for c in classes:
idxs = np.flatnonzero(y == c)
idxs = RNG(seed=1337).choice(idxs, samples_per_class, replace=False)
for i, idx in enumerate(idxs):
plt_idx = i * num_classes + c + 1
ax = plt.subplot(samples_per_class, num_classes, plt_idx)
ax.spines['bottom'].set_linewidth(2.)
ax.spines['top'].set_linewidth(2.)
ax.spines['left'].set_linewidth(2.)
ax.spines['right'].set_linewidth(2.)
plt.tick_params(axis='both',
which='both',
bottom='off',
top='off',
left='off',
right='off',
labelbottom='off',
labelleft='off',
labelright='off')
plt.imshow(X[idx].astype('uint8'), **imshow_params)
if i == 0:
plt.title(get_cifar10_label(c))
plt.suptitle(title, **title_params)
plt.subplots_adjust(wspace=0, hspace=0)
if __name__ == '__main__':
# run corresponding tests
from testing import run_tests
run_tests(__file__)
lambda: sssp_test(bellman_ford,
with_weight_w(nx.circular_ladder_graph(4), 2.0), 0), # 9
lambda: sssp_test(bellman_ford,
with_weight_w(nx.circular_ladder_graph(6), 2.0), 0
), # 10
lambda: sssp_test(bellman_ford, G_negative_edges, 0), # 11
lambda: sssp_test(dial, with_weight_w(nx.path_graph(10)), 0), # 12
lambda: sssp_test(dial, with_weight_w(nx.star_graph(10), 2.0), 0), # 13
lambda: sssp_test(dial, with_weight_w(nx.complete_graph(10)), 0), # 14
lambda: sssp_test(dial, with_weight_w(nx.circular_ladder_graph(20), 2.0), 0
), # 15
lambda: sssp_test(dial, G_spt_different_weights, 0), # 16
lambda: sssp_test(delta_stepping, with_weight_w(nx.path_graph(10)), 0
), # 17
lambda: sssp_test(delta_stepping, with_weight_w(nx.star_graph(10), 2.0), 0
), # 18
lambda: sssp_test(delta_stepping, with_weight_w(nx.complete_graph(10)), 0
), # 19
lambda: sssp_test(delta_stepping,
with_weight_w(nx.circular_ladder_graph(20), 2.0), 0
), # 20
lambda: sssp_test(delta_stepping, G_spt_different_weights, 0), # 21
lambda: sssp_test(delta_stepping, G_disconnected_graph, 0), # 22
lambda: sssp_test(dial, G_disconnected_graph, 0), # 23
lambda: sssp_test(bellman_ford, G_disconnected_graph, 0), # 24
lambda: sssp_test(dijkstra, G_disconnected_graph, 0), # 25
]
if __name__ == "__main__":
run_tests(tests)
while remaining != '':
doc = remaining[:50]
remaining = remaining[50:]
to_send.append(doc)
while to_send:
docpart = to_send.popleft()
b_complete = 0
if not to_send:
b_complete = 1
#
payload = gruel_press.create_docdata_payload(b_complete=b_complete,
data=docpart)
#
cs_tcp_recv = cs.CsTcpRecv()
cs_tcp_recv.engine = engine
cs_tcp_recv.client_sid = 'fake_sid'
cs_tcp_recv.data = payload
prop_gruel_client._engine_on_tcp_recv(cs_tcp_recv=cs_tcp_recv)
server_sends_large_doc()
#
# confirm effects
assert len(doc_receiver.docs) > docs_received
assert doc_receiver.docs[-1] == large_doc
#
return True
if __name__ == '__main__':
run_tests(unders_file=sys.modules['__main__'].__file__)
spt_actual = impl(G)
# all vertices in SPT
vertices_present_msg = {True: "all_present", False: "vertex_missing"}
vp_test_result = (len(spt_actual.nodes()) == len(G.nodes())) and (set(spt_actual.nodes()) == set(G.nodes()))
# summary cost equal to one returned by NetworkX
cost_equal_msg = {True: "cost_equal", False: "cost_different"}
calc_cost = lambda G: reduce(lambda a,b: a+b, map(lambda (u, v): G[u][v]["weight"], G.edges()))
ce_test_result = calc_cost(spt_actual) == calc_cost(nx.minimum_spanning_tree(G))
# edges in SPT should be subset of edges in G
edges_subset_msg = {True: "edge_subset", False: "additional_edges"}
edges_without_data = lambda G: map(lambda t: t[0:2], G.edges())
# this is needed because for undirected graphs NetworkX has edges only in one direction
edges_without_data_G = edges_without_data(G)
edges_both_dirs_G = edges_without_data_G + map(lambda t: tuple(reversed(t)), edges_without_data_G)
es_test_result = set(edges_without_data(spt_actual)) <= set(edges_both_dirs_G)
result_str_repr = lambda vp, ce, es: vertices_present_msg[vp] + "_" + cost_equal_msg[ce] + "_" + edges_subset_msg[es]
return result_str_repr(vp_test_result, ce_test_result, es_test_result), result_str_repr(True, True, True)
tests = [
lambda: spt_func_test(kruscal, with_weight_w(nx.complete_graph(10), 2.0)),
lambda: spt_func_test(kruscal, G_spt_different_weights),
]
if __name__ == "__main__":
run_tests(tests)
def run_from_argv(self, argv):
import nose2
with run_tests():
nose2.main(module=None, argv=argv[1:])
def run_from_argv(self, argv):
import nose
with run_tests():
nose.main(argv[2:])
def run_from_argv(self, argv):
import pytest
with run_tests():
pytest.main(argv[2:])
