From 4b72731bd65dd3bc5342f6e4a24684376558ad33 Mon Sep 17 00:00:00 2001
From: Valentin Bruch <valentin.bruch@rwth-aachen.de>
Date: Wed, 26 Oct 2022 15:37:22 +0200
Subject: [PATCH] bug fixes in gen_data; doc string in final_plots
gen_data: bug fixes in automatic selection of nmax (preset was ignored)
final_plots: added doc string for export_omega5_interp (npz export)
---
experiments.py | 2 ++
final_plots.py | 36 ++++++++++++++++++++++++++++++++++++
gen_data.py | 22 ++++++++++++----------
plot.py | 34 ++++++++++++++++++++++++++++++++++
4 files changed, 84 insertions(+), 10 deletions(-)
diff --git a/experiments.py b/experiments.py
index 922d00e..3bcc3b8 100644
--- a/experiments.py
+++ b/experiments.py
@@ -242,6 +242,8 @@ def kogan04_calibrate(dm, **kwargs):
yscale = np.pi,
calibrate_min = 1,
calibrate_max = 1.6,
+ include_Ga = True,
+ integral_method = -15,
**kwargs,
)
diff --git a/final_plots.py b/final_plots.py
index d3af580..df0c95a 100644
--- a/final_plots.py
+++ b/final_plots.py
@@ -245,6 +245,42 @@ def export_omega5_interp(
ac_res = 201,
korder = 2,
):
+ """
+ Export interpolated data for given parameters.
+ Data are stored with units e=hbar=kB=Tkrg=1.
+ All results are exported as 2d arrays of the same shape.
+ Results have the naming convention
+
+ {observable}_{order}{padding}_{method}_{suffix}
+
+ observable:
+ gdc DC differential conductance, may have suffix "_ispline"
+ gac AC differential conductance, must have suffix "_ispline"
+ idc average current, may have suffix "_spline"
+ iac oscillating current, may have suffix "_spline"
+ phase AC phase
+ gamma Γ(E=0) (not an observable)
+
+ order:
+ o2 2nd order RG equations
+ o3 3rd order RG equations without Ga and with approximated integral
+ o3a 3rd order RG equations with approximated integral
+ o3p 3rd order RG equations with full integral
+
+ padding:
+ "" no Floquet matrix extrapolation
+ "_p" Floquet matrix extrapolation to mitigate truncation effects
+
+ method:
+ mu no unitary transformation, oscillating chemical potentials
+ J include oscillating voltage in coupling by unitary transformation
+
+ suffix
+ "" interpolation is done using griddata
+ "_spline" interpolation is done using spline
+ "_ispline" data is derived from spline interpolation for the
+ current (dc or ac)
+ """
dm = DataManager()
data = dm.list(
omega = omega,
diff --git a/gen_data.py b/gen_data.py
index 86eb40b..3c2daef 100644
--- a/gen_data.py
+++ b/gen_data.py
@@ -18,13 +18,14 @@ from data_management import DataManager
from kondo import Kondo
-def get_ref_nmax_omega5(dm, omega, vdc, vac, preset="normal"):
- assert omega == 16.5372
+def get_ref_nmax(dm, omega, vdc, vac, preset="precise"):
parameters = dict(
- precise = dict(omega=16.5372, solver_tol_rel=1e-8, solver_tol_abs=1e-10, d=1e9, method="mu", padding=0, good_flags=0x1000, bad_flags=0x0ffc),
- normal = dict(omega=16.5372, solver_tol_rel=1e-9, solver_tol_abs=1e-11, d=1e5, method="mu", padding=0, good_flags=0x1000, bad_flags=0x0ffc),
+ old = dict(omega=omega, solver_tol_rel=1e-8, solver_tol_abs=1e-10, d=1e9, method="mu", padding=0, good_flags=0x0000, bad_flags=0x1ffc, xL=0.5, voltage_branches=4),
+ precise = dict(omega=omega, solver_tol_rel=1e-8, solver_tol_abs=1e-10, d=1e9, method="mu", padding=0, good_flags=0x1000, bad_flags=0x0ffc, xL=0.5, voltage_branches=4),
+ normal = dict(omega=omega, solver_tol_rel=1e-9, solver_tol_abs=1e-11, d=1e5, method="mu", padding=0, good_flags=0x1000, bad_flags=0x0ffc, xL=0.5, voltage_branches=4),
)
data = dm.list(**parameters[preset])
+ assert data.size > 0
vdc_arr, vac_arr = np.broadcast_arrays(vdc, vac)
nmax = -np.ones(vdc_arr.shape, dtype=np.int64).reshape((-1,))
for i, (vdc, vac) in enumerate(zip(vdc_arr.flat, vac_arr.flat)):
@@ -244,8 +245,8 @@ python -m frtrg_kondo.gen_data \\
method_group.add_argument("--truncation_order", metavar="int", type=int,
choices=(2,3), default=3,
help = "Truncation order of RG equations.")
