예제 #1
0
 def _get(self, name, remove=False):
     varname = name
     vartype = self._var_type(varname)
     if vartype in self._mlabraw_can_convert:
         var = mlabraw.get(self._session, varname)
         if type(var) is Numeric.ArrayType:
             if self._flatten_row_vecs and Numeric.shape(var)[0] == 1:
                 var.shape = var.shape[1:2]
             elif self._flatten_col_vecs and Numeric.shape(var)[1] == 1:
                 var.shape = var.shape[0:1]
             if self._array_cast:
                 var = self._array_cast(var)
     else:
         var = None
         if self._optionally_convert.get(vartype):
             # manual conversions may fail (e.g. for multidimensional
             # cell arrays), in that case just fall back on proxying.
             try:
                 var = self._manually_convert(varname, vartype)
             except MlabConversionError: pass
         if var is None:
             # we can't convert this to a python object, so we just
             # create a proxy, and don't delete the real matlab
             # reference until the proxy is garbage collected
             var = self._make_proxy(varname)
     if remove:
         mlabraw.eval(self._session, "clear('%s');" % varname)
     return var
예제 #2
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    def matlabFindTargets(self):
        pymat.put(self.handle, 'focus', [])
        pymat.put(self.handle, 'acquisition', [])

        d, f = os.path.split(self.settings['module path'])

        if d:
            pymat.eval(self.handle, 'path(path, \'%s\')' % d)

        if not f[:-2]:
            raise RuntimeError

        pymat.eval(self.handle,
                   '[acquisition, focus] = %s(image,image_id)' % f[:-2])

        focus = pymat.get(self.handle, 'focus')
        acquisition = pymat.get(self.handle, 'acquisition')

        self.setTargets(acquisition, 'acquisition')
        self.setTargets(focus, 'focus')
        import time
        time.sleep(1)

        if self.settings['user check']:
            self.panel.foundTargets()
def runAceCorrect(imgdict,params):
        imgname = imgdict['filename']
        imgpath = os.path.join(imgdict['session']['image path'], imgname+'.mrc')

        voltage = (imgdict['scope']['high tension'])
        apix    = apDatabase.getPixelSize(imgdict)

        ctfvalues, conf = ctfdb.getBestCtfValueForImage(imgdict)

        ctdimname = imgname
        ctdimpath = os.path.join(params['rundir'],ctdimname)
        print "Corrected Image written to " + ctdimpath

        #pdb.set_trace()
        acecorrectcommand=("ctfcorrect1('%s', '%s', '%.32f', '%.32f', '%f', '%f', '%f');" % \
                (imgpath, ctdimpath, ctfvalues['defocus1'], ctfvalues['defocus2'], -ctfvalues['angle_astigmatism'], voltage, apix))
        print acecorrectcommand
        try:
                matlab = pymat.open("matlab -nosplash")
        except:
                apDisplay.environmentError()
                raise
        pymat.eval(matlab, acecorrectcommand)
        pymat.close(matlab)

        return
예제 #4
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 def __init__(self, display = False):
     import mlabraw
     if display:
         self.handle = mlabraw.open("matlab -logfile /tmp/matlablog")       
     else:
         self.handle = mlabraw.open("matlab -nodesktop -nodisplay -nojvm -logfile /tmp/matlablog")       
     mlabraw.eval(self.handle, "addpath('%s');"%os.path.join(os.path.dirname(lfd.__file__), "matlab"))
예제 #5
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 def eval_code(self, builder):
     self.builder = builder
 
     #should get a list of func names
     func_names = []
     for program in builder.project:
         print program.summary()
         #flatten tree and find Func.names
         nodes = program.flatten(False, False, False)
         for node in nodes:
             if node.cls == "Func":
                 func_names.append(node.name)
     
     #print func_names
     self.func_names = func_names
     self.called_func_names = []
     
     #check if main
     func = builder[0][1][0]
     
     if func.name == 'main':
         code_block = func[3]
     
         #evaluate, recursive function
         self._evaluate(code_block)
         mlabraw.eval(self.session, 'whos_f')
     else:
         print 'matlab have to run script file'
예제 #6
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def runAceCorrect(imgdict,params):
	imgname = imgdict['filename']
	imgpath = os.path.join(imgdict['session']['image path'], imgname+'.mrc')

	voltage = (imgdict['scope']['high tension'])
	apix    = apDatabase.getPixelSize(imgdict)

	ctfvalues = ctfdb.getBestCtfByResolution(imgdata)
	conf = ctfdb.calculateConfidenceScore(bestctfvalue)

	ctdimname = imgname
	ctdimpath = os.path.join(params['rundir'],ctdimname)
	print "Corrected Image written to " + ctdimpath

	#pdb.set_trace()
	acecorrectcommand=("ctfcorrect1('%s', '%s', '%.32f', '%.32f', '%f', '%f', '%f');" % \
		(imgpath, ctdimpath, ctfvalues['defocus1'], ctfvalues['defocus2'], -ctfvalues['angle_astigmatism'], voltage, apix))
	print acecorrectcommand
	try:
		matlab = pymat.open("matlab -nosplash")
	except:
		apDisplay.environmentError()
		raise
	pymat.eval(matlab, acecorrectcommand)
	pymat.close(matlab)

	return
예제 #7
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 def _get_part(self, to_get):
     if self._mlabwrap._var_type(to_get) in self._mlabwrap._mlabraw_can_convert:
         #!!! need assignment to TMP_VAL__ because `mlabraw.get` only works
         # with 'atomic' values like ``foo`` and not e.g. ``foo.bar``.
         mlabraw.eval(self._mlabwrap._session, "TMP_VAL__=%s" % to_get)
         return self._mlabwrap._get('TMP_VAL__', remove=True)
     return type(self)(self._mlabwrap, to_get, self)
예제 #8
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    def eval_code(self, builder):
        self.builder = builder

        #should get a list of func names
        func_names = []
        for program in builder.project:
            print program.summary()
            #flatten tree and find Func.names
            nodes = program.flatten(False, False, False)
            for node in nodes:
                if node.cls == "Func":
                    func_names.append(node.name)

        #print func_names
        self.func_names = func_names
        self.called_func_names = []

        #check if main
        func = builder[0][1][0]

        if func.name == 'main':
            code_block = func[3]

            #evaluate, recursive function
            self._evaluate(code_block)
            mlabraw.eval(self.session, 'whos_f')
        else:
            print 'matlab have to run script file'
예제 #9
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    def _get(self, name, remove=False):
        r"""Directly access a variable in matlab space.

