Python: Split sound file by transients - python

I wrote some functions that analyze a sound file, and are supposed to separate that sound file by it's transients(each time the sound in the file abruptly changes). You can listen the sound file in slow motion here to understand what I mean further.
def transients_from_onsets(onset_samples):
"""Takes a list of onset times for an audio file and returns the list of start and stop times for that audio file
Args:
onset_samples ([int]): I don't really know what these are actually. I thought they were start times for each sound change but I don't know
Returns:
[(int, int)]: A list of start and stop times for each sound change
"""
starts = onset_samples[0:-1]
stops = onset_samples[1:]
transientTimes = []
for s in range(len(starts)):
transientTimes.append((starts[s], stops[s]))
return transientTimes
def transients_from_sound_file(fileName, sr=44100):
"""Takes the path to an audio file
and returns the list of start and stop times for that audio file
as a frame rate
Args:
fileName (string): The path to an audio file
sr (int, optional): The sample rate of the audio file. Defaults to 44100.
Returns:
[(int, int)]: A list of start and stop times for each sound change
"""
y, sr = librosa.load(soundFile, sr=sr)
C = np.abs(librosa.cqt(y=y, sr=sr))
o_env = librosa.onset.onset_strength(sr=sr, S=librosa.amplitude_to_db(C, ref=np.max))
onset_frames = librosa.onset.onset_detect(onset_envelope=o_env, sr=sr)
onset_samples = list(librosa.frames_to_samples(onset_frames))
onset_samples = np.concatenate(onset_samples, len(y))
transientTimes = transients_from_onsets(onset_samples)
return transientTimes, transientSamples
The one I wrote works ok, but it's a little bit off what it should be, and some sounds are being split into 2 when they should only be one. Below I have the results that my program puts out, and the expected results. I'm wondering how I can get my results to look more like the expected results.
These are the start and stop times of each sound(transient) as determined by my program, followed by a link to the sound files created when the original sound file is split by these start and stop times
in frames: [(1536, 6144), (6144, 11264), (11264, 15360), (15360, 20992), (20992, 26624), (26624, 31744), (31744, 36352), (36352, 41984), (41984, 47104), (47104, 51712), (51712, 56832), (56832, 61440), (61440, 62976), (62976, 66560), (66560, 71680), (71680, 76800), (76800, 82944), (82944, 89088), (89088, 92672), (92672, 96768), (96768, 98304), (98304, 103936), (103936, 107008), (107008, 113664), (113664, 117760), (117760, 123904), (123904, 128512), (128512, 139264), (139264, 147968), (147968, 150016), (150016, 153088), (153088, 154624), (154624, 159232), (159232, 164864), (164864, 169472), (169472, 175616), (175616, 179200), (179200, 180736), (180736, 189440), (189440, 196096)]
in time: [(0.03566585034013605, 0.1426634013605442), (0.1426634013605442, 0.26154956916099775), (0.26154956916099775, 0.3566585034013605), (0.3566585034013605, 0.4874332879818594), (0.4874332879818594, 0.6182080725623583), (0.6182080725623583, 0.7370942403628118), (0.7370942403628118, 0.84409179138322), (0.84409179138322, 0.9748665759637188), (0.9748665759637188, 1.0937527437641723), (1.0937527437641723, 1.2007502947845805), (1.2007502947845805, 1.319636462585034), (1.319636462585034, 1.426634013605442), (1.426634013605442, 1.4622998639455782), (1.4622998639455782, 1.5455201814058959), (1.5455201814058959, 1.6644063492063492), (1.6644063492063492, 1.7832925170068026), (1.7832925170068026, 1.925955918367347), (1.925955918367347, 2.0686193197278913), (2.0686193197278913, 2.1518396371882087), (2.1518396371882087, 2.2469485714285717), (2.2469485714285717, 2.282614421768707), (2.282614421768707, 2.413389206349206), (2.413389206349206, 2.4847209070294785), (2.4847209070294785, 2.639272925170068), (2.639272925170068, 2.7343818594104308), (2.7343818594104308, 2.877045260770975), (2.877045260770975, 2.9840428117913835), (2.9840428117913835, 3.2337037641723354), (3.2337037641723354, 3.4358102494331066), (3.4358102494331066, 3.483364716553288), (3.483364716553288, 3.55469641723356), (3.55469641723356, 3.590362267573696), (3.590362267573696, 3.697359818594104), (3.697359818594104, 3.8281346031746035), (3.8281346031746035, 3.9351321541950113), (3.9351321541950113, 4.077795555555555), (4.077795555555555, 4.161015873015873), (4.161015873015873, 4.196681723356009), (4.196681723356009, 4.39878820861678), (4.39878820861678, 4.553340226757369)]
sound files
And these are what the start and stop times should be
in frames: [(2067, 6431), (6431, 10795), (10795, 15389), (15389, 25495), (25495, 28940), (28940, 33534), (33534, 38587), (38587, 43640), (43640, 47085), (47085, 51679), (51679, 55814), (55814, 60867), (60867, 65231), (65231, 69595), (69595, 75337), (75337, 79931), (79931, 83606), (83606, 87740), (87740, 96928), (96928, 101521), (101521, 105885), (105885, 110479), (110479, 115073), (115073, 124031), (124031, 133218), (133218, 137353), (137353, 142176), (142176, 147229), (147229, 152282), (152282, 155728), (155728, 160321), (160321, 169739)]
in time: [(0.0479956462585034, 0.1493275283446712), (0.1493275283446712, 0.250659410430839), (0.250659410430839, 0.3573318820861678), (0.3573318820861678, 0.5919927437641723), (0.5919927437641723, 0.6719854875283447), (0.6719854875283447, 0.7786579591836735), (0.7786579591836735, 0.8959883900226757), (0.8959883900226757, 1.013318820861678), (1.013318820861678, 1.0933115646258504), (1.0933115646258504, 1.1999840362811791), (1.1999840362811791, 1.2959985487528345), (1.2959985487528345, 1.4133289795918367), (1.4133289795918367, 1.5146608616780044), (1.5146608616780044, 1.6159927437641723), (1.6159927437641723, 1.749321723356009), (1.749321723356009, 1.8559941950113379), (1.8559941950113379, 1.9413275283446711), (1.9413275283446711, 2.037318820861678), (2.037318820861678, 2.2506637641723355), (2.2506637641723355, 2.357313015873016), (2.357313015873016, 2.4586448979591835), (2.4586448979591835, 2.565317369614512), (2.565317369614512, 2.6719898412698413), (2.6719898412698413, 2.879994195011338), (2.879994195011338, 3.093315918367347), (3.093315918367347, 3.1893304308390027), (3.1893304308390027, 3.3013202721088435), (3.3013202721088435, 3.4186507029478457), (3.4186507029478457, 3.5359811337868483), (3.5359811337868483, 3.615997097505669), (3.615997097505669, 3.722646349206349), (3.722646349206349, 3.9413318820861676)]
sound files

Related

Generating a nested dictionary in Python through iterations

I'm new in Python and I have to retrieve datas from a txt file (which I have already did) and then I need to make a nested dictionary like this:
new_dict = {"2009-10-16": {"KitchenSensor":"active for x minutes today",
"BathroomSensor":"active for y minutes today"...}
"2009-10-24":{"KitchenSensor":"active for x minutes today",
"BathroomSensor":"active for y minutes today"...}
"2009-11-13":{"KitchenSensor":"active for x minutes today",
"BathroomSensor":"active for y minutes today"...}}
my code looks like this
namesFile = open("data.txt", "r")
listaDati = namesFile.readlines()
listaDivisa = []
for i in listaDati:
if i[27] != "T":
listaDivisa.append(
i.split())
and the datas in my txt file have this format:
2009-10-16 00:01:04.000059 KITCHENSENSOR ON
2009-10-16 02:33:12.000093 KITCHENSENSOR OFF
2009-10-24 21:25:52.000023 BATHROOMSENSOR ON
2009-10-24 23:13:52.000014 BATHROOMSENSOR OFF
2009-11-13 09:03:23.000053 BATHROOMSENSOR ON
2009-11-13 12:13:42.000014 BATHROOMSENSOR OFF
the timestamp changes every now and then so I want to create a new key with the new timestamp everytime I meet a new one and saving the infos I have to save. I was trying doing this with an enumerative for loop but I don't understand how I can create the dictionary.
Thank you!

