Note
Go to the end to download the full example code
Fit a 2D PRF model#
Here we fit a 2D PRF model to data from the Szinte (2024)-dataset.
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
from IPython.display import HTML, display
from braincoder.utils.data import load_szinte2024
import numpy as np
import pandas as pd
# Load data
data = load_szinte2024()
stimulus = data['stimulus']
grid_coordinates = data['grid_coordinates']
# Set up a function to draw a single frame
def update(frame):
plt.clf() # Clear the current figure
plt.imshow(stimulus[frame, :, :].T, cmap='viridis')
plt.title(f"Frame {frame}")
# Create the animation
fig = plt.figure()
ani = FuncAnimation(fig, update, frames=range(stimulus.shape[0]), interval=100)
# Convert to HTML for easy display
HTML(ani.to_html5_video())
# Set up a PRF model
# Now we will set up fake PRFs just to show how the data is structured
# We make a 9-by-9 grid of simulated PRFs
x, y = np.meshgrid(np.linspace(-6, 6, 3), np.linspace(-4, 4, 3))
# Set them up in a parameter table
# All PRFs have the same baseline and amplitude
from braincoder.models import GaussianPRF2DWithHRF
from braincoder.hrf import SPMHRFModel
parameters = pd.DataFrame({'x':x.ravel(),
'y':y.ravel(),
'sd':2.5,
'baseline':0.0,
'amplitude':1.}).astype(np.float32)
model = GaussianPRF2DWithHRF(grid_coordinates=grid_coordinates,
paradigm=stimulus,
parameters=parameters,
hrf_model=SPMHRFModel(tr=data['tr']))
# Let's plot all the RFs
rfs = model.get_rf(as_frame=True)
for i, rf in rfs.groupby(level=0):
plt.subplot(3, 3, i+1)
plt.title(f'RF {i+1}')
plt.imshow(rf.unstack('y').loc[i].T)
plt.axis('off')
# We simulate data for the given paradigm and parameters and plot the resulting time series
import seaborn as sns
data = model.simulate(noise=1.)
data.columns.set_names('voxel', inplace=True)
tmp = data.stack().to_frame('activity')
sns.relplot(x='frame', y='activity', data=tmp.reset_index(), hue='voxel', kind='line', palette=sns.color_palette('tab10', n_colors=parameters.shape[0]), aspect=2.)
<seaborn.axisgrid.FacetGrid object at 0x1742e63b0>
# We can also fit parameters back to data
from braincoder.optimize import ParameterFitter
# We set up a parameter fitter
par_fitter = ParameterFitter(model, data, stimulus)
# We set up a grid of parameters to search over
x = np.linspace(-8, 8, 20)
y = np.linspace(-4, 4, 20)
sd = np.linspace(1, 5, 10)
# For now, we only use one amplitude and baseline, because we
# use a correlation cost function, which is indifferent to
# the overall scaling of the model
# We can easily estimate these later using OLS
amplitudes = [1.0]
baseline = [0.0]
# Note that the grids should be given in the correct order (can be found back in
# model.parameter_labels)
grid_pars = par_fitter.fit_grid(x, y, sd, baseline, amplitudes, use_correlation_cost=True)
# Once we have the best parameters from the grid, we can optimize the baseline
# and amplitude
refined_grid_pars = par_fitter.refine_baseline_and_amplitude(grid_pars)
# We get the explained variance of these parameters
from braincoder.utils import get_rsq
refined_grid_r2 = get_rsq(data, model.predict(parameters=refined_grid_pars))
# Now we use gradient descent to further optimize the parameters
pars = par_fitter.fit(init_pars=refined_grid_pars, learning_rate=1e-2, max_n_iterations=5000,
min_n_iterations=100,
r2_atol=0.0001)
fitted_r2 = get_rsq(data, model.predict(parameters=pars))
# The fitted R2s tend to be a bit better than the grid R2s
display(refined_grid_r2.to_frame('r2').join(fitted_r2.to_frame('r2'), lsuffix='_grid', rsuffix='_fitted'))
# The real parameters are very similar to the estimated parameters
display(pars.join(parameters, lsuffix='_fit', rsuffix='_true'))
Working with chunk size of 493827
Using correlation cost!
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Number of problematic voxels (mask): 0
Number of voxels remaining (mask): 9
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Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 134/5000 [00:01<00:30, 160.27it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 134/5000 [00:01<00:30, 160.27it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 134/5000 [00:01<00:30, 160.27it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 134/5000 [00:01<00:30, 160.27it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 134/5000 [00:01<00:30, 160.27it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 134/5000 [00:01<00:30, 160.27it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 134/5000 [00:01<00:30, 160.27it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 134/5000 [00:01<00:30, 160.27it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 134/5000 [00:01<00:30, 160.27it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 134/5000 [00:01<00:30, 160.27it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 134/5000 [00:01<00:30, 160.27it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 134/5000 [00:01<00:30, 160.27it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 134/5000 [00:01<00:30, 160.27it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 134/5000 [00:01<00:30, 160.27it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 134/5000 [00:01<00:30, 160.27it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 134/5000 [00:01<00:30, 160.27it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 134/5000 [00:01<00:30, 160.27it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 154/5000 [00:01<00:28, 169.43it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 154/5000 [00:01<00:28, 169.43it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 154/5000 [00:01<00:28, 169.43it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 154/5000 [00:01<00:28, 169.43it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 154/5000 [00:01<00:28, 169.43it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 154/5000 [00:01<00:28, 169.43it/s]
Current R2: 0.83567/Best R2: 0.83567: 3%|▎ | 154/5000 [00:01<00:40, 119.46it/s]
r2_grid r2_fitted
voxel
0 0.824868 0.828932
1 0.797670 0.801265
2 0.824878 0.827677
3 0.870314 0.875129
4 0.868841 0.872212
5 0.870115 0.876152
6 0.832838 0.839583
7 0.799692 0.806287
8 0.785446 0.793833
x_fit y_fit sd_fit baseline_fit amplitude_fit x_true y_true sd_true baseline_true amplitude_true
voxel
0 -6.082412 -3.095559 2.002349 0.362517 0.887169 -6.0 -4.0 2.5 0.0 1.0
1 -0.161248 -4.214838 2.708304 0.001365 1.036097 0.0 -4.0 2.5 0.0 1.0
2 6.071422 -3.268449 1.980779 0.091875 0.981898 6.0 -4.0 2.5 0.0 1.0
3 -5.993935 0.147049 2.326955 0.090884 1.033542 -6.0 0.0 2.5 0.0 1.0
4 0.217859 0.221512 2.600718 0.001285 0.995714 0.0 0.0 2.5 0.0 1.0
5 5.822233 -0.074940 2.463377 -0.141839 1.024832 6.0 0.0 2.5 0.0 1.0
6 -5.958484 4.140279 2.500950 -0.064439 1.055699 -6.0 4.0 2.5 0.0 1.0
7 -0.043025 3.928314 2.412460 0.088119 0.967487 0.0 4.0 2.5 0.0 1.0
8 6.003477 4.873376 2.840907 -0.208204 1.177829 6.0 4.0 2.5 0.0 1.0
# Decode the *stimulus* from "unseen" data:
# First we need to fit a noise model
from braincoder.optimize import ResidualFitter
resid_fitter = ResidualFitter(model, data, stimulus, parameters=pars)
omega, dof = resid_fitter.fit()
# Simulate new "unseen" data
unseen_data = model.simulate(noise=1.)
# For stimulus reconstruction, we slightly downsample the stimulus space
# otherwise the optimization takes too long on a CPU
# we can do that by simply setting up a new model with a different grid
data = load_szinte2024(resize_factor=2.5)
grid_coordinates = data['grid_coordinates']
stimulus = data['stimulus']
model = GaussianPRF2DWithHRF(grid_coordinates=grid_coordinates,
parameters=parameters,
hrf_model=SPMHRFModel(tr=data['tr']))
# We set up a stimulus fitter
from braincoder.optimize import StimulusFitter
stim_fitter = StimulusFitter(unseen_data, model, omega)
# Legacy Adam is a bit faster than the default Adam optimizer on M1
# Learning rate of 1.0 is a bit high, but works well here
reconstructed_stimulus = stim_fitter.fit(legacy_adam=True, min_n_iterations=200, max_n_iterations=200, learning_rate=.1)
# Here we make a movie of the decoded stimulus
# Set up a function to draw a single frame
vmin, vmax = 0.0, np.quantile(reconstructed_stimulus.values.ravel(), 0.95)
def update(frame):
plt.clf() # Clear the current figure
plt.imshow(reconstructed_stimulus.stack('y').loc[frame], cmap='viridis', vmin=vmin, vmax=vmax)
plt.axis('off')
plt.title(f"Frame {frame}")
# Create the animation
fig = plt.figure()
ani = FuncAnimation(fig, update, frames=range(stimulus.shape[0]), interval=100)
HTML(ani.to_html5_video())
init_tau: 0.897517204284668, 1.071190357208252
USING A PSEUDO-WWT!
