def test_broadcast_decimal(self):
# Use almost equal because precision is tested in the explicit tests,
# this test is to ensure broadcast with Decimal is not broken.
assert_almost_equal(npf.ppmt(Decimal('0.1') / Decimal('12'),
list(range(1, 5)), Decimal('24'),
Decimal('2000')),
[Decimal('-75.62318601'),
Decimal('-76.25337923'), Decimal('-76.88882405'),
Decimal('-77.52956425')], 4)
result = npf.ppmt(
Decimal('0.1') / Decimal('12'),
list(range(1, 5)),
Decimal('24'),
Decimal('2000'),
Decimal('0'),
[Decimal('0'), Decimal('1'), 'end', 'begin']
)
desired = [
Decimal('-75.62318601'),
Decimal('-75.62318601'),
Decimal('-76.88882405'),
Decimal('-76.88882405')
]
assert_almost_equal(result, desired, decimal=4)
def test_when_is_end(self, when):
args = (0.1 / 12, 1, 60, 55000, 0)
result = npf.ppmt(*args) if when is None else npf.ppmt(*args, when)
assert_allclose(
result,
-710.254126, # Computed using Google Sheet's PPMT
rtol=1e-9,
)
def test_when_is_end_decimal(self, when):
args = (Decimal('0.08') / Decimal('12'), Decimal('1'), Decimal('60'),
Decimal('15000.'), Decimal('0'))
result = npf.ppmt(*args) if when is None else npf.ppmt(*args, when)
assert_almost_equal(
result,
Decimal('-204.145914'), # Computed using Google Sheet's PPMT
decimal=5,
)
def test_broadcast(self):
assert_almost_equal(npf.nper(0.075, -2000, 0, 100000., [0, 1]),
[21.5449442, 20.76156441], 4)
assert_almost_equal(npf.ppmt(0.1 / 12, list(range(5)), 24, 2000),
[numpy.nan, -75.62318601, -76.25337923,
-76.88882405, -77.52956425], 4)
assert_almost_equal(npf.ppmt(0.1 / 12, list(range(5)), 24, 2000, 0,
[0, 0, 1, 'end', 'begin']),
[numpy.nan, -75.62318601, -75.62318601,
-76.88882405, -76.88882405], 4)
def raise_error_because_not_equal():
assert_equal(
round(
npf.ppmt(
Decimal('0.23') / Decimal('12'), 1, 60,
Decimal('10000000000')), 8),
Decimal('-90238044.232277036'))
def amortization_schedule(input_intrate, mortgage, years, down_paymnt):
##### PARAMETERS #####
# CONVERT MORTGAGE AMOUNT TO NEGATIVE BECAUSE MONEY IS GOING OUT
down = down_payment(mortgage, down_paymnt)
loan = mortgage - down
mortgage_amount = -(loan)
interest_rate = (input_intrate / 100) / 12
periods = years * 12
# CREATE ARRAY
n_periods = np.arange(years * 12) + 1
##### BUILD AMORTIZATION SCHEDULE #####
# INTEREST PAYMENT
interest_monthly = npf.ipmt(interest_rate, n_periods, periods,
mortgage_amount)
# PRINCIPAL PAYMENT
principal_monthly = npf.ppmt(interest_rate, n_periods, periods,
mortgage_amount)
# JOIN DATA
df_initialize = list(zip(n_periods, interest_monthly, principal_monthly))
df = pd.DataFrame(df_initialize,
columns=['Period', 'Interest', 'Principal'])
# MONTHLY MORTGAGE PAYMENT
df['Monthly Payment'] = df['Interest'] + df['Principal']
# CALCULATE CUMULATIVE SUM OF MORTAGE PAYMENTS
df['Balance'] = df['Monthly Payment'].cumsum()
# REVERSE VALUES SINCE WE ARE PAYING DOWN THE BALANCE
df.Balance = df.Balance.values[::-1]
return df
def mortgage_monthly(price, years, percent, down_paymnt):