You're maybe looking for something like this; I separated the task into
parsing the input lines (could be from a file, but here they're just a list) into events (3-tuples of datetime, sensor name and state)
grouping the events by date, and looking at the state changes.
import datetime
from itertools import groupby
def parse_line(line):
# Split the line at the two spaces.
time_string, event = line.split(" ", 1)
# Split the rest of the line at one space.
sensor, event = event.split(" ", 1)
# Parse the time string to a real datetime object.
t = datetime.datetime.strptime(time_string, "%Y-%m-%d %H:%M:%S.%f")
return (t, sensor, event == "ON")
def collate_sorted_events(sorted_events):
zero_delta = datetime.timedelta(0)
for day, events in groupby(
sorted_events, lambda event_triple: event_triple[0].date()
):
# We're assuming all sensors start off each day.
turn_on_times = {}
durations = {}
for time, sensor, state in events:
if state: # Turning on?
# If it was on already, that's not an issue; we just consider that a glitch.
if sensor not in turn_on_times:
turn_on_times[sensor] = time
else:
if sensor not in turn_on_times:
raise ValueError("Sensor was turned off before it was turned on.")
this_duration = time - turn_on_times[sensor]
durations[sensor] = durations.get(sensor, zero_delta) + this_duration
del turn_on_times[sensor]
yield (day, durations)
if turn_on_times:
# This check could be removed, but for now it's a good sanity check...
raise ValueError(
"Some sensors were left on at the end of the day; this could be a problem"
)
listaDati = [
"2009-10-16 00:01:04.000059 KITCHENSENSOR ON",
"2009-10-16 02:33:12.000093 KITCHENSENSOR OFF",
"2009-10-24 21:25:52.000023 BATHROOMSENSOR ON",
"2009-10-24 23:13:52.000014 BATHROOMSENSOR OFF",
"2009-11-13 09:03:23.000053 BATHROOMSENSOR ON",
"2009-11-13 12:13:42.000014 BATHROOMSENSOR OFF",
]
# Parse and sort input lines. It's imperative that the events are sorted
# so the rest of the code works as it should.
sorted_events = sorted(parse_line(i) for i in listaDati)
# Collate events by day; the function yields day/durations tuples,
# and `dict` accepts that format to create a dict with.
output = dict(collate_sorted_events(sorted_events))
print(output)
for date, deltas in sorted(output.items()):
for sensor, delta in sorted(deltas.items()):
print(f"{date} {sensor} {delta.total_seconds() / 60:.2f} minutes")
The output is
{
datetime.date(2009, 10, 16): {'KITCHENSENSOR': datetime.timedelta(seconds=9128, microseconds=34)},
datetime.date(2009, 10, 24): {'BATHROOMSENSOR': datetime.timedelta(seconds=6479, microseconds=999991)},
datetime.date(2009, 11, 13): {'BATHROOMSENSOR': datetime.timedelta(seconds=11418, microseconds=999961)},
}
followed by the formatted
2009-10-16 KITCHENSENSOR 152.13 minutes
2009-10-24 BATHROOMSENSOR 108.00 minutes
2009-11-13 BATHROOMSENSOR 190.32 minutes

