Пример #1
0
def test_plot_scatter():
    # Set the random seed for consistency
    np.random.seed(12)

    fig, ax = plt.subplots(1)

    # The default line style is iterating over color, line, and marker with
    # hollow types.
    linestyle = mpltex.linestyle_generator(colors=[],
                                           lines=['-',':'],
                                           markers=['o','s'],
                                           hollow_styles=[False, False, True, True],
                                           )
    for i in range(8):
        y = np.random.normal(size=10).cumsum()
        x = np.arange(10)
        ax.plot(x, y, label=str(i), **linestyle.next())

    ax.locator_params(nbins=5)
    ax.set_xlabel('Number of steps')
    ax.set_ylabel('Distance')
    ax.legend(loc='best', ncol=4)

    fig.tight_layout(pad=0.1)
    fig.savefig('test_special_custom_linestyle_generator')
Пример #2
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def test_plot_scatter():
    # Set the random seed for consistency
    np.random.seed(12)

    fig, ax = plt.subplots(1)

    # The default line style is iterating over color, line, and marker with
    # hollow types.
    linestyle = mpltex.linestyle_generator(
        colors=[],
        lines=['-', ':'],
        markers=['o', 's'],
        hollow_styles=[False, False, True, True],
    )
    for i in range(8):
        y = np.random.normal(size=10).cumsum()
        x = np.arange(10)
        ax.plot(x, y, label=str(i), **next(linestyle))

    ax.locator_params(nbins=5)
    ax.set_xlabel('Number of steps')
    ax.set_ylabel('Distance')
    ax.legend(loc='best', ncol=4)

    fig.tight_layout(pad=0.35)
    fig.savefig('test_special_custom_linestyle_generator')
Пример #3
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def plot_fig():
    data = np.loadtxt("all.dat", 
                    dtype={'names': ('folder', 'x', 'dA/dx', 'err', 'A'),
                         'formats': ('S20', 'f4', 'f4', 'f4', 'f4')})
    xcut = 27.5 # free energy beyong 27.5 is too large
    x0 = 28.36  # the top layer of Cu
    
    x, y = [], []
    for i in range(len(data)):
        tx = data[i][1]
        ty = data[i][4]
        if tx < xcut:
            x.append(x0-tx)
            y.append(data[i][4])

    fig, ax = plt.subplots(1)
    linestyle = mpltex.linestyle_generator(
                colors=["black", "green", "red"],
                lines=['-',':'], markers=['o','s'], 
                hollow_styles=[False, False, True, True],
                )

    ax.plot(x, y, label="", 
            **linestyle.next())
    ax.set_xlim([0, 9])
    #ax.yaxis.set_ticks([0, 1, 2, 3, 4, 5, 6])

    ax.set_xlabel("z$_I$ ($\AA$)")
    ax.set_ylabel("Free Energy (kcal/mol)")
    ax.legend(loc='best')
    fig.tight_layout(pad=0.1)
    fig.savefig("test.png", dpi=600)
Пример #4
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def plot_fig():
    data = np.loadtxt("dA.dat") 
    data = data.transpose() 
    
    x, y = data[0], data[1]
    y_int = integrate.cumtrapz(y, x, initial=0)

    linestyle = mpltex.linestyle_generator(
                colors=["black", "green", "red"],
                lines=['-',':'], markers=['o','s'], 
                hollow_styles=[False, False, True, True],
                )

    fig, ax = plt.subplots(1)
    ax.plot(x[::50], y_int[::50], label="FE",
             **linestyle.next())

    ax.set_xlabel("r$_{C-O}$ ($\AA$)")
    ax.set_ylabel("FE (eV)")
    ax.legend(loc='best')

    ax2 = ax.twinx()
    ax2.plot(x[::50], y[::50], label="PMF", 
            **linestyle.next())
    ax2.set_ylabel("PMF (eV/$\AA$)", color="green")
    ax2.legend(loc='lower left')

    fig.tight_layout(pad=0.1)
    fig.savefig("test.png", dpi=600)
    o = open("all.dat", "w")
    for i in range(len(x)):
        o.write("%12.4f%12.4f%12.4f\n"%
                (x[i], y[i], y_int[i]))
    o.close()
Пример #5
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def plot_fig_fe_pmf():
    data = get_fe()

