def main():
bridge = Bridge()
mmc = bridge.get_core()
# Data set parameters
path = Path('E://20201023//')
name = 'test'
# z stack parameters
start_end_pos = -5
mid_pos = 5
step_size = .25
relative = True
# time series parameters
exposure_time = 200 # in milliseconds
num_z_positions = int(abs(mid_pos - start_end_pos)/step_size + 1)
z_idx = list(range(num_z_positions))
num_time_points = 10
# setup cameras
mmc.set_exposure(exposure_time)
# setup z stage
z_stage = mmc.get_focus_device()
z_pos, pos_sequence = upload_stage_sequence(bridge, start_end_pos, mid_pos, step_size, relative)
num_z_positions = len(pos_sequence)
print(pos_sequence)
# move to first position
mmc.set_position(z_stage, pos_sequence[0])
events = []
z_idx_ = z_idx.copy()
for i in range(num_time_points):
for j in z_idx_:
events.append({'axes': {'time':i, 'z': j}})
z_idx_.reverse()
with Acquisition(directory=path, name=name) as acq:
acq.acquire(events)
# turn off sequencing
mmc.set_property(z_stage, "UseFastSequence", "No")
mmc.set_property(z_stage, "UseSequence", "No")
def main():
#------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------Begin setup of scan parameters--------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------
# lasers to use
# 0 -> inactive
# 1 -> active
state_405 = 1
state_488 = 0
state_561 = 0
state_635 = 1
state_730 = 0
# laser powers (0 -> 100%)
power_405 = 10
power_488 = 0
power_561 = 0
power_635 = 10
power_730 = 0
# exposure time
exposure_ms = 5.
# scan axis limits. Use stage positions reported by MM
scan_axis_start_um = -26000. #unit: um
scan_axis_end_um = -25500. #unit: um
# tile axis limits. Use stage positions reported by MM
tile_axis_start_um = -7000 #unit: um
tile_axis_end_um = -6500. #unit: um
# height axis limits. Use stage positions reported by MM
height_axis_start_um = 345. #unit: um
height_axis_end_um = 375. #unit: um
# FOV parameters
# ONLY MODIFY IF NECESSARY
ROI = [0, 1024, 1599, 255] #unit: pixels
# setup file name
save_directory = Path('E:/20201130/')
save_name = Path('shaffer_lung_v1.h5')
#------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------End setup of scan parameters----------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------
# instantiate the Python-Java bridge to MM
bridge = Bridge()
core = bridge.get_core()
# turn off lasers
core.set_config('Coherent-State', 'off')
core.wait_for_config('Coherent-State', 'off')
# set camera into 16bit readout mode
core.set_property('Camera', 'ReadoutRate', '100MHz 16bit')
time.sleep(1)
# set camera into low noise readout mode
core.set_property('Camera', 'Gain', '2-CMS')
time.sleep(1)
# set camera to trigger first mode
# TO DO: photometrics claims this setting doesn't exist in PVCAM. Why is it necessary then?
core.set_property('Camera', 'Trigger Timeout (secs)', 300)
time.sleep(1)
# set camera to internal trigger
core.set_property('Camera', 'TriggerMode', 'Internal Trigger')
time.sleep(1)
# change core timeout for long stage moves
core.set_property('Core', 'TimeoutMs', 100000)
# crop FOV
#core.set_roi(*ROI)
# set exposure
core.set_exposure(exposure_ms)
# grab one image to determine actual framerate
# get actual framerate from micromanager properties
actual_readout_ms = float(core.get_property(
'Camera', 'ActualInterval-ms')) #unit: ms
# camera pixel size
pixel_size_um = .115 # unit: um
# scan axis setup
scan_axis_step_um = 0.4 # unit: um
scan_axis_step_mm = scan_axis_step_um / 1000. #unit: mm
scan_axis_start_mm = scan_axis_start_um / 1000. #unit: mm
scan_axis_end_mm = scan_axis_end_um / 1000. #unit: mm
scan_axis_range_um = np.abs(scan_axis_end_um -
scan_axis_start_um) # unit: um
scan_axis_range_mm = scan_axis_range_um / 1000 #unit: mm
actual_exposure_s = actual_readout_ms / 1000. #unit: s
scan_axis_speed = np.round(scan_axis_step_mm / actual_exposure_s,
2) #unit: mm/s
scan_axis_positions = np.rint(scan_axis_range_mm /
scan_axis_step_mm).astype(
int) #unit: number of positions
# tile axis setup
tile_axis_overlap = 0.2 #unit: percentage
tile_axis_range_um = np.abs(tile_axis_end_um -
tile_axis_start_um) #unit: um
tile_axis_range_mm = tile_axis_range_um / 1000 #unit: mm
tile_axis_ROI = ROI[2] * pixel_size_um #unit: um
tile_axis_step_um = np.round((tile_axis_ROI) * (1 - tile_axis_overlap),
2) #unit: um
tile_axis_step_mm = tile_axis_step_um / 1000 #unit: mm
tile_axis_positions = np.rint(tile_axis_range_mm /
tile_axis_step_mm).astype(
int) #unit: number of positions
# if tile_axis_positions rounded to zero, make sure we acquire at least one position
if tile_axis_positions == 0:
tile_axis_positions = 1
# height axis setup
# this is more complicated, since we have an oblique light sheet
# the height of the scan is the length of the ROI in the tilted direction * sin(tilt angle)
height_axis_overlap = 0.2 #unit: percentage
height_axis_range_um = np.abs(height_axis_end_um -
height_axis_start_um) #unit: um
height_axis_range_mm = height_axis_range_um / 1000 #unit: mm
height_axis_ROI = ROI[3] * pixel_size_um * np.sin(
30 * (np.pi / 180.)) #unit: um
height_axis_step_um = np.round(
(height_axis_ROI) * (1 - height_axis_overlap), 2) #unit: um
height_axis_step_mm = height_axis_step_um / 1000 #unit: mm
height_axis_positions = np.rint(height_axis_range_mm /
height_axis_step_mm).astype(
int) #unit: number of positions
# if height_axis_positions rounded to zero, make sure we acquire at least one position
if height_axis_positions == 0:
height_axis_positions = 1
# get handle to xy and z stages
xy_stage = core.get_xy_stage_device()
z_stage = core.get_focus_device()
# Setup PLC card to give start trigger
plcName = 'PLogic:E:36'
propPosition = 'PointerPosition'
propCellConfig = 'EditCellConfig'
#addrOutputBNC3 = 35
addrOutputBNC1 = 33
addrStageSync = 46 # TTL5 on Tiger backplane = stage sync signal
# connect stage sync signal to BNC output
core.set_property(plcName, propPosition, addrOutputBNC1)
core.set_property(plcName, propCellConfig, addrStageSync)
# turn on 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub', 'OnlySendSerialCommandOnChange', 'No')
# set tile axis speed for all moves
command = 'SPEED Y=.1'
core.set_property('TigerCommHub', 'SerialCommand', command)
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand', command)
ready = core.get_property('TigerCommHub', 'SerialResponse')
time.sleep(.500)
# set scan axis speed for large move to initial position
command = 'SPEED X=.1'
core.set_property('TigerCommHub', 'SerialCommand', command)
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand', command)
ready = core.get_property('TigerCommHub', 'SerialResponse')
time.sleep(.500)
# turn off 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub', 'OnlySendSerialCommandOnChange', 'Yes')
# move scan scan stage to initial position
core.set_xy_position(scan_axis_start_um, tile_axis_start_um)
core.wait_for_device(xy_stage)
core.set_position(height_axis_start_um)
core.wait_for_device(z_stage)
# turn on 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub', 'OnlySendSerialCommandOnChange', 'No')
# set scan axis speed to correct speed for continuous stage scan
# expects mm/s
command = 'SPEED X=' + str(scan_axis_speed)
core.set_property('TigerCommHub', 'SerialCommand', command)
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand', command)
ready = core.get_property('TigerCommHub', 'SerialResponse')
time.sleep(.500)
# set scan axis to true 1D scan with no backlash
command = '1SCAN X? Y=0 Z=9 F=0'
core.set_property('TigerCommHub', 'SerialCommand', command)
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand', command)
ready = core.get_property('TigerCommHub', 'SerialResponse')
time.sleep(.500)
# set range and return speed (10% of max) for scan axis
# expects mm
command = '1SCANR X=' + str(scan_axis_start_mm) + ' Y=' + str(
scan_axis_end_mm) + ' R=10'
core.set_property('TigerCommHub', 'SerialCommand', command)
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand', command)
ready = core.get_property('TigerCommHub', 'SerialResponse')
time.sleep(.500)
# turn off 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub', 'OnlySendSerialCommandOnChange', 'Yes')
# construct boolean array for lasers to use
channel_states = [state_405, state_488, state_561, state_635, state_730]
channel_powers = [power_405, power_488, power_561, power_635, power_730]
# set lasers to user defined power
core.set_property('Coherent-Scientific Remote',
'Laser 405-100C - PowerSetpoint (%)', channel_powers[0])
core.set_property('Coherent-Scientific Remote',
'Laser 488-150C - PowerSetpoint (%)', channel_powers[1])
core.set_property('Coherent-Scientific Remote',
'Laser OBIS LS 561-150 - PowerSetpoint (%)',
channel_powers[2])
core.set_property('Coherent-Scientific Remote',
'Laser 637-140C - PowerSetpoint (%)', channel_powers[3])
core.set_property('Coherent-Scientific Remote',
'Laser 730-30C - PowerSetpoint (%)', channel_powers[4])
# calculate total tiles
total_tiles = tile_axis_positions * height_axis_positions
# output acquisition metadata
print('Number of X positions: ' + str(scan_axis_positions))
print('Number of Y tiles: ' + str(tile_axis_positions))
print('Number of Z slabs: ' + str(height_axis_positions))
print('Number of channels:' + str(np.sum(channel_states)))
print('Number of BDV H5 tiles: ' + str(total_tiles))
# define unit tranformation matrix
unit_matrix = np.array((
(1.0, 0.0, 0.0, 0.0), # change the 4. value for x_translation (px)
(0.0, 1.0, 0.0, 0.0), # change the 4. value for y_translation (px)
(0.0, 0.0, 1.0, 0.0))) # change the 4. value for z_translation (px)
# create BDV H5 using npy2bdv
fname = save_directory / save_name
bdv_writer = npy2bdv.BdvWriter(fname,
nchannels=np.sum(channel_states),
ntiles=total_tiles,
subsamp=((1, 1, 1), ),
blockdim=((1, 128, 256), ))
# reset tile index for BDV H5 file
tile_index = 0
for y in range(tile_axis_positions):
# calculate tile axis position
tile_position_um = tile_axis_start_um + (tile_axis_step_um * y)
# move XY stage to new tile axis position
core.set_xy_position(scan_axis_start_um, tile_position_um)
core.wait_for_device(xy_stage)
for z in range(height_axis_positions):
print('Tile index: ' + str(tile_index))
# calculate height axis position
height_position_um = height_axis_start_um + (height_axis_step_um *
z)
# move Z stage to new height axis position
core.set_position(height_position_um)
core.wait_for_device(z_stage)
# reset channel index for BDV H5 file
channel_index = 0
for c in range(len(channel_states)):
# determine active channel
if channel_states[c] == 1:
if (c == 0):
core.set_config('Coherent-State', '405nm')
core.wait_for_config('Coherent-State', '405nm')
elif (c == 1):
core.set_config('Coherent-State', '488nm')
core.wait_for_config('Coherent-State', '488nm')
elif (c == 2):
core.set_config('Coherent-State', '561nm')
core.wait_for_config('Coherent-State', '561nm')
elif (c == 3):
core.set_config('Coherent-State', '637nm')
core.wait_for_config('Coherent-State', '637nm')
elif (c == 4):
core.set_config('Coherent-State', '730nm')
core.wait_for_config('Coherent-State', '730nm')
print('Channel index: ' + str(channel_index))
print('Active channel: ' + str(c))
# set camera to trigger first mode for stage synchronization
core.set_property('Camera', 'TriggerMode', 'Trigger first')
time.sleep(1)
# get current X, Y, and Z stage positions for translation transformation
point = core.get_xy_stage_position()
x_now = point.get_x()
y_now = point.get_y()
z_now = core.get_position(z_stage)
# calculate affine matrix components for translation transformation
affine_matrix = unit_matrix
affine_matrix[
0,
3] = y_now / pixel_size_um # x axis in BDV H5 (tile axis on scope).
affine_matrix[1, 3] = z_now / (
pixel_size_um * np.sin(30. * np.pi / 180.)
) # y axis in BDV H5 (height axis on scope).
affine_matrix[2, 3] = x_now / (
pixel_size_um * np.cos(30. * np.pi / 180.)
) # z axis in BDV H5 (scan axis on scope).
