analyse_burst

Usage
usage: analyse_burst.py [-h] [--nchan NCHAN] [--data_type DATA_TYPE] [--verbose VERBOSE] [--stack_plot STACK_PLOT] [--stack_off STACK_OFF] [--check_range CHECK_RANGE]
                        [--print_hash PRINT_HASH] [--fiducial_plot FIDUCIAL_PLOT] [--uut UUT]
                        data

Positional Arguments

data

data

Named Arguments

--nchan

Default: 32

--data_type

Use int16 or int32 for data demux.

--verbose

increase verbosity

Default: 0

--stack_plot

if non zero, make a stack plot of selected channel

Default: 0

--stack_off

offset each element in stack to make a waterfall chart

Default: 0

--check_range

c0,c1,[atol,rtol] : range of channels to check, atol, rtol: see numpy.rclose

Default: “1,1”

--print_hash

print sha1 of the file (protect against possibility of duplicate data

Default: 0

--fiducial_plot

if non zero, make a stack plot of selected channel

Default: 0

--uut

uut for title

Outline:

Created on 20 Jul 2023

@author: pgm

class ES_STATS[source]

Bases: object

the_stats = []
the_raw_ix = []
the_sample_counts = []
the_clk_counts = []
__init__(_es_fields)[source]
print()[source]
print_all()[source]
is_valid()[source]
get_raw_ix()[source]
get_sample_counts()[source]
get_clk_counts()[source]
get_blen()[source]
is_valid_es(iraw, es)[source]
analyse_es(args, raw_es)[source]
sample_count_plot(ax)[source]
timing_plot(ax)[source]
stack_plot(raw_adc, ch, ax, label='', delta=False, stackoff=0)[source]
correlate(raw_adc, ch0, _atol, _rtol)[source]
analyse_fiducial(args, raw_adc)[source]
plot_timeseries(raw_adc, ch, ax, label)[source]
analyse(args)[source]
get_parser()[source]
fix_args(args)[source]
run_main()[source]