base_EKHrestore1.py
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title = "EKH-Restore"
tip = "restore multi-horn maps scanned in Azimuth"
onein = False
import copy as cp
import numpy as np
#from scipy.ndimage import gaussian_filter1d
from scipy.interpolate import interp1d
from guidata.qt.QtGui import QMessageBox
from guidata.dataset.datatypes import DataSet
from guidata.dataset.dataitems import (IntItem, StringItem, ChoiceItem, FloatItem, BoolItem)
from guiqwt.config import _
from nodmath import nan_interpol
def factorial(n):
return reduce(lambda x,y:x*y,[1]+range(1,n+1))
def median(x):
xl = list(x)
xl.sort()
return xl[len(xl)/2]
def nint(x):
if x > 0: return int(x+0.5)
else: return int(x-0.5)
class NOD3_App:
def __init__(self, parent):
self.parent = parent
self.parent.activateWindow()
def Error(self, msg):
QMessageBox.critical(self.parent.parent(), title,
_(u"Error:")+"\n%s" % str(msg))
def compute_app(self, **args):
class FuncParam(DataSet):
order = IntItem('Order', default=7, max=13, min=1)
#adjust = BoolItem('Adjust', default=False)
name = title.replace(" ", "")
if args == {}:
param = FuncParam(_(title), "description")
else:
param = self.parent.ScriptParameter(name, args)
# if no parameter needed set param to None. activate next line
param = None
self.parent.compute_11(name, lambda m, p: self.function(m, p), param, onein)
def autocal(self, data1, data2, ix):
d1 = list(np.ravel(data1[:,ix:]))
d2 = list(np.ravel(data2[:,:-ix]))
d1.sort()
d2.sort()
nl = max(10, len(d1)/10)
a1, a0 = np.polyfit(d2[-nl:], d1[-nl:], 1)
return data1, a0 + a1*data2
def polymat(self, order, dx, xx):
mat = []
for x in xx:
y = []
#for n in range(order-1,-1,-1):
for n in range(order-1,1,-1):
y.append(float(x+dx)**n - float(x)**n)
#y.append(float(x-dx))
y.append(float(dx))
y.append(1.0)
mat.append(y)
return np.array(mat)
def xconv(self, diff, cols, cfunc, rnorm):
out = []
ldif = len(diff)
lfun = len(cfunc)
for i in range(cols):
asum = 0.0
for j in range(lfun):
k = i - ldif + j + 2
if k >= 0 and k < cols:
asum += diff[k] * cfunc[j]
out.append(asum/rnorm)
return np.array(out)
def conf4(self, ndim, ptsep):
ndim2 = 2*ndim - 1
nsincs = int((float(ndim) / ptsep) + 0.5)
nsinc2 = nsincs * 2 + 1
cfunc = []
sumt = 0.0
for i in range(ndim2):
dx = i - ndim + 1
asum = 0.0
b1 = - (nsincs * ptsep)
for j in range(nsinc2):
sn = b1
b1 += ptsep
asum -= np.sinc(dx - sn)
cfunc.append(asum)
sumt += asum
sumt = (-sumt * ndim) / float(ndim2)
for k in range(ndim2):
cfunc[k] = cfunc[k]/sumt
cfunc[ndim-1] += 1.0
return cfunc
def conf22(self, ndim, ptsep):
ptsep2 = ptsep*0.5
ndim2 = 2*ndim - 1
nsincs = int((float(ndim) / ptsep) + 0.5)
nsinc2 = nsincs * 2
cfunc = []
for i in range(ndim2):
dx = i - ndim + 1 #+ ptsep2
asum = 0.0
b1 = (ptsep/2.0) - (nsincs * ptsep)
alpha = 1.0
for j in range(nsinc2):
sn = b1
b1 += ptsep
asum -= np.sinc(dx - sn) * np.sign(sn)
cfunc.append(asum)
#return cfunc
for i in range(ndim):
k = ndim2-1 - i
x = cfunc[k]
cfunc[k] = -cfunc[i]
cfunc[i] = -x
return cfunc
def ipol(self, y, x, dx):
ix = int(dx)
d = dx-ix
if d == 0.0:
return y[x-ix]
val0 = y[x-ix]
val1 = y[x-ix-1]
return val0*(1-d) + val1*d
def function(self, ms, p):
nmaps = len(ms)
combinations = factorial(nmaps)/(2*factorial(nmaps-2))
data = []
coord = []
for n in range(nmaps):
for m in range(n+1, nmaps):
m1 = ms[n]
m2 = ms[m]
mask1, m1.data = nan_interpol(m1.data)
mask2, m2.data = nan_interpol(m2.data)
dx = (m1.header['PATLONG'] - m2.header['PATLONG']) / m1.header['CDELT1']
if dx < 0:
m1 = ms[m]
m2 = ms[n]
dx = (m1.header['PATLONG'] - m2.header['PATLONG']) / m1.header['CDELT1']
if abs(dx) > 30.0: dx = abs(dx)/3600.0
ix = nint(dx)
data1, data2 = self.autocal(m1.data, m2.data, ix)
rows, cols = data1.shape
kamm = self.conf22(cols, dx)
basl = self.conf4(cols, dx)
for row in range(rows):
diff = data2[row] - data1[row]
diff = self.xconv(diff, cols, basl, 1.0)
data1[row] = self.xconv(diff, cols, kamm, 2.0)
m1.data = data1
#m1.header['CRPIX1'] -= dx/2 + 2
m1.header['CRPIX1'] -= 2
m1.header['PATLONG'] = 0.0
self.parent.SidOut = True
return m1, p