# turn off 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub',
'OnlySendSerialCommandOnChange', 'No')
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand',
command)
ready = core.get_property('TigerCommHub',
'SerialResponse')
time.sleep(.500)
# turn off 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub',
'OnlySendSerialCommandOnChange', 'Yes')
# start acquistion
core.start_sequence_acquisition(int(scan_axis_positions),
float(0.0), True)
# tell stage to execute scan
command = '1SCAN'
core.set_property('TigerCommHub', 'SerialCommand', command)
# reset image counter
image_counter = 0
# place stack into BDV H5
bdv_writer.append_view(
stack=None,
virtual_stack_dim=(scan_axis_positions, ROI[3],
ROI[2]),
time=0,
channel=channel_index,
tile=tile_index,
m_affine=affine_matrix,
name_affine='stage translation',
voxel_size_xyz=(.115, .115, .200),
voxel_units='um')
# grab images from buffer
while (image_counter < scan_axis_positions):
# if there are images in the buffer, grab and process
if (core.get_remaining_image_count() > 0):
# grab top image in buffer
tagged_image = core.pop_next_tagged_image()
# grab metadata to convert 1D array to 2D image
image_height = tagged_image.tags['Height']
image_width = tagged_image.tags['Width']
# convert to 2D image and place into virtual stack in BDV H5
bdv_writer.append_plane(plane=np.flipud(
tagged_image.pix.reshape(
(image_height, image_width))),
plane_index=image_counter,
time=0,
channel=channel_index)
# increment image counter
image_counter = image_counter + 1
# no images in buffer, wait for another image to arrive.
else:
time.sleep(np.minimum(.01 * exposure_ms, 1) / 1000)
# clean up acquistion
core.stop_sequence_acquisition()
# turn off lasers
core.set_config('Coherent-State', 'off')
core.wait_for_config('Coherent-State', 'off')
# set camera to internal trigger
# this is necessary to avoid PVCAM driver issues that we keep having for long acquisitions.
core.set_property('Camera', 'TriggerMode',
'Internal Trigger')
time.sleep(1)
# increment channel index for BDV H5 file
channel_index = channel_index + 1
# turn off 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub',
'OnlySendSerialCommandOnChange', 'No')
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand',
command)
ready = core.get_property('TigerCommHub',
'SerialResponse')
time.sleep(.500)
# turn off 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub',
'OnlySendSerialCommandOnChange', 'Yes')
# increment tile index for BDV H5
tile_index = tile_index + 1
# write BDV XML and close BDV H5
bdv_writer.write_xml_file(ntimes=1)
bdv_writer.close()
from skimage import morphology
from shared.analysis import central_pixel_without_cells, bleach_location
from shared.find_blobs import select
# variables
from shared.find_organelles import find_organelle
nr = 40
nr_between_projector_checks = 2
cal_exposure = 200
cal_offset = 5
n_curve = 500
# build up pycromanager bridge
bridge = Bridge()
mmc = bridge.get_core()
mm = bridge.get_studio()
projector = bridge.construct_java_object(
"org.micromanager.projector.ProjectorAPI")
projector_device = projector.get_projection_device()
def snap_and_get_bleach_location(exposure, cutoff):
"""
Takes an image with the current settings. Finds a location close to the center where there are
no objects (as defined in function central_picel_without_cells). If no such location is found, returns -1.
Targets bleacher to this location, exposes and takes an image of that exposure. Finds the center of the
actual bleach spot. When the square of the distance between the intended target and the actual bleach spot is
greater than provided offset, will execute a full calibration.
:param exposure: exposure time to use for bleaching
"""
https://pycro-manager.readthedocs.io/en/latest/core.html
This example shows how to use pycromanager to interact with the micro-manager core.
Aside from the setup section, each following section can be run independently
"""
from pycromanager import Bridge
import numpy as np
import matplotlib.pyplot as plt
#### Setup ####
with Bridge() as bridge:
#get object representing micro-manager core
core = bridge.get_core()
#### Calling core functions ###
exposure = core.get_exposure()
#### Setting and getting properties ####
#Here we set a property of the core itself, but same code works for device properties
auto_shutter = core.get_property('Core', 'AutoShutter')
core.set_property('Core', 'AutoShutter', 0)
#### Acquiring images ####
#The micro-manager core exposes several mechanisms foor acquiring images. In order to
#not interfere with other pycromanager functionality, this is the one that should be used
core.snap_image()
tagged_image = core.get_tagged_image()
#If using micro-manager multi-camera adapter, use core.getTaggedImage(i), where i is
#the camera index
from pycromanager import Bridge, Acquisition
import numpy as np
bridge = Bridge()
# get object representing micro-magellan API
magellan = bridge.get_magellan()
def hook_fn(event):
coordinates = np.array([event["x"], event["y"], event["z"]])
return event
if __name__ == "__main__":
# magellan example
acq = Acquisition(magellan_acq_index=0, post_hardware_hook_fn=hook_fn)
acq.await_completion()
pass
from pycromanager import Acquisition, multi_d_acquisition_events, Bridge, start_headless
import time
mm_app_path = '/Applications/Micro-Manager-2.0.0-gamma1'
# mm_app_path = 'C:/Program Files/Micro-Manager-2.0gamma'
config_file = mm_app_path + "/MMConfig_demo.cfg"
#Optional: specify your own version of java to run with
java_loc = "/Library/Internet Plug-Ins/JavaAppletPlugin.plugin/Contents/Home/bin/java"
# java_loc = None
start_headless(mm_app_path, config_file, java_loc=java_loc, port=5000)
with Bridge(port=5000) as b:
b.get_core().snap_image()
print(b.get_core().get_image())
save_dir = "/Users/henrypinkard/tmp"
# save_dir = "C:/Users/Henry Pinkard/Desktop/datadump"
with Acquisition(directory=save_dir, name="tcz_acq", port=5000) as acq:
# Generate the events for a single z-stack
events = multi_d_acquisition_events(
num_time_points=5,
time_interval_s=0,
channel_group="Channel",
channels=["DAPI", "FITC"],
z_start=0,
z_end=6,
z_step=0.4,
order="tcz",
def main():
#------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------Begin setup of scan parameters--------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------
# lasers to use
# 0 -> inactive
# 1 -> active
state_405 = 1
state_488 = 0
state_561 = 0
state_635 = 1
state_730 = 0
# laser powers (0 -> 100%)
power_405 = 10
power_488 = 0
power_561 = 0
power_635 = 5
power_730 = 0
# exposure time
exposure_ms = 5.
# scan axis limits. Use stage positions reported by MM
scan_axis_start_um = 6000. #unit: um
scan_axis_end_um = 16000. #unit: um
# tile axis limits. Use stage positions reported by MM
tile_axis_start_um = -1300 #unit: um
tile_axis_end_um = -1350. #unit: um
# height axis limits. Use stage positions reported by MM
height_axis_start_um = 320. #unit: um
height_axis_end_um = 360. #unit: um
# FOV parameters
# ONLY MODIFY IF NECESSARY
ROI = [0, 1024, 1599, 255] #unit: pixels
# setup file name
save_directory = Path('E:/20201211/')
save_name = 'shaffer_lung'
#------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------End setup of scan parameters----------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------
bridge = Bridge()
core = bridge.get_core()
# turn off lasers
core.set_config('Coherent-State', 'off')
core.wait_for_config('Coherent-State', 'off')
# set camera into 16bit readout mode
# give camera time to change modes if necessary
core.set_property('Camera', 'ReadoutRate', '100MHz 16bit')
time.sleep(1)
# set camera into low noise readout mode
# give camera time to change modes if necessary
core.set_property('Camera', 'Gain', '2-CMS')
time.sleep(1)
# set camera to trigger first mode
# give camera time to change modes if necessary
core.set_property('Camera', 'Trigger Timeout (secs)', 300)
time.sleep(1)
# set camera to internal trigger
# give camera time to change modes if necessary
core.set_property('Camera', 'TriggerMode', 'Internal Trigger')
time.sleep(1)
# change core timeout for long stage moves
time.sleep(1)
# crop FOV
#core.set_roi(*ROI)
# set exposure
core.set_exposure(exposure_ms)
# get actual framerate from micromanager properties
# TO DO: fix need for user to have manually run an exposure with correct crop to get this value
actual_readout_ms = float(core.get_property(
'Camera', 'ActualInterval-ms')) #unit: ms
# camera pixel size
pixel_size_um = .115 # unit: um
# scan axis setup
scan_axis_step_um = 0.2 # unit: um
scan_axis_step_mm = scan_axis_step_um / 1000. #unit: mm
scan_axis_start_mm = scan_axis_start_um / 1000. #unit: mm
scan_axis_end_mm = scan_axis_end_um / 1000. #unit: mm
scan_axis_range_um = np.abs(scan_axis_end_um -
scan_axis_start_um) # unit: um
scan_axis_range_mm = scan_axis_range_um / 1000 #unit: mm
actual_exposure_s = actual_readout_ms / 1000. #unit: s
scan_axis_speed = np.round(scan_axis_step_mm / actual_exposure_s,
2) #unit: mm/s
scan_axis_positions = np.rint(scan_axis_range_mm /
scan_axis_step_mm).astype(
int) #unit: number of positions
# tile axis setup
tile_axis_overlap = 0.2 #unit: percentage
tile_axis_range_um = np.abs(tile_axis_end_um -
tile_axis_start_um) #unit: um
tile_axis_range_mm = tile_axis_range_um / 1000 #unit: mm
tile_axis_ROI = ROI[2] * pixel_size_um #unit: um
tile_axis_step_um = np.round((tile_axis_ROI) * (1 - tile_axis_overlap),
2) #unit: um
tile_axis_step_mm = tile_axis_step_um / 1000 #unit: mm
tile_axis_positions = np.rint(tile_axis_range_mm /
tile_axis_step_mm).astype(
int) #unit: number of positions
# if tile_axis_positions rounded to zero, make sure we acquire at least one position
if tile_axis_positions == 0:
tile_axis_positions = 1
# height axis setup
height_axis_overlap = 0.2 #unit: percentage
height_axis_range_um = np.abs(height_axis_end_um -
height_axis_start_um) #unit: um
height_axis_range_mm = height_axis_range_um / 1000 #unit: mm
#height_axis_ROI = ROI[3]*pixel_size_um*np.sin(30*(np.pi/180.)) #unit: um TO DO: Why is overlap so large when using oblique pixel height??
height_axis_ROI = ROI[3] * pixel_size_um #unit: um
height_axis_step_um = np.round(
(height_axis_ROI) * (1 - height_axis_overlap), 2) #unit: um
height_axis_step_mm = height_axis_step_um / 1000 #unit: mm
height_axis_positions = np.rint(height_axis_range_mm /
height_axis_step_mm).astype(
int) #unit: number of positions
# if height_axis_positions rounded to zero, make sure we acquire at least one position
if height_axis_positions == 0:
height_axis_positions = 1
# get handle to xy and z stages
xy_stage = core.get_xy_stage_device()
z_stage = core.get_focus_device()
# Setup Tiger controller to pass signal when the scan stage cross the start position to the PLC
plcName = 'PLogic:E:36'
propPosition = 'PointerPosition'
propCellConfig = 'EditCellConfig'
#addrOutputBNC3 = 35 # BNC3 on the PLC front panel
addrOutputBNC1 = 33 # BNC1 on the PLC front panel
addrStageSync = 46 # TTL5 on Tiger backplane = stage sync signal
# connect stage sync signal to BNC output
core.set_property(plcName, propPosition, addrOutputBNC1)
core.set_property(plcName, propCellConfig, addrStageSync)
# turn on 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub', 'OnlySendSerialCommandOnChange', 'No')
# set tile axis speed for all moves
command = 'SPEED Y=.1'
core.set_property('TigerCommHub', 'SerialCommand', command)
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand', command)
ready = core.get_property('TigerCommHub', 'SerialResponse')
time.sleep(.500)
# set scan axis speed for large move to initial position
command = 'SPEED X=.1'
core.set_property('TigerCommHub', 'SerialCommand', command)
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand', command)
ready = core.get_property('TigerCommHub', 'SerialResponse')
time.sleep(.500)
# turn off 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub', 'OnlySendSerialCommandOnChange', 'Yes')
# move scan scan stage to initial position
core.set_xy_position(scan_axis_start_um, tile_axis_start_um)
core.wait_for_device(xy_stage)
core.set_position(height_axis_start_um)
core.wait_for_device(z_stage)
# turn on 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub', 'OnlySendSerialCommandOnChange', 'No')
# set scan axis speed to correct speed for continuous stage scan
# expects mm/s
command = 'SPEED X=' + str(scan_axis_speed)
core.set_property('TigerCommHub', 'SerialCommand', command)
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand', command)
ready = core.get_property('TigerCommHub', 'SerialResponse')
time.sleep(.500)
# set scan axis to true 1D scan with no backlash
command = '1SCAN X? Y=0 Z=9 F=0'
core.set_property('TigerCommHub', 'SerialCommand', command)
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand', command)
ready = core.get_property('TigerCommHub', 'SerialResponse')
time.sleep(.500)
# set range and return speed (5% of max) for scan axis
# expects mm
command = '1SCANR X=' + str(scan_axis_start_mm) + ' Y=' + str(
scan_axis_end_mm) + ' R=10'
core.set_property('TigerCommHub', 'SerialCommand', command)
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand', command)
ready = core.get_property('TigerCommHub', 'SerialResponse')
time.sleep(.500)
# turn off 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub', 'OnlySendSerialCommandOnChange', 'Yes')
# construct boolean array for lasers to use
channel_states = [state_405, state_488, state_561, state_635, state_730]
channel_powers = [power_405, power_488, power_561, power_635, power_730]
# set lasers to user defined power
core.set_property('Coherent-Scientific Remote',
'Laser 405-100C - PowerSetpoint (%)', channel_powers[0])
core.set_property('Coherent-Scientific Remote',
'Laser 488-150C - PowerSetpoint (%)', channel_powers[1])
core.set_property('Coherent-Scientific Remote',
'Laser OBIS LS 561-150 - PowerSetpoint (%)',
channel_powers[2])
core.set_property('Coherent-Scientific Remote',
'Laser 637-140C - PowerSetpoint (%)', channel_powers[3])
core.set_property('Coherent-Scientific Remote',
'Laser 730-30C - PowerSetpoint (%)', channel_powers[4])
print('Number of X positions: ' + str(scan_axis_positions))
print('Number of Y tiles: ' + str(tile_axis_positions))
print('Number of Z slabs: ' + str(height_axis_positions))
#time.sleep(10)
for y in range(tile_axis_positions):
# calculate tile axis position
tile_position_um = tile_axis_start_um + (tile_axis_step_um * y)
# move XY stage to new tile axis position
core.set_xy_position(scan_axis_start_um, tile_position_um)
core.wait_for_device(xy_stage)
for z in range(height_axis_positions):
# calculate height axis position
height_position_um = height_axis_start_um + (height_axis_step_um *
z)
# move Z stage to new height axis position
core.set_position(height_position_um)
core.wait_for_device(z_stage)
# create events to execute scan across this z plane
events = []
for c in range(len(channel_states)):
for x in range(
scan_axis_positions + 10
): #TO DO: Fix need for extra frames in ASI setup, not here.
