50 lines
1.7 KiB
Python
50 lines
1.7 KiB
Python
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from Baseline import get_baseline_class
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from CellData import CellData, icelldata_of_dir
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from models.LIFACnoise import LifacNoiseModel
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from Baseline import BaselineCellData, BaselineModel
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from os import listdir
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import numpy as np
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from IPython import embed
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import pyrelacs.DataLoader as Dl
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from ModelFit import ModelFit, get_best_fit
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from FiCurve import FICurveModel, FICurveCellData
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import os
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import matplotlib.pyplot as plt
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import functions as fu
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from scipy.optimize import curve_fit
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from scipy.signal import find_peaks
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from thunderfish.eventdetection import threshold_crossing_times, threshold_crossings, detect_peaks
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import helperFunctions as hF
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import models.smallModels as sM
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from stimuli.SinusoidalStepStimulus import SinusoidalStepStimulus
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from matplotlib import gridspec
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from plottools.axes import labelaxes_params
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def demo():
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""" Run a demonstration of the axes module.
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"""
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def afigure():
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fig = plt.figure()
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gs = gridspec.GridSpec(2, 3, width_ratios=[5, 1.5, 2.4])
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gs.update(left=0.075, bottom=0.14, right=0.985, top=0.9, wspace=0.6, hspace=0.6)
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ax1 = fig.add_subplot(gs[:, 0])
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ax2 = fig.add_subplot(gs[0, 1:])
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ax3 = fig.add_subplot(gs[1, 1])
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ax4 = fig.add_subplot(gs[1, 2])
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for ax in [ax1, ax2, ax3, ax4]:
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ax.set_xlabel('xlabel')
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ax.set_ylabel('ylabel')
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return fig, (ax1, ax2, ax3, ax4)
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labelaxes_params(xoffs='auto', yoffs=-1, labels='A', font=dict(fontweight='bold'))
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fig, axs = afigure()
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# axs[0].text(0.5, 0.5, 'fig.label_axes()', transform=axs[0].transAxes, ha='center')
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# axs[0].text(0.0, 0.0, 'X', transform=fig.transFigure, ha='left', va='bottom')
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fig.label_axes()
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plt.show()
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demo() |