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# -*- coding: utf-8 -*- |
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""" |
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This module operates a confocal microsope. |
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Qudi is free software: you can redistribute it and/or modify |
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it under the terms of the GNU General Public License as published by |
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the Free Software Foundation, either version 3 of the License, or |
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(at your option) any later version. |
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Qudi is distributed in the hope that it will be useful, |
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but WITHOUT ANY WARRANTY; without even the implied warranty of |
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
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GNU General Public License for more details. |
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You should have received a copy of the GNU General Public License |
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along with Qudi. If not, see <http://www.gnu.org/licenses/>. |
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Copyright (c) the Qudi Developers. See the COPYRIGHT.txt file at the |
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top-level directory of this distribution and at <https://github.com/Ulm-IQO/qudi/> |
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""" |
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from qtpy import QtCore |
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from collections import OrderedDict |
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from copy import copy |
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from datetime import datetime |
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import numpy as np |
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import matplotlib as mpl |
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import matplotlib.pyplot as plt |
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from io import BytesIO |
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from logic.generic_logic import GenericLogic |
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from core.util.mutex import Mutex |
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def numpy_from_b(compressed_b): |
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f = BytesIO(bytes(compressed_b)) |
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np_file = np.load(f) |
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redict = dict() |
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for name in np_file.files: |
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redict.update({name: np_file[name]}) |
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f.close() |
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return redict |
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class OldConfigFileError(Exception): |
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def __init__(self): |
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super().__init__('Old configuration file detected. Ignoring history.') |
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class ConfocalHistoryEntry(QtCore.QObject): |
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""" This class contains all relevant parameters of a Confocal scan. |
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It provides methods to extract, restore and serialize this data. |
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""" |
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def __init__(self, confocal): |
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""" Make a confocal data setting with default values. """ |
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super().__init__() |
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self.xy_line_pos = 0 |
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self.depth_line_pos = 0 |
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# Reads in the maximal scanning range. The unit of that scan range is micrometer! |
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self.x_range = confocal._scanning_device.get_position_range()[0] |
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self.y_range = confocal._scanning_device.get_position_range()[1] |
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self.z_range = confocal._scanning_device.get_position_range()[2] |
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# Sets the current position to the center of the maximal scanning range |
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self.current_x = (self.x_range[0] + self.x_range[1]) / 2 |
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self.current_y = (self.y_range[0] + self.y_range[1]) / 2 |
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self.current_z = (self.z_range[0] + self.z_range[1]) / 2 |
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self.current_a = 0.0 |
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# Sets the size of the image to the maximal scanning range |
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self.image_x_range = self.x_range |
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self.image_y_range = self.y_range |
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self.image_z_range = self.z_range |
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# Default values for the resolution of the scan |
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self.xy_resolution = 100 |
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self.z_resolution = 50 |
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# Initialization of internal counter for scanning |
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self.xy_line_position = 0 |
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self.depth_line_position = 0 |
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# Variable to check if a scan is continuable |
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self.xy_scan_continuable = False |
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self.depth_scan_continuable = False |
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# tilt correction stuff: |
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self.tilt_correction = False |
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# rotation point for tilt correction |
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self.tilt_reference_x = 0.5 * (self.x_range[0] + self.x_range[1]) |
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self.tilt_reference_y = 0.5 * (self.y_range[0] + self.y_range[1]) |
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# sample slope |
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self.tilt_slope_x = 0 |
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self.tilt_slope_y = 0 |
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# tilt correction points |
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self.point1 = np.array((0, 0, 0)) |
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self.point2 = np.array((0, 0, 0)) |
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self.point3 = np.array((0, 0, 0)) |
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def restore(self, confocal): |
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""" Write data back into confocal logic and pull all the necessary strings """ |
