def plot(self, filename=None): import gist gist.window(self.id, wait = 1) gist.pltitle(self.title) gist.animate(1) var = self.vars[0] if isinstance(var, FaceVariable): x, y = var.getMesh().getFaceCenters() elif isinstance(var, CellVariable): x, y = var.getMesh().getCellCenters() gist.plmesh(numerix.array([y, y]), numerix.array([x, y])) vx = numerix.array(var[0]) vy = numerix.array(var[1]) maxVec = var.getMag().max().getValue() maxGrid = var.getMesh()._getCellDistances().max() gist.plv(numerix.array([vy,vy]), numerix.array([vx,vx]), scale=maxGrid / maxVec * 3, hollow=1, aspect=0.25) #,scale=0.002) if filename is not None: gist.hcp_file(filename) gist.hcp() gist.fma()
def plotMesh(self, filename = None): self._plot() faceVertexIDs = self.mesh.faceVertexIDs vertexCoords = self.mesh.vertexCoords x0 = numerix.take(vertexCoords[0], faceVertexIDs[0]) y0 = numerix.take(vertexCoords[1], faceVertexIDs[0]) x1 = numerix.take(vertexCoords[0], faceVertexIDs[1]) y1 = numerix.take(vertexCoords[1], faceVertexIDs[1]) import gist gist.pldj(x0, y0, x1, y1) if filename is not None: import os.path root, ext = os.path.splitext(filename) if ext.lower() in (".eps", ".epsi"): gist.eps(root) else: gist.hcp_file(filename, dump = 1) gist.hcp() gist.hcp_finish(-1) gist.fma()
def movie(data,aslice,plen,loop=1,direc='z',cmax=None,cmin=None): "movie(data,slice,pause,loop=1,direc='z')" gist.animate(1) if type(aslice) is types.IntType: num = aslice aslice = [slice(None)]*3 aslice[ord('x')-ord(direc)-1] = num for num in range(loop): for k in range(data.shape[0]): gist.fma() gist.pli(data[k][aslice],cmax=cmax,cmin=cmin) gist.pause(plen) gist.animate(0)
def plot(self, filename=None): import gist if filename is not None: import os.path root, ext = os.path.splitext(filename) if ext.lower() in (".eps", ".epsi"): gist.eps(root) else: gist.hcp_file(filename, dump=1) gist.hcp() gist.hcp_finish(-1) gist.fma()
def plot(self, filename=None): import gist if filename is not None: import os.path root, ext = os.path.splitext(filename) if ext.lower() in (".eps", ".epsi"): gist.eps(root) else: gist.hcp_file(filename, dump = 1) gist.hcp() gist.hcp_finish(-1) gist.fma()
def imagesc(z,cmin=None,cmax=None,xryr=None,_style='default', palette=None, color='black',colormap=None): """Plot an image on axes. z -- The data cmin -- Value to map to lowest color in palette (min(z) if None) cmax -- Value to map to highest color in palette (max(z) if None) xryr -- (xmin, ymin, xmax, ymax) coordinates to print (0, 0, z.shape[1], z.shape[0]) if None _style -- A 'style-sheet' to use if desired (a default one will be used if 'default'). If None, then no style will be imposed. palette -- A string for a palette previously saved in a file (see write_palette) or an array specifying the red-green-blue values (2-d array N x 3) or gray-scale values (2-d array N x 1 or 1-d array). color -- The color to use for the axes. """ if xryr is None: xryr = (0,0,z.shape[1],z.shape[0]) try: _style = None saveval = gist.plsys(2) gist.plsys(saveval) except: _style = 'default' if not _hold: gist.fma() gist.animate(0) if _style is not None: if _style == "default": _style=os.path.join(_user_path,'image.gs') system = write_style.getsys(hticpos='below',vticpos='left',frame=1, color=color) fid = open(_style,'w') fid.write(write_style.style2string(system)) fid.close() gist.window(style=_style) _current_style=_style if cmax is None: cmax = max(ravel(z)) if cmin is None: cmin = min(ravel(z)) cmax = float(cmax) cmin = float(cmin) byteimage = gist.bytscl(z,cmin=cmin,cmax=cmax) if (colormap is not None): palette=colormap change_palette(palette) gist.pli(byteimage,xryr[0],xryr[1],xryr[2],xryr[3]) return
