def write_frequent_itemsets(input_path, output_path, support=-10, min_set_size=1, max_set_size=3):
# parse transactions from file
transactions = parser.parse_csv_to_mat(input_path)
# mine frequent itemsets
frequent_itemsets = fpgrowth(transactions, supp=support, min=min_set_size, max=max_set_size)
# write result to file
with open(output_path, 'w+') as fd:
pickle.dump(frequent_itemsets, fd)
def item_stats():
"""
Plot stats on frequent itemset occurences
"""
transactions = parser.parse_csv_to_mat('/Users/ahkj/Dropbox/SAAS/data/csv/sample-big/customers.txt')
frequent_itemsets = fpgrowth(transactions, supp=0.0005, max=3 )
frequencies_1=[]
frequencies_2 =[]
frequencies_3 = []
for frequent_itemset in frequent_itemsets:
if len(frequent_itemset[0])==1:
frequencies_1.append(frequent_itemset[1][0])
elif len(frequent_itemset[0])==2:
frequencies_2.append(frequent_itemset[1][0])
elif len(frequent_itemset[0])==3:
frequencies_3.append(frequent_itemset[1][0])
frequencies_counts_1 = [0 for x in range(max(frequencies_1)+1)]
frequencies_counts_2 = [0 for x in range(max(frequencies_2)+1)]
frequencies_counts_3 = [0 for x in range(max(frequencies_3)+1)]
for frequencie in frequencies_1:
frequencies_counts_1[frequencie]+=1
for frequencie in frequencies_2:
frequencies_counts_2[frequencie]+=1
for frequencie in frequencies_3:
frequencies_counts_3[frequencie]+=1
cleaned_ys_1 = frequencies_counts_1[0:30]
xs_1 =[x for x in range(len(cleaned_ys_1))]
plt.scatter(xs_1, cleaned_ys_1)
plot_item_stats(xs_1, cleaned_ys_1, '../tmp/plots/item_stats/signletons.png')
cleaned_ys_2 = frequencies_counts_2[0:30]
xs_2 =[x for x in range(len(cleaned_ys_2))]
plot_item_stats(xs_2, cleaned_ys_2, '../tmp/plots/item_stats/pairs.png')
cleaned_ys_3 = frequencies_counts_3[0:30]
xs_3 =[x for x in range(len(cleaned_ys_3))]
plot_item_stats(xs_3, cleaned_ys_3, '../tmp/plots/item_stats/triples.png')
# item_stats()
