def test_plotfits_log_leahy(self):
pe = PSDParEst(self.ps)
t0 = [2.0, 1, 1, 1]
res = pe.fit(self.lpost, t0)
pe.plotfits(res, save_plot=True, log=True)
assert os.path.exists("test_ps_fit.png")
os.unlink("test_ps_fit.png")
def test_plotfits_leahy(self):
pe = PSDParEst(self.ps)
t0 = [2.0, 1, 1, 1]
lpost = PSDPosterior(self.ps, self.model, self.priors)
res = pe.fit(lpost, t0)
pe.plotfits(res, save_plot=True)
assert os.path.exists("test_ps_fit.png")
os.unlink("test_ps_fit.png")
def test_plotfits_leahy(self):
pe = PSDParEst(self.ps)
t0 = [2.0, 1, 1, 1]
lpost = PSDPosterior(self.ps.freq, self.ps.power,
self.model, self.priors, m=self.ps.m)
res = pe.fit(lpost, t0)
pe.plotfits(res, save_plot=True)
assert os.path.exists("test_ps_fit.png")
os.unlink("test_ps_fit.png")
def test_fit_method_works_with_correct_parameter(self):
pe = PSDParEst(self.ps)
lpost = PSDPosterior(self.ps.freq, self.ps.power,
self.model, self.priors, m=self.ps.m)
t0 = [2.0, 1, 1, 1]
res = pe.fit(lpost, t0)
assert isinstance(res, OptimizationResults), "res must be of type " \
"OptimizationResults"
pe.plotfits(res, save_plot=True)
assert os.path.exists("test_ps_fit.png")
os.unlink("test_ps_fit.png")
pe.plotfits(res, save_plot=True, log=True)
assert os.path.exists("test_ps_fit.png")
os.unlink("test_ps_fit.png")
pe.plotfits(res, res2=res, save_plot=True)
assert os.path.exists("test_ps_fit.png")
os.unlink("test_ps_fit.png")
pe.plotfits(res, res2=res, log=True, save_plot=True)
assert os.path.exists("test_ps_fit.png")
os.unlink("test_ps_fit.png")
def test_plotfits_log_pow(self):
ps = Powerspectrum()
ps.freq = self.ps.freq
ps.power = self.ps.power
ps.m = self.ps.m
ps.df = self.ps.df
ps.norm = "none"
pe = PSDParEst(ps)
t0 = [2.0, 1, 1, 1]
res = pe.fit(self.lpost, t0)
pe.plotfits(res, res2=res, save_plot=True, log=True)
assert os.path.exists("test_ps_fit.png")
os.unlink("test_ps_fit.png")
def test_plotfits_pow(self):
t0 = [2.0, 1, 1, 1]
ps = Powerspectrum()
ps.freq = self.ps.freq
ps.power = self.ps.power
ps.m = self.ps.m
ps.df = self.ps.df
ps.norm = "none"
pe = PSDParEst(ps)
lpost = PSDPosterior(self.ps, self.model, self.priors)
res = pe.fit(self.lpost, t0)
pe.plotfits(res, res2=res, save_plot=True)
assert os.path.exists("test_ps_fit.png")
os.unlink("test_ps_fit.png")