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confocal._current_x = self.current_x |
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confocal._current_y = self.current_y |
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confocal._current_z = self.current_z |
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confocal._current_a = self.current_a |
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confocal.image_x_range = np.copy(self.image_x_range) |
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confocal.image_y_range = np.copy(self.image_y_range) |
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confocal.image_z_range = np.copy(self.image_z_range) |
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confocal.xy_resolution = self.xy_resolution |
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confocal.z_resolution = self.z_resolution |
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confocal._xy_line_pos = self.xy_line_position |
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confocal._depth_line_pos = self.depth_line_position |
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confocal._xyscan_continuable = self.xy_scan_continuable |
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confocal._zscan_continuable = self.depth_scan_continuable |
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confocal.TiltCorrection = self.tilt_correction |
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confocal.point1 = np.copy(self.point1) |
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confocal.point2 = np.copy(self.point2) |
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confocal.point3 = np.copy(self.point3) |
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confocal._tiltreference_x = self.tilt_reference_x |
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confocal._tiltreference_y = self.tilt_reference_y |
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confocal._tilt_variable_ax = self.tilt_slope_x |
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confocal._tilt_variable_ay = self.tilt_slope_y |
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confocal.initialize_image() |
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try: |
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if confocal.xy_image.shape == self.xy_image.shape: |
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confocal.xy_image = np.copy(self.xy_image) |
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except AttributeError: |
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self.xy_image = np.copy(confocal.xy_image) |
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confocal._zscan = True |
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confocal.initialize_image() |
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try: |
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if confocal.depth_image.shape == self.depth_image.shape: |
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confocal.depth_image = np.copy(self.depth_image) |
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except AttributeError: |
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self.depth_image = np.copy(confocal.depth_image) |
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confocal._zscan = False |
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def snapshot(self, confocal): |
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""" Extract all necessary data from a confocal logic and keep it for later use """ |
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self.current_x = confocal._current_x |
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self.current_y = confocal._current_y |
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self.current_z = confocal._current_z |
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self.current_a = confocal._current_a |
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self.image_x_range = np.copy(confocal.image_x_range) |
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self.image_y_range = np.copy(confocal.image_y_range) |
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self.image_z_range = np.copy(confocal.image_z_range) |
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self.xy_resolution = confocal.xy_resolution |
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self.z_resolution = confocal.z_resolution |
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self.xy_line_position = confocal._xy_line_pos |
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self.depth_line_position = confocal._depth_line_pos |
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self.xy_scan_continuable = confocal._xyscan_continuable |
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self.depth_scan_continuable = confocal._zscan_continuable |
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self.tilt_correction = confocal.TiltCorrection |
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self.point1 = np.copy(confocal.point1) |
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self.point2 = np.copy(confocal.point2) |
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self.point3 = np.copy(confocal.point3) |
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self.tilt_reference_x = confocal._tiltreference_x |
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self.tilt_reference_y = confocal._tiltreference_y |
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self.tilt_slope_x = confocal._tilt_variable_ax |
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self.tile_slope_y = confocal._tilt_variable_ay |
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self.xy_image = np.copy(confocal.xy_image) |
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self.depth_image = np.copy(confocal.depth_image) |
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def serialize(self): |
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""" Give out a dictionary that can be saved via the usual means """ |
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serialized = dict() |
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serialized['focus_position'] = [self.current_x, self.current_y, self.current_z, self.current_a] |
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serialized['x_range'] = self.image_x_range |
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serialized['y_range'] = self.image_y_range |
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serialized['z_range'] = self.image_z_range |
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serialized['xy_resolution'] = self.xy_resolution |
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serialized['z_resolution'] = self.z_resolution |
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serialized['xy_line_position'] = self.xy_line_position |
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serialized['depth_linne_position'] = self.depth_line_position |
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serialized['xy_scan_cont'] = self.xy_scan_continuable |
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serialized['depth_scan_cont'] = self.depth_scan_continuable |
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serialized['tilt_correction'] = self.tilt_correction |
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serialized['tilt_point1'] = self.point1 |
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serialized['tilt_point2'] = self.point2 |
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serialized['tilt_point3'] = self.point3 |
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serialized['tilt_reference'] = [self.tilt_reference_x, self.tilt_reference_y] |
