def multivariate_load(data_dir, post_proc_dir, timeindex, timepoint):
"""
Arguments:
=========
- `data_dir` : where the data lives
- `post_proc_dir` : where to put my output/cache
- `timeindex`: the indices to load
- `timepoint`: the time stamp of interest
"""
ccf = kio.load_csv_frame(
DATA_DIR, "local_clustering_coefficients", POST_PROC_DIR + "localcc.1.100.10.csv", TIMEINDEX
)
trif = kio.load_csv_frame(DATA_DIR, "triangles", POST_PROC_DIR + "triangles.1.100.10.csv", TIMEINDEX)
bcf = kio.load_csv_frame(DATA_DIR, "betweenness_centrality", POST_PROC_DIR + "bc.1.100.10.csv", TIMEINDEX)
namesf = pd.read_csv(DATA_DIR + "triangles.100.csv", header=None)
names = namesf[[0, 1]].set_index(0)
names[1].name = "name"
triseq = trif[t]
ccseq = ccf[t]
bcseq = bcf[t]
triseq.name = "tri"
ccseq.name = "cc"
bcseq.name = "bc"
bcseq.dtype = np.float
tf = names.join(triseq)
tf = tf.join(ccseq)
tf = tf.join(bcseq)
return trif, ccf, bcf, namesf, tf
def multivariate_load(data_dir, post_proc_dir, timeindex, timepoint):
"""
Arguments:
=========
- `data_dir` : where the data lives
- `post_proc_dir` : where to put my output/cache
- `timeindex`: the indices to load
- `timepoint`: the time stamp of interest
"""
ccf = kio.load_csv_frame(DATA_DIR, 'local_clustering_coefficients',
POST_PROC_DIR + 'localcc.1.100.10.csv', TIMEINDEX)
trif = kio.load_csv_frame(DATA_DIR, 'triangles',
POST_PROC_DIR + 'triangles.1.100.10.csv',
TIMEINDEX)
bcf = kio.load_csv_frame(DATA_DIR, 'betweenness_centrality',
POST_PROC_DIR + 'bc.1.100.10.csv', TIMEINDEX)
namesf = pd.read_csv(DATA_DIR + 'triangles.100.csv', header=None)
names = namesf[[0, 1]].set_index(0)
names[1].name = 'name'
triseq = trif[t]
ccseq = ccf[t]
bcseq = bcf[t]
triseq.name = 'tri'
ccseq.name = 'cc'
bcseq.name = 'bc'
bcseq.dtype = np.float
tf = names.join(triseq)
tf = tf.join(ccseq)
tf = tf.join(bcseq)
return trif, ccf, bcf, namesf, tf
def load_data(data_dir, post_proc_dir, timeindex, timepoint):
"""
Arguments:
=========
- `data_dir` : where the data lives
- `post_proc_dir` : where to put my output/cache
- `timeindex`: the indices to load
- `timepoint`: the time stamp of interest
"""
ccf = kio.load_csv_frame(DATA_DIR, 'local_clustering_coefficients',
POST_PROC_DIR+'localcc.1.100.10.csv', TIMEINDEX)
trif = kio.load_csv_frame(DATA_DIR, 'triangles',
POST_PROC_DIR+'triangles.1.100.10.csv', TIMEINDEX)
namesf = pd.read_csv(DATA_DIR+'triangles.100.csv', header=None)
names = namesf[[0,1]].set_index(0)
return trif, ccf, namesf
def load_data(data_dir, post_proc_dir, timeindex, timepoint):
"""
Arguments:
=========
- `data_dir` : where the data lives
- `post_proc_dir` : where to put my output/cache
- `timeindex`: the indices to load
- `timepoint`: the time stamp of interest
"""
ccf = kio.load_csv_frame(DATA_DIR, 'local_clustering_coefficients',
POST_PROC_DIR + 'localcc.1.100.10.csv', TIMEINDEX)
trif = kio.load_csv_frame(DATA_DIR, 'triangles',
POST_PROC_DIR + 'triangles.1.100.10.csv',
TIMEINDEX)
namesf = pd.read_csv(DATA_DIR + 'triangles.100.csv', header=None)
names = namesf[[0, 1]].set_index(0)
return trif, ccf, namesf