# THIS IMPLEMENTS AN APPROACH TO FINDING A MONTHLY MORTGAGE AMOUNT FROM THE PURCHASE PRICE,
# YEARS, INTEREST RATE AND DOWN PAYMENT
##### PARAMETERS #####
down = down_payment(price, down_paymnt)
loan = price - down
mortgage_amount = -loan
interest_rate = (percent / 100) / 12
periods = years * 12
# CREATE ARRAY
n_periods = np.arange(years * 12) + 1
##### BUILD AMORTIZATION SCHEDULE #####
# INTEREST PAYMENT
interest_monthly = npf.ipmt(interest_rate, n_periods, periods,
mortgage_amount)
# PRINCIPAL PAYMENT
principal_monthly = npf.ppmt(interest_rate, n_periods, periods,
mortgage_amount)
# JOIN DATA
df_initialize = list(zip(n_periods, interest_monthly, principal_monthly))
df = pd.DataFrame(df_initialize,
columns=['Period', 'Interest', 'Principal'])
# MONTHLY MORTGAGE PAYMENT
df['Monthly Payment'] = df['Interest'] + df['Principal']
payment = df['Monthly Payment'].mean()
return payment
def test_decimal(self):
result = npf.ppmt(
Decimal('0.1') / Decimal('12'), Decimal('1'), Decimal('60'),
Decimal('55000'))
assert_equal(
result,
Decimal('-710.2541257864217612489830917'),
)
def get_planned_payments_at(self, date):
if before(self.date, date):
return 0.0
initial_date = self.date + relativedelta(days=10)
num_intervals = get_interval_in_months(initial_date, date)
total_paid = 0
for p in range(num_intervals):
total_paid += npf.ppmt(self.rate, p + 1, self.periods, self.amount)
return total_paid
def test_when_is_begin_decimal(self, when):
result = npf.ppmt(
Decimal('0.08') / Decimal('12'), Decimal('1'), Decimal('60'),
Decimal('15000.'), Decimal('0'), when)
assert_almost_equal(
result,
Decimal('-302.131703'), # Computed using Google Sheet's PPMT
decimal=5,
)
def principal_remaining_after(p, n, r, rem_years):
rr = r / 1200.0
nn = n*12
rem_mths = rem_years * 12
paid_mths = nn - rem_mths
paid_prin = 0.0
for i in range(1,paid_mths+1):
pp = npf.ppmt(rr, i, nn, p)
paid_prin += pp
return (p*-1) - paid_prin
def test_broadcast(self):
assert_almost_equal(npf.nper(0.075, -2000, 0, 100000., [0, 1]),
[21.5449442, 20.76156441], 4)
assert_almost_equal(npf.ipmt(0.1 / 12, list(range(5)), 24, 2000), [
-17.29165168, -16.66666667, -16.03647345, -15.40102862,
-14.76028842
], 4)
assert_almost_equal(npf.ppmt(0.1 / 12, list(range(5)), 24, 2000), [
-74.998201, -75.62318601, -76.25337923, -76.88882405, -77.52956425
], 4)
assert_almost_equal(
npf.ppmt(0.1 / 12, list(range(5)), 24, 2000, 0,
[0, 0, 1, 'end', 'begin']), [
-74.998201, -75.62318601, -75.62318601, -76.88882405,
-76.88882405
], 4)
def calcLoan(self, loan=0.6, interest=0.04, years=10):
quantity = loan * self.CAPEX
assert quantity > 0
assert interest >= 0 and interest <= 1
assert years > 1
self.loan_payment = pmt(interest, years, quantity)
self.loan_interest = ipmt(interest,
np.arange(years) + 1, years, quantity)
self.loan_principal = ppmt(interest,
np.arange(years) + 1, years, quantity)
def _get_mortgage_balance(
mortgage: Dict[str, Union[int, float]]) -> np.ndarray:
"""
Returns array of outstanding mortgage balance for each month, from dict of mortgage information.
