def newfig(self, num=None):
if num is None:
if len(self.figs) > 0:
num = max(self.figs.keys()) + 1
else:
num = 1
thisFig = Figure(size=(600, 400))
thisFig.show()
win = gtk.Window()
win.set_title("Figure %d" % num)
win.connect("destroy", lambda *args: win.destroy())
win.set_border_width(5)
vbox = gtk.VBox(spacing=3)
win.add(vbox)
vbox.show()
vbox.pack_start(thisFig)
toolbar = NavigationToolbar(thisFig, win)
toolbar.show()
vbox.pack_start(toolbar, gtk.FALSE, gtk.FALSE)
figwin = FigureWin(thisFig, win, vbox, toolbar)
self.figs[num] = figwin
win.show()
return figwin
def newfig(self, num=None):
if num is None:
if len(self.figs)>0:
num = max(self.figs.keys())+1
else:
num = 1
thisFig = Figure(size=(600,400))
thisFig.show()
win = gtk.Window()
win.set_title("Figure %d" % num)
win.connect("destroy", lambda *args: win.destroy())
win.set_border_width(5)
vbox = gtk.VBox(spacing=3)
win.add(vbox)
vbox.show()
vbox.pack_start(thisFig)
toolbar = NavigationToolbar( thisFig, win)
toolbar.show()
vbox.pack_start(toolbar, gtk.FALSE, gtk.FALSE )
figwin = FigureWin(thisFig, win, vbox, toolbar)
self.figs[num] = figwin
win.show()
return figwin
def start_button_clicked(self):
cost_fun = str(self.cost_function.text())
max_it = int(self.max_iter.text())
eps = self.epsilon.text()
div_err = float(self.div_err.text())
x0 = self.initial_cond.text()
x0 = x0.replace(" ", "")
x0 = x0.split(",")
if len(x0) == 1:
x0 = float(x0[0])
else:
x0 = tuple(float(i) for i in x0)
eps = eps.replace(" ", "")
eps = eps.split(",")
if len(eps) == 3:
eps = tuple(float(i) for i in eps)
else:
eps = tuple(float(eps[0]) for i in range(3))
#ustawic tolerancje!!!!!! w funckacji
#gtol=1e-05, xtol=1e-09, fxtol=1e-09
opts = {'gtol': eps[0],
'xtol': eps[1],
'fxtol': eps[2],
'epsilon': div_err,
'maxiter': max_it
}
fun = Function(cost_fun)
x = fmindfp(fun, x0, disp=True, **opts)
#normalizacjay wjscia:
output = np.asarray(x[2])
output = output.tolist()
text = '\n'.join(output)
self.txt_browser.setText(text)
vec = x[1]
vec = np.asanyarray(vec)
print(vec.shape)
print(vec)
fig = Figure(fun, vec)
fig.show()
def createBarDiagram():
dialog = Figure()
dialog.exec_()
dialog.show()
class Stack:
"A class to load and manipulate images generated during single molecule experiments"
defaultROI = {}
defaultDonorROI = 'donor'
defaultAcceptorROI = 'acceptor'
@classmethod
def fromfile(cls, imgfile, camfile=''):
img = fileIO.loadimg(imgfile)
camfile = camfile or fileIO.to_cam_filename(imgfile)
metadata = fileIO.loadcam(camfile)
metadata['filename'] = imgfile
stack = cls(img, metadata)
# Keeping the .filename attribute for backward compatibility, but should move to
# metadata lookup
stack.filename = metadata['filename']
return stack
# def __init__(self, filename, camFile='', deepcopy=False):
def __init__(self, data, metadata={}, roi={}):
self._img = copy.copy(data)
self.metadata = dict(metadata)
self._donorROIName = Stack.defaultDonorROI
self._acceptorROIName = Stack.defaultAcceptorROI
self._figure = Figure()
self._roi = roi
if not roi:
self.addROI(*self.defaultROI.values())
self._frame_iter = cycle(range(self.frames))
if metadata:
self.origin = (self.metadata['roileft'],self.metadata['roibottom'])
if self._img.shape != (self.metadata['frames'],self.metadata['height'],self.metadata['width']):
raise StackError, ".img file and .cam file dimensions do not agree"
def copy(self, deep=True):
newstack = copy.copy(self)
if deep:
newstack._img = copy.copy(self._img)
return newstack
@property
def frames(self):
return self._img.shape[0]
def __len__(self):
return self.frames
@property
def time(self):
return np.arange(1,self.frames+1)*self.metadata['exposurems']/1000.
