Your code is too weak for PEP8. You lack DISCIPLINE

Author: pyarnold

Chapter2_MorePyMC/daft_plot.py

@@ -1,15 +1,14 @@
-#daft drawing for SMS example
+# daft drawing for SMS example
 import matplotlib.pyplot as plt
 
 
-
 try:
     import daft
 except ImportError:
     print "python library Daft required."
-    
 
-pgm = daft.PGM([9, 4], origin=[.5,.5])
+
+pgm = daft.PGM([9, 4], origin=[.5, .5])
 pgm.add_node(daft.Node("tau", r"$\tau$", 4.0, 3.5))
 pgm.add_node(daft.Node("alpha", r"$\alpha$", 6, 4.0))
 pgm.add_node(daft.Node("lambda1", r"$\lambda_1$", 5.5, 3.2,))
@@ -18,7 +17,6 @@
 pgm.add_node(daft.Node("obs", "obs", 5.0, 1.0, 1.2, observed=True))
 
 
-
 pgm.add_edge("tau", "lambda")
 pgm.add_edge("alpha", "lambda1")
 pgm.add_edge("alpha", "lambda2")
@@ -27,5 +25,5 @@
 
 pgm.add_edge("lambda", "obs")
 pgm.render()
-plt.figure( figsize=(12,5) )
-plt.show()
+plt.figure(figsize=(12, 5))
+plt.show()

Chapter2_MorePyMC/separation_plot.py

@@ -7,49 +7,44 @@
 import numpy as np
 
 
-
-def separation_plot( p, y, **kwargs ):
+def separation_plot(p, y, **kwargs):
     """
     This function creates a separation plot for logistic and probit classification. 
     See http://mdwardlab.com/sites/default/files/GreenhillWardSacks.pdf
-    
+
     p: The proportions/probabilities, can be a nxM matrix which represents M models.
     y: the 0-1 response variables.
-    
-    """    
+
+    """
     assert p.shape[0] == y.shape[0], "p.shape[0] != y.shape[0]"
     n = p.shape[0]
 
     try:
         M = p.shape[1]
     except:
-        p = p.reshape( n, 1 )
+        p = p.reshape(n, 1)
         M = p.shape[1]
 
-    #colors = np.array( ["#fdf2db", "#e44a32"] )
-    colors_bmh = np.array( ["#eeeeee", "#348ABD"] )
+    # colors = np.array( ["#fdf2db", "#e44a32"] )
+    colors_bmh = np.array(["#eeeeee", "#348ABD"])
 
+    fig = plt.figure()  # figsize = (8, 1.3*M) )
 
-    fig = plt.figure( )#figsize = (8, 1.3*M) )
-    
     for i in range(M):
-        ax = fig.add_subplot(M, 1, i+1)
-        ix = np.argsort( p[:,i] )
-        #plot the different bars
-        bars = ax.bar( np.arange(n), np.ones(n), width=1., 
-                color = colors_bmh[ y[ix].astype(int) ], 
-                edgecolor = 'none')
-        ax.plot( np.arange(n), p[ix,i], "k", 
-                linewidth = 1.,drawstyle="steps-post" )
-        #create expected value bar.
-        ax.vlines( [(1-p[ix,i]).sum()], [0], [1] )
-        #ax.grid(False)
-        #ax.axis('off')
-        plt.xlim( 0, n-1)
-        
+        ax = fig.add_subplot(M, 1, i + 1)
+        ix = np.argsort(p[:, i])
+        # plot the different bars
+        bars = ax.bar(np.arange(n), np.ones(n), width=1.,
+                      color=colors_bmh[y[ix].astype(int)],
+                      edgecolor='none')
+        ax.plot(np.arange(n), p[ix, i], "k",
+                linewidth=1., drawstyle="steps-post")
+        # create expected value bar.
+        ax.vlines([(1 - p[ix, i]).sum()], [0], [1])
+        # ax.grid(False)
+        # ax.axis('off')
+        plt.xlim(0, n - 1)
+
     plt.tight_layout()
-    
-    return
-    
 
-    
+    return

Chapter3_MCMC/github_pull.py

@@ -1,4 +1,4 @@
-#github data scrapper
+# github data scrapper
 
 """
 variables of interest:
@@ -21,69 +21,66 @@
 from requests import get
 
 
-
 MAX = 8000000
-today =  datetime.datetime.today()
+today = datetime.datetime.today()
 randint = np.random.randint
-N = 120 #sample size. 
-auth = ("username", "password" )
+N = 120  # sample size.
+auth = ("username", "password")
 
-language_mappings = {"Python": 0, "JavaScript": 1, "Ruby": 2, "Java":3, "Shell":4, "PHP":5}
+language_mappings = {
+    "Python": 0, "JavaScript": 1, "Ruby": 2, "Java": 3, "Shell": 4, "PHP": 5}
 
