def load_file_callback(self): directory = open_directory(caption='Select images', directory='/opt/Microscope/DMD/', parent=self.parent) self.directory = directory print(self.directory) self.load_file_label.setText(self.directory)
def create_report(): directory = filedialogs.open_directory() files = filedialogs.get_files_directory(directory + '/*.hdf5') total_balls = {} for file in files: file_short = os.path.splitext(os.path.split(file)[1])[0] meta = dataframes.MetaStore(file) total_balls[file_short] = meta.metadata['n'] plt.figure() plt.bar(range(len(total_balls)), list(total_balls.values()), align='center') plt.xticks(range(len(total_balls)), list(total_balls.keys())) plt.ylabel('Total Balls')
from Generic import filedialogs, images direc = filedialogs.open_directory() files = filedialogs.get_files_directory(direc + '/*.png') final_image = [] for file in files: im = images.load(file) im = images.bgr_2_grayscale(im) final_image.append(im) # %% mean_image = images.mean(final_image) images.save(mean_image, direc + '/mean_image.png')
import os import numpy as np from Generic import filedialogs from Generic.equipment import pico_scope as scope from Shaker import power power_supply = power.PowerSupply() PicoScope = scope.Scope() direc = filedialogs.open_directory('Create a directory') if os.path.exists(direc) is False: os.mkdir(direc) for d in range(0, 1001, 1): print(d) power_supply.change_duty(d) for repeat in range(1, 6): times, data, _ = PicoScope.get_V(refine_range=True) np.savetxt(direc + '/times_{}_r{}.txt'.format(d, repeat), times) np.savetxt(direc + '/voltage_{}_r{}.txt'.format(d, repeat), data) power_supply.quit()
from Generic import filedialogs from ParticleTracking import linking, configurations import logging ch = logging.StreamHandler() formatter = logging.Formatter('\x1b[80D\x1b[1A\x1b[K%(message)s') ch.setFormatter(formatter) directory = filedialogs.open_directory('') files = filedialogs.get_files_directory(directory + '/*.hdf5') config = configurations.TRACKPY_NITRILE_PARAMETERS for file in files: print(file) linker = linking.Linker(file) linker.link(config['search_range'], memory=config['memory'])
from Generic import filedialogs from ParticleTracking import correlations directory = filedialogs.open_directory('Open Directory containing videos') files = filedialogs.get_files_directory(directory + '/*.hdf5') for file in files: if 'corr' not in file: print(file) correlations.calculate_corr_data(file)
import matplotlib.pyplot as plt import numpy as np import seaborn as sns from scipy import signal, optimize from tqdm import tqdm from Generic import filedialogs sns.set() #%% direc = filedialogs.open_directory('select a directory') #%% times = np.loadtxt(direc + '/times_452.txt') voltage = np.loadtxt(direc + '/voltage_452.txt') plt.figure() plt.plot(times, voltage) plt.show() # %% n0 = 850 n1 = 950 times0, times1 = (np.loadtxt(direc + '/times_{}.txt'.format(n0)), np.loadtxt(direc + '/times_{}.txt'.format(n1))) voltage0, voltage1 = (np.loadtxt(direc + '/voltage_{}.txt'.format(n0)), np.loadtxt(direc + '/voltage_{}.txt'.format(n1))) plt.figure() plt.plot(times0, voltage0, label=n0) plt.plot(times1, voltage1, label=n1) plt.xlabel('Time (s)')