    x, y, yerr = data[0], data[1], data[2]
    y_int = integrate.cumtrapz(y, x, initial=0)

    linestyle = mpltex.linestyle_generator(
        colors=["black", "green", "red"],
        lines=['-', ':'],
        markers=['o', 's'],
        hollow_styles=[False, False, True, True],
    )

    fig, ax = plt.subplots(1)
    ax.plot(x, y_int, label="FE", **linestyle.next())

    ax.set_xlabel("r$_{C-O}$ ($\AA$)")
    ax.set_ylabel("FE (eV)")
    ax.legend(loc='best')

    ax2 = ax.twinx()
    ax2.errorbar(x, y, yerr=yerr, label="PMF", **linestyle.next())
    ax2.set_ylabel("PMF (eV/$\AA$)", color="green")
    ax2.legend(loc='lower left')

    fig.tight_layout(pad=0.1)
    fig.savefig("01-fe-pmf.png", dpi=600)
    o = open("all.dat", "w")
    o.write('# CV PMF PMF(Error) Int\n')
    for i in range(len(x)):
        o.write("%12.4f%12.4f%12.4f%12.4f\n" % (x[i], y[i], yerr[i], y_int[i]))
    o.close()
Пример #6
0
def plot_fig():
    data = np.loadtxt("all.dat",
                      dtype={
                          'names': ('folder', 'x', 'dA/dx', 'err', 'A'),
                          'formats': ('S20', 'f4', 'f4', 'f4', 'f4')
                      })
    xcut = 27.5  # free energy beyong 27.5 is too large
    x0 = 28.36  # the top layer of Cu

    x, y = [], []
    for i in range(len(data)):
        tx = data[i][1]
        ty = data[i][4]
        if tx < xcut:
            x.append(x0 - tx)
            y.append(data[i][4])

    fig, ax = plt.subplots(1)
    linestyle = mpltex.linestyle_generator(
        colors=["black", "green", "red"],
        lines=['-', ':'],
        markers=['o', 's'],
        hollow_styles=[False, False, True, True],
    )

    ax.plot(x, y, label="", **linestyle.next())
    ax.set_xlim([0, 9])
    #ax.yaxis.set_ticks([0, 1, 2, 3, 4, 5, 6])

    ax.set_xlabel("z$_I$ ($\AA$)")
    ax.set_ylabel("Free Energy (kcal/mol)")
    ax.legend(loc='best')
    fig.tight_layout(pad=0.1)
    fig.savefig("test.png", dpi=600)
Пример #7
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def plot_fig():
    data = np.loadtxt("fe.dat") 
    data = data.transpose() 
    
    x, y, yerr = data[0], data[1], data[2]
    y_int = integrate.cumtrapz(y, x, initial=0)

    linestyle = mpltex.linestyle_generator(
                colors=["black", "green", "red"],
                lines=['-',':'], markers=['o','s'], 
                hollow_styles=[False, False, True, True],
                )

    fig, ax = plt.subplots(1)
    ax.plot(x, y_int, label="FE",
             **linestyle.next())

    ax.set_xlabel("r$_{C-O}$ ($\AA$)")
    ax.set_ylabel("FE (eV)")
    ax.legend(loc='best')

    ax2 = ax.twinx()
    ax2.errorbar(x, y, yerr=yerr, label="PMF", 
            **linestyle.next())
    ax2.set_ylabel("PMF (eV/$\AA$)", color="green")
    ax2.legend(loc='lower left')

    fig.tight_layout(pad=0.1)
    fig.savefig("test.png", dpi=600)
    o = open("all.dat", "w")
    for i in range(len(x)):
        o.write("%12.4f%12.4f%12.4f%12.4f\n"%
                (x[i], y[i], yerr[i], y_int[i]))
    o.close()
Пример #8
0
def plot_density():
    #base_dir = 'benchmark/BCC'
    data_dir = ['B0.5_C25_scft/scft_out_943.mat',
                'B0.5_C25_fts/fts_out_50000.mat',
                'B25_C0.5_scft/scft_out_788.mat',
                'B25_C0.5_fts/fts_out_50000.mat',
                ]
    is_cl = [False, True, False, True]
    labels = ['SCFT, $B=0.5, C=25$',
              'CL, $B=0.5, C=25$',
              'SCFT, $B=25, C=0.5$',
              'CL, $B=25, C=0.5$',
              ]

