1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
|
{# USES_VARIABLES { N, _clock_t, count,
_source_start, _source_stop} #}
{% extends 'common_group.pyx' %}
{% block maincode %}
{# Get the name of the array that stores these events (e.g. the spikespace array) #}
{% set _eventspace = get_array_name(eventspace_variable) %}
cdef size_t _num_events = {{_eventspace}}[_num{{_eventspace}}-1]
cdef size_t _start_idx, _end_idx, _curlen, _newlen, _j
{% for varname, var in record_variables | dictsort %}
cdef {{cpp_dtype(var.dtype)}}[:] _{{varname}}_view
{% endfor %}
if _num_events > 0:
# For subgroups, we do not want to record all spikes
# We assume that spikes are ordered
_start_idx = _num_events
_end_idx = _num_events
for _j in range(_num_events):
_idx = {{_eventspace}}[_j]
if _idx >= _source_start:
_start_idx = _j
break
for _j in range(_num_events-1, _start_idx-1, -1):
_idx = {{_eventspace}}[_j]
if _idx < _source_stop:
break
_end_idx = _j
_num_events = _end_idx - _start_idx
if _num_events > 0:
# scalar code
_vectorisation_idx = 1
{{ scalar_code|autoindent }}
_curlen = {{N}}
_newlen = _curlen + _num_events
# Resize the arrays
_owner.resize(_newlen)
{{N}} = _newlen
{% for varname, var in record_variables | dictsort %}
_{{varname}}_view = {{get_array_name(var, access_data=False)}}.data
{% endfor %}
# Copy the values across
for _j in range(_start_idx, _end_idx):
_idx = {{_eventspace}}[_j]
_vectorisation_idx = _idx
{{ vector_code|autoindent }}
{% for varname in record_variables | sort %}
_{{varname}}_view [_curlen + _j - _start_idx] = _to_record_{{varname}}
{% endfor %}
{{count}}[_idx - _source_start] += 1
{% endblock %}
|