        This should normally not be used by user code."""
        # FIXME should this really be needed in normal operation?
        if name in self._proxies: return self._proxies[name]
        varname = name
        vartype = self._var_type(varname)
        if vartype in self._mlabraw_can_convert:
            var = mlabraw.get(self._session, varname)
            if isinstance(var, ndarray):
                if self._flatten_row_vecs and numpy.shape(var)[0] == 1:
                    var.shape = var.shape[1:2]
                elif self._flatten_col_vecs and numpy.shape(var)[1] == 1:
                    var.shape = var.shape[0:1]
                if self._array_cast:
                    var = self._array_cast(var)
        else:
            var = None
            if self._dont_proxy.get(vartype):
                # manual conversions may fail (e.g. for multidimensional
                # cell arrays), in that case just fall back on proxying.
                try:
                    var = self._manually_convert(varname, vartype)
                except MlabConversionError:
                    pass
            if var is None:
                # we can't convert this to a python object, so we just
                # create a proxy, and don't delete the real matlab
                # reference until the proxy is garbage collected
                var = self._make_proxy(varname)
        if remove:
            mlabraw.eval(self._session, "clear('%s');" % varname)
        return var
예제 #10
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 def _var_type(self, varname):
     mlabraw.eval(self._session,
                  "TMP_CLS__ = class(%(x)s); if issparse(%(x)s),"
                  "TMP_CLS__ = [TMP_CLS__,'-sparse']; end;" % dict(x=varname))
     res_type = mlabraw.get(self._session, "TMP_CLS__")
     mlabraw.eval(self._session, "clear TMP_CLS__;") # unlikely to need try/finally to ensure clear
     return res_type
예제 #11
0
 def _get_values(self, varnames):
     if not varnames: raise ValueError("No varnames") #to prevent clear('')
     res = []
     for varname in varnames:
         res.append(self._get(varname))
     mlabraw.eval(self._session, "clear('%s');" % "','".join(varnames)) #FIXME wrap try/finally?
     return res
예제 #12
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    def _get(self, name, remove=False):
        r"""Directly access a variable in matlab space. 

        This should normally not be used by user code."""
        # FIXME should this really be needed in normal operation?
        if name in self._proxies: return self._proxies[name]
        varname = name
        vartype = self._var_type(varname)
        if vartype in self._mlabraw_can_convert:
            var = mlabraw.get(self._session, varname)
            if isinstance(var, ndarray):
                if var.shape:
                  if self._flatten_row_vecs and numpy.shape(var)[0] == 1:
                      var.shape = var.shape[1:2]
                  elif len(var.shape) > 1 and self._flatten_col_vecs and numpy.shape(var)[1] == 1:
                      var.shape = var.shape[0:1]
                if self._array_cast:
                    var = self._array_cast(var)
        else:
            var = None
            if self._dont_proxy.get(vartype):
                # manual conversions may fail (e.g. for multidimensional
                # cell arrays), in that case just fall back on proxying.
                try:
                    var = self._manually_convert(varname, vartype)
                except MlabConversionError: pass
            if var is None:
                # we can't convert this to a python object, so we just
                # create a proxy, and don't delete the real matlab
                # reference until the proxy is garbage collected
                var = self._make_proxy(varname)
        if remove:
            mlabraw.eval(self._session, "clear('%s');" % varname)
        return var
예제 #13
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 def _get_part(self, to_get):
     if self._mlabwrap._var_type(to_get) in self._mlabwrap._mlabraw_can_convert:
         #!!! need assignment to TMP_VAL__ because `mlabraw.get` only works
         # with 'atomic' values like ``foo`` and not e.g. ``foo.bar``.
         mlabraw.eval(self._mlabwrap._session, "TMP_VAL__=%s" % to_get)
         return self._mlabwrap._get('TMP_VAL__', remove=True)
     return type(self)(self._mlabwrap, to_get, self)
예제 #14
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def get3d(handle, name):
    mlabraw.eval(handle, """
    flat_array = %s(:);
    shape = size(%s);
    """%(name, name))
    flat_array = mlabraw.get(handle, "flat_array")
    shape = map(int, mlabraw.get(handle, "shape").flat)
    return np.ndarray(buffer = flat_array, shape = shape, order="F")
예제 #15
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 def transform_points(self, points):
     
     mlabraw.put(self.handle, "points", points)
     mlabraw.eval(self.handle,"""
     points_result = tps_eval(points, params);        
     """)
     points_result = mlabraw.get(self.handle, "points_result")
     return points_result
예제 #16
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 def _get_values(self, varnames):
     if not varnames: raise ValueError("No varnames")  #to prevent clear('')
     res = []
     for varname in varnames:
         res.append(self._get(varname))
     mlabraw.eval(self._session, "clear('%s');" %
                  "','".join(varnames))  #FIXME wrap try/finally?
     return res
예제 #17
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    def _set(self, name, value):
        r"""Directly set a variable `name` in matlab space to `value`.
        
        This should normally not be used in user code."""
        if isinstance(value, MlabObjectProxy):
            mlabraw.eval(self._session, "%s = %s;" % (name, value._name))
        else:
##             mlabraw.put(self._session, name, self._as_mlabable_type(value))
            mlabraw.put(self._session, name, value)
예제 #18
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 def _var_type(self, varname):
     mlabraw.eval(
         self._session, "TMP_CLS__ = class(%(x)s); if issparse(%(x)s),"
         "TMP_CLS__ = [TMP_CLS__,'-sparse']; end;" % dict(x=varname))
     res_type = mlabraw.get(self._session, "TMP_CLS__")
     mlabraw.eval(
         self._session,
         "clear TMP_CLS__;")  # unlikely to need try/finally to ensure clear
     return res_type
예제 #19
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    def _set(self, name, value):
        r"""Directly set a variable `name` in matlab space to `value`.

        This should normally not be used in user code."""
        if isinstance(value, MlabObjectProxy):
            mlabraw.eval(self._session, "%s = %s;" % (name, value._name))
        else:
            ##             mlabraw.put(self._session, name, self._as_mlabable_type(value))
            mlabraw.put(self._session, name, value)
예제 #20
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def branch_points(bw):
    initialize()
    mlabraw.put(MATLAB, "bw",bw)
    mlabraw.eval(MATLAB, """
    bp = bwmorph(bw,'branchpoints')
    bp_d = double(bp);
    """)
    bp_d = mlabraw.get(MATLAB, "bp_d")
    bp =  bp_d.astype('uint8')
    return bp
예제 #21
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    def _make_proxy(self, varname, parent=None, constructor=MlabObjectProxy):
        """Creates a proxy for a variable.