WWT max: 0.026428351178765297
0%| | 0/1000 [00:00<?, ?it/s]
fit stat: 1913.0149 (best: 1913.0149, rho: 0.098, sigma2: 0.001, mean tau: 1.0032: 0%| | 0/1000 [00:00<?, ?it/s]
fit stat: 1913.0149 (best: 1913.0149, rho: 0.098, sigma2: 0.001, mean tau: 1.0032: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1912.1532 (best: 1912.1532, rho: 0.096, sigma2: 0.001, mean tau: 1.0138: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1911.7467 (best: 1911.7467, rho: 0.095, sigma2: 0.001, mean tau: 1.0202: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1911.5450 (best: 1911.5450, rho: 0.093, sigma2: 0.001, mean tau: 1.0220: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1911.3282 (best: 1911.3282, rho: 0.091, sigma2: 0.001, mean tau: 1.0203: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1911.0270 (best: 1911.0270, rho: 0.090, sigma2: 0.001, mean tau: 1.0167: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1910.6749 (best: 1910.6749, rho: 0.088, sigma2: 0.001, mean tau: 1.0122: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1910.3201 (best: 1910.3201, rho: 0.087, sigma2: 0.001, mean tau: 1.0078: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1909.9911 (best: 1909.9911, rho: 0.085, sigma2: 0.001, mean tau: 1.0040: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1909.7000 (best: 1909.7000, rho: 0.084, sigma2: 0.001, mean tau: 1.0011: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1909.4449 (best: 1909.4449, rho: 0.082, sigma2: 0.001, mean tau: 0.9994: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1909.2117 (best: 1909.2117, rho: 0.081, sigma2: 0.001, mean tau: 0.9987: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1908.9812 (best: 1908.9812, rho: 0.079, sigma2: 0.001, mean tau: 0.9989: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1908.7404 (best: 1908.7404, rho: 0.078, sigma2: 0.001, mean tau: 0.9998: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1908.4884 (best: 1908.4884, rho: 0.077, sigma2: 0.001, mean tau: 1.0009: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1908.2338 (best: 1908.2338, rho: 0.075, sigma2: 0.001, mean tau: 1.0020: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1907.9894 (best: 1907.9894, rho: 0.074, sigma2: 0.001, mean tau: 1.0031: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1907.7625 (best: 1907.7625, rho: 0.073, sigma2: 0.001, mean tau: 1.0038: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1907.5555 (best: 1907.5555, rho: 0.071, sigma2: 0.001, mean tau: 1.0042: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1907.3624 (best: 1907.3624, rho: 0.070, sigma2: 0.001, mean tau: 1.0041: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1907.1752 (best: 1907.1752, rho: 0.069, sigma2: 0.001, mean tau: 1.0037: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1906.9873 (best: 1906.9873, rho: 0.068, sigma2: 0.001, mean tau: 1.0029: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1906.7971 (best: 1906.7971, rho: 0.067, sigma2: 0.001, mean tau: 1.0018: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1906.6074 (best: 1906.6074, rho: 0.066, sigma2: 0.001, mean tau: 1.0006: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1906.4237 (best: 1906.4237, rho: 0.065, sigma2: 0.001, mean tau: 0.9993: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1906.2507 (best: 1906.2507, rho: 0.064, sigma2: 0.001, mean tau: 0.9981: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1906.0898 (best: 1906.0898, rho: 0.063, sigma2: 0.001, mean tau: 0.9970: 0%| | 1/1000 [00:00<02:58, 5.59it/s]
fit stat: 1906.0898 (best: 1906.0898, rho: 0.063, sigma2: 0.001, mean tau: 0.9970: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1905.9381 (best: 1905.9381, rho: 0.062, sigma2: 0.001, mean tau: 0.9962: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1905.7909 (best: 1905.7909, rho: 0.061, sigma2: 0.001, mean tau: 0.9958: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1905.6453 (best: 1905.6453, rho: 0.060, sigma2: 0.001, mean tau: 0.9957: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1905.4998 (best: 1905.4998, rho: 0.059, sigma2: 0.001, mean tau: 0.9958: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1905.3573 (best: 1905.3573, rho: 0.058, sigma2: 0.001, mean tau: 0.9962: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1905.2207 (best: 1905.2207, rho: 0.057, sigma2: 0.001, mean tau: 0.9967: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1905.0919 (best: 1905.0919, rho: 0.056, sigma2: 0.001, mean tau: 0.9971: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1904.9698 (best: 1904.9698, rho: 0.055, sigma2: 0.001, mean tau: 0.9974: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1904.8522 (best: 1904.8522, rho: 0.054, sigma2: 0.001, mean tau: 0.9975: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1904.7369 (best: 1904.7369, rho: 0.054, sigma2: 0.001, mean tau: 0.9973: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1904.6241 (best: 1904.6241, rho: 0.053, sigma2: 0.001, mean tau: 0.9968: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1904.5144 (best: 1904.5144, rho: 0.052, sigma2: 0.001, mean tau: 0.9962: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1904.4086 (best: 1904.4086, rho: 0.051, sigma2: 0.001, mean tau: 0.9955: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1904.3073 (best: 1904.3073, rho: 0.051, sigma2: 0.001, mean tau: 0.9947: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1904.2097 (best: 1904.2097, rho: 0.050, sigma2: 0.001, mean tau: 0.9941: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1904.1155 (best: 1904.1155, rho: 0.049, sigma2: 0.001, mean tau: 0.9935: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1904.0245 (best: 1904.0245, rho: 0.049, sigma2: 0.001, mean tau: 0.9932: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1903.9363 (best: 1903.9363, rho: 0.048, sigma2: 0.001, mean tau: 0.9932: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1903.8508 (best: 1903.8508, rho: 0.047, sigma2: 0.001, mean tau: 0.9932: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1903.7678 (best: 1903.7678, rho: 0.047, sigma2: 0.002, mean tau: 0.9934: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1903.6873 (best: 1903.6873, rho: 0.046, sigma2: 0.002, mean tau: 0.9937: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1903.6099 (best: 1903.6099, rho: 0.046, sigma2: 0.002, mean tau: 0.9938: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1903.5349 (best: 1903.5349, rho: 0.045, sigma2: 0.002, mean tau: 0.9939: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1903.4626 (best: 1903.4626, rho: 0.045, sigma2: 0.002, mean tau: 0.9939: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1903.3928 (best: 1903.3928, rho: 0.044, sigma2: 0.002, mean tau: 0.9936: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1903.3247 (best: 1903.3247, rho: 0.044, sigma2: 0.002, mean tau: 0.9933: 3%|▎ | 27/1000 [00:00<00:08, 118.37it/s]
fit stat: 1903.3247 (best: 1903.3247, rho: 0.044, sigma2: 0.002, mean tau: 0.9933: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1903.2587 (best: 1903.2587, rho: 0.043, sigma2: 0.002, mean tau: 0.9928: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1903.1948 (best: 1903.1948, rho: 0.043, sigma2: 0.002, mean tau: 0.9923: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1903.1328 (best: 1903.1328, rho: 0.042, sigma2: 0.002, mean tau: 0.9919: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1903.0730 (best: 1903.0730, rho: 0.042, sigma2: 0.002, mean tau: 0.9915: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1903.0149 (best: 1903.0149, rho: 0.041, sigma2: 0.002, mean tau: 0.9914: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1902.9584 (best: 1902.9584, rho: 0.041, sigma2: 0.002, mean tau: 0.9913: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1902.9036 (best: 1902.9036, rho: 0.040, sigma2: 0.002, mean tau: 0.9914: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1902.8503 (best: 1902.8503, rho: 0.040, sigma2: 0.002, mean tau: 0.9915: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1902.7988 (best: 1902.7988, rho: 0.039, sigma2: 0.002, mean tau: 0.9916: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1902.7488 (best: 1902.7488, rho: 0.039, sigma2: 0.002, mean tau: 0.9916: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1902.7000 (best: 1902.7000, rho: 0.039, sigma2: 0.002, mean tau: 0.9915: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1902.6528 (best: 1902.6528, rho: 0.038, sigma2: 0.002, mean tau: 0.9912: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1902.6066 (best: 1902.6066, rho: 0.038, sigma2: 0.002, mean tau: 0.9909: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1902.5618 (best: 1902.5618, rho: 0.037, sigma2: 0.002, mean tau: 0.9906: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1902.5183 (best: 1902.5183, rho: 0.037, sigma2: 0.002, mean tau: 0.9903: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1902.4760 (best: 1902.4760, rho: 0.037, sigma2: 0.002, mean tau: 0.9900: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1902.4346 (best: 1902.4346, rho: 0.036, sigma2: 0.002, mean tau: 0.9898: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1902.3943 (best: 1902.3943, rho: 0.036, sigma2: 0.002, mean tau: 0.9898: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1902.3552 (best: 1902.3552, rho: 0.036, sigma2: 0.002, mean tau: 0.9897: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1902.3169 (best: 1902.3169, rho: 0.035, sigma2: 0.002, mean tau: 0.9896: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1902.2797 (best: 1902.2797, rho: 0.035, sigma2: 0.002, mean tau: 0.9895: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1902.2432 (best: 1902.2432, rho: 0.035, sigma2: 0.003, mean tau: 0.9894: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1902.2076 (best: 1902.2076, rho: 0.034, sigma2: 0.003, mean tau: 0.9892: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1902.1729 (best: 1902.1729, rho: 0.034, sigma2: 0.003, mean tau: 0.9890: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1902.1390 (best: 1902.1390, rho: 0.034, sigma2: 0.003, mean tau: 0.9888: 5%|▌ | 53/1000 [00:00<00:05, 171.77it/s]
