我们从Python开源项目中，提取了以下7个代码示例，用于说明如何使用astropy.units.AA。
def plot_profile(wave, flux, line, name): # define the velocity scale [AA / s] vel_aas = (wave - line*(1+zem[i])) / (line*(1+zem[i])) * c # convert to [km / s] vel_kms = vel_aas.to('km/s') # define parameters for the x and y axes ax.set_xlim(xmin, xmax) ax.xaxis.set_minor_locator(minorLocator) ax.tick_params(axis='x', labelsize=xls) ax.set_ylim(0., 1.5) # make the plot ax.plot(vel_kms, flux) # include the name of the line plt.text(xmin+0.03*(xmax-xmin), 0.15, name) # mark the approximate centroid velocity plt.axvline(x=vcen[i], ymin=0., ymax = 1.5, linewidth=1, color='k', linestyle='dotted') plt.axvline(x=vcen[i]+30., ymin=0., ymax = 1.5, linewidth=0.5, color='k') plt.axvline(x=vcen[i]-30., ymin=0., ymax = 1.5, linewidth=0.5, color='k') # label other lines for clarity for k in range(0, len(lines)): vel_off_aas = (lines[k] - line) / line * c vel_off_kms = vel_off_aas.to('km/s') / (u.km / u.s) plt.axvline(x=vcen[i]+vel_off_kms, ymin=0., ymax = 1.5, linewidth=1, color='k', linestyle='dotted') # define the data directory
def plot_profile(wave, flux, line, name): # define the velocity scale [AA / s] vel_aas = (wave - line*(1+zem[i])) / (line*(1+zem[i])) * c # convert to [km / s] vel_kms = vel_aas.to('km/s') # define parameters for the x and y axes ax.set_xlim(xmin, xmax) ax.xaxis.set_minor_locator(minorLocator) ax.tick_params(axis='x', labelsize=xls) ax.set_ylim(0., 3.) # make the plot ax.plot(vel_kms, np.log(1/flux)) # include the name of the line plt.text(xmin+0.03*(xmax-xmin), 2.3, name) # mark the approximate centroid velocity plt.axvline(x=vcen[i], ymin=0., ymax = 1.5, linewidth=1, color='k', linestyle='dotted') plt.axvline(x=vcen[i]+30., ymin=0., ymax = 1.5, linewidth=0.5, color='k') plt.axvline(x=vcen[i]-30., ymin=0., ymax = 1.5, linewidth=0.5, color='k') # label other lines for clarity for k in range(0, len(lines)): vel_off_aas = (lines[k] - line) / line * c vel_off_kms = vel_off_aas.to('km/s') / (u.km / u.s) plt.axvline(x=vcen[i]+vel_off_kms, ymin=0., ymax = 1.5, linewidth=1, color='k', linestyle='dotted') # define the data directory
def get_stellar_mass(self, z=0, rnorm=1., cosmo=Planck15): """ Get M/L, L, stellar mass, as measured in R-band Returns: M/Lr, log10(Lr), log10(stellar_mass) """ from sedpy.observate import Filter import astropy.units as u import astropy.constants as const MLr, MLi, MLk = self.get_M2L() #plt.plot(self.wave, self.spec); print(MLr) rfilt = Filter('sdss_r0') norm_spec = self.get_model(in_place=False)*rnorm #rband_Jy = rfilt.obj_counts(self.wave, norm_spec)/rfilt.ab_zero_counts*3631 #rband_flam = rband_Jy/(3.34e4*rfilt.wave_pivot**2)#*u.erg/u.second/u.cm**2/u.AA #dL = Planck15.luminosity_distance(z) Mr = rfilt.ab_mag(self.wave, norm_spec) - cosmo.distmod(z).value Lr = 10**(-0.4*(Mr-rfilt.solar_ab_mag)) #Lr = (rband_flam*4*np.pi*dL.to(u.cm).value**2)/3.828e+33*rfilt.wave_pivot*(1+z) stellar_mass = Lr*MLr return MLr, np.log10(Lr), np.log10(stellar_mass)
def plot_profile(wave, flux, line, name, fosc): # define the velocity scale [AA / s] vel_aas = (wave - line*(1+zem[i])) / (line*(1+zem[i])) * c # convert to [km / s] vel_kms = vel_aas.to('km/s') # define parameters for the x and y axes ax.set_xlim(xmin, xmax) ax.xaxis.set_minor_locator(minorLocator) ax.tick_params(axis='x', labelsize=xls) ymax = 3.e12 ax.set_ylim(0., ymax) # make the plot (using equations 5 and 8 from Savage & Sembach 1991) ax.plot(vel_kms, np.log(1/flux) / 2.654e-15 / (fosc * line)) # include the name of the line plt.text(xmin+0.03*(xmax-xmin), ymax*0.6, name) # mark the approximate centroid velocity plt.axvline(x=vcen[i], ymin=0., ymax = 1.5, linewidth=1, color='k', linestyle='dotted') plt.axvline(x=vcen[i]+30., ymin=0., ymax = 1.5, linewidth=0.5, color='k') plt.axvline(x=vcen[i]-30., ymin=0., ymax = 1.5, linewidth=0.5, color='k') # label other lines for clarity for k in range(0, len(lines)): vel_off_aas = (lines[k] - line) / line * c vel_off_kms = vel_off_aas.to('km/s') / (u.km / u.s) plt.axvline(x=vcen[i]+vel_off_kms, ymin=0., ymax = 1.5, linewidth=1, color='k', linestyle='dotted') # define the data directory
