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nilmtools-
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nilmtools-
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40
Makefile
40
Makefile
@@ -1,33 +1,40 @@
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#URL="http://bucket.mit.edu:8080/nilmdb"
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URL="http://localhost/nilmdb"
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all:
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ifeq ($(INSIDE_EMACS), t)
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@make test
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else
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@echo "Try 'make install'"
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endif
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all: test
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test: test_pipewatch
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test:
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ifeq ($(INSIDE_EMACS), t)
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@make test_sinefit
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else
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@echo 'No test suite for nilmtools. Try "make install"'
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endif
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test_pipewatch:
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nilmtools/pipewatch.py -t 3 "seq 10 20" "seq 20 30"
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test_trainola:
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-nilmtool -u http://bucket/nilmdb remove -s min -e max \
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/sharon/prep-a-matches
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nilmtools/trainola.py "$$(cat extras/trainola-test-param-2.js)"
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-nilmtool -u http://bucket/nilmdb remove -s min -e max \
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/sharon/prep-a-matches
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nilmtools/trainola.py "$$(cat extras/trainola-test-param.js)"
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test_trainola2:
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-nilmtool -u http://bucket/nilmdb remove -s min -e max \
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/sharon/prep-a-matches
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nilmtools/trainola.py "$$(cat extras/trainola-test-param-2.js)"
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test_trainola3:
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-nilmtool -u "http://bucket/nilmdb" destroy -R /test/jim
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nilmtool -u "http://bucket/nilmdb" create /test/jim uint8_3
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nilmtools/trainola.py "$$(cat extras/trainola-test-param-3.js)"
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nilmtool -u "http://bucket/nilmdb" extract /test/jim -s min -e max
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test_cleanup:
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nilmtools/cleanup.py -e extras/cleanup.cfg
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nilmtools/cleanup.py extras/cleanup.cfg
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test_insert:
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nilmtools/insert.py --file --dry-run /test/foo </dev/null
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nilmtools/insert.py --skip --file --dry-run /foo/bar ~/data/20130311T2100.prep1.gz ~/data/20130311T2100.prep1.gz ~/data/20130311T2200.prep1.gz
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test_copy:
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nilmtools/copy_wildcard.py -U "http://nilmdb.com/bucket/" -D /lees*
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@@ -46,10 +53,19 @@ test_prep: /tmp/raw.dat
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nilmtool create /test/sinefit float32_3
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nilmtool create /test/prep float32_8
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nilmtool insert -s '@0' -t -r 8000 /test/raw /tmp/raw.dat
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nilmtools/sinefit.py -a 0.5 -c 1 /test/raw /test/sinefit
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nilmtools/sinefit.py -a 0.5 -c 1 -s '@0' -e '@5000000' /test/raw /test/sinefit
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nilmtools/prep.py -c 2 /test/raw /test/sinefit /test/prep
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nilmtools/prep.py -c 2 /test/raw /test/sinefit /test/prep
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nilmtool extract -s min -e max /test/prep | head -20
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test_sinefit:
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make install >/dev/null 2>&1
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-nilmtool destroy -R /test/sinefit
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nilmtool create /test/sinefit float32_3
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nilmtools/sinefit.py -c 5 -s '2013/03/25 09:11:00' \
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-e '2013/03/25 10:11:00' /sharon/raw /test/sinefit
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nilmtool extract -s min -e max /test/sinefit | head -20
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test_decimate:
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-@nilmtool destroy /lees-compressor/no-leak/raw/4 || true
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-@nilmtool destroy /lees-compressor/no-leak/raw/16 || true
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|
@@ -8,7 +8,7 @@ Prerequisites:
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sudo apt-get install python2.7 python2.7-dev python-setuptools
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sudo apt-get install python-numpy python-scipy python-daemon
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nilmdb (1.8.1+)
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nilmdb (1.8.5+)
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Install:
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10
extras/sample-cron-scripts/capture.sh
Executable file
10
extras/sample-cron-scripts/capture.sh
Executable file
@@ -0,0 +1,10 @@
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#!/bin/bash
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# Start the ethstream capture using nilm-pipewatch
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# Bail out on errors
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set -e
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nilm-pipewatch --daemon --lock "/tmp/nilmdb-capture.lock" --timeout 30 \
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"ethstream -a 192.168.1.209 -n 9 -r 8000 -N" \
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"nilm-insert -m 10 -r 8000 --live /sharon/raw"
|
9
extras/sample-cron-scripts/cleanup.cfg
Normal file
9
extras/sample-cron-scripts/cleanup.cfg
Normal file
@@ -0,0 +1,9 @@
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[/sharon/prep-*]
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keep = 1y
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[/sharon/raw]
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keep = 2w
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[/sharon/sinefit]
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keep = 1y
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decimated = false
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15
extras/sample-cron-scripts/crontab
Normal file
15
extras/sample-cron-scripts/crontab
Normal file
@@ -0,0 +1,15 @@
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# Install this by running "crontab crontab" (will replace existing crontab)
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SHELL=/bin/bash
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PATH=/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/bin:/sbin
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# m h dom mon dow cmd
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# Run NilmDB processing every 5 minutes
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*/5 * * * * chronic /home/nilm/data/process.sh
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# Try frequently restarting the capture process in case it died
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*/5 * * * * chronic /home/nilm/data/capture.sh
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# Run fsck at startup
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@reboot chronic nilmdb-fsck --fix --no-data /home/nilm/data/db/
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32
extras/sample-cron-scripts/process.sh
Executable file
32
extras/sample-cron-scripts/process.sh
Executable file
@@ -0,0 +1,32 @@
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#!/bin/bash
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# Run all necessary processing on NilmDB data.