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serialized['tilt_slope'] = [self.tilt_slope_x, self.tilt_slope_y] |
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serialized['xy_image'] = self.xy_image |
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serialized['depth_image'] = self.depth_image |
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return serialized |
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def deserialize(self, serialized): |
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""" Restore Confocal history object from a dict """ |
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if 'focus_position' in serialized and len(serialized['focus_position']) == 4: |
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self.current_x = serialized['focus_position'][0] |
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self.current_y = serialized['focus_position'][1] |
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self.current_z = serialized['focus_position'][2] |
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self.current_a = serialized['focus_position'][3] |
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if 'x_range' in serialized and len(serialized['x_range']) == 2: |
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self.image_x_range = serialized['x_range'] |
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if 'y_range' in serialized and len(serialized['y_range']) == 2: |
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self.image_y_range = serialized['y_range'] |
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if 'z_range' in serialized and len(serialized['z_range']) == 2: |
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self.image_z_range = serialized['z_range'] |
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if 'xy_resolution' in serialized: |
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self.xy_resolution = serialized['xy_resolution'] |
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if 'z_resolution' in serialized: |
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self.z_resolution = serialized['z_resolution'] |
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if 'tilt_correction' in serialized: |
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self.tilt_correction = serialized['tilt_correction'] |
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if 'tilt_reference' in serialized and len(serialized['tilt_reference']) == 2: |
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self.tilt_reference_x = serialized['tilt_reference'][0] |
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self.tilt_reference_y = serialized['tilt_reference'][1] |
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if 'tilt_slope' in serialized and len(serialized['tilt_slope']) == 2: |
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self.tilt_slope_x = serialized['tilt_slope'][0] |
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self.tilt_slope_y = serialized['tilt_slope'][1] |
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if 'tilt_point1' in serialized and len(serialized['tilt_point1'] ) == 3: |
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self.point1 = np.array(serialized['tilt_point1']) |
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if 'tilt_point2' in serialized and len(serialized['tilt_point2'] ) == 3: |
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self.point2 = np.array(serialized['tilt_point2']) |
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if 'tilt_point3' in serialized and len(serialized['tilt_point3'] ) == 3: |
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self.point3 = np.array(serialized['tilt_point3']) |
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if 'xy_image' in serialized: |
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if isinstance(serialized['xy_image'], np.ndarray): |
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self.xy_image = serialized['xy_image'] |
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else: |
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try: |
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self.xy_image = numpy_from_b( |
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eval(serialized['xy_image']))['image'] |
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except: |
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raise OldConfigFileError() |
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if 'depth_image' in serialized: |
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if isinstance(serialized['depth_image'], np.ndarray): |
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self.depth_image = serialized['depth_image'].copy() |
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else: |
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try: |
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self.depth_image = numpy_from_b( |
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eval(serialized['depth_image']))['image'] |
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except: |
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raise OldConfigFileError() |
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class ConfocalLogic(GenericLogic): |
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""" |
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This is the Logic class for confocal scanning. |
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""" |
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_modclass = 'confocallogic' |
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_modtype = 'logic' |
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# declare connectors |
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_in = { |
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'confocalscanner1': 'ConfocalScannerInterface', |
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'savelogic': 'SaveLogic' |
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} |
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_out = {'scannerlogic': 'ConfocalLogic'} |
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# signals |
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signal_start_scanning = QtCore.Signal() |
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signal_continue_scanning = QtCore.Signal() |
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signal_scan_lines_next = QtCore.Signal() |
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signal_xy_image_updated = QtCore.Signal() |
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signal_depth_image_updated = QtCore.Signal() |
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signal_change_position = QtCore.Signal(str) |
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sigImageXYInitialized = QtCore.Signal() |
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sigImageDepthInitialized = QtCore.Signal() |
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signal_history_event = QtCore.Signal() |
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def __init__(self, config, **kwargs): |
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super().__init__(config=config, **kwargs) |
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self.log.info('The following configuration was found.') |
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# checking for the right configuration |
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for key in config.keys(): |
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self.log.info('{0}: {1}'.format(key, config[key])) |
