Quick Primer on Numpy

Alluxia-F · Jul 6, 2017 · 6fc99dc · 6fc99dc
1 parent 444e44a
commit 6fc99dc
Showing 1 changed file with 119 additions and 0 deletions.
diff --git a/Chapter 3/7. Quick Primer on Numpy.ipynb b/Chapter 3/7. Quick Primer on Numpy.ipynb
@@ -270,6 +270,125 @@
     "# Regardless of wheth- er you're \"dotting\" vectors or matrices.  eir \"shape\"(number of rows and columns) must line up. \n",
     "#The col-umns on the \"le \" matrix must equal rows on the \"right\"."
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(2, 3)\n"
+     ]
+    }
+   ],
+   "source": [
+    "a=np.zeros((2,4))\n",
+    "b=np.zeros((4,3))\n",
+    "\n",
+    "c=a.dot(b)\n",
+    "\n",
+    "print c.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(2, 3)\n"
+     ]
+    }
+   ],
+   "source": [
+    "e=np.zeros((2,1))\n",
+    "f=np.zeros((1,3))\n",
+    "\n",
+    "g=e.dot(f)\n",
+    "print g.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[ 0.  0.  0.  0.  0.]\n",
+      " [ 0.  0.  0.  0.  0.]\n",
+      " [ 0.  0.  0.  0.  0.]\n",
+      " [ 0.  0.  0.  0.  0.]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "h=np.zeros((5,4)).T\n",
+    "print h"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(4, 6)\n"
+     ]
+    }
+   ],
+   "source": [
+    "i=np.zeros((5,6))\n",
+    "j=h.dot(i)\n",
+    "\n",
+    "print j.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ValueError",
+     "evalue": "shapes (5,4) and (5,6) not aligned: 4 (dim 1) != 5 (dim 0)",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-45-74e2469b12b9>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mzeros\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m6\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mj\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mh\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0;32mprint\u001b[0m \u001b[0mj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mValueError\u001b[0m: shapes (5,4) and (5,6) not aligned: 4 (dim 1) != 5 (dim 0)"
+     ]
+    }
+   ],
+   "source": [
+    "h=np.zeros((5,4))\n",
+    "i=np.zeros((5,6))\n",
+    "\n",
+    "j=h.dot(i)\n",
+    "\n",
+    "print j.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {