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ryantan 2025-04-14 10:29:39 +02:00
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FunctionsTest.py Normal file
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import re
import numpy as np
def sep_num_from_units(powerbox_output :str)->list:
'''
Receives a string as input and separates the numberic value and unit and returns it as a list.
Parameters
----------
powerbox_output : str
string output from the attocube powerbox, e.g. 1.35325kG
Returns
-------
list
list of float value and string (b value and it's units). If string is purely alphabets, then return a single element list
'''
match = re.match(r'\s*([+-]?\d*\.?\d+)([A-Za-z]+)', powerbox_output)
if match:
numeric_part = float(match.group(1)) # Convert the numeric part to a float
alphabetic_part = match.group(2) # Get the alphabetic part
return [numeric_part, alphabetic_part]
else:
return [powerbox_output,]
angles = [1,2,3]
print(str(angles[0]) +"\n"+ str(angles[-1]))
rates_lst = list(sep_num_from_units(el) for el in "0.0kG;1.0kG".split(";"))
print(rates_lst[1][0])

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Mag_Field_Sweep_2024_10_21.py Normal file
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Mapping_Script_Lukas_Version_2024_08_27.py Normal file
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# -*- coding: utf-8 -*-
"""
Created on Fri Dec 22 15:10:10 2023
Lightfield + Positioner
@author: Local Admin
"""
import AMC
import csv
import time
import clr
import sys
import os
import spe2py as spe
import spe_loader as sl
import pandas as pd
import time
from System.IO import *
from System import String
import numpy as np
import matplotlib.pyplot as plt
import datetime
#First choose your controller
IP_AMC300 = "192.168.71.101"
IP_AMC100 = "192.168.71.100"
# IP = "192.168.1.1"
IP = IP_AMC300
# Import os module
import os, glob, string
# Import System.IO for saving and opening files
from System.IO import *
from System.Threading import AutoResetEvent
# Import C compatible List and String
from System import String
from System.Collections.Generic import List
# Add needed dll references
sys.path.append(os.environ['LIGHTFIELD_ROOT'])
sys.path.append(os.environ['LIGHTFIELD_ROOT']+"\\AddInViews")
sys.path.append(r'C:\Program Files\Princeton Instruments\LightField\AddInViews') #I added them by hand -serdar
sys.path.append(r'C:\Program Files\Princeton Instruments\LightField') #this one also
clr.AddReference('PrincetonInstruments.LightFieldViewV5')
clr.AddReference('PrincetonInstruments.LightField.AutomationV5')
clr.AddReference('PrincetonInstruments.LightFieldAddInSupportServices')
os.environ['LIGHTFIELD_ROOT'] = r'C:\Program Files\Princeton Instruments\LightField'
# PI imports
from PrincetonInstruments.LightField.Automation import Automation
from PrincetonInstruments.LightField.AddIns import ExperimentSettings
from PrincetonInstruments.LightField.AddIns import CameraSettings
#from PrincetonInstruments.LightField.AddIns import DeviceType
from PrincetonInstruments.LightField.AddIns import SpectrometerSettings
from PrincetonInstruments.LightField.AddIns import RegionOfInterest
######################################################################################################### code begins from here #############################################
def set_custom_ROI():
# Get device full dimensions
dimensions = experiment.FullSensorRegion()
regions = []
# Add two ROI to regions
regions.append(
RegionOfInterest(
int(dimensions.X), int(dimensions.Y),
int(dimensions.Width), int(dimensions.Height//4), # Use // for integer division
int(dimensions.XBinning), int(dimensions.Height//4)))
# Set both ROI
experiment.SetCustomRegions(regions)
def experiment_completed(sender, event_args): #callback function which is hooked to event completed, this is the listener
print("... Acquisition Complete!")