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#locking for thread safety |
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self.threadlock = Mutex() |
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# counter for scan_image |
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self._scan_counter = 0 |
|
284
|
|
|
self._zscan = False |
|
285
|
|
|
self.stopRequested = False |
|
286
|
|
|
self.depth_scan_dir_is_xz = True |
|
287
|
|
|
self.permanent_scan = False |
|
288
|
|
|
|
|
289
|
|
|
def on_activate(self, e): |
|
290
|
|
|
""" Initialisation performed during activation of the module. |
|
291
|
|
|
|
|
292
|
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|
@param e: error code |
|
293
|
|
|
""" |
|
294
|
|
|
self._scanning_device = self.get_in_connector('confocalscanner1') |
|
295
|
|
|
# print("Scanning device is", self._scanning_device) |
|
296
|
|
|
|
|
297
|
|
|
self._save_logic = self.get_in_connector('savelogic') |
|
298
|
|
|
|
|
299
|
|
|
#default values for clock frequency and slowness |
|
300
|
|
|
#slowness: steps during retrace line |
|
301
|
|
|
if 'clock_frequency' in self._statusVariables: |
|
302
|
|
|
self._clock_frequency = self._statusVariables['clock_frequency'] |
|
303
|
|
|
else: |
|
304
|
|
|
self._clock_frequency = 500 |
|
305
|
|
|
if 'return_slowness' in self._statusVariables: |
|
306
|
|
|
self.return_slowness = self._statusVariables['return_slowness'] |
|
307
|
|
|
else: |
|
308
|
|
|
self.return_slowness = 50 |
|
309
|
|
|
|
|
310
|
|
|
# Reads in the maximal scanning range. The unit of that scan range is micrometer! |
|
311
|
|
|
self.x_range = self._scanning_device.get_position_range()[0] |
|
312
|
|
|
self.y_range = self._scanning_device.get_position_range()[1] |
|
313
|
|
|
self.z_range = self._scanning_device.get_position_range()[2] |
|
314
|
|
|
|
|
315
|
|
|
# restore here ... |
|
316
|
|
|
self.history = [] |
|
317
|
|
|
if 'max_history_length' in self._statusVariables: |
|
318
|
|
|
self.max_history_length = self._statusVariables ['max_history_length'] |
|
319
|
|
|
for i in reversed(range(1, self.max_history_length)): |
|
320
|
|
|
try: |
|
321
|
|
|
new_history_item = ConfocalHistoryEntry(self) |
|
322
|
|
|
new_history_item.deserialize(self._statusVariables['history_{0}'.format(i)]) |
|
323
|
|
|
self.history.append(new_history_item) |
|
324
|
|
|
except KeyError: |
|
325
|
|
|
pass |
|
326
|
|
|
except OldConfigFileError: |
|
327
|
|
|
self.log.warning('Old style config file detected. ' |
|
328
|
|
|
'History {0} ignored.'.format(i)) |
|
329
|
|
|
except: |
|
330
|
|
|
self.log.warning( |
|
331
|
|
|
'Restoring history {0} failed.'.format(i)) |
|
332
|
|
|
else: |
|
333
|
|
|
self.max_history_length = 10 |
|
334
|
|
|
try: |
|
335
|
|
|
new_state = ConfocalHistoryEntry(self) |
|
336
|
|
|
new_state.deserialize(self._statusVariables['history_0']) |
|
337
|
|
|
new_state.restore(self) |
|
338
|
|
|
except: |
|
339
|
|
|
new_state = ConfocalHistoryEntry(self) |
|
340
|
|
|
new_state.restore(self) |
|
341
|
|
|
finally: |
|
342
|
|
|
self.history.append(new_state) |
|
343
|
|
|
|
|
344
|
|
|
self.history_index = len(self.history) - 1 |
|
345
|
|
|
|
|
346
|
|
|
# Sets connections between signals and functions |
|
347
|
|
|
self.signal_scan_lines_next.connect(self._scan_line, QtCore.Qt.QueuedConnection) |
|
348
|
|
|
self.signal_start_scanning.connect(self.start_scanner, QtCore.Qt.QueuedConnection) |
|
349
|
|
|
self.signal_continue_scanning.connect(self.continue_scanner, QtCore.Qt.QueuedConnection) |
|
350
|
|
|
|
|
351
|
|
|
self._change_position('activation') |
|
352
|
|
|
|
|
353
|
|
|
def on_deactivate(self, e): |
|
354
|
|
|
""" Reverse steps of activation |
|
355
|
|
|
|
|
356
|
|
|
@param e: error code |
|
357
|
|
|
|
|
358
|
|
|
@return int: error code (0:OK, -1:error) |
|
359
|
|
|
""" |
|
360
|
|
|
self._statusVariables['clock_frequency'] = self._clock_frequency |
|
361
|
|
|
self._statusVariables['return_slowness'] = self.return_slowness |
|
362
|
|
|
self._statusVariables['max_history_length'] = self.max_history_length |
|
363
|
|
|
closing_state = ConfocalHistoryEntry(self) |
|
364
|
|
|
closing_state.snapshot(self) |
|
365
|
|
|
self.history.append(closing_state) |
|
366
|
|
|
histindex = 0 |
|
367
|
|
|
for state in reversed(self.history): |
|
368
|
|
|
self._statusVariables['history_{0}'.format(histindex)] = state.serialize() |
|
369
|
|
|
histindex += 1 |
|
370
|
|
|
return 0 |
|
371
|
|
|
|
|
372
|
|
|
def switch_hardware(self, to_on=False): |
|
373
|
|
|
""" Switches the Hardware off or on. |
|
374
|
|
|
|
|
375
|
|
|
@param to_on: True switches on, False switched off |
|
376
|
|
|
|
|
377
|
|
|
@return int: error code (0:OK, -1:error) |
|
378
|
|
|
""" |
|
379
|
|
|
if to_on: |
|
380
|
|
|
return self._scanning_device.activation() |
|
381
|
|
|
else: |
|
382
|
|
|
return self._scanning_device.reset_hardware() |
|
383
|
|
|
|
|
384
|
|
|
def set_clock_frequency(self, clock_frequency): |
|
385
|
|
|
"""Sets the frequency of the clock |
|
386
|
|
|
|
|
387
|
|
|
@param int clock_frequency: desired frequency of the clock |
|
388
|
|
|
|
|
389
|
|
|
@return int: error code (0:OK, -1:error) |
|
390
|
|
|
""" |
|
391
|
|
|
self._clock_frequency = int(clock_frequency) |
|
392
|
|
|
#checks if scanner is still running |
|
393
|
|
|
if self.getState() == 'locked': |
|
394
|
|
|
return -1 |
|
395
|
|
|
else: |
|
396
|
|
|
return 0 |
|
397
|
|
|
|
|
398
|
|
|
def start_scanning(self, zscan = False): |
|
399
|
|
|
"""Starts scanning |
|
400
|
|
|
|
|
401
|
|
|
@param bool zscan: zscan if true, xyscan if false |
|
402
|
|
|
|
|
403
|
|
|
@return int: error code (0:OK, -1:error) |
|
404
|
|
|
""" |
|
405
|
|
|
# TODO: this is dirty, but it works for now |
|
406
|
|
|
# while self.getState() == 'locked': |
|
407
|
|
|
# time.sleep(0.01) |
|
408
|
|
|
self._scan_counter = 0 |
|
409
|
|
|
self._zscan = zscan |
|
410
|
|
|
if self._zscan: |
|
411
|
|
|
self._zscan_continuable = True |
|
412
|
|
|
else: |
|
413
|
|
|
self._xyscan_continuable = True |
|
414
|
|
|
|
|
415
|
|
|
self.signal_start_scanning.emit() |
|
416
|
|
|
return 0 |
|
417
|
|
|
|
|
418
|
|
|
|
|
419
|
|
|
def continue_scanning(self,zscan): |
|
420
|
|
|
"""Continue scanning |
|
421
|
|
|
|
|
422
|
|
|
@return int: error code (0:OK, -1:error) |
|
423
|
|
|
""" |
|
424
|
|
|
self._zscan = zscan |
|
425
|
|
|
if zscan: |
|
426
|
|
|
self._scan_counter = self._depth_line_pos |
|
427
|
|
|
else: |
|
428
|
|
|
self._scan_counter = self._xy_line_pos |
|
429
|
|
|
self.signal_continue_scanning.emit() |
|
430
|
|
|
return 0 |
|
431
|
|
|
|
|
432
|
|
|
|
|
433
|
|
|
def stop_scanning(self): |
|
434
|
|
|
"""Stops the scan |
|
435
|
|
|
|
|
436
|
|
|
@return int: error code (0:OK, -1:error) |
|
437
|
|
|
""" |
|
438
|
|
|
with self.threadlock: |
|
439
|
|
|
if self.getState() == 'locked': |
|
440
|
|
|
self.stopRequested = True |
|
441
|
|
|
return 0 |
|
442
|
|
|
|
|
443
|
|
|
def initialize_image(self): |
|
444
|
|
|
"""Initalization of the image. |
|
445
|
|
|
|
|
446
|
|
|
@return int: error code (0:OK, -1:error) |
|
447
|
|
|
""" |
|
448
|
|
|
# x1: x-start-value, x2: x-end-value |
|
449
|
|
|
x1, x2 = self.image_x_range[0], self.image_x_range[1] |
|
450
|
|
|
# y1: x-start-value, y2: x-end-value |
|
451
|
|
|
y1, y2 = self.image_y_range[0], self.image_y_range[1] |
|
452
|
|
|
# z1: x-start-value, z2: x-end-value |
|
453
|
|
|
z1, z2 = self.image_z_range[0], self.image_z_range[1] |
|
454
|
|
|
|
|
455
|
|
|
# Checks if the x-start and x-end value are ok |
|
456
|
|
|
if x2 < x1: |
|
457
|
|
|
self.log.error( |
|
458
|
|
|
'x1 must be smaller than x2, but they are ' |
|
459
|
|
|
'({0:.3f},{1:.3f}).'.format(x1, x2)) |
|
460
|
|
|
return -1 |
|
461
|
|
|
|