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# Bail out on errors
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set -e
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# Ensure only one copy of this code runs at a time:
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LOCKFILE="/tmp/nilmdb-process.lock"
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exec 99>"$LOCKFILE"
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if ! flock -n -x 99 ; then
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echo "NilmDB processing already running, giving up..."
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exit 0
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fi
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trap 'rm -f "$LOCKFILE"' 0
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# redirect stdout/stderr to log, but keep it on the console too
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exec > >(tee /home/nilm/data/process.log)
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exec 2> >(tee -a /home/nilm/data/process.log >&2)
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echo "sinefit on phase A voltage"
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nilm-sinefit -c 5 /sharon/raw /sharon/sinefit
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echo "prep on A, B, C with appropriate rotations"
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nilm-prep -c 1 -r 0 /sharon/raw /sharon/sinefit /sharon/prep-a
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nilm-prep -c 2 -r 120 /sharon/raw /sharon/sinefit /sharon/prep-b
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nilm-prep -c 3 -r 240 /sharon/raw /sharon/sinefit /sharon/prep-c
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echo "decimate raw and prep data"
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nilm-decimate-auto /sharon/raw /sharon/prep*
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echo "run cleanup"
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nilm-cleanup --yes /home/nilm/data/cleanup.cfg
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40
extras/trainola-test-param-3.js
Normal file
40
extras/trainola-test-param-3.js
Normal file
@@ -0,0 +1,40 @@
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{
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"url": "http://bucket/nilmdb",
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"stream": "/sharon/prep-a",
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"dest_stream": "/test/jim",
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"start": 1364184839901599,
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"end": 1364184942407610.2,
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"columns": [ { "index": 0, "name": "P1" } ],
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"exemplars": [
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{
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"name": "A - True DBL Freezer ON",
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"dest_column": 0,
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"url": "http://bucket/nilmdb",
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"stream": "/sharon/prep-a",
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"columns": [ { "index": 0, "name": "P1" } ],
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"start": 1365277707649000,
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"end": 1365277710705000
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},
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{
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"name": "A - Boiler 1 Fan OFF",
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"dest_column": 1,
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"url": "http://bucket/nilmdb",
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"stream": "/sharon/prep-a",
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"columns": [ { "index": 0, "name": "P1" } ],
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"start": 1364188370735000,
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"end": 1364188373819000
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},
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{
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"name": "A - True DBL Freezer OFF",
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"dest_column": 2,
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"url": "http://bucket/nilmdb",
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"stream": "/sharon/prep-a",
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"columns": [ { "index": 0, "name": "P1" } ],
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"start": 1365278087982000,
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"end": 1365278089340000
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}
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]
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}
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@@ -12,6 +12,8 @@ import sys
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def main(argv = None):
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f = nilmtools.filter.Filter()
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parser = f.setup_parser("Copy a stream")
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parser.add_argument('-n', '--nometa', action='store_true',
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help="Don't copy or check metadata")
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# Parse arguments
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try:
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@@ -25,14 +27,15 @@ def main(argv = None):
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raise SystemExit(1)
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# Copy metadata
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meta = f.client_src.stream_get_metadata(f.src.path)
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f.check_dest_metadata(meta)
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if not args.nometa:
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meta = f.client_src.stream_get_metadata(f.src.path)
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f.check_dest_metadata(meta)
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# Copy all rows of data using the faster Numpy interfaces
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extractor = NumpyClient(f.src.url).stream_extract_numpy
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inserter = NumpyClient(f.dest.url).stream_insert_numpy_context
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for i in f.intervals():
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print "Processing", f.interval_string(i)
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print "Processing", i.human_string()
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with inserter(f.dest.path, i.start, i.end) as insert_ctx:
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for data in extractor(f.src.path, i.start, i.end):
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insert_ctx.insert(data)
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|
@@ -16,6 +16,8 @@ def main(argv = None):
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Example: %(prog)s -u http://host1/nilmdb -U http://host2/nilmdb /sharon/*
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""", skip_paths = True)
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parser.add_argument('-n', '--nometa', action='store_true',
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help="Don't copy or check metadata")
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parser.add_argument("path", action="store", nargs="+",
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help='Wildcard paths to copy')
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args = parser.parse_args(argv)
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@@ -56,6 +58,8 @@ def main(argv = None):
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new_argv.extend(["--end", "@" + repr(args.end)])
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if args.dry_run:
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new_argv.extend(["--dry-run"])
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if args.nometa:
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new_argv.extend(["--nometa"])
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if args.force_metadata:
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new_argv.extend(["--force-metadata"])
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new_argv.extend([stream[0], stream[0]])
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|
@@ -21,9 +21,9 @@ def main(argv = None):
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parser.add_argument("-u", "--url", action="store",
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default="http://localhost/nilmdb/",
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help="NilmDB server URL (default: %(default)s)")
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parser.add_argument('-f', '--factor', action='store', default=4, type=int,
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parser.add_argument("-f", "--factor", action="store", default=4, type=int,
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help='Decimation factor (default: %(default)s)')
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parser.add_argument("--force-metadata", action="store_true",
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parser.add_argument("-F", "--force-metadata", action="store_true",
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default = False,
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help="Force metadata changes if the dest "
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||||
"doesn't match")
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|
@@ -133,6 +133,34 @@ def process_numpy_interval(interval, extractor, inserter, warn_rows,
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# we'll not miss any data when we run again later.
