Source code for triqs.gf.plot.plot_base

# 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) 2016 Igor Krivenko
# Copyright (c) 2020 Simons Foundation
#
# 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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