|
462
|
|
|
if self._zscan: |
|
463
|
|
|
# creates an array of evenly spaced numbers over the interval |
|
464
|
|
|
# x1, x2 and the spacing is equal to xy_resolution |
|
465
|
|
|
self._X = np.linspace(x1, x2, self.xy_resolution) |
|
466
|
|
|
# Checks if the z-start and z-end value are ok |
|
467
|
|
|
if z2 < z1: |
|
468
|
|
|
self.log.error( |
|
469
|
|
|
'z1 must be smaller than z2, but they are ' |
|
470
|
|
|
'({0:.3f},{1:.3f}).'.format(z1, z2)) |
|
471
|
|
|
return -1 |
|
472
|
|
|
# creates an array of evenly spaced numbers over the interval |
|
473
|
|
|
# z1, z2 and the spacing is equal to z_resolution |
|
474
|
|
|
self._Z = np.linspace(z1, z2, max(self.z_resolution, 2)) |
|
475
|
|
|
else: |
|
476
|
|
|
# Checks if the y-start and y-end value are ok |
|
477
|
|
|
if y2 < y1: |
|
478
|
|
|
self.log.error( |
|
479
|
|
|
'y1 must be smaller than y2, but they are ' |
|
480
|
|
|
'({0:.3f},{1:.3f}).'.format(y1, y2)) |
|
481
|
|
|
return -1 |
|
482
|
|
|
|
|
483
|
|
|
# prevents distorion of the image |
|
484
|
|
|
if (x2 - x1) >= (y2 - y1): |
|
485
|
|
|
self._X = np.linspace(x1, x2, max(self.xy_resolution, 2)) |
|
486
|
|
|
self._Y = np.linspace(y1, y2, max(int(self.xy_resolution*(y2-y1)/(x2-x1)), 2)) |
|
487
|
|
|
else: |
|
488
|
|
|
self._Y = np.linspace(y1, y2, max(self.xy_resolution, 2)) |
|
489
|
|
|
self._X = np.linspace(x1, x2, max(int(self.xy_resolution*(x2-x1)/(y2-y1)), 2)) |
|
490
|
|
|
|
|
491
|
|
|
self._XL = self._X |
|
492
|
|
|
self._YL = self._Y |
|
493
|
|
|
self._AL = np.zeros(self._XL.shape) |
|
494
|
|
|
|
|
495
|
|
|
# Arrays for retrace line |
|
496
|
|
|
self._return_XL = np.linspace(self._XL[-1], self._XL[0], self.return_slowness) |
|
497
|
|
|
self._return_AL = np.zeros(self._return_XL.shape) |
|
498
|
|
|
|
|
499
|
|
|
if self._zscan: |
|
500
|
|
|
if self.depth_scan_dir_is_xz: |
|
501
|
|
|
self._image_vert_axis = self._Z |
|
502
|
|
|
# creates an image where each pixel will be [x,y,z,counts] |
|
503
|
|
|
self.depth_image = np.zeros((len(self._image_vert_axis), len(self._X), 4)) |
|
504
|
|
|
self.depth_image[:, : ,0] = np.full((len(self._image_vert_axis), len(self._X)), self._XL) |
|
505
|
|
|
self.depth_image[:, :, 1] = self._current_y * np.ones((len(self._image_vert_axis), len(self._X))) |
|
506
|
|
|
z_value_matrix = np.full((len(self._X), len(self._image_vert_axis)), self._Z) |
|
507
|
|
|
self.depth_image[:, :, 2] = z_value_matrix.transpose() |
|
508
|
|
|
else: # depth scan is yz instead of xz |
|
509
|
|
|
self._image_vert_axis = self._Z |
|
510
|
|
|
# creats an image where each pixel will be [x,y,z,counts] |
|
511
|
|
|
self.depth_image = np.zeros((len(self._image_vert_axis), len(self._Y), 4)) |
|
512
|
|
|
self.depth_image[:, :, 0] = self._current_x * np.ones((len(self._image_vert_axis), len(self._Y))) |
|
513
|
|
|
self.depth_image[:, :, 1] = np.full((len(self._image_vert_axis), len(self._Y)), self._YL) |
|
514
|
|
|
z_value_matrix = np.full((len(self._Y), len(self._image_vert_axis)), self._Z) |
|
515
|
|
|
self.depth_image[:, :, 2] = z_value_matrix.transpose() |
|
516
|
|
|
# now we are scanning along the y-axis, so we need a new return line along Y: |
|
517
|
|
|
self._return_YL = np.linspace(self._YL[-1], self._YL[0], self.return_slowness) |
|
518
|
|
|
self._return_AL = np.zeros(self._return_YL.shape) |
|
519
|
|
|
self.sigImageDepthInitialized.emit() |
|
520
|
|
|
else: |
|
521
|
|
|
self._image_vert_axis = self._Y |
|
522
|
|
|
# creats an image where each pixel will be [x,y,z,counts] |
|
523
|
|
|
self.xy_image = np.zeros((len(self._image_vert_axis), len(self._X), 4)) |
|
524
|
|
|
self.xy_image[:, :, 0] = np.full((len(self._image_vert_axis), len(self._X)), self._XL) |
|
525
|
|
|
y_value_matrix = np.full((len(self._X), len(self._image_vert_axis)), self._Y) |
|
526
|
|
|
self.xy_image[:, :, 1] = y_value_matrix.transpose() |
|
527
|
|
|
self.xy_image[:, :, 2] = self._current_z * np.ones((len(self._image_vert_axis), len(self._X))) |
|
528
|
|
|
self.sigImageXYInitialized.emit() |
|
529
|
|
|
return 0 |
|
530
|
|
|
|
|
531
|
|
|
def start_scanner(self): |
|
532
|
|
|
"""Setting up the scanner device and starts the scanning procedure |
|
533
|
|
|
|
|
534
|
|
|
@return int: error code (0:OK, -1:error) |
|
535
|
|
|
""" |
|
536
|
|
|
self.lock() |
|
537
|
|
|
self._scanning_device.lock() |
|
538
|
|
|
if self.initialize_image() < 0: |
|
539
|
|
|
self._scanning_device.unlock() |
|
540
|
|
|
self.unlock() |
|
541
|
|
|
return -1 |
|
542
|
|
|
|
|
543
|
|
|
returnvalue = self._scanning_device.set_up_scanner_clock(clock_frequency=self._clock_frequency) |
|
544
|
|
|
if returnvalue < 0: |
|
545
|
|
|
self._scanning_device.unlock() |
|
546
|
|
|
self.unlock() |
|
547
|
|
|
self.set_position('scanner') |
|
548
|
|
|
return |
|
549
|
|
|
|
|
550
|
|
|
returnvalue = self._scanning_device.set_up_scanner() |
|
551
|
|
|
if returnvalue < 0: |
|
552
|
|
|
self._scanning_device.unlock() |
|
553
|
|
|
self.unlock() |
|
554
|
|
|
self.set_position('scanner') |
|
555
|
|
|
return |
|
556
|
|
|
|
|
557
|
|
|
self.signal_scan_lines_next.emit() |
|
558
|
|
|
return 0 |
|
559
|
|
|
|
|
560
|
|
|
def continue_scanner(self): |
|
561
|
|
|
"""Continue the scanning procedure |
|
562
|
|
|
|
|
563
|
|
|
@return int: error code (0:OK, -1:error) |
|
564
|
|
|
""" |
|
565
|
|
|
self.lock() |
|
566
|
|
|
self._scanning_device.lock() |
|
567
|
|
|
self._scanning_device.set_up_scanner_clock(clock_frequency=self._clock_frequency) |
|
568
|
|
|
self._scanning_device.set_up_scanner() |
|
569
|
|
|
self.signal_scan_lines_next.emit() |
|
570
|
|
|
return 0 |
|
571
|
|
|
|
|
572
|
|
|
def kill_scanner(self): |
|
573
|
|
|
"""Closing the scanner device. |
|
574
|
|
|
|
|
575
|
|
|
@return int: error code (0:OK, -1:error) |
|
576
|
|
|
""" |
|
577
|
|
|
try: |
|
578
|
|
|
self._scanning_device.close_scanner() |
|
579
|
|
|
self._scanning_device.close_scanner_clock() |
|
580
|
|
|
except Exception as e: |
|
581
|
|
|
self.log.exception('Could not even close the scanner, giving up.') |
|
582
|
|
|
raise e |
|
583
|
|
|
try: |
|
584
|
|
|
self._scanning_device.unlock() |
|
585
|
|
|
except Exception as e: |
|
586
|
|
|
self.log.exception('Could not unlock scanning device.') |
|
587
|
|
|
|
|
588
|
|
|
return 0 |
|
589
|
|
|
|
|
590
|
|
|
def set_position(self, tag, x=None, y=None, z=None, a=None): |
|
591
|
|
|
"""Forwarding the desired new position from the GUI to the scanning device. |
|
592
|
|
|
|
|
593
|
|
|
@param string tag: TODO |
|
594
|
|
|
|
|
595
|
|
|
@param float x: if defined, changes to postion in x-direction (microns) |
|
596
|
|
|
@param float y: if defined, changes to postion in y-direction (microns) |
|
597
|
|
|
@param float z: if defined, changes to postion in z-direction (microns) |
|
598
|
|
|
@param float a: if defined, changes to postion in a-direction (microns) |
|
599
|
|
|
|
|
600
|
|
|
@return int: error code (0:OK, -1:error) |
|
601
|
|
|
""" |
|
602
|
|
|
# print(tag, x, y, z) |
|
603
|
|
|
# Changes the respective value |
|
604
|
|
|
if x is not None: |
|
605
|
|
|
self._current_x = x |
|
606
|
|
|
if y is not None: |
|
607
|
|
|
self._current_y = y |
|
608
|
|
|
if z is not None: |
|
609
|
|
|
self._current_z = z |
|
610
|
|
|
|
|
611
|
|
|
# Checks if the scanner is still running |
|
612
|
|
|
if self.getState() == 'locked' or self._scanning_device.getState() == 'locked': |
|
613
|
|
|
return -1 |
|
614
|
|
|
else: |
|
615
|
|
|
self._change_position(tag) |
|
616
|
|
|
self.signal_change_position.emit(tag) |
|
617
|
|
|
return 0 |
|
618
|
|
|
|
|
619
|
|
|
|
|
620
|
|
|
def _change_position(self, tag): |
|
621
|
|
|
""" Threaded method to change the hardware position. |
|
622
|
|
|
|
|
623
|
|
|
@return int: error code (0:OK, -1:error) |
|
624
