def makestats():
# nr_of_reads_list = [100]
# average_length_list = [100]
nr_of_reads_list = [100, 200, 300, 400, 500, 600, 700, 800, 900, 1000]
average_length_list = [100, 200, 300, 400, 500, 600, 700, 800, 900]
mydict = {}
with open("/run/media/andreas/INTENSO/fastas/artdata/stats.csv", "w") as f:
f.write("nr_of_reads; average_length; nr_of_edges; best_edge_list \n")
for nr_of_reads in nr_of_reads_list:
for average_length in average_length_list:
curr_DIR = DIR + "shuffled_{}_{}/".format(nr_of_reads, average_length)
os.chdir(curr_DIR)
filename = "shuffled_{}_{}".format(nr_of_reads, average_length)
(nr_best_edge_used, scores) = stats.make_stat(filename)
f.write("{}; {}; {}; {}\n".format(nr_of_reads, average_length, len(scores), nr_best_edge_used))
mydict[(nr_of_reads, average_length)] = nr_best_edge_used
mydict2 = {}
mydict2[(0, 0)] = [sum(x) for x in zip(*[y for key, y in mydict.items()])]
for average_length in average_length_list:
mydict2[(0, average_length)] = [sum(x) for x in zip(*[mydict[(x, average_length)] for x in nr_of_reads_list])]
for nr_of_reads in nr_of_reads_list:
mydict2[(nr_of_reads, 0)] = [sum(x) for x in zip(*[mydict[(nr_of_reads, x)] for x in average_length_list])]
mydict.update(mydict2)
return mydict
def plot_all_without_sum():
DIR = "/run/media/andreas/INTENSO/fastas/artdata/"
# nr_of_reads_list = [100]
# average_length_list = [300]
nr_of_reads_list = [100, 200, 300, 400, 500, 600, 700, 800, 900, 1000]
average_length_list = [100, 200, 300, 400, 500, 600, 700, 800, 900, 1000]
for nr_of_reads in nr_of_reads_list:
for average_length in average_length_list:
curr_DIR = DIR + "shuffled_{}_{}/".format(nr_of_reads, average_length)
os.chdir(curr_DIR)
filename = "shuffled_{}_{}".format(nr_of_reads, average_length)
(nr_best_edge_used, scores) = stats.make_stat(filename)
plt.plot(nr_best_edge_used, 'k', nr_best_edge_used, "bo")
plt.title(filename)
plt.grid(True)
plt.xticks(range(len(nr_best_edge_used)))
plt.yticks(range(0, max(nr_best_edge_used) + 10, 5))
plt.ylabel("How often is the n_th best edge used")
plt.xlabel("n-th best edge")
plt.savefig(filename + "_plot.pdf")