Output not displaying full list of elements appended

from csv import reader
def func(sku_list):
values = []
with open(sku_list, 'r', encoding = 'utf-8') as pr:
rows = reader(pr)
for sku in rows:
values.append(sku[1])
return(values)
if __name__ == '__main__':
dir_path = "C:/Users/XXXX/Downloads/"
vendors = dir_path + 'file.csv'
new_prices = func(vendors)
print(new_prices)
sku_list is a csv file filled with pairs of brand names and their skus that I have downloaded from my db, for some reason as it iters through the rows and grabs just the sku value, hence sku[1], it stops well short of the actual length I expect the list to be
sku_list is 85,892 tuples long but when I print out the values appended to the list values it simply returns this:
['SKU', 'MWGB4896', 'MWGB4872', 'MWGB4848', 'MWGB3648', 'WGB4896', 'WGB4872', 'WGB4848', 'WGB3648', 'WGB2436', 'WGB1824', 'BKGB4896NT', 'BKGB4872NT', 'BKGB4848NT', 'BKGB3648NT', 'BKGB2436NT', 'BKGB1824NT', 'WFC2418G', 'WFC2418', 'WFC3624', 'WFC2418LB', 'WFC3648LB', 'WFC3624LB', 'WFC3624G', 'WFC3648G', 'WFC3648', 'LOWFC3624LB', 'LOWFC3624G', 'LOWFC3624', 'LOWFC2418LB', 'LOWFC2418G', 'LOWFC2418', 'LOWFC3648LB', 'LOWFC3648', 'LOWFC3648G', 'WM-7-B', 'WM-7-G', 'WM-7-BK', 'WMC-7', 'WM-7-R', 'APS-50', 'APS-70', 'APS-60', 'APS-84', 'SS15W', 'SC15W', 'SB15W', 'MFL-2W', 'WP-48', 'WP-40', 'WP-36', 'MP-48', 'MP-40', 'MP-36', 'OP-40', 'OP-36', 'OP-48', 'FFVSU96-2', 'FFVSU144-2', 'FFVSU192-2', '1-WA-1B', '1-WA-1BP', 'WCS-12', 'WCS-144', 'OPLD3416LSPP-2', 'OPLD3416LSPP-4', 'OPLD3416LSPP-5', 'OPLD3416LSPP-7', 'OPLD3416LSPP-8', 'OPLD1818LSPP-2', 'OPLD1818LSPP-4', 'OPLD1818LSPP-5', 'OPLD1818LSPP-7', 'OPLD1818LSPP-8', 'OPLD1818L-2', 'OPLD1818L-5', 'OPLD1818L-4', 'OPLD3416L-2', 'OPLD3416L-4', 'OPLD3416L-5', 'OPLD3416L-7', 'OPLD3416L-8', 'OPLD1818L-7', 'OPLD1818L-8', 'OPLD3416SPP-8-892', 'OPLD3416SPP-8-897', 'OPLD3416SPP-8-878', 'OPLD3416SPP-8-885', 'OPLD3416SPP-8-887', 'OPLD3416SPP-8-890', 'OPLD3416SPP-8-845', 'OPLD3416SPP-8-854', 'OPLD3416SPP-8-856', 'OPLD3416SPP-8-876', 'OPLD3416SPP-8-802', 'OPLD3416SPP-8-706', 'OPLD3416SPP-8-705', 'OPLD3416SPP-8-704', 'OPLD3416SPP-8-837', 'OPLD3416SPP-8-831', 'OPLD3416SPP-8-819', 'OPLD3416SPP-8-812', 'OPLD3416SPP-8-685', 'OPLD3416SPP-8-683', 'OPLD3416SPP-8-679', 'OPLD3416SPP-8-531', 'OPLD3416SPP-8-703', 'OPLD3416SPP-8-702', 'OPLD3416SPP-8-701', 'OPLD3416SPP-8-700', 'OPLD3416SPP-7-892', 'OPLD3416SPP-7-897', 'OPLD3416SPP-7-887', 'OPLD3416SPP-7-890', 'OPLD3416SPP-8-530', 'OPLD3416SPP-7-845', 'OPLD3416SPP-7-854', 'OPLD3416SPP-7-831', 'OPLD3416SPP-7-837', 'OPLD3416SPP-7-878', 'OPLD3416SPP-7-885', 'OPLD3416SPP-7-856', 'OPLD3416SPP-7-876', 'OPLD3416SPP-7-703', 'OPLD3416SPP-7-702', 'OPLD3416SPP-7-705', 'OPLD3416SPP-7-704', 'OPLD3416SPP-7-802', 'OPLD3416SPP-7-706', 'OPLD3416SPP-7-819', 'OPLD3416SPP-7-812', 'OPLD3416SPP-7-530', 'OPLD3416SPP-7-679', 'OPLD3416SPP-7-531', 'OPLD3416SPP-7-685', 'OPLD3416SPP-7-683', 'OPLD3416SPP-7-701', 'OPLD3416SPP-7-700', 'OPLD3416SPP-5-878', 'OPLD3416SPP-5-885', 'OPLD3416SPP-5-887', 'OPLD3416SPP-5-890', 'OPLD3416SPP-5-892', 'OPLD3416SPP-5-897', 'OPLD3416SPP-5-812', 'OPLD3416SPP-5-819', 'OPLD3416SPP-5-831', 'OPLD3416SPP-5-837', 'OPLD3416SPP-5-845', 'OPLD3416SPP-5-854', 'OPLD3416SPP-5-856', 'OPLD3416SPP-5-876', 'OPLD1818SPP-8-819', 'OPLD1818SPP-8-831', 'OPLD1818SPP-8-802', 'OPLD1818SPP-8-812', 'OPLD1818SPP-8-854', 'OPLD1818SPP-8-856', 'OPLD1818SPP-8-837', 'OPLD1818SPP-8-845', 'OPLD1818SPP-8-701', 'OPLD1818SPP-8-702', 'OPLD1818SPP-8-685', 'OPLD1818SPP-8-700', 'OPLD1818SPP-8-705', 'OPLD1818SPP-8-706', 'OPLD1818SPP-8-703', 'OPLD1818SPP-8-704', 'OPLD1818SPP-8-887', 'OPLD1818SPP-8-885', 'OPLD1818SPP-8-878', 'OPLD1818SPP-8-876', 'OPLD1818SPP-8-897', 'OPLD1818SPP-8-892', 'OPLD1818SPP-8-890', 'OPLD3416SPP-4-837', 'OPLD3416SPP-4-831', 'OPLD3416SPP-4-854', 'OPLD3416SPP-4-845', 'OPLD3416SPP-4-802', 'OPLD3416SPP-4-706',
'OPLD3416SPP-4-819', 'OPLD3416SPP-4-812', 'OPLD3416SPP-4-890', 'OPLD3416SPP-4-887', 'OPLD3416SPP-4-897', 'OPLD3416SPP-4-892', 'OPLD3416SPP-4-876', 'OPLD3416SPP-4-856', 'OPLD3416SPP-4-885', 'OPLD3416SPP-4-878', 'OPLD3416SPP-5-531', 'OPLD3416SPP-5-679', 'OPLD3416SPP-5-683', 'OPLD3416SPP-5-685', 'OPLD3416SPP-5-530', 'OPLD3416SPP-5-704', 'OPLD3416SPP-5-705', 'OPLD3416SPP-5-706', 'OPLD3416SPP-5-802', 'OPLD3416SPP-5-700', 'OPLD3416SPP-5-701', 'OPLD3416SPP-5-702', 'OPLD3416SPP-5-703', 'OPLD3416SPP-2-837', 'OPLD3416SPP-2-831', 'OPLD3416SPP-2-819', 'OPLD3416SPP-2-812', 'OPLD3416SPP-2-802', 'OPLD3416SPP-2-706', 'OPLD3416SPP-2-705', 'OPLD3416SPP-2-704', 'OPLD3416SPP-2-890', 'OPLD3416SPP-2-887', 'OPLD3416SPP-2-885', 'OPLD3416SPP-2-878', 'OPLD3416SPP-2-876', 'OPLD3416SPP-2-856', 'OPLD3416SPP-2-854', 'OPLD3416SPP-2-845', 'OPLD3416SPP-4-531', 'OPLD3416SPP-4-679', 'OPLD3416SPP-4-530', 'OPLD3416SPP-2-892', 'OPLD3416SPP-2-897', 'OPLD3416SPP-4-704', 'OPLD3416SPP-4-705', 'OPLD3416SPP-4-702', 'OPLD3416SPP-4-703', 'OPLD3416SPP-4-700', 'OPLD3416SPP-4-701', 'OPLD3416SPP-4-683', 'OPLD3416SPP-4-685', 'OPLD3416SPP-2-530', 'OPLD3416SPP-2-531', 'OPLD3416SPP-2-679', 'OPLD3416SPP-2-683', 'OPLD3416SPP-2-685', 'OPLD3416SPP-2-700', 'OPLD3416SPP-2-701', 'OPLD3416SPP-2-702', 'OPLD3416SPP-2-703', 'OPLD1818SPP-7-819', 'OPLD1818SPP-7-831', 'OPLD1818SPP-7-837', 'OPLD1818SPP-7-845', 'OPLD1818SPP-7-705', 'OPLD1818SPP-7-706', 'OPLD1818SPP-7-802', 'OPLD1818SPP-7-812', 'OPLD1818SPP-7-701', 'OPLD1818SPP-7-702', 'OPLD1818SPP-7-703', 'OPLD1818SPP-7-704', 'OPLD1818SPP-7-679', 'OPLD1818SPP-7-683', 'OPLD1818SPP-7-685', 'OPLD1818SPP-7-700', 'OPLD1818SPP-8-531', 'OPLD1818SPP-8-530', 'OPLD1818SPP-8-683', 'OPLD1818SPP-8-679', 'OPLD1818SPP-7-897', 'OPLD1818SPP-7-887', 'OPLD1818SPP-7-885', 'OPLD1818SPP-7-892', 'OPLD1818SPP-7-890', 'OPLD1818SPP-7-856', 'OPLD1818SPP-7-854', 'OPLD1818SPP-7-878', 'OPLD1818SPP-7-876', 'OPLD1818SPP-5-819', 'OPLD1818SPP-5-831', 'OPLD1818SPP-5-802', 'OPLD1818SPP-5-812', 'OPLD1818SPP-5-705', 'OPLD1818SPP-5-706', 'OPLD1818SPP-5-703', 'OPLD1818SPP-5-704', 'OPLD1818SPP-5-701', 'OPLD1818SPP-5-702', 'OPLD1818SPP-5-685', 'OPLD1818SPP-5-700', 'OPLD1818SPP-5-679', 'OPLD1818SPP-5-683', 'OPLD1818SPP-5-530', 'OPLD1818SPP-5-531', 'OPLD1818SPP-7-531', 'OPLD1818SPP-7-530', 'OPLD1818SPP-5-897', 'OPLD1818SPP-5-892', 'OPLD1818SPP-5-890', 'OPLD1818SPP-5-887', 'OPLD1818SPP-5-885', 'OPLD1818SPP-5-878', 'OPLD1818SPP-5-876', 'OPLD1818SPP-5-856', 'OPLD1818SPP-5-854', 'OPLD1818SPP-5-845', 'OPLD1818SPP-5-837', 'OPLD1818SPP-4-701', 'OPLD1818SPP-4-702', 'OPLD1818SPP-4-703', 'OPLD1818SPP-4-704', 'OPLD1818SPP-4-705', 'OPLD1818SPP-4-706', 'OPLD1818SPP-4-802', 'OPLD1818SPP-4-812', 'OPLD1818SPP-4-530', 'OPLD1818SPP-4-531', 'OPLD1818SPP-4-679', 'OPLD1818SPP-4-683', 'OPLD1818SPP-4-685', 'OPLD1818SPP-4-700', 'OPLD1818SPP-4-887', 'OPLD1818SPP-2-837', 'OPLD1818SPP-2-845', 'OPLD1818SPP-2-854', 'OPLD1818SPP-2-856', 'OPLD1818SPP-2-802', 'OPLD1818SPP-2-812', 'OPLD1818SPP-2-819', 'OPLD1818SPP-2-831', 'OPLD1818SPP-2-890', 'OPLD1818SPP-2-892', 'OPLD1818SPP-2-897', 'OPLD1818SPP-2-876', 'OPLD1818SPP-2-878', 'OPLD1818SPP-2-885', 'OPLD1818SPP-2-887', 'OPLD1818SPP-2-531', 'OPLD1818SPP-2-530', 'OPLD1818SPP-2-683', 'OPLD1818SPP-2-679', 'OPLD1818SPP-2-704', 'OPLD1818SPP-2-703',
