# Copyright (c) 2013-2017 Commissariat à l'énergie atomique et aux énergies alternatives (CEA)
# Copyright (c) 2013-2017 Centre national de la recherche scientifique (CNRS)
# Copyright (c) 2020-2023 Simons Foundation
# Copyright (c) 2016 Igor Krivenko
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You may obtain a copy of the License at
# https:#www.gnu.org/licenses/gpl-3.0.txt
#
# Authors: Michel Ferrero, Igor Krivenko, Olivier Parcollet, Priyanka Seth, Nils Wentzell
import numpy
from warnings import warn
from triqs.plot.protocol import clip_array
[docs]
def plot_base(self, opt_dict, xlabel, ylabel, X, allow_spectral_mode=False):
r"""
Plot protocol for Green's function objects.
Parameters
----------
opt_dict: dictionary
MUST contain:
- name: str
Name for the plotting label
Can contain:
- mode: string, default None
Mode to plot the Green's function in:
-- 'R': real part only
-- 'I': imaginary part only
-- 'S': spectral function
- x_window: tuple, default None
(xmin,xmax)
xlabel: str
Label to apply to the x axis.
ylabel: lambda : str -> str
Label to apply to the y axis.
X: list
The x values the object can take, i.e. the mesh.
allow_spectral_mode: boolean, default False
Can the spectral function be measured for this type of Green's function?
Returns
-------
plot_data: list of dict
Object passed to oplot to plot.
"""
assert 'name_prefix' not in opt_dict, "name_prefix is deprecated"
#if 'name' not in opt_dict:
# warnings.warn("oplot REQUIRES a name = for making the legend and labels. Using self.name, but it is deprecated and WILL BE REMOVED")
name = opt_dict.pop('name', self.name)
rx = opt_dict.pop('x_window', None)
X = numpy.array(X).real
sl = clip_array(X, *rx) if rx else slice(len(X)) # the slice due to clip option x_window
def mdic(prefix, f):
from itertools import product
ind_range = product(*list(map(range,reversed(self.target_shape))))
make_label = lambda ind: "%s%s %s" % (prefix,name,"_".join(map(str, reversed(ind))))
make_data_sl = lambda ind: (sl,) + tuple(reversed(ind))
return [{'xlabel': xlabel,
'ylabel': ylabel(name),
'xdata': X[sl],
'label': make_label(ind),
'ydata': f(self.data[make_data_sl(ind)])} for ind in ind_range]
# if data is real, overrule
mode = opt_dict.pop('mode', '')
if self.data.dtype == numpy.float64 :
res = mdic('', lambda x: x)
elif mode == '':
res = mdic('Re ', lambda x: x.real) + mdic('Im ', lambda x: x.imag)
elif mode == 'R':
res = mdic('Re ', lambda x: x.real)
elif mode == 'I':
res = mdic('Im ', lambda x: x.imag)
elif mode == 'S':
if allow_spectral_mode:
res = mdic('', lambda x: -1 / numpy.pi * x.imag)
else:
raise ValueError("Cannot measure the spectral function for this type of Green's function.")
else:
raise ValueError("The 'mode' flag is meaningless. Expected 'R', 'I', or 'S' and I got %s." % mode)
for r in res: r.update(opt_dict) # Add all other unused parameters to the dictionaries
return res
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