        XXX create and cache nested proxies also here.
        """
        proxy_val_name = "PROXY_VAL%d__" % self._proxy_count
        self._proxy_count += 1
        mlabraw.eval(self._session, "%s = %s;" % (proxy_val_name, varname))
        res = constructor(self, proxy_val_name, parent)
        self._proxies[proxy_val_name] = res
        return res
def branch_points(bw):
    initialize()
    mlabraw.put(MATLAB, "bw", bw)
    mlabraw.eval(
        MATLAB, """
    bp = bwmorph(bw,'branchpoints')
    bp_d = double(bp);
    """)
    bp_d = mlabraw.get(MATLAB, "bp_d")
    bp = bp_d.astype('uint8')
    return bp
예제 #23
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 def fit_transformation(self, points0, points1):
     assert len(points0) == len(points1)
     mlabraw.put(self.handle, "points0", points0)
     mlabraw.put(self.handle, "points1", points1)
     
     mlabraw.eval(self.handle, """
     opts = opts_fit;
     opts.reg = .01;
     params = tps_fit(points0, points1, opts);
     save('/tmp/after_fitting.mat');
     """)                
예제 #24
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    def _make_proxy(self, varname, parent=None, constructor=MlabObjectProxy):
        """Creates a proxy for a variable.

        XXX create and cache nested proxies also here.
        """
        # FIXME why not just use gensym here?
        proxy_val_name = "PROXY_VAL%d__" % self._proxy_count
        self._proxy_count += 1
        mlabraw.eval(self._session, "%s = %s;" % (proxy_val_name, varname))
        res = constructor(self, proxy_val_name, parent)
        self._proxies[proxy_val_name] = res
        return res
예제 #25
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    def _set(self, name, value):
        r"""Directly set a variable `name` in matlab space to `value`.
        
        This should normally not be used in user code."""
        if isinstance(value, MlabObjectProxy):
            mlabraw.eval(self._session, "%s = %s;" % (name, value._name))
        else:
##             mlabraw.put(self._session, name, self._as_mlabable_type(value))

            if isinstance(value, numpy.ndarray):
                value = value.copy() # XXX: mlabraw seems to badly handle strides.
            mlabraw.put(self._session, name, value)
예제 #26
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    def _var_type(self, varname):
        """Ask matlab what the type of varname is.

        :param varname: string variable
        :return: string type, e.g. ``double`` or ``char``.
        """

        mlabraw.eval(self._session,
                     "TMP_CLS__ = class(%(x)s); if issparse(%(x)s),"
                     "TMP_CLS__ = [TMP_CLS__,'-sparse']; end;" % dict(x=varname))
        res_type = mlabraw.get(self._session, "TMP_CLS__")
        mlabraw.eval(self._session, "clear TMP_CLS__;") # unlikely to need try/finally to ensure clear
        return res_type
예제 #27
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    def _var_type(self, varname):
        """Ask matlab what the type of varname is.

        :param varname: string variable
        :return: string type, e.g. ``double`` or ``char``.
        """

        mlabraw.eval(self._session,
                     "TMP_CLS__ = class(%(x)s); if issparse(%(x)s),"
                     "TMP_CLS__ = [TMP_CLS__,'-sparse']; end;" % dict(x=varname))
        res_type = mlabraw.get(self._session, "TMP_CLS__")
        mlabraw.eval(self._session, "clear TMP_CLS__;") # unlikely to need try/finally to ensure clear
        return res_type
예제 #28
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 def __setstate__(self, state):
     "Experimental unpickling support."
     global mlab  #XXX this should be dealt with correctly
     old_name = state['name']
     mlab_name = "UNPICKLED%s__" % gensym('')
     tmp_filename = None
     try:
         tmp_filename = strToTempfile(state['mlab_contents'],
                                      suffix='.mat',
                                      binary=1)
         mlabraw.eval(
             mlab._session, "TMP_UNPICKLE_STRUCT__ = load('%s', '%s');" %
             (tmp_filename, old_name))
         mlabraw.eval(
             mlab._session,
             "%s = TMP_UNPICKLE_STRUCT__.%s;" % (mlab_name, old_name))
         mlabraw.eval(mlab._session, "clear TMP_UNPICKLE_STRUCT__;")
         # XXX
         mlab._make_proxy(
             mlab_name,
             constructor=lambda *args: self.__init__(*args) or self)
         mlabraw.eval(mlab._session, 'clear %s;' % mlab_name)
     finally:
         if tmp_filename and os.path.exists(tmp_filename):
             os.remove(tmp_filename)
예제 #29
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    def transform_poses(self, points, rots):
        mlabraw.put(self.handle, "points", points)                
        put3d(self.handle, "rots", rots)
        
        mlabraw.eval(self.handle,"""
        [points_result, rots_result] = tps_eval_frames(points, rots, params);
        """)
        points_result = mlabraw.get(self.handle,"points_result")
        rots_result = get3d(self.handle, "rots_result")
        
        return points_result, rots_result


        
def setScopeParams(matlab,params):
        tempdir = params['tempdir']+"/"
        if os.path.isdir(tempdir):
                plist = (params['kv'],params['cs'],params['apix'],tempdir)
                acecmd1 = makeMatlabCmd("setscopeparams(",");",plist)
                pymat.eval(matlab,acecmd1)

                plist = (params['kv'],params['cs'],params['apix'])
                acecmd2 = makeMatlabCmd("scopeparams = [","];",plist)
                pymat.eval(matlab,acecmd2)

        else:
                apDisplay.printError("Temp directory, '"+params['tempdir']+"' not present.")
        return
예제 #31
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def setScopeParams(matlab,params):
	tempdir = params['tempdir']+"/"
	if os.path.isdir(tempdir):
		plist = (params['kv'],params['cs'],params['apix'],tempdir)
		acecmd1 = makeMatlabCmd("setscopeparams(",");",plist)
		pymat.eval(matlab,acecmd1)

		plist = (params['kv'],params['cs'],params['apix'])
		acecmd2 = makeMatlabCmd("scopeparams = [","];",plist)
		pymat.eval(matlab,acecmd2)

