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post_processing.py
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import numpy as np
def read_sse_output(filename):
"""
reads SSE simulation outputs
parameters:
filename - path for the output file
output:
dictionary with all of the sampled quantitites
dictionary with simulation info
"""
sim_info = dict()
sampled = dict()
with open(filename, "r") as file:
# read simulation info
file.readline()
line = file.readline().strip().split(',')
sim_info["d"] = int(line[0])
sim_info["L"] = int(line[1])
sim_info["boundary_cond"] = line[2]
sim_info["S"] = float(line[3])
sim_info["delta"] = float(line[4])
sim_info["h"] = float(line[5])
sim_info["epsilon"] = float(line[6])
file.readline()
line = file.readline().strip().split(',')
sim_info["therm_cycles"]= int(line[0])
sim_info["mc_cycles"] = int(line[1])
sim_info["n_bins"] = int(line[2])
file.readline()
line = file.readline().strip().split(',')
sim_info["cpu_time"] = float(line[0])
sim_info["n_threads"] = int(line[1])
file.readline()
line = file.readline().strip().split(',')
sim_info["n_betas"] = int(line[0])
sim_info["n_k"] = int(line[1])
sim_info["x"] = int(line[2])
sim_info["y"] = int(line[3])
sim_info["cond"] = line[4]
# read sampled quantities
sampled["beta"] = np.zeros(sim_info["n_betas"])
sampled["T"] = np.zeros(sim_info["n_betas"])
sampled["n"] = np.zeros(sim_info["n_betas"])
sampled["n_std"] = np.zeros(sim_info["n_betas"])
sampled["E"] = np.zeros(sim_info["n_betas"])
sampled["E_std"] = np.zeros(sim_info["n_betas"])
sampled["C"] = np.zeros(sim_info["n_betas"])
sampled["C_std"] = np.zeros(sim_info["n_betas"])
sampled["m"] = np.zeros(sim_info["n_betas"])
sampled["m_std"] = np.zeros(sim_info["n_betas"])
sampled["m2"] = np.zeros(sim_info["n_betas"])
sampled["m2_std"] = np.zeros(sim_info["n_betas"])
sampled["m4"] = np.zeros(sim_info["n_betas"])
sampled["m4_std"] = np.zeros(sim_info["n_betas"])
sampled["ms"] = np.zeros(sim_info["n_betas"])
sampled["ms_std"] = np.zeros(sim_info["n_betas"])
sampled["m2s"] = np.zeros(sim_info["n_betas"])
sampled["m2s_std"] = np.zeros(sim_info["n_betas"])
sampled["m4s"] = np.zeros(sim_info["n_betas"])
sampled["m4s_std"] = np.zeros(sim_info["n_betas"])
sampled["m_sus"] = np.zeros(sim_info["n_betas"])
sampled["m_sus_std"] = np.zeros(sim_info["n_betas"])
sampled["S_mean"] = np.zeros(sim_info["n_betas"])
sampled["S_std"] = np.zeros(sim_info["n_betas"])
file.readline()
for j in range(sim_info["n_betas"]):
sampled["beta"][j], sampled["n"][j], _, sampled["n_std"][j], \
sampled["E"][j], sampled["E_std"][j], sampled["C"][j], sampled["C_std"][j], \
sampled["m"][j], sampled["m_std"][j], sampled["m2"][j], sampled["m2_std"][j], \
sampled["m4"][j], sampled["m4_std"][j], sampled["ms"][j], sampled["ms_std"][j], \
sampled["m2s"][j], sampled["m2s_std"][j], sampled["m4s"][j], sampled["m4s_std"][j], \
sampled["m_sus"][j], sampled["m_sus_std"][j], sampled["S_mean"][j], sampled["S_std"][j] \
= [float(x) for x in file.readline().strip().split(',')]
sampled["T"][j] = 1.0 / sampled["beta"][j]
# read equal time spin-spin correlation function
sampled["corr_mean"] = np.zeros((sim_info["n_betas"], sim_info["L"]))
sampled["corr_std"] = np.zeros((sim_info["n_betas"], sim_info["L"]))
for j in range(sim_info["n_betas"]):
file.readline()
file.readline()
file.readline()
for i in range(sim_info["L"]):
sampled["corr_mean"][j, i], sampled["corr_std"][j, i] = [float(x) for x in file.readline().strip().split(',')]
# spin conductivity
if sim_info["n_k"] != 0 and sim_info["cond"] != ".":
sampled["w_k"] = np.zeros((sim_info["n_betas"], sim_info["n_k"]))
sampled["g_spin_mean"] = np.zeros((sim_info["n_betas"], sim_info["n_k"]))
sampled["g_spin_std"] = np.zeros((sim_info["n_betas"], sim_info["n_k"]))
sampled["g_heat_mean"] = np.zeros((sim_info["n_betas"], sim_info["n_k"]))