def imagesc_cb(z,cmin=None,cmax=None,xryr=None,_style='default', zlabel=None,font='helvetica',fontsize=16,color='black', palette=None): """Plot an image on axes with a colorbar on the side. z -- The data cmin -- Value to map to lowest color in palette (min(z) if None) cmax -- Value to map to highest color in palette (max(z) if None) xryr -- (xmin, ymin, xmax, ymax) coordinates to print (0, 0, z.shape[1], z.shape[0]) if None _style -- A 'style-sheet' to use if desired (a default one will be used if 'default'). If None, then no style will be imposed. palette -- A string for a palette previously saved in a file (see write_palette) or an array specifying the red-green-blue values (2-d array N x 3) or gray-scale values (2-d array N x 1 or 1-d array). zlabel -- The label to attach to the colorbar (font, fontsize, and color match this). color -- The color to use for the ticks and frame. """ if xryr is None: xryr = (0,0,z.shape[1],z.shape[0]) if not _hold: gist.fma() gist.animate(0) if _style is not None: if _style == 'default': _style=os.path.join(_user_path,"colorbar.gs") system = write_style.getsys(hticpos='below',vticpos='left',frame=1,color=color) fid = open(_style,'w') fid.write(write_style.style2string(system)) fid.close() gist.window(style=_style) _current_style=_style if cmax is None: cmax = max(ravel(z)) if cmin is None: cmin = min(ravel(z)) cmax = float(cmax) cmin = float(cmin) change_palette(palette) byteimage = gist.bytscl(z,cmin=cmin,cmax=cmax) gist.pli(byteimage,xryr[0],xryr[1],xryr[2],xryr[3]) colorbar.color_bar(cmin,cmax,ncol=240,zlabel=zlabel,font=font,fontsize=fontsize,color=color)
def matplot(x,y=None,axis=-1): if y is None: # no axis data y = x x = Numeric.arange(0,y.shape[axis]) x,y = Numeric.asarray(x), Numeric.asarray(y) assert(len(y.shape)==2) assert(len(x)==y.shape[axis]) otheraxis = (1+axis) % 2 sliceobj = [slice(None)]*2 if not _hold and gist.plsys() < 2: gist.fma() clear_global_linetype() for k in range(y.shape[otheraxis]): thiscolor = _colors[_corder[k % len(_corder)]] sliceobj[otheraxis] = k ysl = where(numpy.isfinite(y[sliceobj]),y[sliceobj],0) gist.plg(ysl,x,type='solid',color=thiscolor,marks=0) append_global_linetype(_rcolors[thiscolor]+'-')
def matplot(x,y=None,axis=-1): if y is None: # no axis data y = x x = numpy.arange(0,y.shape[axis]) x,y = numpy.asarray(x), numpy.asarray(y) assert(len(y.shape)==2) assert(len(x)==y.shape[axis]) otheraxis = (1+axis) % 2 sliceobj = [slice(None)]*2 if not _hold and gist.plsys() < 2: gist.fma() clear_global_linetype() for k in range(y.shape[otheraxis]): thiscolor = _colors[_corder[k % len(_corder)]] sliceobj[otheraxis] = k ysl = where(numpy.isfinite(y[sliceobj]),y[sliceobj],0) gist.plg(ysl,x,type='solid',color=thiscolor,marks=0) append_global_linetype(_rcolors[thiscolor]+'-')
def errorbars(x,y,err,ptcolor='r',linecolor='B',pttype='o',linetype='-',fac=0.25): """Draw connected points with errorbars. Description: Plot connected points with errorbars. Inputs: x, y -- The points to plot. err -- The error in the y values. ptcolor -- The color for the points. linecolor -- The color of the connecting lines and error bars. pttype -- The type of point ('o', 'x', '+', '.', 'x', '*') linetype -- The type of line ('-', '|', ':', '-.', '-:') fac -- Adjusts how long the horizontal lines are which make the top and bottom of the error bars. """ # create line arrays yb = y - err ye = y + err try: override = 1 savesys = gist.plsys(2) gist.plsys(savesys) except: override = 0 if _hold or override: pass else: gist.fma() y = where(numpy.isfinite(y),y,0) gist.plg(y,x,color=_colors[ptcolor],marker=_markers[pttype],type='none') gist.pldj(x,yb,x,ye,color=_colors[linecolor],type=_types[linetype]) viewp = gist.viewport() plotlims = gist.limits() conv_factorx = (viewp[1] - viewp[0]) / (plotlims[1]-plotlims[0]) conv_factory = (viewp[3] - viewp[2]) / (plotlims[3]-plotlims[2]) width = fac*(x[1]-x[0]) x0 = x-width/2.0 x1 = x+width/2.0 gist.pldj(x0,ye,x1,ye,color=_colors[linecolor],type=_types[linetype]) gist.pldj(x0,yb,x1,yb,color=_colors[linecolor],type=_types[linetype]) return