	else:
		apDisplay.printError("Temp directory, '"+params['tempdir']+"' not present.")
	return
예제 #32
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    def onRunParamGUI(self, evt):
        # added for GUI parametrization:

        self.handle = pymat.open()

        d, f = os.path.split(self.widgets["parametergui path"].GetValue())  # self.settings['parametergui path'])

        if d:
            pymat.eval(self.handle, "path(path, '%s')" % d)

        if not f[:-2]:
            raise RuntimeError

        pymat.eval(self.handle, "%s" % f[:-2])
    def onRunParamGUI(self, evt):
        # added for GUI parametrization:

        self.handle = pymat.open()

        d, f = os.path.split(self.widgets['parametergui path'].GetValue()
                             )  #self.settings['parametergui path'])

        if d:
            pymat.eval(self.handle, 'path(path, \'%s\')' % d)

        if not f[:-2]:
            raise RuntimeError

        pymat.eval(self.handle, '%s' % f[:-2])
예제 #34
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    def testRawMlabraw(self):
        """A few explicit tests for mlabraw"""
        import mlabraw
        #print "test mlabraw"
        self.assertRaises(TypeError, mlabraw.put, 33, 'a', 1)
        self.assertRaises(TypeError, mlabraw.get, object(), 'a')
        self.assertRaises(TypeError, mlabraw.eval, object(), '1')

        # -100 is picked kinda arbitrarily to account for internal "overhead";
        # I don't want to hardcode the exact value; users can assume 1000
        # chars is safe
        mlabraw.eval(mlab._session, '1' * (BUFSIZE - 100))
        assert numpy.inf == mlabraw.get(mlab._session, 'ans');
        # test for buffer overflow detection
        self.assertRaises(Exception, mlabraw.eval, mlab._session, '1' * BUFSIZE)
예제 #35
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    def test_mlab_raw_eval(self):
        """Test evaluating strings in mlabraw module.

        N.B. This is currently known to fail.

        It appears that doing
        mlabraw.eval(mlab._session, r"'x'")
        does not return the string 'x' as exected.
        """

        import mlabraw
        self.assertEqual(mlabraw.eval(mlab._session, r"fprintf('1\n')"), '1\n')
        try:
            self.assertEqual(mlabraw.eval(mlab._session, r"1"), '')
        finally:
            mlabraw.eval(mlab._session, 'clear ans')
예제 #36
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 def fit_transformation_icp(self, points0, points1):
     mlabraw.put(self.handle, "points0", points0)
     mlabraw.put(self.handle, "points1", points1)
     
     mlabraw.eval(self.handle, """
     opts = opts_icp;
     opts.n_iter=6;
     opts.lines_from_orig=1;
     opts.corr_opts.method='bipartite';
     opts.fit_opts.reg = .01;
     %opts.plot_grid = 1;
     opts.corr_opts.bipartite_opts.deficient_col_penalty=1;
     opts.corr_opts.bipartite_opts.deficient_row_penalty=1;
     params = tps_rpm(points0, points1, opts);
     save('/tmp/after_fitting.mat');
     """)
예제 #37
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 def _get_cell(self, varname):
     # XXX can currently only handle 1D
     mlabraw.eval(self._session,
                "TMP_SIZE_INFO__ = \
                [min(size(%(vn)s)) == 1 & ndims(%(vn)s) == 2, \
                max(size(%(vn)s))];" % {'vn':varname})
     is_rank1, cell_len = self._get("TMP_SIZE_INFO__", remove=True).flat
     if is_rank1:
         cell_bits = (["TMP%i%s__" % (i, gensym('_'))
                        for i in range(cell_len)])
         mlabraw.eval(self._session, '[%s] = deal(%s{:});' %
                    (",".join(cell_bits), varname))
         # !!! this recursive call means we have to take care with
         # overwriting temps!!!
         return self._get_values(cell_bits)
     else:
         raise MlabConversionError("Not a 1D cell array")
예제 #38
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def runAceDrift(matlab,imgdict,params):
	imgname = imgdict['filename']
	imgpath = os.path.join(imgdict['session']['image path'], imgname+'.mrc')

	if params['nominal']:
		nominal=params['nominal']
	else:
		nominal=imgdict['scope']['defocus']

	#pdb.set_trace()
	acecommand=("measureAnisotropy('%s','%s',%d,'%s',%e,'%s','%s','%s', '%s');" % \
		( imgpath, params['outtextfile'], params['display'],\
		params['medium'], -nominal, params['tempdir']+"/", params['opimagedir'], params['matdir'], imgname))

	#~ acecommand=("mnUpCut = measureDrift('%s','%s',%d,%d,'%s',%e,'%s');" % \
		#~ ( imgpath, params['outtextfile'], params['display'], params['stig'],\
		#~ params['medium'], -nominal, params['tempdir']))

	pymat.eval(matlab,acecommand)
예제 #39
0
def remove_holes(labels,min_size):
    initialize()
    mlabraw.put(MATLAB, "L",labels)
    mlabraw.put(MATLAB, "min_size",min_size)
    mlabraw.eval(MATLAB, """
    max_label = max(L(:));
    good_pix = L==0;
    for label = 1:max_label
        good_pix = good_pix | bwareaopen(L==label,min_size,4);    
    end
    bad_pix = ~logical(good_pix);
    
    [~,I] = bwdist(good_pix,'Chessboard');
    NewL = L;
    NewL(bad_pix) = L(I(bad_pix));
    NewL_d = double(NewL);
    """)
    NewL_d = mlabraw.get(MATLAB, "NewL_d")
    return NewL_d.astype('uint8')
def runAceDrift(matlab,imgdict,params):
        imgname = imgdict['filename']
        imgpath = os.path.join(imgdict['session']['image path'], imgname+'.mrc')

        if params['nominal']:
                nominal=params['nominal']
        else:
                nominal=imgdict['scope']['defocus']

        #pdb.set_trace()
        acecommand=("measureAnisotropy('%s','%s',%d,'%s',%e,'%s','%s','%s', '%s');" % \
                ( imgpath, params['outtextfile'], params['display'],\
                params['medium'], -nominal, params['tempdir']+"/", params['opimagedir'], params['matdir'], imgname))

