From c0e342f10a4614d7a78ac094224b28e878f715b4 Mon Sep 17 00:00:00 2001
From: Philipp Arras <parras@mpa-garching.mpg.de>
Date: Sat, 10 Aug 2019 10:09:17 +0200
Subject: [PATCH] Add energy analyze plot
---
nifty5/__init__.py | 2 +-
nifty5/plot.py | 54 ++++++++++++++++++++++++++++++++++++++++++++++
2 files changed, 55 insertions(+), 1 deletion(-)
diff --git a/nifty5/__init__.py b/nifty5/__init__.py
index a9326ba4a..b32ab5fcd 100644
--- a/nifty5/__init__.py
+++ b/nifty5/__init__.py
@@ -73,7 +73,7 @@ from .minimization.energy_adapter import EnergyAdapter
from .minimization.metric_gaussian_kl import MetricGaussianKL
from .sugar import *
-from .plot import Plot
+from .plot import Plot, energy_history_analysis
from .library.smooth_linear_amplitude import (
SLAmplitude, LinearSLAmplitude, CepstrumOperator)
diff --git a/nifty5/plot.py b/nifty5/plot.py
index e7fc65b10..af4143479 100644
--- a/nifty5/plot.py
+++ b/nifty5/plot.py
@@ -17,6 +17,7 @@
import os
+import matplotlib.pyplot as plt
import numpy as np
from . import dobj
@@ -523,3 +524,56 @@ class Plot(object):
_plot(self._plots[i], ax, **self._kwargs[i])
fig.tight_layout()
_makeplot(kwargs.pop("name", None))
+
+
+def energy_history_analysis(fname_outer, fname_inner, fname_sampling,
+ fname=None, figsize=[30, 10]):
+ """Visualizes the behaviour of the various minimizers during a
+ minimization procedure.
+
+ Parameters
+ ----------
+ fname_outer : string
+ File name of file which was written by an :class:`IterationController`
+ and contains the energy history of the Newton minimizer.
+ fname_inner : string
+ File name of file which was written by an :class:`IterationController`
+ and contains the energy history of the inverter inside of the Newton
+ minimizer.
+ fname_sampling : string
+ File name of file which was written by an :class:`IterationController`
+ and contains the energy history of the inverter which controls the
+ sampling.
+ fname : string
+ File name of the output plot. None lets matplotlib open an interactive
+ window and no file is written. Default is None.
+ figsize : tuple of float
+ figsize of output plot (see `matplotlib.pyplot.subplots`). Default is
+ [30, 10].
+ """
+ # FIXME Visualize convergence criteria as well
+ tsa, esa, _ = np.loadtxt(fname_sampling, delimiter=' ').T
+ tou, eou, _ = np.loadtxt(fname_outer, delimiter=' ').T
+ tin, ein, _ = np.loadtxt(fname_inner, delimiter=' ').T
+ t0 = np.min([tsa, tou, tin])
+ tsa = (tsa-t0)/3600
+ tou = (tou-t0)/3600
+ tin = (tin-t0)/3600
+
+ fig, (ax0, ax1) = plt.subplots(nrows=2, sharex=True, figsize=figsize)
+ p1 = ax0.scatter(tin, ein, marker='x', c='r', label='Newton inverter',
+ alpha=.3)
+ p2 = ax0.scatter(tsa, esa, marker='x', label='Sampling inverter', alpha=.3)
+ ax0.set_ylim([1.5*np.min(esa), np.max(esa) - 0.1*np.min(esa)])
+ ax0.set_ylabel('Conjugate gradient energy')
+ ax0.legend([p1, p2], [p1.get_label(), p2.get_label()])
+ ax1.scatter(tou, eou, marker='>', c='g')
+ ax1.set_ylabel('Newton energy')
+ ax1.set_yscale('log')
+ ax1.set_xlabel("Time [h]")
+ plt.tight_layout()
+ if fname is None:
+ plt.savefig(fname)
+ else:
+ plt.show()
+ plt.close()
--
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