StackOverflow73632991
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import numpy as np
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.pyplot as plt
from matplotlib.pyplot import figure
from matplotlib.pyplot import figure
from sympy import sieve, prime
from sympy import sieve, prime
import itertools
import itertools
import pandas as pd
import pandas as pd
matrix_size = 200
matrix_size = 200
matrix = np.zeros((matrix_size, matrix_size))
matrix = np.zeros((matrix_size, matrix_size))
with open('C:/Users/esultano/git/elliptic_curves/data/elliptic_curves.csv') as f:
with open('elliptic_curves.csv') as f:
for line in f.readlines():
for line in f.readlines():
line = line.strip()
line = line.strip()
p, q, cases = eval(line)
p, q, cases = eval(line)
idx_p = sieve.search(p)[0]-2
idx_p = sieve.search(p)[0]-2
idx_q = sieve.search(q)[0]-2
idx_q = sieve.search(q)[0]-2
if idx_p < matrix_size and idx_q < matrix_size:
if idx_p < matrix_size and idx_q < matrix_size:
cases_set = set()
cases_set = set()
for case in cases:
for case in cases:
cases_set.add(case[0])
cases_set.add(case[0])
cases_list = list(cases_set)
cases_list = list(cases_set)
val = sum(i*i for i in cases_list)
val = sum(i*i for i in cases_list)
matrix[idx_p,idx_q] = val
matrix[idx_p,idx_q] = val
matrix[idx_q,idx_p] = val
matrix[idx_q,idx_p] = val
max_prime = prime(matrix_size+2)
max_prime = prime(matrix_size+2)
axis_labels = list(sieve.primerange(3, max_prime))
axis_labels = list(enumerate(sieve.primerange(3, max_prime)))
axis_labels = axis_labels[::len(axis_labels) // 9][:-1] + [axis_labels[-1]]
ticks = [e[0] for e in axis_labels]
ticklabels = [e[1] for e in axis_labels]
fig = plt.figure(figsize=(8, 8))
fig = plt.figure(figsize=(8, 8))
ax = fig.add_subplot(111)
ax = fig.add_subplot(111)
matrix_plot = ax.matshow(matrix, interpolation='nearest')
matrix_plot = ax.matshow(matrix, interpolation='nearest')
ax.set_xticklabels(axis_labels)
ax.set_xticks(ticks); ax.set_xticklabels(ticklabels)
ax.set_yticklabels(axis_labels)
ax.set_yticks(ticks); ax.set_yticklabels(ticklabels)
plt.show()
plt.show()