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insert_ctx.update_end(old_array[processed][0])
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def example_callback_function(data, interval, args, insert_func, final):
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"""Example of the signature for the function that gets passed
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to process_numpy_interval.
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'data': array of data to process -- may be empty
|
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||||
'interval': overall interval we're processing (but not necessarily
|
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the interval of this particular chunk of data)
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|
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'args': opaque arguments passed to process_numpy
|
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|
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'insert_func': function to call in order to insert array of data.
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Should be passed a 2-dimensional array of data to insert.
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Data timestamps must be within the provided interval.
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|
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'final': True if this is the last bit of data for this
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contiguous interval, False otherwise.
|
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|
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Return value of 'function' is the number of data rows processed.
|
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Unprocessed data will be provided again in a subsequent call
|
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(unless 'final' is True).
|
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|
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If unprocessed data remains after 'final' is True, the interval
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being inserted will be ended at the timestamp of the first
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unprocessed data point.
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"""
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raise NotImplementedError("example_callback_function does nothing")
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class Filter(object):
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def __init__(self, parser_description = None):
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@@ -144,8 +172,8 @@ class Filter(object):
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self.dest = None
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self.start = None
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self.end = None
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self.interhost = False
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self.force_metadata = False
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self._interhost = False
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self._force_metadata = False
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if parser_description is not None:
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self.setup_parser(parser_description)
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self.parse_args()
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@@ -178,7 +206,7 @@ class Filter(object):
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default = False,
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help="Just print intervals that would be "
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"processed")
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group.add_argument("--force-metadata", action="store_true",
|
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group.add_argument("-F", "--force-metadata", action="store_true",
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default = False,
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help="Force metadata changes if the dest "
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"doesn't match")
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@@ -208,12 +236,12 @@ class Filter(object):
|
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if dest_url is None:
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dest_url = url
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if url != dest_url:
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self.interhost = True
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self._interhost = True
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self._client_src = Client(url)
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self._client_dest = Client(dest_url)
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if (not self.interhost) and (srcpath == destpath):
|
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if (not self._interhost) and (srcpath == destpath):
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raise ArgumentError("source and destination path must be different")
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# Open the streams
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@@ -231,8 +259,8 @@ class Filter(object):
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# Print info
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if not quiet:
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print "Source:", self.src.string(self.interhost)
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print " Dest:", self.dest.string(self.interhost)
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print "Source:", self.src.string(self._interhost)
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print " Dest:", self.dest.string(self._interhost)
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||||
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def parse_args(self, argv = None):
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||||
"""Parse arguments from a command line"""
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@@ -241,7 +269,7 @@ class Filter(object):
|
||||
self.set_args(args.url, args.dest_url, args.srcpath, args.destpath,
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args.start, args.end, quiet = False, parsed_args = args)
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self.force_metadata = args.force_metadata
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self._force_metadata = args.force_metadata
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if args.dry_run:
|
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for interval in self.intervals():
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print interval.human_string()
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||||
@@ -252,7 +280,7 @@ class Filter(object):
|
||||
"""Generate all the intervals that this filter should process"""
|
||||
self._using_client = True
|
||||
|
||||
if self.interhost:
|
||||
if self._interhost:
|
||||
# Do the difference ourselves
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||||
s_intervals = ( Interval(start, end)
|
||||
for (start, end) in
|
||||
@@ -289,10 +317,11 @@ class Filter(object):
|
||||
str(e), toparse))
|
||||
|
||||
def check_dest_metadata(self, data):
|
||||
"""See if the metadata jives, and complain if it doesn't. If
|
||||
there's no conflict, update the metadata to match 'data'."""