-#define data matrix: 
-X = np.zeros( (N , 12), dtype = int )
+# define data matrix:
+X = np.zeros((N, 12), dtype=int)
 
 for i in xrange(N):
     is_fork = True
     is_valid_language = False
-    
+
     while is_fork == True or is_valid_language == False:
         is_fork = True
         is_valid_language = False
-        
-        params = {"since":randint(0, MAX ) }
-        r = get("https://api.github.com/repositories", params = params, auth=auth )
-        results = loads( r.text )[0]
-        #im only interested in the first one, and if it is not a fork.
+
+        params = {"since": randint(0, MAX)}
+        r = get(
+            "https://api.github.com/repositories", params=params, auth=auth)
+        results = loads(r.text)[0]
+        # im only interested in the first one, and if it is not a fork.
         is_fork = results["fork"]
-        
-        r = get( results["url"], auth = auth)
-        
-        #check the language
-        repo_results = loads( r.text )
-        try: 
-            language_mappings[ repo_results["language" ] ]
+
+        r = get(results["url"], auth=auth)
+
+        # check the language
+        repo_results = loads(r.text)
+        try:
+            language_mappings[repo_results["language"]]
             is_valid_language = True
         except:
             pass
-        
-    
 
-    #languages 
-    X[ i, language_mappings[ repo_results["language" ] ] ] = 1
-    
-    #delta time
-    X[ i, 6] = ( today - datetime.datetime.strptime( repo_results["created_at"][:10], "%Y-%m-%d" ) ).days
-    
-    #haswiki
+    # languages
+    X[i, language_mappings[repo_results["language"]]] = 1
+
+    # delta time
+    X[i, 6] = (
+        today - datetime.datetime.strptime(repo_results["created_at"][:10], "%Y-%m-%d")).days
+
+    # haswiki
     X[i, 7] = repo_results["has_wiki"]
-    
-    #get user information
-    r = get( results["owner"]["url"] , auth = auth)
-    user_results = loads( r.text )
+
+    # get user information
+    r = get(results["owner"]["url"], auth=auth)
+    user_results = loads(r.text)
     X[i, 8] = user_results["following"]
     X[i, 9] = user_results["followers"]
-    
-    #get dep. data
+
+    # get dep. data
     X[i, 10] = repo_results["watchers_count"]
     X[i, 11] = repo_results["forks_count"]
-    print 
+    print
     print " -------------- "
-    print i, ": ", results["full_name"], repo_results["language" ], repo_results["watchers_count"], repo_results["forks_count"]
+    print i, ": ", results["full_name"], repo_results["language"], repo_results["watchers_count"], repo_results["forks_count"]
     print " -------------- "
-    print 
-    
-np.savetxt("data/github_data.csv", X, delimiter=",", fmt="%d" )
-    
-
+    print
 
+np.savetxt("data/github_data.csv", X, delimiter=",", fmt="%d")

Chapter4_TheGreatestTheoremNeverTold/top_pic_comments.py

@@ -7,20 +7,20 @@
 
 
 reddit = praw.Reddit("BayesianMethodsForHackers")
-subreddit  = reddit.get_subreddit( "pics" )
+subreddit = reddit.get_subreddit("pics")
 
 top_submissions = subreddit.get_top()
 
 
-n_pic = int( sys.argv[1] ) if sys.argv[1] else 1
+n_pic = int(sys.argv[1]) if sys.argv[1] else 1
 
 i = 0
 while i < n_pic:
     top_submission = top_submissions.next()
     while "i.imgur.com" not in top_submission.url:
-        #make sure it is linking to an image, not a webpage.
+        # make sure it is linking to an image, not a webpage.
         top_submission = top_submissions.next()
-    i+=1
+    i += 1
 
 print "Title of submission: \n", top_submission.title
 top_post_url = top_submission.url
@@ -31,33 +31,13 @@
 downvotes = []
 contents = []
 _all_comments = top_submission.comments
-all_comments=[]
+all_comments = []
 for comment in _all_comments:
-            try:
-                upvotes.append( comment.ups )
-                downvotes.append( comment.downs )
-                contents.append( comment.body )
-            except Exception as e:
-                continue
-                
-votes = np.array( [ upvotes, downvotes] ).T
-
-
-
-
-    
-    
-    
-    
-    
-    
-    
-    
-    
-    
-    
-    
-    
-
-    
-
+    try:
+        upvotes.append(comment.ups)
+        downvotes.append(comment.downs)
+        contents.append(comment.body)
+    except Exception as e:
+        continue
+
+votes = np.array([upvotes, downvotes]).T