+ PYTHONPATH=/home/tkloczko/rpmbuild/BUILDROOT/python-pymeeus-0.5.11-10.fc36.x86_64/usr/lib64/python3.9/site-packages:/home/tkloczko/rpmbuild/BUILDROOT/python-pymeeus-0.5.11-10.fc36.x86_64/usr/lib/python3.9/site-packages
+ /usr/bin/pytest -ra -m 'not network'
==================================================================================== test session starts ====================================================================================
platform linux -- Python 3.9.18, pytest-8.1.0, pluggy-1.4.0
rootdir: /home/tkloczko/rpmbuild/BUILD/pymeeus-0.5.11
configfile: pyproject.toml
collected 251 items
tests/test_angle.py ........................................ [ 15%]
tests/test_coordinates.py ....................................... [ 31%]
tests/test_curvefitting.py .FFFF [ 33%]
tests/test_earth.py ................ [ 39%]
tests/test_epoch.py ................................. [ 52%]
tests/test_interpolation.py .FFF. [ 54%]
tests/test_jupiter.py .......... [ 58%]
tests/test_jupiterMoons.py ......... [ 62%]
tests/test_mars.py .......... [ 66%]
tests/test_mercury.py ............ [ 71%]
tests/test_minor.py .. [ 72%]
tests/test_moon.py .............. [ 77%]
tests/test_neptune.py ...... [ 80%]
tests/test_pluto.py .. [ 80%]
tests/test_saturn.py .............. [ 86%]
tests/test_sun.py ............ [ 91%]
tests/test_uranus.py ........ [ 94%]
tests/test_venus.py .............. [100%]
========================================================================================= FAILURES ==========================================================================================
____________________________________________________________________________ test_curvefitting_correlation_coeff ____________________________________________________________________________
def test_curvefitting_correlation_coeff():
"""Tests the correlation_coeff() method of CurveFitting class"""
> r = cf1.correlation_coeff()
tests/test_curvefitting.py:92:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = CurveFitting([], [])
def correlation_coeff(self):
"""This method returns the coefficient of correlation, as a float.
:returns: Coefficient of correlation.
:rtype: float
>>> cf = CurveFitting([73.0, 38.0, 35.0, 42.0, 78.0, 68.0, 74.0, 42.0,
... 52.0, 54.0, 39.0, 61.0, 42.0, 49.0, 50.0, 62.0,
... 44.0, 39.0, 43.0, 54.0, 44.0, 37.0],
... [90.4, 125.3, 161.8, 143.4, 52.5, 50.8, 71.5,
... 152.8, 131.3, 98.5, 144.8, 78.1, 89.5, 63.9,
... 112.1, 82.0, 119.8, 161.2, 208.4, 111.6, 167.1,
... 162.1])
>>> r = cf.correlation_coeff()
>>> print(round(r, 3))
-0.767
"""
> n = self._N
E AttributeError: 'CurveFitting' object has no attribute '_N'
pymeeus/CurveFitting.py:321: AttributeError
_____________________________________________________________________________ test_curvefitting_linear_fitting ______________________________________________________________________________
def test_curvefitting_linear_fitting():
"""Tests the linear_fitting() method of CurveFitting class"""
> a, b = cf1.linear_fitting()
tests/test_curvefitting.py:100:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = CurveFitting([], [])
def linear_fitting(self):
"""This method returns a tuple with the 'a', 'b' coefficients of the
linear equation *'y = a*x + b'* that best fits the table data, using
the least squares approach.
:returns: 'a', 'b' coefficients of best linear equation fit.
:rtype: tuple
:raises: ZeroDivisionError if input data leads to a division by zero
>>> cf = CurveFitting([73.0, 38.0, 35.0, 42.0, 78.0, 68.0, 74.0, 42.0,
... 52.0, 54.0, 39.0, 61.0, 42.0, 49.0, 50.0, 62.0,
... 44.0, 39.0, 43.0, 54.0, 44.0, 37.0],
... [90.4, 125.3, 161.8, 143.4, 52.5, 50.8, 71.5,
... 152.8, 131.3, 98.5, 144.8, 78.1, 89.5, 63.9,
... 112.1, 82.0, 119.8, 161.2, 208.4, 111.6, 167.1,
... 162.1])
>>> a, b = cf.linear_fitting()
>>> print("a = {}\tb = {}".format(round(a, 2), round(b, 2)))
a = -2.49 b = 244.18
"""
> n = self._N
E AttributeError: 'CurveFitting' object has no attribute '_N'
pymeeus/CurveFitting.py:351: AttributeError
____________________________________________________________________________ test_curvefitting_quadratic_fitting ____________________________________________________________________________
def test_curvefitting_quadratic_fitting():
"""Tests the quadratic_fitting() method of CurveFitting class"""
> a, b, c = cf3.quadratic_fitting()
tests/test_curvefitting.py:118:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = CurveFitting([], [])
def quadratic_fitting(self):
"""This method returns a tuple with the 'a', 'b', 'c' coefficients of
the quadratic equation *'y = a*x*x + b*x + c'* that best fits the table
data, using the least squares approach.
