Fix unicode handling in filter metadata match

And adjust the period locator accordingly.
Fitting \sin is the same mathematically, it's just conceptually more
straightforward since we're locating zero crossings anyway.

setup.py

@@ -61,7 +61,7 @@ setup(name='nilmtools',
       long_description = "NILM Database Tools",
       license = "Proprietary",
       author_email = 'jim@jtan.com',
-      install_requires = [ 'nilmdb >= 1.5.0',
+      install_requires = [ 'nilmdb >= 1.6.0',
                            'numpy',
                            'scipy',
                            'matplotlib',

src/cleanup.py

@@ -238,12 +238,15 @@ def main(argv = None):
                        timestamp_to_seconds(total)))
             continue
         printf("  removing data before %s\n", timestamp_to_human(remove_before))
-        if args.yes:
+        # Clean in reverse order.  Since we only use the primary stream and not
-            client.stream_remove(path, None, remove_before)
+        # the decimated streams to figure out which data to remove, removing
-        for ap in streams[path].also_clean_paths:
+        # the primary stream last means that we might recover more nicely if
-            printf("  also removing from %s\n", ap)
+        # we are interrupted and restarted.
+        clean_paths = list(reversed(streams[path].also_clean_paths)) + [ path ]
+        for p in clean_paths:
+            printf("  removing from %s\n", p)
             if args.yes:
-                client.stream_remove(ap, None, remove_before)
+                client.stream_remove(p, None, remove_before)
 
     # All done
     if not args.yes:

src/decimate_auto.py

@@ -4,15 +4,19 @@ import nilmtools.filter
 import nilmtools.decimate
 import nilmdb.client
 import argparse
+import fnmatch
 
 def main(argv = None):
     parser = argparse.ArgumentParser(
         formatter_class = argparse.RawDescriptionHelpFormatter,
-        version = "1.0",
+        version = nilmtools.__version__,
         description = """\
     Automatically create multiple decimations from a single source
     stream, continuing until the last decimated level contains fewer
     than 500 points total.
+
+    Wildcards and multiple paths are accepted.  Decimated paths are
+    ignored when matching wildcards.
     """)
     parser.add_argument("-u", "--url", action="store",
                         default="http://localhost/nilmdb/",
@@ -23,20 +27,36 @@ def main(argv = None):
                         default = False,
                         help="Force metadata changes if the dest "
                         "doesn't match")
-    parser.add_argument("path", action="store",
+    parser.add_argument("path", action="store", nargs='+',
                         help='Path of base stream')
     args = parser.parse_args(argv)
 
     # Pull out info about the base stream
     client = nilmdb.client.Client(args.url)
 
-    info = nilmtools.filter.get_stream_info(client, args.path)
+    # Find list of paths to process
-    if not info:
+    streams = [ unicode(s[0]) for s in client.stream_list() ]
-        raise Exception("path " + args.path + " not found")
+    streams = [ s for s in streams if "~decim-" not in s ]
+    paths = []
+    for path in args.path:
+        new = fnmatch.filter(streams, unicode(path))
+        if not new:
+            print "error: no stream matched path:", path
+            raise SystemExit(1)
+        paths.extend(new)
 
-    meta = client.stream_get_metadata(args.path)
+    for path in paths:
+        do_decimation(client, args, path)
+
+def do_decimation(client, args, path):
+    print "Decimating", path
+    info = nilmtools.filter.get_stream_info(client, path)
+    if not info:
+        raise Exception("path " + path + " not found")
+
+    meta = client.stream_get_metadata(path)
     if "decimate_source" in meta:
-        print "Stream", args.path, "was decimated from", meta["decimate_source"]
+        print "Stream", path, "was decimated from", meta["decimate_source"]
         print "You need to pass the base stream instead"
         raise SystemExit(1)
 
@@ -53,7 +73,7 @@ def main(argv = None):
         if info.rows <= 500:
             break
         factor *= args.factor
-        new_path = "%s~decim-%d" % (args.path, factor)
+        new_path = "%s~decim-%d" % (path, factor)
 
         # Create the stream if needed
         new_info = nilmtools.filter.get_stream_info(client, new_path)
@@ -72,5 +92,7 @@ def main(argv = None):
         # Update info using the newly decimated stream
         info = nilmtools.filter.get_stream_info(client, new_path)
 