acquireCompleted.Set() #set the event. This puts the autoresetevent false.(look at .NET library for furher info)
def InitializerFilenameParams():
experiment.SetValue(ExperimentSettings.FileNameGenerationAttachIncrement, False)
experiment.SetValue(ExperimentSettings.FileNameGenerationIncrementNumber, 1.0)
experiment.SetValue(ExperimentSettings.FileNameGenerationIncrementMinimumDigits, 2.0)
experiment.SetValue(ExperimentSettings.FileNameGenerationAttachDate, False)
experiment.SetValue(ExperimentSettings.FileNameGenerationAttachTime, False)
def AcquireAndLock(name):
print("Acquiring...", end = "")
# name += 'Exp{0:06.2f}ms.CWL{1:07.2f}nm'.format(\
# experiment.GetValue(CameraSettings.ShutterTimingExposureTime)\
# ,experiment.GetValue(SpectrometerSettings.GratingCenterWavelength))
experiment.SetValue(ExperimentSettings.FileNameGenerationBaseFileName, name) #this creates .spe file with the name
experiment.Acquire() # this is an ashynrchronus func.
acquireCompleted.WaitOne()
def calculate_distance(x1, y1, x2, y2):
return np.sqrt((x2 - x1)**2 + (y2 - y1)**2)
def generate_scan_positions(center, range_val, resolution):
positive_range = np.arange(center, center + range_val + resolution, resolution)
return positive_range
def save_as_csv(filename, position_x, position_y):
file_existance = os.path.isfile(filename)
with open(filename, 'a', newline = '') as csvfile:
writer = csv.writer(csvfile)
if not file_existance:
writer.writerow(['x_coordinates','y_coordinates'])
writer.writerow([position_x, position_y])
def move_axis(axis, target):
"""
This function moves an axis to the specified target and stop moving after it is in the really closed
vicinity (+- 25nm) of the target (listener hooked to it).
"""
amc.move.setControlTargetPosition(axis, target)
amc.control.setControlMove(axis, True)
# while not (target - 25) < amc.move.getPosition(axis) < (target + 25):
# time.sleep(0.1)
# time.sleep(0.15)
# while not (target - 25) < amc.move.getPosition(axis) < (target + 25):
# time.sleep(0.1)
# amc.control.setControlMove(axis, False)
def move_xy(target_x, target_y): # moving in x and y direction closed to desired position
amc.move.setControlTargetPosition(0, target_x)
amc.control.setControlMove(0, True)
amc.move.setControlTargetPosition(1, target_y)
amc.control.setControlMove(1, True)
while not (target_x - 25) < amc.move.getPosition(0) < (target_x + 25) and (target_y - 25) < amc.move.getPosition(1) < (target_y + 25):
time.sleep(0.1)
time.sleep(0.15)
while not (target_x - 25) < amc.move.getPosition(0) < (target_x + 25) and (target_y - 25) < amc.move.getPosition(1) < (target_y + 25):
time.sleep(0.1)
amc.control.setControlOutput(0, False)
amc.control.setControlOutput(1, False)
# intensity_data = [] # To store data from each scan
# data_list = []
def move_scan_xy(range_x, range_y, resolution, Settings, baseFileName):
"""
This function moves the positioners to scan the sample with desired ranges and resolution in 2 dimensions.
At the end it saves a csv file
Parameters
----------
range_x : integer in nm. max value is 5um
Scan range in x direction.
range_y : integer in nm. max value is 5um
Scan range in y direction.
resolution : integer in nm.
Room temprature max res is 50nm. In cyrostat (4K) it is 10nm (check the Attocube manual)
baseFileName: string. At the end the saved file will be: baseFileName_scan_data.csv and it will be saved to the current directory
Returns
-------
None.
