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