def main():
ast_mode = False
# -ast flag will print the AST instead of the evaluation
if len(sys.argv) > 1 and sys.argv[1] == "-ast":
ast_mode = True
# Standard REPL
while True:
try:
expr = input("> ")
if expr == "exit": break
if ast_mode:
print(parse(expr))
else:
print(evaluate(parse(expr)))
except EOFError:
break
except Exception as e:
print("Error: " + str(e))
def worker_clustering(_clustering_info: dict) -> None:
"""Download, extract data and forward the content."""
thread = current_thread()
logger.debug('%s: Worker started', thread.name)
# Fetch data
prometheus_metrics.METRICS['gets'].inc()
try:
resp = _retryable('get', source_url, stream=True)
except requests.HTTPError as exception:
logger.error('%s: Unable to fetch source data for "%s": %s',
thread.name, source_id, exception)
prometheus_metrics.METRICS['get_errors'].inc()
return
prometheus_metrics.METRICS['get_successes'].inc()
try:
with NamedTemporaryFile(delete=False) as tmp_file:
file_name = tmp_file.name
for chunk in filter(None, resp.iter_content(chunk_size=CHUNK)):
tmp_file.write(chunk)
except IOError as exception:
logger.error('%s: Unable to create temp file for "%s": %s',
thread.name, source_id, exception)
return
# Unpack data and stream it
# Build the POST data object
data = {
'id': source_id,
'data': custom_parser.parse(file_name),
}
# Pass to next service
prometheus_metrics.METRICS['posts'].inc()
try:
resp = _retryable('post',
f'http://{dest_url}',
json=data,
headers={"x-rh-identity": b64_identity})
prometheus_metrics.METRICS['post_successes'].inc()
except requests.HTTPError as exception:
logger.error('%s: Failed to pass data for "%s": %s', thread.name,
source_id, exception)
prometheus_metrics.METRICS['post_errors'].inc()
# Cleanup
with suppress(IOError):
os.remove(file_name)
logger.debug('%s: Done, exiting', thread.name)
def test_failure_atom(self):
with self.assertRaises(Exception):
parse("idk")
def test_failure_mult(self):
with self.assertRaises(Exception):
parse("2*")
def test_failure_add(self):
with self.assertRaises(Exception):
parse("2+")
def test_parentheses(self):
self.assertEqual(parse("(2+1)*3"), Binary(Times, Binary(Plus, N(2), N(1)), N(3)))
def test_operator_precedence(self):
self.assertEqual(parse("2+1*3"), Binary(Plus, N(2), Binary(Times, N(1), N(3))))
def test_add(self):
self.assertEqual(parse("1+3"), Binary(Plus, N(1), N(3)))
self.assertEqual(parse("1-3"), Binary(Minus, N(1), N(3)))
+ elem(m1, n1, 0, 2) * elem(m2, n2, 2, 0)) \
+ 0.500 * d * elem(m1, n1, 1, 1) * elem(m2, n2, 1, 1) \
+ 0.250 * d * (elem(m1, n1, 1, 3) * elem(m2, n2, 0, 0)
+ elem(m1, n1, 3, 1) * elem(m2, n2, 0, 0)
+ elem(m1, n1, 0, 0) * elem(m2, n2, 1, 3)
+ elem(m1, n1, 0, 0) * elem(m2, n2, 3, 1)
+ elem(m1, n1, 0, 2) * elem(m2, n2, 1, 1)
+ elem(m1, n1, 2, 0) * elem(m2, n2, 1, 1)
+ elem(m1, n1, 1, 1) * elem(m2, n2, 0, 2)
+ elem(m1, n1, 1, 1) * elem(m2, n2, 2, 0)) \
+ 0.0625 * d * (elem(m1, n1, 4, 0) * elem(m2, n2, 0, 0)
+ elem(m1, n1, 0, 4) * elem(m2, n2, 0, 0)
+ elem(m1, n1, 0, 0) * elem(m2, n2, 4, 0)
+ elem(m1, n1, 0, 0) * elem(m2, n2, 0, 4)
+ 2 * elem(m1, n1, 2, 0) * elem(m2, n2, 2, 0)
+ 2 * elem(m1, n1, 0, 2) * elem(m2, n2, 0, 2))
end = timer()
print('hamilt: ', end - start)
np.savez_compressed('hamilt.npz', H=H)
return H
# print(H)
if __name__ == '__main__':
B, D, N, _ = parse()
for b in B:
for d in D:
for n in N:
main(1, b, d, n)
def test_atom(self):
self.assertEqual(parse("2"), N(2))
import os
import custom_parser
from project_setup import Project
from genetic_algorithm import GeneticAlgorithm
from visualization import visualize
from project_stats import plot_evolution_over_time
if __name__ == "__main__":
csv_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), '..',
'data', 'activities.csv')
component_list = custom_parser.parse(csv_path=csv_path)