:returns: 'a', 'b', 'c' coefficients of best quadratic equation fit.
:rtype: tuple
:raises: ZeroDivisionError if input data leads to a division by zero
>>> cf2 = CurveFitting([-2.0, -1.5, -1.0, -0.5, 0.0, 0.5, 1.0, 1.5,
... 2.0, 2.5,3.0],
... [-9.372, -3.821, 0.291, 3.730, 5.822, 8.324,
... 9.083, 6.957, 7.006, 0.365, -1.722])
>>> a, b, c = cf2.quadratic_fitting()
>>> print("a = {}; b = {}; c = {}".format(round(a, 2), round(b, 2),
... round(c, 2)))
a = -2.22; b = 3.76; c = 6.64
"""
> n = self._N
E AttributeError: 'CurveFitting' object has no attribute '_N'
pymeeus/CurveFitting.py:384: AttributeError
_____________________________________________________________________________ test_curvefitting_general_fitting _____________________________________________________________________________
def test_curvefitting_general_fitting():
"""Tests the general_fitting() method of CurveFitting class"""
# Let's define the three functions to be used for fitting
def sin1(x):
return sin(radians(x))
def sin2(x):
return sin(radians(2.0*x))
def sin3(x):
return sin(radians(3.0*x))
> a, b, c = cf4.general_fitting(sin1, sin2, sin3)
tests/test_curvefitting.py:142:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = CurveFitting([], []), f0 = <function test_curvefitting_general_fitting.<locals>.sin1 at 0x7f8356bea1f0>
f1 = <function test_curvefitting_general_fitting.<locals>.sin2 at 0x7f8356bea280>, f2 = <function test_curvefitting_general_fitting.<locals>.sin3 at 0x7f8356bea310>
def general_fitting(self, f0, f1=lambda *args: 0.0, f2=lambda *args: 0.0):
"""This method returns a tuple with the 'a', 'b', 'c' coefficients of
the general equation *'y = a*f0(x) + b*f1(x) + c*f2(x)'* that best fits
the table data, using the least squares approach.
:param f0, f1, f2: Functions used to build the general equation.
:type f0, f1, f2: function
:returns: 'a', 'b', 'c' coefficients of best general equation fit.
:rtype: tuple
:raises: ZeroDivisionError if input functions are null or input data
leads to a division by zero
>>> cf4 = CurveFitting([3, 20, 34, 50, 75, 88, 111, 129, 143, 160, 183,
... 200, 218, 230, 248, 269, 290, 303, 320, 344],
... [0.0433, 0.2532, 0.3386, 0.3560, 0.4983, 0.7577,
... 1.4585, 1.8628, 1.8264, 1.2431, -0.2043,
... -1.2431, -1.8422, -1.8726, -1.4889, -0.8372,
... -0.4377, -0.3640, -0.3508, -0.2126])
>>> def sin1(x): return sin(radians(x))
>>> def sin2(x): return sin(radians(2.0*x))
>>> def sin3(x): return sin(radians(3.0*x))
>>> a, b, c = cf4.general_fitting(sin1, sin2, sin3)
>>> print("a = {}; b = {}; c = {}".format(round(a, 2), round(b, 2),
... round(c, 2)))
a = 1.2; b = -0.77; c = 0.39
>>> cf5 = CurveFitting([0, 1.2, 1.4, 1.7, 2.1, 2.2])
>>> a, b, c = cf5.general_fitting(sqrt)
>>> print("a = {}; b = {}; c = {}".format(round(a, 3), round(b, 3),
... round(c, 3)))
a = 1.016; b = 0.0; c = 0.0
"""
m = 0
p = 0
q = 0
r = 0
s = 0
t = 0
u = 0
v = 0
w = 0
xl = list(self._x)
yl = list(self._y)
for i, value in enumerate(xl):
x = value
y = yl[i]
m += f0(x) * f0(x)
p += f0(x) * f1(x)
q += f0(x) * f2(x)
r += f1(x) * f1(x)
s += f1(x) * f2(x)
t += f2(x) * f2(x)
u += y * f0(x)
v += y * f1(x)
w += y * f2(x)
if abs(r) < TOL and abs(t) < TOL and abs(m) >= TOL:
return (u / m, 0.0, 0.0)
if abs(m * r * t) < TOL:
> raise ZeroDivisionError("Invalid input functions: They are null")
E ZeroDivisionError: Invalid input functions: They are null
pymeeus/CurveFitting.py:467: ZeroDivisionError
__________________________________________________________________________________ test_interpolation_call __________________________________________________________________________________
def test_interpolation_call():
