def main():
parser = ArgParser(
description='Calibrates DC offsets for the OffsetSubtractor',
formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument('--middlescale', dest='action', action='store_const',
const=middlescale, default=parser.print_help,
help='Sets the offset to the middle of the scale')
parser.add_argument('--curroff', dest='action', action='store_const',
const=curroff, default=parser.print_help,
help='Calibrates to the current measured offset')
args = parser.parse_args()
args.action()
def main():
description = 'Translates a model trained by gymnotools into C source code for compiling the recog module'
parser = ArgParser(description=description, formatter_class=argparse.RawTextHelpFormatter)
parser.add_argument('--filter', required=True, type=argparse.FileType('r'), help='Feature filter')
parser.add_argument('--rescale', required=True, type=argparse.FileType('rb'), help='Rescaling factors')
parser.add_argument('--svm', required=True, type=argparse.FileType('r'), help='SVM model')
args = parser.parse_args()
filtered_features = map(int, args.filter.xreadlines())
rescale_num_features = os.fstat(args.rescale.fileno()).st_size // np.dtype(np.float32).itemsize // 2
rescale = np.memmap(args.rescale, mode='r', dtype=np.float32, shape=(2, rescale_num_features))
rescale = np.array(rescale)
if rescale.shape[1] != len(filtered_features):
rescale = rescale[:, filtered_features]
svm = SVMModel(args.svm)
assert svm.elements == rescale.shape[1], 'SVM model trained for an incorrect number of features'
gen_filter('feature_filter.h', filtered_features)
gen_rescale('rescaling_factors.h', rescale)
gen_svm('svm_model.h', svm)
gen_cfg('generated_cfg.h')
def main():
description = "Generates a .spikes file from winCollect FIFO output"
parser = ArgParser(description=description, formatter_class=argparse.RawTextHelpFormatter)
parser.add_argument("fifofile", type=argparse.FileType("r"), help="Input data (from winCollect FIFO)")
parser.add_argument("outfile", type=argparse.FileType("w"), help="Output file (.spikes)")
parser.add_argument("--fixedwin", help="Fixed window (use for single-fish data files)", action="store_true")
parser.add_argument("--windowSize", type=int, default=cfg.SpikesWinSize, help="Window size, if --fixedwin")
parser.add_argument(
"--afterRef", type=int, default=cfg.SpikesAfterRef, help="Samples after reference point, if --fixedwin"
)
parser.add_argument("--saturation", type=str, help="high,low saturation level to filter out")
parser.add_argument("--onlyabove", type=float, default=0.0, help="Only output spikes above this amplitude")
parser.add_argument("--winlen", type=argparse.FileType("w"), help="Output original window lengths to a text file")
args = parser.parse_args()
fifofile = args.fifofile
nchan = cfg.EnabledCh
outfile = args.outfile
fixedwin = args.fixedwin
windowSize = args.windowSize
afterRef = args.afterRef
saturation = args.saturation
satHigh = np.inf
satLow = -np.inf
if saturation is not None:
satHigh = float(saturation.split(",")[0].strip())
satLow = float(saturation.split(",")[1].strip())
onlyAbove = args.onlyabove
winlenFile = args.winlen
afterRef += 1 # calc correction
lastEventLen = 0
for size, ref, ts, win in iter_fifo_windows(fifofile):
if winlenFile:
winlenFile.write("%d\n" % size)
if fixedwin == True:
samples = windowSize
window = np.zeros((windowSize, nchan))
win = win.reshape((size, nchan))
# cut end
if ref > afterRef:
win = win[: -ref + afterRef, :]
ref = afterRef
size = win.shape[0]
# cut start
if size > windowSize:
win = win[size - windowSize :, :]
size = win.shape[0]
# copy to fixed size window
assert ref <= afterRef
assert size <= windowSize
endpos = windowSize - afterRef + ref
startpos = endpos - size
window[startpos:endpos, :] = win
# fill any remaining samples with DC level
for i in xrange(0, startpos):
window[i, :] = window[startpos, :]
for i in xrange(endpos, windowSize):
window[i, :] = window[endpos - 1, :]
# make array plain once again
window = window.reshape((windowSize * nchan,))
else:
samples = size
window = win
filtered_windowsDic = check_window(window, nchan, samples, onlyAbove, satLow, satHigh)
offset = ts * nchan * np.dtype("float32").itemsize
outfile.write(struct.pack("i", lastEventLen))
outfile.write(struct.pack("q", offset))
outfile.write(struct.pack("i", samples))
outfile.write(struct.pack("i", len(filtered_windowsDic)))
lastLengths = 0
for c in sorted(filtered_windowsDic.keys()):
outfile.write(struct.pack("i", c))
buff = filtered_windowsDic[c].astype(np.dtype("float32")).tostring()
outfile.write(buff)
lastLengths = lastLengths + 4 + len(buff)
lastEventLen = headerLen + lastLengths