        #~ acecommand=("mnUpCut = measureDrift('%s','%s',%d,%d,'%s',%e,'%s');" % \
                #~ ( imgpath, params['outtextfile'], params['display'], params['stig'],\
                #~ params['medium'], -nominal, params['tempdir']))

        pymat.eval(matlab,acecommand)
def remove_holes(labels, min_size):
    initialize()
    mlabraw.put(MATLAB, "L", labels)
    mlabraw.put(MATLAB, "min_size", min_size)
    mlabraw.eval(
        MATLAB, """
    max_label = max(L(:));
    good_pix = L==0;
    for label = 1:max_label
        good_pix = good_pix | bwareaopen(L==label,min_size,4);    
    end
    bad_pix = ~logical(good_pix);
    
    [~,I] = bwdist(good_pix,'Chessboard');
    NewL = L;
    NewL(bad_pix) = L(I(bad_pix));
    NewL_d = double(NewL);
    """)
    NewL_d = mlabraw.get(MATLAB, "NewL_d")
    return NewL_d.astype('uint8')
예제 #42
0
 def _get_cell(self, varname):
     # XXX can currently only handle ``{}`` and 1D cells
     mlabraw.eval(self._session,
                "TMP_SIZE_INFO__ = \
                [all(size(%(vn)s) == 0), \
                 min(size(%(vn)s)) == 1 & ndims(%(vn)s) == 2, \
                 max(size(%(vn)s))];" % {'vn':varname})
     is_empty, is_rank1, cell_len = map(int,
                                        self._get("TMP_SIZE_INFO__", remove=True).flat)
     if is_empty:
         return []
     elif is_rank1:
         cell_bits = (["TMP%i%s__" % (i, gensym('_'))
                        for i in range(cell_len)])
         mlabraw.eval(self._session, '[%s] = deal(%s{:});' %
                    (",".join(cell_bits), varname))
         # !!! this recursive call means we have to take care with
         # overwriting temps!!!
         return self._get_values(cell_bits)
     else:
         raise MlabConversionError("Not a 1D cell array")
예제 #43
0
 def _get_cell(self, varname):
     # XXX can currently only handle ``{}`` and 1D cells
     mlabraw.eval(self._session,
                "TMP_SIZE_INFO__ = \
                [all(size(%(vn)s) == 0), \
                 min(size(%(vn)s)) == 1 & ndims(%(vn)s) == 2, \
                 max(size(%(vn)s))];" % {'vn':varname})
     is_empty, is_rank1, cell_len = map(int,
                                        self._get("TMP_SIZE_INFO__", remove=True).flat)
     if is_empty:
         return []
     elif is_rank1:
         cell_bits = (["TMP%i__" % (self.proxy_count+i)
                        for i in range(cell_len)])
         self._proxy_count += cell_len
         mlabraw.eval(self._session, '[%s] = deal(%s{:});' %
                    (",".join(cell_bits), varname))
         # !!! this recursive call means we have to take care with
         # overwriting temps!!!
         return self._get_values(cell_bits)
     else:
         raise MlabConversionError("Not a 1D cell array")
예제 #44
0
 def _set_part(self, to_set, value):
     #FIXME s.a.
     if isinstance(value, MlabObjectProxy):
         mlabraw.eval(self._mlabwrap._session, "%s = %s;" % (to_set, value._name))
     else:
         self._mlabwrap._set("TMP_VAL__", value)
         mlabraw.eval(self._mlabwrap._session, "%s = TMP_VAL__;" % to_set)
         mlabraw.eval(self._mlabwrap._session, 'clear TMP_VAL__;')
예제 #45
0
 def _set_part(self, to_set, value):
     #FIXME s.a.
     if isinstance(value, MlabObjectProxy):
         mlabraw.eval(self._mlabwrap._session, "%s = %s;" % (to_set, value._name))
     else:
         self._mlabwrap._set("TMP_VAL__", value)
         mlabraw.eval(self._mlabwrap._session, "%s = TMP_VAL__;" % to_set)
         mlabraw.eval(self._mlabwrap._session, 'clear TMP_VAL__;')
        def matlabFindTargets(self):
                pymat.put(self.handle, 'focus', [])
                pymat.put(self.handle, 'acquisition', [])

                d, f = os.path.split(self.settings['module path'])

                if d:
                        pymat.eval(self.handle, 'path(path, \'%s\')' % d)

                if not f[:-2]:
                        raise RuntimeError

                pymat.eval(self.handle, '[acquisition, focus] = %s(image,image_id)' % f[:-2])

                focus = pymat.get(self.handle, 'focus')
                acquisition = pymat.get(self.handle, 'acquisition')

                self.setTargets(acquisition, 'acquisition')
                self.setTargets(focus, 'focus')
                import time
                time.sleep(1)

                if self.settings['user check']:
                        self.panel.foundTargets()
예제 #47
0
 def __setstate__(self, state):
     "Experimental unpickling support."
     global mlab         #XXX this should be dealt with correctly
     old_name = state['name']
     mlab_name = "UNPICKLED%s__" % gensym('')
     try:
         tmp_filename = tempfile.mktemp('.mat')
         spitOut(state['mlab_contents'], tmp_filename, binary=1)
         mlabraw.eval(mlab._session,
                    "TMP_UNPICKLE_STRUCT__ = load('%s', '%s');" % (
             tmp_filename, old_name))
         mlabraw.eval(mlab._session,
                    "%s = TMP_UNPICKLE_STRUCT__.%s;" % (mlab_name, old_name))
         mlabraw.eval(mlab._session, "clear TMP_UNPICKLE_STRUCT__;")
         # XXX
         mlab._make_proxy(mlab_name, constructor=lambda *args: self.__init__(*args) or self)
         mlabraw.eval(mlab._session, 'clear %s;' % mlab_name)
     finally:
         if os.path.exists(tmp_filename): os.remove(tmp_filename)
예제 #48
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    def testRawMlabraw(self):
        """A few explicit tests for mlabraw"""
        import mlabraw
        #print "test mlabraw"
        self.assertRaises(TypeError, mlabraw.put, 33, 'a', 1)
        self.assertRaises(TypeError, mlabraw.get, object(), 'a')
        self.assertRaises(TypeError, mlabraw.eval, object(), '1')