|
||||
"""See if the metadata jives, and complain if it doesn't. For
|
||||
each key in data, if the stream contains the key, it must match
|
||||
values. If the stream does not contain the key, it is created."""
|
||||
metadata = self._client_dest.stream_get_metadata(self.dest.path)
|
||||
if not self.force_metadata:
|
||||
if not self._force_metadata:
|
||||
for key in data:
|
||||
wanted = data[key]
|
||||
if not isinstance(wanted, basestring):
|
||||
@@ -316,7 +345,8 @@ class Filter(object):
|
||||
self._client_dest.stream_update_metadata(self.dest.path, data)
|
||||
|
||||
# The main filter processing method.
|
||||
def process_numpy(self, function, args = None, rows = 100000):
|
||||
def process_numpy(self, function, args = None, rows = 100000,
|
||||
intervals = None):
|
||||
"""Calls process_numpy_interval for each interval that currently
|
||||
exists in self.src, but doesn't exist in self.dest. It will
|
||||
process the data in chunks as follows:
|
||||
@@ -325,30 +355,13 @@ class Filter(object):
|
||||
corresponding to the data. The data is converted to a Numpy
|
||||
array in chunks of 'rows' rows at a time.
|
||||
|
||||
'function' should be defined as:
|
||||
# def function(data, interval, args, insert_func, final)
|
||||
If 'intervals' is not None, process those intervals instead of
|
||||
the default list.
|
||||
|
||||
'data': array of data to process -- may be empty
|
||||
|
||||
'interval': overall interval we're processing (but not necessarily
|
||||
the interval of this particular chunk of data)
|
||||
|
||||
'args': opaque arguments passed to process_numpy
|
||||
|
||||
'insert_func': function to call in order to insert array of data.
|
||||
Should be passed a 2-dimensional array of data to insert.
|
||||
Data timestamps must be within the provided interval.
|
||||
|
||||
'final': True if this is the last bit of data for this
|
||||
contiguous interval, False otherwise.
|
||||
|
||||
Return value of 'function' is the number of data rows processed.
|
||||
Unprocessed data will be provided again in a subsequent call
|
||||
(unless 'final' is True).
|
||||
|
||||
If unprocessed data remains after 'final' is True, the interval
|
||||
being inserted will be ended at the timestamp of the first
|
||||
unprocessed data point.
|
||||
'function' should be defined with the same interface as
|
||||
nilmtools.filter.example_callback_function. See the
|
||||
documentation of that for details. 'args' are passed to
|
||||
'function'.
|
||||
"""
|
||||
extractor = NumpyClient(self.src.url).stream_extract_numpy
|
||||
inserter = NumpyClient(self.dest.url).stream_insert_numpy_context
|
||||
@@ -358,7 +371,7 @@ class Filter(object):
|
||||
maxrows = rows)
|
||||
inserter_func = functools.partial(inserter, self.dest.path)
|
||||
|
||||
for interval in self.intervals():
|
||||
for interval in (intervals or self.intervals()):
|
||||
print "Processing", interval.human_string()
|
||||
process_numpy_interval(interval, extractor_func, inserter_func,
|
||||
rows * 3, function, args)
|
||||
|
@@ -53,7 +53,8 @@ def parse_args(argv = None):
|
||||
is stepped forward to match 'clock'.
|
||||
|
||||
- If 'data' is running ahead, there is overlap in the data, and an
|
||||
error is raised.
|
||||
error is raised. If '--skip' is specified, the current file
|
||||
is skipped instead of raising an error.
