# -*- coding: utf-8 -*-
from __future__ import absolute_import
from __future__ import print_function
import click
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
from matplotlib import gridspec
import json
import sys
from aiida_yambo.commands.utils import command
from aiida_yambo.commands import options
import os
[docs]def get_extremes(mn, mx, mn_state, mx_state):
if mx_state == None:
mx_state = mx
if mn_state == None:
mn_state = mn
if mn < mn_state:
mn_state = mn
if mx > mx_state:
mx_state = mx
return mx_state, mn_state
[docs]def plotter(fig, gs, ax1, ind, dep, var):
print(("ind {} dep {} var {}".format(ind, dep, var)))
ax1.plot(ind, dep, label=var, marker='+')
[docs]def read_intp_out(jsondata, legendpos, label, output="fullconv"):
fig = plt.figure()
gs = gridspec.GridSpec(1, 1)
gs.update(wspace=0.3)
ax1 = fig.add_subplot(gs[0, 0])
full_result = jsondata
max_dependent = None
min_dependent = None
independent_ax = np.arange(1)
for data in full_result['ordered_step_output']:
if "kpoints" in list(data["convergence_space"].keys()):
dep_kp = np.array(data['energy_widths'])
indep_kp = np.array(data['convergence_space']['kpoints'])
indep_kp = 1.0 / indep_kp
independent_ax = np.arange(0, indep_kp.size)
plotter(fig, gs, ax1, independent_ax, dep_kp, "kpoints")
mx = np.amax(dep_kp)
mn = np.amin(dep_kp)
min_dependent, max_dependent = get_extremes(
mn, mx, min_dependent, max_dependent)
if "FFTGvecs" in list(data["convergence_space"].keys()):
indep_fft = np.array(data['convergence_space']['FFTGvecs'])
mn, mx = indep_fft[0], indep_fft[-1]
dep_fft = np.array(data['energy_widths'])
independent_ax = np.arange(independent_ax[-1],
independent_ax[-1] + indep_fft.size)
plotter(fig, gs, ax1, independent_ax, dep_fft,
"FFT {}-{} Ry".format(mn, mx))
mx = np.amax(dep_fft)
mn = np.amin(dep_fft)
min_dependent, max_dependent = get_extremes(
mn, mx, min_dependent, max_dependent)
if "GbndRnge" in list(data["convergence_space"].keys()):
indep_bands = np.array(
[el[-1] for el in data['convergence_space']['GbndRnge']])
mn, mx = indep_bands[0], indep_bands[-1]
dep_bands = np.array(data['energy_widths'])
independent_ax = np.arange(
independent_ax[-1],
independent_ax[-1] + np.unique(indep_bands).size)
plotter(fig, gs, ax1, independent_ax, dep_bands,
"Bands (1-{})-(1-{})".format(mn, mx))
mx = np.amax(dep_bands)
mn = np.amin(dep_bands)
min_dependent, max_dependent = get_extremes(
mn, mx, min_dependent, max_dependent)
if "NGsBlkXp" in list(data["convergence_space"].keys()):
indep_G = np.array(data['convergence_space']['NGsBlkXp'])
mn, mx = indep_G[0], indep_G[-1]
dep_G = np.array(data['energy_widths'])
independent_ax = np.arange(independent_ax[-1],
independent_ax[-1] + indep_G.size)
plotter(fig, gs, ax1, independent_ax, dep_G, "W {}-{} Ry".format(
mn, mx))
mx = np.amax(dep_G)
mn = np.amin(dep_G)
min_dependent, max_dependent = get_extremes(
mn, mx, min_dependent, max_dependent)
h, l = ax1.get_legend_handles_labels()
ax1.legend(h, l, loc=legendpos, ncol=1, prop={'size': 12})
ax1.set_ylabel("Energy (eV)")
ax1.set_xlabel('Convergence space')
#fig.suptitle(r'Direct Gap at $\Gamma$', size=14)
fig.suptitle(r'{}'.format(label), size=14)
plt.xticks([], [])
print((min_dependent * 0.7, max_dependent * 1.5))
plt.ylim(min_dependent * 0.7, max_dependent * 1.5)
plt.xlim(0, independent_ax[-1])
plt.savefig(output, format='eps', dpi=1200)
plt.show()
plt.close()
mpl.rcParams.update(mpl.rcParamsDefault)
@command()
@options.node()
@options.legend()
@options.label()
@options.output()
[docs]def plotconv(node=None, legendpos=None, label=None, output=None):
"""
Create a plot showing the convergence behaviour of the Full convergence workflow
"""
plot_data = node
read_intp_out(plot_data, legendpos, label, output)
