def test_intensity_black_body(clib, nu, T):
func = clib.intensity_black_body
func.restype = c_double
func.argtypes = [c_double, c_double]
actual = func(nu, T)
expected = intensity_black_body(nu, T)
ntest.assert_almost_equal(actual, expected)
def test_intensity_black_body(clib, nu, T):
func = clib.intensity_black_body
func.restype = c_double
func.argtypes = [c_double, c_double]
actual = func(nu, T)
expected = intensity_black_body(nu, T)
ntest.assert_almost_equal(
actual,
expected
)
def calculate(self, lines, nu, t_rad, w, j_blues_norm_factor,
j_blue_estimator):
# Used for initialization
if len(j_blue_estimator) == 0:
return JBluesDiluteBlackBody.calculate(lines, nu, t_rad, w)
else:
j_blues = pd.DataFrame(j_blue_estimator *
j_blues_norm_factor.value,
index=lines.index,
columns=np.arange(len(t_rad)))
for i in xrange(len(t_rad)):
zero_j_blues = j_blues[i] == 0.0
j_blues[i][zero_j_blues] = (
self.w_epsilon *
intensity_black_body(nu[zero_j_blues].values, t_rad[i]))
return j_blues
def calculate(self, lines, nu, t_rad, w, j_blues_norm_factor,
j_blue_estimator):
# Used for initialization
if len(j_blue_estimator) == 0:
return JBluesDiluteBlackBody.calculate(lines, nu, t_rad, w)
else:
j_blues = pd.DataFrame(
j_blue_estimator *
j_blues_norm_factor.value,
index=lines.index,
columns=np.arange(len(t_rad)))
for i in range(len(t_rad)):
zero_j_blues = j_blues[i] == 0.0
j_blues[i][zero_j_blues] = (
self.w_epsilon *
intensity_black_body(nu[zero_j_blues].values,
t_rad[i]))
return j_blues
def test_intensity_black_body(nu, t, i):
assert np.isclose(intensity_black_body(nu, t), i)
def calculate(lines, nu, t_rad, w):
j_blues = w * intensity_black_body(nu.values[np.newaxis].T, t_rad)
j_blues = pd.DataFrame(j_blues,
index=lines.index,
columns=np.arange(len(t_rad)))
return j_blues
def test_intensity_black_body(nu, t, i):
assert np.isclose(intensity_black_body(nu, t), i)
def test_intensity_black_body(nu, T):
func = formal_integral.intensity_black_body
actual = func(nu, T)
print(actual, type(actual))
expected = intensity_black_body(nu, T)
ntest.assert_almost_equal(actual, expected)
def calculate(lines, nu, t_rad, w):
j_blues = w * intensity_black_body(nu.values[np.newaxis].T, t_rad)
j_blues = pd.DataFrame(j_blues, index=lines.index,
columns=np.arange(len(t_rad)))
return j_blues
def test_intensity_black_body(nu, t, i):
assert float(intensity_black_body(nu, t)) == i
def test_intensity_black_body(nu, t, i):
assert float(intensity_black_body(nu, t)) == i