def view(binaryfile, probefile, nbits, chs, time, span):
'''
view raw or mua file with or without spk_info:
`spiketag view mua.bin spk.bin prb.json`
'''
from spiketag.base import probe
from spiketag.base import MUA
from vispy import app
nbits, time, span = int(nbits), float(time), float(span)
chs_tbview = slice(*[int(_) for _ in chs.split(',')])
prb = probe()
prb.load(probefile)
if len(binaryfile) == 2:
mua_filename, spk_filename = binaryfile
click.echo('loadding {} and {}'.format(mua_filename, spk_filename))
mua = MUA(mua_filename=mua_filename,
spk_filename=spk_filename,
probe=prb,
numbytes=nbits // 8,
scale=False)
if span == -1: span = None
mua.show(chs=prb.chs[chs_tbview], span=span, time=time)
app.run()
elif len(binaryfile) == 1:
mua_filename = binaryfile[0]
click.echo('loadding {}'.format(mua_filename))
mua = MUA(mua_filename=mua_filename,
spk_filename=None,
probe=prb,
numbytes=nbits // 8,
scale=False)
if span == -1: span = None
mua.show(chs=prb.chs[chs_tbview], span=span, time=time)
app.run()
def sort(binaryfile, probefile):
'''
sort without notebook:
`spiketag sort mua.bin spk.bin prb.json`
'''
mua_filename, spk_filename = binaryfile
click.echo('spiketag-sort: loadding {} and {}'.format(
mua_filename, spk_filename))
import sys
from PyQt5.QtWidgets import QApplication
from spiketag.mvc.Control import controller
from spiketag.base import probe
prb = probe()
prb.load(probefile)
app = QApplication(sys.argv)
ctrl = controller(probe=prb,
mua_filename=mua_filename,
spk_filename=spk_filename,
binary_radix=13,
scale=False
# time_segs=[[0,320]]
)
# ctrl.model.sort(clu_method='dpgmm', group_id=0, n_comp=8, max_iter=400)
ctrl.show()
sys.exit(app.exec_())
def view_data(filename, prbfile, nbits, time=0, span=5):
prb = probe()
prb.load(prbfile)
mua = MUA(filename, prb, numbytes=nbits // 8, scale=False)
if span == -1: span = None
mua.show(chs=prb.chs[:128], span=span, time=time)
app.run()
def prb_check(prbfile, font_size=33):
'''
check prb by visualization
'''
from spiketag.base import probe
prb = probe()
prb.load(prbfile)
prb.show(font_size)
def check_fpga(prbfile, var):
prb = probe()
prb.load(prbfile)
prb.n_ch = 160
prb.fs = 25000.
fpga = xike_config(prb)
if var in dir(fpga):
exec('print(fpga.{})'.format(var))
def fpga(probefile):
'''
init fpga with probe file:
`spiketag fpga prb.json`
'''
click.echo('init FPGA with probe file {}'.format(probefile))
from spiketag.fpga import xike_config
from spiketag.base import probe
prb = probe()
prb.load(probefile)
prb.show()
fpga = xike_config(prb)
click.echo('init FPGA success, check fpga with "spiketag fpga-check"')
def report(binaryfile, probefile, nbits=32):
'''
view raw or mua file with or without spk_info:
`spiketag view mua.bin spk.bin prb.json`
'''
from spiketag.base import probe
from spiketag.base import MUA
from collections import Counter
import seaborn as sns
import mplcursors
nbits = int(nbits)
prb = probe()
prb.load(probefile)
if len(binaryfile) == 2:
mua_filename, spk_filename = binaryfile
click.echo('loadding {} and {}'.format(mua_filename, spk_filename))
mua = MUA(mua_filename=mua_filename,
spk_filename=spk_filename,
probe=prb,
numbytes=nbits // 8,
scale=False)
## report ch<-->nspks statistics
spk_info = np.fromfile(spk_filename, np.int32).reshape(-1, 2)
t, ch = spk_info[:, 0] / prb.fs, spk_info[:, 1]
ch = ch[t > 0.004]
t = t[t > 0.004]
c = Counter(ch)
nspks = np.array([c[ch] for ch in prb.chs])
nspks_max = nspks.max()
sns.set_context('paper')
sns.set(font_scale=1.5)
sns.set_style('white')
plt.style.use('dark_background')
fig, ax = plt.subplots(1,
2,
figsize=(25, 15),
gridspec_kw={'width_ratios': [3, 1]})
sns.scatterplot(t,
prb.ch_idx[ch],
hue=prb.ch_idx[ch],
palette=plt.cm.hsv,
s=18,
marker='|',
legend=False,
ax=ax[0])
ax[0].set_facecolor((.1, .1, .1, .0))
ax[0].set_ylim(ax[0].get_ylim()[::-1])
ax[0].set_xlabel('Time(secs)')
ax[0].set_ylabel('Virtual Channel Number')
ax[0].set_yticks(np.arange(0, 160, 8))
ax[0].invert_yaxis()
ax[0].set_title('#spikes found on (channels) vs (time)')
nspks_img = ax[1].imshow(nspks.reshape(-1, prb.group_len),
cmap=plt.cm.magma) #ocean_r
ax[1].grid(which='minor', color='w', linestyle='-', linewidth=2)
ax[1].set_ylabel('Group Number')
ax[1].set_xticks(range(prb.group_len))
ax[1].set_yticks(range(prb.n_group))
ax[1].set_xlabel('Channels in the Group')
ax[1].set_title('#spikes found on (channels) in (group)')
ax[1].invert_yaxis()
sns.despine()
for i in range(prb.grp_matrix.shape[0]):
for j in range(prb.grp_matrix.shape[1]):
if nspks[prb.grp_matrix[i, j]] < nspks_max * 0.7:
ax[1].text(j,
i,
str(prb.grp_matrix[i, j]),
color='white',
ha='center',
va='center',
fontsize=10)
else:
ax[1].text(j,
i,
str(prb.grp_matrix[i, j]),
color='black',
ha='center',
va='center',
fontsize=10)
fig.colorbar(nspks_img)
plt.tight_layout()
mplcursors.cursor()
plt.show()
elif len(binaryfile) == 1:
mua_filename = binaryfile[0]
click.echo('loadding {}'.format(mua_filename))
mua = MUA(mua_filename=mua_filename,
spk_filename=None,
probe=prb,
numbytes=nbits // 8,
scale=False)
import numpy as np
from spiketag.base import probe
from spiketag.view import probe_view
prb_bowtie_LL = probe(shank_no=6, prb_type='bow_tie')
prb_bowtie_LL.shanks[0].l = [59, 60, 10, 58, 12, 11, 57, 56]
prb_bowtie_LL.shanks[0].r = [5, 52, 3, 54, 53, 4, 13, 2, 55]
prb_bowtie_LL.shanks[0].xl = -100.
