import numpy as np
import hyperspy.utils.markers as hm
def _get_4d_points_marker_list(peaks_list, signal_axes=None, color='red',
size=20, bool_array=None, bool_invert=False):
"""Get a list of 4 dimensional point markers.
The markers will be displayed on the signal dimensions.
Parameters
----------
peaks_list : 4D NumPy array
signal_axes : HyperSpy axes_manager object
color : string, optional
Color of point marker. Default 'red'.
size : scalar, optional
Size of the point marker. Default 20.
bool_array : NumPy array, optional
Same shape as peaks_list.
bool_invert : bool, optional
Default False.
Returns
-------
marker_list : list of HyperSpy marker objects
Example
-------
>>> s = ps.dummy_data.get_cbed_signal()
>>> peak_array = s.find_peaks(lazy_result=False, show_progressbar=False)
>>> import pixstem.marker_tools as mt
>>> marker_list = mt._get_4d_points_marker_list(
... peak_array, s.axes_manager.signal_axes)
"""
if bool_array is not None:
peaks_list = _filter_peak_array_with_bool_array(
peaks_list, bool_array, bool_invert=bool_invert)
max_peaks = 0
if peaks_list.dtype == np.object:
peaks_list_shape = peaks_list.shape
else:
peaks_list_shape = peaks_list.shape[:-2]
for index in np.ndindex(peaks_list_shape):
islice = np.s_[index]
peak_list = peaks_list[islice]
if peak_list is not None:
n_peaks = len(peak_list)
if n_peaks > max_peaks:
max_peaks = n_peaks
marker_array_shape = list(peaks_list_shape)
marker_array_shape.append(max_peaks)
marker_x_array = np.ones(marker_array_shape) * -1000
marker_y_array = np.ones(marker_array_shape) * -1000
for index in np.ndindex(peaks_list_shape):
islice = np.s_[index]
peak_list = peaks_list[islice]
if peak_list is not None:
for i_p, peak in enumerate(peak_list):
i2slice = list(islice)
i2slice.append(i_p)
i2slice = tuple(i2slice)
if signal_axes is None:
marker_x_array[i2slice] = peak[1]
marker_y_array[i2slice] = peak[0]
else:
i0min = signal_axes[0].low_index
i0max = signal_axes[0].high_index
i1min = signal_axes[1].low_index
i1max = signal_axes[1].high_index
bool0 = i0min <= peak[1] <= i0max
bool1 = i1min <= peak[0] <= i1max
if bool0 and bool1:
vx = signal_axes[0].index2value(int(peak[1]))
vy = signal_axes[1].index2value(int(peak[0]))
marker_x_array[i2slice] = vx
marker_y_array[i2slice] = vy
marker_list = []
for i_p in range(max_peaks):
marker = hm.point(
marker_x_array[..., i_p], marker_y_array[..., i_p],
color=color, size=size)
marker_list.append(marker)
return marker_list
def _filter_peak_array_with_bool_array(
peak_array, bool_array, bool_invert=False):
if bool_array.shape != peak_array.shape:
raise ValueError(
"bool_array {0} and peak_array {1} must have the"
" same shape".format(bool_array.shape, peak_array.shape))
peak_array_filter = np.empty(shape=(peak_array.shape[:2]), dtype=np.object)
for ix, iy in np.ndindex(peak_array.shape[:2]):
peak_list = np.array(peak_array[ix, iy])
bool_list = np.array(bool_array[ix, iy], dtype=np.bool)
if bool_list is None:
if bool_invert:
peak_list = []
else:
if bool_invert:
bool_list = ~bool_list
peak_list = peak_list[bool_list]
peak_array_filter[ix, iy] = peak_list
return peak_array_filter
def _get_4d_line_segment_list(lines_array, signal_axes=None, color='red',
linewidth=1, linestyle='solid'):
"""Get a list of 4 dimensional line segments markers.
The markers will be displayed on the signal dimensions.
Parameters
----------
lines_array : 4D NumPy array
signal_axes : HyperSpy axes_manager object
color : string, optional
Color of point marker. Default 'red'.
