read the RELEASE NOTES please

tools/karoo_data_sort.py

@@ -1,67 +0,0 @@
-# Karoo Dataset Builder
-# by Kai Staats, MSc UCT / AIMS and Arun Kumar, PhD
-# version 0.9.1.9
-
-import sys
-import numpy as np
-
-np.set_printoptions(linewidth = 320) # set the terminal to print 320 characters before line-wrapping in order to view Trees
-
-'''
-In machine learning, it is often the case that your engaged dataset is derived from a larger parent. In constructing 
-the subset, if we grab a series of datapoints (rows in a .csv) from the larger dataset in sequential order, only from 
-the top, middle, or bottom, we will likely bias the new dataset and incorrectly train the machine learning algorithm. 
-Therefore, it is imperative that we engage a random function, guided only by the number of data points for each class.
-
-This script can be used *before* karoo_normalise.py, and assumes no header has yet been applied to the .csv.
-'''
-
-### USER INTERACTION ###
-if len(sys.argv) == 1: print '\n\t\033[31mERROR! You have not assigned an input file. Try again ...\033[0;0m'; sys.exit()
-elif len(sys.argv) > 2: print '\n\t\033[31mERROR! You have assigned too many command line arguments. Try again ...\033[0;0m'; sys.exit()
-else: filename = sys.argv[1]
-
-#n = range(1,101)
-#while True:
-#	try:
-#		labels = raw_input('\n\tEnter number of unique class labels, or 0 for a regression dataset (default 2): ')
-#		if labels not in str(n) and labels not in '': raise ValueError()
-#		# if labels == '0': labels = 1; break
-#		labels = labels or 2; labels = int(labels); break
-#	except ValueError: print '\n\t\033[32mEnter a number from 0 including 100. Try again ...\033[0;0m'
-
-n = range(10,10001)
-while True:
-	try:
-		samples = raw_input('\n\tEnter number of desired datapoints per class (default 100): ')
-		if samples not in str(n) and samples not in '': raise ValueError()
-		if samples == '0': samples = 10; break
-		samples = samples or 100; samples = int(samples); break
-	except ValueError: print '\n\t\033[32mEnter a number from 10 including 10000. Try again ...\033[0;0m'
-
-
-### LOAD THE ORIGINAL DATASET ###
-print '\n\t\033[36m\n\tLoading dataset:', filename, '\033[0;0m\n'
-data = np.loadtxt(filename, delimiter = ',') # load data
-data_sort = np.empty(shape = [0, data.shape[1]]) # build an empty array of the proper dimensions
-
-
-### SORT DATA by LABEL ###
-labels = len(np.unique(data[:,-1]))
-
-for label in range(labels):
-	data_list = np.where(data[:,-1] == label) # build a list of all rows which end in the current label
-
-	data_select = np.random.choice(data_list[0], samples, replace = False) # select user defined 'samples' from list
-	print data_select
-	
-	data_sort = np.append(data_sort, data[data_select], axis = 0)
-
-
-### SAVE THE SORTED DATASET ###
-file_tmp = filename.split('.')[0]
-np.savetxt(file_tmp + '-SORT.csv', data_sort, delimiter = ',')
-
-print '\n\t\033[36mThe sorted dataset has been written to the file:', file_tmp + '-SORT.csv', '\033[0;0m'
-
-

tools/karoo_sort.py

@@ -1,6 +1,6 @@
 # Karoo Dataset Builder
 # by Kai Staats, MSc UCT / AIMS and Arun Kumar, PhD
-# version 0.9.2.0
+# version 0.9.1.9
 
 import sys
 import numpy as np