def plot_single_cluster(clusters_file_path, cluster_number, average=False):
clusters_file = open(clusters_file_path, "r")
# Create temporary file for plot data.
plot_data_tmpfile_path = tempfile.mkstemp()[1]
plot_data_tmpfile = open(plot_data_tmpfile_path, "w")
# Start searching for cluster we want to plot in file
# with clusters.
found_cluster = False
line = clusters_file.readline().strip()
while line != "":
if line.isdigit() == True and int(line) == cluster_number:
found_cluster = True
if average:
# We will now average price vectors from all
# companies in this group.
company_name = clusters_file.readline().strip()
vec = utils.make_prices_vec_by_company(data, company_name)
company_number = 1
company_name = clusters_file.readline().strip()
while not company_name.isdigit() and company_name != "":
vec2 = utils.make_prices_vec_by_company(data, company_name)
company_number += 1
vec = [x+y for x,y in zip(vec,vec2)]
company_name = clusters_file.readline().strip()
vec = [ (x/company_number) for x in vec ]
map(lambda p: plot_data_tmpfile.write(str(p) + "\n"), vec)
plot_data_tmpfile.write("\n\n")
else:
# Ok, we've found our cluster. Now we iterate companies in
# this group and write their prices vectors seperated by two
# blank lines to one file (used as input for gnuplot).
company_name = clusters_file.readline().strip()
while not company_name.isdigit() and company_name != "":
vec = utils.make_prices_vec_by_company(data, company_name)
map(lambda p: plot_data_tmpfile.write(str(p) + "\n"), vec)
plot_data_tmpfile.write("\n\n")
company_name = clusters_file.readline().strip()
# Great, we're done, we wanted data for only one cluster,
# so break here.
break
line = clusters_file.readline().strip()
# Close this file here, we'll need file buffers to be flushed for this
# file before running gnuplot.
plot_data_tmpfile.close()
clusters_file.close()
return found_cluster, plot_data_tmpfile_path
def testMakePricesVecByCompany(self): """Obtaining prices vector by company name.""" ambra_prices_vec = utils.make_prices_vec_by_company(self.data1, "AMBRA") self.assertEqual(ambra_prices_vec, [9.5, 9, 10.5, 20.5]) tvn_prices_vec = utils.make_prices_vec_by_company(self.data1, "TVN") self.assertEqual(tvn_prices_vec, [9.5, 16.5, 17.5, 18.5])
