def join_cities(cities):
"""Concatenate matrix for all `cities` but keep track from which city each
point come from."""
features = None
for idx, city in enumerate(cities):
mat = load_matrix(city)['v']
coming_from = idx * np.ones((1, mat.shape[0])).ravel()
if features is not None:
features = np.vstack([features, mat])
origin = np.hstack([origin, coming_from]).ravel()
else:
features = mat
origin = coming_from
return features, origin
def join_cities(cities):
"""Concatenate matrix for all `cities` but keep track from which city each
point come from."""
features = None
for idx, city in enumerate(cities):
mat = load_matrix(city)['v']
coming_from = idx*np.ones((1, mat.shape[0])).ravel()
if features is not None:
features = np.vstack([features, mat])
origin = np.hstack([origin, coming_from]).ravel()
else:
features = mat
origin = coming_from
return features, origin
cities = [
'amsterdam', 'atlanta', 'barcelona', 'berlin', 'chicago', 'helsinki',
'houston', 'indianapolis', 'london', 'losangeles', 'moscow', 'newyork',
'paris', 'prague', 'rome', 'sanfrancisco', 'seattle', 'stlouis',
'stockholm', 'washington'
]
cities = [
'paris', 'barcelona', 'rome', 'berlin', 'barcelona', 'sanfrancisco',
'washington', 'newyork'
]
# cities = ['helsinki']
if len(cities) > 1:
features, origin = join_cities(cities)
else:
features = load_matrix(city)['v']
origin = features.shape[0] * [
0,
]
# sio.savemat('tmp', {'A': features}, do_compression=True)
# sys.exit()
features[:, 5] = features[:, 5] / 8e5
# to_keep = set(range(6, 15))
# to_keep = set(range(18, 24)+range(25, 31))
# to_keep = set(range(0, 5))
cats = (8 * features[:, 5]).astype(int)
features[:, 5] = 0
# to_delete = set(range(features.shape[1])).difference(to_keep)
# features = np.delete(features, list(to_delete), axis=1)
# print(features.shape)
# features[:, 5] *= 0.0
features = None
origin = None
cities = ['stockholm', 'prague', 'paris', 'barcelona', 'rome', 'berlin',
'london', 'helsinki', 'amsterdam', 'moscow']
cities = ['amsterdam', 'atlanta', 'barcelona', 'berlin', 'chicago',
'helsinki', 'houston', 'indianapolis', 'london', 'losangeles',
'moscow', 'newyork', 'paris', 'prague', 'rome', 'sanfrancisco',
'seattle', 'stlouis', 'stockholm', 'washington']
cities = ['paris', 'barcelona', 'rome', 'berlin', 'barcelona',
'sanfrancisco', 'washington', 'newyork']
# cities = ['helsinki']
if len(cities) > 1:
features, origin = join_cities(cities)
else:
features = load_matrix(city)['v']
origin = features.shape[0] * [0, ]
# sio.savemat('tmp', {'A': features}, do_compression=True)
# sys.exit()
features[:, 5] = features[:, 5] / 8e5
# to_keep = set(range(6, 15))
# to_keep = set(range(18, 24)+range(25, 31))
# to_keep = set(range(0, 5))
cats = (8*features[:, 5]).astype(int)
features[:, 5] = 0
# to_delete = set(range(features.shape[1])).difference(to_keep)
# features = np.delete(features, list(to_delete), axis=1)
# print(features.shape)
# features[:, 5] *= 0.0
# print(np.sum(features[:, 5]))
Axes3D