The solutions

README.md

@@ -1 +1 @@
-# Week8_Lab
+# Week8_Lab Solutions

aNewFolder/fileinfolder

@@ -0,0 +1,3 @@
+#newfloder with a file in it
+
+There is some words in the file.

ccuboid.py

@@ -0,0 +1,34 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Fri May 20 12:31:56 2016
+
+@author: Mebius
+"""
+import random
+from cuboid import Cuboid
+
+class CCuboid(Cuboid):
+    def __init__(self, x,y,z, color ):
+        Cuboid.__init__(self, x , y , z )
+        self.color = color
+
+    def set_color(self, color):
+        self.color = color
+
+    def get_color(self):
+        return self.color
+
+    def __str__(self):
+        a_str = super().__str__() + \
+                ', Color: ' + str(self.get_color())
+        return a_str     
+
+
+if __name__ == "__main__":
+
+    x=random.randint(1,20)
+    y=random.randint(1,20)
+    z=random.randint(1,20)
+    color= input("Input your color: ")
+    a = CCuboid(x,y,z,color)
+    print("The color of the cuboid is", a.get_color())

cuboid_student.py → cuboid.py

@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 """
-Created on Fri May 20 12:29:33 2016
+Created on Thu May 19 13:07:12 2016
 
 @author: Mebius
 """
@@ -12,13 +12,12 @@ def __init__(self,x,y,z):
         self.x=x
         self.y=y
         self.z=z
-
-        #implement this!
+
     def get_area(self):
-        pass
-        #implement this!
+        return 2*self.x*self.y +2*self.x*self.z +2*self.z*self.y
+
     def get_volume(self):
-        pass
+        return self.x*self.y*self.z
 
     def __str__(self):
         c_str = 'Length: ' + str(self.x) + \
@@ -30,27 +29,28 @@ def __str__(self):
 
 class CCuboid(Cuboid):
     def __init__(self, x,y,z, color ):
-            Cuboid.__init__(self, x , y , z )
-            pass
+        Cuboid.__init__(self, x , y , z )
+        #super().__init__(x, y, z)
+        self.color = color
 
     def set_color(self, color):
-        pass
+        self.color = color
 
     def get_color(self):
-        pass
+        return self.color
 
     def __str__(self):
-        a_str = super().__str__() + ', Color: ' + str(self.get_color())
+        a_str = super().__str__() + \
+                ', Color: ' + str(self.get_color())
         return a_str    
 
 if __name__ == "__main__":
 
-    x=1
-    y=2
-    z=3
-
-    c = Cuboid(x,y,z)
-    print(c)
+    x=random.randint(1,20)
+    y=random.randint(1,20)
+    z=random.randint(1,20)
+    #c = Cuboid(x,y,z)
+    #print(c)
 
     color= input("Input your color: ")
 

dice_student.py → dice.py

@@ -1,40 +1,44 @@
-# -*- coding: utf-8 -*-
-"""
-Created on Sat Mar 19 15:23:36 2016
-
-@author: zhengzhang
-"""
-import random
-import dice_helper
-
-class Dice:
-    def __init__(self, sides=2):
-        self.n_sides = sides
-        self.bounds = [x/sides for x in range(0, sides)]
-        self.bounds.append(1.0)
-        self.point = None
-        self.lands = 0
-
-    def set_bounds(self, r):
-        assert len(r) == len(self.bounds)
-        self.bounds = r
-
-    def get_bounds(self):
-        return self.bounds
-
-    def roll(self):
-# replace the following line with you code
-# it should set self.point as a random var in [0, 1]
-# return which side the dice lands on
-        return dice_helper.roll(self)
-
-if __name__ == "__main__":       
-    d = Dice()
-    ''' make a biased dice '''
-    d.set_bounds([0.0, 0.3, 1.0])  
-    ones = 0
-    num_rolls = 1000
-    for i in range(num_rolls):
-        ones += d.roll()
-    print("the dice is:", ones/float(num_rolls))
+# -*- coding: utf-8 -*-
+"""
+Created on Thu Oct 27 13:42:25 2016
+
+@author: Mebius
+"""
+
+import random
+
+class Dice:
+    def __init__(self, sides=2):
+        self.n_sides = sides
+        self.bounds = [x/sides for x in range(0, sides)]
+        self.bounds.append(1.0)
+        self.point = None
+        self.lands = 0
+
+    def set_bounds(self, r):
+        assert len(r) == len(self.bounds)
+        self.bounds = r
+
+    def get_bounds(self):
+        return self.bounds
+
+    def roll(self):
+        self.point = random.uniform(0, 1)
+        for i in range(self.n_sides):
+            if self.point > self.bounds[i] \
+            and self.point <= self.bounds[i+1]:
+                break
+        self.lands = i
+        return self.lands
+
+
+if __name__ == "__main__":       
+    d = Dice()
+    ''' make a biased dice '''
+    d.set_bounds([0.0, 0.3, 1.0])  
+    ones = 0
+    num_rolls = 10
+    for i in range(num_rolls):
+        ones += d.roll()
+    print("the dice is:", ones/float(num_rolls))
 