'OPLD1818SPP-2-706', 'OPLD1818SPP-2-705', 'OPLD1818SPP-2-700', 'OPLD1818SPP-2-685', 'OPLD1818SPP-2-702', 'OPLD1818SPP-2-701', 'OPLD1818SPP-4-876', 'OPLD1818SPP-4-878', 'OPLD1818SPP-4-854', 'OPLD1818SPP-4-856', 'OPLD1818SPP-4-837', 'OPLD1818SPP-4-845', 'OPLD1818SPP-4-819', 'OPLD1818SPP-4-831', 'OPLD1818SPP-4-897', 'OPLD1818SPP-4-890', 'OPLD1818SPP-4-892', 'OPLD1818SPP-4-885', 'PLD4832DPP-2-845', 'PLD4832DPP-2-837', 'PLD4832DPP-2-856', 'PLD4832DPP-2-854', 'PLD4832DPP-2-878', 'PLD4832DPP-2-876', 'PLD4832DPP-2-887', 'PLD4832DPP-2-885', 'PLD4832DPP-2-892', 'PLD4832DPP-2-890', 'PLD4832DPP-2-897', 'PLD4832DPP-4-531', 'PLD4832DPP-4-530', 'PLD4832DPP-4-679', 'PLD4832DPP-4-683', 'PLD4832DPP-4-685', 'PLD4832DPP-4-700', 'PLD4832DPP-4-701', 'PLD4832DPP-4-702', 'PLD4832DPP-4-703', 'PLD4832DPP-4-704', 'PLD4832DPP-4-705', 'PLD4832DPP-4-706', 'PLD4832DPP-4-802', 'PLD4832DPP-4-812', 'PLD4832DPP-4-819', 'PLD4832DPP-4-831', 'PLD4832DPP-4-837', 'PLD4832DPP-4-845', 'PLD4832DPP-4-878', 'PLD4832DPP-4-876', 'PLD4832DPP-4-856', 'PLD4832DPP-4-854', 'PLD4832DPP-4-892', 'PLD4832DPP-4-890', 'PLD4832DPP-4-887', 'PLD4832DPP-4-885', 'PLD4832DPP-4-897', 'PLD4832DPP-5-683', 'PLD4832DPP-5-679', 'PLD4832DPP-5-531', 'PLD4832DPP-5-530', 'PLD4832DPP-5-701', 'PLD4832DPP-5-702', 'PLD4832DPP-5-685', 'PLD4832DPP-5-700', 'PLD4832DPP-5-705', 'PLD4832DPP-5-706', 'PLD4832DPP-5-703', 'PLD4832DPP-5-704', 'PLD4832DPP-5-819', 'PLD4832DPP-5-831', 'PLD4832DPP-5-802', 'PLD4832DPP-5-812', 'PLD4832DPP-5-854', 'PLD4832DPP-5-856', 'PLD4832DPP-5-837', 'PLD4832DPP-5-845', 'PLD4832DPP-2-701', 'PLD4832DPP-2-702', 'PLD4832DPP-2-685', 'PLD4832DPP-2-700', 'PLD4832DPP-2-679', 'PLD4832DPP-2-683', 'PLD4832DPP-2-530', 'PLD4832DPP-2-531', 'PLD4832DPP-2-819', 'PLD4832DPP-2-831', 'PLD4832DPP-2-802', 'PLD4832DPP-2-812', 'PLD4832DPP-2-705', 'PLD4832DPP-2-706', 'PLD4832DPP-2-703', 'PLD4832DPP-2-704', 'PLD4226DPP-8-887', 'PLD4226DPP-8-890', 'PLD4226DPP-8-892', 'PLD4226DPP-8-897', 'PLD4226DPP-8-856', 'PLD4226DPP-8-876', 'PLD4226DPP-8-878', 'PLD4226DPP-8-885', 'PLD4226DPP-8-831', 'PLD4226DPP-8-837', 'PLD4226DPP-8-845', 'PLD4226DPP-8-854', 'PLD4226DPP-8-706', 'PLD4226DPP-8-802', 'PLD4226DPP-8-812', 'PLD4226DPP-8-819', 'PLD4226DPP-5-892', 'PLD4226DPP-5-897', 'PLD4226DPP-5-887', 'PLD4226DPP-5-890', 'PLD4226DPP-7-530', 'PLD4226DPP-7-683', 'PLD4226DPP-7-685', 'PLD4226DPP-7-531', 'PLD4226DPP-7-679', 'PLD4226DPP-7-702', 'PLD4226DPP-7-703', 'PLD4226DPP-7-700', 'PLD4226DPP-7-701', 'PLD4226DPP-5-705', 'PLD4226DPP-5-704', 'PLD4226DPP-5-703', 'PLD4226DPP-5-702', 'PLD4226DPP-5-819', 'PLD4226DPP-5-812', 'PLD4226DPP-5-802', 'PLD4226DPP-5-706', 'PLD4226DPP-5-854', 'PLD4226DPP-5-845', 'PLD4226DPP-5-837', 'PLD4226DPP-5-831', 'PLD4226DPP-5-885', 'PLD4226DPP-5-878', 'PLD4226DPP-5-876', 'PLD4226DPP-5-856', 'PLD4226DPP-7-892', 'PLD4226DPP-7-897', 'PLD4226DPP-8-530', 'PLD4226DPP-8-531', 'PLD4226DPP-8-679', 'PLD4226DPP-8-683', 'PLD4226DPP-8-685', 'PLD4226DPP-8-700', 'PLD4226DPP-8-701', 'PLD4226DPP-8-702', 'PLD4226DPP-8-703', 'PLD4226DPP-8-704', 'PLD4226DPP-8-705', 'PLD4226DPP-7-705', 'PLD4226DPP-7-704', 'PLD4226DPP-7-802', 'PLD4226DPP-7-706', 'PLD4226DPP-7-819', 'PLD4226DPP-7-812', 'PLD4226DPP-7-837', 'PLD4226DPP-7-831', 'PLD4226DPP-7-854', 'PLD4226DPP-7-845', 'PLD4226DPP-7-876', 'PLD4226DPP-7-856', 'PLD4226DPP-7-885', 'PLD4226DPP-7-878', 'PLD4226DPP-7-890', 'PLD4226DPP-7-887', 'PLD4226DPP-2-892', 'PLD4226DPP-2-897', 'PLD4226DPP-2-887', 'PLD4226DPP-2-890', 'PLD4226DPP-2-878', 'PLD4226DPP-2-885', 'PLD4226DPP-2-856', 'PLD4226DPP-2-876', 'PLD4226DPP-4-683', 'PLD4226DPP-4-685', 'PLD4226DPP-4-531', 'PLD4226DPP-4-679', 'PLD4226DPP-4-530', 'PLD4226DPP-2-705', 'PLD4226DPP-2-704', 'PLD4226DPP-2-703', 'PLD4226DPP-2-702', 'PLD4226DPP-2-701', 'PLD4226DPP-2-700', 'PLD4226DPP-2-685', 'PLD4226DPP-2-683', 'PLD4226DPP-2-854', 'PLD4226DPP-2-845', 'PLD4226DPP-2-837', 'PLD4226DPP-2-831', 'PLD4226DPP-2-819', 'PLD4226DPP-2-812', 'PLD4226DPP-2-802', 'PLD4226DPP-2-706', 'PLD4226DPP-4-892', 'PLD4226DPP-4-897', 'PLD4226DPP-4-878', 'PLD4226DPP-4-885', 'PLD4226DPP-4-887', 'PLD4226DPP-4-890', 'PLD4226DPP-5-683', 'PLD4226DPP-5-685', 'PLD4226DPP-5-700', 'PLD4226DPP-5-701', 'PLD4226DPP-5-530', 'PLD4226DPP-5-531', 'PLD4226DPP-5-679', 'PLD4226DPP-4-705', 'PLD4226DPP-4-704', 'PLD4226DPP-4-802', 'PLD4226DPP-4-706', 'PLD4226DPP-4-701', 'PLD4226DPP-4-700', 'PLD4226DPP-4-703', 'PLD4226DPP-4-702', 'PLD4226DPP-4-854', 'PLD4226DPP-4-845', 'PLD4226DPP-4-876', 'PLD4226DPP-4-856', 'PLD4226DPP-4-819', 'PLD4226DPP-4-812', 'PLD4226DPP-4-837', 'PLD4226DPP-4-831', 'PLD4226DPP-2-530', 'PLD4226DPP-2-679', 'PLD4226DPP-2-531', 'PLD5438DPP-5-683', 'PLD5438DPP-5-685', 'PLD5438DPP-5-531', 'PLD5438DPP-5-679', 'PLD5438DPP-5-702', 'PLD5438DPP-5-703', 'PLD5438DPP-5-700', 'PLD5438DPP-5-701', 'PLD5438DPP-5-706', 'PLD5438DPP-5-802', 'PLD5438DPP-5-704', 'PLD5438DPP-5-705', 'PLD5438DPP-5-831', 'PLD5438DPP-5-837', 'PLD5438DPP-5-812', 'PLD5438DPP-5-819', 'PLD5438DPP-5-876', 'PLD5438DPP-5-856', 'PLD5438DPP-5-854', 'PLD5438DPP-5-845', 'PLD5438DPP-5-890', 'PLD5438DPP-5-887', 'PLD5438DPP-5-885', 'PLD5438DPP-5-878', 'PLD5438DPP-5-897', 'PLD5438DPP-5-892', 'PLD5438DPP-7-679', 'PLD5438DPP-7-531', 'PLD5438DPP-7-530', 'PLD5438DPP-4-530', 'PLD5438DPP-4-531', 'PLD5438DPP-4-679', 'PLD5438DPP-4-683', 'PLD5438DPP-4-685', 'PLD5438DPP-4-700', 'PLD5438DPP-4-701', 'PLD5438DPP-4-702', 'PLD5438DPP-4-703', 'PLD5438DPP-4-704', 'PLD5438DPP-4-705', 'PLD5438DPP-4-706', 'PLD5438DPP-4-802', 'PLD5438DPP-4-812', 'PLD5438DPP-4-819', 'PLD5438DPP-4-837', 'PLD5438DPP-4-831', 'PLD5438DPP-4-854', 'PLD5438DPP-4-845', 'PLD5438DPP-4-876', 'PLD5438DPP-4-856', 'PLD5438DPP-4-885', 'PLD5438DPP-4-878', 'PLD5438DPP-4-890', 'PLD5438DPP-4-887', 'PLD5438DPP-4-897', 'PLD5438DPP-4-892', 'PLD5438DPP-5-530',
'PLD5438DPP
None
the final sku in there PLD5438DPP should be PLD5438DPP-5-683 and for some reason the list cuts off there, which is only element 564/85,892, and the program terminates without an error code
I cannot attach the file of skus, this is for my job, just hoping someone can shed light on what I am doing to cause the list to cut short like that
this may or may not also be relevant but when I call .append(sku) as opposed to sku[1] and grab the whole tuple the same issue occurs but at element 292, exactly half of the amount of element appended when only doing half the tuple