if channel_states[c] == 1:
if (c == 0):
evt = {
'axes': {
'z': x
},
'channel': {
'group': 'Coherent-State',
'config': '405nm'
}
}
elif (c == 1):
evt = {
'axes': {
'z': x
},
'channel': {
'group': 'Coherent-State',
'config': '488nm'
}
}
elif (c == 2):
evt = {
'axes': {
'z': x
},
'channel': {
'group': 'Coherent-State',
'config': '561nm'
}
}
elif (c == 3):
evt = {
'axes': {
'z': x
},
'channel': {
'group': 'Coherent-State',
'config': '637nm'
}
}
elif (c == 4):
evt = {
'axes': {
'z': x
},
'channel': {
'group': 'Coherent-State',
'config': '730nm'
}
}
events.append(evt)
# set camera to trigger first mode for stage synchronization
# give camera time to change modes
core.set_property('Camera', 'TriggerMode', 'Trigger first')
time.sleep(1)
# update save_name with current Z plane
save_name_z = save_name + '_y' + str(y).zfill(4) + '_z' + str(
z).zfill(4)
# run acquisition at this Z plane
with Acquisition(directory=save_directory,
name=save_name_z,
post_hardware_hook_fn=post_hook_fn,
post_camera_hook_fn=camera_hook_fn,
show_display=False,
max_multi_res_index=0) as acq:
acq.acquire(events)
# added this code in an attempt to clean up resources, given the ZMQ error we are getting when using two hooks
acq.acquire(None)
acq.await_completion()
# try to clean up acquisition so that AcqEngJ releases directory. This way we can move it to the network storage
# in the background.
acq = None
# turn off lasers
core.set_config('Coherent-State', 'off')
core.wait_for_config('Coherent-State', 'off')
# set camera to internal trigger
# this is necessary to avoid PVCAM driver issues that we keep having for long acquisitions.
# give camera time to change modes
core.set_property('Camera', 'TriggerMode', 'Internal Trigger')
time.sleep(1)
def main():
#------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------Begin setup of scan parameters--------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------
# set up lasers
channel_labels = ["405", "488", "561", "635", "730"]
channel_states = [False, False, True, False,
False] # true -> active, false -> inactive
channel_powers = [30, 30, 100, 100, 0] # (0 -> 100%)
do_ind = [0, 1, 2, 3,
4] # digital output line corresponding to each channel
# parse which channels are active
active_channel_indices = [
ind for ind, st in zip(do_ind, channel_states) if st
]
n_active_channels = len(active_channel_indices)
print("%d active channels: " % n_active_channels, end="")
for ind in active_channel_indices:
print("%s " % channel_labels[ind], end="")
print("")
# exposure time
exposure_ms = 2.0 #unit: ms
# scan axis range
scan_axis_range_um = 20.0 # unit: microns
# galvo voltage at neutral
#galvo_neutral_volt = 0 # unit: volts
galvo_neutral_volt = -.150
scan_axis_step_um = 0.4 # unit: um
# timepoints
timepoints = 400
# timepoint interval (s)
timing_interval = 0
# setup file name
save_directory = Path('D:/20211204')
save_name = 'fla-suc40'
# automatically transfer files to NAS at end of dataset
transfer_files = False
# display data
display_flag = False
#------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------End setup of scan parameters----------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------
with Bridge() as bridge:
core = bridge.get_core()
# give camera time to change modes if necessary
core.set_config('Camera-Setup', 'ScanMode3')
core.wait_for_config('Camera-Setup', 'ScanMode3')
# set camera to internal trigger
core.set_config('Camera-TriggerSource', 'INTERNAL')
core.wait_for_config('Camera-TriggerSource', 'INTERNAL')
# set camera to internal trigger
# give camera time to change modes if necessary
core.set_property('OrcaFusionBT', 'OUTPUT TRIGGER KIND[0]', 'EXPOSURE')
core.set_property('OrcaFusionBT', 'OUTPUT TRIGGER KIND[1]', 'EXPOSURE')
core.set_property('OrcaFusionBT', 'OUTPUT TRIGGER KIND[2]', 'EXPOSURE')
core.set_property('OrcaFusionBT', 'OUTPUT TRIGGER POLARITY[0]',
'POSITIVE')
core.set_property('OrcaFusionBT', 'OUTPUT TRIGGER POLARITY[1]',
'POSITIVE')
core.set_property('OrcaFusionBT', 'OUTPUT TRIGGER POLARITY[2]',
'POSITIVE')
# set exposure time
core.set_exposure(exposure_ms)
# determine image size
core.snap_image()
y_pixels = core.get_image_height()
x_pixels = core.get_image_width()
# turn all lasers on
core.set_config('Laser', 'Off')
core.wait_for_config('Laser', 'Off')
# set all laser to external triggering
core.set_config('Modulation-405', 'External-Digital')
core.wait_for_config('Modulation-405', 'External-Digital')
core.set_config('Modulation-488', 'External-Digital')
core.wait_for_config('Modulation-488', 'External-Digital')
core.set_config('Modulation-561', 'External-Digital')
core.wait_for_config('Modulation-561', 'External-Digital')
core.set_config('Modulation-637', 'External-Digital')
core.wait_for_config('Modulation-637', 'External-Digital')
core.set_config('Modulation-730', 'External-Digital')
core.wait_for_config('Modulation-730', 'External-Digital')
# turn all lasers on
core.set_config('Laser', 'AllOn')
core.wait_for_config('Laser', 'AllOn')
core.set_property('Coherent-Scientific Remote',
'Laser 405-100C - PowerSetpoint (%)',
channel_powers[0])
core.set_property('Coherent-Scientific Remote',
'Laser 488-150C - PowerSetpoint (%)',
channel_powers[1])
core.set_property('Coherent-Scientific Remote',
'Laser OBIS LS 561-150 - PowerSetpoint (%)',
channel_powers[2])
core.set_property('Coherent-Scientific Remote',
'Laser 637-140C - PowerSetpoint (%)',
channel_powers[3])
core.set_property('Coherent-Scientific Remote',
'Laser 730-30C - PowerSetpoint (%)',
channel_powers[4])
# camera pixel size
pixel_size_um = .115 # unit: um
# galvo scan setup
scan_axis_calibration = 0.043 # unit: V / um
min_volt = -(scan_axis_range_um * scan_axis_calibration /
2.) + galvo_neutral_volt # unit: volts
scan_axis_step_volts = scan_axis_step_um * scan_axis_calibration # unit: V
scan_axis_range_volts = scan_axis_range_um * scan_axis_calibration # unit: V
scan_steps = np.rint(scan_axis_range_volts / scan_axis_step_volts).astype(
np.int16) # galvo steps
# handle case where no scan steps
if scan_steps == 0:
scan_steps = 1
# output experiment info
print(
"Scan axis range: %.1f um = %0.3fV, Scan axis step: %.1f nm = %0.3fV , Number of galvo positions: %d"
% (scan_axis_range_um, scan_axis_range_volts, scan_axis_step_um * 1000,
scan_axis_step_volts, scan_steps))
print('Galvo neutral (Volt): ' + str(galvo_neutral_volt) +
', Min voltage (volt): ' + str(min_volt))
print('Time points: ' + str(timepoints))
# create events to execute scan
events = []
# Changes to event structure motivated by Henry's notes that pycromanager struggles to read "non-standard" axes.
# https://github.com/micro-manager/pycro-manager/issues/220
for t in range(timepoints):
for x in range(scan_steps):
ch_idx = 0
for c in range(len(do_ind)):
if channel_states[c]:
if timing_interval == 0:
evt = {'axes': {'t': t, 'z': x, 'c': ch_idx}}
else:
evt = {
'axes': {
't': t,
'z': x,
'c': ch_idx
},
'min_start_time': t * timing_interval
}
ch_idx = ch_idx + 1
events.append(evt)
print("Generated %d events" % len(events))
# setup DAQ
nvoltage_steps = scan_steps
# 2 time steps per frame, except for first frame plus one final frame to reset voltage
#samples_per_ch = (nvoltage_steps * 2 - 1) + 1
samples_per_ch = (nvoltage_steps * 2 * n_active_channels - 1) + 1
DAQ_sample_rate_Hz = 10000
#retriggerable = True
num_DI_channels = 8
# Generate values for DO
dataDO = np.zeros((samples_per_ch, num_DI_channels), dtype=np.uint8)
for ii, ind in enumerate(active_channel_indices):
dataDO[2 * ii::2 * n_active_channels, ind] = 1
dataDO[-1, :] = 0
# generate voltage steps
max_volt = min_volt + scan_axis_range_volts # 2
voltage_values = np.linspace(min_volt, max_volt, nvoltage_steps)
# Generate values for AO
waveform = np.zeros(samples_per_ch)
# one less voltage value for first frame
waveform[0:2 * n_active_channels - 1] = voltage_values[0]
if len(voltage_values) > 1:
# (2 * # active channels) voltage values for all other frames
waveform[2 * n_active_channels - 1:-1] = np.kron(
voltage_values[1:], np.ones(2 * n_active_channels))
# set back to initial value at end
waveform[-1] = voltage_values[0]
#def read_di_hook(event):
try:
# ----- DIGITAL input -------
taskDI = daq.Task()
taskDI.CreateDIChan("/Dev1/PFI0", "", daq.DAQmx_Val_ChanForAllLines)
## Configure change detectin timing (from wave generator)
taskDI.CfgInputBuffer(
0) # must be enforced for change-detection timing, i.e no buffer
taskDI.CfgChangeDetectionTiming("/Dev1/PFI0", "/Dev1/PFI0",
daq.DAQmx_Val_ContSamps, 0)
## Set where the starting trigger
taskDI.CfgDigEdgeStartTrig("/Dev1/PFI0", daq.DAQmx_Val_Rising)
## Export DI signal to unused PFI pins, for clock and start
taskDI.ExportSignal(daq.DAQmx_Val_ChangeDetectionEvent, "/Dev1/PFI2")
taskDI.ExportSignal(daq.DAQmx_Val_StartTrigger, "/Dev1/PFI1")
# ----- DIGITAL output ------
taskDO = daq.Task()
