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# -*- coding: utf-8 -*-
#
# Written 2009-12-22 by Jérôme Kieffer
# Copyright (C) 2009-2016 European Synchrotron Radiation Facility
# Grenoble, France
#
# Principal authors: Jérôme Kieffer (jerome.kieffer@esrf.fr)
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
"""This is piece of software aims at manipulating spline files
describing for geometric corrections of the 2D detectors using cubic-spline.
Mainly used at ESRF with FReLoN CCD camera.
"""
from __future__ import print_function, division
__author__ = "Jérôme Kieffer"
__contact__ = "Jerome.Kieffer@esrf.eu"
__license__ = "MIT"
__date__ = "12/01/2018"
__copyright__ = "European Synchrotron Radiation Facility, Grenoble, France"
import os
import time
import sys
import numpy
import logging
import scipy.optimize
import scipy.interpolate
try:
# multithreaded version in Cython: about 2x faster on large array evaluation
from . import _bispev as fitpack
except ImportError:
from scipy.interpolate import fitpack
import traceback
logger = logging.getLogger(__name__)
class Spline(object):
"""
This class is a python representation of the spline file
Those file represent cubic splines for 2D detector distortions and
makes heavy use of fitpack (dierckx in netlib) --- A Python-C
wrapper to FITPACK (by P. Dierckx). FITPACK is a collection of
FORTRAN programs for curve and surface fitting with splines and
tensor product splines. See
_http://www.cs.kuleuven.ac.be/cwis/research/nalag/research/topics/fitpack.html
or _http://www.netlib.org/dierckx/index.html
"""
def __init__(self, filename=None):
"""
This is the constructor of the Spline class.
:param filename: name of the ascii file containing the spline
:type filename: str
"""
self.splineOrder = 3 # This is the default, so cubic splines
self.lenStrFloat = 14 # by default one float is 14 char in ascii
self.xmin = None
self.ymin = None
self.xmax = None
self.ymax = None
self.xDispArray = None
self.yDispArray = None
self.xSplineKnotsX = []
self.xSplineKnotsY = []
self.xSplineCoeff = []
self.ySplineKnotsX = []
self.ySplineKnotsY = []
self.ySplineCoeff = []
self.pixelSize = None # 2-tuple of float
self.grid = None
self.filename = None # string
if filename is not None:
self.read(filename)
def __repr__(self):
lst = ["Array size: x= %s - %s\ty= %s - %s" %
(self.xmin, self.xmax, self.ymin, self.ymax)]
lst.append("Pixel size = %s microns, Grid spacing = %s" %
(self.pixelSize, self.grid))
lst.append("X-Displacement spline %i X_knots, %i Y_knots and %i coef: "
"should be (X_knot-1-X_order)*(Y_knot-1-Y_order)" % (len(self.xSplineKnotsX),
len(self.xSplineKnotsY),
len(self.xSplineCoeff)))
lst.append("Y-Displacement spline %i X_knots, %i Y_knots and %i coef: "
"should be (X_knot-1-X_order)*(Y_knot-1-Y_order)" % (len(self.ySplineKnotsX),
len(self.ySplineKnotsY),
len(self.ySplineCoeff)))
return os.linesep.join(lst)
def __copy__(self):
""":return: Shallow copy of the spline"""
unmutable = "splineOrder", "lenStrFloat", "xmin", "ymin", "xmax", "ymax", "filename", "pixelSize", "grid"
arrays = "xDispArray", "yDispArray"
lists = "xSplineKnotsX", "xSplineKnotsY", "xSplineCoeff", "ySplineKnotsX", "ySplineKnotsY", "ySplineCoeff"
new = self.__class__()
for key in unmutable + arrays + lists:
new.__setattr__(key, self.__getattribute__(key))
return new
def __deepcopy__(self, memo=None):
""":return: deep copy of the spline"""
unmutable = "splineOrder", "lenStrFloat", "xmin", "ymin", "xmax", "ymax", "filename", "pixelSize", "grid"
arrays = "xDispArray", "yDispArray"
lists = "xSplineKnotsX", "xSplineKnotsY", "xSplineCoeff", "ySplineKnotsX", "ySplineKnotsY", "ySplineCoeff"
if memo is None:
memo = {}
new = self.__class__()
memo[id(self)] = new
for key in unmutable:
old_value = self.__getattribute__(key)
memo[id(old_value)] = old_value
new.__setattr__(key, old_value)
for key in arrays:
old_value = self.__getattribute__(key)
if (old_value is None) or (old_value is False):
new_value = old_value
elif "copy" in dir(old_value):
new_value = old_value.copy()
else:
new_value = 1 * old_value
memo[id(old_value)] = new_value
new.__setattr__(key, new_value)
for key in lists:
old_value = self.__getattribute__(key)
new_value = old_value[:]
memo[id(old_value)] = new_value
new.__setattr__(key, new_value)
return new
def zeros(self, xmin=0.0, ymin=0.0, xmax=2048.0, ymax=2048.0,
pixSize=None):
"""
Defines a spline file with no ( zero ) displacement.