+    return
+
 if __name__ == "__main__":
     main()

src/filter.py

@@ -67,7 +67,7 @@ def get_stream_info(client, path):
 
 class Filter(object):
 
-    def __init__(self):
+    def __init__(self, parser_description = None):
         self._parser = None
         self._client_src = None
         self._client_dest = None
@@ -78,6 +78,9 @@ class Filter(object):
         self.end = None
         self.interhost = False
         self.force_metadata = False
+        if parser_description is not None:
+            self.setup_parser(parser_description)
+            self.parse_args()
 
     @property
     def client_src(self):
@@ -233,8 +236,12 @@ class Filter(object):
         metadata = self._client_dest.stream_get_metadata(self.dest.path)
         if not self.force_metadata:
             for key in data:
-                wanted = str(data[key])
+                wanted = data[key]
                 val = metadata.get(key, wanted)
+                # Force UTF-8 encoding for comparison and display
+                wanted = wanted.encode('utf-8')
+                val = val.encode('utf-8')
+                key = key.encode('utf-8')
                 if val != wanted and self.dest.rows > 0:
                     m =  "Metadata in destination stream:\n"
                     m += "  %s = %s\n" % (key, val)
@@ -275,6 +282,10 @@ class Filter(object):
         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.
         """
         if args is None:
             args = []
@@ -319,7 +330,13 @@ class Filter(object):
 
                 # Last call for this contiguous interval
                 if old_array.shape[0] != 0:
-                    function(old_array, interval, args, insert_function, True)
+                    processed = function(old_array, interval, args,
+                                         insert_function, True)
+                    if processed != old_array.shape[0]:
+                        # Truncate the interval we're inserting at the first
+                        # unprocessed data point.  This ensures that
+                        # we'll not miss any data when we run again later.
+                        insert_ctx.update_end(old_array[processed][0])
 
 def main(argv = None):
     # This is just a dummy function; actual filters can use the other

src/prep.py

@@ -3,6 +3,8 @@
 # Spectral envelope preprocessor.
 # Requires two streams as input: the original raw data, and sinefit data.
 
+from nilmdb.utils.printf import *
+from nilmdb.utils.time import timestamp_to_human
 import nilmtools.filter
 import nilmdb.client
 from numpy import *
@@ -77,7 +79,8 @@ def main(argv = None):
     # Check and set metadata in prep stream
     f.check_dest_metadata({ "prep_raw_source": f.src.path,
                             "prep_sinefit_source": sinefit.path,
-                            "prep_column": args.column })
+                            "prep_column": args.column,
+                            "prep_rotation": repr(rotation) })
 
     # Run the processing function on all data
     f.process_numpy(process, args = (client_sinefit, sinefit.path, args.column,
@@ -105,7 +108,6 @@ def process(data, interval, args, insert_function, final):
     # Pull out sinefit data for the entire time range of this block
     for sinefit_line in client.stream_extract(sinefit_path,
                                               data[0, 0], data[rows-1, 0]):
-
         def prep_period(t_min, t_max, rot):
             """
             Compute prep coefficients from time t_min to t_max, which
@@ -162,7 +164,15 @@ def process(data, interval, args, insert_function, final):
                 break
             processed = idx_max
 
-    print "Processed", processed, "of", rows, "rows"
+    # If we processed no data but there's lots in here, pretend we
+    # processed half of it.
+    if processed == 0 and rows > 10000:
+        processed = rows / 2
+        printf("%s: warning: no periods found; skipping %d rows\n",
+               timestamp_to_human(data[0][0]), processed)
+    else:
+        printf("%s: processed %d of %d rows\n",
+               timestamp_to_human(data[0][0]), processed, rows)
     return processed
 
 if __name__ == "__main__":

src/sinefit.py

@@ -18,6 +18,15 @@ def main(argv = None):
     group.add_argument('-f', '--frequency', action='store', type=float,
                        default=60.0,
                        help='Approximate frequency (default: %(default)s)')
+    group.add_argument('-m', '--min-freq', action='store', type=float,
+                       help='Minimum valid frequency '
+                       '(default: approximate frequency / 2))')
+    group.add_argument('-M', '--max-freq', action='store', type=float,
+                       help='Maximum valid frequency '
+                       '(default: approximate frequency * 2))')
+    group.add_argument('-a', '--min-amp', action='store', type=float,
+                       default=20.0,
+                       help='Minimum signal amplitude (default: %(default)s)')
 