def getFocusCents(zernlist={3: 1.}, nact=9, readnoise=10., usePoisson=1, sig=500. / 64, plot=0, fullpupil=0): """Compute centroids that would be obtained for a focus zernike term. zernlist can also be a phasescreen... """ import util.zernikeMod, util.centroid, util.tel nphs = (nact - 1) * 8 pupil = util.tel.Pupil(nphs, nphs / 2, 0) if fullpupil: pupil.fn[:] = 1 avphase = numpy.zeros((nact - 1, nact - 1), numpy.float64) if type(zernlist) == numpy.ndarray: phase = zernlist else: zern = util.zernikeMod.Zernike(pupil, max(zernlist.keys()) + 1) phase = numpy.zeros((nphs, nphs), "d") for key in zernlist.keys(): phase += zernlist[key] * zern.zern[key] #focus zernike for i in range(nact - 1): for j in range(nact - 1): avphase[i, j] = numpy.average( numpy.array(phase[i * 8:i * 8 + 8, j * 8:j * 8 + 8].flat)) c = util.centroid.centroid(nact - 1, pupil.fn, readnoise=readnoise, addPoisson=usePoisson, readbg=0., sig=sig) c.printmax = 1 cents = c.calc(phase) if plot: print "Max counts: %g, max, min per subap %g %g, plotting SHS image..." % ( max(c.tile.flat), max(c.photPerSubap.flat), min( c.photPerSubap.flat)) gist.fma() gist.pli(c.tile) #cents=util.centroid.calc(phase,8,pupil.fn) return c, phase, avphase
def run(arrow_scales=True): gist.fma() # generate a random field test_dim=10 dx=numpy.random.rand(test_dim**2)-0.5 dy=numpy.random.rand(test_dim**2)-0.5 p=numpy.indices((test_dim,test_dim)) x=p[0].ravel() y=p[1].ravel() X1=x Y1=y X2=x+dx Y2=y+dy gist.pldj(X1,Y1,X2,Y2) arrow_a = numpy.pi/6. arrow_len = .5 slo=(Y2-Y1)/(X2-X1) ang=numpy.arctan(slo) ang1=ang+arrow_a ang2=ang-arrow_a if arrow_scales: ar_=numpy.sign(X2-X1)*arrow_len*((X2-X1)**2+(Y2-Y1)**2) aX1=X2-ar_*numpy.cos(ang1) aY1=Y2-ar_*numpy.sin(ang1) aX2=X2-ar_*numpy.cos(ang2) aY2=Y2-ar_*numpy.sin(ang2) else: ar_=numpy.sign(X2-X1)*arrow_len*numpy.max(((X2-X1)**2+(Y2-Y1)**2)**.5) aX1=X2-ar_*numpy.cos(ang1) aY1=Y2-ar_*numpy.sin(ang1) aX2=X2-ar_*numpy.cos(ang2) aY2=Y2-ar_*numpy.sin(ang2) gist.pldj(X2,Y2,aX1,aY1,color='red') gist.pldj(X2,Y2,aX2,aY2,color='red') gist.limits()
def stem(m, y, linetype='b-', mtype='mo', shift=0.013): y0 = Numeric.zeros(len(y),y.dtype.char) y1 = y x0 = m x1 = m try: override = 1 savesys = gist.plsys(2) gist.plsys(savesys) except: override = 0 if not (_hold or override): gist.fma() thetype,thecolor,themarker,tomark = _parse_type_arg(linetype,0) lcolor = thecolor gist.pldj(x0, y0, x1, y1, color=thecolor, type=thetype) thetype,thecolor,themarker,tomark = _parse_type_arg(mtype,0) if themarker not in ['o','x','.','*']: themarker = 'o' y = where(numpy.isfinite(y),y,0) gist.plg(y,m,color=thecolor,marker=themarker,type='none') gist.plg(Numeric.zeros(len(m)),m,color=lcolor,marks=0) gist.limits() lims = gist.limits() newlims = [None]*4 vp = gist.viewport() factor1 = vp[1] - vp[0] factor2 = vp[3] - vp[2] cfactx = factor1 / (lims[1] - lims[0]) cfacty = factor2 / (lims[3] - lims[2]) d1 = shift / cfactx d2 = shift / cfacty newlims[0] = lims[0] - d1 newlims[1] = lims[1] + d1 newlims[2] = lims[2] - d2 newlims[3] = lims[3] + d2 gist.limits(*newlims) return
def stem(m, y, linetype='b-', mtype='mo', shift=0.013): y0 = numpy.zeros(len(y),y.dtype.char) y1 = y x0 = m x1 = m try: override = 1 savesys = gist.plsys(2) gist.plsys(savesys) except: override = 0 if not (_hold or override): gist.fma() thetype,thecolor,themarker,tomark = _parse_type_arg(linetype,0) lcolor = thecolor gist.pldj(x0, y0, x1, y1, color=thecolor, type=thetype) thetype,thecolor,themarker,tomark = _parse_type_arg(mtype,0) if themarker not in ['o','x','.','*']: themarker = 'o' y = where(numpy.isfinite(y),y,0) gist.plg(y,m,color=thecolor,marker=themarker,type='none') gist.plg(numpy.zeros(len(m)),m,color=lcolor,marks=0) gist.limits() lims = gist.limits() newlims = [None]*4 vp = gist.viewport() factor1 = vp[1] - vp[0] factor2 = vp[3] - vp[2] cfactx = factor1 / (lims[1] - lims[0]) cfacty = factor2 / (lims[3] - lims[2]) d1 = shift / cfactx d2 = shift / cfacty newlims[0] = lims[0] - d1 newlims[1] = lims[1] + d1 newlims[2] = lims[2] - d2 newlims[3] = lims[3] + d2 gist.limits(*newlims) return
def barplot(x,y,width=0.8,color=0): """Plot a barplot. Description: Plot a barplot with centers at x and heights y with given color Inputs: x, y -- Centers and heights of bars width -- Relative width of the bars. color -- A number from the current palette. """ N = 4*Numeric.ones(len(x)) hw = width * (x[1]-x[0])/ 2.0 Xa = x-hw Xb = x+hw Ya = Numeric.zeros(len(y),'d') Yb = y X = Numeric.array((Xa,Xa,Xb,Xb)) Y = Numeric.array((Ya,Yb,Yb,Ya)) X = Numeric.reshape(Numeric.transpose(X),(4*len(N),)) Y = Numeric.reshape(Numeric.transpose(Y),(4*len(N),)) try: override = 1 savesys = gist.plsys(2) gist.plsys(savesys) except: override = 0 if _hold or override: pass else: gist.fma() Z = color * Numeric.ones(len(N)) gist.plfp(Z.astype('B'),Y,X,N) return
