maps.py 11 KB
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"""
------------------------------------------------------
Utility functions for handling mirror surface
maps. Some functions based on earlier version
in Matlab (http://www.gwoptics.org/simtools/)
Work in progress, currently these functions are
untested!

http://www.gwoptics.org/pykat/
------------------------------------------------------
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

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from pykat.optics.romhom import makeReducedBasis, makeEmpiricalInterpolant, makeWeights
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from scipy.interpolate import interp2d
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import numpy as np
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import math
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from pykat.math.zernike import *        
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class surfacemap(object):
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    def __init__(self, name, maptype, size, center, step_size, scaling, data=None):
        
        self.name = name
        self.type = maptype
        self.center = center
        self.step_size = step_size
        self.scaling = scaling
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        self.__interp = None
        
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        if data is None:
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            self.data = np.zeros(size)
        else:
            self.data = data

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        self._rom_weights = None
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    def write_map(self, filename):
        with open(filename,'w') as mapfile:
            
            mapfile.write("% Surface map\n")
            mapfile.write("% Name: {0}\n".format(self.name))
            mapfile.write("% Type: {0}\n".format(self.type))
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            mapfile.write("% Size: {0} {1}\n".format(self.data.shape[0], self.data.shape[1]))
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            mapfile.write("% Optical center (x,y): {0} {1}\n".format(self.center[0], self.center[1]))
            mapfile.write("% Step size (x,y): {0} {1}\n".format(self.step_size[0], self.step_size[1]))
            mapfile.write("% Scaling: {0}\n".format(float(self.scaling)))
            mapfile.write("\n\n")
            
            for i in range(0, self.data.shape[0]):
                for j in range(0, self.data.shape[1]):
                    mapfile.write("%.15g " % self.data[i,j])
                mapfile.write("\n")
    
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    @property
    def data(self):
        return self.__data
    
    @data.setter
    def data(self, value):
        self.__data = value
        self.__interp = None
    
    @property
    def center(self):
        return self.__center
    
    @center.setter
    def center(self, value):
        self.__center = value
        self.__interp = None
    
    @property
    def step_size(self):
        return self.__step_size
    
    @step_size.setter
    def step_size(self, value):
        self.__step_size = value
        self.__interp = None

    @property
    def scaling(self):
        return self.__scaling
    
    @scaling.setter
    def scaling(self, value):
        self.__scaling = value
        self.__interp = None

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    @property
    def x(self):
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        return self.step_size[0] * (np.array(range(1, self.data.shape[0]+1)) - self.center[0])
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    @property
    def y(self):
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        return self.step_size[1] * (np.array(range(1, self.data.shape[1]+1))- self.center[1])
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    @property
    def size(self):
        return self.data.shape
            
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    @property
    def offset(self):
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        return np.array(self.step_size)*(np.array(self.center) - 1/2. - np.array(self.size)/2.0)
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    @property
    def ROMWeights(self):
        return self._rom_weights
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    def z_xy(self, x=None, y=None, wavelength=1064e-9, direction="reflection", nr1=1.0, nr2=1.0):
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        if x is None and y is None:
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            data = self.scaling * self.data
        else:
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            if self.__interp is None:
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                self.__interp = interp2d(self.x, self.y, self.data * self.scaling)
                
            data = self.__interp(x, y)
            
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        if direction == "reflection":
            if "phase" in self.type:
                k = math.pi * 2 / wavelength
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                return np.exp(2j * k * data)
                
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            elif "absorption" in self.type:
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                return np.sqrt(1.0 - data)
                
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            else:
                raise BasePyKatException("Map type needs handling")
        elif direction == "transmission":
            if "phase" in self.type:
                k = math.pi * 2 / wavelength
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                return np.exp((nr1-nr2)*k * data)
                
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            elif "absorption" in self.type:
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                return np.sqrt(1.0 - data)
                
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            else:
                raise BasePyKatException("Map type needs handling")
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        else:
            raise BasePyKatException("Map type needs handling")
        
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    def generateROMWeights(self, isModeMatched=True, verbose=False, interpolate=False, interpolate_N=None, tolerance = 1e-12, sigma = 1, sort=False, greedyfile=None):
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        if interpolate:
            from scipy.interpolate import interp2d
            import numpy as np

            D = interp2d(self.x, self.y, self.data, fill_value=0)
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            if interpolate_N is None:
                interpolate_N = (self.size[0], self.size[1])
                
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            # only want even number of data points spread equally
            # about the axes
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            if interpolate_N[0] % 2 == 0:
                Nx = interpolate_N[0]
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            else:
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                Nx = interpolate_N[0]-1
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            if interpolate_N[1] % 2 == 0:
                Ny = interpolate_N[1]
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            else:
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                Ny = interpolate_N[1]-1
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            nx = np.linspace(min(self.x), max(self.x), interpolate_N[0]) 
            ny = np.linspace(min(self.y), max(self.y), interpolate_N[1])
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            data = D(nx-self.offset[0], ny-self.offset[0])
            
            self.name += " [ROMHOM interpolated]"
            
            self.center = (np.array(data.shape)+1)/2.0
            
            self.data = data
        
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        xm = self.x[self.x<0]
        ym = self.y[self.y<0]
        
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        symm = False
        
        if min(xm) == min(ym) and max(xm) == max(ym) and len(xm) == len(ym):
            symm = True
        