The issue seems to be one on my local machine, where it was unable to print such a long list, this one was of size 85,892
for those with similar issues see if any of our specs are overlapping and that may determine the cause of this issue:
VSCode:
Version: 1.52.0 (user setup)
Commit: 940b5f4bb5fa47866a54529ed759d95d09ee80be
Date: 2020-12-10T22:45:11.850Z
Electron: 9.3.5
Chrome: 83.0.4103.122
Node.js: 12.14.1
V8: 8.3.110.13-electron.0
OS: Windows_NT x64 10.0.18363
Python:
3.9.0
see discussion in comments for other details

How do you model multiple arrival distributions?

Python:
I am simulating a call-centre with 2 types of incoming calls: Sales calls, and service calls.
These calls have different, independent distributions, which enter the same system.
I have function, arrivals which contains:
iat_sales = random.expovariate(1/3)
yield env.timeout(iat_sales)
I want to incorporate:
iat_service = random.triangular(0,0,6)
yield env.timeout(iat_service)
how can I yield each event simultaneously?
This is the solution I have come up with:
def arrival_list():
sales_time = 0 #sim time of sales arrival
service_time = 0 #sim time of service arrival
sales_list=[] #list of sequential sales arrivals [arrival time,'sales']
service_list=[] #list of sequential sales arrivals [arrival time,'service']
arrivals = [] #ordered list of arrivals (sales and service merged) [arrival time,arrival type,iat]
while sales_time < sim_end:
iat_sales = random.expovariate(sales_rate)
sales_time += iat_sales
sales=[sales_time,'sales']
sales_list.append(sales)
while service_time < sim_end:
iat_service = random.triangular(0,6,0) ####
service_time += iat_service
service=[service_time,'service']
service_list.append(service)
arrivals = sales_list + service_list
arrivals.sort()
arrivals[0].append(arrivals[0][0])
for i in range(len(arrivals)-1):
arrivals[i+1].append(arrivals[i+1][0]-arrivals[i][0])
return arrivals

As a reference, a simple implementation can be done like this, where a simulation is run indefinitely with 1 second intervals and calls are considered to arrive if their random values exceed some thresholds:
import random
import time
def generate_calls():
return random.expovariate(1/3), random.triangular(10, 20, 5)
def simulation(count, sales_acceptance, services_acceptance):
# run the simulation indefinitely
while True:
print('Time: {}'.format(count))
sales_call, services_call = generate_calls()
# calls arrive if the values exceed some thresholds
if sales_call > sales_acceptance:
print('Sales call arrived!')
if services_call > services_acceptance:
print('Services call arrived!')
time.sleep(1)
count += 1
simulation(1, 2, 13)

You can have three separate parallel processes.
1- One process for making Sales calls.
2- One process for making service calls.
3- One process for handling calls.
import simpy
import random
sim_end = 1000;
def generateSalesCall(env, call_pipe):
while env.now < sim_end:
# put call in the pipe
yield call_pipe.put("sales");
interval = random.expovariate(1/3);
yield env.timeout(interval);
def generateServiceCall(env, call_pipe):
while env.now < sim_end:
# put call in the pipe
yield call_pipe.put("service");
interval = random.triangular(0,6,0);
yield env.timeout(interval);
def handleCalls(env, call_pipe):
while(True):
call = yield call_pipe.get();
if call == "sales":
print(env.now, "sales call");
elif call == "service":
print(env.now, "service call");
env = simpy.Environment();
call_pipe = simpy.Store(env);
env.process(generateSalesCall(env, call_pipe));
env.process(generateServiceCall(env, call_pipe));
env.process(handleCalls(env, call_pipe));
env.run();

For loop doesn't go all around a dictionary

so i have the code down below
import requests
import json
with open("forex_rates.json", "r") as file:
rate = json.load(file)
nrate = rate
Base = input("enter your base currency: ")
if Base not in rate["rates"]:
print("That's not a valid currency...")
Base = input("enter your base currency: ")
with open("forex_rates.json", "r") as file:
nrate["base"] = Base
for i in rate["rates"]:
nrate["rates"][i] = rate["rates"].get(i) / rate["rates"].get(Base)
print(nrate["rates"])
I'm trying to make a program that converts different currencies, for example:
1 EUR --> 1.18 USD
and in order to do this I have to edit the forex rates everytime depending on the base value
when i finished up the code i ran t and it worked all fine and it converted all values until it hit the same value in the forex value file
like if i convert from USD it will change all currency values depending on USD but when it hits the USD in the file the loop breaks
i tried for so long 'till i tried moving USD to the very bottom of the file as there is nothing after it to break. and it worked but that's for USD only.
when i change the base value inside the program it breaks again
for people saying the code isn't even finished i'd say that i almost finished this part of the program the converting part which i believe the most difficult and any other code left is only the GUI and some multiplying math
and i'll list the forex data below
#sorry if it's too big
{
"success":true,
"timestamp":1597402446,
"base":"EUR",
"date":"2020-08-14",
"rates":{
"AED":4.335266,
"AFN":91.176403,
"ALL":123.979569,
"AMD":572.651268,
"ANG":2.125143,
"AOA":695.22591,
"ARS":86.213707,
"AUD":1.651881,
"AWG":2.124558,
"AZN":2.001576,
"BAM":1.954795,
"BBD":2.390258,
"BDT":100.546318,
"BGN":1.956895,
"BHD":0.444938,
"BIF":2283.56194,
"BMD":1.18031,
"BND":1.622912,
"BOB":8.173103,
"BRL":6.336422,
"BSD":1.183874,
"BTC":0.0001,
"BTN":88.576746,
"BWP":13.863097,
"BYN":2.914727,
"BYR":23134.077322,
"BZD":2.38624,
"CAD":1.562064,
"CDF":2302.785095,
"CHF":1.074967,
"CLF":0.033942,
"CLP":936.574514,
"CNY":8.203627,
"COP":4452.129574,
"CRC":704.672423,
"CUC":1.18031,
"CUP":31.278217,
"CVE":110.201987,
"CZK":26.106129,
"DJF":210.746982,
"DKK":7.446693,
"DOP":69.149105,
"DZD":151.514114,
"EGP":18.805169,
"ERN":17.704664,
"ETB":42.448715,
"EUR":1,
"FJD":2.523208,
"FKP":0.90119,
"GBP":0.900976,
"GEL":3.647475,
"GGP":0.90119,
"GHS":6.811663,
"GIP":0.90119,
"GMD":61.163652,
"GNF":11418.288925,
"GTQ":9.116687,
"GYD":247.470583,
"HKD":9.14817,
"HNL":29.203723,
"HRK":7.531326,
"HTG":132.978265,
"HUF":346.161502,
"IDR":17595.177253,
"ILS":4.019203,
"IMP":0.90119,
"INR":88.434024,
"IQD":1413.229387,
"IRR":49696.95603,
"ISK":161.076893,
"JEP":0.90119,
"JMD":176.632894,
"JOD":0.836814,
"JPY":125.951475,
"KES":127.822789,
"KGS":92.238283,
"KHR":4859.521032,
"KMF":491.421896,
"KPW":1062.314938,
"KRW":1401.210938,
"KWD":0.360975,
"KYD":0.986486,
"KZT":496.331879,
"LAK":10752.381531,
"LBP":1789.879783,
"LKR":216.488093,
"LRD":235.294815,
"LSL":20.549263,
"LTL":3.485149,
"LVL":0.713958,
"LYD":1.626859,
"MAD":10.913322,
"MDL":19.82872,
"MGA":4566.909302,
"MKD":61.58448,
"MMK":1610.391686,
"MNT":3362.205621,
"MOP":9.449856,
"MRO":421.37087,
"MUR":46.799002,
"MVR":18.243058,
"MWK":879.737053,
"MXN":26.199071,
"MYR":4.949633,
"MZN":83.979304,
"NAD":20.548996,
"NGN":449.107914,
"NIO":41.242296,
"NOK":10.544902,
"NPR":141.752962,
"NZD":1.80663,
"OMR":0.454403,
"PAB":1.183663,
"PEN":4.2222,
"PGK":4.165565,
"PHP":57.516411,
"PKR":199.282277,
"PLN":4.396536,
"PYG":8227.988848,
"QAR":4.297547,
"RON":4.835722,
"RSD":117.576625,
"RUB":86.625365,
"RWF":1142.595148,
"SAR":4.426709,
"SBD":9.756128,
"SCR":21.044237,
"SDG":65.300702,
"SEK":10.291595,
"SGD":1.620105,
"SHP":0.90119,
"SLL":11537.53114,
"SOS":689.301231,
"SRD":8.802808,
"STD":25132.067341,
"SVC":10.358743,
"SYP":603.981109,
"SZL":20.627972,
"THB":36.753085,
"TJS":12.208818,
"TMT":4.131085,
"TND":3.240537,
"TOP":2.698542,
"TRY":8.706498,
"TTD":8.006077,
"TWD":34.707966,
"TZS":2744.220413,
"UAH":32.433598,
"UGX":4343.852885,
"USD":1.18031,
"UYU":50.261259,
"UZS":12111.300903,
"VEF":11.788346,
"VND":27353.095658,
"VUV":134.283098,
"WST":3.09309,
"XAF":655.754247,
"XAG":0.044343,
"XAU":0.000606,
"XCD":3.189847,
"XDR":0.840933,
"XOF":655.720927,
"XPF":119.624668,
"YER":295.426891,
"ZAR":20.617975,
"ZMK":10624.212769,
"ZMW":21.85909,
"ZWL":380.05997
}
}