Args:
mortgage: dict with keys 'mortgage_size', 'term', 'offer_term', 'interest_rate' and 'offer_rate'
Returns:
array of outstanding mortgage balances
"""
# Get variables
mortgage_size = int(mortgage.get("mortgage_size")) * 1000
term = mortgage.get("term") * 12
offer_term = mortgage.get("offer_term") * 12
remaining_term = term - offer_term
interest_rate = (mortgage.get("interest_rate") / 12) / 100
offer_rate = (mortgage.get("offer_rate") /
12) / 100 # monthly interest rate
# Get offer principal payments
offer_per = np.arange(term) + 1
offer_principal_payments = (
-1 * npf.ppmt(offer_rate, offer_per, term, mortgage_size))[:offer_term]
# Get regular principal payments
balance_after_offer = mortgage_size - np.sum(offer_principal_payments)
remaining_per = np.arange(remaining_term) + 1
remaining_principal_payments = -1 * npf.ppmt(
interest_rate, remaining_per, remaining_term, balance_after_offer)
principal_payments = np.append(offer_principal_payments,
remaining_principal_payments)
# Get outstanding balance
outstanding_balance = mortgage_size - np.cumsum(principal_payments)
return outstanding_balance
def calculate_remaining_balance(self):
"""Calculates the remaining balance"""
# Determine the number of periods we are into the loan
num_periods_elapsed = self.calculate_elapsed_periods()
# Find out how much principal we have paid
prin_paid_to_date = 0.0
for current_period in range(0, num_periods_elapsed):
prin_paid_to_date -= round(
npf.ppmt(self.annual_rate / 12, current_period,
self.num_years * 12, self.principal_amt), 2)
return self.principal_amt - prin_paid_to_date
def test_broadcast_decimal(self):
# Use almost equal because precision is tested in the explicit tests,
# this test is to ensure broadcast with Decimal is not broken.
assert_almost_equal(
npf.ipmt(
Decimal('0.1') / Decimal('12'), list(range(5)), Decimal('24'),
Decimal('2000')), [
Decimal('-17.29165168'),
Decimal('-16.66666667'),
Decimal('-16.03647345'),
Decimal('-15.40102862'),
Decimal('-14.76028842')
], 4)
assert_almost_equal(
npf.ppmt(
Decimal('0.1') / Decimal('12'), list(range(5)), Decimal('24'),
Decimal('2000')), [
Decimal('-74.998201'),
Decimal('-75.62318601'),
Decimal('-76.25337923'),
Decimal('-76.88882405'),
Decimal('-77.52956425')
], 4)
assert_almost_equal(
npf.ppmt(
Decimal('0.1') / Decimal('12'), list(range(5)), Decimal('24'),
Decimal('2000'), Decimal('0'),
[Decimal('0'),
Decimal('0'),
Decimal('1'), 'end', 'begin']), [
Decimal('-74.998201'),
Decimal('-75.62318601'),
Decimal('-75.62318601'),
Decimal('-76.88882405'),
Decimal('-76.88882405')
], 4)
def test_ppmt_special_rate_decimal(self):
# When rounded out to 8 decimal places like the float based test,
# this should not equal the same value as the float, substituted
# for the decimal
def raise_error_because_not_equal():
assert_equal(
round(npf.ppmt(Decimal('0.23') / Decimal('12'), 1, 60,
Decimal('10000000000')), 8),
Decimal('-90238044.232277036'))
assert_raises(AssertionError, raise_error_because_not_equal)
assert_equal(npf.ppmt(Decimal('0.23') / Decimal('12'), 1, 60,
Decimal('10000000000')),
Decimal('-90238044.2322778884413969909'))
def calculate_loan(self):
"""Compute annual payment of a loan. Inputs:
quantity [monetary units] == investment which will be funded
interest [as fraction of unity] == annual interest
years == number of yeras to return the loan."""
assert type(self) is Loan
self.res_payment = pmt(self.interest, self.years, self.quantity)
self.res_interest = ipmt(self.interest,
np.arange(self.years) + 1, self.years,
self.quantity)
self.res_principal = ppmt(self.interest,
np.arange(self.years) + 1, self.years,
self.quantity)
def loan(self, prestamo, interest, years):
"""Compute annual payment of a loan. Inputs:
quantity [monetary units] == investment which will be funded
interest [as fraction of unity] == annual interest
years == number of yeras to return the loan."""