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        EI = {}
        
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        EI["xm"] = makeEmpiricalInterpolant(makeReducedBasis(xm, isModeMatched=isModeMatched, tolerance = tolerance, sigma = sigma, greedyfile=greedyfile), sort=sort)
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        if symm:
            EI["ym"] = EI["xm"]
        else:
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            EI["ym"] = makeEmpiricalInterpolant(makeReducedBasis(ym, isModeMatched=isModeMatched, tolerance = tolerance, sigma = sigma, greedyfile=greedyfile), sort=sort)
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        EI["limits"] = EI["xm"].limits
        
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        self._rom_weights = makeWeights(self, EI, verbose=verbose)
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        return self.ROMWeights, EI
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    def plot(self, show=True, clabel=None, xlim=None, ylim=None):
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        import pylab
        
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        if xlim is not None:
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            _x = np.logical_and(self.x<=max(xlim)/100.0, self.x>=min(xlim)/100.0)
            xmin = np.min(np.where(_x == True))
            xmax = np.max(np.where(_x == True))
        else:
            xmin = 0
            xmax = len(self.x)-1
            xlim = [self.x.min()*100, self.x.max()*100]
    
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        if ylim is not None:
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            _y = np.logical_and(self.y<=max(ylim)/100.0, self.y>=min(ylim)/100.0)
            ymin = np.min(np.where(_y == True))
            ymax = np.max(np.where(_y == True))
        else:
            ymin = 0
            ymax = len(self.y)-1
            ylim = [self.y.min()*100, self.y.max()*100]
        
        zmin = self.data[xmin:xmax,ymin:ymax].min()
        zmax = self.data[xmin:xmax,ymin:ymax].max()

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        # 100 factor for scaling to cm
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        xrange = 100*self.x
        yrange = 100*self.y
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        fig = pylab.figure()
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        axes = pylab.pcolormesh(xrange, yrange, self.data, vmin=zmin, vmax=zmax)
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        pylab.xlabel('x [cm]')
        pylab.ylabel('y [cm]')
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        if xlim is not None: pylab.xlim(xlim)
        if ylim is not None: pylab.ylim(ylim)
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        pylab.title('Surface map {0}, type {1}'.format(self.name, self.type))
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        cbar = fig.colorbar(axes)
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        cbar.set_clim(zmin, zmax)
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        if clabel is not None:
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            cbar.set_label(clabel)
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        if show:
            pylab.show()
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        return fig
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class aperturemap(surfacemap):
    
    def __init__(self, name, size, step_size, R):
        surfacemap.__init__(self, name, "absorption both", size, (np.array(size)+1)/2.0, step_size, 1)
        self.R = R
        
    @property
    def R(self):
        return self.__R
    
    @R.setter
    def R(self, value):
        self.__R = value
    
        xx, yy = np.meshgrid(self.x, self.y)
        
        radius = np.sqrt(xx**2 + yy**2)
        
        self.data = np.zeros(self.size)
        self.data[radius > self.R] = 1.0
        
        
class curvedmap(surfacemap):
    
    def __init__(self, name, size, step_size, Rc):
        surfacemap.__init__(self, name, "phase reflection", size, (np.array(size)+1)/2.0, step_size, 1e-6)
        self.Rc = Rc
        
    @property
    def Rc(self):
        return self.__Rc
    
    @Rc.setter
    def Rc(self, value):
        self.__Rc = value
    
        xx, yy = np.meshgrid(self.x, self.y)
        
        Rsq = xx**2 + yy**2
        self.data = (self.Rc - math.copysign(1.0, self.Rc) * np.sqrt(self.Rc**2 - Rsq))/ self.scaling
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class tiltmap(surfacemap):
    
    def __init__(self, name, size, step_size, tilt):
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        surfacemap.__init__(self, name, "phase reflection", size, (np.array(size)+1)/2.0, step_size, 1e-9)
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        self.tilt = tilt
        
    @property
    def tilt(self):
        return self.__tilt
    
    @tilt.setter
    def tilt(self, value):
        self.__tilt = value
        
        xx, yy = np.meshgrid(self.x, self.y)
        
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        self.data = (xx * self.tilt[1] + yy * self.tilt[0])/self.scaling
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class zernikemap(surfacemap):
	def __init__(self, name, size, step_size, radius, scaling=1e-9):
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		surfacemap.__init__(self, name, "phase reflection", size, (np.array(size)+1)/2.0, step_size, scaling)
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		self.__zernikes = {}
		self.radius = radius
		
	@property
	def radius(self): return self.__radius

	@radius.setter
	def radius(self, value, update=True):
		self.__radius = float(value)
		if update: self.update_data()

	def setZernike(self, m, n, amplitude, update=True):
		self.__zernikes["%i%i" % (m, n)] = (m,n,amplitude)
		if update: self.update_data()

	def update_data(self):
		X,Y = np.meshgrid(self.x, self.y)
		R = np.sqrt(X**2 + Y**2)
		PHI = np.arctan2(Y, X)

		data = np.zeros(np.shape(R))

		for i in self.__zernikes.items():
			data += i[1][2] * zernike(i[1][0], i[1][1], R/self.radius, PHI)

		self.data = data
	
			
	
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def read_map(filename):
    with open(filename, 'r') as f:
        
        f.readline()
        name = f.readline().split(':')[1].strip()
        maptype = f.readline().split(':')[1].strip()
        size = tuple(map(lambda x: int(x), f.readline().split(':')[1].strip().split()))
        center = tuple(map(lambda x: float(x), f.readline().split(':')[1].strip().split()))
        step = tuple(map(lambda x: float(x), f.readline().split(':')[1].strip().split()))
        scaling = float(f.readline().split(':')[1].strip())
        
        
        
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    data = np.loadtxt(filename, dtype=np.float64,ndmin=2,comments='%')    
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    return surfacemap(name,maptype,size,center,step,scaling,data)
    
    
        
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