        # -100 is picked kinda arbitrarily to account for internal "overhead";
        # I don't want to hardcode the exact value; users can assume 1000
        # chars is safe
        mlabraw.eval(mlab._session, '1' * (BUFSIZE - 100))
        assert numpy.inf == mlabraw.get(mlab._session, 'ans')
        # test for buffer overflow detection
        self.assertRaises(Exception, mlabraw.eval, mlab._session,
                          '1' * BUFSIZE)
        self.assertEqual(mlabraw.eval(mlab._session, r"fprintf('1\n')"), '1\n')
        try:
            self.assertEqual(mlabraw.eval(mlab._session, r"1"), '')
        finally:
            mlabraw.eval(mlab._session, 'clear ans')
예제 #49
0
 def __del__(self):
     if self._parent is None:
         mlabraw.eval(self._mlabwrap._session, 'clear %s;' % self._name)
def evaluate(string):
    mlabraw.eval(MATLAB, string)
예제 #51
0
    def _execute(self):

        batch_size = self.batch_size
        pooling_region_counts = self.pooling_region_counts
        dataset_family = self.dataset_family
        which_set = self.which_set
        size = self.size

        nan = 0


        dataset_descriptor = dataset_family[which_set][size]

        dataset = dataset_descriptor.dataset_maker()
        expected_num_examples = dataset_descriptor.num_examples

        full_X = dataset.get_design_matrix()
        num_examples = full_X.shape[0]
        assert num_examples == expected_num_examples

        if self.restrict is not None:
            assert self.restrict[1]  <= full_X.shape[0]

            print 'restricting to examples ',self.restrict[0],' through ',self.restrict[1],' exclusive'
            full_X = full_X[self.restrict[0]:self.restrict[1],:]

            assert self.restrict[1] > self.restrict[0]

        #update for after restriction
        num_examples = full_X.shape[0]

        assert num_examples > 0

        dataset.X = None
        dataset.design_loc = None
        dataset.compress = False

        patchifier = ExtractGridPatches( patch_shape = (size,size), patch_stride = (1,1) )

        pipeline = serial.load(dataset_descriptor.pipeline_path)

        assert isinstance(pipeline.items[0], ExtractPatches)
        pipeline.items[0] = patchifier


        print 'defining features'
        Z = T.matrix('Z')

        if self.one_sided:
            feat = abs(Z)
        else:
            pos = T.clip(Z,0.,1e30)
            neg = T.clip(-Z,0.,1e30)

            feat = T.concatenate((pos, neg), axis=1)

        print 'compiling theano function'
        f = function([Z],feat)

        nfeat = self.W.shape[1] * (2 - self.one_sided)
        if not (nfeat == 1600 or nfeat == 3200):
            print nfeat
            assert False

        if config.device.startswith('gpu') and nfeat >= 4000:
            f = halver(f, nfeat)

        topo_feat_var = T.TensorType(broadcastable = (False,False,False,False), dtype='float32')()
        region_features = function([topo_feat_var],
                topo_feat_var.mean(axis=(1,2)) )

        def average_pool( stride ):
            def point( p ):
                return p * ns / stride

            rval = np.zeros( (topo_feat.shape[0], stride, stride, topo_feat.shape[3] ) , dtype = 'float32')

            for i in xrange(stride):
                for j in xrange(stride):
                    rval[:,i,j,:] = region_features( topo_feat[:,point(i):point(i+1), point(j):point(j+1),:] )

            return rval

        outputs = [ np.zeros((num_examples,count,count,nfeat),dtype='float32') for count in pooling_region_counts ]

        assert len(outputs) > 0

        fd = DenseDesignMatrix(X = np.zeros((1,1),dtype='float32'), view_converter = DefaultViewConverter([1, 1, nfeat] ) )

        ns = 32 - size + 1
        depatchifier = ReassembleGridPatches( orig_shape  = (ns, ns), patch_shape=(1,1) )

        if len(range(0,num_examples-batch_size+1,batch_size)) <= 0:
            print num_examples
            print batch_size

        for i in xrange(0,num_examples-batch_size+1,batch_size):
            print i
            t1 = time.time()

            d = copy.copy(dataset)
            d.set_design_matrix(full_X[i:i+batch_size,:])

            t2 = time.time()

            #print '\tapplying preprocessor'
            d.apply_preprocessor(pipeline, can_fit = False)
            X2 = d.get_design_matrix()

            t3 = time.time()

            M.put(s,'batch',X2)

            M.eval(s, 'Z = sparse_codes(batch, dictionary, lambda)')
            Z = M.get(s, 'Z')

            feat = f(np.cast['float32'](Z))

            t4 = time.time()

            assert feat.dtype == 'float32'

            feat_dataset = copy.copy(fd)

            if np.any(np.isnan(feat)):
                nan += np.isnan(feat).sum()
                feat[np.isnan(feat)] = 0

            feat_dataset.set_design_matrix(feat)

            #print '\treassembling features'
            feat_dataset.apply_preprocessor(depatchifier)

            #print '\tmaking topological view'
            topo_feat = feat_dataset.get_topological_view()
            assert topo_feat.shape[0] == batch_size

            t5 = time.time()

            #average pooling
            for output, count in zip(outputs, pooling_region_counts):
                output[i:i+batch_size,...] = average_pool(count)

            t6 = time.time()

            print (t6-t1, t2-t1, t3-t2, t4-t3, t5-t4, t6-t5)

        for output, save_path in zip(outputs, self.save_paths):
            if self.chunk_size is not None:
                assert save_path.endswith('.npy')
                save_path_pieces = save_path.split('.npy')
                assert len(save_path_pieces) == 2
                assert save_path_pieces[1] == ''
                save_path = save_path_pieces[0] + '_' + chr(ord('A')+self.chunk_id)+'.npy'
            np.save(save_path,output)


        if nan > 0:
            warnings.warn(str(nan)+' features were nan')
예제 #52
0
    def _do(self, cmd, *args, **kwargs):
        """Semi-raw execution of a matlab command.

        Smartly handle calls to matlab, figure out what to do with `args`,
        and when to use function call syntax and not.

        If no `args` are specified, the ``cmd`` not ``result = cmd()`` form is
        used in Matlab -- this also makes literal Matlab commands legal
        (eg. cmd=``get(gca, 'Children')``).

        If ``nout=0`` is specified, the Matlab command is executed as
        procedure, otherwise it is executed as function (default), nout
        specifying how many values should be returned (default 1).

        **Beware that if you use don't specify ``nout=0`` for a `cmd` that
        never returns a value will raise an error** (because assigning a
        variable to a call that doesn't return a value is illegal in matlab).


        ``cast`` specifies which typecast should be applied to the result
        (e.g. `int`), it defaults to none.