fit stat: 1902.1390 (best: 1902.1390, rho: 0.034, sigma2: 0.003, mean tau: 0.9888: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1902.1058 (best: 1902.1058, rho: 0.033, sigma2: 0.003, mean tau: 0.9886: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1902.0735 (best: 1902.0735, rho: 0.033, sigma2: 0.003, mean tau: 0.9883: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1902.0419 (best: 1902.0419, rho: 0.033, sigma2: 0.003, mean tau: 0.9882: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1902.0107 (best: 1902.0107, rho: 0.033, sigma2: 0.003, mean tau: 0.9880: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.9805 (best: 1901.9805, rho: 0.032, sigma2: 0.003, mean tau: 0.9878: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.9506 (best: 1901.9506, rho: 0.032, sigma2: 0.003, mean tau: 0.9876: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.9214 (best: 1901.9214, rho: 0.032, sigma2: 0.003, mean tau: 0.9874: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.8929 (best: 1901.8929, rho: 0.031, sigma2: 0.003, mean tau: 0.9871: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.8646 (best: 1901.8646, rho: 0.031, sigma2: 0.003, mean tau: 0.9869: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.8372 (best: 1901.8372, rho: 0.031, sigma2: 0.004, mean tau: 0.9867: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.8103 (best: 1901.8103, rho: 0.031, sigma2: 0.004, mean tau: 0.9865: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.7837 (best: 1901.7837, rho: 0.030, sigma2: 0.004, mean tau: 0.9863: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.7577 (best: 1901.7577, rho: 0.030, sigma2: 0.004, mean tau: 0.9860: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.7321 (best: 1901.7321, rho: 0.030, sigma2: 0.004, mean tau: 0.9857: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.7070 (best: 1901.7070, rho: 0.030, sigma2: 0.004, mean tau: 0.9855: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.6821 (best: 1901.6821, rho: 0.030, sigma2: 0.004, mean tau: 0.9852: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.6577 (best: 1901.6577, rho: 0.029, sigma2: 0.004, mean tau: 0.9849: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.6337 (best: 1901.6337, rho: 0.029, sigma2: 0.005, mean tau: 0.9846: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.6100 (best: 1901.6100, rho: 0.029, sigma2: 0.005, mean tau: 0.9843: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.5869 (best: 1901.5869, rho: 0.029, sigma2: 0.005, mean tau: 0.9840: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.5640 (best: 1901.5640, rho: 0.028, sigma2: 0.005, mean tau: 0.9837: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.5415 (best: 1901.5415, rho: 0.028, sigma2: 0.005, mean tau: 0.9834: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.5192 (best: 1901.5192, rho: 0.028, sigma2: 0.005, mean tau: 0.9831: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.4972 (best: 1901.4972, rho: 0.028, sigma2: 0.006, mean tau: 0.9827: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.4758 (best: 1901.4758, rho: 0.028, sigma2: 0.006, mean tau: 0.9823: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.4546 (best: 1901.4546, rho: 0.027, sigma2: 0.006, mean tau: 0.9820: 8%|▊ | 78/1000 [00:00<00:04, 199.05it/s]
fit stat: 1901.4546 (best: 1901.4546, rho: 0.027, sigma2: 0.006, mean tau: 0.9820: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.4338 (best: 1901.4338, rho: 0.027, sigma2: 0.006, mean tau: 0.9816: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.4133 (best: 1901.4133, rho: 0.027, sigma2: 0.006, mean tau: 0.9812: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.3931 (best: 1901.3931, rho: 0.027, sigma2: 0.006, mean tau: 0.9808: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.3732 (best: 1901.3732, rho: 0.027, sigma2: 0.007, mean tau: 0.9804: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.3538 (best: 1901.3538, rho: 0.027, sigma2: 0.007, mean tau: 0.9800: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.3346 (best: 1901.3346, rho: 0.026, sigma2: 0.007, mean tau: 0.9796: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.3158 (best: 1901.3158, rho: 0.026, sigma2: 0.007, mean tau: 0.9792: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.2972 (best: 1901.2972, rho: 0.026, sigma2: 0.008, mean tau: 0.9788: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.2792 (best: 1901.2792, rho: 0.026, sigma2: 0.008, mean tau: 0.9784: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.2614 (best: 1901.2614, rho: 0.026, sigma2: 0.008, mean tau: 0.9779: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.2440 (best: 1901.2440, rho: 0.025, sigma2: 0.008, mean tau: 0.9775: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.2271 (best: 1901.2271, rho: 0.025, sigma2: 0.008, mean tau: 0.9771: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.2107 (best: 1901.2107, rho: 0.025, sigma2: 0.009, mean tau: 0.9766: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.1943 (best: 1901.1943, rho: 0.025, sigma2: 0.009, mean tau: 0.9762: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.1785 (best: 1901.1785, rho: 0.025, sigma2: 0.009, mean tau: 0.9758: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.1631 (best: 1901.1631, rho: 0.025, sigma2: 0.009, mean tau: 0.9754: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.1476 (best: 1901.1476, rho: 0.025, sigma2: 0.009, mean tau: 0.9750: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.1328 (best: 1901.1328, rho: 0.024, sigma2: 0.010, mean tau: 0.9746: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.1183 (best: 1901.1183, rho: 0.024, sigma2: 0.010, mean tau: 0.9743: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.1041 (best: 1901.1041, rho: 0.024, sigma2: 0.010, mean tau: 0.9739: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.0905 (best: 1901.0905, rho: 0.024, sigma2: 0.010, mean tau: 0.9736: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.0765 (best: 1901.0765, rho: 0.024, sigma2: 0.010, mean tau: 0.9733: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.0632 (best: 1901.0632, rho: 0.024, sigma2: 0.010, mean tau: 0.9731: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.0499 (best: 1901.0499, rho: 0.023, sigma2: 0.011, mean tau: 0.9728: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.0370 (best: 1901.0370, rho: 0.023, sigma2: 0.011, mean tau: 0.9726: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.0242 (best: 1901.0242, rho: 0.023, sigma2: 0.011, mean tau: 0.9725: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1901.0114 (best: 1901.0114, rho: 0.023, sigma2: 0.011, mean tau: 0.9723: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1900.9990 (best: 1900.9990, rho: 0.023, sigma2: 0.011, mean tau: 0.9722: 10%|█ | 104/1000 [00:00<00:04, 218.87it/s]
fit stat: 1900.9990 (best: 1900.9990, rho: 0.023, sigma2: 0.011, mean tau: 0.9722: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.9867 (best: 1900.9867, rho: 0.023, sigma2: 0.011, mean tau: 0.9721: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.9745 (best: 1900.9745, rho: 0.023, sigma2: 0.011, mean tau: 0.9720: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.9624 (best: 1900.9624, rho: 0.022, sigma2: 0.011, mean tau: 0.9719: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.9506 (best: 1900.9506, rho: 0.022, sigma2: 0.011, mean tau: 0.9719: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.9388 (best: 1900.9388, rho: 0.022, sigma2: 0.011, mean tau: 0.9719: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.9274 (best: 1900.9274, rho: 0.022, sigma2: 0.011, mean tau: 0.9719: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.9160 (best: 1900.9160, rho: 0.022, sigma2: 0.011, mean tau: 0.9719: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.9045 (best: 1900.9045, rho: 0.022, sigma2: 0.011, mean tau: 0.9719: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.8937 (best: 1900.8937, rho: 0.022, sigma2: 0.011, mean tau: 0.9719: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.8827 (best: 1900.8827, rho: 0.022, sigma2: 0.011, mean tau: 0.9719: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.8719 (best: 1900.8719, rho: 0.021, sigma2: 0.011, mean tau: 0.9719: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.8612 (best: 1900.8612, rho: 0.021, sigma2: 0.011, mean tau: 0.9719: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.8510 (best: 1900.8510, rho: 0.021, sigma2: 0.011, mean tau: 0.9719: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.8407 (best: 1900.8407, rho: 0.021, sigma2: 0.011, mean tau: 0.9719: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.8307 (best: 1900.8307, rho: 0.021, sigma2: 0.011, mean tau: 0.9719: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.8208 (best: 1900.8208, rho: 0.021, sigma2: 0.011, mean tau: 0.9719: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.8109 (best: 1900.8109, rho: 0.021, sigma2: 0.011, mean tau: 0.9719: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.8013 (best: 1900.8013, rho: 0.021, sigma2: 0.011, mean tau: 0.9718: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.7917 (best: 1900.7917, rho: 0.020, sigma2: 0.011, mean tau: 0.9718: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.7822 (best: 1900.7822, rho: 0.020, sigma2: 0.011, mean tau: 0.9717: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.7732 (best: 1900.7732, rho: 0.020, sigma2: 0.011, mean tau: 0.9716: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.7638 (best: 1900.7638, rho: 0.020, sigma2: 0.011, mean tau: 0.9716: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.7550 (best: 1900.7550, rho: 0.020, sigma2: 0.011, mean tau: 0.9715: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.7460 (best: 1900.7460, rho: 0.020, sigma2: 0.011, mean tau: 0.9714: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.7372 (best: 1900.7372, rho: 0.020, sigma2: 0.011, mean tau: 0.9713: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.7284 (best: 1900.7284, rho: 0.020, sigma2: 0.011, mean tau: 0.9712: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.7201 (best: 1900.7201, rho: 0.020, sigma2: 0.011, mean tau: 0.9711: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.7114 (best: 1900.7114, rho: 0.020, sigma2: 0.011, mean tau: 0.9710: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.7031 (best: 1900.7031, rho: 0.019, sigma2: 0.011, mean tau: 0.9709: 13%|█▎ | 132/1000 [00:00<00:03, 237.83it/s]
