diff --git a/gstlal-calibration/tests/check_calibration/Makefile b/gstlal-calibration/tests/check_calibration/Makefile
index da73eee9486191b9d83e1f5b1fd43594a4dd3489..7ed7951b0fb2b8e5fd5e34cdba4d9bec83f39ff8 100644
--- a/gstlal-calibration/tests/check_calibration/Makefile
+++ b/gstlal-calibration/tests/check_calibration/Makefile
@@ -139,6 +139,9 @@ latency_tests:
#$(IFO)1_hoft_GDS_OLD_frames.cache $(IFO)1_hoft_GDS_BETTER_frames.cache
python latency_plot.py --intime-file-list 'gstlal_compute_strain_timestamps_in_resample.txt,gstlal_compute_strain_timestamps_in_old.txt,gstlal_compute_strain_timestamps_in_better.txt' --outtime-file-list 'gstlal_compute_strain_timestamps_out_resample.txt,gstlal_compute_strain_timestamps_out_old.txt,gstlal_compute_strain_timestamps_out_better.txt' --plot-filename-prefix $(IFO)1GDS_latency --labels 'Including resampling latency,6s Tukey-windowed actuation filter,3.5s Kaiser-windowed actuation filter'
+RMS_timeseries: $(IFO)1_C00_frames.cache $(IFO)1_X02_frames.cache
+ python plot_rms_timeseries.py --ifo $(IFO)1 --gps-end-time $(PLOT_END) --gps-start-time $(PLOT_START) --frame-cache-list '$(IFO)1_C00_frames.cache,$(IFO)1_X02_frames.cache' --channel-list 'GDS-CALIB_STRAIN,DCS-CALIB_STRAIN_X02' --sample-rates '16,16' --labels 'C00,X02' --fmax 5.0
+
CALCS_GDS_ASD: $(IFO)1_hoft_GDS_frames.cache $(IFO)1_easy_raw_frames.cache
./ASD_comparison_plots --ifo $(IFO)1 --gps-start-time $(PLOT_START) --gps-end-time $(PLOT_END) --raw-frame-cache $(IFO)1_easy_raw_frames.cache --hoft-frame-cache $(IFO)1_hoft_GDS_frames.cache
diff --git a/gstlal-calibration/tests/check_calibration/plot_rms_timeseries.py b/gstlal-calibration/tests/check_calibration/plot_rms_timeseries.py
new file mode 100644
index 0000000000000000000000000000000000000000..8674c4b083b8875a283ec6dded4c884514448286
--- /dev/null
+++ b/gstlal-calibration/tests/check_calibration/plot_rms_timeseries.py
@@ -0,0 +1,215 @@
+#!/usr/bin/env python
+# Copyright (C) 2019 Aaron Viets
+#
+# 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 2 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 should have received a copy of the GNU General Public License along
+# with this program; if not, write to the Free Software Foundation, Inc.,
+# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
+
+#
+# =============================================================================
+#
+# Preamble
+#
+# =============================================================================
+#
+
+
+import sys
+import os
+import numpy
+import time
+from math import pi
+import resource
+import datetime
+import time
+import matplotlib
+from matplotlib import rc
+rc('text', usetex = True)
+matplotlib.rcParams['font.family'] = 'Times New Roman'
+matplotlib.rcParams['font.size'] = 22
+matplotlib.rcParams['legend.fontsize'] = 18
+matplotlib.rcParams['mathtext.default'] = 'regular'
+matplotlib.use('Agg')
+import glob
+import matplotlib.pyplot as plt
+
+from optparse import OptionParser, Option
+
+import gi
+gi.require_version('Gst', '1.0')
+from gi.repository import GObject, Gst
+GObject.threads_init()
+Gst.init(None)
+
+import lal
+from lal import LIGOTimeGPS
+
+from gstlal import pipeparts
+from gstlal import calibration_parts
+from gstlal import simplehandler
+from gstlal import datasource
+
+from ligo import segments
+from gstlal import test_common
+
+parser = OptionParser()
+parser.add_option("--gps-start-time", metavar = "seconds", type = int, help = "GPS time at which to start processing data")
+parser.add_option("--gps-end-time", metavar = "seconds", type = int, help = "GPS time at which to stop processing data")
+parser.add_option("--ifo", metavar = "name", type = str, help = "Name of the interferometer (IFO), e.g., H1, L1")
+parser.add_option("--frame-cache-list", metavar = "name", type = str, help = "Comma-separated list of frame cache files that contain data you want to plot")
+parser.add_option("--channel-list", metavar = "list", type = str, default = None, help = "Comma-separated list of channel-names of which to compute RMS")
+parser.add_option("--labels", metavar = "list", type = str, help = "Comma-separated list of labels for each channel. This is put in the plot legends and in the txt file names to distinguish them.")
