ex2_3_1.py

# exercise 2.3.1
import importlib_resources
import numpy as np
import xlrd

filename = importlib_resources.files("dtuimldmtools").joinpath("data/iris.xls")
# Load xls sheet with data
doc = xlrd.open_workbook(filename).sheet_by_index(0)

# Extract attribute names
attributeNames = doc.row_values(0, 0, 4)

# Extract class names to python list,
# then encode with integers (dict)
classLabels = doc.col_values(4, 1, 151)
classNames = sorted(set(classLabels))
classDict = dict(zip(classNames, range(len(classNames))))

# Extract vector y, convert to NumPy matrix and transpose
y = np.array([classDict[value] for value in classLabels])

# Preallocate memory, then extract data to matrix X
X = np.empty((150, 4))
for i in range(4):
    X[:, i] = np.array(doc.col_values(i, 1, 151)).T

# Compute values of N, M and C.
N = len(y)
M = len(attributeNames)
C = len(classNames)

print("Ran Exercise 2.3.1 - loading the Iris data")