SR :adding chapter 8 file and updating scalar multiplication for mat.py

Author: sushmit

.DS_Store

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "#col_label_list = sorted(rowlist[0].D, key=hash)\n",
+    "from vec import  *\n",
+    "from mat import *\n",
+    "from matutil import *\n",
+    "from echelon import *\n",
+    "from vecutil import *\n",
+    "from GF2 import one\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "         0\n",
+      "     -----\n",
+      " 0  |    1\n",
+      " 1  |  -89\n",
+      " 2  |    0\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "def projection_matrix(v):\n",
+    "    v_norm = v * v\n",
+    "    return 0\n",
+    "a0 = list2vec([1,-89,0])\n",
+    "dict_a = {}\n",
+    "dict_a[0] = a0\n",
+    "print(coldict2mat(dict_a))"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.5.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}

.ipynb_checkpoints/Chapter8-checkpoint.ipynb

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+# Copyright 2013 Philip N. Klein
+from orthonormalization import aug_orthonormalize
+from dictutil import dict2list, list2dict
+from matutil import mat2coldict, coldict2mat
+
+def factor(A):
+    col_labels = sorted(A.D[1], key=repr)
+    Acols = dict2list(mat2coldict(A),col_labels)
+    Qlist, Rlist = aug_orthonormalize(Acols)
+    #Now make Mats
+    Q = coldict2mat(Qlist)
+    R = coldict2mat(list2dict(Rlist, col_labels))
+    return Q,R

Chapter8.ipynb

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+age	height
+18	76.1
+19	77
+20	78.1
+21	78.2
+22	78.8
+23	79.7
+24	79.9
+25	81.1
+26	81.2
+27	81.8
+28	82.8
+29	83.5

Dali.png

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+# Copyright 2013 Philip N. Klein
+from vec import Vec
+from matutil import rowdict2mat
+
+def read_training_data(fname, D=None):
+    """Given a file in appropriate format, and given a set D of features,
+    returns the pair (A, b) consisting of
+    a P-by-D matrix A and a P-vector b,
+    where P is a set of patient identification integers (IDs).
+
+    For each patient ID p,
+      - row p of A is the D-vector describing patient p's tissue sample,
+      - entry p of b is +1 if patient p's tissue is malignant, and -1 if it is benign.
+
+    The set D of features must be a subset of the features in the data (see text).
+    """
+    file = open(fname)
+    params = ["radius", "texture", "perimeter","area","smoothness","compactness","concavity","concave points","symmetry","fractal dimension"];
+    stats = ["(mean)", "(stderr)", "(worst)"]
+    feature_labels = set([y+x for x in stats for y in params])
+    feature_map = {params[i]+stats[j]:j*len(params)+i for i in range(len(params)) for j in range(len(stats))}
+    if D is None: D = feature_labels
+    feature_vectors = {}
+    patient_diagnoses = {}
+    for line in file:
+        row = line.split(",")
+        patient_ID = int(row[0])
+        patient_diagnoses[patient_ID] = -1 if row[1]=='B' else +1
+        feature_vectors[patient_ID] = Vec(D, {f:float(row[feature_map[f]+2]) for f in D})
+    return rowdict2mat(feature_vectors), Vec(set(patient_diagnoses.keys()), patient_diagnoses)

QR.py

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+# Copyright 2013 Philip N. Klein
+def FFT(w, s):
+    """"
+    w should be a complex numbers such that w^n = 1
+    where n is the number of elements in the list s
+    of numbers.
+    """
+    n = len(s)
+    if n==1: return [s[0]]
+    f0 = FFT(w*w, [s[i] for i in range(n) if i % 2 == 0])
+    f1 = FFT(w*w, [s[i] for i in range(n) if i % 2 == 1])
+    return [f0[j]+w**j*f1[j] for j in range(n//2)] + [f0[j]-w**(j+n//2)*f1[j] for j in range(n//2)]