random_walk_student.py → random_walk.py

@@ -1,78 +1,80 @@
-# -*- coding: utf-8 -*-
-"""
-Created on Sat Mar 19 16:14:38 2016
-
-@author: zhengzhang
-"""
-import dice_student
-import math
-import matplotlib.pyplot as plt
-
-import random_walk_helper
-
-class Walker:
-    def __init__(self, directions=4, num_steps=10):
-        self.dice = dice_student.Dice(directions)
-        self.num_steps = num_steps
-        self.x_pos = 0
-        self.y_pos = 0
-
-    def set_bounds(self, r):
-        self.dice.set_bounds(r)
-
-    def run(self):
-# replace the following line with you code
-# roll the dice, according to the outcome:
-# - go left one step (x -= 1)
-# - go right one step (x += 1)
-# - go north one step (y += 1)
-# - go south one step (y -= 1)
-        random_walk_helper.run(self)
-
-    def get_position(self):
-        return self.x_pos, self.y_pos
-
-    def get_dist(self):
-
-        def comp_dist(a, b):
-            assert len(a) == len(b)
-            d = 0
-            for i in range(len(a)):
-                d += (a[i] - b[i]) ** 2
-            return math.sqrt(d)
-
-        return comp_dist([0, 0], [self.x_pos, self.y_pos])
-
-if __name__ == "__main__":
-    one_walker = Walker()
-    one_walker.run()
-    print("one walk", one_walker.get_dist())
-
-    num_steps = 100
-    total_walks = 2000
-    result = []
-    x_pos_list = []
-    y_pos_list = []
-
-    weights = [0.0, 0.25, 0.5, 0.75, 1.0]
-
-    for i in range(total_walks):
-        one_walker = Walker(num_steps=num_steps)
-        one_walker.set_bounds(weights)
-        one_walker.run()
-        x, y = one_walker.get_position()
-        x_pos_list.append(x)
-        y_pos_list.append(y)
-        result.append(one_walker.get_dist())
-
-    print("mean distance:", sum(result)/total_walks)
-    plt.subplot(2, 1, 1)
-    plt.hist(result)
-    plt.title('position distribution')
-
-    plt.subplot(2, 1, 2)
-    plt.title('2D distribution')
-    plt.scatter(x_pos_list, y_pos_list)
-
-    plt.show()
+# -*- coding: utf-8 -*-
+"""
+Created on Thu Oct 27 13:41:17 2016
+
+@author: Mebius
+"""
+
+import dice
+import math
+import matplotlib.pyplot as plt
+
+class Walker:
+    def __init__(self, directions=4, num_steps=10):
+        self.dice = dice.Dice(directions)
+        self.num_steps = num_steps
+        self.x_pos = 0
+        self.y_pos = 0
+
+    def set_bounds(self, r):
+        self.dice.set_bounds(r)
+
+    def run(self):
+        for i in range(self.num_steps):
+            direction = self.dice.roll()
+            if direction == 0:
+                self.x_pos += 1
+            elif direction == 1:
+                self.x_pos -= 1
+            elif direction == 2:
+                self.y_pos += 1
+            elif direction == 3:
+                self.y_pos -= 1
+
+    def get_position(self):
+        return self.x_pos, self.y_pos
+
+    def get_dist(self):
+
+        def comp_dist(a, b):
+            assert len(a) == len(b)
+            d = 0
+            for i in range(len(a)):
+                d += (a[i] - b[i]) ** 2
+            return math.sqrt(d)
+
+        return comp_dist([0, 0], [self.x_pos, self.y_pos])
+
+if __name__ == "__main__":
+    one_walker = Walker()
+    one_walker.run()
+    print("one walk", one_walker.get_dist())
+
+    num_steps = 100
+    total_walks = 2000
+    result = []
+    x_pos_list = []
+    y_pos_list = []
+
+    weights = [0.0, 0.25, 0.5, 0.75, 1.0]
+
+    for i in range(total_walks):
+        one_walker = Walker(num_steps=num_steps)
+        one_walker.set_bounds(weights)
+        one_walker.run()
+        x, y = one_walker.get_position()
+        x_pos_list.append(x)
+        y_pos_list.append(y)
+        result.append(one_walker.get_dist())
+
+    print("mean distance:", sum(result)/total_walks)
+    plt.subplot(2, 1, 1)
+    plt.hist(result)
+    plt.title('position distribution')
+
+    plt.subplot(2, 1, 2)
+    plt.title('2D distribution')
+    plt.scatter(x_pos_list, y_pos_list)
+
+    plt.show()