def test_timeseries_transactions(db, fname, backend):
evaler = cym.Evaluator(db)
cal = ts.transactions(evaler)
exp_head = ['Time', 'Mass']
assert_equal(list(cal), exp_head) # Check we have the correct headers
if not HAVE_PYNE:
raise SkipTest
# test single nuclide selection
cal = ts.transactions(evaler, nucs=['942390000'])
refs = pd.DataFrame(
np.array([
(0, 0.000000000),
(1, 0.0444814879803),
(2, 0.0889629759607),
(3, 0.0889629759607),
(4, 0.0889629759607),
],
dtype=ensure_dt_bytes([('Time', '<i8'), ('Mass', '<f8')])))
assert_frame_equal(cal, refs)
# test multiple nuclide selection
cal = ts.transactions(evaler, nucs=['942390000', '922380000'])
refs = pd.DataFrame(
np.array([
(0, 0.000000000),
(1, 0.831724864011),
(2, 1.66344972802),
(3, 2.62344972802),
(4, 2.62344972802),
],
dtype=ensure_dt_bytes([('Time', '<i8'), ('Mass', '<f8')])))
assert_frame_equal(cal, refs)
def get_val(ev, parameter):
key = parameter[0]
for i in range(len(parameter))[1:]:
if parameter[i] == ['']:
parameter[i][:] = []
fac1 = parameter[1]
fac2 = parameter[2]
nucs = parameter[3]
cumul = parameter[4]
if key == "inv":
pdf = cytim.inventories(ev, facilities=parameter[1],
nucs=parameter[3])['Quantity']
if cumul == ["cumul"]:
val = 0
for index, row in pdf.iteritems():
row += val
val = row
return pdf
if key == "trans":
pdf = cytim.transactions(ev, senders=parameter[1],
receivers=parameter[2], nucs=parameter[3])['Mass']
if cumul == ["cumul"]:
val = 0
for i, row in pdf.iteritems():
pdf.at[i] += val
val = pdf.at[i]
return pdf
def Trans(file, rec=(), send=(), nucs_=(), coms=()):
''' Return the transactions between senders (send) and receivers (rec),
filtered by nuclide (nucs) and commodities (coms)
'''
db = cym.dbopen(file)
ev = cym.Evaluator(db=db, write=False)
df1 = tm.transactions(ev,
receivers=rec,
senders=send,
nucs=nucs_,
commodities=coms)
return df1
def TransFrac(file='',
ev=None,
rec=(),
send=(),
nucs1=(),
nucs2=(),
factor1=1,
factor2=1):
''' Return the fraction nucs1 / (nucs1+nucs2) in the transaction between
senders and receivers, weighting factor can be added on nucs1 and nucs2
'''
if (file != ''):
db = cym.dbopen(file)
ev = cym.Evaluator(db=db, write=False)
elif (ev == None):
print('Need either a Filename or a cymetric evaler....')
return None
df1 = tm.transactions(ev, receivers=rec, senders=send, nucs=nucs1)
df2 = tm.transactions(ev, receivers=rec, senders=send, nucs=nucs2)
df_r = df2
df_r[df_r.columns[1]] = (df2[df2.columns[1]] / factor2) / \
(df1[df1.columns[1]] / factor1 + df2[df2.columns[1]] / factor2)
return df_r
def test_timeseries_transactions(db, fname, backend):
evaler = cym.Evaluator(db)
cal = ts.transactions(evaler)
exp_head = ['Time', 'Mass']
assert_equal(list(cal), exp_head) # Check we have the correct headers
if not HAVE_PYNE:
raise SkipTest
# test single nuclide selection
cal = ts.transactions(evaler, nucs=['942390000'])
refs = pd.DataFrame(np.array([
(0, 0.000000000),
(1, 0.0444814879803),
(2, 0.0889629759607),
(3, 0.0889629759607),
(4, 0.0889629759607),
], dtype=ensure_dt_bytes([
('Time', '<i8'), ('Mass', '<f8')
]))
)
assert_frame_equal(cal, refs)
# test multiple nuclide selection
cal = ts.transactions(
evaler, nucs=['942390000', '922380000'])
refs = pd.DataFrame(np.array([
(0, 0.000000000),
(1, 0.831724864011),
(2, 1.66344972802),
(3, 2.62344972802),
(4, 2.62344972802),
], dtype=ensure_dt_bytes([
('Time', '<i8'), ('Mass', '<f8')
]))
)
assert_frame_equal(cal, refs)