Remove accidentially added plot script from repo

plot_g4iw.py

-# %%
-import h5py
-import matplotlib.pyplot as plt
-from matplotlib import rc
-from matplotlib import rcParams
-from mpl_toolkits.axes_grid1 import make_axes_locatable
-import colorcet as cc
-import numpy as np
-import os
-
-plt.style.use("default")
-
-# rc('font',**{'family':'sans-serif','sans-serif':['Helvetica']})
-# rc("text", usetex=True)
-
-rcParams["text.usetex"] = True
-plt.rcParams['text.latex.preamble'] = [r"""
-    \usepackage{helvet}
-    \usepackage[helvet]{sfmath}
-    """]
-rcParams["legend.fontsize"] = 12
-rcParams["font.family"] = "sans-serif"
-
-# %matplotlib inline
-# plt.rcParams['text.usetex'] = True
-# # plt.rcParams['font.family'] = 'sans-serif'
-# # plt.rcParams['font.sans-serif'] = 'ph'
-# plt.rcParams['legend.fontsize'] = 12
-
-# %%
-directory = "D:/Patrick/02_Studieren/04_Doktorat/Jackknife/DmftRuns"
-# file_name = "two_particle_4_worms.hdf5"
-
-# file_name = "U4_b2_w2_n1e5-2019-07-02-Tue-14-55-45.hdf5"
-# file_name = "U4_b2_w4_n1e5_2019-18-06-Tue-15-53-26.hdf5"
-# file_name = "U4_b2_w8_n1e5-2019-07-02-Tue-13-06-26.hdf5"
-# file_name = "U4_b2_w16_n1e5-2019-07-02-Tue-14-56-27.hdf5"
-# file_name = "U4_b2_w16_n1e4-2019-07-03-Wed-13-15-39.hdf5"
-# file_name = "U4_b2_w16_n1e3-2019-07-03-Wed-14-07-05.hdf5"
-
-# file_name = "U4_b2_w16_n1e5-2019-08-01-Thu-13-32-07.hdf5"
-file_name = "U4_b2_w64_n1e5-2019-07-31-Wed-14-25-02.hdf5"
-
-file_path = os.path.join(directory, file_name)
-f_g = h5py.File(file_path, "r")
-n_worm_groups = f_g[".config"].attrs["general.wormsteps"]
-print("n_worm_steps=" + str(n_worm_groups))
-worm_groups = [s + "/ineq-001/" for s in f_g.keys()
-               if (("worm-" in s) and (s != "worm-last"))]
-g0s = np.array([f_g[worm_group + "g0iw/value"][...]
-                for worm_group in worm_groups])
-compound_indexes = list(f_g[worm_groups[0] + "g4iw-worm/"].keys())
-g4s = []
-for worm_group in worm_groups:
-    g4_groups = [worm_group + "g4iw-worm/" + i + "/value"
-                 for i in compound_indexes]
-    g4 = np.array([f_g[g4_group][...] for g4_group in g4_groups])
-    g4s.append(g4)
-g4s = np.array(g4s)
-mean_g = np.array(f_g["worm-001/ineq-001/g4iw-worm/00001/value"][...])
-error_g = np.array(f_g["worm-001/ineq-001/g4iw-worm/00001/error"][...])
-n_nus_g = mean_g.shape[0]
-print("n_nus=" + str(n_nus_g))
-n_omegas_g = mean_g.shape[2]
-print("n_omegas=" + str(n_omegas_g))
-f_g.close()
-
-# %%
-# Plot real part of 2-particle Green's function from w2dynamics
-omega_g = 0
-n = n_nus_g // 2
-plt.matshow(np.real(mean_g[:, :, omega_g + n_omegas_g//2]), origin="lower",
-            extent=[-n, n, -n, n])
-plt.title(r"$\mathrm{Re}\ G^{(2)}_{\nu,\nu'}(\omega=$" + str(omega_g) + "$)$")
-plt.xlabel(r"$\nu$")
-plt.ylabel(r"$\nu'$")
-plt.colorbar()
-ax = plt.gca()
-ax.xaxis.set_ticks_position("bottom")
-# ax.xaxis.tick_bottom()
-# ax.XAxis.set_ticks_postion("bottom")
-plt.show()
-
-# %%
-# Plot error of the 2-particle Green's function from w2dynamics
-omega_g = 0
-n = n_nus_g // 2
-max_ = np.amax(np.real(mean_g[:, :, omega_g + n_omegas_g//2]))
-min_ = np.amin(np.real(mean_g[:, :, omega_g + n_omegas_g//2]))
-plt.matshow(error_g[:, :, omega_g + n_omegas_g//2], origin="lower",
-            extent=[-n, n, -n, n], vmin=min_, vmax=max_)
-plt.title(r"$\mathrm{Re}\ G^{(2)}_{\nu,\nu'}(\omega=$" + str(omega_g) + "$)$")
-plt.xlabel(r"$\nu$")
-plt.ylabel(r"$\nu'$")
-plt.colorbar()
-ax = plt.gca()
-ax.xaxis.set_ticks_position("bottom")
-plt.show()
-
-# %%
-# Plot a 1D slice of the 2-particle Green's function
-omega_g = 0
-n = 15
-xvalues = [x - n_nus_g//2 + 0.5 for x in range(n_nus_g)]
-plt.errorbar(xvalues,
-             np.real(mean_g[:, n + n_nus_g//2, omega_g + n_omegas_g//2]),
-             yerr=error_g[:, n + n_nus_g//2, omega_g + n_omegas_g//2],
-             label="$\\nu={}$".format(n + 0.5), linewidth=1, elinewidth=0.5,
