コード例 #1
0
def _profiles_contour(profiles, contours=_CONTOURS, npoints=200):
    import pylab

    any_magnetic = False
    for p in profiles.values():
        # Find limits of all profiles
        z = np.hstack([line[0] for line in p])
        zp = np.linspace(np.min(z), np.max(z), npoints)
        if len(p[0]) == 3:
            rho_color = next_color()
            # Interpolate rho on common z
            rho = np.vstack([np.interp(zp, L[0], L[1]) for L in p])
            # Plot the quantiles
            plot_quantiles(zp, rho, contours, rho_color)
            # Plot the best
            pylab.plot(zp, rho[0], '-', color=dhsv(rho_color, dv=-0.2))
        else:
            any_magnetic = True
            rho_color = next_color()
            rhoM_color = next_color()
            # Interpolate rho, rhoM on common z
            rho = np.vstack([np.interp(zp, L[0], L[1]) for L in p])
            rhoM = np.vstack([np.interp(zp, L[0], L[3]) for L in p])
            # Plot the quantiles
            plot_quantiles(zp, rho, contours, rho_color)
            plot_quantiles(zp, rhoM, contours, rhoM_color)
            # Plot the best
            pylab.plot(zp, rho[0], '-', color=dhsv(rho_color, dv=-0.2))
            pylab.plot(zp, rhoM[0], '-', color=dhsv(rhoM_color, dv=-0.2))
    _profiles_labels(any_magnetic)
コード例 #2
0
def _profiles_overplot(profiles):
    import pylab

    alpha = 0.1
    any_magnetic = False
    for p in profiles.values():
        if len(p[0]) == 3:
            rho_color = next_color()
            for z, rho, _ in p[1:]:
                pylab.plot(z, rho, '-', color=rho_color, alpha=alpha)
            # Plot best
            z, rho, _ = p[0]
            pylab.plot(z, rho, '-', color=dhsv(rho_color, dv=-0.2))
        else:
            any_magnetic = True
            rho_color = next_color()
            rhoM_color = next_color()
            for z, rho, _, rhoM, _ in p[1:]:
                pylab.plot(z, rho, '-', color=rho_color, alpha=alpha)
                pylab.plot(z, rhoM, '-', color=rhoM_color, alpha=alpha)
            # Plot best
            z, rho, _, rhoM, _ = p[0]
            pylab.plot(z, rho, '-', color=dhsv(rho_color, dv=-0.2))
            pylab.plot(z, rhoM, '-', color=dhsv(rhoM_color, dv=-0.2))
    _profiles_labels(any_magnetic)
コード例 #3
0
ファイル: errors.py プロジェクト: ohcpaull/refl1d
def _profiles_overplot(profiles):
    for model, group in profiles.items():
        name = model.name
        absorbing = any((L[2] != 1e-4).any() for L in group)
        magnetic = (len(group[0]) > 3)
        # Note: Use 3 colours per dataset for consistency
        _draw_overplot(group, 1, name + ' rho')
        if absorbing:
            _draw_overplot(group, 2, name + ' irho')
        else:
            next_color()
        if magnetic:
            _draw_overplot(group, 3, name + ' rhoM')
        else:
            next_color()
    _profile_labels()
コード例 #4
0
ファイル: errors.py プロジェクト: ohcpaull/refl1d
def _residuals_contour(Q, residuals, contours=CONTOURS):
    import matplotlib.pyplot as plt
    shift = 0
    for m, r in residuals.items():
        color = next_color()
        plot_quantiles(Q[m], shift + r.T, contours, color)
        plt.plot(Q[m],
                 shift + r[:, 0],
                 '.',
                 label=m.name,
                 markersize=1,
                 color=dark(color))
        # Use 3 colours from cycle so reflectivity matches rho for each dataset
        next_color()
        next_color()
        shift += 5
    _residuals_labels()
コード例 #5
0
ファイル: errors.py プロジェクト: ohcpaull/refl1d
def _draw_contours(group, index, label, zp, contours):
    import matplotlib.pyplot as plt
    color = next_color()
    # Interpolate on common z
    fp = np.vstack([np.interp(zp, L[0], L[index]) for L in group])
    # Plot the quantiles
    plot_quantiles(zp, fp, contours, color)
    # Plot the best
    plt.plot(zp, fp[0], '-', label=label, color=dark(color))
コード例 #6
0
ファイル: errors.py プロジェクト: ohcpaull/refl1d
def _draw_overplot(group, index, label):
    import matplotlib.pyplot as plt
    alpha = 0.1
    color = next_color()
    for L in group[1:]:
        plt.plot(L[0], L[index], '-', color=color, alpha=alpha)
    # Plot best
    L = group[0]
    plt.plot(L[0], L[index], '-', label=label, color=dark(color))
コード例 #7
0
def _residuals_contour(Q, residuals, contours=_CONTOURS):
    import pylab
    shift = 0
    for m, r in residuals.items():
        color = next_color()
        plot_quantiles(Q[m], shift+r.T, contours, color)
        pylab.plot(Q[m], shift+r[:, 0], '.', markersize=1,
                   color=dhsv(color, dv=-0.2)) # best
        shift += 5
    _residuals_labels()
コード例 #8
0
ファイル: errors.py プロジェクト: ohcpaull/refl1d
def _profiles_contour(profiles, contours=CONTOURS, npoints=200):
    for model, group in profiles.items():
        name = model.name
        absorbing = any((L[2] > 1e-4).any() for L in group)
        magnetic = (len(group[0]) > 3)
        # Find limits of all profiles
        z = np.hstack([line[0] for line in group])
        zp = np.linspace(np.min(z), np.max(z), npoints)
        # Note: Use 3 colours per dataset for consistency
        _draw_contours(group, 1, name + ' rho', zp, contours)
        if absorbing:
            _draw_contours(group, 2, name + ' irho', zp, contours)
        else:
            next_color()
        if magnetic:
            _draw_contours(group, 3, name + ' rhoM', zp, contours)
        else:
            next_color()
    _profile_labels()
コード例 #9
0
def _residuals_overplot(Q, residuals):
    import pylab
    alpha = 0.4
    shift = 0
    for m, r in residuals.items():
        color = next_color()
        pylab.plot(Q[m], shift+r[:, 1:], '.', markersize=1,
                   color=color, alpha=alpha)
        pylab.plot(Q[m], shift+r[:, 0], '.', markersize=1,
                   color=dhsv(color, dv=-0.2)) # best
        shift += 5
    _residuals_labels()
コード例 #10
0
ファイル: errors.py プロジェクト: ohcpaull/refl1d
def _residuals_overplot(Q, residuals):
    import matplotlib.pyplot as plt
    alpha = 0.4
    shift = 0
    for m, r in residuals.items():
        color = next_color()
        plt.plot(Q[m],
                 shift + r[:, 1:],
                 '.',
                 markersize=1,
                 color=color,
                 alpha=alpha)
        plt.plot(Q[m],
                 shift + r[:, 0],
                 '.',
                 label=m.name,
                 markersize=1,
                 color=dark(color))
        # Use 3 colours from cycle so reflectivity matches rho for each dataset
        next_color()
        next_color()
        shift += 5
    _residuals_labels()