fit stat: 1900.7031 (best: 1900.7031, rho: 0.019, sigma2: 0.011, mean tau: 0.9709: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.6949 (best: 1900.6949, rho: 0.019, sigma2: 0.011, mean tau: 0.9707: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.6869 (best: 1900.6869, rho: 0.019, sigma2: 0.011, mean tau: 0.9706: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.6787 (best: 1900.6787, rho: 0.019, sigma2: 0.011, mean tau: 0.9705: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.6709 (best: 1900.6709, rho: 0.019, sigma2: 0.012, mean tau: 0.9704: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.6628 (best: 1900.6628, rho: 0.019, sigma2: 0.012, mean tau: 0.9703: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.6553 (best: 1900.6553, rho: 0.019, sigma2: 0.012, mean tau: 0.9701: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.6476 (best: 1900.6476, rho: 0.019, sigma2: 0.012, mean tau: 0.9700: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.6400 (best: 1900.6400, rho: 0.019, sigma2: 0.012, mean tau: 0.9699: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.6326 (best: 1900.6326, rho: 0.019, sigma2: 0.012, mean tau: 0.9698: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.6254 (best: 1900.6254, rho: 0.018, sigma2: 0.012, mean tau: 0.9697: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.6180 (best: 1900.6180, rho: 0.018, sigma2: 0.012, mean tau: 0.9696: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.6110 (best: 1900.6110, rho: 0.018, sigma2: 0.012, mean tau: 0.9696: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.6039 (best: 1900.6039, rho: 0.018, sigma2: 0.012, mean tau: 0.9695: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.5968 (best: 1900.5968, rho: 0.018, sigma2: 0.012, mean tau: 0.9694: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.5898 (best: 1900.5898, rho: 0.018, sigma2: 0.012, mean tau: 0.9693: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.5831 (best: 1900.5831, rho: 0.018, sigma2: 0.012, mean tau: 0.9693: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.5763 (best: 1900.5763, rho: 0.018, sigma2: 0.012, mean tau: 0.9692: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.5695 (best: 1900.5695, rho: 0.018, sigma2: 0.012, mean tau: 0.9691: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.5630 (best: 1900.5630, rho: 0.018, sigma2: 0.012, mean tau: 0.9691: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.5564 (best: 1900.5564, rho: 0.018, sigma2: 0.012, mean tau: 0.9690: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.5500 (best: 1900.5500, rho: 0.017, sigma2: 0.012, mean tau: 0.9690: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.5436 (best: 1900.5436, rho: 0.017, sigma2: 0.012, mean tau: 0.9689: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.5375 (best: 1900.5375, rho: 0.017, sigma2: 0.012, mean tau: 0.9689: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.5311 (best: 1900.5311, rho: 0.017, sigma2: 0.012, mean tau: 0.9688: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.5249 (best: 1900.5249, rho: 0.017, sigma2: 0.012, mean tau: 0.9688: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.5189 (best: 1900.5189, rho: 0.017, sigma2: 0.012, mean tau: 0.9687: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.5127 (best: 1900.5127, rho: 0.017, sigma2: 0.012, mean tau: 0.9687: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.5068 (best: 1900.5068, rho: 0.017, sigma2: 0.012, mean tau: 0.9686: 16%|█▌ | 161/1000 [00:00<00:03, 252.12it/s]
fit stat: 1900.5068 (best: 1900.5068, rho: 0.017, sigma2: 0.012, mean tau: 0.9686: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.5010 (best: 1900.5010, rho: 0.017, sigma2: 0.012, mean tau: 0.9686: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.4951 (best: 1900.4951, rho: 0.017, sigma2: 0.012, mean tau: 0.9685: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.4893 (best: 1900.4893, rho: 0.017, sigma2: 0.012, mean tau: 0.9684: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.4836 (best: 1900.4836, rho: 0.017, sigma2: 0.012, mean tau: 0.9684: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.4780 (best: 1900.4780, rho: 0.017, sigma2: 0.012, mean tau: 0.9683: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.4724 (best: 1900.4724, rho: 0.016, sigma2: 0.013, mean tau: 0.9683: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.4668 (best: 1900.4668, rho: 0.016, sigma2: 0.013, mean tau: 0.9682: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.4614 (best: 1900.4614, rho: 0.016, sigma2: 0.013, mean tau: 0.9681: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.4561 (best: 1900.4561, rho: 0.016, sigma2: 0.013, mean tau: 0.9681: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.4507 (best: 1900.4507, rho: 0.016, sigma2: 0.013, mean tau: 0.9680: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.4454 (best: 1900.4454, rho: 0.016, sigma2: 0.013, mean tau: 0.9679: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.4402 (best: 1900.4402, rho: 0.016, sigma2: 0.013, mean tau: 0.9679: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.4349 (best: 1900.4349, rho: 0.016, sigma2: 0.013, mean tau: 0.9678: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.4297 (best: 1900.4297, rho: 0.016, sigma2: 0.013, mean tau: 0.9677: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.4248 (best: 1900.4248, rho: 0.016, sigma2: 0.013, mean tau: 0.9677: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.4197 (best: 1900.4197, rho: 0.016, sigma2: 0.013, mean tau: 0.9676: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.4148 (best: 1900.4148, rho: 0.016, sigma2: 0.013, mean tau: 0.9676: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.4099 (best: 1900.4099, rho: 0.016, sigma2: 0.013, mean tau: 0.9675: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.4050 (best: 1900.4050, rho: 0.016, sigma2: 0.013, mean tau: 0.9674: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.4001 (best: 1900.4001, rho: 0.016, sigma2: 0.013, mean tau: 0.9674: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.3955 (best: 1900.3955, rho: 0.015, sigma2: 0.013, mean tau: 0.9673: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.3906 (best: 1900.3906, rho: 0.015, sigma2: 0.013, mean tau: 0.9673: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.3860 (best: 1900.3860, rho: 0.015, sigma2: 0.013, mean tau: 0.9672: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.3815 (best: 1900.3815, rho: 0.015, sigma2: 0.013, mean tau: 0.9672: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.3767 (best: 1900.3767, rho: 0.015, sigma2: 0.013, mean tau: 0.9671: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.3724 (best: 1900.3724, rho: 0.015, sigma2: 0.013, mean tau: 0.9671: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.3678 (best: 1900.3678, rho: 0.015, sigma2: 0.013, mean tau: 0.9670: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.3633 (best: 1900.3633, rho: 0.015, sigma2: 0.013, mean tau: 0.9670: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.3589 (best: 1900.3589, rho: 0.015, sigma2: 0.013, mean tau: 0.9669: 19%|█▉ | 189/1000 [00:00<00:03, 260.52it/s]
fit stat: 1900.3589 (best: 1900.3589, rho: 0.015, sigma2: 0.013, mean tau: 0.9669: 22%|██▏ | 218/1000 [00:00<00:02, 269.37it/s]
fit stat: 1900.3546 (best: 1900.3546, rho: 0.015, sigma2: 0.013, mean tau: 0.9669: 22%|██▏ | 218/1000 [00:00<00:02, 269.37it/s]
fit stat: 1900.3503 (best: 1900.3503, rho: 0.015, sigma2: 0.013, mean tau: 0.9668: 22%|██▏ | 218/1000 [00:00<00:02, 269.37it/s]
fit stat: 1900.3458 (best: 1900.3458, rho: 0.015, sigma2: 0.013, mean tau: 0.9668: 22%|██▏ | 218/1000 [00:00<00:02, 269.37it/s]
fit stat: 1900.3416 (best: 1900.3416, rho: 0.015, sigma2: 0.013, mean tau: 0.9667: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.3375 (best: 1900.3375, rho: 0.015, sigma2: 0.013, mean tau: 0.9667: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.3334 (best: 1900.3334, rho: 0.015, sigma2: 0.013, mean tau: 0.9666: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.3291 (best: 1900.3291, rho: 0.015, sigma2: 0.013, mean tau: 0.9666: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.3251 (best: 1900.3251, rho: 0.014, sigma2: 0.013, mean tau: 0.9665: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.3208 (best: 1900.3208, rho: 0.014, sigma2: 0.013, mean tau: 0.9665: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.3170 (best: 1900.3170, rho: 0.014, sigma2: 0.013, mean tau: 0.9664: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.3131 (best: 1900.3131, rho: 0.014, sigma2: 0.013, mean tau: 0.9664: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.3091 (best: 1900.3091, rho: 0.014, sigma2: 0.013, mean tau: 0.9663: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.3053 (best: 1900.3053, rho: 0.014, sigma2: 0.013, mean tau: 0.9663: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.3013 (best: 1900.3013, rho: 0.014, sigma2: 0.013, mean tau: 0.9662: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.2976 (best: 1900.2976, rho: 0.014, sigma2: 0.013, mean tau: 0.9662: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.2937 (best: 1900.2937, rho: 0.014, sigma2: 0.013, mean tau: 0.9661: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.2898 (best: 1900.2898, rho: 0.014, sigma2: 0.014, mean tau: 0.9661: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.2860 (best: 1900.2860, rho: 0.014, sigma2: 0.014, mean tau: 0.9660: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.2823 (best: 1900.2823, rho: 0.014, sigma2: 0.014, mean tau: 0.9660: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.2788 (best: 1900.2788, rho: 0.014, sigma2: 0.014, mean tau: 0.9660: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.2753 (best: 1900.2753, rho: 0.014, sigma2: 0.014, mean tau: 0.9659: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.2717 (best: 1900.2717, rho: 0.014, sigma2: 0.014, mean tau: 0.9659: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.2679 (best: 1900.2679, rho: 0.014, sigma2: 0.014, mean tau: 0.9658: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.2643 (best: 1900.2643, rho: 0.014, sigma2: 0.014, mean tau: 0.9658: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.2609 (best: 1900.2609, rho: 0.014, sigma2: 0.014, mean tau: 0.9657: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.2574 (best: 1900.2574, rho: 0.013, sigma2: 0.014, mean tau: 0.9657: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.2540 (best: 1900.2540, rho: 0.013, sigma2: 0.014, mean tau: 0.9656: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.2506 (best: 1900.2506, rho: 0.013, sigma2: 0.014, mean tau: 0.9656: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.2473 (best: 1900.2473, rho: 0.013, sigma2: 0.014, mean tau: 0.9656: 22%|██▏ | 218/1000 [00:01<00:02, 269.37it/s]
