Exemple #1
0
    def __init__(self, app, ini=None, base_dir=None):
        """
        Initialize of GUI components.
        """
        super(MainWindow, self).__init__()

        if base_dir is None: base_dir = batchJob.getCodeRootPath()
        os.chdir(base_dir)
        self.updating = False
        self.app = app
        self.base_dir = base_dir

        # GUI setup
        self.createWidgets()
        self.createActions()
        self.createMenus()
        self.createStatusBar()

        self.setAttribute(Qt.WA_DeleteOnClose)
        self.setWindowTitle("GetDist GUI")

        # Allow to shutdown the GUI with Ctrl+C
        signal.signal(signal.SIGINT, signal.SIG_DFL)

        # Path for .ini file
        self.iniFile = ini or MCSamples.default_getdist_settings

        # Path of root directory
        self.rootdirname = None

        self.plot_module = 'GetDistPlots'

        self._resetGridData()
        self._resetPlotData()

        lastDir = self.getSettings().value('lastSearchDirectory')
        if lastDir:
            self.openDirectory(lastDir)
Exemple #2
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def BAOdensity(prob_file):
    d = loadtxt(prob_file)
    ix = 0
    prob = np.zeros((alpha_npoints, alpha_npoints))
    alpha_perp = np.zeros(alpha_npoints)
    alpha_pl = np.zeros(alpha_npoints)
    for i in range(alpha_npoints):
        for j in range(alpha_npoints):
            alpha_perp[i] = d[ix, 0]
            alpha_pl[j] = d[ix, 1]
            prob[j, i] = d[ix, 2]
            ix += 1
    prob = prob / np.max(prob)
    return alpha_perp, alpha_pl, prob

alpha_perp, alpha_pl, prob = BAOdensity(batchJob.getCodeRootPath() + 'data/sdss_DR11CMASS_consensus.dat')


densityG = BAOdensityG()

perp = alpha_perp * DA_fid
para = H_fid / alpha_pl

density = GetDistPlots.Density2D()
density.pts = prob
density.x1 = perp
density.x2 = para
density.contours = exp(-np.array([1.509, 2.4477]) ** 2 / 2)

root = 'base_plikHM_TT_lowTEB_lensing'
Exemple #3
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    FAP, f8 = np.meshgrid(FAP, f8)
    like = (FAP - FAPbar) ** 2 * invcov[0, 0] + 2 * (FAP - FAPbar) * (f8 - f8bar) * invcov[0, 1] + (f8 - f8bar) ** 2 * invcov[1, 1]

    density = GetDistPlots.Density2D()
    density.pts = exp(-like / 2)
    density.x1 = FAP
    density.x2 = f8
    density.contours = exp(-np.array([1.509, 2.4477]) ** 2 / 2)
    return density



FAPbar = 0.6725
f8bar = 0.4412
density = RSDdensity(FAPbar, f8bar, batchJob.getCodeRootPath() + 'data/sdss_DR11CMASS_RSD_bao_invcov_Samushia.txt')
g.add_2d_contours(roots[0], 'FAP057', 'fsigma8z057', filled=True, density=density)


# CS = contourf(FAP, f8, like, origin='lower', levels=[2.279, 5.991], colors='r')


FAPbar = .683
f8bar = 0.422
density = RSDdensity(FAPbar, f8bar, batchJob.getCodeRootPath() + 'data/sdss_DR11CMASS_RSD_bao_invcov_Beutler.txt')
g.add_2d_contours(roots[0], 'FAP057', 'fsigma8z057', filled=False, density=density, ls=':', alpha=0.5)

g.add_2d_contours(roots[0], 'FAP057', 'fsigma8z057', filled=True, plotno=3)


g.add_legend(['BOSS CMASS (Samushia et al.)', 'BOSS CMASS (Beutler et al.)', s.defplanck + '+lensing'], legend_loc='upper left')
Exemple #4
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    d = loadtxt(prob_file)
    ix = 0
    prob = np.zeros((alpha_npoints, alpha_npoints))
    alpha_perp = np.zeros(alpha_npoints)
    alpha_pl = np.zeros(alpha_npoints)
    for i in range(alpha_npoints):
        for j in range(alpha_npoints):
            alpha_perp[i] = d[ix, 0]
            alpha_pl[j] = d[ix, 1]
            prob[j, i] = d[ix, 2]
            ix += 1
    prob = prob / np.max(prob)
    return alpha_perp, alpha_pl, prob


alpha_perp, alpha_pl, prob = BAOdensity(batchJob.getCodeRootPath() +
                                        'data/sdss_DR11CMASS_consensus.dat')

densityG = BAOdensityG()

perp = alpha_perp * DA_fid
para = H_fid / alpha_pl

density = GetDistPlots.Density2D()
density.pts = prob
density.x1 = perp
density.x2 = para
density.contours = exp(-np.array([1.509, 2.4477])**2 / 2)

root = 'base_plikHM_TT_lowTEB_lensing'
Exemple #5
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s = GetDistPlots.defaultSettings
s.legend_frame = False
s.figure_legend_frame = False
s.prob_label = r'$P/P_{\rm max}$'
s.norm_prob_label = 'Probability density'
s.prob_y_ticks = True
s.param_names_for_labels = 'clik_units.paramnames'
s.alpha_filled_add = 0.85
s.solid_contour_palefactor = 0.6

s.solid_colors = [('#8CD3F5', '#006FED'), ('#F7BAA6', '#E03424'), ('#D1D1D1', '#A1A1A1'), 'g', 'cadetblue', 'indianred']
s.axis_marker_lw = 0.6
s.lw_contour = 1

use_plot_data = MCSamples.use_plot_data
rootdir = MCSamples.default_grid_root or os.path.join(batchJob.getCodeRootPath(), 'main')
output_base_dir = MCSamples.output_base_dir or batchJob.getCodeRootPath()

H0_gpe = [70.6, 3.3]

# various Omegam sigma8 constraints for plots
def planck_lensing(omm, sigma):
    # g60_full
    return  (0.591 + 0.021 * sigma) * omm ** (-0.25)


def plotBounds(omm, data, c='gray'):
    pylab.fill_between(omm, data(omm, -2), data(omm, 2), facecolor=c, alpha=0.15, edgecolor=c, lw=0)
    pylab.fill_between(omm, data(omm, -1), data(omm, 1), facecolor=c, alpha=0.25, edgecolor=c, lw=0)