        XXX: should we add ``parens`` parameter?
        """
        handle_out = kwargs.get('handle_out', _flush_write_stdout)
        #self._session = self._session or mlabraw.open()
        # HACK
        if self._autosync_dirs:
            mlabraw.eval(self._session,
                         "cd('%s');" % os.getcwd().replace("'", "''"))
        nout = kwargs.get('nout', 1)
        #XXX what to do with matlab screen output
        argnames = []
        tempargs = []
        try:
            for count, arg in enumerate(args):
                if isinstance(arg, MlabObjectProxy):
                    argnames.append(arg._name)
                else:
                    nextName = 'arg%d__' % count
                    argnames.append(nextName)
                    tempargs.append(nextName)
                    # have to convert these by hand
                    ##                 try:
                    ##                     arg = self._as_mlabable_type(arg)
                    ##                 except TypeError:
                    ##                     raise TypeError("Illegal argument type (%s.:) for %d. argument" %
                    ##                                     (type(arg), type(count)))
                    mlabraw.put(self._session, argnames[-1], arg)

            if args:
                cmd = "%s(%s)%s" % (cmd, ", ".join(argnames),
                                    ('', ';')[kwargs.get('show', 0)])
            # got three cases for nout:
            # 0 -> None, 1 -> val, >1 -> [val1, val2, ...]
            if nout == 0:
                handle_out(mlabraw.eval(self._session, cmd))
                return
            # deal with matlab-style multiple value return
            resSL = ((["RES%d__" % i for i in range(nout)]))
            handle_out(
                mlabraw.eval(self._session,
                             '[%s]=%s;' % (", ".join(resSL), cmd)))
            res = self._get_values(resSL)

            if nout == 1: res = res[0]
            else: res = tuple(res)
            if kwargs.has_key('cast'):
                if nout == 0: raise TypeError("Can't cast: 0 nout")
                return kwargs['cast'](res)
            else:
                return res
        finally:
            if len(tempargs) and self._clear_call_args:
                mlabraw.eval(self._session,
                             "clear('%s');" % "','".join(tempargs))
예제 #53
0
    def _do(self, cmd, *args, **kwargs):
        """Semi-raw execution of a matlab command.

        Smartly handle calls to matlab, figure out what to do with `args`,
        and when to use function call syntax and not.

        If no `args` are specified, the ``cmd`` not ``result = cmd()`` form is
        used in Matlab -- this also makes literal Matlab commands legal
        (eg. cmd=``get(gca, 'Children')``).

        If ``nout=0`` is specified, the Matlab command is executed as
        procedure, otherwise it is executed as function (default), nout
        specifying how many values should be returned (default 1).

        **Beware that if you use don't specify ``nout=0`` for a `cmd` that
        never returns a value will raise an error** (because assigning a
        variable to a call that doesn't return a value is illegal in matlab).


        ``cast`` specifies which typecast should be applied to the result
        (e.g. `int`), it defaults to none.

        XXX: should we add ``parens`` parameter?
        """
        handle_out = kwargs.get('handle_out', _flush_write_stdout)
        #self._session = self._session or mlabraw.open()
        # HACK
        if self._autosync_dirs:
            mlabraw.eval(self._session,  "cd('%s');" % os.getcwd().replace("'", "''"))
        nout =  kwargs.get('nout', 1)
        #XXX what to do with matlab screen output
        argnames = []
        tempargs = []
        try:
            for count, arg in enumerate(args):
                if isinstance(arg, MlabObjectProxy):
                    argnames.append(arg._name)
                else:
                    nextName = 'arg%d__' % count
                    argnames.append(nextName)
                    tempargs.append(nextName)
                    # have to convert these by hand
    ##                 try:
    ##                     arg = self._as_mlabable_type(arg)
    ##                 except TypeError:
    ##                     raise TypeError("Illegal argument type (%s.:) for %d. argument" %
    ##                                     (type(arg), type(count)))
                    mlabraw.put(self._session,  argnames[-1], arg)

            if args:
                cmd = "%s(%s)%s" % (cmd, ", ".join(argnames),
                                    ('',';')[kwargs.get('show',0)])
            # got three cases for nout:
            # 0 -> None, 1 -> val, >1 -> [val1, val2, ...]
            if nout == 0:
                handle_out(mlabraw.eval(self._session, cmd))
                return
            # deal with matlab-style multiple value return
            resSL = ((["RES%d__" % i for i in range(nout)]))
            handle_out(mlabraw.eval(self._session, '[%s]=%s;' % (", ".join(resSL), cmd)))
            res = self._get_values(resSL)

            if nout == 1: res = res[0]
            else:         res = tuple(res)
            if kwargs.has_key('cast'):
                if nout == 0: raise TypeError("Can't cast: 0 nout")
                return kwargs['cast'](res)
            else:
                return res
        finally:
            if len(tempargs) and self._clear_call_args:
                mlabraw.eval(self._session, "clear('%s');" %
                             "','".join(tempargs))
예제 #54
0
def setAceConfig(matlab,params):
	tempdir=params['tempdir']+"/"
	if os.path.isdir(tempdir):
		pymat.eval(matlab, "edgethcarbon="+str(params['edgethcarbon'])+";")
		pymat.eval(matlab, "edgethice="+str(params['edgethice'])+";")
		pymat.eval(matlab, "pfcarbon="+str(params['pfcarbon'])+";")
		pymat.eval(matlab, "pfice="+str(params['pfice'])+";")
		pymat.eval(matlab, "overlap="+str(params['overlap'])+";")
		pymat.eval(matlab, "fieldsize="+str(params['fieldsize'])+";")
		pymat.eval(matlab, "resamplefr="+str(params['resamplefr'])+";")
		pymat.eval(matlab, "drange="+str(params['drange'])+";")

		aceconfig=os.path.join(tempdir,"aceconfig.mat")
		acecmd = "save('"+aceconfig+"','edgethcarbon','edgethice','pfcarbon','pfice',"+\
			"'overlap','fieldsize','resamplefr','drange');"
		pymat.eval(matlab, acecmd)
	else:
		apDisplay.printError("Temp directory, '"+tempdir+"' not present.")
	return
예제 #55
0
def runAce(matlab, imgdata, params, showprev=True):
	imgname = imgdata['filename']