# TO DO: Write each laser line separately!
taskDO.CreateDOChan("/Dev1/port0/line0:7", "",
daq.DAQmx_Val_ChanForAllLines)
## Configure timing (from DI task)
taskDO.CfgSampClkTiming("/Dev1/PFI2", DAQ_sample_rate_Hz,
daq.DAQmx_Val_Rising, daq.DAQmx_Val_ContSamps,
samples_per_ch)
## Write the output waveform
samples_per_ch_ct_digital = ct.c_int32()
taskDO.WriteDigitalLines(samples_per_ch, False, 10.0,
daq.DAQmx_Val_GroupByChannel, dataDO,
ct.byref(samples_per_ch_ct_digital), None)
# ------- ANALOG output -----------
# first, set the galvo to the initial point if it is not already
taskAO_first = daq.Task()
taskAO_first.CreateAOVoltageChan("/Dev1/ao0", "", -6.0, 6.0,
daq.DAQmx_Val_Volts, None)
taskAO_first.WriteAnalogScalarF64(True, -1, waveform[0], None)
taskAO_first.StopTask()
taskAO_first.ClearTask()
# now set up the task to ramp the galvo
taskAO = daq.Task()
taskAO.CreateAOVoltageChan("/Dev1/ao0", "", -6.0, 6.0,
daq.DAQmx_Val_Volts, None)
## Configure timing (from DI task)
taskAO.CfgSampClkTiming("/Dev1/PFI2", DAQ_sample_rate_Hz,
daq.DAQmx_Val_Rising, daq.DAQmx_Val_ContSamps,
samples_per_ch)
## Write the output waveform
samples_per_ch_ct = ct.c_int32()
taskAO.WriteAnalogF64(samples_per_ch, False, 10.0,
daq.DAQmx_Val_GroupByScanNumber, waveform,
ct.byref(samples_per_ch_ct), None)
## ------ Start both tasks ----------
taskAO.StartTask()
taskDO.StartTask()
taskDI.StartTask()
except daq.DAQError as err:
print("DAQmx Error %s" % err)
# run acquisition
with Acquisition(directory=save_directory,
name=save_name,
show_display=display_flag,
max_multi_res_index=0,
saving_queue_size=5000) as acq:
acq.acquire(events)
acq = None
# stop DAQ
try:
## Stop and clear both tasks
taskDI.StopTask()
taskDO.StopTask()
taskAO.StopTask()
taskDI.ClearTask()
taskAO.ClearTask()
taskDO.ClearTask()
except daq.DAQError as err:
print("DAQmx Error %s" % err)
# save galvo scan parameters
scan_param_data = [{
'root_name': str(save_name),
'scan_type': 'galvo',
'theta': 30.0,
'exposure_ms': exposure_ms,
'scan_step': scan_axis_step_um * 1000.,
'pixel_size': pixel_size_um * 1000.,
'galvo_scan_range_um': scan_axis_range_um,
'galvo_volts_per_um': scan_axis_calibration,
'num_t': int(timepoints),
'num_y': 1, # might need to change this eventually
'num_z': 1, # might need to change this eventually
'num_ch': int(n_active_channels),
'scan_axis_positions': int(scan_steps),
'y_pixels': y_pixels,
'x_pixels': x_pixels,
'405_active': channel_states[0],
'488_active': channel_states[1],
'561_active': channel_states[2],
'635_active': channel_states[3],
'730_active': channel_states[4]
}]
data_io.write_metadata(scan_param_data[0],
save_directory / 'scan_metadata.csv')
with Bridge() as bridge:
core = bridge.get_core()
# turn all lasers off
core.set_config('Laser', 'Off')
core.wait_for_config('Laser', 'Off')
# set all lasers back to software control
core.set_config('Modulation-405', 'CW (constant power)')
core.wait_for_config('Modulation-405', 'CW (constant power)')
core.set_config('Modulation-488', 'CW (constant power)')
core.wait_for_config('Modulation-488', 'CW (constant power)')
core.set_config('Modulation-561', 'CW (constant power)')
core.wait_for_config('Modulation-561', 'CW (constant power)')
core.set_config('Modulation-637', 'CW (constant power)')
core.wait_for_config('Modulation-637', 'CW (constant power)')
core.set_config('Modulation-730', 'CW (constant power)')
core.wait_for_config('Modulation-730', 'CW (constant power)')
# set all laser to zero power
channel_powers = [0, 0, 0, 0, 0]
core.set_property('Coherent-Scientific Remote',
'Laser 405-100C - PowerSetpoint (%)',
channel_powers[0])
core.set_property('Coherent-Scientific Remote',
'Laser 488-150C - PowerSetpoint (%)',
channel_powers[1])
core.set_property('Coherent-Scientific Remote',
'Laser OBIS LS 561-150 - PowerSetpoint (%)',
channel_powers[2])
core.set_property('Coherent-Scientific Remote',
'Laser 637-140C - PowerSetpoint (%)',
channel_powers[3])
core.set_property('Coherent-Scientific Remote',
'Laser 730-30C - PowerSetpoint (%)',
channel_powers[4])
# put the galvo back to neutral
# first, set the galvo to the initial point if it is not already
taskAO_last = daq.Task()
taskAO_last.CreateAOVoltageChan("/Dev1/ao0", "", -6.0, 6.0,
daq.DAQmx_Val_Volts, None)
taskAO_last.WriteAnalogScalarF64(True, -1, galvo_neutral_volt, None)
taskAO_last.StopTask()
taskAO_last.ClearTask()
if transfer_files:
# make parent directory on NAS and start reconstruction script on the server
# make home directory on NAS
save_directory_path = Path(save_directory)
remote_directory = Path('y:/') / Path(save_directory_path.parts[1])
cmd = 'mkdir ' + str(remote_directory)
status_mkdir = subprocess.run(cmd, shell=True)
# copy full experiment metadata to NAS
src = Path(save_directory) / Path('scan_metadata.csv')
dst = Path(remote_directory) / Path('scan_metadata.csv')
Thread(target=shutil.copy, args=[str(src), str(dst)]).start()
# copy data to NAS
save_directory_path = Path(save_directory)
remote_directory = Path('y:/') / Path(save_directory_path.parts[1])
src = Path(save_directory) / Path(save_name + '_1')
dst = Path(remote_directory) / Path(save_name + '_1')
Thread(target=shutil.copytree, args=[str(src), str(dst)]).start()
from pycromanager import Acquisition, multi_d_acquisition_events, Bridge, start_headless
mm_app_path = '/Applications/Micro-Manager-2.0.0-gamma1'
# mm_app_path = 'C:/Program Files/Micro-Manager-2.0gamma'
config_file = mm_app_path + "/MMConfig_demo.cfg"
#Optional: specify your own version of java to run with
java_loc = "/Library/Internet Plug-Ins/JavaAppletPlugin.plugin/Contents/Home/bin/java"
# java_loc = None
start_headless(mm_app_path, config_file, java_loc=java_loc)
b = Bridge()
b.get_core().snap_image()
print(b.get_core().get_image())
save_dir = "/Users/henrypinkard/tmp"
# save_dir = "C:/Users/Henry Pinkard/Desktop/datadump"
with Acquisition(directory=save_dir, name="tcz_acq", debug=True) as acq:
# Generate the events for a single z-stack
events = multi_d_acquisition_events(
num_time_points=5,
time_interval_s=0,
channel_group="Channel",
channels=["DAPI", "FITC"],
z_start=0,
z_end=6,
z_step=0.4,
order="tcz",
)
def main():
bridge = Bridge()
core = bridge.get_core()
# FOV parameters
ROI = [1024, 0, 256, 1024] #unit: pixels
# camera exposure
exposure_ms = 5 #unit: ms
# set to high-res camera
core.set_config('Camera', 'HighRes')
# crop FOV
core.set_roi(*ROI)
# set exposure
core.set_exposure(exposure_ms)
# setup file name
save_directory = Path('C:/data/test/')
save_name = 'test_stages'
# get handle to xy and z stages
xy_stage = core.get_xy_stage_device()
z_stage = core.get_focus_device()
# move the stages to verify core can talk to them
# positions chosen at random
core.set_xy_position(100., 100.)
core.wait_for_device(xy_stage)
core.set_position(50.)
core.wait_for_device(z_stage)
# create events to hold all of the scan axis images during constant speed stage scan
channel_configs = ['DAPI', 'FITC', 'Rhodamine', 'Cy5']
events = []
for y in range(2):
for z in range(2):
for c in range(len(channel_configs)):
for x in range(2):
evt = {
'axes': {
'x': x,
'y': y,
'z': z
},
'x': 100,
'y': y * 1000,
'z': z * 100,
'channel': {
'group': 'Channel',
'config': channel_configs[c]
}
}
events.append(evt)
# run acquisition
# TO DO: properly handle an error here if camera driver fails to return expected number of images.
with Acquisition(directory=save_directory,
name=save_name,
post_hardware_hook_fn=setup_scan_fn,
post_camera_hook_fn=hook_fn,
show_display=False,
max_multi_res_index=0,
debug=False) as acq:
acq.acquire(events)
acq.acquire(None)
acq.await_completion()
layer_names = ['GFP', 'RFP']
# initialize global variables
# flag to break while loops
acq_running = False
# empty queue for image data and z positions
img_queue = queue.Queue()
# xyz data stack
data = np.random.rand(z_range[2], clip[0], clip[1]) * clim[1]
# if z-stage is controlled through micromanager:
# need bridge to move stage at beginning of stack
# USE WITH CAUTION: only tested with micromanager demo config
if not (simulate) and not (z_stack_external):
from pycromanager import Bridge
bridge = Bridge()
#get object representing micro-manager core
core = bridge.get_core()
print(core)
core.set_position(z_range[0])
#########################################################################
# function to write data into queue #
#########################################################################
def place_data(image):
""" fnc to place image data into the queue.
Keeps track of z-position in stacks and of active color channels.