:param xmin: minimum coordinate in x, usually zero
:type xmin: float
:param xmax: maximum coordinate in x (+1) usually 2048
:type xmax: float
:param ymin: minimum coordinate in y, usually zero
:type ymin: float
:param ymax: maximum coordinate y (+1) usually 2048
:type ymax: float
:param pixSize: size of the pixel
:type pixSize: float
"""
self.xmin = xmin
self.ymin = ymin
self.xmax = xmax
self.ymax = ymax
self.xDispArray = numpy.zeros((int(xmax - xmin + 1),
int(ymax - ymin + 1)))
self.yDispArray = numpy.zeros((int(xmax - xmin + 1),
int(ymax - ymin + 1)))
if pixSize:
self.pixelSize = pixSize
def zeros_like(self, other):
"""
Defines a spline file with no ( zero ) displacement with the
same shape as the other one given.
:param other: another Spline instance
:type other: Spline instance
"""
self.zeros(self, other.xmin, other.ymin, other.xmax, other.ymax)
def read(self, filename):
"""
read an ascii spline file from file
:param filename: file containing the cubic spline distortion file
:type filename: str
"""
if not os.path.isfile(filename):
raise IOError("Spline File does not exist %s" % filename)
self.filename = filename
with open(filename) as opened_file:
stringSpline = [i.rstrip() for i in opened_file]
try:
indexLine = 0
for oneLine in stringSpline:
stripedLine = oneLine.strip().upper()
if stripedLine == "VALID REGION":
data = stringSpline[indexLine + 1]
self.xmin = float(data[self.lenStrFloat * 0:self.lenStrFloat * 1])
self.ymin = float(data[self.lenStrFloat * 1:self.lenStrFloat * 2])
self.xmax = float(data[self.lenStrFloat * 2:self.lenStrFloat * 3])
self.ymax = float(data[self.lenStrFloat * 3:self.lenStrFloat * 4])
elif stripedLine == "GRID SPACING, X-PIXEL SIZE, Y-PIXEL SIZE":
data = stringSpline[indexLine + 1]
self.grid = float(data[:self.lenStrFloat])
self.pixelSize = \
(float(data[self.lenStrFloat:self.lenStrFloat * 2]),
float(data[self.lenStrFloat * 2:self.lenStrFloat * 3]))
elif stripedLine == "X-DISTORTION":
data = stringSpline[indexLine + 1]
[splineKnotsXLen, splineKnotsYLen] = \
[int(i) for i in data.split()]
databloc = []
for line in stringSpline[indexLine + 2:]:
if len(line) > 0:
for i in range(len(line) // self.lenStrFloat):
databloc.append(float(line[i * self.lenStrFloat: (i + 1) * self.lenStrFloat]))
else:
break
self.xSplineKnotsX = numpy.array(databloc[:splineKnotsXLen], dtype=numpy.float32)
self.xSplineKnotsY = numpy.array(databloc[splineKnotsXLen:splineKnotsXLen + splineKnotsYLen], dtype=numpy.float32)
self.xSplineCoeff = numpy.array(databloc[splineKnotsXLen + splineKnotsYLen:], dtype=numpy.float32)
elif stripedLine == "Y-DISTORTION":
data = stringSpline[indexLine + 1]
[splineKnotsXLen, splineKnotsYLen] = [int(i) for i in data.split()]
databloc = []
for line in stringSpline[indexLine + 2:]:
if len(line) > 0:
for i in range(len(line) // self.lenStrFloat):
databloc.append(float(line[i * self.lenStrFloat:(i + 1) * self.lenStrFloat]))
