = timer()-t
+print(soln)
+print(f'{COLORS} colors took {time} sec') \ No newline at end of file
generated by cgit v1.2.3 (git 2.25.1) at 2025-12-06 08:25:49 +0000