def calculate(wave, flux, line, fosc): # define the velocity scale [AA / s] vel_aas = (wave - line*(1+zem[i])) / (line*(1+zem[i])) * c # convert to [km / s] vel_kms = vel_aas.to('km/s') # label other lines for clarity tau = np.log(1/flux) for k in range(0, len(lines)): vel_off_aas = (lines[k] - line) / line * c vel_off_kms = vel_off_aas.to('km/s') / (u.km / u.s) return(tau)
def compute_ck2004_response(self, path, verbose=False): """ Computes Castelli & Kurucz (2004) intensities across the entire range of model atmospheres. @path: path to the directory containing ck2004 SEDs @verbose: switch to determine whether computing progress should be printed on screen Returns: n/a """ models = glob.glob(path+'/*M1.000*') Nmodels = len(models) # Store the length of the filename extensions for parsing: offset = len(models[0])-models[0].rfind('.') Teff, logg, abun = np.empty(Nmodels), np.empty(Nmodels), np.empty(Nmodels) InormE, InormP = np.empty(Nmodels), np.empty(Nmodels) if verbose: print('Computing Castelli & Kurucz (2004) passband intensities for %s:%s. This will take a while.' % (self.pbset, self.pbname)) for i, model in enumerate(models): #~ spc = np.loadtxt(model).T -- waaay slower spc = np.fromfile(model, sep=' ').reshape(-1,2).T Teff[i] = float(model[-17-offset:-12-offset]) logg[i] = float(model[-11-offset:-9-offset])/10 sign = 1. if model[-9-offset]=='P' else -1. abun[i] = sign*float(model[-8-offset:-6-offset])/10 spc[0] /= 1e10 # AA -> m spc[1] *= 1e7 # erg/s/cm^2/A -> W/m^3 wl = spc[0][(spc[0] >= self.ptf_table['wl'][0]) & (spc[0] <= self.ptf_table['wl'][-1])] fl = spc[1][(spc[0] >= self.ptf_table['wl'][0]) & (spc[0] <= self.ptf_table['wl'][-1])] fl *= self.ptf(wl) flP = fl*wl InormE[i] = np.log10(fl.sum()/self.ptf_area*(wl[1]-wl[0])) # energy-weighted intensity InormP[i] = np.log10(flP.sum()/self.ptf_photon_area*(wl[1]-wl[0])) # photon-weighted intensity if verbose: if 100*i % (len(models)) == 0: print('%d%% done.' % (100*i/(len(models)-1))) # Store axes (Teff, logg, abun) and the full grid of Inorm, with # nans where the grid isn't complete. self._ck2004_axes = (np.unique(Teff), np.unique(logg), np.unique(abun)) self._ck2004_energy_grid = np.nan*np.ones((len(self._ck2004_axes[0]), len(self._ck2004_axes[1]), len(self._ck2004_axes[2]), 1)) self._ck2004_photon_grid = np.nan*np.ones((len(self._ck2004_axes[0]), len(self._ck2004_axes[1]), len(self._ck2004_axes[2]), 1)) for i, I0 in enumerate(InormE): self._ck2004_energy_grid[Teff[i] == self._ck2004_axes[0], logg[i] == self._ck2004_axes[1], abun[i] == self._ck2004_axes[2], 0] = I0 for i, I0 in enumerate(InormP): self._ck2004_photon_grid[Teff[i] == self._ck2004_axes[0], logg[i] == self._ck2004_axes[1], abun[i] == self._ck2004_axes[2], 0] = I0 # Tried radial basis functions but they were just terrible. #~ self._log10_Inorm_ck2004 = interpolate.Rbf(self._ck2004_Teff, self._ck2004_logg, self._ck2004_met, self._ck2004_Inorm, function='linear') self.content.append('ck2004') self.atmlist.append('ck2004')
def ingest_lines(self): print("Ingesting lines from {}".format(self.data_source.short_name)) for rdr in self.ion_readers: atomic_number = rdr.ion.Z ion_charge = rdr.ion.Ion - 1 ion = Ion.as_unique(self.session, atomic_number=atomic_number, ion_charge=ion_charge) try: bound_lines = rdr.bound_lines except ChiantiIonReaderError: print("Lines not found for ion {} {}".format(convert_atomic_number2symbol(atomic_number), ion_charge)) continue print("Ingesting lines for {} {}".format(convert_atomic_number2symbol(atomic_number), ion_charge)) lvl_index2id = self.get_lvl_index2id(ion) for index, row in bound_lines.iterrows(): # index: (lower_level_index, upper_level_index) lower_level_index, upper_level_index = index try: lower_level_id = int(lvl_index2id.loc[lower_level_index]) upper_level_id = int(lvl_index2id.loc[upper_level_index]) except KeyError: raise IngesterError("Levels from this source have not been found." "You must ingest levels before transitions") # Create a new line line = Line( lower_level_id=lower_level_id, upper_level_id=upper_level_id, data_source=self.data_source, wavelengths=[ LineWavelength(quantity=row["wavelength"]*u.AA, data_source=self.data_source, medium=MEDIUM_VACUUM, method=row["method"]) ], a_values=[ LineAValue(quantity=row["a_value"]*u.Unit("s**-1"), data_source=self.data_source) ], gf_values=[ LineGFValue(quantity=row["gf_value"], data_source=self.data_source) ] ) self.session.add(line)