- method_group.add_argument("--preset", metavar="str", type=str, nargs='+',
- choices=("normal", "precise"), default="precise",
+ method_group.add_argument("--preset", metavar="str", type=str,
+ choices=("normal", "precise", "old"), default="precise",
help = "Preset for choosing nmax if set explicitly")
# Numerical parameters concerning Floquet matrices
@@ -338,6 +339,7 @@ python -m frtrg_kondo.gen_data \\
atol = options.pop("atol"),
method = options.pop("solver_method"),
)
+ preset = options.pop("preset", "precise")
# Detect number of CPUs (if necessary)
if threads == 0:
@@ -353,7 +355,7 @@ python -m frtrg_kondo.gen_data \\
assert np.abs(kondo_options["vdc"] - vdc) < 1e-9
kondo_options["vdc"] = vdc
if kondo_options["nmax"] < 0:
- kondo_options["nmax"] = get_ref_nmax_omega5(dm, kondo_options["omega"], kondo_options["vdc"], kondo_options["vac"])
+ kondo_options["nmax"] = get_ref_nmax(dm, kondo_options["omega"], kondo_options["vdc"], kondo_options["vac"], preset)
if kondo_options["nmax"] < 0:
settings.logger.error(f"Invalid value nmax={nmax}: must be ≥0")
continue
@@ -373,7 +375,7 @@ python -m frtrg_kondo.gen_data \\
lock = mp.Lock()
queue = mp.Queue()
# create processes
- processes = [mp.Process(target=save_data_mp, args=(queue, lock, solver_options, filename, include, find_pole)) for i in range(threads)]
+ processes = [mp.Process(target=save_data_mp, args=(queue, lock, solver_options, filename, include, find_pole, False, preset)) for i in range(threads)]
# start processes
for p in processes:
p.start()
@@ -385,7 +387,7 @@ python -m frtrg_kondo.gen_data \\
queue.put(None)
-def save_data_mp(queue, lock, solver_options, filename, include='all', find_pole=False, overwrite=False):
+def save_data_mp(queue, lock, solver_options, filename, include='all', find_pole=False, overwrite=False, preset="precise"):
"""
Generate data points in own process and save them to HDF5 file.
Each process owns one DataManager instance.
@@ -401,7 +403,7 @@ def save_data_mp(queue, lock, solver_options, filename, include='all', find_pole
assert np.abs(kondo_options["vdc"] - vdc) < 1e-9
kondo_options["vdc"] = vdc
if kondo_options["nmax"] < 0:
- kondo_options["nmax"] = get_ref_nmax_omega5(dm, kondo_options["omega"], kondo_options["vdc"], kondo_options["vac"])
+ kondo_options["nmax"] = get_ref_nmax(dm, kondo_options["omega"], kondo_options["vdc"], kondo_options["vac"], preset)
if kondo_options["nmax"] < 0:
settings.logger.error(f"Invalid value nmax={kondo_options['nmax']}: must be ≥0")
continue
diff --git a/plot.py b/plot.py
index aec9255..8611536 100644
--- a/plot.py
+++ b/plot.py
@@ -1721,6 +1721,40 @@ def RGeq_comparison_contours(
plt.show()
+def RGeq_comparison_contours2(
+ dm = None,
+ filename = "figdata/omega5_interp.npz",
+ observable = "gdc",
+ prefactor = np.pi,
+ **trashparams):
+ omega = 16.5372
+ kwargs = dict(linewidths=0.8)
+ colors = dict(o2="#ff0000", o3="#6000ff", o3a="#00f000", o3p="#000000", ref="#808080")
+ zorder = dict(o2=1, o3=2, o3a=3, o3p=4)
+ approximations = list(zorder.keys())
+ data = np.load(filename)
+ vdc = data["vdc"] / omega
+ vac = data["vac"] / omega
+ levels = (1/np.linspace(1, 12, 12)[::-1]) / prefactor
+ fig, ax = plt.subplots(nrows=1, ncols=1, sharex=True, sharey=True)
+ for approx in approximations:
+ ax.contour(vdc, vac, data[f"{observable}_mu_{approx}"], levels, zorder=zorder[approx], colors=colors[approx], **kwargs)
+ try:
+ ax.contour(vdc, vac, data[f"{observable}_J_{approx}"], levels, zorder=zorder[approx], colors=colors[approx], **kwargs)
+ except KeyError:
+ settings.logger.warning(f"No data available for {observable}_J_{approx}")
+ try:
+ ax.contour(vdc, vac, data[f"{observable}_J_{approx}_p"], levels, zorder=zorder[approx], colors=colors[approx], **kwargs)
+ except KeyError:
+ settings.logger.warning(f"No data available for {observable}_J_{approx}_p")
+
+ #ax.contour(-vdc, vac, data[f"{observable}_mu_o3p"], levels, zorder=-1, colors=colors["ref"], **kwargs)
+ #ax.vlines((0,), 0, vac[-1], color="#808080", linewidth=0.5)
+ ax.set_xlabel(r"$V_\mathrm{avg}~(\Omega)$")
+ ax.set_ylabel(r"$V_\mathrm{osc}~(\Omega)$")
+ plt.show()
+
+
def plot_Ga_max(
dm,
omega = 16.5372,
--
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