def createQEAxes(DataSet=None,axis=0,figure = None, projectionVector1 = None, projectionVector2 = None):
"""Function to create Q E plot
Kwargs:
- DataSet (DataSet): If provided and no projections vectors creates QE axis for main direction (default None)
- axis (int): Whether to create axis 0 or 1 (projection vector 0 or orthogonal to this, default 0)
- figure (figure): If provided, this is used to create the axis within (default None)
- projectionVector1 (vec): Projection vector along which data is plotted. If not provided sample vector is used (default None)
- projectionVector2 (vec): Projection vector orthogonal to data. If not provided sample vector is used (default None)
"""
if projectionVector1 is None or projectionVector2 is None:
v1 = DataSet.sample[0].projectionVector1
v2 = DataSet.sample[0].projectionVector2
angle = DataSet.sample[0].projectionAngle
orientationMatrix = DataSet.sample[0].orientationMatrix
else:
v1 = np.array(projectionVector1)
v2 = np.array(projectionVector2)
if not np.all([x.shape==(3,) for x in [v1,v2]]) or not np.all([len(x.shape)==1 for x in [v1,v2]]):
raise AttributeError('Provided vector(s) is not 3D: projectionVector1.shape={} or projectionVector2.shape={}'.format(v1.shape,v2.shape))
angle = np.arccos(np.dot(v1,v2)/(np.linalg.norm(v1)*np.linalg.norm(v2)))
orientationMatrix = np.ones(3)
sample = copy.deepcopy(DataSet.sample)
v1,v2 = sample[0].projectionVector1,sample[0].projectionVector2
angle = np.sign(np.dot(np.cross(v1,v2),sample[0].planeNormal))*sample[0].projectionAngle
v2Length = np.linalg.norm(v2)/np.linalg.norm(v1)
projectionMatrix = np.linalg.inv(np.array([[1,0],[np.cos(angle)*v2Length,np.sin(angle)*v2Length]]).T)
projectionVectorQX = np.dot(np.dot(projectionMatrix,[1,0]),np.array([v1,v2]))
projectionVectorQY = np.dot(np.dot(projectionMatrix,[0,1]),np.array([v1,v2]))
projectionVectorQX = _tools.LengthOrder(projectionVectorQX)
projectionVectorQY = _tools.LengthOrder(projectionVectorQY)
projectionVectorQXLength = np.linalg.norm(np.dot(orientationMatrix,projectionVectorQY))
projectionVectorQYLength = np.linalg.norm(np.dot(orientationMatrix,projectionVectorQX))
projectionVectorQXFormated = ', '.join(['{:.3f}'.format(x) for x in projectionVectorQX])
projectionVectorQYFormated = ', '.join(['{:.3f}'.format(x) for x in projectionVectorQY])
if axis == 0:
projectionVectorLength = projectionVectorQYLength
projectionVectorLengthORthogonal = projectionVectorQXLength
projectionVectorFormated = projectionVectorQXFormated
projectionVector = projectionVectorQX
projectionVectorOrthogonal = projectionVectorQY
elif axis == 1:
projectionVectorLength = projectionVectorQXLength
projectionVectorFormated = projectionVectorQYFormated
projectionVectorLengthORthogonal = projectionVectorQYLength
projectionVector = projectionVectorQY
projectionVectorOrthogonal = projectionVectorQX
else:
raise AttributeError('Provided axis of {} is not allowed. Should be either 0 or 1.'.format(axis))
if figure is None:
figure = plt.figure(figsize=(7, 4))
else:
figure.clf()
def inv_tr(l,x,y):
return x*l,y
def tr(l,x,y):
return x/l,y
if pythonVersion == 3:
grid_locator1 = MultipleLocator(base=1.0) # Standard X ticks is multiple locator
grid_helper = GridHelperCurveLinear((lambda x,y:inv_tr(projectionVectorLength,x,y),
lambda x,y:tr(projectionVectorLength,x,y)),grid_locator1=grid_locator1)
else:
grid_helper = GridHelperCurveLinear((lambda x,y:inv_tr(projectionVectorLength,x,y),
lambda x,y:tr(projectionVectorLength,x,y)))
ax = SubplotHost(figure, 1, 1, 1, grid_helper=grid_helper)
ax.sample = sample[0]
figure.add_subplot(ax)
#ax.set_aspect(1.)