|
|
|
""" |
|
625
|
|
|
# if tag == 'optimizer' or tag == 'scanner' or tag == 'activation': |
|
626
|
|
|
self._scanning_device.scanner_set_position( |
|
627
|
|
|
x=self._current_x, |
|
628
|
|
|
y=self._current_y, |
|
629
|
|
|
z=self._current_z, |
|
630
|
|
|
a=self._current_a |
|
631
|
|
|
) |
|
632
|
|
|
return 0 |
|
633
|
|
|
|
|
634
|
|
|
|
|
635
|
|
|
def get_position(self): |
|
636
|
|
|
"""Forwarding the desired new position from the GUI to the scanning device. |
|
637
|
|
|
|
|
638
|
|
|
@return list: with three entries x, y and z denoting the current |
|
639
|
|
|
position in microns |
|
640
|
|
|
""" |
|
641
|
|
|
#FIXME: change that to SI units! |
|
642
|
|
|
return self._scanning_device.get_scanner_position()[:3] |
|
643
|
|
|
|
|
644
|
|
|
|
|
645
|
|
|
def _scan_line(self): |
|
646
|
|
|
"""scanning an image in either depth or xy |
|
647
|
|
|
|
|
648
|
|
|
""" |
|
649
|
|
|
# TODO: change z_values, if z is changed during scan! |
|
650
|
|
|
# stops scanning |
|
651
|
|
|
if self.stopRequested: |
|
652
|
|
|
with self.threadlock: |
|
653
|
|
|
self.kill_scanner() |
|
654
|
|
|
self.stopRequested = False |
|
655
|
|
|
self.unlock() |
|
656
|
|
|
self.signal_xy_image_updated.emit() |
|
657
|
|
|
self.signal_depth_image_updated.emit() |
|
658
|
|
|
self.set_position('scanner') |
|
659
|
|
|
if self._zscan: |
|
660
|
|
|
self._depth_line_pos = self._scan_counter |
|
661
|
|
|
else: |
|
662
|
|
|
self._xy_line_pos = self._scan_counter |
|
663
|
|
|
# add new history entry |
|
664
|
|
|
new_history = ConfocalHistoryEntry(self) |
|
665
|
|
|
new_history.snapshot(self) |
|
666
|
|
|
self.history.append(new_history) |
|
667
|
|
|
if len(self.history) > self.max_history_length: |
|
668
|
|
|
self.history.pop(0) |
|
669
|
|
|
self.history_index = len(self.history) - 1 |
|
670
|
|
|
return |
|
671
|
|
|
|
|
672
|
|
|
if self._zscan: |
|
673
|
|
|
if self.TiltCorrection: |
|
674
|
|
|
image = copy(self.depth_image) |
|
675
|
|
|
image[:, :, 2] += self._calc_dz(x=image[:, :, 0], y=image[:, :, 1]) |
|
676
|
|
|
else: |
|
677
|
|
|
image = self.depth_image |
|
678
|
|
|
else: |
|
679
|
|
|
if self.TiltCorrection: |
|
680
|
|
|
image = copy(self.xy_image) |
|
681
|
|
|
image[:, :, 2] += self._calc_dz(x=image[:, :, 0], y=image[:, :, 1]) |
|
682
|
|
|
else: |
|
683
|
|
|
image = self.xy_image |
|
684
|
|
|
|
|
685
|
|
|
try: |
|
686
|
|
|
if self._scan_counter == 0: |
|
687
|
|
|
# defines trace of positions for single line scan |
|
688
|
|
|
start_line = np.vstack(( |
|
689
|
|
|
np.linspace(self._current_x, image[self._scan_counter, 0, 0], self.return_slowness), |
|
690
|
|
|
np.linspace(self._current_y, image[self._scan_counter, 0, 1], self.return_slowness), |
|
691
|
|
|
np.linspace(self._current_z, image[self._scan_counter, 0, 2], self.return_slowness), |
|
692
|
|
|
np.linspace(self._current_a, 0, self.return_slowness) |
|
693
|
|
|
)) |
|
694
|
|
|
# scan of a single line |
|
695
|
|
|
start_line_counts = self._scanning_device.scan_line(start_line) |
|
696
|
|
|
# defines trace of positions for a single line scan |
|
697
|
|
|
line = np.vstack((image[self._scan_counter, :, 0], |
|
698
|
|
|
image[self._scan_counter, :, 1], |
|
699
|
|
|
image[self._scan_counter, :, 2], |
|
700
|
|
|
image[self._scan_counter, :, 3])) |
|
701
|
|
|
# scan of a single line |
|
702
|
|
|
line_counts = self._scanning_device.scan_line(line) |
|
703
|
|
|
# defines trace of positions for a single return line scan |
|
704
|
|
|
if self.depth_scan_dir_is_xz: |
|
705
|
|
|
return_line = np.vstack(( |
|
706
|
|
|
self._return_XL, |
|
707
|
|
|
image[self._scan_counter, 0, 1] * np.ones(self._return_XL.shape), |
|
708
|
|
|
image[self._scan_counter, 0, 2] * np.ones(self._return_XL.shape), |
|
709
|
|
|
self._return_AL |
|
710
|
|
|
)) |
|
711
|
|
|
else: |
|
712
|
|
|
return_line = np.vstack(( |
|
713
|
|
|
image[self._scan_counter, 0, 1] * np.ones(self._return_YL.shape), |
|
714
|
|
|
self._return_YL, |
|
715
|
|
|
image[self._scan_counter, 0, 2] * np.ones(self._return_YL.shape), |
|
716
|
|
|
self._return_AL |
|
717
|
|
|
)) |
|
718
|
|
|
|
|
719
|
|
|
# scan of a single return-line |
|
720
|
|
|
# This is just needed in order to return the scanner to the start of next line |
|
721
|
|
|
return_line_counts = self._scanning_device.scan_line(return_line) |
|
722
|
|
|
|
|
723
|
|
|
# updating images |
|
724
|
|
|
if self._zscan: |
|
725
|
|
|
if self.depth_scan_dir_is_xz: |
|
726
|
|
|
self.depth_image[self._scan_counter, :, 3] = line_counts |
|
727
|
|
|
else: |
|
728
|
|
|
self.depth_image[self._scan_counter, :, 3] = line_counts |
|
729
|
|
|
self.signal_depth_image_updated.emit() |
|
730
|
|
|
else: |
|
731
|
|
|
self.xy_image[self._scan_counter, :, 3] = line_counts |
|
732
|
|
|
self.signal_xy_image_updated.emit() |
|
733
|
|
|
|
|
734
|
|
|
# call this again from event loop |
|
735
|
|
|
self._scan_counter += 1 |
|
736
|
|
|
# stop scanning when last line scan was performed and makes scan not continuable |
|
737
|
|
|
|
|
738
|
|
|
if self._scan_counter >= np.size(self._image_vert_axis): |
|
739
|
|
|
if not self.permanent_scan: |
|
740
|
|
|
self.stop_scanning() |
|
741
|
|
|
if self._zscan: |
|
742
|
|
|
self._zscan_continuable = False |
|
743
|
|
|
else: |
|
744
|
|
|
self._xyscan_continuable = False |
|
745
|
|
|
else: |
|
746
|
|
|
self._scan_counter = 0 |
|
747
|
|
|
|
|
748
|
|
|
self.signal_scan_lines_next.emit() |
|
749
|
|
|
|
|
750
|
|
|
except Exception as e: |
|
751
|
|
|
self.log.critical('The scan went wrong, killing the scanner.') |
|
752
|
|
|
self.stop_scanning() |
|
753
|
|
|
self.signal_scan_lines_next.emit() |
|
754
|
|
|
raise e |
|
755
|
|
|
|
|
756
|
|
|
|
|
757
|
|
|
def save_xy_data(self, colorscale_range=None, percentile_range=None): |
|
758
|
|
|
""" Save the current confocal xy data to file. |
|
759
|
|
|
|
|
760
|
|
|
Two files are created. The first is the imagedata, which has a text-matrix of count values |
|
761
|
|
|
corresponding to the pixel matrix of the image. Only count-values are saved here. |
|
762
|
|
|
|
|
763
|
|
|
The second file saves the full raw data with x, y, z, and counts at every pixel. |
|
764
|
|
|
|
|
765
|
|
|
A figure is also saved. |
|
766
|
|
|
|
|
767
|
|
|
@param: list colorscale_range (optional) The range [min, max] of the display colour scale (for the figure) |
|
768
|
|
|
|
|
769
|
|
|
@param: list percentile_range (optional) The percentile range [min, max] of the color scale |
|
770
|
|
|
""" |
|
771
|
|
|
save_time = datetime.now() |
|
772
|
|
|
|
|
773
|
|
|
filepath = self._save_logic.get_path_for_module(module_name='Confocal') |
|
774
|
|
|
|
|
775
|
|
|
# Prepare the metadata parameters (common to both saved files): |
|
776
|
|
|
parameters = OrderedDict() |
|
777
|
|
|
|
|
778
|
|
|
parameters['X image min (micrometer)'] = self.image_x_range[0] |
|
779
|
|
|
parameters['X image max (micrometer)'] = self.image_x_range[1] |
|
780
|
|
|
parameters['X image range (micrometer)'] = self.image_x_range[1] - self.image_x_range[0] |
|
781
|
|
|
|
|
782
|
|
|
parameters['Y image min'] = self.image_y_range[0] |
|
783
|
|
|
parameters['Y image max'] = self.image_y_range[1] |
|
784
|
|
|
parameters['Y image range'] = self.image_y_range[1] - self.image_y_range[0] |
|
785
|
|
|
|
|
786
|
|
|
parameters['XY resolution (samples per range)'] = self.xy_resolution |
|
787
|
|
|
parameters['XY Image at z position (micrometer)'] = self._current_z |
|
788
|
|
|
|
|
789
|
|
|
parameters['Clock frequency of scanner (Hz)'] = self._clock_frequency |
|
790
|
|
|
parameters['Return Slowness (Steps during retrace line)'] = self.return_slowness |
|
791
|
|
|
|
|
792
|
|
|
# data for the text-array "image": |
|
793
|
|
|
image_data = OrderedDict() |
|
794
|
|
|