     # Parse arguments
     try:
@@ -34,13 +43,24 @@ def main(argv = None):
         parser.error("need a column number >= 1")
     if args.frequency < 0.1:
         parser.error("frequency must be >= 0.1")
+    if args.min_freq is None:
+        args.min_freq = args.frequency / 2
+    if args.max_freq is None:
+        args.max_freq = args.frequency * 2
+    if (args.min_freq > args.max_freq or
+        args.min_freq > args.frequency or
+        args.max_freq < args.frequency):
+        parser.error("invalid min or max frequency")
+    if args.min_amp < 0:
+        parser.error("min amplitude must be >= 0")
 
     f.check_dest_metadata({ "sinefit_source": f.src.path,
                             "sinefit_column": args.column })
-    f.process_numpy(process, args = (args.column, args.frequency))
+    f.process_numpy(process, args = (args.column, args.frequency, args.min_amp,
+                                     args.min_freq, args.max_freq))
 
 def process(data, interval, args, insert_function, final):
-    (column, f_expected) = args
+    (column, f_expected, a_min, f_min, f_max) = args
     rows = data.shape[0]
 
     # Estimate sampling frequency from timestamps
@@ -66,18 +86,24 @@ def process(data, interval, args, insert_function, final):
         (A, f0, phi, C) = sfit4(this, fs)
 
         # Check bounds.  If frequency is too crazy, ignore this window
-        if f0 < (f_expected/2) or f0 > (f_expected*2):
+        if f0 < f_min or f0 > f_max:
-            print "frequency", f0, "too far from expected value", f_expected
+            print "frequency", f0, "outside valid range", f_min, "-", f_max
+            start += N
+            continue
+
+        # If amplitude is too low, results are probably just noise
+        if A < a_min:
+            print "amplitude", A, "below minimum threshold", a_min
             start += N
             continue
 
         #p.plot(arange(N), this)
-        #p.plot(arange(N), A * cos(f0/fs * 2 * pi * arange(N) + phi) + C, 'g')
+        #p.plot(arange(N), A * sin(f0/fs * 2 * pi * arange(N) + phi) + C, 'g')
 
-        # Period starts when the argument of cosine is 3*pi/2 degrees,
+        # Period starts when the argument of sine is 0 degrees,
         # so we're looking for sample number:
-        #     n = (3 * pi / 2 - phi) / (f0/fs * 2 * pi)
+        #     n = (0 - phi) / (f0/fs * 2 * pi)
-        zc_n = (3 * pi / 2 - phi) / (f0 / fs * 2 * pi)
+        zc_n = (0 - phi) / (f0 / fs * 2 * pi)
         period_n = fs/f0
 
         # Add periods to make N positive
@@ -123,15 +149,15 @@ def sfit4(data, fs):
 
     Output:
       Parameters [A, f0,  phi, C] to fit the equation
-        x[n] = A * cos(f0/fs * 2 * pi * n + phi) + C
+        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 * cos(f0 * 2 * pi * t + phi) + C
+        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) / fs, N)
+    t = linspace(0, (N-1) / float(fs), N)
 
     ## Estimate frequency using FFT (step b)
     Fc = fft(data)
@@ -156,32 +182,31 @@ def sfit4(data, fs):
     i = arccos((Z2*cos(ni2) - Z1*cos(ni1)) / (Z2-Z1)) / n
 
     # Convert to Hz
-    f0 = i * fs / N
+    f0 = i * float(fs) / N
 
-    ## Fit it
+    # Fit it.  We'll catch exceptions here and just returns zeros
-    # first guess for A0, B0 using 3-parameter fit (step c)
+    # if something fails with the least squares fit, etc.
-    w = 2*pi*f0
-    D = c_[cos(w*t), sin(w*t), ones(N)]
-    s = linalg.lstsq(D, data)[0]
-
-    # Now iterate 6 times (step i)
-    for idx in range(6):
-        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)
     try:
-        phi = -arctan2(s[1], s[0]) # eqn B.22
+        # first guess for A0, B0 using 3-parameter fit (step c)
-    except TypeError:
+        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)
-    C = s[2]
-
-    return (A, f0, phi, C)
 
 if __name__ == "__main__":
     main()