R DTW multivariate series with asymmetric step fails to compute alignment

I'm using the DTW implementation found in R along with the python bindings in order to verify the effects of changing different parameters(like local constraint, local distance function and others) for my data. The data represents feature vectors that an audio processing frontend outputs(MFCC). Because of this I am dealing with multivariate time series, each feature vector has a size of 8. The problem I'm facing is when I try to use certain local constraints ( or step patterns ) I get the following error:
Error in if (is.na(gcm$distance)) { : argument is of length zero
Traceback (most recent call last):
File "r_dtw_simplified.py", line 32, in <module>
alignment = R.dtw(canDist, rNull, "Euclidean", stepPattern, "none", True, Fa
lse, True, False )
File "D:\Python27\lib\site-packages\rpy2\robjects\functions.py", line 86, in _
_call__
return super(SignatureTranslatedFunction, self).__call__(*args, **kwargs)
File "D:\Python27\lib\site-packages\rpy2\robjects\functions.py", line 35, in _
_call__
res = super(Function, self).__call__(*new_args, **new_kwargs)
rpy2.rinterface.RRuntimeError: Error in if (is.na(gcm$distance)) { : argument is
of length zero
Because the process of generating and adapting the input data is complicated I only made a simplified script to ilustrate the error i'm receiving.
#data works
#reference = [[-0.126678, -1.541763, 0.29985, 1.719757, 0.755798, -3.594681, -1.492798, 3.493042], [-0.110596, -1.638184, 0.128174, 1.638947, 0.721085, -3.247696, -0.920013, 3.763977], [-0.022415, -1.643539, -0.130692, 1.441742, 1.022064, -2.882172, -0.952225, 3.662842], [0.071259, -2.030411, -0.531891, 0.835114, 1.320419, -2.432281, -0.469116, 3.871094], [0.070526, -2.056702, -0.688293, 0.530396, 1.962128, -1.681915, -0.368973, 4.542419], [0.047745, -2.005127, -0.798203, 0.616028, 2.146988, -1.895874, 0.371597, 4.090881], [0.013962, -2.162796, -1.008545, 0.363495, 2.062866, -0.856613, 0.543884, 4.043335], [0.066757, -2.152969, -1.087097, 0.257263, 2.592697, -0.422424, -0.280533, 3.327576], [0.123123, -2.061035, -1.012863, 0.389282, 2.50206, 0.078186, -0.887711, 2.828247], [0.157455, -2.060425, -0.790344, 0.210419, 2.542114, 0.016983, -0.959274, 1.916504], [0.029648, -2.128204, -1.047318, 0.116547, 2.44899, 0.166534, -0.677551, 2.49231], [0.158554, -1.821365, -1.045044, 0.374207, 2.426712, 0.406952, -1.055084, 2.543762], [0.077026, -1.863235, -1.14827, 0.277069, 2.669067, 0.362549, -1.294342, 1.66748], [0.101822, -1.800293, -1.126801, 0.364594, 2.503815, 0.294846, -0.881302, 1.281616], [0.166138, -1.627762, -0.866013, 0.494476, 2.450668, 0.569, -1.392868, 0.651184], [0.225006, -1.596069, -1.07634, 0.550049, 2.167435, 0.554123, -1.432983, 1.166931], [0.114777, -1.462769, -0.793167, 0.565704, 2.183792, 0.345978, -1.410919, 0.708679], [0.144028, -1.444458, -0.831985, 0.536652, 2.222366, 0.330368, -0.715149, 0.517212], [0.147888, -1.450577, -0.809372, 0.479584, 2.271378, 0.250763, -0.540359, -0.036072], [0.090714, -1.485474, -0.888153, 0.268768, 2.001221, 0.412537, -0.698868, 0.17157], [0.11972, -1.382767, -0.890457, 0.218414, 1.666519, 0.659592, -0.069641, 0.914307], [0.189774, -1.18428, -0.785797, 0.106659, 1.429977, 0.195236, 0.627029, 0.503296], [0.194702, -1.098068, -0.956818, 0.020386, 1.369247, 0.10437, 0.641724, 0.410767], [0.215134, -1.069092, -1.11644, 0.283234, 1.313507, 0.110962, 0.600861, 0.752869], [0.216766, -1.065338, -1.047974, 0.080231, 1.500702, -0.113388, 0.712646, 0.914307], [0.259933, -0.964386, -0.981369, 0.092224, 1.480667, -0.00238, 0.896255, 0.665344], [0.265991, -0.935257, -0.93779, 0.214966, 1.235275, 0.104782, 1.33754, 0.599487], [0.266098, -0.62619, -0.905792, 0.131409, 0.402908, 0.103363, 1.352814, 1.554688], [0.273468, -0.354691, -0.709579, 0.228027, 0.315125, -0.15564, 0.942123, 1.024292], [0.246429, -0.272522, -0.609924, 0.318604, -0.007355, -0.165756, 1.07019, 1.087708], [0.248596, -0.232468, -0.524887, 0.53009, -0.476334, -0.184479, 1.088089, 0.667358], [0.074478, -0.200455, -0.058411, 0.662811, -0.111923, -0.686462, 1.205154, 1.271912], [0.063065, -0.080765, 0.065552, 0.79071, -0.569946, -0.899506, 0.875687, 0.095215], [0.117706, -0.270584, -0.021027, 0.723694, -0.200073, -0.365158, 0.892624, -0.152466], [0.00148, -0.075348, 0.017761, 0.757507, 0.719299, -0.355362, 0.749329, 0.315247], [0.035034, -0.110794, 0.038559, 0.949677, 0.478699, 0.005951, 0.097305, -0.388245], [-0.101944, -0.392487, 0.401886, 1.154938, 0.199127, 0.117371, -0.070007, -0.562439], [-0.083282, -0.388657, 0.449066, 1.505951, 0.46405, -0.566208, 0.216293, -0.528076], [-0.152054, -0.100113, 0.833054, 1.746857, 0.085861, -1.314102, 0.294632, -0.470947], [-0.166672, -0.183777, 0.988373, 1.925262, -0.202057, -0.961441, 0.15242, 0.594421], [-0.234573, -0.227707, 1.102112, 1.802002, -0.382492, -1.153336, 0.29335, 0.074036], [-0.336426, 0.042435, 1.255096, 1.804535, -0.610153, -0.810745, 1.308441, 0.599854], [-0.359344, 0.007248, 1.344543, 1.441559, -0.758286, -0.800079, 1.0233, 0.668213], [-0.321823, 0.027618, 1.1521, 1.509827, -0.708267, -0.668152, 1.05722, 0.710571], [-0.265335, 0.012344, 1.491501, 1.844971, -0.584137, -1.042419, -0.449188, 0.5354], [-0.302399, 0.049698, 1.440643, 1.674866, -0.626633, -1.158554, -0.906937, 0.405579], [-0.330276, 0.466675, 1.444153, 0.855499, -0.645447, -0.352158, 0.730423, 0.429932], [-0.354721, 0.540207, 1.570786, 0.626648, -0.897446, -0.007416, 0.174042, 0.100525], [-0.239609, 0.669983, 0.978851, 0.85321, -0.156784, 0.107986, 0.915054, 0.114197], [-0.189346, 0.930756, 0.824295, 0.516083, -0.339767, -0.206314, 0.744049, -0.36377]]
#query = [[0.387268, -1.21701, -0.432266, -1.394104, -0.458984, -1.469788, 0.12764, 2.310059], [0.418091, -1.389526, -0.150146, -0.759155, -0.578003, -2.123199, 0.276001, 3.022339], [0.264694, -1.526886, -0.238907, -0.511108, -0.90683, -2.699249, 0.692032, 2.849854], [0.246628, -1.675171, -0.533432, 0.070007, -0.392151, -1.739227, 0.534485, 2.744019], [0.099335, -1.983826, -0.985291, 0.428833, 0.26535, -1.285583, -0.234451, 2.4729], [0.055893, -2.108063, -0.401825, 0.860413, 0.724106, -1.959137, -1.360458, 2.350708], [-0.131592, -1.928314, -0.056213, 0.577698, 0.859146, -1.812286, -1.21669, 2.2052], [-0.162796, -2.149933, 0.467239, 0.524231, 0.74913, -1.829498, -0.741913, 1.616577], [-0.282745, -1.971008, 0.837616, 0.56427, 0.198288, -1.826935, -0.118027, 1.599731], [-0.497223, -1.578705, 1.277298, 0.682983, 0.055084, -2.032562, 0.64151, 1.719238], [-0.634232, -1.433258, 1.760513, 0.550415, -0.053787, -2.188568, 1.666687, 1.611938], [-0.607498, -1.302826, 1.960556, 1.331726, 0.417633, -2.271973, 2.095001, 0.9823], [-0.952957, -0.222076, 0.772064, 2.062256, -0.295258, -1.255371, 3.450974, -0.047607], [-1.210587, 1.00061, 0.036392, 1.952209, 0.470123, 0.231628, 2.670502, -0.608276], [-1.213287, 0.927002, -0.414825, 2.104065, 1.160126, 0.088898, 1.32959, -0.018311], [-1.081558, 1.007751, -0.337509, 1.7146, 0.653687, 0.297089, 1.916733, -0.772461], [-1.064804, 