"""Tests the __call__() method of Interpolation class"""
m = Interpolation([-1.0, 0.0, 1.0], [-2.0, 3.0, 2.0])
assert abs(m(-0.8) - (-0.52)) < TOL, \
"ERROR: In 1st __call__() test, output value doesn't match"
assert abs(m(0.7) - 2.93) < TOL, \
"ERROR: In 2nd __call__() test, output value doesn't match"
assert abs(m(-1.0) - (-2.0)) < TOL, \
"ERROR: In 3rd __call__() test, output value doesn't match"
m = Interpolation([-3.0, 0.0, 2.5], [12.0, -3.0, -1.75])
assert abs(m(-2.0) - 5.0) < TOL, \
"ERROR: In 4th __call__() test, output value doesn't match"
assert abs(m(2.5) - (-1.75)) < TOL, \
"ERROR: In 5th __call__() test, output value doesn't match"
# This interpolation test uses Right Ascension
> a = Angle(i_ra(11.0))
tests/test_interpolation.py:118:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = Interpolation([], []), x = 11.0
def __call__(self, x):
"""Method to interpolate the function at a given 'x'.
:param x: Point where the interpolation will be carried out.
:type x: int, float, :py:class:`Angle`
:returns: Resulting value of the interpolation.
:rtype: float
:raises: ValueError if input value is outside of interpolation range.
:raises: TypeError if input value is of wrong type.
>>> i = Interpolation([7, 8, 9], [0.884226, 0.877366, 0.870531])
>>> y = round(i(8.18125), 6)
>>> print(y)
0.876125
"""
# Check if input value is of correct type
if isinstance(x, (int, float, Angle)):
# Check if 'x' already belongs to the data table
for i in range(len(self._x)):
if abs(x - self._x[i]) < self._tol:
return self._y[i] # We don't need to look further
# Check if Newton coefficients table is not empty
if len(self._table) == 0:
> raise RuntimeError("Internal table is empty. Use set().")
E RuntimeError: Internal table is empty. Use set().
pymeeus/Interpolation.py:404: RuntimeError
_______________________________________________________________________________ test_interpolation_derivative _______________________________________________________________________________
def test_interpolation_derivative():
"""Tests the derivative() method of Interpolation class"""
m = Interpolation([-1.0, 0.0, 1.0], [-2.0, 3.0, 2.0])
assert abs(m.derivative(-1.0) - 8.0) < TOL, \
"ERROR: In 1st derivative() test, output value doesn't match"
assert abs(m.derivative(0.0) - 2.0) < TOL, \
"ERROR: In 2nd derivative() test, output value doesn't match"
assert abs(m.derivative(0.5) - (-1.0)) < TOL, \
"ERROR: In 3rd derivative() test, output value doesn't match"
m = Interpolation([-3.0, 0.0, 2.5], [12.0, -3.0, -1.75])
assert abs(m.derivative(-3.0) - (-8.0)) < TOL, \
"ERROR: In 4th derivative() test, output value doesn't match"
assert abs(m.derivative(0.0) - (-2.0)) < TOL, \
"ERROR: In 5th derivative() test, output value doesn't match"
assert abs(m.derivative(2.5) - 3.0) < TOL, \
"ERROR: In 6th derivative() test, output value doesn't match"
# Do test with an interpolation object with 6 table entries, based on sine
# We need to adjust the result because degrees were used instead of radians
> res = degrees(i_sine.derivative(30.0))
tests/test_interpolation.py:158:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = Interpolation([], []), x = 30.0
def derivative(self, x):
"""Method to compute the derivative from interpolation polynomial.
:param x: Point where the interpolation derivative will be carried out.
:type x: int, float, :py:class:`Angle`
:returns: Resulting value of the interpolation derivative.
:rtype: float
:raises: ValueError if input value is outside of interpolation range.
:raises: TypeError if input value is of wrong type.