else:
break
self.ySplineKnotsX = numpy.array(databloc[:splineKnotsXLen], dtype=numpy.float32)
self.ySplineKnotsY = numpy.array(databloc[splineKnotsXLen:splineKnotsXLen + splineKnotsYLen], dtype=numpy.float32)
self.ySplineCoeff = numpy.array(databloc[splineKnotsXLen + splineKnotsYLen:], dtype=numpy.float32)
# Keep this at the end
indexLine += 1
except:
traceback.print_exc()
raise IOError("Spline File parsing error: %s" % (filename))
def comparison(self, ref, verbose=False):
"""
Compares the current spline distortion with a reference
:param ref: another spline file
:type ref: Spline instance
:param verbose: print or not pylab plots
:type verbose: bool
:return: True or False depending if the splines are the same or not
:rtype: bool
"""
self.spline2array()
ref.spline2array()
deltax = (self.xDispArray - ref.xDispArray)
deltay = (self.yDispArray - ref.yDispArray)
histX = numpy.histogram(deltax.reshape(deltax.size), bins=100)
histY = numpy.histogram(deltay.reshape(deltay.size), bins=100)
histXdr = (histX[1][1:] + histX[1][:-1]) / 2.0
histYdr = (histY[1][1:] + histY[1][:-1]) / 2.0
histXmax = histXdr[histX[0].argmax()]
histYmax = histYdr[histY[0].argmax()]
maxErrX = abs(deltax).max()
maxErrY = abs(deltay).max()
curvX = scipy.interpolate.interp1d(histXdr, histX[0] - histX[0].max() / 2.0)
curvY = scipy.interpolate.interp1d(histYdr, histY[0] - histY[0].max() / 2.0)
fFWHM_X = scipy.optimize.bisect(curvX, histXmax, histXdr[-1]) - scipy.optimize.bisect(curvX, histXdr[0], histXmax)
fFWHM_Y = scipy.optimize.bisect(curvY, histYmax, histYdr[-1]) - scipy.optimize.bisect(curvY, histYdr[0], histYmax)
logger.info("Analysis of the difference between two splines")
logger.info("Maximum error in X= %.3f pixels,\t in Y= %.3f pixels.", maxErrX, maxErrY)
logger.info("Maximum of histogram in X= %.3f pixels,\t in Y= %.3f pixels.", histXmax, histYmax)
logger.info("Mean of histogram in X= %.3f pixels,\t in Y= %.3f pixels.", deltax.mean(), deltay.mean())
logger.info("FWHM in X= %.3f pixels,\t in Y= %.3f pixels.", fFWHM_X, fFWHM_Y)
if verbose:
import pylab
pylab.plot(histXdr, histX[0], label="error in X")
pylab.plot(histYdr, histY[0], label="error in Y")
pylab.legend()
pylab.show()
return (fFWHM_X < 0.05) and (fFWHM_Y < 0.05) and (maxErrX < 0.5) and (maxErrY < 0.5) \
and (deltax.mean() < 0.01) and(deltay.mean() < 0.01) and (histXmax < 0.01) and (histYmax < 0.01)
def spline2array(self, timing=False):
"""
Calculates the displacement matrix using fitpack
bisplev(x, y, tck, dx = 0, dy = 0)
:param timing: profile the calculation or not
:type timing: bool
:return: Nothing !
:rtype: float or ndarray
Evaluate a bivariate B-spline and its derivatives. Return a
rank-2 array of spline function values (or spline derivative
values) at points given by the cross-product of the rank-1
arrays x and y. In special cases, return an array or just a
float if either x or y or both are floats.
