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")