"""
start_time = time.time()
axis_x = 0 #first axis
axis_y = 1 #second axis
center_x = amc.move.getPosition(axis_x)
center_y = amc.move.getPosition(axis_y)
# #check if the intput range is reasonable
# if amc.move.getPosition(axis_x) + range_x >= 5000 or amc.move.getPosition(axis_x)- range_x <= 0 or amc.move.getPosition(axis_y) + range_y >=5000 or amc.move.getPosition(axis_y) - range_y <= 5000 :
# print("scan range is out of range!")
# return
# +- range from current positions for x and y directions
array_x = generate_scan_positions(center_x, range_x, resolution)
array_y = generate_scan_positions(center_y, range_y, resolution)
total_points = len(array_x)*len(array_y)
len_y = len(array_y)
intensity_data = [] # To store data from each scan
data_list = []
cwd = os.getcwd() # save original directory
#This gives a directory, in which the script will save the spectrum of each spot as spe
#However, it will open the spectrum, convert it to txt, add it to the intensity_data and delete the spe file
Path_save = "C:/Users/localadmin/Desktop/Users/Lukas/Map_dump"
#scanning loop
for i, x_positions in enumerate(array_x):
move_axis(axis_x, x_positions)
y = False
for j, y_positions in enumerate(array_y):
move_axis(axis_y, y_positions)
time.sleep(2)
if j == 0:
time.sleep(10)
#each time when the positioner comes to the beggining of a new line
#this if will make the positioner wait a bit longer to really go to the target.
if y == False:
move_axis(axis_y, y_positions)
y = True
#we acquire with the LF
acquire_name_spe = f'{baseFileName}_X{x_positions}_Y{y_positions}'
AcquireAndLock(acquire_name_spe) #this creates a .spe file with the scan name.
#read the .spe file and get the data as loaded_files
cwd = os.getcwd() # save original directory
os.chdir(Path_save) #change directory
loaded_files = sl.load_from_files([acquire_name_spe + '.spe']) # get the .spe file as a variable
os.chdir(cwd) # go back to original directory
# Delete the created .spe file from acquiring after getting necessary info
spe_file_path = os.path.join(Path_save, acquire_name_spe + '.spe')
os.remove(spe_file_path)
distance = calculate_distance(x_positions, y_positions,amc.move.getPosition(axis_x), amc.move.getPosition(axis_y))
points_left = total_points - (i * len_y + (j+1)) + 1
print('Points left in the scan: ', points_left)
#append the intensity data as it is (so after every #of_wl_points, the spectrum of the next point begins)
intensity_data.append(loaded_files.data[0][0][0])
data_list.append({
'position_x': x_positions,
'position_y': y_positions,
'actual_x': amc.move.getPosition(axis_x),
'actual_y': amc.move.getPosition(axis_y),
'distance': distance,
})
#moves back to starting position
move_axis(axis_x, center_x)
move_axis(axis_y, center_y)
#prints total time the mapping lasted
end_time = time.time()
elapsed_time = (end_time - start_time) / 60
print('Scan time: ', elapsed_time, 'minutes')
# df = pd.DataFrame(data_list)
#save intensity & WL data as .txt
os.chdir('C:/Users/localadmin/Desktop/Users/Priyanka/2025/stacked_2L/PL_Map_0T/250325')
# creates new folder for MAP data
new_folder_name = "PL_Map_By_0T_" + f"{datetime.datetime.now().strftime('%Y_%m_%d_%H.%M')}"
os.mkdir(new_folder_name)