Inputs: np.array image: image data
Global variables: image_queue to write image and z position
z_range to keep track of z position
def main():
#------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------Begin setup of scan parameters--------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------
# set up lasers
channel_labels = ["405", "488", "561", "635", "730"]
channel_states = [False, False, True, False,
False] # true -> active, false -> inactive
channel_powers = [50, 10, 90, 100, 95] # (0 -> 100%)
do_ind = [0, 1, 2, 3,
4] # digital output line corresponding to each channel
# parse which channels are active
active_channel_indices = [
ind for ind, st in zip(do_ind, channel_states) if st
]
n_active_channels = len(active_channel_indices)
print("%d active channels: " % n_active_channels, end="")
for ind in active_channel_indices:
print("%s " % channel_labels[ind], end="")
print("")
# exposure time
exposure_ms = 50.0
# excess scan positions
excess_scan_positions = 10
# galvo voltage at neutral
galvo_neutral_volt = -0.15 # unit: volts
# scan axis limits. Use stage positions reported by MM
scan_axis_start_um = 8680. #unit: um
scan_axis_end_um = 8800. #unit: um
# tile axis limits. Use stage positions reported by MM
tile_axis_start_um = -3841.28 #unit: um
tile_axis_end_um = -3841.28 #unit: um
# height axis limits. Use stage positions reported by MM
height_axis_start_um = 13128.63 #unit: um
height_axis_end_um = 13128.63 #unit: um
# number of timepoints to execute
# TO DO: add in control for rate of experiment
timepoints = 1
# FOV parameters
# ONLY MODIFY IF NECESSARY
# ROI = [0, 1152, 2304, 512] #unit: pixels
# setup file name
save_directory = Path('D:/20210831')
save_name = 'stage_scan'
#------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------End setup of scan parameters----------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------
# connect to Micromanager instance
bridge = Bridge()
core = bridge.get_core()
# turn off lasers
core.set_config('Laser', 'Off')
core.wait_for_config('Laser', 'Off')
# set camera to fast readout mode
core.set_config('Camera-Setup', 'ScanMode3')
core.wait_for_config('Camera-Setup', 'ScanMode3')
# set camera to START mode upon input trigger
core.set_config('Camera-TriggerType', 'START')
core.wait_for_config('Camera-TriggerType', 'START')
# set camera to positive input trigger
core.set_config('Camera-TriggerPolarity', 'POSITIVE')
core.wait_for_config('Camera-TriggerPolarity', 'POSITIVE')
# set camera to internal control
core.set_config('Camera-TriggerSource', 'INTERNAL')
core.wait_for_config('Camera-TriggerSource', 'INTERNAL')
# set camera to output positive triggers on all lines for exposure
core.set_property('OrcaFusionBT', 'OUTPUT TRIGGER KIND[0]', 'EXPOSURE')
core.set_property('OrcaFusionBT', 'OUTPUT TRIGGER KIND[1]', 'EXPOSURE')
core.set_property('OrcaFusionBT', 'OUTPUT TRIGGER KIND[2]', 'EXPOSURE')
core.set_property('OrcaFusionBT', 'OUTPUT TRIGGER POLARITY[0]', 'POSITIVE')
core.set_property('OrcaFusionBT', 'OUTPUT TRIGGER POLARITY[1]', 'POSITIVE')
core.set_property('OrcaFusionBT', 'OUTPUT TRIGGER POLARITY[2]', 'POSITIVE')
# change core timeout for long stage moves
core.set_property('Core', 'TimeoutMs', 100000)
time.sleep(1)
# set exposure
core.set_exposure(exposure_ms)
# determine image size
core.snap_image()
y_pixels = core.get_image_height()
x_pixels = core.get_image_width()
# grab exposure
true_exposure = core.get_exposure()
# get actual framerate from micromanager properties
actual_readout_ms = true_exposure + float(
core.get_property('OrcaFusionBT', 'ReadoutTime')) #unit: ms
# camera pixel size
pixel_size_um = .115 # unit: um
# scan axis setup
scan_axis_step_um = 0.4 # unit: um
scan_axis_step_mm = scan_axis_step_um / 1000. #unit: mm
scan_axis_start_mm = scan_axis_start_um / 1000. #unit: mm
scan_axis_end_mm = scan_axis_end_um / 1000. #unit: mm
scan_axis_range_um = np.abs(scan_axis_end_um -
scan_axis_start_um) # unit: um
scan_axis_range_mm = scan_axis_range_um / 1000 #unit: mm
actual_exposure_s = actual_readout_ms / 1000. #unit: s
scan_axis_speed = np.round(scan_axis_step_mm / actual_exposure_s,
4) #unit: mm/s
scan_axis_positions = np.rint(scan_axis_range_mm /
scan_axis_step_mm).astype(
int) #unit: number of positions
# tile axis setup
tile_axis_overlap = 0.2 #unit: percentage
tile_axis_range_um = np.abs(tile_axis_end_um -
tile_axis_start_um) #unit: um
tile_axis_range_mm = tile_axis_range_um / 1000 #unit: mm
tile_axis_ROI = x_pixels * pixel_size_um #unit: um
tile_axis_step_um = np.round((tile_axis_ROI) * (1 - tile_axis_overlap),
2) #unit: um
tile_axis_step_mm = tile_axis_step_um / 1000 #unit: mm
tile_axis_positions = np.rint(
tile_axis_range_mm /
tile_axis_step_mm).astype(int) + 1 #unit: number of positions
# if tile_axis_positions rounded to zero, make sure we acquire at least one position
if tile_axis_positions == 0:
tile_axis_positions = 1
# height axis setup
height_axis_overlap = 0.2 #unit: percentage
height_axis_range_um = np.abs(height_axis_end_um -
height_axis_start_um) #unit: um
height_axis_range_mm = height_axis_range_um / 1000 #unit: mm
height_axis_ROI = y_pixels * pixel_size_um * np.sin(
30. * np.pi / 180.) #unit: um
height_axis_step_um = np.round(
(height_axis_ROI) * (1 - height_axis_overlap), 2) #unit: um
height_axis_step_mm = height_axis_step_um / 1000 #unit: mm
height_axis_positions = np.rint(
height_axis_range_mm /
height_axis_step_mm).astype(int) + 1 #unit: number of positions
# if height_axis_positions rounded to zero, make sure we acquire at least one position
if height_axis_positions == 0:
height_axis_positions = 1
# get handle to xy and z stages
xy_stage = core.get_xy_stage_device()
z_stage = core.get_focus_device()
# galvo voltage at neutral
galvo_neutral_volt = -.15 # unit: volts
# set the galvo to the neutral position if it is not already
try:
taskAO_first = daq.Task()
taskAO_first.CreateAOVoltageChan("/Dev1/ao0", "", -4.0, 4.0,
daq.DAQmx_Val_Volts, None)
taskAO_first.WriteAnalogScalarF64(True, -1, galvo_neutral_volt, None)
taskAO_first.StopTask()
taskAO_first.ClearTask()
except:
print("DAQmx Error %s" % err)
# Setup Tiger controller to pass signal when the scan stage cross the start position to the PLC
plcName = 'PLogic:E:36'
propPosition = 'PointerPosition'
propCellConfig = 'EditCellConfig'
#addrOutputBNC3 = 35 # BNC3 on the PLC front panel
addrOutputBNC1 = 33 # BNC1 on the PLC front panel
addrStageSync = 46 # TTL5 on Tiger backplane = stage sync signal
# connect stage sync signal to BNC output
core.set_property(plcName, propPosition, addrOutputBNC1)
core.set_property(plcName, propCellConfig, addrStageSync)
# turn on 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub', 'OnlySendSerialCommandOnChange', 'No')
# set tile axis speed for all moves
command = 'SPEED Y=.1'
core.set_property('TigerCommHub', 'SerialCommand', command)
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand', command)
ready = core.get_property('TigerCommHub', 'SerialResponse')
time.sleep(.500)
# set scan axis speed for large move to initial position
command = 'SPEED X=.1'
core.set_property('TigerCommHub', 'SerialCommand', command)
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand', command)
ready = core.get_property('TigerCommHub', 'SerialResponse')
time.sleep(.500)
# turn off 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub', 'OnlySendSerialCommandOnChange', 'Yes')
# move scan scan stage to initial position
core.set_xy_position(scan_axis_start_um, tile_axis_start_um)
core.wait_for_device(xy_stage)
core.set_position(height_axis_start_um)
core.wait_for_device(z_stage)
# turn on 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub', 'OnlySendSerialCommandOnChange', 'No')
# set scan axis speed to correct speed for continuous stage scan
# expects mm/s
command = 'SPEED X=' + str(scan_axis_speed)
core.set_property('TigerCommHub', 'SerialCommand', command)
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand', command)
ready = core.get_property('TigerCommHub', 'SerialResponse')
time.sleep(.500)
# set scan axis to true 1D scan with no backlash
command = '1SCAN X? Y=0 Z=9 F=0'
core.set_property('TigerCommHub', 'SerialCommand', command)
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand', command)
ready = core.get_property('TigerCommHub', 'SerialResponse')
time.sleep(.500)
# set range and return speed (5% of max) for scan axis
# expects mm
command = '1SCANR X=' + str(scan_axis_start_mm) + ' Y=' + str(
scan_axis_end_mm) + ' R=10'
core.set_property('TigerCommHub', 'SerialCommand', command)
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand', command)
ready = core.get_property('TigerCommHub', 'SerialResponse')
time.sleep(.500)
# turn off 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub', 'OnlySendSerialCommandOnChange', 'Yes')
# set all laser to external triggering
core.set_config('Modulation-405', 'External-Digital')
core.wait_for_config('Modulation-405', 'External-Digital')
core.set_config('Modulation-488', 'External-Digital')
core.wait_for_config('Modulation-488', 'External-Digital')
core.set_config('Modulation-561', 'External-Digital')
core.wait_for_config('Modulation-561', 'External-Digital')
core.set_config('Modulation-637', 'External-Digital')
core.wait_for_config('Modulation-637', 'External-Digital')
core.set_config('Modulation-730', 'External-Digital')
core.wait_for_config('Modulation-730', 'External-Digital')
# turn all lasers on
core.set_config('Laser', 'AllOn')
core.wait_for_config('Laser', 'AllOn')
# set lasers to user defined power
core.set_property('Coherent-Scientific Remote',
'Laser 405-100C - PowerSetpoint (%)', channel_powers[0])
core.set_property('Coherent-Scientific Remote',
'Laser 488-150C - PowerSetpoint (%)', channel_powers[1])
core.set_property('Coherent-Scientific Remote',
'Laser OBIS LS 561-150 - PowerSetpoint (%)',
channel_powers[2])
core.set_property('Coherent-Scientific Remote',
'Laser 637-140C - PowerSetpoint (%)', channel_powers[3])
core.set_property('Coherent-Scientific Remote',
'Laser 730-30C - PowerSetpoint (%)', channel_powers[4])
# setup DAQ
samples_per_ch = 2
DAQ_sample_rate_Hz = 10000
num_DI_channels = 8
# set the galvo to neutral
taskAO_last = daq.Task()
taskAO_last.CreateAOVoltageChan("/Dev1/ao0", "", -4.0, 4.0,
daq.DAQmx_Val_Volts, None)
taskAO_last.WriteAnalogScalarF64(True, -1, galvo_neutral_volt, None)
taskAO_last.StopTask()
taskAO_last.ClearTask()
# output experiment info
print('Number of X positions: ' + str(scan_axis_positions))
print('Number of Y tiles: ' + str(tile_axis_positions))
print('Number of Z slabs: ' + str(height_axis_positions))
print('Number of channels: ' + str(n_active_channels))
# flags for metadata and processing
setup_processing = True
setup_metadata = True
# create events to execute scan
events = []
for x in range(scan_axis_positions + excess_scan_positions):
evt = {'axes': {'z': x}}
events.append(evt)
for t_idx in range(timepoints):
for y_idx in range(tile_axis_positions):
# calculate tile axis position
tile_position_um = tile_axis_start_um + (tile_axis_step_um * y_idx)
# move XY stage to new tile axis position
core.set_xy_position(scan_axis_start_um, tile_position_um)
core.wait_for_device(xy_stage)
for z_idx in range(height_axis_positions):
# calculate height axis position
height_position_um = height_axis_start_um + (
height_axis_step_um * z_idx)
# move Z stage to new height axis position
core.set_position(height_position_um)
core.wait_for_device(z_stage)
for ch_idx in active_channel_indices:
# create DAQ pattern for laser strobing controlled via rolling shutter
dataDO = np.zeros((samples_per_ch, num_DI_channels),
dtype=np.uint8)
dataDO[0, ch_idx] = 1
dataDO[1, ch_idx] = 0
#print(dataDO)
# update save_name with current tile information
save_name_tyzc = save_name + '_t' + str(t_idx).zfill(
4) + '_y' + str(y_idx).zfill(4) + '_z' + str(
z_idx).zfill(4) + '_ch' + str(ch_idx).zfill(4)
# turn on 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub',
'OnlySendSerialCommandOnChange', 'No')
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand',
command)
ready = core.get_property('TigerCommHub',
'SerialResponse')
time.sleep(.500)
# turn off 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub',
'OnlySendSerialCommandOnChange', 'Yes')
# save actual stage positions
xy_pos = core.get_xy_stage_position()
stage_x = xy_pos.x
stage_y = xy_pos.y
stage_z = core.get_position()
current_stage_data = [{
'stage_x': stage_x,
'stage_y': stage_y,
'stage_z': stage_z
}]
df_current_stage = pd.DataFrame(current_stage_data)
# setup DAQ for laser strobing
try:
# ----- DIGITAL input -------
taskDI = daq.Task()
taskDI.CreateDIChan("/Dev1/PFI0", "",
daq.DAQmx_Val_ChanForAllLines)
## Configure change detection timing (from wave generator)
taskDI.CfgInputBuffer(
0
) # must be enforced for change-detection timing, i.e no buffer
taskDI.CfgChangeDetectionTiming(
"/Dev1/PFI0", "/Dev1/PFI0",
daq.DAQmx_Val_ContSamps, 0)
## Set where the starting trigger
taskDI.CfgDigEdgeStartTrig("/Dev1/PFI0",
daq.DAQmx_Val_Rising)
## Export DI signal to unused PFI pins, for clock and start
taskDI.ExportSignal(daq.DAQmx_Val_ChangeDetectionEvent,
"/Dev1/PFI2")
taskDI.ExportSignal(daq.DAQmx_Val_StartTrigger,
"/Dev1/PFI1")
# ----- DIGITAL output ------
taskDO = daq.Task()
taskDO.CreateDOChan("/Dev1/port0/line0:7", "",
daq.DAQmx_Val_ChanForAllLines)
## Configure timing (from DI task)
taskDO.CfgSampClkTiming("/Dev1/PFI2",
DAQ_sample_rate_Hz,
daq.DAQmx_Val_Rising,
daq.DAQmx_Val_ContSamps,
samples_per_ch)
## Write the output waveform
samples_per_ch_ct_digital = ct.c_int32()
taskDO.WriteDigitalLines(
samples_per_ch, False, 10.0,
daq.DAQmx_Val_GroupByChannel, dataDO,
ct.byref(samples_per_ch_ct_digital), None)
## ------ Start digital input and output tasks ----------
taskDO.StartTask()
taskDI.StartTask()
except daq.DAQError as err:
print("DAQmx Error %s" % err)
# set camera to external control
# DCAM sets the camera back to INTERNAL mode after each acquisition
core.set_config('Camera-TriggerSource', 'EXTERNAL')
core.wait_for_config('Camera-TriggerSource', 'EXTERNAL')
# verify that camera actually switched back to external trigger mode
trigger_state = core.get_property('OrcaFusionBT',
'TRIGGER SOURCE')
# if not in external control, keep trying until camera changes settings
while not (trigger_state == 'EXTERNAL'):
time.sleep(2.0)
core.set_config('Camera-TriggerSource', 'EXTERNAL')
core.wait_for_config('Camera-TriggerSource',
'EXTERNAL')
trigger_state = core.get_property(
'OrcaFusionBT', 'TRIGGER SOURCE')
print('T: ' + str(t_idx) + ' Y: ' + str(y_idx) + ' Z: ' +
str(z_idx) + ' C: ' + str(ch_idx))
# run acquisition for this tyzc combination
with Acquisition(directory=save_directory,
name=save_name_tyzc,
post_camera_hook_fn=camera_hook_fn,
show_display=False,
max_multi_res_index=0,
saving_queue_size=5000) as acq:
acq.acquire(events)
