def _plotArrays(self):
import gist
for array in self._getArrays():
gist.plg(*array)
gist.logxy(self.xlog, self.ylog)
def _plotArrays(self):
import gist
for array in self._getArrays():
gist.plg(*array)
gist.logxy(self.xlog, self.ylog)
def bode(w,H,win=0,frame=0,lcolor='blue',color='black',tcolor='black',freq='rad'):
"""Plot a bode plot of the transfer function H as a function of w.
"""
if freq == 'Hz':
w = w /2.0 / pi
subplot(2,1,win,hsep=120,frame=frame,color=color)
gist.plsys(1)
gist.plg(20*numpy.log10(abs(H)),w,type='solid',color=lcolor,marks=0)
gist.logxy(1,0)
gist.gridxy(1,1)
if freq == 'Hz':
xlabel('Frequency (Hz)',color=tcolor,deltay=-0.005)
else:
xlabel('Frequency (rad/s)',color=tcolor,deltay=-0.005)
ylabel('Magnitude (dB)',color=tcolor,deltax=-0.005)
title("Bode Plot",color=tcolor)
gist.plsys(2)
gist.plg(180/pi*numpy.unwrap(MLab.angle(H)),w,type='solid',color=lcolor,marks=0)
gist.logxy(1,0)
gist.gridxy(1,1)
if freq == 'Hz':
xlabel('Frequency (Hz)',color=tcolor,deltay=-0.005)
else:
xlabel('Frequency (rad/s)',color=tcolor,deltay=-0.005)
ylabel('Phase (deg.)',color=tcolor,deltax=-0.005)
def bode(w,H,win=0,frame=0,lcolor='blue',color='black',tcolor='black',freq='rad'):
"""Plot a bode plot of the transfer function H as a function of w.
"""
if freq == 'Hz':
w = w /2.0 / pi
subplot(2,1,win,hsep=120,frame=frame,color=color)
gist.plsys(1)
gist.plg(20*numpy.log10(abs(H)),w,type='solid',color=lcolor,marks=0)
gist.logxy(1,0)
gist.gridxy(1,1)
if freq == 'Hz':
xlabel('Frequency (Hz)',color=tcolor,deltay=-0.005)
else:
xlabel('Frequency (rad/s)',color=tcolor,deltay=-0.005)
ylabel('Magnitude (dB)',color=tcolor,deltax=-0.005)
title("Bode Plot",color=tcolor)
gist.plsys(2)
gist.plg(180/pi*numpy.unwrap(numpy.angle(H)),w,type='solid',color=lcolor,marks=0)
gist.logxy(1,0)
gist.gridxy(1,1)
if freq == 'Hz':
xlabel('Frequency (Hz)',color=tcolor,deltay=-0.005)
else:
xlabel('Frequency (rad/s)',color=tcolor,deltay=-0.005)
ylabel('Phase (deg.)',color=tcolor,deltax=-0.005)
def makeleg(leg,pos,lenx,dd,theight=12):
# Place legend
x0,y0 = pos
dx,dy = dd
for k in range(len(leg['txt'])):
gist.plg([y0+k*dy]*2,[x0,x0+lenx],type=leg['sym'][k][1],marks=0)
if leg['sym'][k][0] is not None:
gist.plg([y0+k*dy]*2,[x0,x0+lenx],type='none',marks=1,marker=leg['sym'][k][0])
if leg['txt'][k] != "":
gist.plt(leg['txt'][k],x0+lenx+dx,y0+k*dy,height=theight,tosys=1,justify='LH')
return
def makeleg(leg,pos,lenx,dd,theight=12):
# Place legend
x0,y0 = pos
dx,dy = dd
for k in range(len(leg['txt'])):
gist.plg([y0+k*dy]*2,[x0,x0+lenx],type=leg['sym'][k][1],marks=0)
if leg['sym'][k][0] is not None:
gist.plg([y0+k*dy]*2,[x0,x0+lenx],type='none',marks=1,marker=leg['sym'][k][0])
if leg['txt'][k] != "":
gist.plt(leg['txt'][k],x0+lenx+dx,y0+k*dy,height=theight,tosys=1,justify='LH')
return
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 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 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 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 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 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 onGist ( self, event ):
# print "... Gist button pressed"
self.isGistWindowOn = 1
gist.plg([0,1])
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
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
import gist
gist.pldefault(marks=0)
n = 5000
t = 0.001
v = numpy.empty(n)
for i in range(n):
a = time.time()
time.sleep(t)
v[i] = time.time() - a
print v.min(), v.max(), v.std()
gist.plg(v, color="red")
tt = long(1e9 * t)
v = numpy.empty(n)
rt.sched_setscheduler()
time.sleep(1)
for i in range(n):
a = time.time()
rt.clock_nanosleep(tt)
v[i] = time.time() - a
print v.min(), v.max(), v.std()
gist.plg(v, color="blue")
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