ax.grid(True, zorder=0)
def calculateRLU(l,v1,x,y,v,step):
return np.asarray(x)/l*v1+v*step, np.asarray(y)
def format_coord(x,y): # pragma: no cover # x is H,K,L and y is energy
xformated = ', '.join(['{} = {}'.format(Y[0],Y[1]) for Y in zip(['h','k','l'],['{:.4f}'.format(X) for X in x])])
return '{}, E={:.4f}'.format(xformated,y)
ax.set_xlabel('{} [RLU]'.format(projectionVectorFormated))
ax.set_ylabel('E [meV]')
ax._length = projectionVectorLengthORthogonal
ax._projectionVector = projectionVector
ax._projectionVectorOrthogonal = projectionVectorOrthogonal
ax._step = 0.0
ax.calculateRLU = lambda x,y: calculateRLU(projectionVectorLength,ax._projectionVector,x,y,ax._projectionVectorOrthogonal,ax._step)
ax.format_coord = lambda x,y: format_coord(*ax.calculateRLU(x,y))
if pythonVersion == 3:
ax.forceGridUpdate = lambda:forceGridUpdate(ax)
ax.xticks = 7
def xAxisChanged(axis, forceUpdate=False):
locator = axis._grid_helper.grid_finder.grid_locator1
xlim = axis.get_xlim()
xlimDiff = np.diff(xlim)
if isinstance(locator,MultipleLocator):
if hasattr(axis,'xBase'):
base = axis.xBase
else:
base = calculateBase(locator,xlimDiff,axis.xticks)
locator.set_params(base=base)
elif isinstance(locator,MaxNLocator):
if hasattr(axis,'xTicks'):
ticks = getattr(axis,'xTicks')
else:
ticks = 7
locator.set_params(nbins = ticks)
else:
return
axis.forceGridUpdate()
ax.callbacks.connect('xlim_changed', xAxisChanged)
ax.callbacks.connect('draw_event',lambda ax: xAxisChanged(ax,forceUpdate=True))
ax.xAxisChanged = lambda: xAxisChanged(ax,forceUpdate=True)
@updateXAxisDecorator(ax=ax)
def set_xticks_base(xBase=None,ax=ax):
"""Setter of the base x ticks to be used for plotting
Kwargs:
- xBase (float): Base of the tick marks (default automatic)
"""
if not isinstance(ax._grid_helper.grid_finder.grid_locator1,MultipleLocator):
l1 = MultipleLocator(base=xBase)
ax._grid_helper.update_grid_finder(grid_locator1=l1)
if xBase is None:
if hasattr(ax,'xBase'):
delattr(ax,'xBase')
else:
ax.xBase = xBase
@updateXAxisDecorator(ax=ax)
def set_xticks_number(xNumber = None,ax=ax):
"""Setter of the number of x ticks to be used for plotting
Kwargs:
- xNumber (int): Number of x tick marks (default 7)
"""
if xNumber is None:
xNumber = 7
if not isinstance(ax._grid_helper.grid_finder.grid_locator1,MaxNLocator):
l1 = MaxNLocator(nbins=xNumber)
ax._grid_helper.update_grid_finder(grid_locator1=l1)
ax.xTicks = xNumber
ax.set_xticks_base = set_xticks_base
ax.set_xticks_number = set_xticks_number
return ax
def createRLUAxes(self,figure=None,ids=[1, 1, 1],basex=None,basey=None):
"""Create a reciprocal lattice plot for a given DataSet object.
Args:
- Dataset (DataSet): DataSet object for which the RLU plot is to be made.
Kwargs:
- figure: Matplotlib figure in which the axis is to be put (default None)
- ids (array): List of integer numbers provided to the SubplotHost ids attribute (default [1,1,1])
- basex (float): Ticks are positioned at multiples of this value along x (default None)
- basey (float): Ticks are positioned at multiples of this value along y (default None)
Returns:
- ax (Matplotlib axes): Axes containing the RLU plot.
.. note::
When rlu axis is created, the orientation of Qx and Qy is assumed to be rotated as well.
This is to be done in the self.View3D method call!
.. note::
When using python 2 the changing of tick marks is not supported due to limitations in matplotlib. However, if python 3 is used, the number
of ticks and their location can be change after the initialization using the set_xticks_number, set_yticks_number chaning the wanted number
of tick marks, or the set_xticks_base or set_yticks_base to change the base number, see RLU tutorial under Tools. As default a sufficient base
number is found and will update when zooming.
