def strip_find(band, icol, dpix=50, margin=10, devide=8.0):
'''
Find the start and the end position of each strip
by using numerical derivatives
- input
1. column data (1d-array)
2. dpix (pixel width to distinguish different aperture)
3. margin (margin for eliminating the edge of numerical derivatives)
- output
1. a list of starting positions of the apertures
2. a list of ending positions of the apertures
'''
if band == "H":
devide = 5.5
else:
devide = 20.0
ny = len(icol)
print 'len icol', ny
yy = np.arange(ny)
dval = ip.nderiv(yy, icol)
# maximun and minimum of numerical derivatives
vmin, vmax = np.nanmin(dval[margin:(ny - margin)]), np.nanmax(
dval[margin:(ny - margin)])
print 'vmin, vmax', vmin, vmax
# define the threshold for detecting local maxima
vthres = (np.abs(vmax) + np.abs(vmin)) / devide #8.0 # Edit by Huynh Anh
# find the local maxima and minima
pll, pval = ip.find_features(yy, dval, gpix=dpix, thres=vthres)
nll, nval = ip.find_features(yy, -dval, gpix=dpix, thres=vthres)
# exclude the edge positions
pvv, = np.where((pll > margin) & (pll < ny - margin))
nvv, = np.where((nll > margin) & (nll < ny - margin))
p_num, n_num = len(pll), len(nll)
if p_num * n_num == 0:
print 'Found no strips ...'
p_pos, n_pos = None, None
else:
p_pos, n_pos = pll[pvv], nll[nvv]
#p_pos, n_pos = pll, nll
'''
plt.subplot(211)
plt.plot(yy,icol)
plt.plot(p_pos, icol[p_pos], 'go')
plt.plot(n_pos, icol[n_pos], 'ro')
plt.subplot(212)
plt.plot(yy,dval)
plt.plot(p_pos, dval[p_pos], 'go')
plt.plot(n_pos, dval[n_pos], 'ro')
plt.show()
'''
return p_pos, n_pos
def strip_find(band, icol, dpix=50, margin=10, devide=8.0):
'''
Find the start and the end position of each strip
by using numerical derivatives
- input
1. column data (1d-array)
2. dpix (pixel width to distinguish different aperture)
3. margin (margin for eliminating the edge of numerical derivatives)
- output
1. a list of starting positions of the apertures
2. a list of ending positions of the apertures
'''
if band == "H":
devide = 5.5
else:
devide = 20.0
ny = len(icol)
print 'len icol', ny
yy = np.arange(ny)
dval = ip.nderiv(yy, icol)
# maximun and minimum of numerical derivatives
vmin, vmax = np.nanmin(dval[margin:(ny-margin)]), np.nanmax(dval[margin:(ny-margin)])
print 'vmin, vmax', vmin, vmax
# define the threshold for detecting local maxima
vthres = (np.abs(vmax) + np.abs(vmin)) / devide #8.0 # Edit by Huynh Anh
# find the local maxima and minima
pll, pval = ip.find_features(yy, dval, gpix=dpix, thres=vthres)
nll, nval = ip.find_features(yy, -dval, gpix=dpix, thres=vthres)
# exclude the edge positions
pvv, = np.where((pll > margin) & (pll < ny-margin))
nvv, = np.where((nll > margin) & (nll < ny-margin))
p_num, n_num = len(pll), len(nll)
if p_num * n_num == 0:
print 'Found no strips ...'
p_pos, n_pos = None, None
else:
p_pos, n_pos = pll[pvv], nll[nvv]
#p_pos, n_pos = pll, nll
'''
plt.subplot(211)
plt.plot(yy,icol)
plt.plot(p_pos, icol[p_pos], 'go')
plt.plot(n_pos, icol[n_pos], 'ro')
plt.subplot(212)
plt.plot(yy,dval)
plt.plot(p_pos, dval[p_pos], 'go')
plt.plot(n_pos, dval[n_pos], 'ro')
plt.show()
'''
return p_pos, n_pos
def key_press(event):
ax = event.inaxes
if ax == None: return
ax_title = ax.get_title()
if event.key == 'q': plt.close('all')
if event.key == 'm':
click_x, click_y = event.xdata, event.ydata
rr = np.arange((x2-2*dpix),(x2+2*dpix+1), dtype=np.int)
#p = ip.gauss_fit(rr, row[rr], p0=[1, x2, 1])
#a2.plot(rr, ip.gauss(rr, *p), 'r--')
#mx = p[1]
mx, mval = ip.find_features(rr, row[rr], gpix=dpix)
mx, mval = mx[0], mval[0]
a2.plot(mx, mval, 'ro')
fig.canvas.draw()
fwv = cwv[np.argmin(np.abs(cwv-wav[mx]))]
strtmp = raw_input('input wavelength at (%d, %d) = %.7f:' % (mx, my, fwv))
if strtmp == '': strtmp = fwv
try:
mwv = np.float(strtmp)
lxx.append(mx)
lyy.append(my)
lwv.append(mwv)
a1.plot(mx, my, 'ro')
fig.canvas.draw()
print '%.7f at (%d, %d)' % (mwv, mx, my)
except:
print 'No input, again...'
def key_press(event):
ax = event.inaxes
if ax == None: return
ax_title = ax.get_title()
if event.key == 'q': plt.close('all')
if event.key == 'm':
click_x, click_y = event.xdata, event.ydata
rr = np.arange((click_x - 2 * dpix), (click_x + 2 * dpix + 1),
dtype=np.int)
#p = ip.gauss_fit(rr, row[rr], p0=[1, x2, 1])
#a2.plot(rr, ip.gauss(rr, *p), 'r--')
#mx = p[1]
mx, mval = ip.find_features(rr, row[rr], gpix=dpix)
mx, mval = mx[0], mval[0]
a2.plot(mx, mval, 'ro')
fig.canvas.draw()
fwv = cwv[np.argmin(np.abs(cwv - wav[mx]))]
strtmp = raw_input('input wavelength at (%d, %d) = %.7f:' %
(mx, my, fwv))
if strtmp == '': strtmp = fwv
try:
mwv = np.float(strtmp)
lxx.append(mx)
lyy.append(my)
lwv.append(mwv)
a1.plot(mx, my, 'ro')
fig.canvas.draw()
print '%.7f at (%d, %d)' % (mwv, mx, my)
except:
print 'No input, again...'
