12 files changed, 106 insertions, 1 deletions
diff --git a/.gitignore b/.gitignore
index c32ce0d..7eee375 100644
--- a/.gitignore
+++ b/.gitignore
@@ -2,4 +2,4 @@
 .idea/bilibili_vlogs.iml
 .idea/modules.xml
 .idea/workspace.xml
-
+data/
+\ No newline at end of file
diff --git a/classic_or/__init__.py b/classic_or/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/classic_or/__init__.py
diff --git a/classic_or/kp/__init__.py b/classic_or/kp/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/classic_or/kp/__init__.py
diff --git a/classic_or/kp/simple_knapsack.py b/classic_or/kp/simple_knapsack.py
new file mode 100644
index 0000000..7244862
--- /dev/null
+++ b/classic_or/kp/simple_knapsack.py
@@ -0,0 +1,18 @@
+from pyomo.environ import *
+
+A = ['hammer', 'wrench', 'screwdriver', 'towel']
+b = {'hammer': 8, 'wrench': 3, 'screwdriver': 6, 'towel': 11}
+w = {'hammer': 5, 'wrench': 7, 'screwdriver': 4, 'towel': 3}
+
+W_max = 14
+model = ConcreteModel()
+model.x = Var(A, within=Binary)
+
+model.value = Objective(
+    expr=sum(b[i] * model.x[i] for i in A), sense=maximize)
+model.weight = Constraint(
+    expr=sum(w[i] * model.x[i] * model.x[i] for i in A) <= W_max)
+opt = SolverFactory('ipopt')
+result_obj = opt.solve(model, tee=True)
+
+model.pprint()
+\ No newline at end of file
diff --git a/data_science/__init__.py b/data_science/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/data_science/__init__.py
diff --git a/data_science/pandas_demo/__init__.py b/data_science/pandas_demo/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/data_science/pandas_demo/__init__.py
diff --git a/data_science/pandas_demo/groupby_demo.py b/data_science/pandas_demo/groupby_demo.py
new file mode 100644
index 0000000..d271010
--- /dev/null
+++ b/data_science/pandas_demo/groupby_demo.py
@@ -0,0 +1,11 @@
+import pandas as pd
+import numpy as np
+
+df = pd.DataFrame([('bird', 'Falconiformes', 389.0),
+                   ('bird', 'Psittaciformes', 24.0),
+                   ('mammal', 'Carnivora', 80.2),
+                   ('mammal', 'Primates', np.nan),
+                   ('mammal', 'Carnivora', 58)],
+                  index=['falcon', 'parrot', 'lion', 'monkey', 'leopard'],
+                  columns=('class', 'order', 'max_speed'))
+print(df)
diff --git a/nlp/__init__.py b/nlp/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/nlp/__init__.py
diff --git a/nlp/demo.py b/nlp/demo.py
new file mode 100644
index 0000000..9eb7154
--- /dev/null
+++ b/nlp/demo.py
@@ -0,0 +1,31 @@
+from scipy.optimize import minimize, LinearConstraint
+import numpy as np
+
+
+def test1():
+    fun = lambda x: x**2 + 2*x - 3
+    x0 = 1
+    res = minimize(fun, [x0], bounds=[[0, None]], )
+    print(res)
+
+
+def test2():
+    fun = lambda x: (x[0]-2)**2 + 4*(x[1]-1)**2
+    x0 = [0, 0]
+    cons = ({'type': 'ineq', 'fun': lambda x: 2 - x[0] - 2*x[1]})
+    res = minimize(fun, np.asarray(x0),
+                   method='slsqp',
+                   constraints=cons, options={'disp': True})
+    print(res)
+
+
+def test3():
+    fun = lambda x: -x[0]**2*x[1]
+    x0 = np.asarray([0, 0])
+    cons = ({'type': 'eq', 'fun': lambda x: x[0]**2+x[1]**2-1})
+    res = minimize(fun, x0, constraints=cons, options={'disp': True})
+    print(res)
+
+
+if __name__ == '__main__':
+    test3()
diff --git a/opt/__init__.py b/opt/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/opt/__init__.py
diff --git a/opt/dual/__init__.py b/opt/dual/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/opt/dual/__init__.py
diff --git a/opt/dual/dual_demo.py b/opt/dual/dual_demo.py
new file mode 100644
index 0000000..22eb8f0
--- /dev/null
+++ b/opt/dual/dual_demo.py
@@ -0,0 +1,45 @@
+from scipy import optimize
+from scipy.spatial import distance
+
+from ortools.sat.python import cp_model
+
+
+def obj(x1, x2):
+    return -(3*x1 + 4*x2)
+
+
+if __name__ == '__main__':
+
+    # 原始问题
+    c = [-3, -4]
+    A = [[1/2, 2], [3, 1]]
+    b = [30, 25]
+
+    res = optimize.linprog(c, A_ub=A, b_ub=b, bounds=[[0, None], [0, None]])
+    print(res)
+
+    print('=============')
+
+    c = [30, 25]
+    A = [[-1/2, -3], [-2, -1]]
+    b = [-3, -4]
+    res = optimize.linprog(c, A_ub=A, b_ub=b, bounds=[[0, None], [0, None]])
+    print(res)
+    print('=============')
+
+    c = [5, 1]
+    A = [[-2, -1], [-1, -1], [-2, -20]]
+    b = [-6, -4, -21]
+    res = optimize.linprog(c, A_ub=A, b_ub=b, bounds=[[0, None], [0, None]])
+    print(res)
+    print('=============')
+
+    c = [-3, -5]
+    A = [[1, 3], [3, 4]]
+    b = [60, 120]
+    res = optimize.linprog(c, A_ub=A, b_ub=b, bounds=[[10, None], [0, None]])
+    print(res)
+    print('=============')
+
+    model = cp_model.CpModel()
+    model.AddBoolOr()