def save_matching(matching, lsensors, rescale=True):
"""
:param smatching:
:return:
"""
collist = choose_color(len(matching))
lpages = []
c = canvas.canvas()
c.text(0, (len(matching) + 1) * 5, "%s" % (datainfo.name), [text.size(5)])
for i, s in enumerate(lsensors):
c.text((i * 5) + 1, len(matching) * 5, s, [text.size(5)])
c.text((i * 5) + 1, -2, s, [text.size(5)])
for i, match in enumerate(matching):
p = path.rect(-5.5, i * 5, 5, 5)
c.stroke(p, [deco.filled([collist[i]])])
peaks = [False] * len(lsensors)
nclust = [''] * len(lsensors)
for m in match:
if m[0:4] in lsensors:
peaks[lsensors.index(m[0:4])] = True
nclust[lsensors.index(m[0:4])] = str(int(m[4:]) + 1)
for j in range(len(lsensors)):
if peaks[j]:
isens = datainfo.sensors.index(lsensors[j])
fname = datainfo.dpath + '/' + datainfo.name + "/Results/icons/" + datainfo.name + lsensors[j] \
+ '.nc' + str(datainfo.clusters[isens]) + '.cl' + nclust[j] + '.jpg'
bm = bitmap.jpegimage(fname)
bm.info = {}
bm.info['dpi'] = (100, 100)
bm2 = bitmap.bitmap(j * 5, i * 5, bm, compressmode=None)
c.insert(bm2)
lpages.append(document.page(c))
d = document.document(lpages)
res = ''
if rescale:
res = 'rescale'
d.writePDFfile(datainfo.dpath + '/' + datainfo.name +
"/Results/peaksmatching-%s-%s" % (datainfo.name, res))
def save_matching(matching, lsensors, rescale=True):
"""
:param smatching:
:return:
"""
collist = choose_color(len(matching))
lpages = []
c = canvas.canvas()
c.text(0, (len(matching)+1)*5, "%s" % (datainfo.name), [text.size(5)])
for i, s in enumerate(lsensors):
c.text((i*5)+1, len(matching)*5, s, [text.size(5)])
c.text((i*5)+1, -2, s, [text.size(5)])
for i, match in enumerate(matching):
p = path.rect(-5.5, i*5, 5, 5)
c.stroke(p, [deco.filled([collist[i]])])
peaks = [False] * len(lsensors)
nclust = [''] * len(lsensors)
for m in match:
if m[0:4] in lsensors:
peaks[lsensors.index(m[0:4])] = True
nclust[lsensors.index(m[0:4])] = str(int(m[4:])+1)
for j in range(len(lsensors)):
if peaks[j]:
isens = datainfo.sensors.index(lsensors[j])
fname = datainfo.dpath + '/' + datainfo.name + "/Results/icons/" + datainfo.name + lsensors[j] \
+ '.nc' + str(datainfo.clusters[isens]) + '.cl' + nclust[j] + '.jpg'
bm = bitmap.jpegimage(fname)
bm.info = {}
bm.info['dpi'] = (100, 100)
bm2 = bitmap.bitmap(j*5, i*5, bm, compressmode=None)
c.insert(bm2)
lpages.append(document.page(c))
d = document.document(lpages)
res = ''
if rescale:
res = 'rescale'
d.writePDFfile(datainfo.dpath + '/' + datainfo.name + "/Results/peaksmatching-%s-%s" % (datainfo.name, res))
def plot_sequences(nfile, lseq, nsym, sensor, lmatch=0, mapping=None):
"""
plots the sequence of frequent pairs
:param nfile:
:param lseq:
:return:
"""
if lmatch != 0:
collist = choose_color(lmatch)
else:
collist = choose_color(nsym)
lpages = []
c = canvas.canvas()
if lmatch != 0:
mtx = np.zeros(lmatch) + 0.5
for i in range(nsym):
mtx[mapping[i]] = 1
for i, col in enumerate(collist):
p = path.rect(3 + i, 7, 1, mtx[i])