    fig, ax = plt.subplots(1)
    linestyle = mpltex.linestyle_generator(lines=['-'], markers=[])

    i = 0
    for f in data_dir:
        print 'Processing ', f
        try:
            mat = loadmat(f)
        except:
            print 'Missing datafile', f
            continue
        x = mat['x']
        x = x.reshape(x.size)
        if is_cl[i]:
            phi = mat['phi_avg'].real
            phi = phi.reshape(phi.size)
        else:
            phi = mat['phi']
            phi = phi.reshape(phi.size)
        y = np.arange(-1, 1, 0.01)
        phi = cheb_interpolation_1d(y, phi)
        yp = 0.5 * (y + 1) * (x.max() - x.min())
        ax.plot(yp, phi, label=labels[i], **linestyle.next())
        i += 1

    #ax.set_yscale('log')
    ax.locator_params(nbins=5)
    ax.set_xlabel('$x$')
    ax.set_ylabel('$\phi$')
    #ax.set_xlim([0.4, 0.6])
    #ax.set_ylim([1.71, 1.76])
    ax.legend(loc='best')

    fig.tight_layout(pad=0.1)
    fig.savefig('density_profile')
Пример #9
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def my_plot(name):
    fig, ax = plt.subplots(1)
    linestyles = mpltex.linestyle_generator(markers=[])
    #ax.plot(t, t, label='$t$', **next(linestyles))
    ax.xaxis.set_major_locator(matplotlib.ticker.MultipleLocator(0.05))
    ax.plot(strain, pz,linewidth=1, **next(linestyles),label="Pz")
    ax.plot(strain, py,linewidth=1, **next(linestyles),label="Py")
    ax.plot(strain, px,linewidth=1, **next(linestyles),label="Px")


    ax.set_xlabel('Strain')
    ax.set_ylabel('Stress')
    ax.legend(loc='best', ncol=2)
    plt.grid()
    fig.tight_layout(pad=0.1)
    fig.savefig("plot"+name[:-4])
Пример #10
0
def plot_fig():
    data = np.loadtxt("all_wf.dat",
                      dtype={
                          'names': ('folder', 'x', 'dA/dx', 'err', 'A', 'wf'),
                          'formats': ('S20', 'f4', 'f4', 'f4', 'f4', 'f4')
                      })
    xcut = 27.5  # free energy beyong 27.5 is too large
    x0 = 28.36  # the top layer of Cu

    x, y, wf = [], [], []
    for i in range(len(data)):
        tx = data[i][1]
        ty = data[i][4]
        twf = data[i][5]
        if tx < xcut:
            x.append(x0 - tx)
            y.append(ty)
            wf.append(-twf)

    fig, ax = plt.subplots(1)
    linestyle = mpltex.linestyle_generator(
        colors=["black", "green", "red"],
        lines=['-', ':'],
        markers=['o', 's'],
        hollow_styles=[False, False, True, True],
    )

    ax.plot(x, y, label="Free Energy", **linestyle.next())
    #ax.yaxis.set_ticks([0, 1, 2, 3, 4, 5, 6])
    ax.set_xlabel("z$_I$ ($\AA$)")
    ax.set_ylabel("Free Energy (eV)")
    ax.legend(loc='upper right', bbox_to_anchor=(0.88, 0.97))

    ax2 = ax.twinx()
    ax2.plot(x, wf, label="Work Function", **linestyle.next())
    ax2.set_ylim([-5, -3])
    ax2.set_ylabel("Work Function (eV)", color="green")
    ax2.tick_params(axis='y', colors='green')
    ax2.legend(loc='upper right', bbox_to_anchor=(0.93, 0.87))

    ax.set_xlim([0, 9])
    fig.tight_layout(pad=0.1)
    fig.savefig("test.png", dpi=600)
Пример #11
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def plot_timeseries(t, data, ylabel, figname):
    fig, ax = plt.subplots(1)
    linestyle = mpltex.linestyle_generator(lines=['-'], markers=[],
                                           hollow_styles=[])
    i = 0
    for d in data:
        if t.size > 0:
            ax.plot(t, d, **linestyle.next())
        else:
            ax.plot(d, **linestyle.next())
        i += 1

    ax.locator_params(nbins=5)
    ax.set_xlabel('$t$')
    ax.set_ylabel(ylabel)