fit stat: 1900.2473 (best: 1900.2473, rho: 0.013, sigma2: 0.014, mean tau: 0.9656: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.2438 (best: 1900.2438, rho: 0.013, sigma2: 0.014, mean tau: 0.9655: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.2405 (best: 1900.2405, rho: 0.013, sigma2: 0.014, mean tau: 0.9655: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.2372 (best: 1900.2372, rho: 0.013, sigma2: 0.014, mean tau: 0.9654: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.2339 (best: 1900.2339, rho: 0.013, sigma2: 0.014, mean tau: 0.9654: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.2306 (best: 1900.2306, rho: 0.013, sigma2: 0.014, mean tau: 0.9654: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.2274 (best: 1900.2274, rho: 0.013, sigma2: 0.014, mean tau: 0.9653: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.2242 (best: 1900.2242, rho: 0.013, sigma2: 0.014, mean tau: 0.9653: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.2209 (best: 1900.2209, rho: 0.013, sigma2: 0.014, mean tau: 0.9652: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.2179 (best: 1900.2179, rho: 0.013, sigma2: 0.014, mean tau: 0.9652: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.2148 (best: 1900.2148, rho: 0.013, sigma2: 0.014, mean tau: 0.9652: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.2118 (best: 1900.2118, rho: 0.013, sigma2: 0.014, mean tau: 0.9651: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.2087 (best: 1900.2087, rho: 0.013, sigma2: 0.014, mean tau: 0.9651: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.2057 (best: 1900.2057, rho: 0.013, sigma2: 0.014, mean tau: 0.9650: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.2025 (best: 1900.2025, rho: 0.013, sigma2: 0.014, mean tau: 0.9650: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.1995 (best: 1900.1995, rho: 0.013, sigma2: 0.014, mean tau: 0.9650: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.1965 (best: 1900.1965, rho: 0.013, sigma2: 0.014, mean tau: 0.9649: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.1936 (best: 1900.1936, rho: 0.013, sigma2: 0.014, mean tau: 0.9649: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.1907 (best: 1900.1907, rho: 0.013, sigma2: 0.014, mean tau: 0.9648: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.1876 (best: 1900.1876, rho: 0.012, sigma2: 0.014, mean tau: 0.9648: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.1848 (best: 1900.1848, rho: 0.012, sigma2: 0.014, mean tau: 0.9648: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.1821 (best: 1900.1821, rho: 0.012, sigma2: 0.014, mean tau: 0.9647: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.1792 (best: 1900.1792, rho: 0.012, sigma2: 0.014, mean tau: 0.9647: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.1764 (best: 1900.1764, rho: 0.012, sigma2: 0.014, mean tau: 0.9647: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.1736 (best: 1900.1736, rho: 0.012, sigma2: 0.014, mean tau: 0.9646: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.1710 (best: 1900.1710, rho: 0.012, sigma2: 0.014, mean tau: 0.9646: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.1682 (best: 1900.1682, rho: 0.012, sigma2: 0.014, mean tau: 0.9645: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.1654 (best: 1900.1654, rho: 0.012, sigma2: 0.014, mean tau: 0.9645: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.1628 (best: 1900.1628, rho: 0.012, sigma2: 0.014, mean tau: 0.9645: 25%|██▍ | 247/1000 [00:01<00:02, 274.47it/s]
fit stat: 1900.1628 (best: 1900.1628, rho: 0.012, sigma2: 0.014, mean tau: 0.9645: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1602 (best: 1900.1602, rho: 0.012, sigma2: 0.014, mean tau: 0.9644: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1575 (best: 1900.1575, rho: 0.012, sigma2: 0.014, mean tau: 0.9644: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1548 (best: 1900.1548, rho: 0.012, sigma2: 0.014, mean tau: 0.9644: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1521 (best: 1900.1521, rho: 0.012, sigma2: 0.014, mean tau: 0.9643: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1495 (best: 1900.1495, rho: 0.012, sigma2: 0.014, mean tau: 0.9643: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1470 (best: 1900.1470, rho: 0.012, sigma2: 0.014, mean tau: 0.9643: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1444 (best: 1900.1444, rho: 0.012, sigma2: 0.014, mean tau: 0.9642: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1418 (best: 1900.1418, rho: 0.012, sigma2: 0.014, mean tau: 0.9642: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1393 (best: 1900.1393, rho: 0.012, sigma2: 0.014, mean tau: 0.9642: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1368 (best: 1900.1368, rho: 0.012, sigma2: 0.014, mean tau: 0.9641: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1343 (best: 1900.1343, rho: 0.012, sigma2: 0.014, mean tau: 0.9641: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1318 (best: 1900.1318, rho: 0.012, sigma2: 0.014, mean tau: 0.9641: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1294 (best: 1900.1294, rho: 0.012, sigma2: 0.014, mean tau: 0.9640: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1270 (best: 1900.1270, rho: 0.012, sigma2: 0.015, mean tau: 0.9640: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1245 (best: 1900.1245, rho: 0.011, sigma2: 0.015, mean tau: 0.9640: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1222 (best: 1900.1222, rho: 0.011, sigma2: 0.015, mean tau: 0.9639: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1198 (best: 1900.1198, rho: 0.011, sigma2: 0.015, mean tau: 0.9639: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1174 (best: 1900.1174, rho: 0.011, sigma2: 0.015, mean tau: 0.9639: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1150 (best: 1900.1150, rho: 0.011, sigma2: 0.015, mean tau: 0.9638: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1127 (best: 1900.1127, rho: 0.011, sigma2: 0.015, mean tau: 0.9638: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1102 (best: 1900.1102, rho: 0.011, sigma2: 0.015, mean tau: 0.9638: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1082 (best: 1900.1082, rho: 0.011, sigma2: 0.015, mean tau: 0.9637: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1060 (best: 1900.1060, rho: 0.011, sigma2: 0.015, mean tau: 0.9637: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1035 (best: 1900.1035, rho: 0.011, sigma2: 0.015, mean tau: 0.9637: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.1013 (best: 1900.1013, rho: 0.011, sigma2: 0.015, mean tau: 0.9636: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.0990 (best: 1900.0990, rho: 0.011, sigma2: 0.015, mean tau: 0.9636: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.0968 (best: 1900.0968, rho: 0.011, sigma2: 0.015, mean tau: 0.9636: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.0947 (best: 1900.0947, rho: 0.011, sigma2: 0.015, mean tau: 0.9635: 28%|██▊ | 275/1000 [00:01<00:02, 272.03it/s]
fit stat: 1900.0947 (best: 1900.0947, rho: 0.011, sigma2: 0.015, mean tau: 0.9635: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0925 (best: 1900.0925, rho: 0.011, sigma2: 0.015, mean tau: 0.9635: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0903 (best: 1900.0903, rho: 0.011, sigma2: 0.015, mean tau: 0.9635: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0881 (best: 1900.0881, rho: 0.011, sigma2: 0.015, mean tau: 0.9635: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0861 (best: 1900.0861, rho: 0.011, sigma2: 0.015, mean tau: 0.9634: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0839 (best: 1900.0839, rho: 0.011, sigma2: 0.015, mean tau: 0.9634: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0817 (best: 1900.0817, rho: 0.011, sigma2: 0.015, mean tau: 0.9634: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0796 (best: 1900.0796, rho: 0.011, sigma2: 0.015, mean tau: 0.9633: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0775 (best: 1900.0775, rho: 0.011, sigma2: 0.015, mean tau: 0.9633: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0757 (best: 1900.0757, rho: 0.011, sigma2: 0.015, mean tau: 0.9633: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0736 (best: 1900.0736, rho: 0.011, sigma2: 0.015, mean tau: 0.9633: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0714 (best: 1900.0714, rho: 0.011, sigma2: 0.015, mean tau: 0.9632: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0693 (best: 1900.0693, rho: 0.011, sigma2: 0.015, mean tau: 0.9632: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0674 (best: 1900.0674, rho: 0.011, sigma2: 0.015, mean tau: 0.9632: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0654 (best: 1900.0654, rho: 0.011, sigma2: 0.015, mean tau: 0.9631: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0634 (best: 1900.0634, rho: 0.011, sigma2: 0.015, mean tau: 0.9631: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0614 (best: 1900.0614, rho: 0.010, sigma2: 0.015, mean tau: 0.9631: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0593 (best: 1900.0593, rho: 0.010, sigma2: 0.015, mean tau: 0.9631: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0575 (best: 1900.0575, rho: 0.010, sigma2: 0.015, mean tau: 0.9630: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0555 (best: 1900.0555, rho: 0.010, sigma2: 0.015, mean tau: 0.9630: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0536 (best: 1900.0536, rho: 0.010, sigma2: 0.015, mean tau: 0.9630: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0516 (best: 1900.0516, rho: 0.010, sigma2: 0.015, mean tau: 0.9629: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0498 (best: 1900.0498, rho: 0.010, sigma2: 0.015, mean tau: 0.9629: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0479 (best: 1900.0479, rho: 0.010, sigma2: 0.015, mean tau: 0.9629: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0461 (best: 1900.0461, rho: 0.010, sigma2: 0.015, mean tau: 0.9629: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0443 (best: 1900.0443, rho: 0.010, sigma2: 0.015, mean tau: 0.9628: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0424 (best: 1900.0424, rho: 0.010, sigma2: 0.015, mean tau: 0.9628: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0404 (best: 1900.0404, rho: 0.010, sigma2: 0.015, mean tau: 0.9628: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0387 (best: 1900.0387, rho: 0.010, sigma2: 0.015, mean tau: 0.9628: 30%|███ | 303/1000 [00:01<00:02, 272.14it/s]