def barplot(x,y,width=0.8,color=0): """Plot a barplot. Description: Plot a barplot with centers at x and heights y with given color Inputs: x, y -- Centers and heights of bars width -- Relative width of the bars. color -- A number from the current palette. """ N = 4*numpy.ones(len(x), dtype=numpy.int32) hw = width * (x[1]-x[0])/ 2.0 Xa = x-hw Xb = x+hw Ya = numpy.zeros(len(y),'d') Yb = y X = numpy.array((Xa,Xa,Xb,Xb)) Y = numpy.array((Ya,Yb,Yb,Ya)) X = numpy.reshape(numpy.transpose(X),(4*len(N),)) Y = numpy.reshape(numpy.transpose(Y),(4*len(N),)) try: override = 1 savesys = gist.plsys(2) gist.plsys(savesys) except: override = 0 if _hold or override: pass else: gist.fma() Z = color * numpy.ones(len(N)) gist.plfp(Z.astype(numpy.uint8),Y,X,N) return
def plotImg(img): import gist im=img[256*256:] im.shape=128,128 gist.fma() gist.pli(im)
def plot(x,*args,**keywds): """Plot curves. Description: Plot one or more curves on the same graph. Inputs: There can be a variable number of inputs which consist of pairs or triples. The second variable is plotted against the first using the linetype specified by the optional third variable in the triple. If only two plots are being compared, the x-axis does not have to be repeated. """ try: override = 1 savesys = gist.plsys(2) gist.plsys(savesys) except: override = 0 global _hold try: _hold=keywds['hold'] except KeyError: pass try: linewidth=float(keywds['width']) except KeyError: linewidth=1.0 try: msize = float(keywds['msize']) except KeyError: msize=1.0 if _hold or override: pass else: gist.fma() gist.animate(0) savesys = gist.plsys() winnum = gist.window() if winnum < 0: gist.window(0) if savesys >= 0: gist.plsys(savesys) nargs = len(args) if nargs == 0: y = _minsqueeze(x) x = numpy.arange(0,len(y)) if numpy.iscomplexobj(y): print "Warning: complex data plotting real part." y = y.real y = where(numpy.isfinite(y),y,0) gist.plg(y,x,type='solid',color='blue',marks=0,width=linewidth) return y = args[0] argpos = 1 nowplotting = 0 clear_global_linetype() while 1: try: thearg = args[argpos] except IndexError: thearg = 0 thetype,thecolor,themarker,tomark = _parse_type_arg(thearg,nowplotting) if themarker == 'Z': # args[argpos] was data or non-existent. pass append_global_linetype(_rtypes[thetype]+_rcolors[thecolor]) else: # args[argpos] was a string argpos = argpos + 1 if tomark: append_global_linetype(_rtypes[thetype]+_rcolors[thecolor]+_rmarkers[themarker]) else: append_global_linetype(_rtypes[thetype]+_rcolors[thecolor]) if numpy.iscomplexobj(x) or numpy.iscomplexobj(y): print "Warning: complex data provided, using only real part." x = numpy.real(x) y = numpy.real(y) y = where(numpy.isfinite(y),y,0) y = _minsqueeze(y) x = _minsqueeze(x) gist.plg(y,x,type=thetype,color=thecolor,marker=themarker,marks=tomark,msize=msize,width=linewidth) nowplotting = nowplotting + 1 ## Argpos is pointing to the next potential triple of data. ## Now one of four things can happen: ## ## 1: argpos points to data, argpos+1 is a string ## 2: argpos points to data, end ## 3: argpos points to data, argpos+1 is data ## 4: argpos points to data, argpos+1 is data, argpos+2 is a string if argpos >= nargs: break # no more data if argpos == nargs-1: # this is a single data value. x = x y = args[argpos] argpos = argpos+1 elif type(args[argpos+1]) is types.StringType: x = x y = args[argpos] argpos = argpos+1 else: # 3 x = args[argpos] y = args[argpos+1] argpos = argpos+2 return
import numpy import gist gist.fma() # generate a random field test_dim = 10 dx = numpy.random.rand(test_dim**2) - 0.5 dy = numpy.random.rand(test_dim**2) - 0.5 p = numpy.indices((test_dim, test_dim)) x = p[0].ravel() y = p[1].ravel() X1 = x Y1 = y X2 = x + dx Y2 = y + dy gist.pldj(X1, Y1, X2, Y2) arrow_a = numpy.pi / 6. arrow_len = .5 arrow_scales = False arrow_scales = True slo = (Y2 - Y1) / (X2 - X1) ang = numpy.arctan(slo) ang1 = ang + arrow_a ang2 = ang - arrow_a
