#!/usr/bin/env python
# coding: utf-8

# ## Math
# - https://www.tensorflow.org/api_docs/python/math_ops/

# ### 0. Loading TF and Fixtures

# In[2]:


import tensorflow as tf
sess = tf.InteractiveSession()


# In[3]:


def namestr(obj, namespace):
    return [name for name in namespace if namespace[name] is obj][0]


# In[5]:


m1 = tf.constant(value = [[1., 2.]])
m2 = tf.constant(value = [[3.],[4.]])
m3 = tf.constant(value = [[[1., 2., 3.], [4., 5., 6.]]])
m4 = tf.constant(value = [[[1., 2., 3.], [4., 5., 6.]], [[7., 8., 9.] ,[10., 11., 12.]]])
m5 = tf.constant(value = [[[1., 2.], [3., 4.]]])
m6 = tf.constant(value = [[3., 4., 5.]])

def printFixture(isShapeOut, tensorMatrixList):
    print "======Fixture======="
    
    for m in tensorMatrixList:
        print "Tensor Matrix - " + namestr(m, globals())
        if (isShapeOut):
            print "Shape:", m.get_shape()
        print m.eval()
        print
        
    print "===================="

printFixture(True, (m1, m2, m3, m4, m5, m6))    


# ### 1. Arithmetic Operators

# #### - tf.add(x, y, name=None)
# - https://www.tensorflow.org/versions/master/api_docs/python/math_ops/arithmetic_operators#add

# In[4]:


printFixture(True, (m1, m2))
r1 = tf.add(m1, m2)
print r1.eval()
r2 = m1 + m2
print r2.eval()


# #### - tf.multiply(x, y, name=None)
# - https://www.tensorflow.org/api_docs/python/tf/multiply

# In[5]:


printFixture(True, (m1, m2))
r1 = tf.multiply(m1, m2)
print r1.eval()
r2 = tf.multiply(m1, m2)
print r2.eval()
r3 = m1 * m2
print r3.eval()


# ### 3. Matrix Math Functions

# #### - tf.matmul(a, b, transpose_a=False, transpose_b=False, adjoint_a=False, adjoint_b=False, a_is_sparse=False, b_is_sparse=False, name=None)
# - https://www.tensorflow.org/api_docs/python/tf/matmul

# In[6]:


printFixture(True, (m1, m2))
r1 = tf.matmul(a = m1, b = m2)   #(1, 2) x (2, 1)
print r1.eval()
r2 = tf.matmul(a = m2, b = m1)   #(2, 1) x (1, 2)
print r2.eval()