sampled["g_heat_std"] = np.zeros((sim_info["n_betas"], sim_info["n_k"]))
if sim_info["cond"] == "both" or sim_info["cond"] == "spin":
for j in range(sim_info["n_betas"]):
file.readline()
file.readline()
file.readline()
for i in range(sim_info["n_k"]):
sampled["w_k"][j, i], sampled["g_spin_mean"][j, i], sampled["g_spin_std"][j, i] = [float(x) for x in file.readline().strip().split(',')]
if sim_info["cond"] == "both" or sim_info["cond"] == "heat":
for j in range(sim_info["n_betas"]):
file.readline()
file.readline()
file.readline()
for i in range(sim_info["n_k"]):
sampled["w_k"][j, i], sampled["g_heat_mean"][j, i], sampled["g_heat_std"][j, i] = [float(x) for x in file.readline().strip().split(',')]
return sim_info, sampled
def read_exact_output(filename):
"""
reads SSE simulation outputs
parameters:
filename - path for the output file
output:
dictionary with all of the sampled quantitites
dictionary with simulation info
"""
sim_info = dict()
sampled = dict()
with open(filename, "r") as file:
# read simulation info
file.readline()
line = file.readline().strip().split(',')
sim_info["L"] = int(line[0])
sim_info["boundary_cond"] = line[1]
sim_info["S"] = float(line[2])
sim_info["delta"] = float(line[3])
sim_info["h"] = float(line[4])
file.readline()
line = file.readline().strip().split(',')
sim_info["n_betas"] = int(line[0])
sim_info["n_betas_k"] = int(line[1])
sim_info["n_k"] = int(line[2])
sim_info["x"] = int(line[3])
sim_info["y"] = int(line[4])
# read sampled quantities
sampled["beta"] = np.zeros(sim_info["n_betas"])
sampled["T"] = np.zeros(sim_info["n_betas"])
sampled["E"] = np.zeros(sim_info["n_betas"])
sampled["C"] = np.zeros(sim_info["n_betas"])
sampled["m"] = np.zeros(sim_info["n_betas"])
sampled["m2"] = np.zeros(sim_info["n_betas"])
sampled["ms"] = np.zeros(sim_info["n_betas"])
sampled["m2s"] = np.zeros(sim_info["n_betas"])
sampled["m_sus"] = np.zeros(sim_info["n_betas"])
file.readline()
for j in range(sim_info["n_betas"]):
sampled["beta"][j], sampled["E"][j], sampled["C"][j], \
sampled["m"][j], sampled["m2"][j], sampled["ms"][j], \
sampled["m2s"][j], sampled["m_sus"][j] \
= [float(x) for x in file.readline().strip().split(',')]
sampled["T"][j] = 1.0 / sampled["beta"][j]
# spin conductivity
if sim_info["boundary_cond"] != "PBC":
sampled["beta_k"] = np.zeros(sim_info["n_betas_k"])
sampled["w_k"] = np.zeros((sim_info["n_betas_k"], sim_info["n_k"]))
sampled["L_SS"] = np.zeros((sim_info["n_betas_k"], sim_info["n_k"]))
sampled["L_HH"] = np.zeros((sim_info["n_betas_k"], sim_info["n_k"]))
sampled["L_SH"] = np.zeros((sim_info["n_betas_k"], sim_info["n_k"]))
sampled["L_HS"] = np.zeros((sim_info["n_betas_k"], sim_info["n_k"]))
for j in range(sim_info["n_betas_k"]):
file.readline()
line = file.readline().strip().split()
file.readline()
sampled["beta_k"][j] = float(line[0])
for i in range(sim_info["n_k"]):
sampled["w_k"][j, i], sampled["L_SS"][j, i] = [float(x) for x in file.readline().strip().split(',')]
for j in range(sim_info["n_betas_k"]):
file.readline()
line = file.readline().strip().split()
file.readline()
sampled["beta_k"][j] = float(line[0])
for i in range(sim_info["n_k"]):
sampled["w_k"][j, i], sampled["L_HH"][j, i] = [float(x) for x in file.readline().strip().split(',')]
for j in range(sim_info["n_betas_k"]):
file.readline()
line = file.readline().strip().split()
file.readline()
sampled["beta_k"][j] = float(line[0])
for i in range(sim_info["n_k"]):
sampled["w_k"][j, i], sampled["L_SH"][j, i] = [float(x) for x in file.readline().strip().split(',')]
for j in range(sim_info["n_betas_k"]):
file.readline()
line = file.readline().strip().split()
file.readline()
sampled["beta_k"][j] = float(line[0])
for i in range(sim_info["n_k"]):
sampled["w_k"][j, i], sampled["L_HS"][j, i] = [float(x) for x in file.readline().strip().split(',')]
return sim_info, sampled