def Gen_bragg(self, w, hkls, range_2th=(0, 90)):
wl, wlintn = w
r_tth = np.deg2rad(range_2th)
tag = FT.where(self.xray.tag_wl, wl)
if not hasattr(self, 'tags'):
self.tags = []
for hkl in hkls:
d_spacing = self.px.d_spacing(hkl)
sinth = wl / (2 * d_spacing)
if sinth < -1 or sinth > 1:
continue
tth = 2 * np.arcsin(sinth)
if tth < r_tth[0] or tth > r_tth[1]:
continue
peak = PK.Peak()
peak.tth = tth
peak.index = hkl
peak.d_spacing = d_spacing
peak.wl = wl
peak.wlintn = wlintn
peak.intn = self.Calc_peak_intn(peak)
if tag:
self.tags.append((peak, tag))
logging.debug(
'PEAK info:index: %r, d: %f, lambda:%f, tth: %f, intn: %f, tag: %r'
% (hkl, d_spacing, wl, np.rad2deg(tth), peak.intn, tag))
yield peak
def Calc_peak(self, hkls, EPS=0):
def isdeplicate(peak, peaks, EPS=np.deg2rad(0.05)):
if len(peaks) == 0:
return False
tth, gamma = peak.tth, peak.gamma
for i, p in enumerate(peaks):
if FT.equal(p.tth, tth, EPS) and FT.equal(p.gamma, gamma, EPS):
if peak.intn > p.intn:
logging.debug('%s is excluded because of %s' %
(peak.index.str, p.index.str))
# print('%s is excluded because of %s'%(p.index.str, peak.index.str))
del peaks[i]
else:
logging.debug('%s is excluded because of %s' %
(peak.index.str, p.index.str))
# print('%s is excluded because of %s'%(peak.index.str, p.index.str))
return True
return False
peaks = []
for sx in self.sx:
inc = self.inc
xr = self.xray
for hkl in hkls:
vec = sx.vec_in_rcp(hkl)
d_spacing = 1 / vec.length
tth = 2 * vec.betweenangle_rad(inc) - np.pi
if tth <= np.deg2rad(1) or tth >= np.deg2rad(179):
continue
wl = 2 * d_spacing * np.sin(tth / 2)
wlintn = xr.intn_wl(wl)
if wlintn == 0:
continue
k_inc = inc / wl
k_out = k_inc + vec
peak = PK.Peak()
peak.index = hkl
peak.vec = vec
peak.tth, peak.gamma = sx.tthgam_rad(k_out, z=inc, x=self.vx)
peak.wl = wl
peak.energy = xr.energy_from_lambda(wl)
peak.wlintn = wlintn
peak.d_spacing = d_spacing
peak.grain = sx
peak.intn = self.Calc_peak_intn(peak)
if peak.intn > EPS and not isdeplicate(peak, peaks):
logging.debug(
'PEAK info:index: %r, d: %f, lambda:%f, tth: %f, intn: %f'
% (hkl, d_spacing, wl, np.rad2deg(tth), peak.intn))
peaks.append(peak)
return np.array(peaks)
def new_peak_f(self, npeak):
self.payload_pix.insert(
0, peak.Peak(npeak.rgb, npeak.red, npeak.green, npeak.blue))
self.payload_pix.pop(len(self.payload_pix) - 1)
send_payload = []
for dd in range(self.parts):
if bool(self.direction) ^ bool(self.parts & 1):
for i in self.payload_pix[::-1]:
send_payload.append(i.red)
send_payload.append(i.green)
send_payload.append(i.blue)
else:
for i in self.payload_pix:
send_payload.append(i.red)
send_payload.append(i.green)
send_payload.append(i.blue)
return send_payload
bio_ps = [convert_biological_to_pvalue(sig) for sig in actual_sigs]
tech_ps = [convert_technical_to_pvalue(sig, mad) for sig, mad in zip(actual_sigs, mad_sigs)]
bio_qs = [convert_p_to_q(bio_p) for bio_p in bio_ps]
tech_qs= [convert_p_to_q(tech_p) for tech_p in tech_ps]
bio_tech_peaks = bio_and_tech_filter(bio_qs, tech_qs)