# clean up acquisition so that AcqEngJ releases directory.
# NOTE: This currently does not work.
acq = None
acq_deleted = False
while not (acq_deleted):
try:
del acq
except:
time.sleep(0.1)
acq_deleted = False
else:
gc.collect()
acq_deleted = True
# stop DAQ and make sure it is at zero
try:
## Stop and clear both tasks
taskDI.StopTask()
taskDO.StopTask()
taskDI.ClearTask()
taskDO.ClearTask()
except daq.DAQError as err:
print("DAQmx Error %s" % err)
# save experimental info after first tile.
# we do it this way so that Pycromanager can manage the directories.
if (setup_metadata):
# save stage scan parameters
scan_param_data = [{
'root_name':
str(save_name),
'scan_type':
str('stage'),
'theta':
float(30.0),
'scan_step':
float(scan_axis_step_um * 1000.),
'pixel_size':
float(pixel_size_um * 1000.),
'num_t':
int(timepoints),
'num_y':
int(tile_axis_positions),
'num_z':
int(height_axis_positions),
'num_ch':
int(n_active_channels),
'scan_axis_positions':
int(scan_axis_positions),
'excess_scan_positions':
int(excess_scan_positions),
'y_pixels':
int(y_pixels),
'x_pixels':
int(x_pixels),
'405_active':
bool(channel_states[0]),
'488_active':
bool(channel_states[1]),
'561_active':
bool(channel_states[2]),
'635_active':
bool(channel_states[3]),
'730_active':
bool(channel_states[4])
}]
# df_stage_scan_params = pd.DataFrame(scan_param_data)
# save_name_stage_params = save_directory / 'scan_metadata.csv'
# df_stage_scan_params.to_csv(save_name_stage_params)
data_io.write_metadata(
scan_param_data[0],
save_directory / Path('scan_metadata.csv'))
setup_metadata = False
# save stage scan positions after each tile
save_name_stage_positions = Path('t' +
str(t_idx).zfill(4) +
'_y' +
str(y_idx).zfill(4) +
'_z' +
str(z_idx).zfill(4) +
'_ch' +
str(ch_idx).zfill(4) +
'_stage_positions.csv')
save_name_stage_positions = save_directory / save_name_stage_positions
# todo: use data_io instead
df_current_stage.to_csv(save_name_stage_positions)
# turn on 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub',
'OnlySendSerialCommandOnChange', 'No')
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand',
command)
ready = core.get_property('TigerCommHub',
'SerialResponse')
time.sleep(.500)
# turn off 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub',
'OnlySendSerialCommandOnChange', 'Yes')
'''
# if first tile, make parent directory on NAS and start reconstruction script on the server
if setup_processing:
# make home directory on NAS
save_directory_path = Path(save_directory)
remote_directory = Path('y:/') / Path(save_directory_path.parts[1])
cmd='mkdir ' + str(remote_directory)
status_mkdir = subprocess.run(cmd, shell=True)
# copy full experiment metadata to NAS
src= Path(save_directory) / Path('scan_metadata.csv')
dst= Path(remote_directory) / Path('scan_metadata.csv')
Thread(target=shutil.copy, args=[str(src), str(dst)]).start()
setup_processing=False
# copy current tyzc metadata to NAS
save_directory_path = Path(save_directory)
remote_directory = Path('y:/') / Path(save_directory_path.parts[1])
src= Path(save_directory) / Path(save_name_stage_positions.parts[2])
dst= Path(remote_directory) / Path(save_name_stage_positions.parts[2])
Thread(target=shutil.copy, args=[str(src), str(dst)]).start()
# copy current tyzc data to NAS
save_directory_path = Path(save_directory)
remote_directory = Path('y:/') / Path(save_directory_path.parts[1])
src= Path(save_directory) / Path(save_name_tyzc+ '_1')
dst= Path(remote_directory) / Path(save_name_tyzc+ '_1')
Thread(target=shutil.copytree, args=[str(src), str(dst)]).start()
'''
# set lasers to zero power
channel_powers = [0., 0., 0., 0., 0.]
core.set_property('Coherent-Scientific Remote',
'Laser 405-100C - PowerSetpoint (%)', channel_powers[0])
core.set_property('Coherent-Scientific Remote',
'Laser 488-150C - PowerSetpoint (%)', channel_powers[1])
core.set_property('Coherent-Scientific Remote',
'Laser OBIS LS 561-150 - PowerSetpoint (%)',
channel_powers[2])
core.set_property('Coherent-Scientific Remote',
'Laser 637-140C - PowerSetpoint (%)', channel_powers[3])
core.set_property('Coherent-Scientific Remote',
'Laser 730-30C - PowerSetpoint (%)', channel_powers[4])
# turn all lasers off
core.set_config('Laser', 'Off')
core.wait_for_config('Laser', 'Off')
# set all lasers back to software control
core.set_config('Modulation-405', 'CW (constant power)')
core.wait_for_config('Modulation-405', 'CW (constant power)')
core.set_config('Modulation-488', 'CW (constant power)')
core.wait_for_config('Modulation-488', 'CW (constant power)')
core.set_config('Modulation-561', 'CW (constant power)')
core.wait_for_config('Modulation-561', 'CW (constant power)')
core.set_config('Modulation-637', 'CW (constant power)')
core.wait_for_config('Modulation-637', 'CW (constant power)')
core.set_config('Modulation-730', 'CW (constant power)')
core.wait_for_config('Modulation-730', 'CW (constant power)')
# set camera to internal control
core.set_config('Camera-TriggerSource', 'INTERNAL')
core.wait_for_config('Camera-TriggerSource', 'INTERNAL')
bridge.close()
def __init__(self,
app,
args=None,
parent=None,
spatial_subsampling=4,
time_subsampling=1):
"""
Intrinsic Imaging GUI
"""
self.app = app
super(MainWindow, self).__init__(i=1, title='intrinsic imaging')
# some initialisation
self.running, self.stim, self.STIM = False, None, None
self.datafolder, self.img, self.vasculature_img = '', None, None
self.t0, self.period = 0, 1
### trying the camera
try:
# we initialize the camera
self.bridge = Bridge()
self.core = self.bridge.get_core()
self.exposure = self.core.get_exposure()
self.demo = False
auto_shutter = self.core.get_property('Core', 'AutoShutter')
self.core.set_property('Core', 'AutoShutter', 0)
except BaseException as be:
print(be)
print('')
print(' /!\ Problem with the Camera /!\ ')
print(' --> no camera found ')
print('')
self.exposure = -1 # flag for no camera
self.demo = True
########################
##### building GUI #####
########################
self.minView = False
self.showwindow()
# layout (from NewWindow class)
self.init_basic_widget_grid(wdgt_length=3, Ncol_wdgt=20, Nrow_wdgt=20)
# -- A plot area (ViewBox + axes) for displaying the image ---
self.view = self.graphics_layout.addViewBox(lockAspect=True,
invertY=True)
self.view.setMenuEnabled(False)
self.view.setAspectLocked()
self.pimg = pg.ImageItem()
# --- setting subject information ---
self.add_widget(QtWidgets.QLabel('subjects file:'))
self.subjectFileBox = QtWidgets.QComboBox(self)
self.subjectFileBox.addItems([
f for f in os.listdir(subjects_path)[::-1] if f.endswith('.json')
])
self.subjectFileBox.activated.connect(self.get_subject_list)
self.add_widget(self.subjectFileBox)
self.add_widget(QtWidgets.QLabel('subject:'))
self.subjectBox = QtWidgets.QComboBox(self)
self.get_subject_list()
self.add_widget(self.subjectBox)
self.add_widget(QtWidgets.QLabel(20 * ' - '))
self.vascButton = QtWidgets.QPushButton(
" - = save Vasculature Picture = - ", self)
self.vascButton.clicked.connect(self.take_vasculature_picture)
self.add_widget(self.vascButton)
self.add_widget(QtWidgets.QLabel(20 * ' - '))
# --- data acquisition properties ---
self.add_widget(QtWidgets.QLabel('data folder:'), spec='small-left')
self.folderB = QtWidgets.QComboBox(self)
self.folderB.addItems(FOLDERS.keys())
self.add_widget(self.folderB, spec='large-right')
self.add_widget(QtWidgets.QLabel(' - protocol:'), spec='small-left')
self.protocolBox = QtWidgets.QComboBox(self)
self.protocolBox.addItems(['ALL', 'up', 'down', 'left', 'right'])
self.add_widget(self.protocolBox, spec='large-right')
self.add_widget(
QtWidgets.QLabel(' - exposure: %.0f ms (from Micro-Manager)' %
self.exposure))
self.add_widget(QtWidgets.QLabel(' - Nrepeat :'), spec='large-left')
self.repeatBox = QtWidgets.QLineEdit()
self.repeatBox.setText('10')
self.add_widget(self.repeatBox, spec='small-right')
self.add_widget(QtWidgets.QLabel(' - stim. period (s):'),
spec='large-left')
self.periodBox = QtWidgets.QLineEdit()
self.periodBox.setText('10')
self.add_widget(self.periodBox, spec='small-right')
self.add_widget(QtWidgets.QLabel(' - bar size (degree):'),
spec='large-left')
self.barBox = QtWidgets.QLineEdit()
self.barBox.setText('6')
self.add_widget(self.barBox, spec='small-right')
self.add_widget(QtWidgets.QLabel(' - spatial sub-sampling (px):'),
spec='large-left')
self.spatialBox = QtWidgets.QLineEdit()
self.spatialBox.setText(str(spatial_subsampling))
self.add_widget(self.spatialBox, spec='small-right')
self.add_widget(QtWidgets.QLabel(' - acq. freq. (Hz):'),
spec='large-left')
self.freqBox = QtWidgets.QLineEdit()
self.freqBox.setText('10')
self.add_widget(self.freqBox, spec='small-right')
# self.add_widget(QtWidgets.QLabel(' - flick. freq. (Hz) /!\ > acq:'),
# spec='large-left')
# self.flickBox = QtWidgets.QLineEdit()
# self.flickBox.setText('10')
# self.add_widget(self.flickBox, spec='small-right')
self.demoBox = QtWidgets.QCheckBox("demo mode")
self.demoBox.setStyleSheet("color: gray;")
self.add_widget(self.demoBox, spec='large-left')
self.demoBox.setChecked(self.demo)
self.camBox = QtWidgets.QCheckBox("cam.")
