Python numpy.pmt方法代碼示例

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import pmt [as 別名]
def test_pmt_decimal(self):
        res = np.pmt(Decimal('0.08') / Decimal('12'), 5 * 12, 15000)
        tgt = Decimal('-304.1459143262052370338701494')
        assert_equal(res, tgt)
        # Test the edge case where rate == 0.0
        res = np.pmt(Decimal('0'), Decimal('60'), Decimal('15000'))
        tgt = -250
        assert_equal(res, tgt)
        # Test the case where we use broadcast and
        # the arguments passed in are arrays.
        res = np.pmt([[Decimal('0'), Decimal('0.8')], [Decimal('0.3'), Decimal('0.8')]],
                     [Decimal('12'), Decimal('3')], [Decimal('2000'), Decimal('20000')])
        tgt = np.array([[Decimal('-166.6666666666666666666666667'), Decimal('-19311.25827814569536423841060')],
                        [Decimal('-626.9081401700757748402586600'), Decimal('-19311.25827814569536423841060')]])

        # Cannot use the `assert_allclose` because it uses isfinite under the covers
        # which does not support the Decimal type
        # See issue: https://github.com/numpy/numpy/issues/9954
        assert_equal(res[0][0], tgt[0][0])
        assert_equal(res[0][1], tgt[0][1])
        assert_equal(res[1][0], tgt[1][0])
        assert_equal(res[1][1], tgt[1][1]) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import pmt [as 別名]
def levelize_costs(self):
        if hasattr(self, 'is_levelized'):
            inflation = cfg.getParamAsFloat('inflation_rate')
            try:
                rate = self.cost_of_capital - inflation
            except:
                pdb.set_trace()
            if self.is_levelized == 0:
                self.values_level = - np.pmt(rate, self.book_life, 1, 0, 'end') * self.values
                util.convert_age(self, vintages=self.vintages, years=self.years, attr_from='values_level', attr_to='values_level', reverse=False)
            elif self.is_levelized==1:
                self.values_level = self.values.copy()
                util.convert_age(self, vintages=self.vintages, years=self.years, attr_from='values_level', attr_to='values_level', reverse=False)
                self.values = np.pv(rate, self.book_life, -1, 0, 'end') * self.values
            elif self.definition == 'relative':
                self.values_level = self.values.copy()
                util.convert_age(self, vintages=self.vintages, years=self.years, attr_from='values_level', attr_to='values_level', reverse=False)
            else:
                raise ValueError("no specification of whether the technology cost is levelized")

        else:
            raise ValueError('Supply Technology id %s needs to indicate whether costs are levelized ' %self.name) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import pmt [as 別名]
def test_pmt(self):
        res = np.pmt(0.08 / 12, 5 * 12, 15000)
        tgt = -304.145914
        assert_allclose(res, tgt)
        # Test the edge case where rate == 0.0
        res = np.pmt(0.0, 5 * 12, 15000)
        tgt = -250.0
        assert_allclose(res, tgt)
        # Test the case where we use broadcast and
        # the arguments passed in are arrays.
        res = np.pmt([[0.0, 0.8], [0.3, 0.8]], [12, 3], [2000, 20000])
        tgt = np.array([[-166.66667, -19311.258], [-626.90814, -19311.258]])
        assert_allclose(res, tgt) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import pmt [as 別名]
def _fv_dispatcher(rate, nper, pmt, pv, when=None):
    return (rate, nper, pmt, pv) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import pmt [as 別名]
def _nper_dispatcher(rate, pmt, pv, fv=None, when=None):
    return (rate, pmt, pv, fv) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import pmt [as 別名]
def _rbl(rate, per, pmt, pv, when):
    """
    This function is here to simply have a different name for the 'fv'
    function to not interfere with the 'fv' keyword argument within the 'ipmt'
    function.  It is the 'remaining balance on loan' which might be useful as
    it's own function, but is easily calculated with the 'fv' function.
    """
    return fv(rate, (per - 1), pmt, pv, when) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import pmt [as 別名]
def _pv_dispatcher(rate, nper, pmt, fv=None, when=None):
    return (rate, nper, nper, pv, fv) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import pmt [as 別名]
def _rate_dispatcher(nper, pmt, pv, fv, when=None, guess=None, tol=None,
                     maxiter=None):
    return (nper, pmt, pv, fv)


# Use Newton's iteration until the change is less than 1e-6
#  for all values or a maximum of 100 iterations is reached.
#  Newton's rule is
#  r_{n+1} = r_{n} - g(r_n)/g'(r_n)
#     where
#  g(r) is the formula
#  g'(r) is the derivative with respect to r. 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import pmt [as 別名]
def ppmt(rate, per, nper, pv, fv=0, when='end'):
    """
    Compute the payment against loan principal.

    Parameters
    ----------
    rate : array_like
        Rate of interest (per period)
    per : array_like, int
        Amount paid against the loan changes.  The `per` is the period of
        interest.
    nper : array_like
        Number of compounding periods
    pv : array_like
        Present value
    fv : array_like, optional
        Future value
    when : {{'begin', 1}, {'end', 0}}, {string, int}
        When payments are due ('begin' (1) or 'end' (0))

    See Also
    --------
    pmt, pv, ipmt

    """
    total = pmt(rate, nper, pv, fv, when)
    return total - ipmt(rate, per, nper, pv, fv, when) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import pmt [as 別名]
def test_pmt(self):
        res = np.pmt(0.08/12, 5*12, 15000)
        tgt = -304.145914
        assert_allclose(res, tgt)
        # Test the edge case where rate == 0.0
        res = np.pmt(0.0, 5*12, 15000)
        tgt = -250.0
        assert_allclose(res, tgt)
        # Test the case where we use broadcast and
        # the arguments passed in are arrays.
        res = np.pmt([[0.0, 0.8],[0.3, 0.8]],[12, 3],[2000, 20000])
        tgt = np.array([[-166.66667, -19311.258],[-626.90814, -19311.258]])
        assert_allclose(res, tgt) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import pmt [as 別名]
def ppmt(rate, per, nper, pv, fv=0.0, when='end'):
    """
    Compute the payment against loan principal.

    Parameters
    ----------
    rate : array_like
        Rate of interest (per period)
    per : array_like, int
        Amount paid against the loan changes.  The `per` is the period of
        interest.
    nper : array_like
        Number of compounding periods
    pv : array_like
        Present value
    fv : array_like, optional
        Future value
    when : {{'begin', 1}, {'end', 0}}, {string, int}
        When payments are due ('begin' (1) or 'end' (0))

    See Also
    --------
    pmt, pv, ipmt

    """
    total = pmt(rate, nper, pv, fv, when)
    return total - ipmt(rate, per, nper, pv, fv, when) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import pmt [as 別名]
def test_pmt(self):
        assert_almost_equal(np.pmt(0.08/12, 5*12, 15000),
                            -304.146, 3)