>>> m = Interpolation([-1.0, 0.0, 1.0], [-2.0, 3.0, 2.0])
>>> m.derivative(-1.0)
8.0
>>> m.derivative(0.5)
-1.0
"""
# Check if input value is of correct type
if isinstance(x, (int, float, Angle)):
# Check that x is within interpolation table values
> if x < self._x[0] or x > self._x[-1]:
E IndexError: list index out of range
pymeeus/Interpolation.py:438: IndexError
__________________________________________________________________________________ test_interpolation_root __________________________________________________________________________________
def test_interpolation_root():
"""Tests the root() method of Interpolation class"""
m = Interpolation([-1.0, 0.0, 1.0], [-2.0, 3.0, 2.0])
assert abs(m.root() - (-0.7207592200561265)) < TOL, \
"ERROR: In 1st root() test, output value doesn't match"
m = Interpolation([-3.0, 0.0, 2.5], [12.0, -3.0, -1.75])
assert abs(m.root(-2.0, 0.0) - (-1.0)) < TOL, \
"ERROR: In 2nd root() test, output value doesn't match"
assert abs(m.root() - (-1.0)) < TOL, \
"ERROR: In 3rd root() test, output value doesn't match"
m = Interpolation([-3.0, 0.0, 2.5, 3.5], [12.0, -3.0, -1.75, 2.25])
assert abs(m.root(0.0, 3.15) - 3.0) < TOL, \
"ERROR: In 4th root() test, output value doesn't match"
# Let's do some tests with Angles
> assert abs(i_angles1.root() - 26.798732705) < TOL, \
"ERROR: In 5th root() test, output value doesn't match"
tests/test_interpolation.py:185:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = Interpolation([], []), xl = 0, xh = 0, max_iter = 1000
def root(self, xl=0, xh=0, max_iter=1000):
"""Method to find the root inside the [xl, xh] range.
This method applies, in principle, the Newton method to find the root;
however, if conditions are such that Newton method may not bei properly
behaving or converging, then it switches to the linear Interpolation
method.
If values xl, xh are not given, the limits of the interpolation table
values will be used.
.. note:: This method returns a ValueError exception if the
corresponding yl = f(xl) and yh = f(xh) values have the same sign.
In that case, the method assumes there is no root in the [xl, xh]
interval.
.. note:: If any of the xl, xh values is beyond the limits given by the
interpolation values, its value will be set to the corresponding
limit.
.. note:: If xl == xh (and not zero), a ValueError exception is raised.
.. note:: If the method doesn't converge within max_iter ierations,
then a ValueError exception is raised.
:param xl: Lower limit of interval where the root will be looked for.
:type xl: int, float, :py:class:`Angle`
:param xh: Higher limit of interval where the root will be looked for.
:type xh: int, float, :py:class:`Angle`
:param max_iter: Maximum number of iterations allowed.
:type max_iter: int
:returns: Root of the interpolated function within [xl, xh] interval.
:rtype: int, float, :py:class:`Angle`
:raises: ValueError if yl = f(xl), yh = f(xh) have same sign.
:raises: ValueError if xl == xh.
:raises: ValueError if maximum number of iterations is exceeded.
:raises: TypeError if input value is of wrong type.
>>> m = Interpolation([-1.0, 0.0, 1.0], [-2.0, 3.0, 2.0])
>>> round(m.root(), 8)
-0.72075922
"""
# Get the limits of the interpolation table
> xmin = self._x[0]
E IndexError: list index out of range
pymeeus/Interpolation.py:503: IndexError
================================================================================== short test summary info ==================================================================================
FAILED tests/test_curvefitting.py::test_curvefitting_correlation_coeff - AttributeError: 'CurveFitting' object has no attribute '_N'
FAILED tests/test_curvefitting.py::test_curvefitting_linear_fitting - AttributeError: 'CurveFitting' object has no attribute '_N'
FAILED tests/test_curvefitting.py::test_curvefitting_quadratic_fitting - AttributeError: 'CurveFitting' object has no attribute '_N'
FAILED tests/test_curvefitting.py::test_curvefitting_general_fitting - ZeroDivisionError: Invalid input functions: They are null
FAILED tests/test_interpolation.py::test_interpolation_call - RuntimeError: Internal table is empty. Use set().
FAILED tests/test_interpolation.py::test_interpolation_derivative - IndexError: list index out of range
FAILED tests/test_interpolation.py::test_interpolation_root - IndexError: list index out of range
=============================================================================== 7 failed, 244 passed in 1.93s ===============================================================================
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