    fig.tight_layout(pad=0.1)
    fig.savefig(figname)
    plt.close(fig)
Пример #12
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def plot_spatial(x, data, ylabel, labels, figname):
    fig, ax = plt.subplots(1)
    linestyle = mpltex.linestyle_generator(lines=['-'], markers=['o'],
                                           hollow_styles=[])
    i = 0
    for d in data:
        if len(data) > 1:
            ax.plot(x, d, label=labels[i], **linestyle.next())
        else:
            ax.plot(x, d, **linestyle.next())
        i += 1

    ax.locator_params(nbins=5)
    ax.set_xlabel('$z$')
    ax.set_ylabel(ylabel)
    if len(data) > 1:
        ax.legend(loc='best')

    fig.tight_layout(pad=0.1)
    fig.savefig(figname)
    plt.close(fig)
Пример #13
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def plot_fig():
    data = np.loadtxt(
        "all_wf.dat",
        dtype={"names": ("folder", "x", "dA/dx", "err", "A", "wf"), "formats": ("S20", "f4", "f4", "f4", "f4", "f4")},
    )
    xcut = 27.5  # free energy beyong 27.5 is too large
    x0 = 28.36  # the top layer of Cu

    x, y, wf = [], [], []
    for i in range(len(data)):
        tx = data[i][1]
        ty = data[i][4]
        twf = data[i][5]
        if tx < xcut:
            x.append(x0 - tx)
            y.append(ty)
            wf.append(-twf)

    fig, ax = plt.subplots(1)
    linestyle = mpltex.linestyle_generator(
        colors=["black", "green", "red"], lines=["-", ":"], markers=["o", "s"], hollow_styles=[False, False, True, True]
    )

    ax.plot(x, y, label="Free Energy", **linestyle.next())
    # ax.yaxis.set_ticks([0, 1, 2, 3, 4, 5, 6])
    ax.set_xlabel("z$_I$ ($\AA$)")
    ax.set_ylabel("Free Energy (eV)")
    ax.legend(loc="upper right", bbox_to_anchor=(0.88, 0.97))

    ax2 = ax.twinx()
    ax2.plot(x, wf, label="Work Function", **linestyle.next())
    ax2.set_ylim([-5, -3])
    ax2.set_ylabel("Work Function (eV)", color="green")
    ax2.tick_params(axis="y", colors="green")
    ax2.legend(loc="upper right", bbox_to_anchor=(0.93, 0.87))

    ax.set_xlim([0, 9])
    fig.tight_layout(pad=0.1)
    fig.savefig("test.png", dpi=600)
Пример #14
0
def plot_fig_fe():
    data = get_fe()

    x, y, yerr = data[0], data[1], data[2]
    y_int = integrate.cumtrapz(y, x, initial=0)

    linestyle = mpltex.linestyle_generator(
        colors=["black", "green", "red"],
        lines=['-', ':'],
        markers=['o', 's'],
        hollow_styles=[False, False, True, True],
    )

    fig, ax = plt.subplots(1)
    ax.plot(x, y_int, label="FE", **linestyle.next())

    ax.set_xlabel("r$_{C-O}$ ($\AA$)")
    ax.set_ylabel("FE (eV)")
    ax.legend(loc='best')