self.camBox.setStyleSheet("color: gray;")
self.add_widget(self.camBox, spec='small-right')
self.camBox.setChecked(True)
# --- launching acquisition ---
self.liveButton = QtWidgets.QPushButton("-- live view -- ", self)
self.liveButton.clicked.connect(self.live_view)
self.add_widget(self.liveButton)
# --- launching acquisition ---
self.acqButton = QtWidgets.QPushButton("-- RUN PROTOCOL -- ", self)
self.acqButton.clicked.connect(self.launch_protocol)
self.add_widget(self.acqButton, spec='large-left')
self.stopButton = QtWidgets.QPushButton(" STOP ", self)
self.stopButton.clicked.connect(self.stop_protocol)
self.add_widget(self.stopButton, spec='small-right')
# --- launching analysis ---
self.add_widget(QtWidgets.QLabel(20 * ' - '))
self.analysisButton = QtWidgets.QPushButton(" - = Analysis GUI = - ",
self)
self.analysisButton.clicked.connect(self.open_analysis)
self.add_widget(self.analysisButton, spec='large-left')
self.pimg.setImage(0 * self.get_frame())
self.view.addItem(self.pimg)
self.view.autoRange(padding=0.001)
self.analysisWindow = None
class MainWindow(NewWindow):
def __init__(self,
app,
args=None,
parent=None,
spatial_subsampling=4,
time_subsampling=1):
"""
Intrinsic Imaging GUI
"""
self.app = app
super(MainWindow, self).__init__(i=1, title='intrinsic imaging')
# some initialisation
self.running, self.stim, self.STIM = False, None, None
self.datafolder, self.img, self.vasculature_img = '', None, None
self.t0, self.period = 0, 1
### trying the camera
try:
# we initialize the camera
self.bridge = Bridge()
self.core = self.bridge.get_core()
self.exposure = self.core.get_exposure()
self.demo = False
auto_shutter = self.core.get_property('Core', 'AutoShutter')
self.core.set_property('Core', 'AutoShutter', 0)
except BaseException as be:
print(be)
print('')
print(' /!\ Problem with the Camera /!\ ')
print(' --> no camera found ')
print('')
self.exposure = -1 # flag for no camera
self.demo = True
########################
##### building GUI #####
########################
self.minView = False
self.showwindow()
# layout (from NewWindow class)
self.init_basic_widget_grid(wdgt_length=3, Ncol_wdgt=20, Nrow_wdgt=20)
# -- A plot area (ViewBox + axes) for displaying the image ---
self.view = self.graphics_layout.addViewBox(lockAspect=True,
invertY=True)
self.view.setMenuEnabled(False)
self.view.setAspectLocked()
self.pimg = pg.ImageItem()
# --- setting subject information ---
self.add_widget(QtWidgets.QLabel('subjects file:'))
self.subjectFileBox = QtWidgets.QComboBox(self)
self.subjectFileBox.addItems([
f for f in os.listdir(subjects_path)[::-1] if f.endswith('.json')
])
self.subjectFileBox.activated.connect(self.get_subject_list)
self.add_widget(self.subjectFileBox)
self.add_widget(QtWidgets.QLabel('subject:'))
self.subjectBox = QtWidgets.QComboBox(self)
self.get_subject_list()
self.add_widget(self.subjectBox)
self.add_widget(QtWidgets.QLabel(20 * ' - '))
self.vascButton = QtWidgets.QPushButton(
" - = save Vasculature Picture = - ", self)
self.vascButton.clicked.connect(self.take_vasculature_picture)
self.add_widget(self.vascButton)
self.add_widget(QtWidgets.QLabel(20 * ' - '))
# --- data acquisition properties ---
self.add_widget(QtWidgets.QLabel('data folder:'), spec='small-left')
self.folderB = QtWidgets.QComboBox(self)
self.folderB.addItems(FOLDERS.keys())
self.add_widget(self.folderB, spec='large-right')
self.add_widget(QtWidgets.QLabel(' - protocol:'), spec='small-left')
self.protocolBox = QtWidgets.QComboBox(self)
self.protocolBox.addItems(['ALL', 'up', 'down', 'left', 'right'])
self.add_widget(self.protocolBox, spec='large-right')
self.add_widget(
QtWidgets.QLabel(' - exposure: %.0f ms (from Micro-Manager)' %
self.exposure))
self.add_widget(QtWidgets.QLabel(' - Nrepeat :'), spec='large-left')
self.repeatBox = QtWidgets.QLineEdit()
self.repeatBox.setText('10')
self.add_widget(self.repeatBox, spec='small-right')
self.add_widget(QtWidgets.QLabel(' - stim. period (s):'),
spec='large-left')
self.periodBox = QtWidgets.QLineEdit()
self.periodBox.setText('10')
self.add_widget(self.periodBox, spec='small-right')
self.add_widget(QtWidgets.QLabel(' - bar size (degree):'),
spec='large-left')
self.barBox = QtWidgets.QLineEdit()
self.barBox.setText('6')
self.add_widget(self.barBox, spec='small-right')
self.add_widget(QtWidgets.QLabel(' - spatial sub-sampling (px):'),
spec='large-left')
self.spatialBox = QtWidgets.QLineEdit()
self.spatialBox.setText(str(spatial_subsampling))
self.add_widget(self.spatialBox, spec='small-right')
self.add_widget(QtWidgets.QLabel(' - acq. freq. (Hz):'),
spec='large-left')
self.freqBox = QtWidgets.QLineEdit()
self.freqBox.setText('10')
self.add_widget(self.freqBox, spec='small-right')
# self.add_widget(QtWidgets.QLabel(' - flick. freq. (Hz) /!\ > acq:'),
# spec='large-left')
# self.flickBox = QtWidgets.QLineEdit()
# self.flickBox.setText('10')
# self.add_widget(self.flickBox, spec='small-right')
self.demoBox = QtWidgets.QCheckBox("demo mode")
self.demoBox.setStyleSheet("color: gray;")
self.add_widget(self.demoBox, spec='large-left')
self.demoBox.setChecked(self.demo)
self.camBox = QtWidgets.QCheckBox("cam.")
self.camBox.setStyleSheet("color: gray;")
self.add_widget(self.camBox, spec='small-right')
self.camBox.setChecked(True)
# --- launching acquisition ---
self.liveButton = QtWidgets.QPushButton("-- live view -- ", self)
self.liveButton.clicked.connect(self.live_view)
self.add_widget(self.liveButton)
# --- launching acquisition ---
self.acqButton = QtWidgets.QPushButton("-- RUN PROTOCOL -- ", self)
self.acqButton.clicked.connect(self.launch_protocol)
self.add_widget(self.acqButton, spec='large-left')
self.stopButton = QtWidgets.QPushButton(" STOP ", self)
self.stopButton.clicked.connect(self.stop_protocol)
self.add_widget(self.stopButton, spec='small-right')
# --- launching analysis ---
self.add_widget(QtWidgets.QLabel(20 * ' - '))
self.analysisButton = QtWidgets.QPushButton(" - = Analysis GUI = - ",
self)
self.analysisButton.clicked.connect(self.open_analysis)
self.add_widget(self.analysisButton, spec='large-left')
self.pimg.setImage(0 * self.get_frame())
self.view.addItem(self.pimg)
self.view.autoRange(padding=0.001)
self.analysisWindow = None
def take_vasculature_picture(self):
filename = generate_filename_path(FOLDERS[self.folderB.currentText()],
filename='vasculature-%s' %
self.subjectBox.currentText(),
extension='.tif')
# save HQ image as tiff
img = self.get_frame(force_HQ=True)
np.save(filename.replace('.tif', '.npy'), img)
img = np.array(255 * (img - img.min()) / (img.max() - img.min()),
dtype=np.uint8)
im = PIL.Image.fromarray(img)
im.save(filename)
print('vasculature image, saved as:')
print(filename)
# then keep a version to store with imaging:
self.vasculature_img = self.get_frame()
self.pimg.setImage(img) # show on displayn
def open_analysis(self):
self.analysisWindow = runAnalysis(self.app, parent=self)
def get_subject_list(self):
with open(
os.path.join(subjects_path,
self.subjectFileBox.currentText())) as f:
self.subjects = json.load(f)
self.subjectBox.clear()
self.subjectBox.addItems(self.subjects.keys())
def init_visual_stim(self, demo=True):
with open(
os.path.join(
pathlib.Path(__file__).resolve().parents[1], 'intrinsic',
'vis_stim', 'up.json'), 'r') as fp:
protocol = json.load(fp)
if self.demoBox.isChecked():
protocol['demo'] = True
self.stim = visual_stim.build_stim(protocol)
self.parent = dummy_parent()
def get_patterns(self, protocol, angle, size, Npatch=30):
patterns = []
if protocol in ['left', 'right']:
z = np.linspace(-self.stim.screen['resolution'][1],
self.stim.screen['resolution'][1], Npatch)
for i in np.arange(len(z) - 1)[(1 if self.flip else 0)::2]:
patterns.append(
visual.Rect(win=self.stim.win,
size=(self.stim.angle_to_pix(size),
z[1] - z[0]),
pos=(self.stim.angle_to_pix(angle), z[i]),
units='pix',
fillColor=1))
if protocol in ['up', 'down']:
x = np.linspace(-self.stim.screen['resolution'][0],
self.stim.screen['resolution'][0], Npatch)
for i in np.arange(len(x) - 1)[(1 if self.flip else 0)::2]:
patterns.append(
visual.Rect(win=self.stim.win,
size=(x[1] - x[0],
self.stim.angle_to_pix(size)),
pos=(x[i], self.stim.angle_to_pix(angle)),
units='pix',
fillColor=1))
return patterns
def run(self):
self.flip = False
self.stim = visual_stim(
{
"Screen": "Dell-2020",
"presentation-prestim-screen": -1,
"presentation-poststim-screen": -1
},
demo=self.demoBox.isChecked())
self.Nrepeat = int(self.repeatBox.text()) #
self.period = float(self.periodBox.text()) # degree / second
self.bar_size = float(self.barBox.text()) # degree / second
# self.dt_save, self.dt = 1./float(self.freqBox.text()), 1./float(self.flickBox.text())
self.dt_save, self.dt = 1. / float(self.freqBox.text()), 1. / float(
self.freqBox.text())
xmin, xmax = 1.15 * np.min(self.stim.x), 1.15 * np.max(self.stim.x)
zmin, zmax = 1.3 * np.min(self.stim.z), 1.3 * np.max(self.stim.z)
self.angle_start, self.angle_max, self.protocol, self.label = 0, 0, '', ''
self.Npoints = int(self.period / self.dt_save)
if self.protocolBox.currentText() == 'ALL':
self.STIM = {
'angle_start': [zmin, xmax, zmax, xmin],
'angle_stop': [zmax, xmin, zmin, xmax],
'label': ['up', 'left', 'down', 'right'],
'xmin': xmin,
'xmax': xmax,
'zmin': zmin,
'zmax': zmax
}
self.label = 'up' # starting point
else:
self.STIM = {
'label': [self.protocolBox.currentText()],
'xmin': xmin,
'xmax': xmax,
'zmin': zmin,
'zmax': zmax
}
if self.protocolBox.currentText() == 'up':
self.STIM['angle_start'] = [zmin]
self.STIM['angle_stop'] = [zmax]
if self.protocolBox.currentText() == 'down':
self.STIM['angle_start'] = [zmax]
self.STIM['angle_stop'] = [zmin]
if self.protocolBox.currentText() == 'left':
self.STIM['angle_start'] = [xmax]
self.STIM['angle_stop'] = [xmin]
if self.protocolBox.currentText() == 'right':
self.STIM['angle_start'] = [xmin]
self.STIM['angle_stop'] = [xmax]
self.label = self.protocolBox.currentText()
for il, label in enumerate(self.STIM['label']):
self.STIM[label + '-times'] = np.arange(
self.Npoints * self.Nrepeat) * self.dt_save
self.STIM[label + '-angle'] = np.concatenate([
np.linspace(self.STIM['angle_start'][il],
self.STIM['angle_stop'][il], self.Npoints)
for n in range(self.Nrepeat)
])
# initialize one episode:
self.iEp, self.iTime, self.t0_episode = 0, 0, time.time()
self.img, self.nSave = self.new_img(), 0
self.save_metadata()
print('acquisition running [...]')
self.update_dt() # while loop
def new_img(self):
return np.zeros(self.imgsize, dtype=np.float64)
def save_img(self):
if self.nSave > 0:
self.img /= self.nSave
if True: # live display
self.pimg.setImage(self.img)
# NEED TO STORE DATA HERE
self.FRAMES.append(self.img)
# re-init time step of acquisition
self.img, self.nSave = self.new_img(), 0
def update_dt(self):
self.tSave = time.time()
while (time.time() - self.tSave) <= self.dt_save:
self.t = time.time()
# show image
patterns = self.get_patterns(
self.STIM['label'][self.iEp % len(self.STIM['label'])],
self.STIM[self.STIM['label'][self.iEp %
len(self.STIM['label'])] +
'-angle'][self.iTime], self.bar_size)
for pattern in patterns:
pattern.draw()
try:
self.stim.win.flip()
except BaseException:
pass
if self.camBox.isChecked():
# # fetch image
self.img += self.get_frame()
self.nSave += 1.0
# time.sleep(max([self.dt-(time.time()-self.t), 0]))
# self.flip = (False if self.flip else True) # flip the flag
self.flip = (False if self.flip else True) # flip the flag
if self.camBox.isChecked():
self.save_img() # re-init image here
self.iTime += 1
# checking if not episode over
if not (self.iTime < len(self.STIM[self.STIM['label'][
self.iEp % len(self.STIM['label'])] + '-angle'])):
if self.camBox.isChecked():
self.write_data() # writing data when over
self.t0_episode, self.img, self.nSave = time.time(), self.new_img(
), 0
self.FRAMES = [] # re init data
self.iTime = 0
self.iEp += 1
# continuing ?
if self.running:
QtCore.QTimer.singleShot(1, self.update_dt)
def write_data(self):
filename = '%s-%i.nwb' % (self.STIM['label'][self.iEp % len(
self.STIM['label'])], int(self.iEp / len(self.STIM['label'])) + 1)
nwbfile = pynwb.NWBFile(
'Intrinsic Imaging data following bar stimulation',
'intrinsic',
datetime.datetime.utcnow(),
file_create_date=datetime.datetime.utcnow())
# Create our time series
angles = pynwb.TimeSeries(
name='angle_timeseries',
data=self.STIM[self.STIM['label'][self.iEp %
len(self.STIM['label'])] +
'-angle'],
unit='Rd',
timestamps=self.STIM[self.STIM['label'][self.iEp %
len(self.STIM['label'])] +
'-times'])
nwbfile.add_acquisition(angles)
images = pynwb.image.ImageSeries(
name='image_timeseries',
data=np.array(self.FRAMES, dtype=np.float64),
unit='a.u.',
timestamps=self.STIM[self.STIM['label'][self.iEp %
len(self.STIM['label'])] +
'-times'])
nwbfile.add_acquisition(images)
# Write the data to file
io = pynwb.NWBHDF5IO(os.path.join(self.datafolder, filename), 'w')
print('writing:', filename)
io.write(nwbfile)
io.close()
print(filename, ' saved !')
