From 5da2296d4b108c88c742ce117d22e9526a7d8318 Mon Sep 17 00:00:00 2001
From: rasbt <se.raschka@me.com>
Date: Sun, 1 Dec 2013 01:43:08 -0500
Subject: [PATCH] numpy

---
 numpy_matrix.py | 36 ++++++++++++++++++++++++++++++++++++
 1 file changed, 36 insertions(+)
 create mode 100644 numpy_matrix.py

diff --git a/numpy_matrix.py b/numpy_matrix.py
new file mode 100644
index 0000000..06d5eb2
--- /dev/null
+++ b/numpy_matrix.py
@@ -0,0 +1,36 @@
+# numpy matrix operations
+# sr 12/01/2013
+
+import numpy
+
+ary1 = numpy.array([1,2,3,4,5])  # must be same type
+ary2 = numpy.zeros((3,4))        # 3x4 matrix consisiting of 0s 
+ary3 = numpy.ones((3,4))         # 3x4 matrix consisiting of 1s 
+ary4 = numpy.identity(3)         # 3x3 identity matrix
+ary5 = ary1.copy()               # make a copy of ary1
+
+item1 = ary3[0, 0]  # item in row1, column1
+
+ary2.shape  # tuple of dimensions. Here: (3,4)
+ary2.size   # number of elements. Here: 12
+
+
+ary2_t = ary2.transpose()    # transposes matrix
+
+ary2.ravel()     # makes an array linear (1-dimensional)
+                 # by concatenating rows
+ary2.reshape(2,6) # reshapes array (must have same dimensions)
+
+ary3[0:2, 0:3]   # submatrix of first 2 rows and first 3 columns 
+
+ary3 = ary3[[2,0,1]]    # re-arrange rows
+
+
+# element-wise operations
+
+ary1 + ary1
+ary1 * ary1
+numpy.dot(ary1, ary1)   # matrix/vector (dot) product
+
+numpy.sum(ary1)   # sums up all elements in the array
+numpy.mean(ary1)   # average of all elements in the array