    fig.tight_layout(pad=0.1)
    fig.savefig("02-fe.png", dpi=600)
Пример #15
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def plot_iw():
    #base_dir = 'benchmark/BCC'
    data_dir = [#'B0.5_C25_fts_fixphi_run1/fts_out_50000.mat',
                'B0.5_C25_fts_fixscftphi/fts_out_100000.mat',
                #'B0.5_C25_fts_fixscftphi_run1/fts_out_50000.mat',
                #'B0.5_C25_fts_fixscftphi_run2/fts_out_50000.mat',
                #'B0.5_C25_fts_fixscftphi_run3/fts_out_100000.mat',
                'B0.5_C25_fts_fixscftphi_run4/fts_out_100000.mat',
                'B0.5_C25_fts_fixscftphi_run5/fts_out_100000.mat',
                #'B0.5_C25_fts_fixscftphi_run6/fts_out_100000.mat',
                #'B0.5_C25_fts_fixotherphi/fts_out_50000.mat',
                #'B0.5_C25_fts_fixphi_Lx128/fts_out_50000.mat',
                ]
    is_cl = [True, True, True, True, True]
    labels = [#'$\phi_{CL}, L_x=64$',
              '$\phi_{SCFT}, \lambda\Delta t=10^{-6}, t=8 \\times 10^4$',
              #'$\phi_{SCFT}, \lambda\Delta t=10^{-3}, t=3 \\times 10^4$',
              #'$\phi_{SCFT}, \lambda\Delta t=10^{-4}, t=3 \\times 10^4$',
              #'$\phi_{SCFT}, \lambda\Delta t=10^{-4}, t=8 \\times 10^4$',
              '$\phi_{SCFT}, \lambda\Delta t=10^{-5}, t=8 \\times 10^4$',
              '$\phi_{SCFT}, \lambda\Delta t=10^{-5}, t=8 \\times 10^4$',
              #'$\phi_{SCFT}, \lambda\Delta t=10^{-2}, t=8 \\times 10^4$',
              #'$\phi_{other}, L_x=64$',
              #'$\phi_{CL}, L_x=128$'
              ]
    B = [0.5, 0.5, 0.5, 0.5, 0.5]
    C = [25, 25, 25, 25, 25]

    fig, ax = plt.subplots(1)
    linestyle = mpltex.linestyle_generator(lines=['-'], markers=['-o'],
                                           hollow_styles=[])

    i = 0
    for f in data_dir:
        print 'Processing ', f
        try:
            mat = loadmat(f)
        except:
            print 'Missing datafile', f
            continue
        x = mat['x']
        x = x.reshape(x.size)
        if is_cl[i]:
            iw_avg = mat['iw_avg'].real
            iw_avg = iw_avg.reshape(iw_avg.size)
            phi_avg = mat['phi_avg'].real
            phi_avg = phi_avg.reshape(phi_avg.size)
        y = np.arange(-1, 1, 0.01)
        #iw_avg = cheb_interpolation_1d(y, iw_avg)
        phi_avg = cheb_interpolation_1d(y, phi_avg)
        yp = 0.5 * (y + 1) * (x.max() - x.min())
        ax.plot(x, iw_avg, label=labels[i], **linestyle.next())
        i += 1

    #ax.set_yscale('log')
    ax.locator_params(nbins=5)
    ax.set_xlabel('$x$')
    ax.set_ylabel('$<iw>$')
    #ax.set_xlim([0.4, 0.6])
    #ax.set_ylim([1.71, 1.76])
    ax.legend(loc='best')

    fig.tight_layout(pad=0.1)
    fig.savefig('iw_profile')
Пример #16
0
mpl.use('Agg')
import matplotlib.pyplot as plt
import mpltex

@mpltex.acs_decorator
def plot_fig():
<<<<<<< HEAD
    data = np.loadtxt("all.xvg")
=======
    data = np.loadtxt("gofr.dat")
>>>>>>> 2fa3d11b619e5b1e1192c57a96f67798715b647c
    data = data.transpose()
    fig, ax = plt.subplots(1)
    linestyle = mpltex.linestyle_generator(
                colors=["black", "green", "red"],
                lines=['-',':'], markers=['o','s'], 
                hollow_styles=[False, False, True, True],
                )

