def diverge_point_plot34(n):
p1 = 0.001
p2 = 0.01
p3 = 0.1
ax = plt.subplot(111)
e1_xlist = list()
e1_ylist = list()
for n_item in range(10, n, 200):
print n_item
e1_xlist.append(n_item)
e1_ylist.append( (motif_expectations.approx4(n_item, p1) - motif_expectations.approx1(n_item, p1))/(p1 *n_item* (n_item-1)))
e2_xlist = list()
e2_ylist = list()
for n_item in range(10, n, 200):
e2_xlist.append(n_item)
e2_ylist.append( (motif_expectations.approx4(n_item, p2) - motif_expectations.approx1(n_item, p2))/(p2 *n_item* (n_item-1)))
e3_xlist = list()
e3_ylist = list()
for n_item in range(10, n, 200):
e3_xlist.append(n_item)
e3_ylist.append( (motif_expectations.approx4(n_item, p3) - motif_expectations.approx1(n_item, p3))/(p3 *n_item* (n_item-1)))
p1, = ax.plot(e1_xlist, e1_ylist, color='red', label="p1 = 0.001")
p2, = ax.plot(e2_xlist, e2_ylist, color='black', label="p2 = 0.01")
p3, = ax.plot(e3_xlist, e3_ylist, color='green', label="p3 = 0.1")
handles, labels = ax.get_legend_handles_labels()
#ax.set_yscale('log')
ax.set_xscale('log')
ax.legend(handles, labels)
plt.xlabel("n")
plt.title("n=" + str(n)+", difference from 4 to 1, Normalized")
# plt.show()
plt.savefig("safeedge_trends_normalized_41", facecolor='w', edgecolor='w',orientation='portrait')
def error_between_k(n, p_in, name):
outfile = "gnudata/" + name +".data"
p = p_in
N_under = n/100
# ax = plt.subplot(111)
e1_xlist = list()
e1_ylist = list()
# for n_item in range(10, 200, 10):
# print n_item
# e1_xlist.append(n_item)
# e1_ylist.append( 1+ abs(motif_expectations.approx4(n_item, p) - motif_expectations.approx1(n_item, p))/(p *n_item* (n_item-1)))
for n_item in range(N_under, n, N_under):
print n_item
e1_xlist.append(n_item)
e1_ylist.append( 1+ abs(motif_expectations.approx4(n_item, p) - motif_expectations.approx1(n_item, p))/(p *n_item* (n_item-1)))
e2_xlist = list()
e2_ylist = list()
# for n_item in range(10, 200, 10):
# e2_xlist.append(n_item)
# e2_ylist.append(1+ abs(motif_expectations.approx4(n_item, p) - motif_expectations.approx2(n_item, p))/(p *n_item* (n_item-1)))
for n_item in range(N_under, n, N_under):
e2_xlist.append(n_item)
e2_ylist.append(1+ abs(motif_expectations.approx4(n_item, p) - motif_expectations.approx2(n_item, p))/(p *n_item* (n_item-1)))
e3_xlist = list()
e3_ylist = list()
# for n_item in range(10, 200, 10):
# e3_xlist.append(n_item)
# e3_ylist.append( 1+ abs(motif_expectations.approx4(n_item, p) - motif_expectations.approx3(n_item, p))/(p *n_item* (n_item-1)))
for n_item in range(N_under, n, N_under):
e3_xlist.append(n_item)
e3_ylist.append( 1+ abs(motif_expectations.approx4(n_item, p) - motif_expectations.approx3(n_item, p))/(p *n_item* (n_item-1)))
with open(outfile, 'w') as outfile:
for i in range(0, len(e1_xlist)):
outfile.write(str(e1_xlist[i]) +' '+ str(e1_ylist[i])+ ' '+ str(e2_ylist[i])+ ' ' +str(e3_ylist[i]) + '\n')