@property
def height(self):
return self._img.shape[1]
@property
def width(self):
return self._img.shape[2]
@property
def donor(self):
if not self._roi.has_key(self._donorROIName):
raise StackError, "ROI called %s hasn't been defined yet" % self._donorROIName
return self.counts(self._roi[self._donorROIName])
@property
def acceptor(self):
if not self._roi.has_key(self._acceptorROIName):
raise StackError, "ROI called %s hasn't been defined yet" % self._acceptorROIName
return self.counts(self._roi[self._acceptorROIName])
@property
def roi(self):
return self._roi
@classmethod
def setDefaultROI(cls, *args):
for _roi in args:
cls.defaultROI[_roi.name]=_roi
def toBackground(self,zfilter='median'):
width, height = self.width, self.height
if zfilter == 'median':
self._img = np.median( self._img, axis=0, overwrite_input=True ).reshape((1,height,width))
elif zfilter == 'mean':
self._img = np.mean( self._img, axis=0 ).reshape((1,height,width))
elif zfilter == 'min':
self._img = np.min( self._img, axis=0 ).reshape((1,height,width))
else:
raise ValueError, "Filter type can only be median, mean, or min"
return self
def addROI(self, *ROIs):
for roi in ROIs:
try:
roi = ROI.copy(roi)
key = roi.name
roi = roi.toRelative(self.origin)
if roi.right > self.width:
raise StackError(
"ROI 'right' {0} is outside right edge of image {1}: \n {2}".format(roi.right,self.width,roi)
)
if roi.top > self.height:
raise StackError, "ROI 'top' is outside top edge of image: {0}\n {1}".format(roi.top,roi)
self._roi[key] = roi
except AttributeError:
raise TypeError, "Must use objects with ROI interface"
def showROI(self,*args):
for roi in args:
self._roi[roi].draw()
def show(self, frame=None, **kwargs):
if not isinstance(frame, int) and frame is not None:
raise ValueError('First argument frame must be an integer')
self._figure = kwargs.pop('figure', self._figure)
if frame is None:
frame = next(self._frame_iter)
else:
self._frame_iter = dropwhile(lambda n: n<=frame, cycle(range(self.frames)))
self._figure.show()
self._figure.makeCurrent()
plt.title('Frame %d' % frame)
self[frame].show(**kwargs)
return frame
def setDonorROI(self, roi_name):
if not self._roi.has_key(roi_name):
raise KeyError, "Image.Stack does not have an ROI named %s" % roi_name
self._donorROIName = roi_name
return self
def setAcceptorROI(self, roi_name):
if not self._roi.has_key(roi_name):
raise KeyError, "Image.Stack does not have an ROI named %s" % roi_name
self._acceptorROIName = roi_name
return self
def counts(self, roi=None):
if roi:
if self._roi.has_key(str(roi)):
roi = self._roi[roi]
roi = roi.toRelative(self.origin)
return self[:,roi.bottom:roi.top,roi.left:roi.right].counts()
else:
return np.sum( np.sum(self._img,axis=1), axis=1 )
def attime(self,time):
if isinstance(time,slice):
start,step = None,None
exposurems = self.metadata['exposurems']
if time.start:
start = time.start/exposurems
if time.step:
step = time.step/exposurems
time = slice(start,time.stop/exposurems,step)
return self[time/exposurems]
def __getitem__(self,key):
if isinstance(key,int): # Single frame
return Frame(self._img[key], self._roi)
else: # It's a slice
temp = self.copy(deep=False)
temp._img = temp._img[key]
if isinstance(temp._img.shape,tuple) and len(temp._img.shape) > 2:
temp.frames = temp._img.shape[0]
else:
temp.frames = 1
return temp
raise IndexError, "Invalid index: %s" % str(key)
def append(self, stack):
temp = copy.copy(self)
temp._img = np.append( temp._img, stack._img, axis=0 )
return temp
def __sub__(self, stack):
return self.__add__(stack.__neg__())
def __add__(self, stack):
temp = self.copy()
if hasattr(stack,'_img'):
try:
temp._img = temp._img + stack._img
except ValueError:
raise StackError("Couldn't add images: check sizes are the same")
else:
temp._img = temp._img + stack
return temp
def __neg__(self):
temp = self.copy()
temp._img = -temp._img
return temp
def __eq__(self, other):
return np.all(self._img == other._img)
def __ne__(self, other):
return not self==other
def __repr__(self):
return "Stack %dx%dx%d" % (self.frames, self.height, self.width)
def __iter__(self):
for i in range(self.frames):
yield self[i]