image_data['Confocal pure XY scan image data without axis.\n' |
|
795
|
|
|
'# The upper left entry represents the signal at the upper ' |
|
796
|
|
|
'left pixel position.\n' |
|
797
|
|
|
'# A pixel-line in the image corresponds to a row ' |
|
798
|
|
|
'of entries where the Signal is in counts/s:'] = self.xy_image[:,:,3] |
|
799
|
|
|
|
|
800
|
|
|
# Prepare a figure to be saved |
|
801
|
|
|
figure_data = self.xy_image[:,:,3] |
|
802
|
|
|
image_extent = [self.image_x_range[0], |
|
803
|
|
|
self.image_x_range[1], |
|
804
|
|
|
self.image_y_range[0], |
|
805
|
|
|
self.image_y_range[1] |
|
806
|
|
|
] |
|
807
|
|
|
axes = ['X', 'Y'] |
|
808
|
|
|
crosshair_pos = [self.get_position()[0], self.get_position()[1]] |
|
809
|
|
|
|
|
810
|
|
|
fig = self.draw_figure(data=figure_data, |
|
811
|
|
|
image_extent=image_extent, |
|
812
|
|
|
scan_axis=axes, |
|
813
|
|
|
cbar_range=colorscale_range, |
|
814
|
|
|
percentile_range=percentile_range, |
|
815
|
|
|
crosshair_pos=crosshair_pos |
|
816
|
|
|
) |
|
817
|
|
|
|
|
818
|
|
|
# Save the image data and figure |
|
819
|
|
|
filelabel = 'confocal_xy_image' |
|
820
|
|
|
self._save_logic.save_data(image_data, |
|
821
|
|
|
filepath, |
|
822
|
|
|
parameters=parameters, |
|
823
|
|
|
filelabel=filelabel, |
|
824
|
|
|
as_text=True, |
|
825
|
|
|
timestamp=save_time, |
|
826
|
|
|
plotfig=fig |
|
827
|
|
|
) |
|
828
|
|
|
#, as_xml=False, precision=None, delimiter=None) |
|
829
|
|
|
plt.close(fig) |
|
830
|
|
|
|
|
831
|
|
|
# prepare the full raw data in an OrderedDict: |
|
832
|
|
|
data = OrderedDict() |
|
833
|
|
|
x_data = [] |
|
834
|
|
|
y_data = [] |
|
835
|
|
|
z_data = [] |
|
836
|
|
|
counts_data = [] |
|
837
|
|
|
|
|
838
|
|
|
for row in self.xy_image: |
|
839
|
|
|
for entry in row: |
|
840
|
|
|
x_data.append(entry[0]) |
|
841
|
|
|
y_data.append(entry[1]) |
|
842
|
|
|
z_data.append(entry[2]) |
|
843
|
|
|
counts_data.append(entry[3]) |
|
844
|
|
|
|
|
845
|
|
|
data['x values (micron)'] = x_data |
|
846
|
|
|
data['y values (micron)'] = y_data |
|
847
|
|
|
data['z values (micron)'] = z_data |
|
848
|
|
|
data['count values (c/s)'] = counts_data |
|
849
|
|
|
|
|
850
|
|
|
# Save the raw data to file |
|
851
|
|
|
filelabel = 'confocal_xy_data' |
|
852
|
|
|
self._save_logic.save_data(data, |
|
853
|
|
|
filepath, |
|
854
|
|
|
parameters=parameters, |
|
855
|
|
|
filelabel=filelabel, |
|
856
|
|
|
as_text=True, |
|
857
|
|
|
timestamp=save_time |
|
858
|
|
|
) |
|
859
|
|
|
#, as_xml=False, precision=None, delimiter=None) |
|
860
|
|
|
|
|
861
|
|
|
self.log.debug('Confocal Image saved to:\n{0}'.format(filepath)) |
|
862
|
|
|
|
|
863
|
|
|
def save_depth_data(self, colorscale_range=None, percentile_range=None): |
|
864
|
|
|
""" Save the current confocal depth data to file. |
|
865
|
|
|
|
|
866
|
|
|
Two files are created. The first is the imagedata, which has a text-matrix of count values |
|
867
|
|
|
corresponding to the pixel matrix of the image. Only count-values are saved here. |
|
868
|
|
|
|
|
869
|
|
|
The second file saves the full raw data with x, y, z, and counts at every pixel. |
|
870
|
|
|
""" |
|
871
|
|
|
save_time = datetime.now() |
|
872
|
|
|
|
|
873
|
|
|
filepath = self._save_logic.get_path_for_module(module_name='Confocal') |
|
874
|
|
|
|
|
875
|
|
|
# Prepare the metadata parameters (common to both saved files): |
|
876
|
|
|
parameters = OrderedDict() |
|
877
|
|
|
|
|
878
|
|
|
# TODO: This needs to check whether the scan was XZ or YZ direction |
|
879
|
|
|
parameters['X image min (micrometer)'] = self.image_x_range[0] |
|
880
|
|
|
parameters['X image max (micrometer)'] = self.image_x_range[1] |
|
881
|
|
|
parameters['X image range (micrometer)'] = self.image_x_range[1] - self.image_x_range[0] |
|
882
|
|
|
|
|
883
|
|
|
parameters['Z image min'] = self.image_z_range[0] |
|
884
|
|
|
parameters['Z image max'] = self.image_z_range[1] |
|
885
|
|
|
parameters['Z image range'] = self.image_z_range[1] - self.image_z_range[0] |
|
886
|
|
|
|
|
887
|
|
|
parameters['XY resolution (samples per range)'] = self.xy_resolution |
|
888
|
|
|
parameters['Z resolution (samples per range)'] = self.z_resolution |
|
889
|
|
|
parameters['Depth Image at y position (micrometer)'] = self._current_y |
|
890
|
|
|
|
|
891
|
|
|
parameters['Clock frequency of scanner (Hz)'] = self._clock_frequency |
|
892
|
|
|
parameters['Return Slowness (Steps during retrace line)'] = self.return_slowness |
|
893
|
|
|
|
|
894
|
|
|
# data for the text-array "image": |
|
895
|
|
|
image_data = OrderedDict() |
|
896
|
|
|
image_data['Confocal pure depth scan image data without axis.\n' |
|
897
|
|
|
'# The upper left entry represents the signal at the upper ' |
|
898
|
|
|
'left pixel position.\n' |
|
899
|
|
|
'# A pixel-line in the image corresponds to a row in ' |
|
900
|
|
|
'of entries where the Signal is in counts/s:'] = self.depth_image[:,:,3] |
|
901
|
|
|
|
|
902
|
|
|
# Prepare a figure to be saved |
|
903
|
|
|
figure_data = self.depth_image[:,:,3] |
|
904
|
|
|
|
|
905
|
|
|
if self.depth_scan_dir_is_xz: |
|
906
|
|
|
horizontal_range = [self.image_x_range[0], self.image_x_range[1]] |
|
907
|
|
|
axes = ['X', 'Z'] |
|
908
|
|
|
crosshair_pos = [self.get_position()[0], self.get_position()[2]] |
|
909
|
|
|
else: |
|
910
|
|
|
horizontal_range = [self.image_y_range[0], self.image_y_range[1]] |
|
911
|
|
|
axes = ['Y', 'Z'] |
|
912
|
|
|
crosshair_pos = [self.get_position()[1], self.get_position()[2]] |
|
913
|
|
|
|
|
914
|
|
|
image_extent = [horizontal_range[0], |
|
915
|
|
|
horizontal_range[1], |
|
916
|
|
|
self.image_z_range[0], |
|
917
|
|
|
self.image_z_range[1] |
|
918
|
|
|
] |
|
919
|
|
|
|
|
920
|
|
|
fig = self.draw_figure(data=figure_data, |
|
921
|
|
|
image_extent=image_extent, |
|
922
|
|
|
scan_axis=axes, |
|
923
|
|
|
cbar_range=colorscale_range, |
|
924
|
|
|
percentile_range=percentile_range, |
|
925
|
|
|
crosshair_pos=crosshair_pos |
|
926
|
|
|
) |
|
927
|
|
|
|
|
928
|
|
|
# Save the image data and figure |
|
929
|
|
|
filelabel = 'confocal_xy_image' |
|
930
|
|
|
self._save_logic.save_data(image_data, |
|
931
|
|
|
filepath, |
|
932
|
|
|
parameters=parameters, |
|
933
|
|
|
filelabel=filelabel, |
|
934
|
|
|
as_text=True, |
|
935
|
|
|
timestamp=save_time, |
|
936
|
|
|
plotfig=fig |
|
937
|
|
|
) |
|
938
|
|
|
#, as_xml=False, precision=None, delimiter=None) |
|
939
|
|
|
plt.close(fig) |
|
940
|
|
|
|
|
941
|
|
|
# prepare the full raw data in an OrderedDict: |
|
942
|
|
|
data = OrderedDict() |
|
943
|
|
|
x_data = [] |
|
944
|
|
|
y_data = [] |
|
945
|
|
|
z_data = [] |
|
946
|
|
|
counts_data = [] |
|
947
|
|
|
|
|
948
|
|
|
for row in self.depth_image: |
|
949
|
|
|
for entry in row: |
|
950
|
|
|
x_data.append(entry[0]) |
|
951
|
|
|
y_data.append(entry[1]) |
|
952
|
|
|
z_data.append(entry[2]) |
|
953
|
|
|
counts_data.append(entry[3]) |
|
954
|
|
|
|
|
955
|
|
|
data['x values (micros)'] = x_data |
|
956
|
|
|
data['y values (micros)'] = y_data |
|
957
|
|
|
data['z values (micros)'] = z_data |
|
958
|
|
|
data['count values (micros)'] = counts_data |
|
959
|
|
|
|
|
960
|
|
|
# Save the raw data to file |
|
961
|
|
|
filelabel = 'confocal_depth_data' |
|
962
|
|
|
self._save_logic.save_data(data, |
|
963
|
|
|
filepath, |
|
964
|
|
|
parameters=parameters, |
|
965
|
|
|
filelabel=filelabel, |
|
966
|
|
|
as_text=True, |
|
967
|
|
|
timestamp=save_time |
|
968
|
|
|
) |
|
969
|
|
|
#, as_xml=False, precision=None, delimiter=None) |
|
970
|
|
|
|
|
971
|
|
|
self.log.debug('Confocal Image saved to:\n{0}'.format(filepath)) |
|
972
|
|
|
|
|
973
|
|
|
def draw_figure(self, data, image_extent, scan_axis=None, cbar_range=None, percentile_range=None, crosshair_pos=None): |
|
974
|
|
|