spotpsf=numpy.zeros((fftsize,fftsize),"f") spotpsf[fftsize/2-5:fftsize/2+5,fftsize/2-5:fftsize/2+5]=1 spotpsf[fftsize/2-7:fftsize/2-3,fftsize/2-7:fftsize/2-3]=1 spotpsf[fftsize/2+3:fftsize/2+7,fftsize/2+3:fftsize/2+7]=1 elif spotpsfdim==4: spotpsf=numpy.zeros((nsubx,nsubx,fftsize,fftsize),"f") spotpsf[:,:,fftsize/2-5:fftsize/2+5,fftsize/2-5:fftsize/2+5]=1 spotpsf[:,:,fftsize/2-7:fftsize/2-3,fftsize/2-7:fftsize/2-3]=1 spotpsf[:,:,fftsize/2+3:fftsize/2+7,fftsize/2+3:fftsize/2+7]=1 spotpsf[2,2,fftsize/2-4:fftsize/2+4,fftsize/2-4:fftsize/2+4]=0 #spotpsf[2,2]=0. else: spotpsf=None if type(sig)==numpy.ArrayType: sig=sig.flat bimg=numpy.zeros((nsubx,nsubx,nimg,nimg),numpy.float32) print "Initialising" cc=util.centcmod.centcmod(nthreads,nsubx,ncen,fftsize,nimg,phasesize,readnoise,readbg,addPoisson,noiseFloor,sig,skybrightness,calsource,pxlPower,nintegrations,seed,reorderedPhs,pup,spotpsf,cents,bimg) print "Running" t=cc.run(calsource) print "Time taken",t def makeImage(bimg): img=numpy.zeros((nsubx*nimg,nsubx*nimg),numpy.float32) for i in range(nsubx): for j in range(nsubx): img[i*nimg:(i+1)*nimg,j*nimg:(j+1)*nimg]=bimg[i,j] return img gist.fma();gist.pli(makeImage(bimg))
from iqe import * import gist def plot_cross(x,y,sz=1,color='red'): gist.pldj([x],[y-sz],[x],[y+sz],color=color) gist.pldj([x-sz],[y],[x+sz],[y],color=color) file=os.path.join(os.path.dirname(__file__),'ascam1_20080710T230802.fits') data=pyfits.open(file)[0].data z=data[686-4-1-5-5:686+4-1+5-5,711-4-1-1-5:711+4-1-1+5] ##z=numpy.flipud(z) ana=iqe(z) gist.fma() gist.pli(z) plot_cross(ana[0]+.5,ana[1]+.5) ## sub-image Z = z[10:18,6:14].copy() ana=iqe(Z) gist.fma() gist.pli(Z) plot_cross(ana[0]+.5,ana[1]+.5) ## add hotspot Z = z[10:18,6:14].copy() Z[3,2]=10.*Z.max() anah=iqe(Z) gist.fma()
def doit(zernlist=None, nact=9, cents=None, avphase=None, readnoise=10., usePoisson=1, sig=1000., fullpupil=0, monteNoiseCovariance=0, phaseCov="bccb", diagonaliseinvChatReordered=1, diagonaliseA=0.5, useChatFromDiagonalisedA=1, oversampleFFT=0, fft2d=1, oversampleAndBinFFTofr=0, removeHiFreqZ=0, removeHiFreqP=0, removeHiFreqX=0, convToPxl=1): """Create a zernike mode and get the centroids for this. Put these centroids into the PCG algorithm, and recreate the phase, and then compare with the original input phase defaultOptions are: diagonaliseinvChatReordered:1#should we diagonlise C-1, or use whole MX? diagonaliseA:0#should we diagonalise A or use the whole MX. useChatFromDiagonalisedA:1#should we compute invChat using a diagonalised chat or not? zernlist can be a dict of zernikes eg {3:1} would be focus, amplitude 1... or it can be the phase, or it can be none (in which case a phasescreen is created). This now seems to be working fairly well, iterates to an exact solution after about 10 iters, and 4-5 should be sufficient for a good solution. """ options = { "diagonaliseinvChatReordered": diagonaliseinvChatReordered, "diagonaliseA": diagonaliseA, "useChatFromDiagonalisedA": useChatFromDiagonalisedA, "oversampleFFT": oversampleFFT, "2dfft": fft2d, "oversampleAndBinFFTofr": oversampleAndBinFFTofr, "removeHiFreqZ": removeHiFreqZ, "removeHiFreqP": removeHiFreqP, "removeHiFreqX": removeHiFreqX } gist.window(0) gist.palette("gray.gp") pupfn = util.tel.Pupil(nact - 1, (nact - 1) / 2., 0).fn actfn = util.tel.Pupil(nact, nact / 2., 0).fn noiseCov = None if type(cents) == type(None): if type(zernlist) in [type(1), type(1.)]: zernlist = {zernlist: 1.} elif type(zernlist) == type([]): tmp = {} for i in zernlist: tmp[i] = 1. zernlist = tmp elif type(zernlist) == type(None): zernlist = science.infScrn.makeInitialScreen(dpix=(nact - 1) * 8, Dtel=4.2, L0=30., scrnXPxls=None, scrnYPxls=None, seed=None, tstep=0.05, globR0=0.2, strLayer=1., natype=numpy.float64, windDirection=0., vWind=10.)