def build_template(tab_filter, preference):
# If tab_filter is not a string, make it an empty string
if not isinstance(tab_filter, str):
tab_filter = ''
template = TABS_TEMPLATE.replace('%FILTER%', tab_filter)
if isinstance(preference, str) and preference != '':
return template.replace('%PREFERENCE%', 'data-tab-preference="{}"'.format(preference))
return template.replace('%PREFERENCE%', '')
def build_template(tab_filter, preference):
# If tab_filter is not a string, make it an empty string
if not isinstance(tab_filter, str):
tab_filter = ''
template = TABS_TEMPLATE.replace('%FILTER%', tab_filter)
if isinstance(preference, str) and preference != '':
return template.replace('%PREFERENCE%', 'data-tab-preference="{}"'.format(preference))
return template.replace('%PREFERENCE%', '')
def buildTemplate(tabFilter, preference):
# If tabFilter is not a string, make it an empty string
if type(tabFilter) != str:
tabFilter = ""
template = TABS_TEMPLATE.replace("%FILTER%", tabFilter)
if type(preference) == str and preference != "":
template = template.replace("%PREFERENCE%", "data-tab-preference=\"" + preference + "\"")
else:
template = template.replace("%PREFERENCE%", "")
return template
p_i = p_list[i]
n_i = n_list[i]
distance_a_p = np.linalg.norm(a_i - p_i)**2
distance_a_n = np.linalg.norm(a_i - n_i)**2
result['distance_{}_a_p'.format(i)] = distance_a_p
result['distance_{}_a_n'.format(i)] = distance_a_n
for j in range(num_samples):
a_j = a_list[j]
p_j = p_list[j]
n_j = n_list[j]
distance_i_j_a = np.linalg.norm(a_i - a_j)**2
distance_i_j_p = np.linalg.norm(p_i - p_j)**2
distance_i_j_n = np.linalg.norm(n_i - n_j)**2
result['distance_{}_{}_a'.format(i, j)] = distance_i_j_a
result['distance_{}_{}_p'.format(i, j)] = distance_i_j_p
result['distance_{}_{}_n'.format(i, j)] = distance_i_j_n
with open('result.json', 'w') as file:
json.dump(result, file, indent=4)
from template import replace
replace()
K.clear_session()