def load_training_data():
training_data = {}
class_names = {}
# Read in the CSV file generated during training - comprised of the corpus (class in this example) name, the
# term (stemmed or not depending on user input) and the probability of the term occurring within the given class.
rows = fs.read_csv("bayes_training.csv")
# Iterate through each of the rows in the CSV file
for index, [category_name, term, probability] in enumerate(rows):
# Skip the header
if index > 0:
# Store the probabilities for each term
if category_name in training_data:
training_data[category_name][term] = probability;
else:
training_data[category_name] = {}
class_names[category_name] = category_name
return training_data, [name for name in class_names.keys()]
def load_training_data():
training_data = {}
class_names = {}
# Read in the CSV file generated during training - comprised of the corpus (class in this example) name, the
# term (stemmed or not depending on user input) and the probability of the term occurring within the given class.
rows = fs.read_csv("bayes_training.csv")
# Iterate through each of the rows in the CSV file
for index, [category_name, term, probability] in enumerate(rows):
# Skip the header
if index > 0:
# Store the probabilities for each term
if category_name in training_data:
training_data[category_name][term] = probability
else:
training_data[category_name] = {}
class_names[category_name] = category_name
return training_data, [name for name in class_names.keys()]
def marbles_and_jars(num_trials):
# read in the csv file of jars
rows = fs.read_csv("marbles.csv")
logging.debug("Read rows: " + str(rows))
jars = {}
headers = []
marble_picks = {}
# go through the rows and build a dictionary of jar_name => array of marble colors
for index, row in enumerate(rows):
# first row is just header data
if index == 0:
headers = row
else:
# go through each of the headers (these are columns)
for column_index, header in enumerate(headers):
# if the first column than it's the name of the jar - initialize the array to empty (no marbles)
if column_index == 0:
jars[row[0]] = []
else:
# each other column represents a number of marbles, the name of the marble is in the header
marble_color = header
# initialize the counters for picking marbles for the given color
marble_picks[marble_color] = 0
# set blank cells to 0, otherwise add the value in the cell
if len(row[column_index]) == 0:
num_marbles = 0
else:
num_marbles = int(row[column_index])
# expand an array of colors, 1 element for each num_marbles
jars[row[0]] += [marble_color] * num_marbles
logging.info("Jars: " + str(jars))
for i in range(0, num_trials):
# pick a random jar from all of the jars w/out taking the marbles into consideration
jar_names = jars.keys()
jar_name = jar_names[random.randint(0, len(jar_names) - 1)]
# now draw a single marble from all the marbles given that we selected a jar
marbles = jars[jar_name];
marble = marbles[random.randint(0, len(marbles) - 1)]
marble_picks[marble] += 1
logging.info("Marble picks : " + str(marble_picks))
# prepare the data for plotting
keys = []
data = []
for key, value in marble_picks.iteritems():
column_name = key + " (" + str(value) + ")"
keys.extend([column_name])
data.extend([value/float(num_trials)])
description_list = []
for jar_name, jar_marbles in jars.iteritems():
description_list.append(jar_name + "(" + str(len(jar_marbles)) + ")")
description = ", ".join(description_list)
# plot the data
charting.bar_chart("marbles.png",
[data],
"Marbles in Jars (" + str(num_trials) + ") - " + description,
keys,
"Probabilities",
None,
['#59799e'])
def marbles_and_jars(num_trials):
# read in the csv file of jars
rows = fs.read_csv("marbles.csv")
logging.debug("Read rows: " + str(rows))
jars = {}
headers = []
marble_picks = {}
# go through the rows and build a dictionary of jar_name => array of marble colors
for index, row in enumerate(rows):
# first row is just header data
if index == 0:
headers = row
else:
# go through each of the headers (these are columns)
for column_index, header in enumerate(headers):
# if the first column than it's the name of the jar - initialize the array to empty (no marbles)
if column_index == 0:
jars[row[0]] = []
else:
# each other column represents a number of marbles, the name of the marble is in the header
marble_color = header
# initialize the counters for picking marbles for the given color
marble_picks[marble_color] = 0
# set blank cells to 0, otherwise add the value in the cell
if len(row[column_index]) == 0:
num_marbles = 0
else:
num_marbles = int(row[column_index])
# expand an array of colors, 1 element for each num_marbles
jars[row[0]] += [marble_color] * num_marbles
logging.info("Jars: " + str(jars))
for i in range(0, num_trials):
# pick a random jar from all of the jars w/out taking the marbles into consideration
jar_names = jars.keys()
jar_name = jar_names[random.randint(0, len(jar_names) - 1)]
# now draw a single marble from all the marbles given that we selected a jar
marbles = jars[jar_name]
marble = marbles[random.randint(0, len(marbles) - 1)]
marble_picks[marble] += 1
logging.info("Marble picks : " + str(marble_picks))
# prepare the data for plotting
keys = []
data = []
for key, value in marble_picks.iteritems():
column_name = key + " (" + str(value) + ")"
keys.extend([column_name])
data.extend([value / float(num_trials)])
description_list = []
for jar_name, jar_marbles in jars.iteritems():
description_list.append(jar_name + "(" + str(len(jar_marbles)) + ")")
description = ", ".join(description_list)
# plot the data
charting.bar_chart(
"marbles.png", [data],
"Marbles in Jars (" + str(num_trials) + ") - " + description, keys,
"Probabilities", None, ['#59799e'])