-             color="red", ecolor="cyan", capsize=1)
-plt.xlabel(r"$\nu'$", fontsize=12)
-plt.ylabel(r"$\mathrm{Re}\ G^{(2)}$", fontsize=12)
-plt.title("$\\omega={}$".format(omega_g))
-plt.axhline(linewidth=0.5)
-plt.axvline(linewidth=0.5)
-plt.legend()
-plt.show()
-
-# %%
-# Plot a 1D slice of the errors of the 2-particle Green's function
-omega_g = 0
-n = 0
-xvalues = [x - n_nus_g//2 + 0.5 for x in range(n_nus_g)]
-plt.plot(xvalues, error_g[:, n + n_nus_g//2, omega_g + n_omegas_g//2], "x-",
-         color="red", label="$\\nu={}$".format(n + 0.5))
-plt.xlabel(r"$\nu'$", fontsize=12)
-plt.ylabel(r"$\Delta G^{(2)}$", fontsize=12)
-plt.title("$\\omega={},\\ Nmeas=1e3$".format(omega_g))
-plt.axhline(linewidth=0.5)
-plt.axvline(linewidth=0.5)
-plt.legend()
-plt.show()
-
-
-# %%
-# Plot covariance matrix of 1P Green's function
-n = g0s.shape[-1] // 2
-covariance = np.cov(g0s[:, 0, 0, :].T)
-# correlation = np.corrcoef(g0s[:,0,0,:].T)
-plt.matshow(np.real(covariance), extent=[-n, n, n, -n], cmap=cc.m_kbc_r)
-plt.title(r"$\mathrm{Re}\ \mathrm{Cov}(G(\nu),G(\nu'))$")
-plt.xlabel(r"$\nu$")
-plt.ylabel(r"$\nu'$")
-plt.colorbar()
-ax = plt.gca()
-ax.xaxis.set_ticks_position("bottom")
-plt.setp([tick.label1 for tick in ax.xaxis.get_major_ticks()], rotation=60,
-         ha="right", va="center", rotation_mode="anchor")
-plt.show()
-
-# %%
-# Plot nu-nu covarinace of 2P Green's function
-omega_g = 0
-n = n_nus_g // 2
-g_slice = np.diagonal(g4s[:, 0, :, :, omega_g + n_omegas_g//2], axis1=1,
-                      axis2=2, offset=0)
-covariance = np.cov(g_slice.T)
-plt.matshow(np.real(covariance), origin="upper", extent=[-n, n, n, -n],
-            cmap=cc.m_kbc_r)
-plt.title(r"$\mathrm{Re}\ \mathrm{Cov}(G^{2}(0,\nu,\nu),G^{2}(0,\nu',\nu'))$")
-plt.xlabel(r"$\nu$")
-plt.ylabel(r"$\nu'$")
-plt.colorbar()
-ax = plt.gca()
-ax.xaxis.set_ticks_position("bottom")
-plt.show()
-
-
-# %%
-# Plot nu-nu correlation of 2P Green's function
-def plot_real_nu_nu_correlation_of_2p_greens_function(fig_name=None):
-    omega_g = 0
-    n = n_nus_g // 2
-    g_slice = np.diagonal(g4s[:, 0, :, :, omega_g + n_omegas_g//2], axis1=1,
-                          axis2=2, offset=0)
-    correlation = np.corrcoef(g_slice.T)
-    plt.figure(figsize=cm2inch(16, 12))
-    # plt.matshow(np.real(correlation), origin="upper", extent=[-n, n, n, -n],
-    #                  vmin=-1, vmax=1, cmap="seismic")
-
-    # plt.pcolormesh(range(-n_nus_g//2, n_nus_g//2 + 1),
-    #                range(-n_nus_g//2, n_nus_g//2 + 1), np.real(correlation),
-    #                vmin=-1, vmax=1, cmap="seismic")
-    plt.imshow(np.real(correlation), vmin=-1, vmax=1, cmap="seismic",
-               extent=[-n, n, n, -n])
-    # plt.title(r"$\mathrm{Re}\ \mathrm{Corr}(G^{2}(0,\nu,\nu),G^{2}$" +
-    #           r"$(0,\nu',\nu'))$")
-    plt.xlabel(r"$\nu$ High", fontsize=16)
-    plt.ylabel(r"$\nu'$", fontsize=16)
-    ax = plt.gca()
-    # ax.xaxis.set_ticks_position("bottom")
-    ax.tick_params(axis="both", which="major", labelsize=16)
-    # plt.colorbar()
-    divider = make_axes_locatable(plt.gca())
-    cax = divider.append_axes("right", "5%", pad="3%")
-    plt.colorbar(cax=cax)
-    # ax.axis("tight")
-    # plt.colorbar(use_gridspec=True)
-    plt.tight_layout()
-    if fig_name is None:
-        plt.show()
-    else:
-        plt.savefig(fig_name, bbox_inches="tight", pad_inches=0)
-    return
-
-
-# %%
-plt.close('all')
-arr = np.arange(100).reshape((10, 10))
-fig = plt.figure(figsize=(4, 4))
-im = plt.imshow(arr)
-divider = make_axes_locatable(plt.gca())
-cax = divider.append_axes("right", "5%", pad="3%")
-plt.colorbar(im, cax=cax)
-plt.tight_layout()
-
-# %%
-def cm2inch(*tupl):
-    inch = 2.54
-    if isinstance(tupl[0], tuple):
-        return tuple(i/inch for i in tupl[0])
-    else:
-        return tuple(i/inch for i in tupl)