<<<<<<< HEAD
    ax.plot(data[0][::10]*10, data[1][::10], label="k =  500", 
            **linestyle.next())
    ax.plot(data[2][::10]*10, data[3][::10] + 1.2, label="k = 1000", 
            **linestyle.next())
    ax.plot(data[4][::10]*10, data[5][::10] + 3.3, label="k = 1500", 
            **linestyle.next())
    ax.set_xlim([1.8, 6.7])
    ax.set_xlabel("r$_{Li-N}$ ($\AA$)")
    ax.set_ylabel("Free Energy (kcal/mol)")
    ax.legend(loc='best')
=======
Пример #17
0
def plot_force():
    #base_dir = 'benchmark/BCC'
    data_dir = [#'B0.5_C25_fts_fixphi_run1/fts_out_50000.mat',
                #'B0.5_C25_fts_fixscftphi/fts_out_100000.mat',
                #'B0.5_C25_fts_fixscftphi_run1/fts_out_50000.mat',
                #'B0.5_C25_fts_fixscftphi_run2/fts_out_50000.mat',
                #'B0.5_C25_fts_fixscftphi_run3/fts_out_100000.mat',
                #'B0.5_C25_fts_fixscftphi_run4/fts_out_100000.mat',
                #'B0.5_C25_fts_fixscftphi_run5/fts_out_100000.mat',
                #'B0.5_C25_fts_fixscftphi_run6/fts_out_100000.mat',
                #'B0.5_C25_fts_fixscftphi_run7/fts_out_100000.mat',
                'B25_C0.5_fts_fixclphi_update_phi_imag/fts_out_100000.mat',
                #'B25_C0.5_fts_fixphi/fts_out_50000.mat',
                #'B25_C0.5_fts_fixphi_run1/fts_out_50000.mat',
                #'B25_C0.5_fts_fixscftphi/fts_out_100000.mat',
                #'B25_C0.5_fts_fixscftphi_update_phi_imag/fts_out_150000.mat',
                #'B25_C0.5_fts_fixscftphi_update_phi_imag_run1/fts_out_100000.mat',
                #'B25_C0.5_fts_fixscftphi_update_phi_imag_run2/fts_out_100000.mat',
                #'B0.5_C25_fts_fixscftphi_update_phi_imag_run1/fts_out_100000.mat',
                #'B0.5_C25_fts_fixscftphi_update_phi_imag_run2/fts_out_100000.mat',
                #'B0.5_C25_fts_fixscftphi_update_phi_imag_run3/fts_out_200000.mat',
                #'B0.5_C25_fts_fixotherphi/fts_out_50000.mat',
                #'B0.5_C25_fts_fixphi_Lx128/fts_out_50000.mat',
                ]
    is_cl = [True, True, True, True, True]
    labels = [#'$\phi_{CL}, L_x=64$',
              '$\phi_{CL}, \lambda\Delta t=10^{-3}, t=8 \\times 10^4$',
              #'$\phi_{CL}, \lambda\Delta t=10^{-3}, t=3 \\times 10^4$',
              #'$\phi_{SCFT}, \lambda\Delta t=10^{-3}, t=8 \\times 10^4$',
              #'$\phi_{SCFT}, \lambda\Delta t=10^{-3}, t=1 \\times 10^5$',
              #'$\phi_{SCFT}, \lambda\Delta t=10^{-3}, t=8 \\times 10^4$',
              #'$\phi_{SCFT}, \lambda\Delta t=10^{-3}, t=6 \\times 10^4$',
              #'$\phi_{SCFT}, \lambda\Delta t=10^{-4}, t=5 \\times 10^4$',
              #'$\phi_{SCFT}, \lambda\Delta t=10^{-3}, t=8 \\times 10^4$',
              #'$\phi_{SCFT}, \lambda\Delta t=10^{-3}, t=1.8 \\times 10^5$',
              #'$\phi_{SCFT}, \lambda\Delta t=10^{-3}, t=3 \\times 10^4$',
              #'$\phi_{SCFT}, \lambda\Delta t=10^{-4}, t=3 \\times 10^4$',
              #'$\phi_{SCFT}, \lambda\Delta t=10^{-4}, t=8 \\times 10^4$',
              #'$\phi_{SCFT}, \lambda\Delta t=10^{-5}, t=8 \\times 10^4$',
              #'$\phi_{SCFT}, \lambda\Delta t=10^{-5}, t=8 \\times 10^4$',
              #'$\phi_{SCFT}, \lambda\Delta t=10^{-2}, t=8 \\times 10^4$',
              #'$\phi_{SCFT}, \lambda\Delta t=10^{-6}, t=8 \\times 10^4$',
              #'$\phi_{other}, L_x=64$',
              #'$\phi_{CL}, L_x=128$'
              ]
    B = [0.5, 0.5, 0.5, 0.5, 0.5]
    C = [25, 25, 25, 25, 25]

    fig, ax = plt.subplots(1)
    linestyle = mpltex.linestyle_generator(lines=['-'], markers=['o'],
                                           hollow_styles=[])

    i = 0
    for f in data_dir:
        print 'Processing ', f
        try:
            mat = loadmat(f)
        except:
            print 'Missing datafile', f
            continue
        x = mat['x']
        x = x.reshape(x.size)
        if is_cl[i]:
            iw_avg = mat['iw_avg'].real
            iw_avg = iw_avg.reshape(iw_avg.size)
            phi = mat['phi'].real
            phi = phi.reshape(phi.size)
        y = np.arange(-1, 1, 0.01)
        force = C[i] * phi - iw_avg / B[i]
        print "\tmean force: ", 0.5 * cheb_quadrature_clencurt(force)
        #force = cheb_interpolation_1d(y, force)
        #yp = 0.5 * (y + 1) * (x.max() - x.min())
        ax.plot(x, force, label=labels[i], **linestyle.next())
        i += 1