fit stat: 1900.0387 (best: 1900.0387, rho: 0.010, sigma2: 0.015, mean tau: 0.9628: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1900.0369 (best: 1900.0369, rho: 0.010, sigma2: 0.015, mean tau: 0.9627: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1900.0350 (best: 1900.0350, rho: 0.010, sigma2: 0.015, mean tau: 0.9627: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1900.0332 (best: 1900.0332, rho: 0.010, sigma2: 0.015, mean tau: 0.9627: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1900.0315 (best: 1900.0315, rho: 0.010, sigma2: 0.015, mean tau: 0.9626: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1900.0297 (best: 1900.0297, rho: 0.010, sigma2: 0.015, mean tau: 0.9626: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1900.0280 (best: 1900.0280, rho: 0.010, sigma2: 0.015, mean tau: 0.9626: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1900.0262 (best: 1900.0262, rho: 0.010, sigma2: 0.015, mean tau: 0.9626: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1900.0245 (best: 1900.0245, rho: 0.010, sigma2: 0.015, mean tau: 0.9625: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1900.0227 (best: 1900.0227, rho: 0.010, sigma2: 0.015, mean tau: 0.9625: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1900.0211 (best: 1900.0211, rho: 0.010, sigma2: 0.015, mean tau: 0.9625: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1900.0193 (best: 1900.0193, rho: 0.010, sigma2: 0.015, mean tau: 0.9625: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1900.0176 (best: 1900.0176, rho: 0.010, sigma2: 0.015, mean tau: 0.9624: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1900.0160 (best: 1900.0160, rho: 0.010, sigma2: 0.015, mean tau: 0.9624: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1900.0144 (best: 1900.0144, rho: 0.010, sigma2: 0.015, mean tau: 0.9624: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1900.0127 (best: 1900.0127, rho: 0.010, sigma2: 0.015, mean tau: 0.9624: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1900.0110 (best: 1900.0110, rho: 0.010, sigma2: 0.015, mean tau: 0.9623: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1900.0094 (best: 1900.0094, rho: 0.010, sigma2: 0.015, mean tau: 0.9623: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1900.0077 (best: 1900.0077, rho: 0.010, sigma2: 0.015, mean tau: 0.9623: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1900.0061 (best: 1900.0061, rho: 0.010, sigma2: 0.015, mean tau: 0.9623: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1900.0045 (best: 1900.0045, rho: 0.010, sigma2: 0.015, mean tau: 0.9622: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1900.0027 (best: 1900.0027, rho: 0.010, sigma2: 0.015, mean tau: 0.9622: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1900.0013 (best: 1900.0013, rho: 0.009, sigma2: 0.015, mean tau: 0.9622: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1899.9996 (best: 1899.9996, rho: 0.009, sigma2: 0.015, mean tau: 0.9622: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1899.9980 (best: 1899.9980, rho: 0.009, sigma2: 0.015, mean tau: 0.9622: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1899.9966 (best: 1899.9966, rho: 0.009, sigma2: 0.015, mean tau: 0.9621: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1899.9950 (best: 1899.9950, rho: 0.009, sigma2: 0.015, mean tau: 0.9621: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1899.9934 (best: 1899.9934, rho: 0.009, sigma2: 0.015, mean tau: 0.9621: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1899.9919 (best: 1899.9919, rho: 0.009, sigma2: 0.015, mean tau: 0.9621: 33%|███▎ | 331/1000 [00:01<00:02, 271.02it/s]
fit stat: 1899.9919 (best: 1899.9919, rho: 0.009, sigma2: 0.015, mean tau: 0.9621: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9904 (best: 1899.9904, rho: 0.009, sigma2: 0.015, mean tau: 0.9620: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9889 (best: 1899.9889, rho: 0.009, sigma2: 0.015, mean tau: 0.9620: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9874 (best: 1899.9874, rho: 0.009, sigma2: 0.015, mean tau: 0.9620: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9857 (best: 1899.9857, rho: 0.009, sigma2: 0.015, mean tau: 0.9620: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9843 (best: 1899.9843, rho: 0.009, sigma2: 0.015, mean tau: 0.9619: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9828 (best: 1899.9828, rho: 0.009, sigma2: 0.015, mean tau: 0.9619: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9812 (best: 1899.9812, rho: 0.009, sigma2: 0.016, mean tau: 0.9619: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9800 (best: 1899.9800, rho: 0.009, sigma2: 0.016, mean tau: 0.9619: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9785 (best: 1899.9785, rho: 0.009, sigma2: 0.016, mean tau: 0.9619: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9771 (best: 1899.9771, rho: 0.009, sigma2: 0.016, mean tau: 0.9618: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9756 (best: 1899.9756, rho: 0.009, sigma2: 0.016, mean tau: 0.9618: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9739 (best: 1899.9739, rho: 0.009, sigma2: 0.016, mean tau: 0.9618: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9728 (best: 1899.9728, rho: 0.009, sigma2: 0.016, mean tau: 0.9618: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9712 (best: 1899.9712, rho: 0.009, sigma2: 0.016, mean tau: 0.9617: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9700 (best: 1899.9700, rho: 0.009, sigma2: 0.016, mean tau: 0.9617: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9683 (best: 1899.9683, rho: 0.009, sigma2: 0.016, mean tau: 0.9617: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9670 (best: 1899.9670, rho: 0.009, sigma2: 0.016, mean tau: 0.9617: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9658 (best: 1899.9658, rho: 0.009, sigma2: 0.016, mean tau: 0.9617: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9644 (best: 1899.9644, rho: 0.009, sigma2: 0.016, mean tau: 0.9616: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9630 (best: 1899.9630, rho: 0.009, sigma2: 0.016, mean tau: 0.9616: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9615 (best: 1899.9615, rho: 0.009, sigma2: 0.016, mean tau: 0.9616: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9602 (best: 1899.9602, rho: 0.009, sigma2: 0.016, mean tau: 0.9616: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9587 (best: 1899.9587, rho: 0.009, sigma2: 0.016, mean tau: 0.9616: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9575 (best: 1899.9575, rho: 0.009, sigma2: 0.016, mean tau: 0.9615: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9563 (best: 1899.9563, rho: 0.009, sigma2: 0.016, mean tau: 0.9615: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9548 (best: 1899.9548, rho: 0.009, sigma2: 0.016, mean tau: 0.9615: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9536 (best: 1899.9536, rho: 0.009, sigma2: 0.016, mean tau: 0.9615: 36%|███▌ | 359/1000 [00:01<00:02, 264.77it/s]
fit stat: 1899.9536 (best: 1899.9536, rho: 0.009, sigma2: 0.016, mean tau: 0.9615: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9521 (best: 1899.9521, rho: 0.009, sigma2: 0.016, mean tau: 0.9615: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9508 (best: 1899.9508, rho: 0.009, sigma2: 0.016, mean tau: 0.9614: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9495 (best: 1899.9495, rho: 0.009, sigma2: 0.016, mean tau: 0.9614: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9482 (best: 1899.9482, rho: 0.009, sigma2: 0.016, mean tau: 0.9614: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9470 (best: 1899.9470, rho: 0.009, sigma2: 0.016, mean tau: 0.9614: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9458 (best: 1899.9458, rho: 0.009, sigma2: 0.016, mean tau: 0.9613: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9445 (best: 1899.9445, rho: 0.009, sigma2: 0.016, mean tau: 0.9613: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9432 (best: 1899.9432, rho: 0.009, sigma2: 0.016, mean tau: 0.9613: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9419 (best: 1899.9419, rho: 0.008, sigma2: 0.016, mean tau: 0.9613: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9407 (best: 1899.9407, rho: 0.008, sigma2: 0.016, mean tau: 0.9613: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9396 (best: 1899.9396, rho: 0.008, sigma2: 0.016, mean tau: 0.9613: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9382 (best: 1899.9382, rho: 0.008, sigma2: 0.016, mean tau: 0.9612: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9370 (best: 1899.9370, rho: 0.008, sigma2: 0.016, mean tau: 0.9612: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9358 (best: 1899.9358, rho: 0.008, sigma2: 0.016, mean tau: 0.9612: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9344 (best: 1899.9344, rho: 0.008, sigma2: 0.016, mean tau: 0.9612: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9332 (best: 1899.9332, rho: 0.008, sigma2: 0.016, mean tau: 0.9612: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9321 (best: 1899.9321, rho: 0.008, sigma2: 0.016, mean tau: 0.9611: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9309 (best: 1899.9309, rho: 0.008, sigma2: 0.016, mean tau: 0.9611: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9296 (best: 1899.9296, rho: 0.008, sigma2: 0.016, mean tau: 0.9611: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9285 (best: 1899.9285, rho: 0.008, sigma2: 0.016, mean tau: 0.9611: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9275 (best: 1899.9275, rho: 0.008, sigma2: 0.016, mean tau: 0.9611: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9260 (best: 1899.9260, rho: 0.008, sigma2: 0.016, mean tau: 0.9610: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9249 (best: 1899.9249, rho: 0.008, sigma2: 0.016, mean tau: 0.9610: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9238 (best: 1899.9238, rho: 0.008, sigma2: 0.016, mean tau: 0.9610: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9226 (best: 1899.9226, rho: 0.008, sigma2: 0.016, mean tau: 0.9610: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9216 (best: 1899.9216, rho: 0.008, sigma2: 0.016, mean tau: 0.9610: 39%|███▊ | 386/1000 [00:01<00:02, 213.90it/s]