|
||||
"""))
|
||||
parser.add_argument("-u", "--url", action="store",
|
||||
default="http://localhost/nilmdb/",
|
||||
@@ -61,6 +62,8 @@ def parse_args(argv = None):
|
||||
group = parser.add_argument_group("Misc options")
|
||||
group.add_argument("-D", "--dry-run", action="store_true",
|
||||
help="Parse files, but don't insert any data")
|
||||
group.add_argument("-s", "--skip", action="store_true",
|
||||
help="Skip files if the data would overlap")
|
||||
group.add_argument("-m", "--max-gap", action="store", default=10.0,
|
||||
metavar="SEC", type=float,
|
||||
help="Max discrepency between clock and data "
|
||||
@@ -235,6 +238,10 @@ def main(argv = None):
|
||||
"is %s but clock time is only %s",
|
||||
timestamp_to_human(data_ts),
|
||||
timestamp_to_human(clock_ts))
|
||||
if args.skip:
|
||||
printf("%s\n", err)
|
||||
printf("Skipping the remainder of this file\n")
|
||||
break
|
||||
raise ParseError(filename, err)
|
||||
|
||||
if (data_ts + max_gap) < clock_ts:
|
||||
|
111
nilmtools/math.py
Normal file
111
nilmtools/math.py
Normal file
@@ -0,0 +1,111 @@
|
||||
#!/usr/bin/python
|
||||
|
||||
# Miscellaenous useful mathematical functions
|
||||
from nilmdb.utils.printf import *
|
||||
from numpy import *
|
||||
from scipy import *
|
||||
|
||||
def sfit4(data, fs):
|
||||
"""(A, f0, phi, C) = sfit4(data, fs)
|
||||
|
||||
Compute 4-parameter (unknown-frequency) least-squares fit to
|
||||
sine-wave data, according to IEEE Std 1241-2010 Annex B
|
||||
|
||||
Input:
|
||||
data vector of input samples
|
||||
fs sampling rate (Hz)
|
||||
|
||||
Output:
|
||||
Parameters [A, f0, phi, C] to fit the equation
|
||||
x[n] = A * sin(f0/fs * 2 * pi * n + phi) + C
|
||||
where n is sample number. Or, as a function of time:
|
||||
x(t) = A * sin(f0 * 2 * pi * t + phi) + C
|
||||
|
||||
by Jim Paris
|
||||
(Verified to match sfit4.m)
|
||||
"""
|
||||
N = len(data)
|
||||
t = linspace(0, (N-1) / float(fs), N)
|
||||
|
||||
## Estimate frequency using FFT (step b)
|
||||
Fc = fft(data)
|
||||
F = abs(Fc)
|
||||
F[0] = 0 # eliminate DC
|
||||
|
||||
# Find pair of spectral lines with largest amplitude:
|
||||
# resulting values are in F(i) and F(i+1)
|
||||
i = argmax(F[0:int(N/2)] + F[1:int(N/2+1)])
|
||||
|
||||
# Interpolate FFT to get a better result (from Markus [B37])
|
||||
try:
|
||||
U1 = real(Fc[i])
|
||||
U2 = real(Fc[i+1])
|
||||
V1 = imag(Fc[i])
|
||||
V2 = imag(Fc[i+1])
|
||||
n = 2 * pi / N
|
||||
ni1 = n * i
|
||||
ni2 = n * (i+1)
|
||||
K = ((V2-V1)*sin(ni1) + (U2-U1)*cos(ni1)) / (U2-U1)
|
||||
Z1 = V1 * (K - cos(ni1)) / sin(ni1) + U1
|
||||
Z2 = V2 * (K - cos(ni2)) / sin(ni2) + U2
|
||||
i = arccos((Z2*cos(ni2) - Z1*cos(ni1)) / (Z2-Z1)) / n
|
||||
except Exception:
|
||||
# Just go with the biggest FFT peak
|
||||
i = argmax(F[0:int(N/2)])
|
||||
|
||||
# Convert to Hz
|
||||
f0 = i * float(fs) / N
|
||||
|
||||
# Fit it. We'll catch exceptions here and just returns zeros
|
||||
# if something fails with the least squares fit, etc.
|
||||
try:
|
||||
# first guess for A0, B0 using 3-parameter fit (step c)
|
||||
s = zeros(3)
|
||||
w = 2*pi*f0
|
||||
|
||||
# Now iterate 7 times (step b, plus 6 iterations of step i)
|
||||
for idx in range(7):
|
||||
D = c_[cos(w*t), sin(w*t), ones(N),
|
||||
-s[0] * t * sin(w*t) + s[1] * t * cos(w*t) ] # eqn B.16
|
||||
s = linalg.lstsq(D, data)[0] # eqn B.18
|
||||
w = w + s[3] # update frequency estimate
|
||||
|
||||
## Extract results
|
||||
A = sqrt(s[0]*s[0] + s[1]*s[1]) # eqn B.21
|
||||
f0 = w / (2*pi)
|
||||
phi = arctan2(s[0], s[1]) # eqn B.22 (flipped for sin instead of cos)
|
||||
C = s[2]
|
||||
return (A, f0, phi, C)
|
||||
except Exception as e:
|
||||
# something broke down; just return zeros
|
||||
return (0, 0, 0, 0)
|
||||
|
||||
def peak_detect(data, delta = 0.1):
|
||||
"""Simple min/max peak detection algorithm, taken from my code
|
||||
in the disagg.m from the 10-8-5 paper.