peaks = call_peaks(idr_filter(bio_tech_peaks, idrs), consolidate=args.bins)
averagerobustz = np.mean([rz.calculate_robust_z(sig) for sig in actual_sigs], 0)
# Make peaks
all_peaks = peak.PeakList()
for i, entry in enumerate(peaks):
start = entry[0]*args.resolution
end = entry[1]*args.resolution
max_value, max_idx = find_max_value(entry[0], entry[1], [averagerobustz], True)
max_valbio = find_max_value(entry[0], entry[1], bio_qs)
max_validr = find_max_value(entry[0], entry[1], idrs, False)
max_valtech = find_max_value(entry[0], entry[1], tech_qs, False)
this_peak = peak.Peak(args.chrom_name, start=int(start), end=int(end),
name = "%s_%s"%(args.outpre,i),
score = max_value,
signalval = max_valtech,
pval = max_valbio,
qval = max_validr, peak = int(max_idx*args.resolution))
if end-start >= args.bins*args.resolution:
all_peaks.add_Peak(this_peak)
else:
continue
# Write peaks
all_peaks.write_narrowPeak_file(args.outpre + ".narrowPeak")
qvalues = arrays[2]
# Make peaks
all_peaks = peak.PeakList()
for i, entry in enumerate(peaks):
start, end = entry
these_invals = array[start:end]
these_pvalues = pvalues[start:end]
these_qvalues = qvalues[start:end]
true_start = convert_coordinate(start, span[0], args.resolution)
true_end = convert_coordinate(end, span[0], args.resolution)
try:
max_idx = np.nanargmax(these_invals)
this_peak = peak.Peak(chrm = args.chrom_name, start=true_start, end=true_end,
name = "%s_%s"%(out_prefix,i),
score = int(these_qvalues[max_idx]*10),
signalval = these_invals[max_idx],
pval = these_pvalues[max_idx],
qval = these_qvalues[max_idx], peak = max_idx)
all_peaks.add_Peak(this_peak)
except:
max_idx = np.argmax(these_qvalues)
print(true_start, true_end, "failed", qvalues[max_idx], pvalues[max_idx])
# Write peaks
all_peaks.write_narrowPeak_file(out_prefix + ".narrowPeak")
if args.plots:
plt.tight_layout()
fig.savefig(out_prefix + ".png")
bio_tech_peaks = bio_and_tech_filter(bio_qs, tech_qs)
peaks = call_peaks(idr_filter(bio_tech_peaks, idrs), consolidate=args.bins)
averagerobustz = np.mean(
[rz.calculate_robust_z(sig) for sig in actual_sigs], 0)
# Make peaks
all_peaks = peak.PeakList()
for i, entry in enumerate(peaks):
start = entry[0] * args.resolution
end = entry[1] * args.resolution
max_value, max_idx = find_max_value(entry[0], entry[1],
[averagerobustz], True)
max_valbio = find_max_value(entry[0], entry[1], bio_qs)
max_validr = find_max_value(entry[0], entry[1], idrs, False)
max_valtech = find_max_value(entry[0], entry[1], tech_qs, False)
this_peak = peak.Peak("gi|48994873|gb|U00096.2|mod|ATCC.47076|",
start=int(start),
end=int(end),
name="%s_%s" % (args.outpre, i),
score=max_value,
signalval=max_valtech,
pval=max_valbio,
qval=max_validr,
peak=int(max_idx * args.resolution))
if end - start >= args.bins * args.resolution:
all_peaks.add_Peak(this_peak)
else:
continue
# Write peaks
all_peaks.write_narrowPeak_file(args.outpre + ".narrowPeak")
def __init__(self, pix_len, zigzag):
self.zigzag = zigzag
self.parts = 2 * zigzag
for i in range(pix_len // self.parts):
self.payload_pix.append(peak.Peak(0, 0, 0, 0))