quantity = prestamo * self.capex()
assert quantity > 0
assert interest >= 0 and interest <= 1
assert years > 1
loan_payment = pmt(interest, years, quantity)
loan_interest = ipmt(interest, np.arange(years) + 1, years, quantity)
loan_principal = ppmt(interest, np.arange(years) + 1, years, quantity)
return loan_payment, loan_interest, loan_principal
def test_when(self):
# begin
assert_equal(npf.rate(10, 20, -3500, 10000, 1),
npf.rate(10, 20, -3500, 10000, 'begin'))
# end
assert_equal(npf.rate(10, 20, -3500, 10000),
npf.rate(10, 20, -3500, 10000, 'end'))
assert_equal(npf.rate(10, 20, -3500, 10000, 0),
npf.rate(10, 20, -3500, 10000, 'end'))
# begin
assert_equal(npf.pv(0.07, 20, 12000, 0, 1),
npf.pv(0.07, 20, 12000, 0, 'begin'))
# end
assert_equal(npf.pv(0.07, 20, 12000, 0),
npf.pv(0.07, 20, 12000, 0, 'end'))
assert_equal(npf.pv(0.07, 20, 12000, 0, 0),
npf.pv(0.07, 20, 12000, 0, 'end'))
# begin
assert_equal(npf.pmt(0.08 / 12, 5 * 12, 15000., 0, 1),
npf.pmt(0.08 / 12, 5 * 12, 15000., 0, 'begin'))
# end
assert_equal(npf.pmt(0.08 / 12, 5 * 12, 15000., 0),
npf.pmt(0.08 / 12, 5 * 12, 15000., 0, 'end'))
assert_equal(npf.pmt(0.08 / 12, 5 * 12, 15000., 0, 0),
npf.pmt(0.08 / 12, 5 * 12, 15000., 0, 'end'))
# begin
assert_equal(npf.ppmt(0.1 / 12, 1, 60, 55000, 0, 1),
npf.ppmt(0.1 / 12, 1, 60, 55000, 0, 'begin'))
# end
assert_equal(npf.ppmt(0.1 / 12, 1, 60, 55000, 0),
npf.ppmt(0.1 / 12, 1, 60, 55000, 0, 'end'))
assert_equal(npf.ppmt(0.1 / 12, 1, 60, 55000, 0, 0),
npf.ppmt(0.1 / 12, 1, 60, 55000, 0, 'end'))
# begin
assert_equal(npf.nper(0.075, -2000, 0, 100000., 1),
npf.nper(0.075, -2000, 0, 100000., 'begin'))
# end
assert_equal(npf.nper(0.075, -2000, 0, 100000.),
npf.nper(0.075, -2000, 0, 100000., 'end'))
assert_equal(npf.nper(0.075, -2000, 0, 100000., 0),
npf.nper(0.075, -2000, 0, 100000., 'end'))
def test_float(self):
assert_allclose(npf.ppmt(0.1 / 12, 1, 60, 55000), -710.25, rtol=1e-4)
def loan_principal(self):
assert self.quantity > 0
assert self.interest >= 0 and self.interest <= 1
assert self.years > 1
return ppmt(self.interest,
np.arange(self.years) + 1, self.years, self.quantity)
def amortization_table(interest_rate,
years,
payments_year,
principal,
addl_principal=0,
start_date=date.today()):
""" Calculate the amortization schedule given the loan details
Args:
interest_rate: The annual interest rate for this loan
years: Number of years for the loan
payments_year: Number of payments in a year
principal: Amount borrowed
addl_principal (optional): Additional payments to be made each period. Assume 0 if nothing provided.
must be a value less then 0, the function will convert a positive value to
negative
start_date (optional): Start date. Will start on first of next month if none provided
Returns:
schedule: Amortization schedule as a pandas dataframe
summary: Pandas dataframe that summarizes the payoff information
"""
# Ensure the additional payments are negative
if addl_principal > 0:
addl_principal = -addl_principal
# Create an index of the payment dates
rng = pd.date_range(start_date, periods=years * payments_year, freq='MS')
rng.name = "Payment_Date"
# Build up the Amortization schedule as a DataFrame
df = pd.DataFrame(index=rng,
columns=[
'Payment', 'Principal', 'Interest', 'Addl_Principal',
'Curr_Balance'
],
dtype='float')
# Add index by period (start at 1 not 0)
df.reset_index(inplace=True)
df.index += 1
df.index.name = "Period"
# Calculate the payment, principal and interests amounts using built in Numpy functions
per_payment = npf.pmt(interest_rate / payments_year, years * payments_year,