1.284302, -0.393585, 2.150635, 0.132294, 0.443298, 1.967575, 0.775513], [-0.972366, 1.039734, -0.588135, 1.413818, 0.423813, 0.781494, 1.977509, -0.556274], [-0.556381, 0.591309, -0.678314, 1.025635, 1.094284, 2.234711, 1.504013, -1.71875], [-0.063477, 0.626129, 0.360489, 0.149902, 0.92804, 0.936493, 1.203018, 0.264282], [0.162003, 0.577698, 0.956863, -0.477051, 1.081161, 0.817749, 0.660843, -0.428711], [-0.049515, 0.423615, 0.82489, 0.446228, 1.323853, 0.562775, -0.144196, 1.145386], [-0.146851, 0.171906, 0.304871, 0.320435, 1.378937, 0.673004, 0.188416, 0.208618], [0.33992, -2.072418, -0.447968, 0.526794, -0.175858, -1.400299, -0.452454, 1.396606], [0.226089, -2.183441, -0.301071, -0.475159, 0.834961, -2.191864, -1.092361, 2.434814], [0.279556, -2.073181, -0.517639, -0.766479, 0.974808, -2.070374, -2.003891, 2.706421], [0.237961, -1.9245, -0.708435, -0.582153, 1.285934, -1.75882, -2.146164, 2.369995], [0.149658, -1.703705, -0.539749, -0.215332, 1.369705, -1.484802, -1.506256, 1.04126], [0.078735, -1.719543, 0.157013, 0.382385, 1.100998, -0.223755, 0.021683, -0.545654], [0.106003, -1.404358, 0.372345, 1.881165, -0.292511, -0.263855, 1.579529, -1.426025], [0.047729, -1.198608, 0.600769, 1.901123, -1.106949, 0.128815, 1.293701, -1.364258], [0.110748, -0.894348, 0.712601, 1.728699, -1.250381, 0.674377, 0.812302, -1.428833], [0.085754, -0.662903, 0.794312, 1.102844, -1.234283, 1.084442, 0.986938, -1.10022], [0.140823, -0.300323, 0.673508, 0.669983, -0.551453, 1.213074, 1.449326, -1.567261], [0.03743, 0.550293, 0.400909, -0.174622, 0.355301, 1.325867, 0.875854, 0.126953], [-0.084885, 1.128906, 0.292099, -0.248779, 0.722961, 0.873871, -0.409515, 0.470581], [0.019684, 0.947754, 0.19931, -0.306274, 0.176849, 1.431702, 1.091507, 0.701416], [-0.094162, 0.895203, 0.687378, -0.229065, 0.549088, 1.376953, 0.892303, -0.642334], [-0.727692, 0.626495, 0.848877, 0.521362, 1.521912, -0.443481, 1.247238, 0.197388], [-0.82048, 0.117279, 0.975174, 1.487244, 1.085281, -0.567993, 0.776093, -0.381592], [-0.009827, -0.553009, -0.213135, 0.837341, 0.482712, -0.939423, 0.140884, 0.330566], [-0.018127, -1.362335, -0.199265, 1.260742, 0.005188, -1.445068, -1.159653, 1.220825], [0.186172, -1.727814, -0.246552, 1.544128, 0.285416, 0.081848, -1.634003, -0.47522], [0.193649, -1.144043, -0.334854, 1.220276, 1.241302, 1.554382, 0.57048, -1.334961], [0.344604, -1.647461, -0.720749, 0.993774, 0.585709, 0.953522, -0.493042, -1.845703], [0.37471, -1.989471, -0.518555, 0.555908, -0.025787, 0.148132, -1.463425, -0.844849], [0.34523, -1.821625, -0.809418, 0.59137, -0.577927, 0.037903, -2.067764, -0.519531], [0.413193, -1.503876, -0.752243, 0.280396, -0.236206, 0.429932, -1.684097, -0.724731], [0.331299, -1.349243, -0.890121, -0.178589, -0.285721, 0.809875, -2.012329, -0.157227], [0.278946, -1.090057, -0.670441, -0.477539, -0.267105, 0.446045, -1.95668, 0.501343], [0.127304, -0.977112, -0.660324, -1.011658, -0.547409, 0.349182, -1.357574, 1.045654], [0.217728, -0.793182, -0.496262, -1.259949, -0.128937, 0.38855, -1.513306, 1.863647], [0.240143, -0.891541, -0.619995, -1.478577, -0.361481, 0.258362, -1.630585, 1.841064], [0.241547, -0.758453, -0.515442, -1.370605, -0.428238, 0.23996, -1.469406, 1.307617], [0.289948, -0.714661, -0.533798, -1.574036, 0.017929, -0.368317, -1.290283, 0.851563], [0.304916, -0.783752, -0.459915, -1.523621, -0.107651, -0.027649, -1.089905, 0.969238], [0.27179, -0.795593, -0.352432, -1.597656, -0.001678, -0.06189, -1.072495, 0.637329], [0.301956, -0.823578, -0.152115, -1.637634, 0.2034, -0.214508, -1.315491, 0.773071], [0.282486, -0.853271, -0.162094, -1.561096, 0.15686, -0.289307, -1.076874, 0.673706], [0.299881, -0.97052, -0.051086, -1.431152, -0.074692, -0.32428, -1.385452, 0.684326], [0.220886, -1.072266, -0.269531, -1.038269, 0.140533, -0.711273, -1.7453, 1.090332], [0.177628, -1.229126, -0.274292, -0.943481, 0.483246, -1.214447, -2.026321, 0.719971], [0.176987, -1.137543, -0.007645, -0.794861, 0.965118, -1.084717, -2.37677, 0.598267], [0.135727, -1.36795, 0.09462, -0.776367, 0.946655, -1.157959, -2.794403, 0.226074], [0.067337, -1.648987, 0.535721, -0.665833, 1.506119, -1.348755, -3.092728, 0.281616], [-0.038101, -1.437347, 0.983917, -0.280762, 1.880722, -1.351318, -3.002258, -0.599609], [-0.152573, -1.146027, 0.717545, -0.60321, 2.126541, -0.59198, -2.282028, -1.048584], [-0.113525, -0.629669, 0.925323, 0.465393, 2.368698, -0.352661, -1.969391, -0.915161], [-0.140121, -0.311951, 0.884262, 0.809021, 1.557693, -0.552429, -1.776062, -0.925537], [-0.189423, -0.117767, 0.975174, 1.595032, 1.284485, -0.698639, -2.007202, -1.307251], [-0.048874, -0.176941, 0.820679, 1.306519, 0.584259, -0.913147, -0.658066, -0.630981], [-0.127594, 0.33313, 0.791336, 1.400696, 0.685577, -1.500275, -0.657959, -0.207642], [-0.044128, 0.653351, 0.615326, 0.476685, 1.099625, -0.902893, -0.154449, 0.325073], [-0.150223, 1.059845, 1.208405, -0.038635, 0.758667, 0.458038, -0.178909, -0.998657], [-0.099854, 1.127197, 0.789871, -0.013611, 0.452805, 0.736176, 0.948273, -0.236328], [-0.250275, 1.188568, 0.935989, 0.34314, 0.130463, 0.879913, 1.669037, 0.12793], [-0.122818, 1.441223, 0.670029, 0.389526, -0.15274, 1.293549, 1.22908, -1.132568]]
#this one doesn't
reference = [[-0.453598, -2.439209, 0.973587, 1.362091, -0.073654, -1.755112, 1.090057, 4.246765], [-0.448502, -2.621201, 0.723282, 1.257324, 0.26619, -1.375351, 1.328735, 4.46991], [-0.481247, -2.29718, 0.612854, 1.078033, 0.309708, -2.037506, 1.056305, 3.181702], [-0.42482, -2.306702, 0.436157, 1.529907, 0.50708, -1.930069, 0.653198, 3.561768], [-0.39032, -2.361343, 0.589294, 1.965607, 0.611801, -2.417084, 0.035675, 3.381104], [-0.233444, -2.281525, 0.703171, 2.17868, 0.519257, -2.474442, -0.502808, 3.569153], [-0.174652, -1.924591, 0.180267, 2.127075, 0.250626, -2.208527, -0.396591, 2.565552], [-0.121078, -1.53801, 0.234344, 2.221039, 0.845367, -1.516205, -0.174149, 1.298645], [-0.18631, -1.047806, 0.629654, 2.073303, 0.775024, -1.931076, 0.382706, 2.278442], [-0.160477, -0.78743, 0.694214, 1.917572, 0.834885, -1.574707, 0.780045, 2.370422], [-0.203659, -0.427246, 0.726486, 1.548767, 0.465698, -1.185379, 0.555206, 2.619629], [-0.208298, -0.393707, 0.771881, 1.646484, 0.612946, -0.996277, 0.658539, 2.499146], [-0.180679, -0.166656, 0.689209, 1.205994, 0.3918, -1.051483, 0.771072, 1.854553], [-0.1978, 0.082764, 0.723541, 1.019104, 0.165405, -0.127533, 1.0522, 0.552368], [-0.171127, 0.168533, 0.529541, 0.584839, 0.702011, -0.36525, 0.711792, 1.029114], [-0.224243, 0.38765, 0.916031, 0.45108, 0.708923, -0.059326, 1.016312, 0.437561], [-0.217072, -0.981766, 1.67363, 1.864014, 0.050812, -2.572815, -0.22937, 0.757996], [-0.284714, -0.784927, 1.720383, 1.782379, -0.093414, -2.492111, 0.623398, 0.629028], [-0.261169, -0.427979, 1.680038, 1.585358, 0.067093, -1.8181, 1.276291, 0.838989], [-0.183075, -0.08197, 1.094147, 1.120392, -0.117752, -0.86142, 1.94194, 0.966858], [-0.188919, 0.121521, 1.277664, 0.90979, 0.114288, -0.880875, 1.920517, 0.95752], [-0.226868, 