""" Create a 2-D color map figure of the scan image. |
|
975
|
|
|
|
|
976
|
|
|
@param: array data: The NxM array of count values from a scan with NxM pixels. |
|
977
|
|
|
|
|
978
|
|
|
@param: list image_extent: The scan range in the form [hor_min, hor_max, ver_min, ver_max] |
|
979
|
|
|
|
|
980
|
|
|
@param: list axes: Names of the horizontal and vertical axes in the image |
|
981
|
|
|
|
|
982
|
|
|
@param: list cbar_range: (optional) [color_scale_min, color_scale_max]. If not supplied then a default of |
|
983
|
|
|
data_min to data_max will be used. |
|
984
|
|
|
|
|
985
|
|
|
@param: list percentile_range: (optional) Percentile range of the chosen cbar_range. |
|
986
|
|
|
|
|
987
|
|
|
@param: list crosshair_pos: (optional) crosshair position as [hor, vert] in the chosen image axes. |
|
988
|
|
|
|
|
989
|
|
|
@return: fig fig: a matplotlib figure object to be saved to file. |
|
990
|
|
|
""" |
|
991
|
|
|
if scan_axis is None: |
|
992
|
|
|
scan_axis = ['X', 'Y'] |
|
993
|
|
|
|
|
994
|
|
|
# If no colorbar range was given, take full range of data |
|
995
|
|
|
if cbar_range is None: |
|
996
|
|
|
cbar_range = [np.min(data), np.max(data)] |
|
997
|
|
|
|
|
998
|
|
|
# Scale color values using SI prefix |
|
999
|
|
|
prefix = ['', 'k', 'M', 'G'] |
|
1000
|
|
|
prefix_count = 0 |
|
1001
|
|
|
image_data = data |
|
1002
|
|
|
draw_cb_range = np.array(cbar_range) |
|
1003
|
|
|
|
|
1004
|
|
|
while draw_cb_range[1] > 1000: |
|
1005
|
|
|
image_data = image_data/1000 |
|
1006
|
|
|
draw_cb_range = draw_cb_range/1000 |
|
1007
|
|
|
prefix_count = prefix_count + 1 |
|
1008
|
|
|
|
|
1009
|
|
|
c_prefix = prefix[prefix_count] |
|
1010
|
|
|
|
|
1011
|
|
|
# Use qudi style |
|
1012
|
|
|
plt.style.use(self._save_logic.mpl_qd_style) |
|
1013
|
|
|
|
|
1014
|
|
|
# Create figure |
|
1015
|
|
|
fig, ax = plt.subplots() |
|
1016
|
|
|
|
|
1017
|
|
|
# Create image plot |
|
1018
|
|
|
cfimage = ax.imshow(image_data, |
|
1019
|
|
|
cmap=plt.get_cmap('inferno'), # reference the right place in qd |
|
1020
|
|
|
origin="lower", |
|
1021
|
|
|
vmin=draw_cb_range[0], |
|
1022
|
|
|
vmax=draw_cb_range[1], |
|
1023
|
|
|
interpolation='none', |
|
1024
|
|
|
extent=image_extent |
|
1025
|
|
|
) |
|
1026
|
|
|
|
|
1027
|
|
|
ax.set_aspect(1) |
|
1028
|
|
|
ax.set_xlabel(scan_axis[0] + ' position (um)') |
|
1029
|
|
|
ax.set_ylabel(scan_axis[1] + ' position (um)') |
|
1030
|
|
|
ax.spines['bottom'].set_position(('outward', 10)) |
|
1031
|
|
|
ax.spines['left'].set_position(('outward', 10)) |
|
1032
|
|
|
ax.spines['top'].set_visible(False) |
|
1033
|
|
|
ax.spines['right'].set_visible(False) |
|
1034
|
|
|
ax.get_xaxis().tick_bottom() |
|
1035
|
|
|
ax.get_yaxis().tick_left() |
|
1036
|
|
|
|
|
1037
|
|
|
# draw the crosshair position if defined |
|
1038
|
|
|
if crosshair_pos is not None: |
|
1039
|
|
|
trans_xmark = mpl.transforms.blended_transform_factory( |
|
1040
|
|
|
ax.transData, |
|
1041
|
|
|
ax.transAxes) |
|
1042
|
|
|
|
|
1043
|
|
|
trans_ymark = mpl.transforms.blended_transform_factory( |
|
1044
|
|
|
ax.transAxes, |
|
1045
|
|
|
ax.transData) |
|
1046
|
|
|
|
|
1047
|
|
|
ax.annotate('', xy=(crosshair_pos[0], 0), xytext=(crosshair_pos[0], -0.01), xycoords=trans_xmark, |
|
1048
|
|
|
arrowprops=dict(facecolor='#17becf', shrink=0.05), |
|
1049
|
|
|
) |
|
1050
|
|
|
|
|
1051
|
|
|
ax.annotate('', xy=(0, crosshair_pos[1]), xytext=(-0.01, crosshair_pos[1]), xycoords=trans_ymark, |
|
1052
|
|
|
arrowprops=dict(facecolor='#17becf', shrink=0.05), |
|
1053
|
|
|
) |
|
1054
|
|
|
|
|
1055
|
|
|
# Draw the colorbar |
|
1056
|
|
|
cbar = plt.colorbar(cfimage, shrink=0.8)#, fraction=0.046, pad=0.08, shrink=0.75) |
|
1057
|
|
|
cbar.set_label('Fluorescence (' + c_prefix + 'c/s)') |
|
1058
|
|
|
|
|
1059
|
|
|
# remove ticks from colorbar for cleaner image |
|
1060
|
|
|
cbar.ax.tick_params(which=u'both', length=0) |
|
1061
|
|
|
|
|
1062
|
|
|
# If we have percentile information, draw that to the figure |
|
1063
|
|
|
if percentile_range is not None: |
|
1064
|
|
|
cbar.ax.annotate(str(percentile_range[0]), |
|
1065
|
|
|
xy=(-0.3, 0.0), |
|
1066
|
|
|
xycoords='axes fraction', |
|
1067
|
|
|
horizontalalignment='right', |
|
1068
|
|
|
verticalalignment='center', |
|
1069
|
|
|
rotation=90 |
|
1070
|
|
|
) |
|
1071
|
|
|
cbar.ax.annotate(str(percentile_range[1]), |
|
1072
|
|
|
xy=(-0.3, 1.0), |
|
1073
|
|
|
xycoords='axes fraction', |
|
1074
|
|
|
horizontalalignment='right', |
|
1075
|
|
|
verticalalignment='center', |
|
1076
|
|
|
rotation=90 |
|
1077
|
|
|
) |
|
1078
|
|
|
cbar.ax.annotate('(percentile)', |
|
1079
|
|
|
xy=(-0.3, 0.5), |
|
1080
|
|
|
xycoords='axes fraction', |
|
1081
|
|
|
horizontalalignment='right', |
|
1082
|
|
|
verticalalignment='center', |
|
1083
|
|
|
rotation=90 |
|
1084
|
|
|
) |
|
1085
|
|
|
|
|
1086
|
|
|
return fig |
|
1087
|
|
|
|
|
1088
|
|
|
##################################### Tilit correction ######################################## |
|
1089
|
|
|
|
|
1090
|
|
|
def set_tilt_point1(self): |
|
1091
|
|
|
""" Gets the first reference point for tilt correction.""" |
|
1092
|
|
|
self.point1 = np.array(self._scanning_device.get_scanner_position()[:3]) |
|
1093
|
|
|
|
|
1094
|
|
|
def set_tilt_point2(self): |
|
1095
|
|
|
""" Gets the second reference point for tilt correction.""" |
|
1096
|
|
|
self.point2 = np.array(self._scanning_device.get_scanner_position()[:3]) |
|
1097
|
|
|
|
|
1098
|
|
|
def set_tilt_point3(self): |
|
1099
|
|
|
"""Gets the third reference point for tilt correction.""" |
|
1100
|
|
|
self.point3 = np.array(self._scanning_device.get_scanner_position()[:3]) |
|
1101
|
|
|
|
|
1102
|
|
|
def calc_tilt_correction(self): |
|
1103
|
|
|
"""Calculates the values for the tilt correction.""" |
|
1104
|
|
|
a = self.point2 - self.point1 |
|
1105
|
|
|
b = self.point3 - self.point1 |
|
1106
|
|
|
n = np.cross(a,b) |
|
1107
|
|
|
self._scanning_device.tilt_variable_ax = n[0] / n[2] |
|
1108
|
|
|
self._scanning_device.tilt_variable_ay = n[1] / n[2] |
|
1109
|
|
|
|
|
1110
|
|
|
def activate_tiltcorrection(self): |
|
1111
|
|
|
self._scanning_device.tiltcorrection = True |
|
1112
|
|
|
self._scanning_device.tilt_reference_x = self._scanning_device.get_scanner_position()[0] |
|
1113
|
|
|
self._scanning_device.tilt_reference_y = self._scanning_device.get_scanner_position()[1] |
|
1114
|
|
|
|
|
1115
|
|
|
def deactivate_tiltcorrection(self): |
|
1116
|
|
|
self._scanning_device.tiltcorrection = False |
|
1117
|
|
|
self._scanning_device.tilt_reference_x = self._scanning_device.get_scanner_position()[0] |
|
1118
|
|
|
self._scanning_device.tilt_reference_y = self._scanning_device.get_scanner_position()[1] |
|
1119
|
|
|
|
|
1120
|
|
View Code Duplication |
def history_forward(self): |
|
|
|
|
|
|
1121
|
|
|
if self.history_index < len(self.history) - 1: |
|
1122
|
|
|
self.history_index += 1 |
|
1123
|
|
|
self.history[self.history_index].restore(self) |
|
1124
|
|
|
self.signal_xy_image_updated.emit() |
|
1125
|
|
|
self.signal_depth_image_updated.emit() |
|
1126
|
|
|
self._change_position('history') |
|
1127
|
|
|
self.signal_change_position.emit('history') |
|
1128
|
|
|
self.signal_history_event.emit() |
|
1129
|
|
|
|
|
1130
|
|
View Code Duplication |
def history_back(self): |
|
|
|
|
|
|
1131
|
|
|
if self.history_index > 0: |
|
1132
|
|
|
self.history_index -= 1 |
|
1133
|
|
|
self.history[self.history_index].restore(self) |
|
1134
|
|
|
self.signal_xy_image_updated.emit() |
|
1135
|
|
|
self.signal_depth_image_updated.emit() |
|
1136
|
|
|
self._change_position('history') |
|
1137
|
|
|
self.signal_change_position.emit('history') |
|
1138
|
|
|
self.signal_history_event.emit() |
|
1139
|
|
|
|
Ulm-IQO /
qudi
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