linewidth : scalar, optional
Default 2
linestyle : string, optional
Default 'solid'
Returns
-------
marker_list : list of HyperSpy marker objects
"""
max_lines = 0
for ix, iy in np.ndindex(lines_array.shape[:2]):
lines_list = lines_array[ix, iy]
if lines_list is not None:
n_lines = len(lines_list)
if n_lines > max_lines:
max_lines = n_lines
marker_array_shape = (lines_array.shape[0], lines_array.shape[1],
max_lines)
marker_x1_array = np.ones(marker_array_shape) * -1000
marker_y1_array = np.ones(marker_array_shape) * -1000
marker_x2_array = np.ones(marker_array_shape) * -1000
marker_y2_array = np.ones(marker_array_shape) * -1000
for ix, iy in np.ndindex(marker_x1_array.shape[:2]):
lines_list = lines_array[ix, iy]
if lines_list is not None:
for i_p, line in enumerate(lines_list):
if signal_axes is None:
marker_x1_array[ix, iy, i_p] = line[1]
marker_y1_array[ix, iy, i_p] = line[0]
marker_x2_array[ix, iy, i_p] = line[3]
marker_y2_array[ix, iy, i_p] = line[2]
else:
if _check_line_segment_inside(signal_axes, line):
sa0iv = signal_axes[0].index2value
sa1iv = signal_axes[1].index2value
marker_x1_array[ix, iy, i_p] = sa0iv(int(line[1]))
marker_y1_array[ix, iy, i_p] = sa1iv(int(line[0]))
marker_x2_array[ix, iy, i_p] = sa0iv(int(line[3]))
marker_y2_array[ix, iy, i_p] = sa1iv(int(line[2]))
marker_list = []
for i_p in range(max_lines):
marker = hm.line_segment(
marker_x1_array[..., i_p], marker_y1_array[..., i_p],
marker_x2_array[..., i_p], marker_y2_array[..., i_p],
color=color, linewidth=linewidth, linestyle=linestyle)
marker_list.append(marker)
return marker_list
def _check_line_segment_inside(signal_axes, line):
sa0_li = signal_axes[0].low_index
sa0_hi = signal_axes[0].high_index
sa1_li = signal_axes[1].low_index
sa1_hi = signal_axes[1].high_index
if line[1] > sa0_hi:
return False
if line[1] < sa0_li:
return False
if line[3] > sa0_hi:
return False
if line[3] < sa0_li:
return False
if line[0] > sa1_hi:
return False
if line[0] < sa1_li:
return False
if line[2] > sa1_hi:
return False
if line[2] < sa1_li:
return False
return True
def _get_2d_line_segment_list(lines_list, signal_axes=None, color='red',
linewidth=1, linestyle='solid'):
"""Get a list of 2d dimensional line segments markers.
The markers will be displayed on the signal dimensions.
Parameters
----------
lines_list : list
In form [[x01, y01, x02, y02], [x11, y11, x12, y12], ...]
signal_axes : HyperSpy axes_manager object
color : string, optional
Color of point marker. Default 'red'.
linewidth : scalar, optional
Default 2
linestyle : string, optional
Default 'solid'
Returns
-------
marker_list : list of HyperSpy marker objects
"""
marker_list = []
for x1, y1, x2, y2 in lines_list:
marker = hm.line_segment(x1, y1, x2, y2, color=color,
linewidth=linewidth, linestyle=linestyle)
marker_list.append(marker)
return marker_list
def _add_permanent_markers_to_signal(signal, marker_list):
"""Add a list of markers to a signal.
Parameters
----------
signal : PixelatedSTEM or Signal2D
marker_list : list of markers
Example
-------
>>> s = ps.dummy_data.get_cbed_signal()
>>> peak_array = s.find_peaks(lazy_result=False, show_progressbar=False)
>>> import pixstem.marker_tools as mt
>>> marker_list = mt._get_4d_points_marker_list(
... peak_array, s.axes_manager.signal_axes)
>>> mt._add_permanent_markers_to_signal(s, marker_list)
>>> s.plot()
"""
if not hasattr(signal.metadata, 'Markers'):
signal.metadata.add_node('Markers')
marker_extra = len(signal.metadata.Markers)
for imarker, marker in enumerate(marker_list):
marker_name = 'marker{0}'.format(imarker + marker_extra)
signal.metadata.Markers[marker_name] = marker
[docs]def add_peak_array_to_signal_as_markers(
signal, peak_array, color='red', size=20, bool_array=None,
bool_invert=False):
"""Add an array of points to a signal as HyperSpy markers.
Parameters
----------
signal : PixelatedSTEM or Signal2D
peak_array : 4D NumPy array
color : string, optional
Default 'red'
size : scalar, optional
Default 20
bool_array : NumPy array, optional
Same shape as peaks_list.
bool_invert : bool, optional
Default False.
Example
-------
>>> s = ps.dummy_data.get_cbed_signal()
>>> peak_array = s.find_peaks(lazy_result=False, show_progressbar=False)
>>> import pixstem.marker_tools as mt
>>> mt.add_peak_array_to_signal_as_markers(s, peak_array)
>>> s.plot()
"""
marker_list = _get_4d_points_marker_list(
peak_array, signal.axes_manager.signal_axes, color=color,
size=size, bool_array=bool_array, bool_invert=bool_invert)
_add_permanent_markers_to_signal(signal, marker_list)