0.338455, 0.78067, 0.803009, 0.347092, -0.387955, 0.641296, 0.374634], [-0.206329, 0.768158, 0.759537, 0.264099, 0.15979, 0.152618, 0.911636, -0.011597], [-0.230453, 0.495941, 0.547165, 0.137604, 0.36377, 0.594406, 1.168839, 0.125916], [0.340851, -0.382736, -1.060455, -0.267792, 1.1306, 0.595047, -1.544922, -1.6828], [0.341492, -0.325836, -1.07164, -0.215607, 0.895645, 0.400177, -0.773956, -1.827515], [0.392075, -0.305389, -0.885422, -0.293427, 0.993225, 0.66655, -1.061218, -1.730713], [0.30191, -0.339005, -0.877853, 0.153992, 0.986588, 0.711823, -1.100525, -1.648376], [0.303574, -0.491241, -1.000183, 0.075378, 0.686295, 0.752792, -1.192123, -1.744568], [0.315781, -0.629456, -0.996063, 0.224731, 1.074173, 0.757736, -1.170807, -2.08313], [0.313675, -0.804688, -1.00325, 0.431641, 0.685883, 0.538879, -0.988373, -2.421326], [0.267181, -0.790329, -0.726974, 0.853027, 1.369629, -0.213638, -1.708023, -1.977844], [0.304459, -0.935257, -0.778061, 1.042633, 1.391861, -0.296768, -1.562164, -2.014099], [0.169754, -0.792953, -0.481842, 1.404236, 0.766983, -0.29805, -1.587265, -1.25531], [0.15918, -0.9814, -0.197662, 1.748718, 0.888367, -0.880234, -1.64949, -1.359802], [0.028244, -0.772934, -0.186172, 1.594238, 0.863571, -1.224701, -1.153183, -0.292664], [-0.020401, -0.461578, 0.368088, 1.000366, 1.079636, -0.389603, -0.144409, 0.651733], [0.018555, -0.725418, 0.632599, 1.707336, 0.535049, -1.783859, -0.916122, 1.557007], [-0.038971, -0.797668, 0.820419, 1.483093, 0.350494, -1.465073, -0.786453, 1.370361], [-0.244888, -0.469513, 1.067978, 1.028809, 0.4879, -1.796585, -0.77887, 1.888977], [-0.260193, -0.226593, 1.141754, 1.21228, 0.214005, -1.200943, -0.441177, 0.532715], [-0.165283, 0.016129, 1.263016, 0.745514, -0.211288, -0.802368, 0.215698, 0.316406], [-0.353134, 0.053787, 1.544189, 0.21106, -0.469086, -0.485367, 0.767761, 0.849548], [-0.330215, 0.162704, 1.570053, 0.304718, -0.561172, -0.410294, 0.895126, 0.858093], [-0.333847, 0.173904, 1.56958, 0.075531, -0.5569, -0.259552, 1.276764, 0.749084], [-0.347107, 0.206665, 1.389832, 0.50473, -0.721664, -0.56955, 1.542618, 0.817444], [-0.299057, 0.140244, 1.402924, 0.215363, -0.62767, -0.550461, 1.60788, 0.506958], [-0.292084, 0.052063, 1.463348, 0.290497, -0.462875, -0.497452, 1.280609, 0.261841], [-0.279877, 0.183548, 1.308609, 0.305756, -0.6483, -0.374771, 1.647781, 0.161865], [-0.28389, 0.27916, 1.148636, 0.466736, -0.724442, -0.21991, 1.819901, -0.218872], [-0.275528, 0.309753, 1.192856, 0.398163, -0.828781, -0.268066, 1.763672, 0.116089], [-0.275284, 0.160019, 1.200623, 0.718628, -0.925552, -0.026596, 1.367447, 0.174866], [-0.302795, 0.383438, 1.10556, 0.441833, -0.968323, -0.137375, 1.851791, 0.357971], [-0.317078, 0.22876, 1.272217, 0.462219, -0.855789, -0.294296, 1.593994, 0.127502], [-0.304932, 0.207718, 1.156189, 0.481506, -0.866776, -0.340027, 1.670105, 0.657837], [-0.257217, 0.155655, 1.041428, 0.717926, -0.761597, -0.17244, 1.114151, 0.653503], [-0.321426, 0.292358, 0.73848, 0.422607, -0.850754, -0.057907, 1.462357, 0.697754], [-0.34642, 0.361526, 0.69722, 0.585175, -0.464508, -0.26651, 1.860596, 0.106201], [-0.339844, 0.584229, 0.542603, 0.184937, -0.341263, 0.085648, 1.837311, 0.160461], [-0.32338, 0.661224, 0.512833, 0.319702, -0.195572, 0.004028, 1.046799, 0.233704], [-0.346329, 0.572388, 0.385986, 0.118988, 0.057556, 0.039001, 1.255081, -0.18573], [-0.383392, 0.558395, 0.553391, -0.358612, 0.443573, -0.086014, 0.652878, 0.829956], [-0.420395, 0.668991, 0.64856, -0.021271, 0.511475, 0.639221, 0.860474, 0.463196], [-0.359039, 0.748672, 0.522964, -0.308899, 0.717194, 0.218811, 0.681396, 0.606812], [-0.323914, 0.942627, 0.249069, -0.418365, 0.673599, 0.797974, 0.162674, 0.120361], [-0.411301, 0.92775, 0.493332, -0.286346, 0.165054, 0.63446, 1.085571, 0.120789], [-0.346191, 0.632309, 0.635056, -0.402496, 0.143814, 0.785614, 0.952164, 0.482727], [-0.203812, 0.789261, 0.240433, -0.47699, -0.12912, 0.91832, 1.145493, 0.052002], [-0.048203, 0.632095, 0.009583, -0.53833, 0.232727, 1.293045, 0.308151, 0.188904], [-0.062393, 0.732315, 0.06694, -0.697144, 0.126221, 0.864578, 0.581635, -0.088379]]
query = [[-0.113144, -3.316223, -1.101563, -2.128418, 1.853867, 3.61972, 1.218185, 1.71228], [-0.128952, -3.37915, -1.152237, -2.033081, 1.860199, 4.008179, 0.445938, 1.665894], [-0.0392, -2.976654, -0.888245, -1.613953, 1.638641, 3.849518, 0.034073, 0.768188], [-0.146042, -2.980713, -1.044113, -1.44397, 0.954514, 3.20929, -0.232422, 1.050781], [-0.155029, -2.997192, -1.064438, -1.369873, 0.67688, 2.570709, -0.855347, 1.523438], [-0.102341, -2.686401, -1.029648, -1.00531, 0.950089, 1.933228, -0.526367, 1.598633], [-0.060272, -2.538727, -1.278259, -0.65332, 0.630875, 1.459717, -0.264038, 1.872925], [0.064087, -2.592682, -1.112823, -0.775024, 0.848618, 0.810883, 0.298965, 2.312134], [0.111557, -2.815277, -1.203506, -1.173584, 0.54863, 0.46756, -0.023071, 3.029053], [0.266068, -2.624786, -1.089066, -0.864136, 0.055389, 0.619446, -0.160965, 2.928589], [0.181488, -2.31073, -1.307785, -0.720276, 0.001297, 0.534668, 0.495499, 2.989502], [0.216202, -2.25354, -1.288193, -0.902039, -0.152283, -0.060791, 0.566315, 2.911621], [0.430084, -2.0289, -1.099594, -1.091736, -0.302505, -0.087799, 0.955963, 2.677002], [0.484253, -1.412842, -0.881882, -1.087158, -1.064072, -0.145935, 1.437683, 2.606567], [0.339081, -1.277222, -1.24498, -1.048279, -0.219498, 0.448517, 1.168625, 0.563843], [0.105728, 0.138275, -1.01413, -0.489868, 1.319275, 1.604645, 1.634003, -0.94812], [-0.209061, 1.025665, 0.180405, 0.955566, 1.527405, 0.91745, 1.951233, -0.40686], [-0.136993, 1.332275, 0.639862, 1.277832, 1.277313, 0.361267, 0.390717, -0.728394], [-0.217758, 1.416718, 1.080002, 0.816101, 0.343933, -0.154175, 1.10347, -0.568848]]
reference = np.array( reference )
query = np.array( query )
rpy2.robjects.numpy2ri.activate()
# Set up our R namespaces
R = rpy2.robjects.r
rNull = R("NULL")
rprint = rpy2.robjects.globalenv.get("print")
rplot = rpy2.robjects.r('plot')
distConstr = rpy2.robjects.r('proxy::dist')
DTW = importr('dtw')
stepName = "asymmetricP05"
stepPattern = rpy2.robjects.r( stepName )
canDist = distConstr( reference, query, "Euclidean" ) #
alignment = R.dtw(canDist, rNull, "Euclidean", stepPattern, "none", True, False, True, False )
For some series the script doesn't generate the error but there are some which do. See the commented lines for examples. It is worth noting that for the classic constraint this error does not appear. I am thinking that perhaps I have not set-up something correct but I am no expert in python nor in R so that is why I was hoping that others who have used the R DTW can help me on this. I am sorry for the long lines for reference and query (the data is from outputting the MFCC's of a 2 second wav file).

One of the two series is too short to be compatible with the fancy step pattern you chose. Use the common symmetric2 pattern, which does not restrict slopes, before the more exotic ones.

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