[:-1, 1:].copy() c, phase, avphase = getFocusCents(zernlist, nact=nact, readnoise=readnoise, usePoisson=usePoisson, sig=sig, plot=1, fullpupil=fullpupil) print phase.shape cents = c.cent if monteNoiseCovariance: noiseCov = c.computeNoiseCovariance(20, convertToRad=1) if convToPxl: #convert from radians to pixel values for the noises... radToPxlFactor = 1. / c.convFactor**2 else: radToPxlFactor = 1. Pcg = testfull(fromdisk=0, nact=nact, pupfn=pupfn, actfn=actfn, fullpmx=1, noiseCov=noiseCov, phaseCov=phaseCov, options=options, radToPxlFactor=radToPxlFactor) #agbhome Pcg.newCentroids(cents) Pcg.initialise() #now inverse A, multiply with b, to get the MVM reconstructed phase... invA = numpy.linalg.inv(Pcg.A) gist.fma() gist.pli(invA) raw_input("Displaying inverse of A... press return") gist.fma() gist.pli(phase) raw_input("The phase... press a key") recphase = quick.dot(invA, Pcg.b) print "Reconstructed phase min/max:", min(recphase.flat), max( recphase.flat) recphase.shape = (9, 9) gist.window(4) gist.palette("gray.gp") gist.fma() gist.pli(recphase) gist.palette("gray.gp") gist.window(0) chires = numpy.zeros((100, ), "d") #also compute what a traditional MVM with pokemx would give... #invpokemx=numpy.linalg.pinv(Pcg.pokemx)#same as generalised_inverse #pmphase=quick.dot(invpokemx,cents) print "Press return for next iteration or key+return to quit" #gist.fma() #gist.pli(numpy.reshape(pmphase,(nact,nact))) if type(avphase) != type(None): print "press a key" raw_input() gist.fma() gist.pli(avphase) actphase = phase2acts(avphase) actphase -= numpy.average(actphase.flat) #remove piston smallpupfn = util.tel.Pupil(nact, nact / 2. - 2, 0).fn raw_input("press return (min, max actphase is %g %g" % (min(actphase.flat), max(actphase.flat))) gist.fma() gist.pli(actphase) gist.window(1) gist.palette("gray.gp") gist.window(2) gist.palette("gray.gp") niter = 0 while len(raw_input()) == 0: niter += 1 gist.window(1) gist.fma() img = numpy.reshape(Pcg.x.real, (nact, nact)) gist.pli(img) gist.window(2) gist.fma() img = smallpupfn * img #gist.pli(numpy.where(img==0,min(img.flat),img)) gist.pli(numpy.reshape(Pcg.p, (nact, nact))) gist.window(3) gist.fma() fftimg = numpy.fft.fft2(numpy.reshape(Pcg.x, (nact, nact))) gist.pli(fftimg.real) Pcg.nextIter() chirespos = niter - 1 if chirespos > 99: chirespos = 99 chires[chirespos] = chi2(Pcg.x, recphase, scale=0) #changed from actphase Pcg.alphaHist[chirespos] = Pcg.alpha Pcg.betaHist[chirespos] = Pcg.beta Pcg.tolerance[chirespos] = max(numpy.fabs(Pcg.xprev - Pcg.x)) print niter, Pcg.tolerance[chirespos], chires[chirespos], min( Pcg.x.real), max(Pcg.x.real), min(Pcg.p), max( Pcg.p), Pcg.alphaHist[chirespos], Pcg.betaHist[chirespos] print "Press return for next iteration or key+return to quit" gist.fma() gist.plg(chires[:chirespos]) gist.window(2) gist.fma() gist.plg(Pcg.tolerance[:niter]) gist.window(0) return Pcg, actphase, phase, recphase, c
def handle(self, data): """Handle data returned from the simulation""" if data[1] == "warning" or data[1] == "error": print "Error retrieving data", data[1:], data[0] elif len(self.gettype()) == 0: #not doing anything with it... pass else: if self.when[:3] != "rpt" or self.repeating == 1: #still expecting data if self.ret != None and data[3].has_key(self.ret): data = data[3][self.ret] else: data = None ret = self.ret if ret == None: ret = "None" if self.button == None: d = {ret: data, "button": None} else: d = {ret: data, "button": self.button[0]} try: exec self.preprocess in d except: pass if self.button != None: self.button[0] = d["button"] data = d[ret] dim = self.dim xaxis = self.xaxis if dim == None: if type(data) == numpy.ndarray: if len(data.shape) > 1: dim = 2 elif len(data.shape) == 1: dim = 1 else: dim = 0 else: dim = 0 if dim == 1: if type(self.xaxis) == types.NoneType: if len(data.shape) > 1: xaxis = data[0] data = data[1:] else: xaxis = numpy.arange(data.shape[0]) data = data else: if type(self.xaxis) == types.StringType: xaxis = eval(self.xaxis) if self.gisttype: if type(data) == numpy.ndarray: if not self.info.has_key("window"): self.info["window"] = 0 if not self.info.has_key("palette"): self.info["palette"] = "gray.gp" if not self.info.has_key("gistdpi"): self.info["gistdpi"] = 