def safely_removable_np(n, p_in, name): #generate plot data for fixed n as p grows outfile = "gnudata/" + name +".data" p_under = p_in/100 N_under = n/100 e1_xlist = list() e1_ylist = list() e1_zlist = list() for n_item in range(N_under, n, N_under): for p_item in my_range(p_under, p_in, p_under): print n_item rate = ( 1 + abs(motif_expectations.approx4(n_item, p_item)))/( 1 + (p_item *n_item* (n_item-1))) if rate <= 1: e1_xlist.append(n_item) e1_ylist.append(p_item) e1_zlist.append(rate) 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(e1_zlist[i]) + '\n')
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')
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 safely_removable_p(n, p_in, name): #generate plot data for fixed p as n grows outfile = "gnudata/" + name +".data" p = p_in N_under = n/100 e1_xlist = list() e1_ylist = list() e2_ylist = list() 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))) e2_ylist.append( 1 + (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]) + '\n')