principal)
df["Payment"] = per_payment
df["Principal"] = npf.ppmt(interest_rate / payments_year, df.index,
years * payments_year, principal)
df["Interest"] = npf.ipmt(interest_rate / payments_year, df.index,
years * payments_year, principal)
# Round the values
df = df.round(2)
# Add in the additional principal payments
df["Addl_Principal"] = addl_principal
# Store the Cumulative Principal Payments and ensure it never gets larger than the original principal
df["Cumulative_Principal"] = (df["Principal"] +
df["Addl_Principal"]).cumsum()
df["Cumulative_Principal"] = df["Cumulative_Principal"].clip(
lower=-principal)
# Calculate the current balance for each period
df["Curr_Balance"] = principal + df["Cumulative_Principal"]
# Determine the last payment date
try:
last_payment = df.query("Curr_Balance <= 0")["Curr_Balance"].idxmax(
axis=1, skipna=True)
except ValueError:
last_payment = df.last_valid_index()
last_payment_date = "{:%m-%d-%Y}".format(df.loc[last_payment,
"Payment_Date"])
# Truncate the data frame if we have additional principal payments:
if addl_principal != 0:
# Remove the extra payment periods
df = df.loc[0:last_payment].copy()
# Calculate the principal for the last row
df.loc[last_payment,
"Principal"] = -(df.loc[last_payment - 1, "Curr_Balance"])
# Calculate the total payment for the last row
df.loc[last_payment,
"Payment"] = df.loc[last_payment,
["Principal", "Interest"]].sum()
# Zero out the additional principal
df.loc[last_payment, "Addl_Principal"] = 0
# Get the payment info into a DataFrame in column order
payment_info = (df[["Payment", "Principal", "Addl_Principal",
"Interest"]].sum().to_frame().T)
# Format the Date DataFrame
payment_details = pd.DataFrame.from_dict(
dict([('payoff_date', [last_payment_date]),
('Interest Rate', [interest_rate]),
('Number of years', [years])]))
# Add a column showing how much we pay each period.
# Combine addl principal with principal for total payment
payment_details["Period_Payment"] = round(per_payment, 2) + addl_principal
payment_summary = pd.concat([payment_details, payment_info], axis=1)
return df, payment_summary
#df, payment_summary = amortization_table(interest_rate, years, payments_year, principal)
#print(payment_summary)
def test_broadcast_decimal(self, when, desired):
args = (Decimal('0.1') / Decimal('12'), numpy.arange(1, 5),
Decimal('24'), Decimal('2000'), Decimal('0'))
result = npf.ppmt(*args) if when is None else npf.ppmt(*args, when)
assert_almost_equal(result, desired, decimal=8)
f'年均收益率{rate * 100:.2f}%，每月投入￥{abs(float(pmt)):.2f}元，投资{nper}年后，期末资产￥{abs(float(fv)):.2f}元，需要投入本金：￥{abs(pv):.2f}元。'
)
'''pmt：计算每期支付金额'''
rate = 0.075
nper = 20
pv = 1000000
fv = 0
per = 240
pmt = npf.pmt(rate=rate / 12, nper=nper * 12, pv=pv, fv=fv)
# rate：年化投资回报率
# nper：投资年数
# pv：现值（正值）
# fv：预期达到的资产总值(正值）
# per：还款的第几期
'''ppmt：每期支付金额之本金'''
ppmt = npf.ppmt(rate=rate / 12, per=per, nper=nper * 12, pv=pv, fv=fv)
'''ipmt：每期支付金额之利息'''
ipmt = npf.ipmt(rate=rate / 12, per=per, nper=nper * 12, pv=pv, fv=fv)
print(
f'年利率{rate * 100}%，贷款总额￥{abs(pv)}元，{nper}年还清，每月还款￥{abs(pmt):.2f}元，第{per}期本金：￥{abs(ppmt):.2f}元，第{per}期利息：￥{abs(ipmt):.2f}元。'
)
'''nper：分期数'''
rate = 0.075
pmt = -8055.93
pv = 1000000
fv = 0
# rate：年利率
# pmt：每期还款金额（负值）
# pv：贷款总额（正值）
# fv：期末剩余贷款金额(正值）
nper = npf.nper(rate=rate / 12, pmt=pmt, pv=pv, fv=fv)
def test_broadcast(self, when, desired):
args = (0.1 / 12, numpy.arange(1, 5), 24, 2000, 0)
result = npf.ppmt(*args) if when is None else npf.ppmt(*args, when)
assert_allclose(result, desired, rtol=1e-5)
def test_invalid_per(self, args):
