def top_k(k = 10, v = None):
''' does all titles if k < 0 '''
A, d2s, i2t = load_data()
print 'data loaded and being read by top_k'
if v is None:
if os.path.isfile('pr.out.npy') == True:
print 'loading existing PR computation'
v = nload('pr.out.npy')
print 'loaded to memory'
else:
print 'doing pagerank'
v = pagerank(A)
print 'done computing PR, saving'
nsave('pr.out.npy', v)
print 'saved'
print 'sorting'
t = reversed(argsort(array(v)[:,0])) # pageranked list of dense IDs
print 'getting titles'
def get_title(x):
''' convert dense ID to sparse ID, then sparse ID to title '''
i = d2s[x]
try:
return i2t[i]
except KeyError:
return 'TITLE_ERROR'
return (get_title(x) for x in islice(t, k)) if k >= 0 else (get_title(x) for x in t)
def main():
v = None
try:
print('checking for previous pagerank computation in pr.out.npy...', end=' ')
v = nload('data/pr.out.npy')
print('loaded')
except IOError:
print('no previous pagerank computation found')
for i, title in enumerate(top_k(v=v), 1):
print('%2d %s' % (i, title))
def main():
v = None
try:
print('checking for previous pagerank computation in pr.out.npy...',
end=' ')
v = nload('data/pr.out.npy')
print('loaded')
except IOError:
print('no previous pagerank computation found')
for i, title in enumerate(top_k(v=v), 1):
print('%2d %s' % (i, title))
def load_data():
print('loading data...')
y = nload(open('data/A.npy'))
print('loaded A.npy')
A = coo_matrix((y['data'], (y['row'], y['col'])), shape=y['shape'])
print('created coo_matrix')
d2s = load(open('data/dense_to_sparse.pkl'))
print('loaded dense_to_sparse.pkl')
i2t = load(open('data/ID-title_dict.pkl'))
print('loaded ID-title_dict.pkl')
return A, d2s, i2t
def load_data():
print('loading data...')
y = nload(open('data/A.npy'))
print('loaded A.npy')
A = coo_matrix((y['data'],(y['row'],y['col'])),shape=y['shape'])
print('created coo_matrix')
d2s = load(open('data/dense_to_sparse.pkl'))
print('loaded dense_to_sparse.pkl')
i2t = load(open('data/ID-title_dict.pkl'))
print('loaded ID-title_dict.pkl')
return A, d2s, i2t
def load_data():
print 'loading data...'
y = nload(open('A.npy'))
print 'loaded A.npy'
A = coo_matrix((y['data'],(y['row'],y['col'])),shape=y['shape'])
print 'created coo_matrix'
d2s = load(open('dense_to_sparse.pickle'))
print 'loaded dense_to_sparse.pickle'
i2t = load(open('ID-title_dict.pickle'))
print 'loaded ID-title_dict.pickle'
return A, d2s, i2t
def load(filename):
filetype = filename.split('.')[-1]
try:
rez = None
print('Loading %s ...' % filename, end='', file=stderr)
if filetype == 'json':
rez = jload(open(filename))
elif filetype == 'dat':
rez = nload(open(filename, 'rb'))
print(' done', file=stderr)
return rez
except Exception as e:
print(' error! %s' % e, file=stderr)
raise e
lon_0=20.)
# RH: better:
# proj=Basemap(projection='lcc',
# resolution='i',
# llcrnrlon=-1.0,
# llcrnrlat=51.0,
# urcrnrlon=26.0,
# urcrnrlat=59.5,
# lat_0=54.0,
# lon_0=10.)
fh=open('proj.pickle','wb')
pickle.dump((proj,),fh,protocol=-1)
fh.close()
else:
(proj,) = nload('proj.pickle')
# read bathymetry
#nc=netCDF4.Dataset('../Topo/NSBS6nm.v01.nc')
nc=netCDF4.Dataset('npzd_soil_stitched.nc')
#nc=netCDF4.Dataset('maecsomexdia_soil_stitched.nc')
ncv=nc.variables
h = ncv['denitrification_rate_in_soil'][:]
#h = ncv['bathymetry'][:]
#lon = ncv['lon'][:]
#lat = ncv['lat'][:]
lon = ncv['lon_2'][:]
lat = ncv['lat_2'][:]
)
# RH: better:
# proj=Basemap(projection='lcc',
# resolution='i',
# llcrnrlon=-1.0,
# llcrnrlat=51.0,
# urcrnrlon=26.0,
# urcrnrlat=59.5,
# lat_0=54.0,
# lon_0=10.)
fh = open("proj.pickle", "wb")
pickle.dump((proj,), fh, protocol=-1)
fh.close()
else:
(proj,) = nload("proj.pickle")
# read bathymetry
# nc=netCDF4.Dataset('../Topo/NSBS6nm.v01.nc')
# nc=netCDF4.Dataset('soil_mossco_gffn_stitched.nc')
nc = netCDF4.Dataset("netcdf_out_stitched.nc")
ncv = nc.variables
# varn = 'denitrification_rate_in_soil'
# varn = 'Detritus_Carbon_detC_in_water'
varn = "Chl_chl_in_water"
var = ncv[varn][:]
unitstr = ncv[varn].units
tv = nc.variables["time"] # this is the variable (including attributes), data in eg., seconds
utime = netcdftime.utime(tv.units) # this is some intermediate variable
