def plot_clusters_all(self):
"""
plot clusters for all regions of japan
you can select the number of clusters and the time period you want
"""
# auxiliar classes that we'll be needed
draw = Draw()
cat = Catalog()
# information relative to the regions
BOUNDS = 0
ZOOM_INDEX = 1
ZOOM_VALUE = 9
info = {}
info["kanto"] = [cat.get_kanto_bounds(), ZOOM_VALUE]
#info["kansai"] = [cat.get_kansai_bounds(), ZOOM_VALUE]
#info["tohoku"] = [cat.get_tohoku_bounds(), ZOOM_VALUE]
#info["east_japan"] = [cat.get_east_japan_bounds(), ZOOM_VALUE]
# list containing the number of clusters to plot and the time period to consider
num_cluster = [10]
time_period = [[0.0, 12 * 366 * 24.0 * 3600.0]]
# get all valid combinations
combinations = list(itertools.product(info, num_cluster, time_period))
REGION_IND = 0
CLUSTER_IND = 1
TIME_IND = 2
# iterate through all combinations
for comb in combinations:
# get region
region = comb[REGION_IND]
# folder we save the results into
folder = '../images/single_link/'
# obtain array of quakes
path = '../results/single_link/declustered_array_' + region
quakes = pickle.load(open(path, 'rb'))
# plot background for current region
draw.plot_quakes_coast_slc(quakes, comb[TIME_IND], num_clusters = comb[CLUSTER_IND])
call(["mv", "temp.png", folder + region + "_back_coast-1.png"])
input("Edit the image and then press Enter")
# plot cluster for the current data we have
self.plot_clusters(quakes, comb[CLUSTER_IND], comb[TIME_IND], folder + region +"_back_coast-1.png")
# save it in the correct format and do cleaning
call(["mv", "temp.png", folder + region + "_clusters_coast.png"])