"""
if self.xDispArray is None:
x_1d_array = numpy.arange(self.xmin, self.xmax + 1)
y_1d_array = numpy.arange(self.ymin, self.ymax + 1)
startTime = time.time()
self.xDispArray = fitpack.bisplev(
x_1d_array, y_1d_array, [self.xSplineKnotsX,
self.xSplineKnotsY,
self.xSplineCoeff,
self.splineOrder,
self.splineOrder],
dx=0, dy=0).transpose()
intermediateTime = time.time()
self.yDispArray = fitpack.bisplev(
x_1d_array, y_1d_array, [self.ySplineKnotsX,
self.ySplineKnotsY,
self.ySplineCoeff,
self.splineOrder,
self.splineOrder],
dx=0, dy=0).transpose()
if timing:
logger.info("Timing for: X-Displacement spline evaluation: %.3f sec,"
" Y-Displacement Spline evaluation: %.3f sec." %
((intermediateTime - startTime),
(time.time() - intermediateTime)))
def splineFuncX(self, x, y, list_of_points=False):
"""
Calculates the displacement matrix using fitpack for the X
direction on the given grid.
:param x: points of the grid in the x direction
:type x: ndarray
:param y: points of the grid in the y direction
:type y: ndarray
:param list_of_points: if true, consider the zip(x,y) instead of the of the square array
:return: displacement matrix for the X direction
:rtype: ndarray
"""
if x.ndim == 2:
if abs(x[1:, :] - x[:-1, :] - numpy.zeros((x.shape[0] - 1, x.shape[1]))).max() < 1e-6:
x = x[0]
y = y[:, 0]
elif abs(x[:, 1:] - x[:, :-1] - numpy.zeros((x.shape[0], x.shape[1] - 1))).max() < 1e-6:
x = x[:, 0]
y = y[0]
if list_of_points and x.ndim == 1 and len(x) == len(y):
lx = ly = len(x)
x_order = x.argsort()
y_order = y.argsort()
x = x[x_order]
y = y[y_order]
x_unordered = numpy.zeros(lx, dtype=int)
y_unordered = numpy.zeros(ly, dtype=int)
x_unordered[x_order] = numpy.arange(lx)
y_unordered[y_order] = numpy.arange(ly)
xDispArray = fitpack.bisplev(
x, y, [self.xSplineKnotsX,
self.xSplineKnotsY,
self.xSplineCoeff,
self.splineOrder,
self.splineOrder],
dx=0, dy=0)
if list_of_points and x.ndim == 1:
return xDispArray[x_unordered, y_unordered]
else:
return xDispArray.T
def splineFuncY(self, x, y, list_of_points=False):
"""
calculates the displacement matrix using fitpack for the Y
direction
:param x: points in the x direction
:type x: ndarray
:param y: points in the y direction
:type y: ndarray
:param list_of_points: if true, consider the zip(x,y) instead of the of the square array
:return: displacement matrix for the Y direction
:rtype: ndarray
"""
if x.ndim == 2:
if abs(x[1:, :] - x[:-1, :] - numpy.zeros((x.shape[0] - 1, x.shape[1]))).max() < 1e-6:
x = x[0]
y = y[:, 0]
elif abs(x[:, 1:] - x[:, :-1] - numpy.zeros((x.shape[0], x.shape[1] - 1))).max() < 1e-6:
x = x[:, 0]
y = y[0]
if list_of_points and x.ndim == 1 and len(x) == len(y):
lx = ly = len(x)
x_order = x.argsort()
y_order = y.argsort()
x = x[x_order]
y = y[y_order]
x_unordered = numpy.zeros(lx, dtype=int)
y_unordered = numpy.zeros(ly, dtype=int)
x_unordered[x_order] = numpy.arange(lx)
y_unordered[y_order] = numpy.arange(ly)
yDispArray = fitpack.bisplev(
x, y, [self.ySplineKnotsX,
self.ySplineKnotsY,
self.ySplineCoeff,
self.splineOrder,
self.splineOrder],
dx=0, dy=0)
if list_of_points and x.ndim == 1:
return yDispArray[x_unordered, y_unordered]
else:
return yDispArray.T
def array2spline(self, smoothing=1000, timing=False):
"""
Calculates the spline coefficients from the displacements
matrix using fitpack.