prb_bowtie_LL.shanks[0].yl = 20
prb_bowtie_LL.shanks[0].xr = -80.
prb_bowtie_LL.shanks[0].yr = 5
prb_bowtie_LL.shanks[1].l = [15, 63, 48, 47, 0, 61, 9, 14, 62, 6]
prb_bowtie_LL.shanks[1].r = [8, 1, 51, 50, 18, 34, 31, 25, 33, 17, 22, 49]
prb_bowtie_LL.shanks[1].xl = -10.
prb_bowtie_LL.shanks[1].yl = 15
prb_bowtie_LL.shanks[1].xr = 10.
prb_bowtie_LL.shanks[1].yr = 0
prb_bowtie_LL.shanks[2].l = [39, 38, 20, 45, 44, 24, 7, 32, 16, 23, 46, 30]
prb_bowtie_LL.shanks[2].r = [
19, 37, 21, 35, 36, 26, 29, 40, 27, 42, 41, 28, 43
]
prb_bowtie_LL.shanks[2].xl = 80.
prb_bowtie_LL.shanks[2].yl = 10
prb_bowtie_LL.shanks[2].xr = 100.
prb_bowtie_LL.shanks[2].yr = -5
prb_bowtie_LL.shanks[3].l = [123, 124, 74, 122, 76, 75, 121, 120]
prb_bowtie_LL.shanks[3].r = [69, 116, 67, 118, 117, 68, 77, 66, 119]
def _to_txt(self, filename):
with open(filename,'w') as f:
for ch, pos in self.mapping.items():
_str = str(ch)+": " + str(pos) + '\n'
f.write(_str)
for grpNo in range(self.n_group):
_str = "groupNo_" + str(grpNo) + ":" + str(self[grpNo]) + '\n'
f.write(_str)
if __name__ == '__main__':
from spiketag.base import ch_group, shank, probe
# shk = shank()
# shk[1] = ch_group([3, 4, 10, 1])
prb = probe(shank_no=3)
prb[0].l = [59,60,10,58,12,11,57,56]
prb[0].r = [5,52,3,54,53,4,13,2,55]
prb[0].x = -100.
prb[0].y = 10
prb[1].l = [15,63,48,47,0,61,9,14,62,6]
prb[1].r = [8, 1,51,50,18,34,31,25,33,17,22]
prb[1].x = -50.
prb[1].y = 5
prb[2].l = [39,38,20,45,44,24,7,32,16,23,46,30]
prb[2].r = [19,37,21,35,36,26,29,40,27,42,41,28,43]
prb[2].x = 0.
prb[2].y = 0
# print prb[0]
def keyPressEvent(self, e):
print("event", e)
# if e.key() == Qt.Key_F5:
# if self.view_timer.isActive():
# self.view_timer.stop()
# else:
# self.view_timer.start(self.update_interval)
# self.close()
# if e.key()==Qt.Key_Space:
# self.close()
if __name__ == '__main__':
# 1. prb, gui and bmi and binner
app = QApplication(sys.argv)
prb = probe(prbfile='./dusty/dusty.json')
gui = BMI_RASTER_GUI(prb=prb, fet_file='./fet.bin')
bin_size, B_bins = 25e-3, 10
gui.bmi.set_binner(bin_size=bin_size, B_bins=B_bins)
# 2. decoder
# pos = np.fromfile('./sorting/dusty_pos.bin').reshape(-1,2)
# pc = place_field(pos=pos, t_step=33.333e-3)
# replay_offset = 2.004
# start = 320
# end = 2500
# pc.align_with_recording(start, end, replay_offset)
# pc.initialize(bin_size=4, v_cutoff=25)
# pc.load_spktag('./sorting/spktag/test_allspikes', show=True)
# dec = NaiveBayes(t_step=bin_size, t_window=B_bins*bin_size)
# dec.connect_to(pc)