def save_metadata(self):
filename = generate_filename_path(FOLDERS[self.folderB.currentText()],
filename='metadata',
extension='.npy')
metadata = {
'subject': str(self.subjectBox.currentText()),
'exposure': self.exposure,
'bar-size': float(self.barBox.text()),
'acq-freq': float(self.freqBox.text()),
'period': float(self.periodBox.text()),
'Nrepeat': int(self.repeatBox.text()),
'imgsize': self.imgsize,
'STIM': self.STIM
}
np.save(filename, metadata)
if self.vasculature_img is not None:
np.save(filename.replace('metadata', 'vasculature'),
self.vasculature_img)
self.datafolder = os.path.dirname(filename)
def launch_protocol(self):
if not self.running:
self.running = True
# initialization of data
self.FRAMES = []
self.img = self.get_frame()
self.imgsize = self.img.shape
self.pimg.setImage(self.img)
self.view.autoRange(padding=0.001)
self.run()
else:
print(
' /!\ --> pb in launching acquisition (either already running or missing camera)'
)
def live_view(self):
self.running, self.t0 = True, time.time()
self.update_Image()
def stop_protocol(self):
if self.running:
self.running = False
if self.stim is not None:
self.stim.close()
else:
print('acquisition not launched')
def get_frame(self, force_HQ=False):
if self.exposure > 0:
self.core.snap_image()
tagged_image = self.core.get_tagged_image()
#pixels by default come out as a 1D array. We can reshape them into an image
img = np.reshape(tagged_image.pix,
newshape=[
tagged_image.tags['Height'],
tagged_image.tags['Width']
])
elif (self.stim is not None) and (self.STIM is not None):
it = int((time.time() - self.t0_episode) / self.dt_save) % int(
self.period / self.dt_save)
protocol = self.STIM['label'][self.iEp % len(self.STIM['label'])]
if protocol == 'left':
img = np.random.randn(*self.stim.x.shape)+\
np.exp(-(self.stim.x-(40*it/self.Npoints-20))**2/2./10**2)*\
np.exp(-self.stim.z**2/2./15**2)
elif protocol == 'right':
img = np.random.randn(*self.stim.x.shape)+\
np.exp(-(self.stim.x+(40*it/self.Npoints-20))**2/2./10**2)*\
np.exp(-self.stim.z**2/2./15**2)
elif protocol == 'up':
img = np.random.randn(*self.stim.x.shape)+\
np.exp(-(self.stim.z-(40*it/self.Npoints-20))**2/2./10**2)*\
np.exp(-self.stim.x**2/2./15**2)
else: # down
img = np.random.randn(*self.stim.x.shape)+\
np.exp(-(self.stim.z+(40*it/self.Npoints-20))**2/2./10**2)*\
np.exp(-self.stim.x**2/2./15**2)
else:
img = np.random.randn(720, 1280)
if (int(self.spatialBox.text()) > 1) and not force_HQ:
return 1.0 * analysis.resample_img(img, int(
self.spatialBox.text()))
else:
return 1.0 * img
def update_Image(self):
# plot it
self.pimg.setImage(self.get_frame())
new_t0 = time.time()
print('dt=%.1f ms' % (1e3 * (new_t0 - self.t0)))
self.t0 = new_t0
if self.running:
QtCore.QTimer.singleShot(1, self.update_Image)
def hitting_space(self):
if not self.running:
self.launch_protocol()
else:
self.stop_protocol()
def process(self):
self.launch_analysis()
def quit(self):
if self.exposure > 0:
self.bridge.close()
sys.exit()
def __init__(self, stageDevice):
bridge = Bridge()
self.mmc = bridge.get_core()
self.mmc.set_xy_stage_device(stageDevice)
layer_names = ['GFP', 'RFP']
# initialize global variables
# flag to break while loops
acq_running = False
# empty queue for image data and z positions
img_queue = queue.Queue()
# xyz data stack
data = np.random.rand(z_range[2], clip[0], clip[1]) * clim[1]
# if z-stage is controlled through micromanager:
# need bridge to move stage at beginning of stack
# USE WITH CAUTION: only tested with micromanager demo config
if not (simulate) and not (z_stack_external):
from pycromanager import Bridge
bridge = Bridge()
#get object representing micro-manager core
core = bridge.get_core()
print(core)
core.set_position(z_range[0])
#########################################################################
# function to write data into queue #
#########################################################################
def place_data(image):
""" fnc to place image data into the queue.
Keeps track of z-position in stacks and of active color channels.
Inputs: np.array image: image data
Global variables: image_queue to write image and z position
z_range to keep track of z position
from pycromanager import Acquisition, multi_d_acquisition_events, Bridge, Dataset
from matplotlib import pyplot as plt
import numpy as np
import cv2
import time, math
import os, sys, re
from PIL import Image
from math import sqrt
from pathlib import Path
bridge = Bridge()
core = bridge.get_core()
mm = bridge.get_studio()
pm = mm.positions()
mmc = mm.core()
pos_list = pm.get_position_list()
#-------------------------------------------
directoryPATH = 'E:\KENZA Folder\CapstoneTests'
nameofSAVEDFILE = 'saving_name'
#--------------------------------------------
def merge_imagesVertical(file1, file2):
"""Merge two images into one vertical image
:return: the merged Image object
"""
image1 = file1
image2 = file2
vis = np.concatenate((image1, image2), axis=0)
def main():
#------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------Begin setup of scan parameters--------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------
# lasers to use
# 0 -> inactive
# 1 -> active
state_405 = 0
state_488 = 0
state_561 = 0
state_635 = 1
state_730 = 0
# laser powers (0 -> 100%)
power_405 = 2
power_488 = 2
power_561 = 2
power_635 = 50
power_730 = 0
# exposure time
exposure_ms = 5.
# scan axis limits. Use stage positions reported by MM
scan_axis_start_um = 1614. #unit: um
scan_axis_end_um = 1625. #unit: um
tile_axis_start_um = -265.
height_axis_start_um = 9500.
# FOV parameters
# ONLY MODIFY IF NECESSARY
ROI = [1024, 0, 256, 2048] #unit: pixels
# setup file name
save_directory = Path('E:/20201023/')
save_name = 'scan_test'
#------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------End setup of scan parameters----------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------------------------
bridge = Bridge()
core = bridge.get_core()
# set camera into 16bit readout mode
# give camera time to change modes if necessary
core.set_property('Camera', 'ReadoutRate', '100MHz 16bit')
time.sleep(5)
# set camera into low noise readout mode
# give camera time to change modes if necessary
core.set_property('Camera', 'Gain', '2-CMS')
time.sleep(5)
# set camera to trigger first mode
# give camera time to change modes if necessary
core.set_property('Camera', 'Trigger Timeout (secs)', 60)
time.sleep(5)
# set camera to internal trigger
# give camera time to change modes if necessary
core.set_property('Camera', 'TriggerMode', 'Internal Trigger')
time.sleep(5)
# set exposure
core.set_exposure(exposure_ms)
# get actual framerate, accounting for readout time
actual_readout_ms = float(core.get_property(
'Camera', 'ActualInterval-ms')) #unit: ms
# camera pixel size
pixel_size_um = .115 # unit: um
# scan axis setup
scan_axis_step_um = 0.2 # unit: um
scan_axis_step_mm = scan_axis_step_um / 1000. #unit: mm
scan_axis_start_mm = scan_axis_start_um / 1000. #unit: mm
scan_axis_end_mm = scan_axis_end_um / 1000. #unit: mm
scan_axis_range_um = np.abs(scan_axis_end_um -
scan_axis_start_um) # unit: um
scan_axis_range_mm = scan_axis_range_um / 1000 #unit: mm
actual_exposure_s = actual_readout_ms / 1000. #unit: s
scan_axis_speed = np.round(scan_axis_step_mm / actual_exposure_s,
2) #unit: mm/s
scan_axis_positions = np.rint(scan_axis_range_mm /
scan_axis_step_mm).astype(int)
# get handle to xy and z stages
xy_stage = core.get_xy_stage_device()
z_stage = core.get_focus_device()
# Setup PLC card to give start trigger
plcName = 'PLogic:E:36'
propPosition = 'PointerPosition'
propCellConfig = 'EditCellConfig'
addrOutputBNC3 = 35
addrStageSync = 46 # TTL5 on Tiger backplane = stage sync signal
# connect stage sync signal to BNC output
core.set_property(plcName, propPosition, addrOutputBNC3)
core.set_property(plcName, propCellConfig, addrStageSync)
# turn on 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub', 'OnlySendSerialCommandOnChange', 'No')
# set tile axis speed for all moves
command = 'SPEED Y=.5'
core.set_property('TigerCommHub', 'SerialCommand', command)
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand', command)
ready = core.get_property('TigerCommHub', 'SerialResponse')
time.sleep(.500)
# set scan axis speed for large move to initial position
command = 'SPEED X=.5'
core.set_property('TigerCommHub', 'SerialCommand', command)
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand', command)
ready = core.get_property('TigerCommHub', 'SerialResponse')
time.sleep(.500)
# turn off 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub', 'OnlySendSerialCommandOnChange', 'Yes')
# move scan scan stage to initial position
core.set_xy_position(scan_axis_start_um, tile_axis_start_um)
core.wait_for_device(xy_stage)
core.set_position(height_axis_start_um)
core.wait_for_device(z_stage)
# turn on 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub', 'OnlySendSerialCommandOnChange', 'No')
# set scan axis speed to correct speed for continuous stage scan
# expects mm/s
command = 'SPEED X=' + str(scan_axis_speed)
core.set_property('TigerCommHub', 'SerialCommand', command)
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand', command)
ready = core.get_property('TigerCommHub', 'SerialResponse')
time.sleep(.500)
# set scan axis to true 1D scan with no backlash
command = '1SCAN X? Y=0 Z=9 F=0'
core.set_property('TigerCommHub', 'SerialCommand', command)
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand', command)
ready = core.get_property('TigerCommHub', 'SerialResponse')
time.sleep(.500)
# set range for scan axis
# expects mm
command = '1SCANR X=' + str(scan_axis_start_mm) + ' Y=' + str(
scan_axis_end_mm) + ' R=50'
core.set_property('TigerCommHub', 'SerialCommand', command)
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand', command)
ready = core.get_property('TigerCommHub', 'SerialResponse')
time.sleep(.500)
#command = '1SCANV X=0 Y=0 Z=2'
#core.set_property('TigerCommHub','SerialCommand',command)
# check to make sure Tiger is not busy
ready = 'B'
while (ready != 'N'):
command = 'STATUS'
core.set_property('TigerCommHub', 'SerialCommand', command)
ready = core.get_property('TigerCommHub', 'SerialResponse')
time.sleep(.500)
# turn off 'transmit repeated commands' for Tiger
core.set_property('TigerCommHub', 'OnlySendSerialCommandOnChange', 'Yes')
# construct boolean array for lasers to use
channel_states = [state_405, state_488, state_561, state_635, state_730]
channel_powers = [power_405, power_488, power_561, power_635, power_730]
# set all lasers to off and user defined power
core.set_property('Coherent-Scientific Remote',
'Laser 405-100C - PowerSetpoint (%)', channel_powers[0])
core.set_property('Coherent-Scientific Remote',
'Laser 488-150C - PowerSetpoint (%)', channel_powers[1])
core.set_property('Coherent-Scientific Remote',
'Laser OBIS LS 561-150 - PowerSetpoint (%)',
channel_powers[2])
core.set_property('Coherent-Scientific Remote',
'Laser 637-140C - PowerSetpoint (%)', channel_powers[3])
core.set_property('Coherent-Scientific Remote',
'Laser 730-30C - PowerSetpoint (%)', channel_powers[4])
print(scan_axis_positions)
# create events to execute scan
events = []
#for t in range(2):
for x in range(scan_axis_positions):
evt = {'axes': {'x': x}}
events.append(evt)
# set camera to internal trigger
# give camera time to change modes if necessary
core.set_property('Camera', 'TriggerMode', 'Trigger first')
time.sleep(1)
# run acquisition
with Acquisition(directory=save_directory,
name=save_name,
post_hardware_hook_fn=post_hook_fn,
post_camera_hook_fn=camera_hook_fn,
show_display=True,
max_multi_res_index=0) as acq:
acq.acquire(events)
# set camera to internal trigger
# give camera time to change modes if necessary
core.set_property('Camera', 'TriggerMode', 'Internal Trigger')
time.sleep(1)