    #ax.set_yscale('log')
    ax.locator_params(nbins=5)
    ax.set_xlabel('$x$')
    ax.set_ylabel('$<\\frac{\delta H}{\delta \phi}>_{\phi}$')
    #ax.set_xlim([0.4, 0.6])
    #ax.set_ylim([1.71, 1.76])
    ax.legend(loc='best')

    fig.tight_layout(pad=0.1)
    fig.savefig('force_profile')
Пример #18
0
def plot_fig():
    fig, ax = plt.subplots(1)
    linestyle = mpltex.linestyle_generator(
        colors=["black", "black", "red", "red"],
        lines=['-', ':'],
        markers=['o', 'o', '^', '^'],
        hollow_styles=[False, False, True, True],
    )

    # plot data 1
    data = np.loadtxt("gofr_1.dat")
    data = data.transpose()
    x, y = [], []
    for i in range(len(data[0])):
        if i <= 50:
            x.append(data[0][i])
            y.append(data[1][i])
        else:
            if i % 10 == 0:
                x.append(data[0][i])
                y.append(data[1][i])

    ax.plot(x, y, label="I$^-$(bulk)-H", **linestyle.next())

    ax2 = ax.twinx()
    ax2.plot(data[0][::10], data[2][::10], **linestyle.next())

    # plot data 2
    data = np.loadtxt("gofr_2.dat")
    data = data.transpose()
    x, y = [], []
    for i in range(len(data[0])):
        if i <= 50:
            x.append(data[0][i])
            y.append(data[1][i])
        else:
            if i % 10 == 0:
                x.append(data[0][i])
                y.append(data[1][i])
    ax.plot(x, y, label="I*(interface)-H", **linestyle.next())

    # add annodate
    ax2.plot(data[0][::5], data[2][::5], **linestyle.next())

    ax2.plot([3.0, 8.0], [5.0, 5.0], ls="dotted", lw=0.5, color="black")

    ax2.text(7.0, 5.2, "N = 5")

    # set up axis
    ax.set_xlabel("r$_{I-H}$ ($\AA$)")
    ax.yaxis.set_ticks([0, 1, 2, 3, 4, 5, 6])
    ax.set_ylabel("g(r)")
    ax.legend(loc='upper right', bbox_to_anchor=(0.85, 0.95))

    ax2.set_ylim([0.0, 8.0])
    ax2.set_xlim([1.0, 8.0])
    ax2.set_ylabel("$\int$g(r) (N)")

    # output
    fig.tight_layout(pad=0.1)
    fig.savefig("test.png", dpi=600)
Пример #19
0
                bbox_inches=bbox)


if __name__ == "__main__":

    gns_display = [
        'email-Enron', 'email-Eu', 'contact-primary-school',
        'contact-high-school', 'NDC-classes', 'NDC-substances', 'DAWN',
        'congress-bills', 'tags-ask-ubuntu', 'tags-math-sx',
        'threads-ask-ubuntu', 'threads-math-sx', 'coauth-MAG-History',
        'coauth-MAG-Geology', 'coauth-DBLP'
    ]

    linestyle_map = defaultdict(str)
    dotstyle_map = defaultdict(str)
    linestyles = mpltex.linestyle_generator()
    dotstyles = mpltex.linestyle_generator(lines=[])
    for gn in gns_display:
        if gn == "DAWN":  # I don't like pink
            next(linestyles)
            next(dotstyles)
        linestyle_map[gn] = next(linestyles)
        dotstyle_map[gn] = next(dotstyles)
    """ Legnd """
    save_legend(n_cols=3)
    """ Dot plot """
    for neg in ["hub", "clique"]:
        for imb in [10]:
            plot_dots(neg_type=neg, imb=imb, seed=0)
    """ MI Correlation plot """
    for imb in [10, 5, 2, 1]: