Downloaded a script from the iPython parallell computing examples in …

…the iPython documentation. The script calculates some statistics about the digits of Pi (up to 150 million, I think)

pidigits.py

@@ -0,0 +1,162 @@
+"""Compute statistics on the digits of pi.
+
+This uses precomputed digits of pi from the website
+of Professor Yasumasa Kanada at the University of
+Tokoyo: http://www.super-computing.org/
+
+Currently, there are only functions to read the
+.txt (non-compressed, non-binary) files, but adding
+support for compression and binary files would be
+straightforward.
+
+This focuses on computing the number of times that
+all 1, 2, n digits sequences occur in the digits of pi.
+If the digits of pi are truly random, these frequencies
+should be equal.
+"""
+
+# Import statements
+from __future__ import division, with_statement
+
+import numpy as np
+from matplotlib import pyplot as plt
+
+try : #python2
+    from urllib import urlretrieve
+except ImportError : #python3
+    from urllib.request import urlretrieve
+
+	# Top-level functions
+
+def fetch_pi_file(filename):
+    """This will download a segment of pi from super-computing.org
+    if the file is not already present.
+    """
+    import os, urllib
+    ftpdir="ftp://pi.super-computing.org/.2/pi200m/"
+    if os.path.exists(filename):
+        # we already have it
+        return
+    else:
+        # download it
+        urlretrieve(ftpdir+filename,filename)
+
+def compute_one_digit_freqs(filename):
+    """
+    Read digits of pi from a file and compute the 1 digit frequencies.
+    """
+    d = txt_file_to_digits(filename)
+    freqs = one_digit_freqs(d)
+    return freqs
+
+def compute_two_digit_freqs(filename):
+    """
+    Read digits of pi from a file and compute the 2 digit frequencies.
+    """
+    d = txt_file_to_digits(filename)
+    freqs = two_digit_freqs(d)
+    return freqs
+
+def reduce_freqs(freqlist):
+    """
+    Add up a list of freq counts to get the total counts.
+    """
+    allfreqs = np.zeros_like(freqlist[0])
+    for f in freqlist:
+        allfreqs += f
+    return allfreqs
+
+def compute_n_digit_freqs(filename, n):
+    """
+    Read digits of pi from a file and compute the n digit frequencies.
+    """
+    d = txt_file_to_digits(filename)
+    freqs = n_digit_freqs(d, n)
+    return freqs
+
+# Read digits from a txt file
+
+def txt_file_to_digits(filename, the_type=str):
+    """
+    Yield the digits of pi read from a .txt file.
+    """
+    with open(filename, 'r') as f:
+        for line in f.readlines():
+            for c in line:
+                if c != '\n' and c!= ' ':
+                    yield the_type(c)
+
+# Actual counting functions
+
+def one_digit_freqs(digits, normalize=False):
+    """
+    Consume digits of pi and compute 1 digit freq. counts.
+    """
+    freqs = np.zeros(10, dtype='i4')
+    for d in digits:
+        freqs[int(d)] += 1
+    if normalize:
+        freqs = freqs/freqs.sum()
+    return freqs
+
+def two_digit_freqs(digits, normalize=False):
+    """
+    Consume digits of pi and compute 2 digits freq. counts.
+    """
+    freqs = np.zeros(100, dtype='i4')
+    last = next(digits)
+    this = next(digits)
+    for d in digits:
+        index = int(last + this)
+        freqs[index] += 1
+        last = this
+        this = d
+    if normalize:
+        freqs = freqs/freqs.sum()
+    return freqs
+
+def n_digit_freqs(digits, n, normalize=False):
+    """
+    Consume digits of pi and compute n digits freq. counts.
+
+    This should only be used for 1-6 digits.
+    """
+    freqs = np.zeros(pow(10,n), dtype='i4')
+    current = np.zeros(n, dtype=int)
+    for i in range(n):
+        current[i] = next(digits)
+    for d in digits:
+        index = int(''.join(map(str, current)))
+        freqs[index] += 1
+        current[0:-1] = current[1:]
+        current[-1] = d
+    if normalize:
+        freqs = freqs/freqs.sum()
+    return freqs
+
+# Plotting functions
+
+def plot_two_digit_freqs(f2):
+    """
+    Plot two digits frequency counts using matplotlib.
+    """
+    f2_copy = f2.copy()
+    f2_copy.shape = (10,10)
+    ax = plt.matshow(f2_copy)
+    plt.colorbar()
+    for i in range(10):
+        for j in range(10):
+            plt.text(i-0.2, j+0.2, str(j)+str(i))
+    plt.ylabel('First digit')
+    plt.xlabel('Second digit')
+    return ax
+
+def plot_one_digit_freqs(f1):
+    """
+    Plot one digit frequency counts using matplotlib.
+    """
+    ax = plt.plot(f1,'bo-')
+    plt.title('Single digit counts in pi')
+    plt.xlabel('Digit')
+    plt.ylabel('Count')
+    return ax