|
||||
|
||||
Returns an array of peaks: each peak is a tuple
|
||||
(n, p, is_max)
|
||||
where n is the row number in 'data', and p is 'data[n]',
|
||||
and is_max is True if this is a maximum, False if it's a minimum,
|
||||
"""
|
||||
peaks = [];
|
||||
cur_min = (None, inf)
|
||||
cur_max = (None, -inf)
|
||||
lookformax = False
|
||||
for (n, p) in enumerate(data):
|
||||
if p > cur_max[1]:
|
||||
cur_max = (n, p)
|
||||
if p < cur_min[1]:
|
||||
cur_min = (n, p)
|
||||
if lookformax:
|
||||
if p < (cur_max[1] - delta):
|
||||
peaks.append((cur_max[0], cur_max[1], True))
|
||||
cur_min = (n, p)
|
||||
lookformax = False
|
||||
else:
|
||||
if p > (cur_min[1] + delta):
|
||||
peaks.append((cur_min[0], cur_min[1], False))
|
||||
cur_max = (n, p)
|
||||
lookformax = True
|
||||
return peaks
|
@@ -84,13 +84,16 @@ def pipewatch(args):
|
||||
bufsize = -1, close_fds = True,
|
||||
stdin = devnull,
|
||||
stdout = subprocess.PIPE,
|
||||
stderr = None)
|
||||
stderr = None,
|
||||
preexec_fn = os.setpgrp)
|
||||
consumer = subprocess.Popen(args.consumer, shell = True,
|
||||
bufsize = -11, close_fds = True,
|
||||
stdin = subprocess.PIPE,
|
||||
stdout = None, stderr = None)
|
||||
stdout = None,
|
||||
stderr = None,
|
||||
preexec_fn = os.setpgrp)
|
||||
|
||||
queue = Queue.Queue(maxsize = 32)
|
||||
queue = Queue.Queue(maxsize = 4)
|
||||
reader = threading.Thread(target = reader_thread,
|
||||
args = (queue, generator.stdout.fileno()))
|
||||
reader.start()
|
||||
@@ -125,16 +128,21 @@ def pipewatch(args):
|
||||
return proc.poll()
|
||||
try:
|
||||
if poll_timeout(proc, 0.5) is None:
|
||||
proc.terminate()
|
||||
os.killpg(proc.pid, signal.SIGTERM)
|
||||
if poll_timeout(proc, 0.5) is None:
|
||||
proc.kill()
|
||||
os.killpg(proc.pid, signal.SIGKILL)
|
||||
except OSError:
|
||||
pass
|
||||
return poll_timeout(proc, 0.5)
|
||||
|
||||
# Wait for them to die, or kill them
|
||||
gret = kill(generator)
|
||||
cret = kill(consumer)
|
||||
gret = kill(generator)
|
||||
|
||||
# Consume all remaining data in the queue until the reader
|
||||
# and watcher threads are done
|
||||
while reader.is_alive() or watcher.is_alive():
|
||||
queue.get(True, 0.1)
|
||||
|
||||
fprintf(sys.stderr, "pipewatch: generator returned %d, " +
|
||||
"consumer returned %d\n", gret, cret)
|
||||
|
@@ -12,6 +12,7 @@ import scipy.fftpack
|
||||
import scipy.signal
|
||||
#from matplotlib import pyplot as p
|
||||
import bisect
|
||||
from nilmdb.utils.interval import Interval
|
||||
|
||||
def main(argv = None):
|
||||
# Set up argument parser
|
||||
@@ -80,11 +81,23 @@ def main(argv = None):
|
||||
f.check_dest_metadata({ "prep_raw_source": f.src.path,
|
||||
"prep_sinefit_source": sinefit.path,
|
||||
"prep_column": args.column,
|
||||
"prep_rotation": repr(rotation) })
|
||||
"prep_rotation": repr(rotation),
|
||||
"prep_nshift": args.nshift })
|
||||
|
||||
# Run the processing function on all data
|
||||
# Find the intersection of the usual set of intervals we'd filter,
|
||||
# and the intervals actually present in sinefit data. This is
|
||||
# what we will process.
|
||||
filter_int = f.intervals()
|
||||
sinefit_int = ( Interval(start, end) for (start, end) in
|
||||
client_sinefit.stream_intervals(
|
||||
args.sinepath, start = f.start, end = f.end) )
|
||||
intervals = nilmdb.utils.interval.intersection(filter_int, sinefit_int)
|
||||
|
||||
# Run the process (using the helper in the filter module)
|
||||
f.process_numpy(process, args = (client_sinefit, sinefit.path, args.column,
|
||||
args.nharm, rotation, args.nshift))
|
||||
args.nharm, rotation, args.nshift),
|
||||
intervals = intervals)
|
||||
|
||||
|
||||
def process(data, interval, args, insert_function, final):