	if showprev is True:
		bestctfvalue = ctfdb.getBestCtfByResolution(imgdata)
		if bestctfvalue:
			bestconf = ctfdb.calculateConfidenceScore(bestctfvalue)
			print ( "Prev best: '"+bestctfvalue['acerun']['name']+"', conf="+
				apDisplay.colorProb(bestconf)+", defocus="+str(round(-1.0*abs(bestctfvalue['defocus1']*1.0e6),2))+
				" microns" )

	if params['uncorrected']:
		tmpname='temporaryCorrectedImage.mrc'
		imgarray = apDBImage.correctImage(imgdata)
		imgpath = os.path.join(params['rundir'],tmpname)
		apImage.arrayToMrc(imgarray, imgpath)
		print "processing", imgpath
	else:
		imgpath = os.path.join(imgdata['session']['image path'], imgname+'.mrc')

	nominal = None
	if params['nominal'] is not None:
		nominal=params['nominal']
	elif params['newnominal'] is True:
		bestctfvalue = ctfdb.getBestCtfByResolution(imgdata)
		nominal = bestctfvalue['defocus1']
	if nominal is None:
		nominal = imgdata['scope']['defocus']

	if nominal is None or nominal > 0 or nominal < -15e-6:
			apDisplay.printWarning("Nominal should be of the form nominal=-1.2e-6"+\
				" for -1.2 microns NOT:"+str(nominal))

	#Neil's Hack
	#if 'autosample' in params and params['autosample']:
	#	x = abs(nominal*1.0e6)
	#	val = 1.585 + 0.057587 * x - 0.044106 * x**2 + 0.010877 * x**3
	#	resamplefr_override = round(val,3)
	#	print "resamplefr_override=",resamplefr_override
	#	pymat.eval(matlab, "resamplefr="+str(resamplefr_override)+";")

	pymat.eval(matlab,("dforig = %e;" % nominal))

	if params['stig'] == 0:
		plist = (imgpath, params['outtextfile'], params['display'], params['stig'],\
			params['medium'], -nominal, params['tempdir']+"/")
		acecmd = makeMatlabCmd("ctfparams = ace(",");",plist)
	else:
		plist = (imgname, imgpath, params['outtextfile'], params['opimagedir'], \
			params['matdir'], params['display'], params['stig'],\
			params['medium'], -nominal, params['tempdir']+"/", params['resamplefr'])
		acecmd = makeMatlabCmd("ctfparams = measureAstigmatism(",");",plist)

	#print acecmd
	pymat.eval(matlab,acecmd)

	matfile = os.path.join(params['matdir'], imgname+".mrc.mat")
	if params['stig']==0:
		savematcmd = "save('"+matfile+"','ctfparams','scopeparams', 'dforig');"
		pymat.eval(matlab,savematcmd)

	ctfvalue = pymat.get(matlab, 'ctfparams')
	ctfvalue=ctfvalue[0]

	printResults(params, nominal, ctfvalue)

	return ctfvalue
예제 #56
0
from theano import tensor as T
#from theano.sandbox.neighbours import images2neibs
from theano import function
from pylearn2.datasets.preprocessing import ExtractPatches, ExtractGridPatches, ReassembleGridPatches
from pylearn2.utils import serial
from pylearn2.datasets.dense_design_matrix import DenseDesignMatrix, DefaultViewConverter
from pylearn2.datasets.cifar10 import CIFAR10
from pylearn2.datasets.cifar100 import CIFAR100
from pylearn2.datasets.tl_challenge import TL_Challenge
import sys
config.floatX = 'float32'
from mlabwrap import mlab
s = mlab._session
import mlabraw as M

M.eval(s, "addpath('/u/goodfeli/SPAMS/release/atlas64')")
M.eval(s, "addpath('/u/goodfeli/galatea/s3c/sc_vq_demo')")

class halver:
    def __init__(self,f,nhid):
        self.f = f
        self.nhid = nhid

    def __call__(self,X):
        m = X.shape[0]
        #mid = m/2
        m1 = m/3
        m2 = 2*m/3

        rval = np.zeros((m,self.nhid),dtype='float32')
        rval[0:m1,:] = self.f(X[0:m1,:])
예제 #57
0
    def _evaluate(self, code_block):
        #eval line by line in code_block
        for node in code_block:
            func_nodes = []
            #multiline code -> for, while, if, case
            #if statement

            #one line code
            if node.cls in ('Assign', 'Assigns', 'Statement'):
                #flatten the node, check for function: Var/Get unknown type name
                sub_nodes = node.flatten(False, False, False)

                #check if Var/Get unknown type name -> self written function
                for sub_node in sub_nodes:
                    if ((sub_node.cls == 'Get' or sub_node.cls == 'Var') and \
                        sub_node.backend == 'unknown' and \
                        sub_node.type == 'TYPE' and \
                        sub_node.name in self.func_names):

                        #Test if function processed before
                        if sub_node.name not in self.called_func_names:
                            func_nodes.append(sub_node)
                            self.called_func_names.append(sub_node.name)

                #loop over func_nodes
                for func_node in func_nodes:
                    #print func_node.name
                    params = []
                    function = False

                    #save and store variables, if entered function
                    # node.func.name is name of caller function
                    mlabraw.eval(self.session,
                                 'save mconvert_' + code_block.func.name)

                    #clear variables, set params, Get function have params
                    mlabraw.eval(self.session, 'clear all')

                    #find function node that is called
                    #check current file for function -> code_block
                    funcs = code_block.func.parent  #funcs
                    for func in funcs:
                        if func_node.name == func.name:
                            new_code_block = func[3]
                            function = True

                    #check other file for function -> code_block
                    if not function:
                        for program in node.project:
                            func = program[1][0]
                            if func_node.name == func.name:
                                params = func[2]
                                new_code_block = func[3]
                                function = True

                    #set params
                    for var, param in zip(func_node, params):
                        my_string = "load (\'mconvert_" + code_block.func.name + "\', \'" + var.name + "\')"
                        mlabraw.eval(self.session, my_string)

                        mlabraw.eval(self.session,
                                     param.name + ' = ' + var.name)

                        if var.name != param.name:
                            mlabraw.eval(self.session, 'clear ' + var.name)

                    #jump into code_block of the function
                    self._evaluate(new_code_block)

                    mlabraw.eval(self.session, 'whos_f')
                    #load previous variables
                    mlabraw.eval(self.session, 'clear all')
                    mlabraw.eval(self.session,
                                 'load mconvert_' + code_block.func.name)

            #eval code line
            mlabraw.eval(self.session, node.code)