def get_all_articles(self):
files = [os.path.join(self.source_path, f) for f in os.listdir(
self.source_path) if f.endswith('.md')]
# http://stackoverflow.com/questions/237079/how-to-get-file-creation-modification-date-times-in-python
# it's better to use basename:
# make sure that same key in windows and linux
maps = {os.path.basename(f): os.path.getctime(f) for f in files}
persistence.persistence(maps, flag=True)
func = lambda f: persistence.get(f, default=os.path.getctime(f))
files.sort(key=func, reverse=True)
articles = []
for f in files:
article = model.Article(*self._get_by_names(f))
articles.append(article)
last = len(articles) - 1
for idx, article in enumerate(articles):
if idx != 0:
article.prev = articles[idx - 1]
if idx != last:
article.next = articles[idx + 1]
return articles
def test_persistence():
assert persistence.persistence(39) == 3
assert persistence.persistence(4) == 0
assert persistence.persistence(25) == 2
assert persistence.persistence(999) == 4
assert persistence.persistence(-25) == 2
assert persistence.persistence(25.5) == 'Error: Input must be an integer'
def get_all_articles(self):
files = [
os.path.join(self.source_path, f)
for f in os.listdir(self.source_path) if f.endswith('.md')
]
# http://stackoverflow.com/questions/237079/how-to-get-file-creation-modification-date-times-in-python
# it's better to use basename:
# make sure that same key in windows and linux
maps = {os.path.basename(f): os.path.getctime(f) for f in files}
persistence.persistence(maps, flag=True)
func = lambda f: persistence.get(f, default=os.path.getctime(f))
files.sort(key=func, reverse=True)
articles = []
for f in files:
article = model.Article(*self._get_by_names(f))
articles.append(article)
last = len(articles) - 1
for idx, article in enumerate(articles):
if idx != 0:
article.prev = articles[idx - 1]
if idx != last:
article.next = articles[idx + 1]
return articles
def run(f_name,path,save_path):
data = np.load(path+f_name)
tri_array = data['tri_array']
coord_array = data['coord_array']
data.close()
# Calculate HKS
steps = 0.001
iters = 1000
HKS = generate_hks.generate_hks(coord_array, tri_array, steps, iters)
# Calculate persistence
v = persistence.persistence(HKS)
# get the connection matrix of points, and save in file 'connection_matrix_points.npy'
adjpts = connection_matrix_point.connection_matrix(coord_array,tri_array)
save_name = f_name[:-4]
np.savez_compressed(save_path+save_name, persistence = v,adjpts=adjpts)
def __init__(self, entrance):
if not os.path.exists(config.outputdir):
os.mkdir(config.outputdir)
self.__persistence = persistence.persistence("picpath/", "docpath/",
"videopath/", "urlpath/",
"datapath/")
self.__useset = set()
self.__usedset = set()
self.__allurlset = set() # save domain all url
self.__imgurlset = set() # save img url
self.__entrance = entrance
matchresule = re.compile(r'.\w*').search(self.__entrance)
if matchresule:
self.__domain = matchresule.group()
self.__access_cnt = 0
self.__img_index = 0
socket.setdefaulttimeout(5)
def test_rand(self):
for _ in range(50):
n = randint(1, 500000)
self.assertEqual(persistence(n), soluce(n),
'Random inputs should work too')
def test(self):
self.assertEqual(persistence(39), 3, 'Basic test')
self.assertEqual(persistence(4), 0, 'Basic test')
self.assertEqual(persistence(25), 2, 'Basic test')
self.assertEqual(persistence(999), 4, 'Basic test')
self.assertEqual(persistence(444), 3, 'Basic test')
(f_name, np.shape(coord_array)[0], np.shape(tri_array)[0]))
# Plot mesh to check
#plot_mesh.plot_mesh(coord_array, tri_array)
# Calculate HKS
steps = 0.001
iters = 1000
HKS = generate_hks.generate_hks(coord_array, tri_array, steps, iters)
# Plot HKS if required at iter n
#n = [0, 10, 50, 299, 799]
#plot_hks.plot_hks(coord_array, tri_array, HKS, n)
# Calculate persistence
v = persistence.persistence(HKS)
# # Plot persistence value
#plot_persistence.plot_persistence(coord_array, tri_array, v, 'value')
#plot_persistence.plot_persistence(coord_array, tri_array, v, 'level')
# get the connection matrix of points, and save in file 'connection_matrix_points.npy'
connection_matrix_point.connection_matrix(coord_array, tri_array)
# Find clusters
#simil = [0.7, 0.75, 0.8, 0.85, 0.9] # Similarity percentages
simil = 0.9
adjm = np.array([])
while adjm.shape[0] < 10:
clusters = cluster.cluster(coord_array, tri_array, v, simil)
cluster_adjmap = cluster.get_attributed_cluster_adj_matrix(
def test_persistence():
assert persistence(39) == 3
assert persistence(4) == 0
assert persistence(25) == 2
assert persistence(999) == 4
assert persistence(444) == 3
def test_2(self):
result = persistence(4)
self.assertEqual(result, 0)
def test_1(self):
result = persistence(39)
self.assertEqual(result, 3)