c.stroke(p, [deco.filled([col])])
else:
for i, col in enumerate(collist):
p = path.rect(3 + i, 7, 1, 1)
c.stroke(p, [deco.filled([col])])
dpos = -5
step = 50
tres = 5000.0
stt = -1
c.text(0, 10, "%s-%s-%s-%s" % (datainfo.name, dfile, sensor, ename),
[text.size(5)])
for seq in lseq:
if len(seq) == 4:
tm1, pk1, tm2, pk2 = seq
coord = tm1 / tres
lng = (tm2 / tres) - coord
if lmatch != 0:
pk1 = int(mapping[pk1])
pk2 = int(mapping[pk2])
dcoord = int(coord / step)
ypos = dcoord * dpos
if stt != dcoord:
stt = dcoord
c.text(0, 3 + ypos, str(tm1), [text.size(1)])
p = path.rect(3 + coord - (dcoord * step), 3 + ypos, lng / 2.0, 1)
c.stroke(p, [deco.filled([collist[pk1]])])
p = path.rect(3 + coord - (dcoord * step) + (lng / 2.0), 3 + ypos,
lng / 2.0, 1)
c.stroke(p, [deco.filled([collist[pk2]])])
c.stroke(p)
# p = path.line(3+coord - (dcoord*step), 3+ypos + 1, 3+coord - (dcoord*step), 3+ypos + 2)
# c.stroke(p, [deco.filled([collist[pk1]])])
c.fill(
path.rect(3 + coord - (dcoord * step), 3 + ypos + 1, 0.05, 1),
[collist[pk1]])
else:
tm1, pk1 = seq
if lmatch != 0:
pk1 = int(mapping[pk1])
coord = tm1 / tres
dcoord = int(coord / step)
ypos = dcoord * dpos
if stt != dcoord:
stt = dcoord
c.text(0, 3 + ypos, str(tm1), [text.size(1)])
# p = path.line(3+coord - (dcoord*step), 3+ypos + 1, 3+coord - (dcoord*step), 3+ypos + 2)
# c.stroke(p, [deco.filled([collist[pk1]])])
c.fill(
path.rect(3 + coord - (dcoord * step), 3 + ypos + 1, 0.05, 1),
[collist[pk1]])
lpages.append(document.page(c))
d = document.document(lpages)
d.writePDFfile(datainfo.dpath + '/' + datainfo.name +
"/Results/peaksseq-%s-%s-%s-%s-%d" %
(datainfo.name, dfile, sensor, ename, nsym))
def plot_sequences(nfile, lseq, nsym, sensor, lmatch=0, mapping=None):
"""
plots the sequence of frequent pairs
:param nfile:
:param lseq:
:return:
"""
if lmatch != 0:
collist = choose_color(lmatch)
else:
collist = choose_color(nsym)
lpages = []
c = canvas.canvas()
if lmatch != 0:
mtx = np.zeros(lmatch) + 0.5
for i in range(nsym):
mtx[mapping[i]] = 1
for i, col in enumerate(collist):
p = path.rect(3 + i , 7, 1, mtx[i])
c.stroke(p, [deco.filled([col])])
else:
for i, col in enumerate(collist):
p = path.rect(3 + i , 7, 1, 1)
c.stroke(p, [deco.filled([col])])
dpos = -5
step = 50
tres = 5000.0
stt = -1
c.text(0, 10, "%s-%s-%s-%s" % (datainfo.name, dfile, sensor, ename), [text.size(5)])
for seq in lseq:
if len(seq) == 4:
tm1, pk1, tm2, pk2 = seq
coord = tm1 / tres
lng = (tm2/tres) - coord
if lmatch != 0:
pk1 = int(mapping[pk1])
pk2 = int(mapping[pk2])
dcoord = int(coord/step)
ypos = dcoord * dpos
if stt != dcoord:
stt = dcoord
c.text(0, 3+ypos, str(tm1), [text.size(1)])
p = path.rect(3+coord - (dcoord*step), 3+ypos, lng/2.0, 1)
c.stroke(p, [deco.filled([collist[pk1]])])
p = path.rect(3+coord - (dcoord*step) +(lng/2.0), 3+ypos, lng/2.0, 1)
c.stroke(p, [deco.filled([collist[pk2]])])
c.stroke(p)