:param smoothing: the greater the smoothing, the fewer the number of knots remaining
:type smoothing: float
:param timing: print the profiling of the calculation
:type timing: bool
"""
self.xmin = 0.0
self.ymin = 0.0
self.xmax = float(self.xDispArray.shape[0] - 1)
self.ymax = float(self.yDispArray.shape[1] - 1)
if timing:
startTime = time.time()
xRectBivariateSpline = scipy.interpolate.fitpack2.RectBivariateSpline(
numpy.arange(self.xmax + 1.0),
numpy.arange(self.ymax + 1),
self.xDispArray.transpose(),
s=smoothing)
if timing:
intermediateTime = time.time()
yRectBivariateSpline = scipy.interpolate.fitpack2.RectBivariateSpline(
numpy.arange(self.xmax + 1.0),
numpy.arange(self.ymax + 1),
self.yDispArray.transpose(),
s=smoothing)
if timing:
logger.info("X-Displ evaluation= %.3f sec, Y-Displ evaluation= %.3f sec.",
intermediateTime - startTime, time.time() - intermediateTime)
logger.info(len(xRectBivariateSpline.get_coeffs()),
"x-coefs", xRectBivariateSpline.get_coeffs())
logger.info(len(yRectBivariateSpline.get_coeffs()),
"y-coefs", yRectBivariateSpline.get_coeffs())
logger.info(len(xRectBivariateSpline.get_knots()[0]),
len(xRectBivariateSpline.get_knots()[1]),
"x-knots", xRectBivariateSpline.get_knots())
logger.info(len(yRectBivariateSpline.get_knots()[0]),
len(yRectBivariateSpline.get_knots()[1]),
"y-knots", yRectBivariateSpline.get_knots())
logger.info("Residual x=%s, y=%s", xRectBivariateSpline.get_residual(),
yRectBivariateSpline.get_residual())
self.xSplineKnotsX = xRectBivariateSpline.get_knots()[0]
self.xSplineKnotsY = xRectBivariateSpline.get_knots()[1]
self.xSplineCoeff = xRectBivariateSpline.get_coeffs()
self.ySplineKnotsX = yRectBivariateSpline.get_knots()[0]
self.ySplineKnotsY = yRectBivariateSpline.get_knots()[1]
self.ySplineCoeff = yRectBivariateSpline.get_coeffs()
def writeEDF(self, basename):
"""
save the distortion matrices into a couple of files called
basename-x.edf and basename-y.edf
:param basename: base of the name used to save the data
:type basename: str
"""
try:
from fabio.edfimage import edfimage
except ImportError:
logger.error("You will need the Fabio library available"
" from the Fable sourceforge")
return
self.spline2array()
edfDispX = edfimage(data=self.xDispArray.astype("float32"), header={})
edfDispY = edfimage(data=self.yDispArray.astype("float32"), header={})
edfDispX.write(basename + "-x.edf", force_type="float32")
edfDispY.write(basename + "-y.edf", force_type="float32")
def write(self, filename):
"""
save the cubic spline in an ascii file usable with Fit2D or
SPD
:param filename: name of the file containing the cubic spline distortion file
:type filename: str
"""
lst = ["SPATIAL DISTORTION SPLINE INTERPOLATION COEFFICIENTS",
"",
" VALID REGION",
"%14.7E%14.7E%14.7E%14.7E" % (self.xmin, self.ymin, self.xmax, self.ymax),
"",
" GRID SPACING, X-PIXEL SIZE, Y-PIXEL SIZE",
"%14.7E%14.7E%14.7E" % (self.grid, self.pixelSize[0], self.pixelSize[1]),
"",
" X-DISTORTION",
"%6i%6i" % (len(self.xSplineKnotsX), len(self.xSplineKnotsY))]
txt = ""
for i, val in enumerate(self.xSplineKnotsX):
txt += "%14.7E" % val
if i % 5 == 4:
lst.append(txt)
txt = ""
if txt:
lst.append(txt)
txt = ""
for i, val in enumerate(self.xSplineKnotsY):
txt += "%14.7E" % val
if i % 5 == 4:
lst.append(txt)
txt = ""
if txt:
lst.append(txt)
txt = ""
for i, val in enumerate(self.xSplineCoeff):