fit stat: 1899.9216 (best: 1899.9216, rho: 0.008, sigma2: 0.016, mean tau: 0.9610: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.9204 (best: 1899.9204, rho: 0.008, sigma2: 0.016, mean tau: 0.9609: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.9192 (best: 1899.9192, rho: 0.008, sigma2: 0.016, mean tau: 0.9609: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.9182 (best: 1899.9182, rho: 0.008, sigma2: 0.016, mean tau: 0.9609: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.9170 (best: 1899.9170, rho: 0.008, sigma2: 0.016, mean tau: 0.9609: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.9160 (best: 1899.9160, rho: 0.008, sigma2: 0.016, mean tau: 0.9609: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.9150 (best: 1899.9150, rho: 0.008, sigma2: 0.016, mean tau: 0.9609: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.9138 (best: 1899.9138, rho: 0.008, sigma2: 0.016, mean tau: 0.9608: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.9126 (best: 1899.9126, rho: 0.008, sigma2: 0.016, mean tau: 0.9608: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.9115 (best: 1899.9115, rho: 0.008, sigma2: 0.016, mean tau: 0.9608: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.9104 (best: 1899.9104, rho: 0.008, sigma2: 0.016, mean tau: 0.9608: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.9094 (best: 1899.9094, rho: 0.008, sigma2: 0.016, mean tau: 0.9608: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.9081 (best: 1899.9081, rho: 0.008, sigma2: 0.016, mean tau: 0.9608: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.9072 (best: 1899.9072, rho: 0.008, sigma2: 0.016, mean tau: 0.9607: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.9061 (best: 1899.9061, rho: 0.008, sigma2: 0.016, mean tau: 0.9607: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.9052 (best: 1899.9052, rho: 0.008, sigma2: 0.016, mean tau: 0.9607: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.9038 (best: 1899.9038, rho: 0.008, sigma2: 0.016, mean tau: 0.9607: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.9030 (best: 1899.9030, rho: 0.008, sigma2: 0.016, mean tau: 0.9607: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.9019 (best: 1899.9019, rho: 0.008, sigma2: 0.016, mean tau: 0.9606: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.9009 (best: 1899.9009, rho: 0.008, sigma2: 0.016, mean tau: 0.9606: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.8998 (best: 1899.8998, rho: 0.008, sigma2: 0.016, mean tau: 0.9606: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.8988 (best: 1899.8988, rho: 0.008, sigma2: 0.016, mean tau: 0.9606: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.8977 (best: 1899.8977, rho: 0.008, sigma2: 0.016, mean tau: 0.9606: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.8967 (best: 1899.8967, rho: 0.008, sigma2: 0.016, mean tau: 0.9606: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.8956 (best: 1899.8956, rho: 0.008, sigma2: 0.016, mean tau: 0.9605: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.8948 (best: 1899.8948, rho: 0.008, sigma2: 0.016, mean tau: 0.9605: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.8937 (best: 1899.8937, rho: 0.008, sigma2: 0.016, mean tau: 0.9605: 41%|████ | 412/1000 [00:01<00:02, 224.36it/s]
fit stat: 1899.8937 (best: 1899.8937, rho: 0.008, sigma2: 0.016, mean tau: 0.9605: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8926 (best: 1899.8926, rho: 0.008, sigma2: 0.016, mean tau: 0.9605: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8917 (best: 1899.8917, rho: 0.008, sigma2: 0.016, mean tau: 0.9605: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8907 (best: 1899.8907, rho: 0.008, sigma2: 0.016, mean tau: 0.9605: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8898 (best: 1899.8898, rho: 0.008, sigma2: 0.016, mean tau: 0.9604: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8885 (best: 1899.8885, rho: 0.008, sigma2: 0.016, mean tau: 0.9604: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8877 (best: 1899.8877, rho: 0.008, sigma2: 0.016, mean tau: 0.9604: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8867 (best: 1899.8867, rho: 0.007, sigma2: 0.016, mean tau: 0.9604: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8859 (best: 1899.8859, rho: 0.007, sigma2: 0.016, mean tau: 0.9604: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8846 (best: 1899.8846, rho: 0.007, sigma2: 0.016, mean tau: 0.9604: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8838 (best: 1899.8838, rho: 0.007, sigma2: 0.016, mean tau: 0.9604: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8829 (best: 1899.8829, rho: 0.007, sigma2: 0.016, mean tau: 0.9603: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8820 (best: 1899.8820, rho: 0.007, sigma2: 0.016, mean tau: 0.9603: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8810 (best: 1899.8810, rho: 0.007, sigma2: 0.016, mean tau: 0.9603: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8800 (best: 1899.8800, rho: 0.007, sigma2: 0.016, mean tau: 0.9603: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8792 (best: 1899.8792, rho: 0.007, sigma2: 0.016, mean tau: 0.9603: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8782 (best: 1899.8782, rho: 0.007, sigma2: 0.016, mean tau: 0.9603: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8772 (best: 1899.8772, rho: 0.007, sigma2: 0.016, mean tau: 0.9602: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8763 (best: 1899.8763, rho: 0.007, sigma2: 0.016, mean tau: 0.9602: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8752 (best: 1899.8752, rho: 0.007, sigma2: 0.016, mean tau: 0.9602: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8745 (best: 1899.8745, rho: 0.007, sigma2: 0.016, mean tau: 0.9602: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8735 (best: 1899.8735, rho: 0.007, sigma2: 0.016, mean tau: 0.9602: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8727 (best: 1899.8727, rho: 0.007, sigma2: 0.016, mean tau: 0.9602: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8718 (best: 1899.8718, rho: 0.007, sigma2: 0.016, mean tau: 0.9601: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8707 (best: 1899.8707, rho: 0.007, sigma2: 0.016, mean tau: 0.9601: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8700 (best: 1899.8700, rho: 0.007, sigma2: 0.016, mean tau: 0.9601: 44%|████▍ | 438/1000 [00:01<00:02, 231.56it/s]
fit stat: 1899.8690 (best: 1899.8690, rho: 0.007, sigma2: 0.016, mean tau: 0.9601: 44%|████▍ | 438/1000 [00:02<00:02, 231.56it/s]
fit stat: 1899.8690 (best: 1899.8690, rho: 0.007, sigma2: 0.016, mean tau: 0.9601: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8683 (best: 1899.8683, rho: 0.007, sigma2: 0.016, mean tau: 0.9601: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8673 (best: 1899.8673, rho: 0.007, sigma2: 0.016, mean tau: 0.9601: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8665 (best: 1899.8665, rho: 0.007, sigma2: 0.016, mean tau: 0.9601: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8655 (best: 1899.8655, rho: 0.007, sigma2: 0.016, mean tau: 0.9600: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8645 (best: 1899.8645, rho: 0.007, sigma2: 0.016, mean tau: 0.9600: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8639 (best: 1899.8639, rho: 0.007, sigma2: 0.016, mean tau: 0.9600: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8629 (best: 1899.8629, rho: 0.007, sigma2: 0.016, mean tau: 0.9600: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8623 (best: 1899.8623, rho: 0.007, sigma2: 0.016, mean tau: 0.9600: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8612 (best: 1899.8612, rho: 0.007, sigma2: 0.016, mean tau: 0.9600: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8604 (best: 1899.8604, rho: 0.007, sigma2: 0.016, mean tau: 0.9600: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8595 (best: 1899.8595, rho: 0.007, sigma2: 0.016, mean tau: 0.9599: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8585 (best: 1899.8585, rho: 0.007, sigma2: 0.016, mean tau: 0.9599: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8579 (best: 1899.8579, rho: 0.007, sigma2: 0.016, mean tau: 0.9599: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8569 (best: 1899.8569, rho: 0.007, sigma2: 0.016, mean tau: 0.9599: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8561 (best: 1899.8561, rho: 0.007, sigma2: 0.016, mean tau: 0.9599: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8553 (best: 1899.8553, rho: 0.007, sigma2: 0.016, mean tau: 0.9599: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8544 (best: 1899.8544, rho: 0.007, sigma2: 0.016, mean tau: 0.9599: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8536 (best: 1899.8536, rho: 0.007, sigma2: 0.016, mean tau: 0.9598: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8529 (best: 1899.8529, rho: 0.007, sigma2: 0.017, mean tau: 0.9598: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8521 (best: 1899.8521, rho: 0.007, sigma2: 0.017, mean tau: 0.9598: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8512 (best: 1899.8512, rho: 0.007, sigma2: 0.017, mean tau: 0.9598: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8505 (best: 1899.8505, rho: 0.007, sigma2: 0.017, mean tau: 0.9598: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8496 (best: 1899.8496, rho: 0.007, sigma2: 0.017, mean tau: 0.9598: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8489 (best: 1899.8489, rho: 0.007, sigma2: 0.017, mean tau: 0.9598: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8479 (best: 1899.8479, rho: 0.007, sigma2: 0.017, mean tau: 0.9597: 46%|████▋ | 464/1000 [00:02<00:02, 238.56it/s]
fit stat: 1899.8479 (best: 1899.8479, rho: 0.007, sigma2: 0.017, mean tau: 0.9597: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8472 (best: 1899.8472, rho: 0.007, sigma2: 0.017, mean tau: 0.9597: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8466 (best: 1899.8466, rho: 0.007, sigma2: 0.017, mean tau: 0.9597: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8455 (best: 1899.8455, rho: 0.007, sigma2: 0.017, mean tau: 0.9597: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8447 (best: 1899.8447, rho: 0.007, sigma2: 0.017, mean tau: 0.9597: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8440 (best: 1899.8440, rho: 0.007, sigma2: 0.017, mean tau: 0.9597: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8431 (best: 1899.8431, rho: 0.007, sigma2: 0.017, mean tau: 0.9597: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8424 (best: 1899.8424, rho: 0.007, sigma2: 0.017, mean tau: 0.9597: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8417 (best: 1899.8417, rho: 0.007, sigma2: 0.017, mean tau: 0.9596: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8409 (best: 1899.8409, rho: 0.007, sigma2: 0.017, mean tau: 0.9596: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8401 (best: 1899.8401, rho: 0.007, sigma2: 0.017, mean tau: 0.9596: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8395 (best: 1899.8395, rho: 0.007, sigma2: 0.017, mean tau: 0.9596: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8387 (best: 1899.8387, rho: 0.007, sigma2: 0.017, mean tau: 0.9596: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8379 (best: 1899.8379, rho: 0.007, sigma2: 0.017, mean tau: 0.9596: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8372 (best: 1899.8372, rho: 0.007, sigma2: 0.017, mean tau: 0.9596: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8364 (best: 1899.8364, rho: 0.007, sigma2: 0.017, mean tau: 0.9595: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8357 (best: 1899.8357, rho: 0.007, sigma2: 0.017, mean tau: 0.9595: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8350 (best: 1899.8350, rho: 0.007, sigma2: 0.017, mean tau: 0.9595: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8341 (best: 1899.8341, rho: 0.007, sigma2: 0.017, mean tau: 0.9595: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8334 (best: 1899.8334, rho: 0.007, sigma2: 0.017, mean tau: 0.9595: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8328 (best: 1899.8328, rho: 0.007, sigma2: 0.017, mean tau: 0.9595: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8320 (best: 1899.8320, rho: 0.006, sigma2: 0.017, mean tau: 0.9595: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8313 (best: 1899.8313, rho: 0.006, sigma2: 0.017, mean tau: 0.9595: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8304 (best: 1899.8304, rho: 0.006, sigma2: 0.017, mean tau: 0.9594: 49%|████▉ | 489/1000 [00:02<00:02, 217.08it/s]