# Note that math.isnan() handles Decimal NaN correctly.
assert math.isnan(npf.ppmt(*args))
def test_decimal_with_when(self):
"""
Test that decimals are still supported if the when argument is passed
"""
# begin
assert_equal(
npf.rate(Decimal('10'), Decimal('20'), Decimal('-3500'),
Decimal('10000'), Decimal('1')),
npf.rate(Decimal('10'), Decimal('20'), Decimal('-3500'),
Decimal('10000'), 'begin'))
# end
assert_equal(
npf.rate(Decimal('10'), Decimal('20'), Decimal('-3500'),
Decimal('10000')),
npf.rate(Decimal('10'), Decimal('20'), Decimal('-3500'),
Decimal('10000'), 'end'))
assert_equal(
npf.rate(Decimal('10'), Decimal('20'), Decimal('-3500'),
Decimal('10000'), Decimal('0')),
npf.rate(Decimal('10'), Decimal('20'), Decimal('-3500'),
Decimal('10000'), 'end'))
# begin
assert_equal(
npf.pv(Decimal('0.07'), Decimal('20'), Decimal('12000'),
Decimal('0'), Decimal('1')),
npf.pv(Decimal('0.07'), Decimal('20'), Decimal('12000'),
Decimal('0'), 'begin'))
# end
assert_equal(
npf.pv(Decimal('0.07'), Decimal('20'), Decimal('12000'),
Decimal('0')),
npf.pv(Decimal('0.07'), Decimal('20'), Decimal('12000'),
Decimal('0'), 'end'))
assert_equal(
npf.pv(Decimal('0.07'), Decimal('20'), Decimal('12000'),
Decimal('0'), Decimal('0')),
npf.pv(Decimal('0.07'), Decimal('20'), Decimal('12000'),
Decimal('0'), 'end'))
# begin
assert_equal(
npf.pmt(
Decimal('0.08') / Decimal('12'),
Decimal('5') * Decimal('12'), Decimal('15000.'), Decimal('0'),
Decimal('1')),
npf.pmt(
Decimal('0.08') / Decimal('12'),
Decimal('5') * Decimal('12'), Decimal('15000.'), Decimal('0'),
'begin'))
# end
assert_equal(
npf.pmt(
Decimal('0.08') / Decimal('12'),
Decimal('5') * Decimal('12'), Decimal('15000.'), Decimal('0')),
npf.pmt(
Decimal('0.08') / Decimal('12'),
Decimal('5') * Decimal('12'), Decimal('15000.'), Decimal('0'),
'end'))
assert_equal(
npf.pmt(
Decimal('0.08') / Decimal('12'),
Decimal('5') * Decimal('12'), Decimal('15000.'), Decimal('0'),
Decimal('0')),
npf.pmt(
Decimal('0.08') / Decimal('12'),
Decimal('5') * Decimal('12'), Decimal('15000.'), Decimal('0'),
'end'))
# begin
assert_equal(
npf.ppmt(
Decimal('0.1') / Decimal('12'), Decimal('1'), Decimal('60'),
Decimal('55000'), Decimal('0'), Decimal('1')),
npf.ppmt(
Decimal('0.1') / Decimal('12'), Decimal('1'), Decimal('60'),
Decimal('55000'), Decimal('0'), 'begin'))
# end
assert_equal(
npf.ppmt(
Decimal('0.1') / Decimal('12'), Decimal('1'), Decimal('60'),
Decimal('55000'), Decimal('0')),
npf.ppmt(
Decimal('0.1') / Decimal('12'), Decimal('1'), Decimal('60'),
Decimal('55000'), Decimal('0'), 'end'))
assert_equal(
npf.ppmt(
Decimal('0.1') / Decimal('12'), Decimal('1'), Decimal('60'),
Decimal('55000'), Decimal('0'), Decimal('0')),
npf.ppmt(
Decimal('0.1') / Decimal('12'), Decimal('1'), Decimal('60'),
Decimal('55000'), Decimal('0'), 'end'))
def test_ppmt(self):
assert_equal(numpy.round(npf.ppmt(0.1 / 12, 1, 60, 55000), 2), -710.25)
def test_when_is_begin(self, when):
assert_allclose(
npf.ppmt(0.1 / 12, 1, 60, 55000, 0, when),
-1158.929712, # Computed using Google Sheet's PPMT
rtol=1e-9,
)