# p = path.line(3+coord - (dcoord*step), 3+ypos + 1, 3+coord - (dcoord*step), 3+ypos + 2)
# c.stroke(p, [deco.filled([collist[pk1]])])
c.fill(path.rect(3+coord - (dcoord*step), 3+ypos + 1, 0.05, 1),[collist[pk1]])
else:
tm1, pk1 = seq
if lmatch != 0:
pk1 = int(mapping[pk1])
coord = tm1 / tres
dcoord = int(coord /step)
ypos = dcoord * dpos
if stt != dcoord:
stt = dcoord
c.text(0,3+ ypos, str(tm1), [text.size(1)])
# p = path.line(3+coord - (dcoord*step), 3+ypos + 1, 3+coord - (dcoord*step), 3+ypos + 2)
# c.stroke(p, [deco.filled([collist[pk1]])])
c.fill(path.rect(3+coord - (dcoord*step), 3+ypos + 1, 0.05, 1),[collist[pk1]])
lpages.append(document.page(c))
d = document.document(lpages)
d.writePDFfile(datainfo.dpath + '/' + datainfo.name + "/Results/peaksseq-%s-%s-%s-%s-%d" % (datainfo.name, dfile, sensor, ename, nsym))
def draw_synchs_boxes(pk, exp, ename, sensors, window, nsym, nmatch=0, dmappings=None):
"""
Draws syncronizations and their time window boxes
:param peakdata:
:param exp:
:param ename:
:param sensors:
:param window:
:param nsym:
:param nmatch:
:param dmappings:
:return:
"""
if nmatch != 0:
collist = choose_color(nmatch)
else:
collist = choose_color(nsym)
lpages = []
c = canvas.canvas()
# Paleta de colores
for i, col in enumerate(collist):
p = path.rect((i * 0.25) + 5, 7, 0.25, 0.25)
c.stroke(p, [deco.filled([col])])
dpos = -len(sensors) - 1
lppage = 10
step = 100
tres = 500.0
stt = -1
lpages = []
npages = 0
nline = 1
c.text(-4, 14, " ", [text.size(5)])
c.text(0, 10, "%s-%s-%s-W%d" % (datainfo.name, dfile, ename, window), [text.size(5)])
for i in range(len(pk)):
l = [False] * len(sensors)
lcol = [cmyk.White] * len(sensors)
ptime = np.zeros(len(sensors))
for p in pk[i]:
sns = sensors[p[0]]
l[p[0]] = True
ptime[p[0]] = p[1]
if dmappings is not None:
lcol[p[0]] = collist[int(dmappings[sns][p[2]])]
else:
lcol[p[0]] = collist[p[2]]
tm1 = np.min([t for _, t, _ in pk[i]])
tm2 = np.max([t for _, t, _ in pk[i]])
coord = tm1 / tres
lng = (tm2 - tm1) / tres
dcoord = int(coord / step)
if stt != dcoord:
# New page
if nline % lppage == 0:
c.text(step+10, 3 + (lppage-1) * dpos, str(npages+1), [text.size(5)])
c.text(step+12, -1 + (lppage-1) * dpos, " ", [text.size(5)])
nline = 1
npages += 1
lpages.append(document.page(c))
c = canvas.canvas()
c.text(-4, 14, " ", [text.size(5)])
c.text(0, 10, "%s-%s-%s-W%d" % (datainfo.name, dfile, ename, window), [text.size(5)])
# Paleta de colores
for i, col in enumerate(collist):
p = path.rect((i * 0.25) + 5, 7, 0.25, 0.25)
c.stroke(p, [deco.filled([col])])
nline += 1
stt = dcoord
ypos = (dcoord * dpos) - (npages * (lppage-1) * dpos)
# Legend on the left for the names of the sensors
c.text(-2, 3 + ypos, str(tm1), [text.size(3)])
for j, sn in enumerate(sensors):
c.text(1, 3 + ypos + 1 - j, sn, [text.size(3)])
else:
ypos = (dcoord * dpos) - (npages * (lppage-1) * dpos)
# Rectangulo que rodea las sincronizaciones
p = path.rect(3 + (coord - (dcoord * step)), 3 + ypos + 2 - len(sensors), lng + .05, len(sensors))
c.stroke(p)
for j in range(len(sensors)):