+parser.add_option("--sample-rates", metavar = "list", type = str, help = "Comma-separated list of sample rates for each channel.")
+parser.add_option("--average-time", type = int, default = 30, help = "Time in seconds over which to take a running mean for the RMS")
+parser.add_option("--fmin", type = float, default = None, help = "Minimum frequency for RMS")
+parser.add_option("--fmax", type = float, default = None, help = "Maximum frequency for RMS")
+parser.add_option("--plot-min", type = float, default = None, help = "Minimum for y-axis of plot")
+parser.add_option("--plot-max", type = float, default = None, help = "Maximum for y-axis of plot")
+parser.add_option("--filename-suffix", type = str, default = "", help = "Suffix for filename to make it unique.")
+
+options, filenames = parser.parse_args()
+
+# Get frame cache list, channel list, and labels
+frame_cache_list = options.frame_cache_list.split(',')
+channel_list = options.channel_list.split(',')
+labels = options.labels.split(',')
+rates = options.sample_rates.split(',')
+for i in range(len(rates)):
+ rates[i] = int(rates[i])
+if len(frame_cache_list) != len(channel_list):
+ raise ValueError('Number of frame cache files must equal number of channels: %d != %d' % (len(frame_cache_list), len(channel_list)))
+if len(labels) != len(channel_list):
+ raise ValueError('Number of labels must equal number of channels: %d != %d' % (len(labels), len(channel_list)))
+if len(rates) != len(channel_list):
+ raise ValueError('Number of sample rates must equal number of channels: %d != %d' % (len(rates), len(channel_list)))
+
+# Read other options
+ifo = options.ifo
+temp = []
+for i in range(0, len(channel_list)):
+ temp.append((ifo, channel_list[i]))
+channel_list = temp
+
+gps_start_time = options.gps_start_time
+gps_end_time = options.gps_end_time
+data_duration = gps_end_time - gps_start_time
+average_time = options.average_time
+fmin = options.fmin
+fmax = options.fmax
+plot_min = options.plot_min
+plot_mas = options.plot_max
+filename_suffix = options.filename_suffix
+
+
+#
+# =============================================================================
+#
+# Pipelines
+#
+# =============================================================================
+#
+
+
+#
+# This pipeline reads in specified channels, computes the RMS,
+# and writes it to a txt file.