project = Project(component_list)
project.print_planning_days()
print("Min:", project.calc_min_fitness())
print("Max:", project.calc_max_fitness())
gen_algo = GeneticAlgorithm(component_list)
gen_algo.run(300)
print("Best project planning:")
gen_algo.get_best_project().print_planning_days()
gen_algo.get_best_project().print_to_csv('best_project')
plot_evolution_over_time(gen_algo.get_best_project())
visualization_path = os.path.join(
os.path.dirname(os.path.abspath(__file__)), '..', 'example',
'index.html')
visualize(gen_algo.get_best_project(), visualization_path)
k = index[sort_idx].sum(axis=1) # n1 + n2
w = 1 / (k + 1) - 0.01 # bar widths
r = [j for i in range(n + 1) for j in range(i)]
x = k - 0.5 + r / (k + 1) # positions
d_no = 0 # number of duplicate states
clean_dir('eigenvectors')
for i in range(eigenvectors.shape[0]):
eigv_len = no_signif_el(eigenvectors[i])
minor_ticks = np.arange(0, eigv_len, 0.5)
# Plot label
label = 'E = ' + str(E[i]) + '\n' + '$\\left|' + \
str(ket[i][0]) + '\\,' + str(ket[i][1]) + '\\right\\rangle$\t' + \
ir_str[i]
fname = str(ket[i][0]) + ' ' + str(ket[i][1]) # filename
index_plot(eigenvectors[i], eigv_len, label, index, sort_idx, fname,
d_no)
energy_plot(eigenvectors[i], eigv_len, x, w, label, index, sort_idx,
fname, d_no)
if __name__ == '__main__':
B, D, N = parse()
for b in B:
for d in D:
for n in N:
main(b, d, n)
('_max_e_' + str(max_energy) + '.pdf' if max_energy else '.pdf')
histogram(rel_sp,
cumulative=True,
bins=np.linspace(0, 4, count),
fit=True,
ylabel=r'$I(s)$',
xlabel='$s$',
weights=w,
count=count,
label=[rnames[i] for i in reps],
fname=fname,
ylim=(0, 1.05),
figsize=(5.8, 3.7))
# Version
with open('version.txt', 'w') as f:
f.write('1.5.0')
os.chdir("../../Scripts")
if __name__ == '__main__':
B, D, N, delta_n, st_epsilon, lvl_epsilon, reselect, cut, bin_size, \
max_energy = parse(advanced=True, select=True, hist_bin=True,
max_e=True)
for b in B:
for d in D:
for n in N:
for max_e in max_energy:
main(b, d, n, delta_n, st_epsilon, lvl_epsilon, reselect,
cut, bin_size, max_e)
f.write("\\begin{longtable}{" + " | ".join(["c"] * 4) + "}\n")
f.write("energy levels & rebde.dat & reuna.dat & reuns.dat\t\\\\\n")
f.write("\\hline\n\\endfirsthead\n")
for row in range(files.shape[1]):
# Find the representation of the energy level
c = 0
for x in range(1, 4):
if files[x + 3][row]:
c = x
line = color(c, True) + '{:.18f}'.format(files[0][row]) + " & " + \
" & ".join(color(x, files[x + 6][row]) +
'{:.18f}'.format(files[x][row])
for x in range(1, 4))
f.write('\t' + line + " \\\\\n")
f.write("\\end{longtable}")
f.write("\n\n\\end{document}")
os.chdir("../../Scripts")
end = timer()
print('total: ', end - start)
if __name__ == '__main__':
B, D, N, delta_n, st_epsilon, lvl_epsilon = parse(advanced=True)
for b in B:
for d in D:
for n in N:
main(b, d, n, delta_n, st_epsilon, lvl_epsilon)
def test_failure_parentheses(self):
with self.assertRaises(Exception):
parse("2+(3*5")
ax.set_ylabel('$\\alpha$')
if energy_plot:
ax.set_xlabel('$\\Delta E$')
else:
ax.set_xlabel('$B$')
ax.set_ylim([0, 1.1])
if not energy_plot:
ax.set_xlim([0, 1])
ax.legend()
# plt.show()
plt.tight_layout(pad=0.3)
if energy_plot:
fig.savefig('../Statistics/alpha_e_B[' +
', '.join('{:.2}'
for i in B).format(*B) + ']_N' + str(N) + '.pdf',
dpi=400)
else:
fig.savefig(
'../Statistics/alpha_N' + str(N) +
('_max_e_' + str(max_energy) +
'.pdf' if len(max_energy) > 1 or max_energy[0] else '.pdf'),
dpi=400)
plt.close()
if __name__ == '__main__':
B, D, N, max_energy, energy_plot, small_plot = \
parse(max_e=True, e_plot=True, s_plot=True)
main(B, D, N, max_energy, energy_plot, small_plot)
def test_mult(self):
self.assertEqual(parse("1*3"), Binary(Times, N(1), N(3)))
self.assertEqual(parse("1/3"), Binary(Div, N(1), N(3)))