if l[j]:
tcoord = ptime[j] / tres
c.fill(path.rect(3 + (tcoord - (dcoord * step)), 3 + ypos + 1 - j, 0.05, 1), [lcol[j]])
# p = path.line(3 + (tcoord - (dcoord*step)), 3+ypos + 1+j, 3 + (tcoord - (dcoord*step)), 3+ypos + 2+j)
# c.stroke(p, [deco.filled([lcol[j]])])
if nline != 0:
c.text(step+10, 3 + (lppage-1) * dpos, str(npages+1), [text.size(5)])
c.text(step+12, -1 + (lppage-1) * dpos, " ", [text.size(5)])
lpages.append(document.page(c))
d = document.document(lpages)
d.writePDFfile(
datainfo.dpath + '/' + datainfo.name + "/Results/peakssyncboxes-%s-%s-%s" % (datainfo.name, dfile, ename))
def draw_synchs(peakdata, exp, ename, sensors, window, nsym, nmatch=0, dmappings=None):
"""
Generates a PDF of the synchronizations
:param peakdata: Dictionary with the synchronizations computed by compute_syncs
:param exps: Experiments in the dictionary
:param window: Window used to determine the synchronizations
:return:
"""
def syncIcon(x, y, sensors, coord, lv, lcol, scale, can):
"""
Generates the drawing for a syncronization
:param x:
:param y:
:param sensors:
:param coord:
:param lv:
:param lcol:
:param scale:
:param can:
:param dmappings:
:return:
"""
scale *= 0.6
y = (y / 2.5) + 2
x += 5
for al, v, col in zip(sensors, lv, lcol):
c = coord[al]
p = path.rect(y + (c[0] * scale), x + (c[1] * scale), scale, scale)
if v:
can.stroke(p, [deco.filled([col])])
else:
can.stroke(p)
# Generates the list of colors
if nmatch == 0:
collist = choose_color(nsym)
else:
collist = choose_color(nmatch)
ncol = 0
npage = 1
lpages = []
pk = peakdata
c = canvas.canvas()
p = path.line(1, 0, 1, 28)
c.stroke(p)
c.text(1.5, 27, '%s - page: %d' % (exp, npage), [text.size(-1)])
vprev = 0
y = 0
yt = 1.25
# Paleta de colores
for i, col in enumerate(collist):
p = path.rect(0, i * 0.25, 0.25, 0.25)
c.stroke(p, [deco.filled([col])])
for i in range(len(pk)):
l = [False] * len(sensors)
lcol = [cmyk.White] * len(sensors)
for p in pk[i]:
l[p[0]] = True
sns = sensors[p[0]]
if dmappings is not None:
lcol[p[0]] = collist[int(dmappings[sns][p[2]])]
else:
lcol[p[0]] = collist[p[2]]
v = np.min([t for _, t, _ in pk[i]]) % 10000 # Time in a page (5000)
if v < vprev:
p = path.line(yt + 2.5, 0, yt + 2.5, 28)
c.stroke(p)
y += 6.3
yt += 2.5
ncol += 1
if ncol % 7 == 0:
# p=path.line(yt+2.5, 0, yt+2.5, 28)
# c.stroke(p)
npage += 1
ncol = 0
lpages.append(document.page(c))
c = canvas.canvas()
p = path.line(1, 0, 1, 28)
c.stroke(p)
c.text(1.5, 27, '%s - page: %d' % (exp, npage), [text.size(-1)])
vprev = 0
y = 0
yt = 1.25
vprev = v
d = v - 1500 # end of the page (800)
# proportion of x axis (200)
c.text(yt, (d / 400.0) + 5.25, '%8s' % str(int(round(pk[i][0][1] * 0.6))), [text.size(-4)])
syncIcon(d / 400.0, y, sensors, coormap, l, lcol, 0.25, c)
# p=path.line(yt+2.5, 0, yt+2.5, 28)
# c.stroke(p)
d = document.document(lpages)
d.writePDFfile(
datainfo.dpath + '/' + datainfo.name + "/Results/peaksynchs-%s-%s-%s-W%d" % (datainfo.name, exp, ename, window))