|
||||
(client, sinefit_path, column, nharm, rotation, nshift) = args
|
||||
|
@@ -3,6 +3,7 @@
|
||||
# Sine wave fitting.
|
||||
from nilmdb.utils.printf import *
|
||||
import nilmtools.filter
|
||||
import nilmtools.math
|
||||
import nilmdb.client
|
||||
from nilmdb.utils.time import (timestamp_to_human,
|
||||
timestamp_to_seconds,
|
||||
@@ -11,7 +12,6 @@ from nilmdb.utils.time import (timestamp_to_human,
|
||||
from numpy import *
|
||||
from scipy import *
|
||||
#import pylab as p
|
||||
import operator
|
||||
import sys
|
||||
|
||||
def main(argv = None):
|
||||
@@ -96,8 +96,11 @@ def process(data, interval, args, insert_function, final):
|
||||
rows = data.shape[0]
|
||||
|
||||
# Estimate sampling frequency from timestamps
|
||||
fs = (rows-1) / (timestamp_to_seconds(data[-1][0]) -
|
||||
timestamp_to_seconds(data[0][0]))
|
||||
ts_min = timestamp_to_seconds(data[0][0])
|
||||
ts_max = timestamp_to_seconds(data[-1][0])
|
||||
if ts_min >= ts_max:
|
||||
return 0
|
||||
fs = (rows-1) / (ts_max - ts_min)
|
||||
|
||||
# Pull out about 3.5 periods of data at once;
|
||||
# we'll expect to match 3 zero crossings in each window
|
||||
@@ -119,7 +122,7 @@ def process(data, interval, args, insert_function, final):
|
||||
t_max = timestamp_to_seconds(data[start+N-1, 0])
|
||||
|
||||
# Do 4-parameter sine wave fit
|
||||
(A, f0, phi, C) = sfit4(this, fs)
|
||||
(A, f0, phi, C) = nilmtools.math.sfit4(this, fs)
|
||||
|
||||
# Check bounds. If frequency is too crazy, ignore this window
|
||||
if f0 < f_min or f0 > f_max:
|
||||
@@ -187,76 +190,5 @@ def process(data, interval, args, insert_function, final):
|
||||
printf("%sMarked %d zero-crossings in %d rows\n", now, num_zc, start)
|
||||
return start
|
||||
|
||||
def sfit4(data, fs):
|
||||
"""(A, f0, phi, C) = sfit4(data, fs)
|
||||
|
||||
Compute 4-parameter (unknown-frequency) least-squares fit to
|
||||
sine-wave data, according to IEEE Std 1241-2010 Annex B
|
||||
|
||||
Input:
|
||||
data vector of input samples
|
||||
fs sampling rate (Hz)
|
||||
|
||||
Output:
|
||||
Parameters [A, f0, phi, C] to fit the equation
|
||||
x[n] = A * sin(f0/fs * 2 * pi * n + phi) + C
|
||||
where n is sample number. Or, as a function of time:
|
||||
x(t) = A * sin(f0 * 2 * pi * t + phi) + C
|
||||
|
||||
by Jim Paris
|
||||
(Verified to match sfit4.m)
|
||||
"""
|
||||
N = len(data)
|
||||
t = linspace(0, (N-1) / float(fs), N)
|
||||
|
||||
## Estimate frequency using FFT (step b)
|
||||
Fc = fft(data)
|
||||
F = abs(Fc)
|
||||
F[0] = 0 # eliminate DC
|
||||
|
||||
# Find pair of spectral lines with largest amplitude:
|
||||
# resulting values are in F(i) and F(i+1)
|
||||
i = argmax(F[0:int(N/2)] + F[1:int(N/2+1)])
|
||||
|
||||
# Interpolate FFT to get a better result (from Markus [B37])
|
||||
U1 = real(Fc[i])
|
||||
U2 = real(Fc[i+1])
|
||||
V1 = imag(Fc[i])
|
||||
V2 = imag(Fc[i+1])
|
||||
n = 2 * pi / N
|
||||
ni1 = n * i
|
||||
ni2 = n * (i+1)
|
||||
K = ((V2-V1)*sin(ni1) + (U2-U1)*cos(ni1)) / (U2-U1)