# Here the things will be saved in a new folder under user Lukas !
# IMPORTANT last / has to be there, otherwise data cannot be saved and will be lost!!!!!!!!!!!!!!!!
os.chdir('C:/Users/localadmin/Desktop/Users/Priyanka/2025/stacked_2L/PL_Map_0T/250325/'+ new_folder_name)
intensity_data = np.array(intensity_data)
np.savetxt(Settings + str(center_x) + '_' + str(center_y) + experiment_name +'.txt', intensity_data)
wl = np.array(loaded_files.wavelength)
np.savetxt("Wavelength.txt", wl)
time.sleep(20)
amc.control.setControlMove(axis_x, False)
amc.control.setControlMove(axis_y, False)
# wl.to_csv("wl", index = False)
# #Plot the scan data
# plt.figure(figsize=(12, 6))
# # Plot 1: Target and Actual Positions
# plt.subplot(1, 2, 1)
# plt.scatter(df['position_x'], df['position_y'], c='green', label='Target Positions')
# plt.scatter(df['actual_x'], df['actual_y'], c='red', label='Actual Positions')
# plt.title('Scan Visualization')
# plt.xlabel('X Position')
# plt.ylabel('Y Position')
# plt.legend()
# plt.grid(True)
# #Plot 2: Distance from Target Position
# mean_distance = df['distance'].mean()
# plt.subplot(1, 2, 2)
# plt.plot(df['distance'], label='Distance from Target Position')
# plt.title(f'Distance from Target Position\nMean Distance: {mean_distance:.2f}')
# plt.xlabel('Scan Point')
# plt.ylabel('Distance')
# plt.subplot(1, 2, 2)
# plt.hist(df['distance'], bins=30, color='skyblue', edgecolor='black', alpha=0.7)
# plt.title(f'Distribution of Distance from Target Position\nMean Distance: {mean_distance:.2f} nm')
# plt.xlabel('Distance')
# plt.ylabel('Frequency')
# plt.legend()
# plt.grid(True)
# plt.text(0.95, 0.95, f'Herz: {(amc.control.getControlFrequency(0)/1000):.2f} Hz', horizontalalignment='right', verticalalignment='top', transform=plt.gca().transAxes)
# plt.text(0.95, 0.90, f'Scan Time: {elapsed_time:.2f} mins', horizontalalignment='right', verticalalignment='top', transform=plt.gca().transAxes)
# plt.text(0.95, 0.05, f"Scan Date: {datetime.datetime.now().strftime('%Y_%m_%d_%H%M')}", horizontalalignment='right', verticalalignment='bottom', transform=plt.gca().transAxes)
# plt.legend()
# plt.grid(True)
# plt.axhline(mean_distance, color='orange', linestyle='--', label=f'Mean Distance: {mean_distance:.2f}')
# plt.tight_layout()
# plt.savefig(Settings + str(center_x) + '_' + str(center_y) +'_' + experiment_name + '.png')
# plt.show()
# os.chdir(cwd)
# Setup connection to AMC
amc = AMC.Device(IP)
amc.connect()
# Internally, axes are numbered 0 to 2
# amc.control.setControlOutput(0, True)
# amc.control.setControlOutput(1, True)
auto = Automation(True, List[String]())
experiment = auto.LightFieldApplication.Experiment
acquireCompleted = AutoResetEvent(False)
experiment.Load("2025_02_13_Priyanka_CrSBr")
experiment.ExperimentCompleted += experiment_completed # we are hooking a listener.
# experiment.SetValue(SpectrometerSettings.GratingSelected, '[750nm,1200][0][0]')
# InitializerFilenameParams()
#set scna range and resolution in nanometers
range_x = 20000
range_y = 20000
resolution = 1000
#Here you can specify the filename of the map e.g. put experiment type, exposure time, used filters, etc....
experiment_settings = 'PL_he ne_stacked_2L_G150_P300uW_5s_test_l1_52_l2_260'
# experiment_settings = 'DR_NKT_OD2_rep_0.15_600g_cwl_660_exp_3s_Start_'
# experiment_settings = 'DR_Halogen_Lamp_lin_b-axis_600g_cwl_910_exp_2s_Start_'
#The program adds the range of the scan as well as the resolution and the date and time of the measurement
experiment_name = f"{range_x}nm_{range_y}nm_{resolution}nm_{datetime.datetime.now().strftime('%Y_%m_%d_%H%M')}"
move_scan_xy(range_x, range_y, resolution, experiment_settings, experiment_name)
# Internally, axes are numbered 0 to 2