75 if self.gistWindow == None: self.gistWindow = gist.window( self.info["window"], wait=1, dpi=self.info["gistdpi"]) gist.animate(0) gist.animate(1) gist.palette(self.info["palette"]) else: gist.window(self.gistWindow) #gist.fma() if dim == 1: for i in range(data.shape[0]): gist.plg(data[i], xaxis) else: gist.pli(data) gist.fma() else: print "Cannot display type %s with gist" % str( type(data)) if self.pylabtype: if type(data) == numpy.ndarray: if not self.info.has_key("palette"): self.info["palette"] = "gray" if not self.info.has_key("interp"): self.info["interp"] = "nearest" if not self.info.has_key("plotwin"): self.info["plotwin"] = mypylab.plot() p = self.info["plotwin"] p.win.set_title(self.title) p.newPalette(self.info["palette"]) p.newInterpolation(self.info["interp"]) p.deactivatefn = self.cancel #deactivate p = self.info["plotwin"] if dim == 1: p.dims = 1 axis = xaxis else: p.dims = 2 axis = None if p.active: p.plot(data, axis=axis) else: if self.button != None: self.button[0] = 0 #print "Not expecting this data any more... (simdata.handle, type=pylab)" self.repeating = 0 else: print "Cannot display type %s with pylab" % str( type(data)) if self.texttype: #self.info["texttype"]=="ownwindow, mainwindow", default own #self.info["replace"]==1 or 0, default 0 if not self.info.has_key("wintype"): self.info["wintype"] = "ownwindow" if not self.info.has_key("textreplace"): self.info["textreplace"] = 0 if self.info["wintype"] == "ownwindow": if self.textWindow == None: self.textWindow = textbox(self.title) self.textWindow.closeFunc = self.cancel #deactivate if self.textWindow.destroyed == 0: #print "adding text",str(data) self.textWindow.addText( str(data) + "\n", replace=self.info["textreplace"]) else: #tell simulation not to send... print "Not expecting this data any more... (simdata.handle, type=text)" self.textWindow = None self.repeating = 0 else: print str(data) if self.savetype: if not self.info.has_key("filetype"): self.info["filetype"] = "fits" if not self.info.has_key("filename"): self.info["filename"] = "tmp.fits" if not self.info.has_key("filereplace"): self.info["filereplace"] = 0 if self.info["filetype"] == "fits": if type(data) == numpy.ndarray: print "WARNING - depreciated - use util.FITS instead (code needs updating)" if self.info["filereplace"]: imghdu = util.pyfits.PrimaryHDU( numarray.array(data)) imghdu.header.update("DATE", time.asctime()) imghdu.header.update("USER", os.environ["USER"]) imghdu.header.update( "CREATOR", "simctrl.py simulation control") imghdu.header.update("TITLE", str(self.title)) imghdu.header.update("COMMAND", str(self.cmd)) imghdu.header.update("RETURN", str(self.ret)) imghdu.header.update("TYPE", self.gettype()) imghdu.header.update("PREPROC", str(self.preprocess)) imghdu.header.update("DIMS", str(self.dim)) imghdu.header.update("XAXIS", str(self.xaxis)) imghdu.header.update("WHEN", str(self.when)) imghdu.header.update("INFO", str(self.info)) hdulist = util.pyfits.HDUList([imghdu]) hdulist.writeto(self.info["filename"], clobber=True) else: f = util.pyfits.open(self.info["filename"], mode="update") imghdu = util.pyfits.ImageHDU( numarray.array(data)) imghdu.header.update("DATE", time.asctime()) imghdu.header.update("USER", os.environ["USER"]) imghdu.header.update( "CREATOR", "simctrl.py simulation control") imghdu.header.update("TITLE", str(self.title)) imghdu.header.update("COMMAND", str(self.cmd)) imghdu.header.update("RETURN", str(self.ret)) imghdu.header.update("TYPE", self.gettype()) imghdu.header.update("PREPROC", str(self.preprocess)) imghdu.header.update("DIMS", str(self.dim)) imghdu.header.update("XAXIS", str(self.xaxis)) imghdu.header.update("WHEN", str(self.when)) imghdu.header.update("INFO", str(self.info)) f.append(imghdu) f.close() else: print "Cannot save fits data of this format:", type( data) elif self.info["filetype"] == "csv": if self.info["filereplace"]: mode = "w" else: mode = "a" f = open(self.info["filename"], mode) f.write( "#Date\t%s\n#User\t%s\n#Creator\tsimctrl.py simulation