|
||||
Z1 = V1 * (K - cos(ni1)) / sin(ni1) + U1
|
||||
Z2 = V2 * (K - cos(ni2)) / sin(ni2) + U2
|
||||
i = arccos((Z2*cos(ni2) - Z1*cos(ni1)) / (Z2-Z1)) / n
|
||||
|
||||
# Convert to Hz
|
||||
f0 = i * float(fs) / N
|
||||
|
||||
# Fit it. We'll catch exceptions here and just returns zeros
|
||||
# if something fails with the least squares fit, etc.
|
||||
try:
|
||||
# first guess for A0, B0 using 3-parameter fit (step c)
|
||||
s = zeros(3)
|
||||
w = 2*pi*f0
|
||||
|
||||
# Now iterate 7 times (step b, plus 6 iterations of step i)
|
||||
for idx in range(7):
|
||||
D = c_[cos(w*t), sin(w*t), ones(N),
|
||||
-s[0] * t * sin(w*t) + s[1] * t * cos(w*t) ] # eqn B.16
|
||||
s = linalg.lstsq(D, data)[0] # eqn B.18
|
||||
w = w + s[3] # update frequency estimate
|
||||
|
||||
## Extract results
|
||||
A = sqrt(s[0]*s[0] + s[1]*s[1]) # eqn B.21
|
||||
f0 = w / (2*pi)
|
||||
phi = arctan2(s[0], s[1]) # eqn B.22 (flipped for sin instead of cos)
|
||||
C = s[2]
|
||||
return (A, f0, phi, C)
|
||||
except Exception as e:
|
||||
# something broke down, just return zeros
|
||||
return (0, 0, 0, 0)
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
|
@@ -3,6 +3,7 @@
|
||||
from nilmdb.utils.printf import *
|
||||
import nilmdb.client
|
||||
import nilmtools.filter
|
||||
import nilmtools.math
|
||||
from nilmdb.utils.time import (timestamp_to_human,
|
||||
timestamp_to_seconds,
|
||||
seconds_to_timestamp)
|
||||
@@ -104,31 +105,6 @@ class Exemplar(object):
|
||||
self.name, self.stream, ",".join(self.columns.keys()),
|
||||
self.count)
|
||||
|
||||
def peak_detect(data, delta):
|
||||
"""Simple min/max peak detection algorithm, taken from my code
|
||||
in the disagg.m from the 10-8-5 paper"""
|
||||
mins = [];
|
||||
maxs = [];
|
||||
cur_min = (None, np.inf)
|
||||
cur_max = (None, -np.inf)
|
||||
lookformax = False
|
||||
for (n, p) in enumerate(data):
|
||||
if p > cur_max[1]:
|
||||
cur_max = (n, p)
|
||||
if p < cur_min[1]:
|
||||
cur_min = (n, p)
|
||||
if lookformax:
|
||||
if p < (cur_max[1] - delta):
|
||||
maxs.append(cur_max)
|
||||
cur_min = (n, p)
|
||||
lookformax = False
|
||||
else:
|
||||
if p > (cur_min[1] + delta):
|
||||
mins.append(cur_min)
|
||||
cur_max = (n, p)
|
||||
lookformax = True
|
||||
return (mins, maxs)
|
||||
|
||||
def timestamp_to_short_human(timestamp):
|
||||
dt = datetime_tz.datetime_tz.fromtimestamp(timestamp_to_seconds(timestamp))
|
||||
return dt.strftime("%H:%M:%S")
|
||||
@@ -164,11 +140,35 @@ def trainola_matcher(data, interval, args, insert_func, final_chunk):
|
||||
|
||||
# Find the peaks using the column with the largest amplitude
|
||||
biggest = e.scale.index(max(e.scale))
|
||||
peaks_minmax = peak_detect(corrs[biggest], 0.1)
|
||||
peaks = [ p[0] for p in peaks_minmax[1] ]
|
||||
peaks = nilmtools.math.peak_detect(corrs[biggest], 0.1)
|
||||
|
||||
# Now look at every peak
|
||||
for row in peaks:
|
||||
# To try to reduce false positives, discard peaks where
|
||||
# there's a higher-magnitude peak (either min or max) within
|
||||
# one exemplar width nearby.
|
||||
good_peak_locations = []
|
||||
for (i, (n, p, is_max)) in enumerate(peaks):
|
||||
if not is_max:
|
||||
continue
|
||||
ok = True
|
||||
# check up to 'e.count' rows before this one
|
||||
j = i-1
|
||||
while ok and j >= 0 and peaks[j][0] > (n - e.count):
|
||||
if abs(peaks[j][1]) > abs(p):
|
||||
ok = False
|
||||
j -= 1
|
||||
|
||||
# check up to 'e.count' rows after this one
|
||||
j = i+1
|
||||
while ok and j < len(peaks) and peaks[j][0] < (n + e.count):
|
||||
if abs(peaks[j][1]) > abs(p):
|
||||
ok = False
|
||||
j += 1
|
||||
|
||||
if ok:
|
||||
good_peak_locations.append(n)
|
||||
|
||||
# Now look at all good peaks
|
||||
for row in good_peak_locations:
|
||||
# Correlation for each column must be close enough to 1.
|
||||
for (corr, scale) in zip(corrs, e.scale):
|
||||
# The accepted distance from 1 is based on the relative
|
||||
@@ -287,8 +287,21 @@ def main(argv = None):
|
||||
|
||||
if argv is None:
|
||||
argv = sys.argv[1:]
|
||||
if len(argv) != 1:
|
||||
raise DataError("need one argument, either a dictionary or JSON string")
|
||||
if len(argv) != 1 or argv[0] == '-h' or argv[0] == '--help':
|
||||
printf("usage: %s [-h] [-v] <json-config-dictionary>\n\n", sys.argv[0])
|
||||
printf(" Where <json-config-dictionary> is a JSON-encoded " +
|
||||
"dictionary string\n")
|
||||
printf(" with exemplar and stream data.\n\n")
|
||||
printf(" See extras/trainola-test-param*.js in the nilmtools " +
|
||||
"repository\n")
|
||||
printf(" for examples.\n")
|
||||
if len(argv) != 1:
|
||||
raise SystemExit(1)
|
||||
raise SystemExit(0)
|
||||
|
||||
if argv[0] == '-v' or argv[0] == '--version':
|
||||
printf("%s\n", nilmtools.__version__)
|
||||
raise SystemExit(0)
|
||||
|
||||
try:
|
||||
# Passed in a JSON string (e.g. on the command line)
|
||||
|
Reference in New Issue
Block a user