txt += "%14.7E" % self.xSplineCoeff[i]
if i % 5 == 4:
lst.append(txt)
txt = ""
if txt:
lst.append(txt)
txt = ""
lst.append("")
lst.append(" Y-DISTORTION\n%6i%6i" % (len(self.ySplineKnotsX),
len(self.ySplineKnotsY)))
for i, val in enumerate(self.ySplineKnotsX):
txt += "%14.7E" % val
if i % 5 == 4:
lst.append(txt)
txt = ""
if txt:
lst.append(txt)
txt = ""
for i, val in enumerate(self.ySplineKnotsY):
txt += "%14.7E" % val
if i % 5 == 4:
lst.append(txt)
txt = ""
if txt:
lst.append(txt)
txt = ""
for i, val in enumerate(self.ySplineCoeff):
txt += "%14.7E" % val
if i % 5 == 4:
lst.append(txt)
txt = ""
if txt:
lst.append(txt)
txt = ""
lst.append("")
with open(filename, "w") as fil:
fil.write("\n".join(lst))
def tilt(self, center=(0.0, 0.0), tiltAngle=0.0, tiltPlanRot=0.0,
distanceSampleDetector=1.0, timing=False):
"""
The tilt method apply a virtual tilt on the detector, the
point of tilt is given by the center
:param center: position of the point of tilt, this point will not be moved.
:type center: 2-tuple of floats
:param tiltAngle: the value of the tilt in degrees
:type tiltAngle: float in the range [-90:+90] degrees
:param tiltPlanRot: the rotation of the tilt plan with the Ox axis (0 deg for y axis invariant, 90 deg for x axis invariant)
:type tiltPlanRot: Float in the range [-180:180]
:param distanceSampleDetector: the distance from sample to detector in meter (along the beam, so distance from sample to center)
:type distanceSampleDetector: float
:return: tilted Spline instance
:rtype: Spline
"""
if self.xDispArray is None:
if self.filename is None:
self.zeros()
else:
self.read(self.filename)
logger.info("center=%s, tilt=%s, tiltPlanRot=%s, distanceSampleDetector=%sm, pixelSize=%sµm", center, tiltAngle, tiltPlanRot, distanceSampleDetector, self.pixelSize)
if timing:
startTime = time.time()
distance = 1.0e6 * distanceSampleDetector # from meters to microns
cosb = numpy.cos(numpy.radians(tiltPlanRot))
sinb = numpy.sin(numpy.radians(tiltPlanRot))
cosf = numpy.cos(numpy.radians(tiltAngle))
sinf = numpy.sin(numpy.radians(tiltAngle))
# x and y are tilted in C/Fortran representation
x = lambda i, j: j - center[0] - 0.5
y = lambda i, j: i - center[1] - 0.5
iPos = numpy.fromfunction(x,
(int(self.ymax - self.ymin + 1),
int(self.xmax - self.xmin + 1)))
jPos = numpy.fromfunction(y,
(int(self.ymax - self.ymin + 1),
int(self.xmax - self.xmin + 1)))
xPos = (iPos + self.xDispArray) * self.pixelSize[0]
yPos = (jPos + self.yDispArray) * self.pixelSize[1]
tiltArrayX = distance * (xPos * (cosf * cosb * cosb + sinb * sinb) + yPos * (cosf * cosb * sinb - cosb * sinb)) / \
(distance + xPos * sinf * cosb + yPos * sinf * sinb) / self.pixelSize[0] - iPos
tiltArrayY = distance * (xPos * (cosf * sinb * cosb - cosb * sinb) + yPos * (cosf * sinb * sinb + cosb * cosb)) / \
(distance + xPos * sinf * cosb + yPos * sinf * sinb) / self.pixelSize[1] - jPos
tiltedSpline = Spline()
tiltedSpline.pixelSize = self.pixelSize
tiltedSpline.grid = self.grid
tiltedSpline.xDispArray = tiltArrayX
tiltedSpline.yDispArray = tiltArrayY
# tiltedSpline.array2spline(smoothing=1e-6, timing=True)
if timing:
logger.info("Time for the generation of the distorted spline: %.3f sec", time.time() - startTime)
return tiltedSpline
def setPixelSize(self, pixelSize):
"""
Sets the size of the pixel from a 2-tuple of floats expressed
in meters.