"""
sample = copy.deepcopy(self.sample)
for samp in sample:
samp.convert = np.einsum('ij,j...->i...',samp.RotMat,samp.convert)
#sample.convert = np.einsum('ij,j...->i...',sample.RotMat,sample.convert)
samp.convertinv = np.linalg.inv(samp.convert) # Convert from Qx, Qy to projX, projY
samp.orientationMatrix = np.dot(samp.RotMat3D,samp.orientationMatrix)
samp.orientationMatrixINV = np.linalg.inv(samp.orientationMatrix)
samp.theta = 0.0
if figure is None:
fig = plt.figure(figsize=(7, 4))
else:
fig = figure
def calculateTicks(ticks,angle,round=True):
val = ticks/np.tan(angle/2.0)
if round:
return np.array(np.round(val),dtype=int)
else:
return val
if pythonVersion==3: # Only for python 3
if not basex is None or not basey is None: # Either basex or basey is provided (or both)
if basex is None:
basex = calculateTicks(basey,sample[0].projectionAngle,round=False)
elif basey is None:
basey = basex/calculateTicks(1.0,sample[0].projectionAngle,round=False)
grid_locator1 = MultipleLocator(base=basex)
grid_locator2 = MultipleLocator(base=basey)
else:
basex = 0.5
basey = 0.5
grid_locator1 = MultipleLocator(base=basex)
grid_locator2 = MultipleLocator(base=basey)
grid_helper = GridHelperCurveLinear((sample[0].inv_tr, sample[0].tr),grid_locator1=grid_locator1,grid_locator2=grid_locator2)
else: # Python 2
grid_helper = GridHelperCurveLinear((sample[0].inv_tr, sample[0].tr))
ax = SubplotHost(fig, *ids, grid_helper=grid_helper)
ax.sample = sample[0]
if pythonVersion==3: # Only for python 3
ax.basex = basex
ax.basey = basey
def set_axis(ax,v1,v2,*args):
if not args is ():
points = np.concatenate([[v1,v2],[x for x in args]],axis=0)
else:
points = np.array([v1,v2])
if points.shape[1] == 3:
points = ax.sample.calculateHKLtoProjection(points[:,0],points[:,1],points[:,2]).T
boundaries = np.array([ax.sample.inv_tr(x[0],x[1]) for x in points])
ax.set_xlim(boundaries[:,0].min(),boundaries[:,0].max())
ax.set_ylim(boundaries[:,1].min(),boundaries[:,1].max())
if pythonVersion == 3: # Only possible in python 3
ax.forceGridUpdate()
fig.add_subplot(ax)
ax.set_aspect(1.)
ax.grid(True, zorder=0)
if not np.isclose(ax.sample.projectionAngle,np.pi/2.0,atol=0.001):
ax.axis["top"].major_ticklabels.set_visible(True)
ax.axis["right"].major_ticklabels.set_visible(True)
ax.format_coord = ax.sample.format_coord
ax.set_axis = lambda v1,v2,*args: set_axis(ax,v1,v2,*args)
def beautifyLabel(vec):
Vec = [x.astype(int) if np.isclose(x.astype(float)-x.astype(int),0.0) else x.astype(float) for x in vec]
return '{} [RLU]'.format(', '.join([str(x) for x in Vec]))
ax.set_xlabel(beautifyLabel(ax.sample.projectionVector1))
ax.set_ylabel(beautifyLabel(ax.sample.projectionVector2))
if pythonVersion==3: # Only for python 3
ax.calculateTicks = lambda value:calculateTicks(value,ax.sample.projectionAngle)
ax.forceGridUpdate = lambda:forceGridUpdate(ax)
ax._oldXlimDiff = np.diff(ax.get_xlim())
ax._oldYlimDiff = np.diff(ax.get_ylim())
ax.get_aspect_ratio = lambda: get_aspect(ax)
ax.callbacks.connect('xlim_changed', axisChanged)
ax.callbacks.connect('ylim_changed', axisChanged)
ax.callbacks.connect('draw_event',lambda ax: axisChanged(ax,forceUpdate=True))
ax.axisChanged = lambda direction='both': axisChanged(ax,forceUpdate=True,direction=direction)
@updateAxisDecorator(ax=ax,direction='x')
def set_xticks_base(xBase,ax=ax):
"""Setter of the base x ticks to be used for plotting
Args:
- xBase (float): Base of the tick marks
"""
if not isinstance(ax._grid_helper.grid_finder.grid_locator1,MultipleLocator):
l1 = MultipleLocator(base=xBase)
ax._grid_helper.update_grid_finder(grid_locator1=l1)
ax.xbase = xBase
@updateAxisDecorator(ax=ax,direction='y')
def set_yticks_base(yBase,ax=ax):
"""Setter of the base y ticks to be used for plotting
Args:
- yBase (float): Base of the tick marks
"""
if not isinstance(ax._grid_helper.grid_finder.grid_locator2,MultipleLocator):
l2 = MultipleLocator(base=yBase)
ax._grid_helper.update_grid_finder(grid_locator2=l2)
ax.ybase = yBase
@updateAxisDecorator(ax=ax,direction='x')
def set_xticks_number(xNumber,ax=ax):
"""Setter of the number of x ticks to be used for plotting
Args:
- xNumber (int): Number of x tick marks
"""
if not isinstance(ax._grid_helper.grid_finder.grid_locator1,MaxNLocator):
l1 = MaxNLocator(nbins=xNumber)
ax._grid_helper.update_grid_finder(grid_locator1=l1)
ax.xticks = xNumber
@updateAxisDecorator(ax=ax,direction='y')
def set_yticks_number(yNumber,ax=ax):
"""Setter of the number of y ticks to be used for plotting
Args:
- yNumber (int): Number of y tick marks
"""
if not isinstance(ax._grid_helper.grid_finder.grid_locator2,MaxNLocator):
l2 = MaxNLocator(nbins=yNumber)
ax._grid_helper.update_grid_finder(grid_locator2=l2)
ax.yticks = yNumber
ax.set_xticks_base = set_xticks_base
ax.set_yticks_base = set_yticks_base
ax.set_xticks_number = set_xticks_number
ax.set_yticks_number = set_yticks_number
return ax