+#
+
+def compute_RMS_timeseries(pipeline, name):
+ # Get the data from the frames
+ for i in range(len(channel_list)):
+ data = pipeparts.mklalcachesrc(pipeline, location = frame_cache_list[i], cache_dsc_regex = ifo)
+ data = pipeparts.mkframecppchanneldemux(pipeline, data, do_file_checksum = False, skip_bad_files = True, channel_list = map("%s:%s".__mod__, channel_list))
+ data = calibration_parts.hook_up(pipeline, data, channel_list[i][1], ifo, 1.0)
+ data = calibration_parts.caps_and_progress(pipeline, data, "audio/x-raw,format=F64LE", labels[i])
+ RMS = calibration_parts.compute_rms(pipeline, data, rates[i], average_time, filter_length = 10.0, f_min = fmin, f_max = fmax, rate_out = 1)
+ pipeparts.mknxydumpsink(pipeline, RMS, "%s_RMS_%s_%d-%d.txt" % (ifo, labels[i].replace(' ', '_'), gps_start_time, data_duration))
+
+ #
+ # done
+ #
+
+ return pipeline
+
+#
+# =============================================================================
+#
+# Main
+#
+# =============================================================================
+#
+
+
+# Run pipeline
+test_common.build_and_run(compute_RMS_timeseries, "compute_RMS_timeseries", segment = segments.segment((LIGOTimeGPS(0, 1000000000 * gps_start_time), LIGOTimeGPS(0, 1000000000 * gps_end_time))))
+
+colors = ['blue', 'limegreen', "royalblue", "deepskyblue", "red", "yellow", "purple", "pink"]
+
+# Read data from txt file.
+rms_data = []
+tdata = []
+for i in range(0, len(labels)):
+ data = numpy.loadtxt('%s_RMS_%s_%d-%d.txt' % (ifo, labels[i].replace(' ', '_'), gps_start_time, data_duration))
+ if not any(tdata):
+ t_start = data[0][0]
+ dur = data[len(data) - 1][0] - t_start
+ dur_in_seconds = dur
+ t_unit = 'seconds'
+ sec_per_t_unit = 1.0
+ if dur > 60 * 60 * 100:
+ t_unit = 'days'
+ sec_per_t_unit = 60.0 * 60.0 * 24.0
+ elif dur > 60 * 100:
+ t_unit = 'hours'
+ sec_per_t_unit = 60.0 * 60.0
+ elif dur > 100:
+ t_unit = 'minutes'
+ sec_per_t_unit = 60.0
+ for k in range(0, int(len(data) / average_time)):
+ tdata.append((data[average_time * k][0] - t_start) / sec_per_t_unit)
+ markersize = 150.0 * numpy.sqrt(float(average_time / dur))
+ markersize = min(markersize, 10.0)
+ markersize = max(markersize, 1.0)
+
+ rms_data.append([])
+ for k in range(0, int(len(data) / average_time)):
+ rms_data[i].append(data[average_time * k][1])
+
+for i in range(0, len(labels)):
+ # Make plot
+ if i == 0:
+ plt.figure(figsize = (10, 6))
+ plt.plot(tdata, rms_data[i], colors[i % 6], linestyle = 'None', marker = '.', markersize = markersize, label = labels[i].replace('_', '\_'))
+ leg = plt.legend(fancybox = True, markerscale = 8.0 / markersize, numpoints = 3)
+ leg.get_frame().set_alpha(0.8)
+ plt.gca().set_xscale('linear')
+ plt.gca().set_yscale('log')
+ if i == 0:
+ if fmin is not None and fmax is not None:
+ plt.title('%s Band-limited RMS [%d - %d Hz]' % (ifo, int(fmin), int(fmax)))
+ elif fmin is not None:
+ plt.title('%s RMS above %d Hz' % (ifo, int(fmin)))
+ elif fmax is not None:
+ plt.title('%s RMS below %d Hz' % (ifo, int(fmax)))
+ else:
+ plt.title('%s RMS' % ifo)
+ plt.ylabel('RMS')
+ plt.xlabel('Time [%s] from %s UTC' % (t_unit, time.strftime("%b %d %Y %H:%M:%S", time.gmtime(gps_start_time + 315964782))))
+ if plot_min is not None:
+ plt.ylim(plot_min, plot_max)
+ plt.grid(True, which = "both", linestyle = ':', linewidth = 0.3, color = 'black')
+plt.savefig('%s_RMS%s_%d-%d.png' % (ifo, filename_suffix, gps_start_time, data_duration))
+plt.savefig('%s_RMS%s_%d-%d.pdf' % (ifo, filename_suffix, gps_start_time, data_duration))
+
+
+