:param: pixel size in meter
:type pixelSize: 2-tuple of float
"""
if len(pixelSize) == 2:
self.pixelSize = (pixelSize[0] * 1.0e6, pixelSize[1] * 1.0e6)
def getPixelSize(self):
"""
Return the size of the pixel from as a 2-tuple of floats expressed
in meters.
:return: the size of the pixel from a 2D detector
:rtype: 2-tuple of floats expressed in meter.
"""
return (self.pixelSize[0] * 1.0e-6, self.pixelSize[1] * 1.0e-6)
def bin(self, binning=None):
"""
Performs the binning of a spline (same camera with different binning)
:param binning: binning factor as integer or 2-tuple of integers
:type: int or (int, int)
"""
if "__len__" in dir(binning):
binX, binY = float(binning[0]), float(binning[1])
else:
binX = binY = float(binning)
self.xSplineKnotsX /= binX
self.xSplineKnotsY /= binY
self.ySplineKnotsX /= binX
self.ySplineKnotsY /= binY
self.pixelSize = (binX * self.pixelSize[0], binY * self.pixelSize[1])
self.xmax = self.xmax / binX
self.ymax = self.ymax / binY
self.xSplineCoeff /= binX
self.ySplineCoeff /= binY
self.xDispArray = None
self.yDispArray = None
def correct(self, pos):
delta1 = fitpack.bisplev(pos[1], pos[0], [self.xSplineKnotsX,
self.xSplineKnotsY,
self.xSplineCoeff,
self.splineOrder,
self.splineOrder],
dx=0, dy=0)
delta0 = fitpack.bisplev(pos[1], pos[0], [self.ySplineKnotsX,
self.ySplineKnotsY,
self.ySplineCoeff,
self.splineOrder,
self.splineOrder],
dx=0, dy=0)
return delta0 + pos[0], delta1 + pos[1]
def flipud(self):
"""
Flip the spline up-down
:return: new spline object
"""
self.spline2array()
other = self.__class__()
other.xmin = self.xmin
other.ymin = self.ymin
other.xmax = self.xmax
other.ymax = self.ymax
other.xDispArray = numpy.flipud(self.xDispArray)
other.yDispArray = -numpy.flipud(self.yDispArray)
other.pixelSize = self.pixelSize
other.grid = self.grid
other.array2spline()
return other
def fliplr(self):
"""
Flip the spline
:return: new spline object
"""
self.spline2array()
other = self.__class__()
other.xmin = self.xmin
other.ymin = self.ymin
other.xmax = self.xmax
other.ymax = self.ymax
other.xDispArray = -numpy.fliplr(self.xDispArray)
other.yDispArray = numpy.fliplr(self.yDispArray)
other.pixelSize = self.pixelSize
other.grid = self.grid
other.array2spline()
return other
def fliplrud(self):
"""
Flip the spline left-right and up-down
:return: new spline object
"""
self.spline2array()
other = self.__class__()
other.xmin = self.xmin
other.ymin = self.ymin
other.xmax = self.xmax
other.ymax = self.ymax
other.xDispArray = -numpy.flipud(numpy.fliplr(self.xDispArray))
other.yDispArray = -numpy.flipud(numpy.fliplr(self.yDispArray))
other.pixelSize = self.pixelSize
other.grid = self.grid
other.array2spline()
return other
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