control\n#Title\t%s\n#Command\t%s\n#Return\t%s\n#Type\t%s\n#Preprocess\t%s\n#Dims\t%s\n#Xaxis\t%s\n#When\t%s\n#Info\t%s\n" % (time.asctime(), os.environ["USER"], str(self.title), str(self.cmd), str(self.ret), self.gettype(), str(self.preprocess), str(self.dim), str(self.xaxis), str( self.when), str(self.info))) if dim == 1: try: for i in range(xaxis.shape[0]): f.write("%g" % float(xaxis[i])) for j in range(data.shape[0]): f.write("\t%g" % float(data[j][i])) f.write("\n") f.write("\n") except: print "Data not in correct 1D format - can't save as csv" f.write(str(data)) f.write("\n\n") else: print "Can't save 2D data as csv... using text instead" f.write(str(data)) f.write("\n\n") f.close() elif self.info["filetype"] == "text": if self.info["filereplace"]: mode = "w" else: mode = "a" f = open(self.info["filename"], mode) f.write( "#Date\t%s\n#User\t%s\n#Creator\tsimctrl.py simulation control\n#Title\t%s\n#Command\t%s\n#Return\t%s\n#Type\t%s\n#Preprocess\t%s\n#Dims\t%s\n#Xaxis\t%s\n#When\t%s\n#Info\t%s\n" % (time.asctime(), os.environ["USER"], str(self.title), str(self.cmd), str(self.ret), self.gettype(), str(self.preprocess), str(self.dim), str(self.xaxis), str( self.when), str(self.info))) f.write(str(data)) f.write("\n\n") f.close() else: print "Unrecognised filetype - not saving" if self.feedbacktype: try: d = {"feedback": data} exec self.info["feedbackmsg"] in d msg = d["msg"] except: msg = "Feedback data:" + str(data) print msg exec self.post else: print "Warning: No longer expecting data for", self.cmd
def plot(x,*args,**keywds): """Plot curves. Description: Plot one or more curves on the same graph. Inputs: There can be a variable number of inputs which consist of pairs or triples. The second variable is plotted against the first using the linetype specified by the optional third variable in the triple. If only two plots are being compared, the x-axis does not have to be repeated. """ try: override = 1 savesys = gist.plsys(2) gist.plsys(savesys) except: override = 0 global _hold try: _hold=keywds['hold'] except KeyError: pass try: linewidth=float(keywds['width']) except KeyError: linewidth=1.0 try: msize = float(keywds['msize']) except KeyError: msize=1.0 if _hold or override: pass else: gist.fma() gist.animate(0) savesys = gist.plsys() winnum = gist.window() if winnum < 0: gist.window(0) if savesys >= 0: gist.plsys(savesys) nargs = len(args) if nargs == 0: y = _minsqueeze(x) x = Numeric.arange(0,len(y)) if numpy.iscomplexobj(y): print "Warning: complex data plotting real part." y = y.real y = where(numpy.isfinite(y),y,0) gist.plg(y,x,type='solid',color='blue',marks=0,width=linewidth) return y = args[0] argpos = 1 nowplotting = 0 clear_global_linetype() while 1: try: thearg = args[argpos] except IndexError: thearg = 0 thetype,thecolor,themarker,tomark = _parse_type_arg(thearg,nowplotting) if themarker == 'Z': # args[argpos] was data or non-existent. pass append_global_linetype(_rtypes[thetype]+_rcolors[thecolor]) else: # args[argpos] was a string argpos = argpos + 1 if tomark: append_global_linetype(_rtypes[thetype]+_rcolors[thecolor]+_rmarkers[themarker]) else: append_global_linetype(_rtypes[thetype]+_rcolors[thecolor]) if numpy.iscomplexobj(x) or numpy.iscomplexobj(y): print "Warning: complex data provided, using only real part." x = numpy.real(x) y = numpy.real(y) y = where(numpy.isfinite(y),y,0) y = _minsqueeze(y) x = _minsqueeze(x) gist.plg(y,x,type=thetype,color=thecolor,marker=themarker,marks=tomark,msize=msize,width=linewidth) nowplotting = nowplotting + 1 ## Argpos is pointing to the next potential triple of data. ## Now one of four things can happen: ## ## 1: argpos points to data, argpos+1 is a string ## 2: argpos points to data, end ## 3: argpos points to data, argpos+1 is data ## 4: argpos points to data, argpos+1 is data, argpos+2 is a string if argpos >= nargs: break # no more data if argpos == nargs-1: # this is a single data value. x = x y = args[argpos] argpos = argpos+1 elif type(args[argpos+1]) is types.StringType: x = x y = args[argpos] argpos = argpos+1 else: # 3 x = args[argpos] y = args[argpos+1] argpos = argpos+2 return