fit stat: 1899.8304 (best: 1899.8304, rho: 0.006, sigma2: 0.017, mean tau: 0.9594: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8298 (best: 1899.8298, rho: 0.006, sigma2: 0.017, mean tau: 0.9594: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8291 (best: 1899.8291, rho: 0.006, sigma2: 0.017, mean tau: 0.9594: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8284 (best: 1899.8284, rho: 0.006, sigma2: 0.017, mean tau: 0.9594: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8276 (best: 1899.8276, rho: 0.006, sigma2: 0.017, mean tau: 0.9594: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8270 (best: 1899.8270, rho: 0.006, sigma2: 0.017, mean tau: 0.9594: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8264 (best: 1899.8264, rho: 0.006, sigma2: 0.017, mean tau: 0.9594: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8256 (best: 1899.8256, rho: 0.006, sigma2: 0.017, mean tau: 0.9594: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8247 (best: 1899.8247, rho: 0.006, sigma2: 0.017, mean tau: 0.9593: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8242 (best: 1899.8242, rho: 0.006, sigma2: 0.017, mean tau: 0.9593: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8235 (best: 1899.8235, rho: 0.006, sigma2: 0.017, mean tau: 0.9593: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8228 (best: 1899.8228, rho: 0.006, sigma2: 0.017, mean tau: 0.9593: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8221 (best: 1899.8221, rho: 0.006, sigma2: 0.017, mean tau: 0.9593: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8214 (best: 1899.8214, rho: 0.006, sigma2: 0.017, mean tau: 0.9593: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8207 (best: 1899.8207, rho: 0.006, sigma2: 0.017, mean tau: 0.9593: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8201 (best: 1899.8201, rho: 0.006, sigma2: 0.017, mean tau: 0.9593: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8193 (best: 1899.8193, rho: 0.006, sigma2: 0.017, mean tau: 0.9592: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8186 (best: 1899.8186, rho: 0.006, sigma2: 0.017, mean tau: 0.9592: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8180 (best: 1899.8180, rho: 0.006, sigma2: 0.017, mean tau: 0.9592: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8174 (best: 1899.8174, rho: 0.006, sigma2: 0.017, mean tau: 0.9592: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8165 (best: 1899.8165, rho: 0.006, sigma2: 0.017, mean tau: 0.9592: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8160 (best: 1899.8160, rho: 0.006, sigma2: 0.017, mean tau: 0.9592: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8154 (best: 1899.8154, rho: 0.006, sigma2: 0.017, mean tau: 0.9592: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8146 (best: 1899.8146, rho: 0.006, sigma2: 0.017, mean tau: 0.9592: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8140 (best: 1899.8140, rho: 0.006, sigma2: 0.017, mean tau: 0.9592: 51%|█████ | 512/1000 [00:02<00:02, 212.24it/s]
fit stat: 1899.8140 (best: 1899.8140, rho: 0.006, sigma2: 0.017, mean tau: 0.9592: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.8134 (best: 1899.8134, rho: 0.006, sigma2: 0.017, mean tau: 0.9591: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.8127 (best: 1899.8127, rho: 0.006, sigma2: 0.017, mean tau: 0.9591: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.8120 (best: 1899.8120, rho: 0.006, sigma2: 0.017, mean tau: 0.9591: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.8113 (best: 1899.8113, rho: 0.006, sigma2: 0.017, mean tau: 0.9591: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.8109 (best: 1899.8109, rho: 0.006, sigma2: 0.017, mean tau: 0.9591: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.8101 (best: 1899.8101, rho: 0.006, sigma2: 0.017, mean tau: 0.9591: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.8096 (best: 1899.8096, rho: 0.006, sigma2: 0.017, mean tau: 0.9591: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.8088 (best: 1899.8088, rho: 0.006, sigma2: 0.017, mean tau: 0.9591: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.8081 (best: 1899.8081, rho: 0.006, sigma2: 0.017, mean tau: 0.9591: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.8076 (best: 1899.8076, rho: 0.006, sigma2: 0.017, mean tau: 0.9590: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.8070 (best: 1899.8070, rho: 0.006, sigma2: 0.017, mean tau: 0.9590: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.8064 (best: 1899.8064, rho: 0.006, sigma2: 0.017, mean tau: 0.9590: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.8058 (best: 1899.8058, rho: 0.006, sigma2: 0.017, mean tau: 0.9590: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.8051 (best: 1899.8051, rho: 0.006, sigma2: 0.017, mean tau: 0.9590: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.8046 (best: 1899.8046, rho: 0.006, sigma2: 0.017, mean tau: 0.9590: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.8040 (best: 1899.8040, rho: 0.006, sigma2: 0.017, mean tau: 0.9590: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.8032 (best: 1899.8032, rho: 0.006, sigma2: 0.017, mean tau: 0.9590: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.8026 (best: 1899.8026, rho: 0.006, sigma2: 0.017, mean tau: 0.9590: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.8020 (best: 1899.8020, rho: 0.006, sigma2: 0.017, mean tau: 0.9589: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.8014 (best: 1899.8014, rho: 0.006, sigma2: 0.017, mean tau: 0.9589: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.8008 (best: 1899.8008, rho: 0.006, sigma2: 0.017, mean tau: 0.9589: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.8002 (best: 1899.8002, rho: 0.006, sigma2: 0.017, mean tau: 0.9589: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.7996 (best: 1899.7996, rho: 0.006, sigma2: 0.017, mean tau: 0.9589: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.7991 (best: 1899.7991, rho: 0.006, sigma2: 0.017, mean tau: 0.9589: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.7985 (best: 1899.7985, rho: 0.006, sigma2: 0.017, mean tau: 0.9589: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.7977 (best: 1899.7977, rho: 0.006, sigma2: 0.017, mean tau: 0.9589: 54%|█████▎ | 536/1000 [00:02<00:02, 219.25it/s]
fit stat: 1899.7977 (best: 1899.7977, rho: 0.006, sigma2: 0.017, mean tau: 0.9589: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7971 (best: 1899.7971, rho: 0.006, sigma2: 0.017, mean tau: 0.9589: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7966 (best: 1899.7966, rho: 0.006, sigma2: 0.017, mean tau: 0.9588: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7960 (best: 1899.7960, rho: 0.006, sigma2: 0.017, mean tau: 0.9588: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7954 (best: 1899.7954, rho: 0.006, sigma2: 0.017, mean tau: 0.9588: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7949 (best: 1899.7949, rho: 0.006, sigma2: 0.017, mean tau: 0.9588: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7943 (best: 1899.7943, rho: 0.006, sigma2: 0.017, mean tau: 0.9588: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7937 (best: 1899.7937, rho: 0.006, sigma2: 0.017, mean tau: 0.9588: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7931 (best: 1899.7931, rho: 0.006, sigma2: 0.017, mean tau: 0.9588: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7927 (best: 1899.7927, rho: 0.006, sigma2: 0.017, mean tau: 0.9588: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7920 (best: 1899.7920, rho: 0.006, sigma2: 0.017, mean tau: 0.9588: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7915 (best: 1899.7915, rho: 0.006, sigma2: 0.017, mean tau: 0.9587: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7908 (best: 1899.7908, rho: 0.006, sigma2: 0.017, mean tau: 0.9587: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7904 (best: 1899.7904, rho: 0.006, sigma2: 0.017, mean tau: 0.9587: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7897 (best: 1899.7897, rho: 0.006, sigma2: 0.017, mean tau: 0.9587: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7891 (best: 1899.7891, rho: 0.006, sigma2: 0.017, mean tau: 0.9587: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7886 (best: 1899.7886, rho: 0.006, sigma2: 0.017, mean tau: 0.9587: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7881 (best: 1899.7881, rho: 0.006, sigma2: 0.017, mean tau: 0.9587: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7875 (best: 1899.7875, rho: 0.006, sigma2: 0.017, mean tau: 0.9587: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7869 (best: 1899.7869, rho: 0.006, sigma2: 0.017, mean tau: 0.9587: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7864 (best: 1899.7864, rho: 0.006, sigma2: 0.017, mean tau: 0.9587: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7859 (best: 1899.7859, rho: 0.006, sigma2: 0.017, mean tau: 0.9586: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7853 (best: 1899.7853, rho: 0.006, sigma2: 0.017, mean tau: 0.9586: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7848 (best: 1899.7848, rho: 0.006, sigma2: 0.017, mean tau: 0.9586: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7842 (best: 1899.7842, rho: 0.006, sigma2: 0.017, mean tau: 0.9586: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7837 (best: 1899.7837, rho: 0.006, sigma2: 0.017, mean tau: 0.9586: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7831 (best: 1899.7831, rho: 0.006, sigma2: 0.017, mean tau: 0.9586: 56%|█████▌ | 562/1000 [00:02<00:01, 230.24it/s]
fit stat: 1899.7831 (best: 1899.7831, rho: 0.006, sigma2: 0.017, mean tau: 0.9586: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7826 (best: 1899.7826, rho: 0.006, sigma2: 0.017, mean tau: 0.9586: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7821 (best: 1899.7821, rho: 0.006, sigma2: 0.017, mean tau: 0.9586: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7815 (best: 1899.7815, rho: 0.006, sigma2: 0.017, mean tau: 0.9586: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7812 (best: 1899.7812, rho: 0.006, sigma2: 0.017, mean tau: 0.9586: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7805 (best: 1899.7805, rho: 0.005, sigma2: 0.017, mean tau: 0.9585: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7800 (best: 1899.7800, rho: 0.005, sigma2: 0.017, mean tau: 0.9585: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7793 (best: 1899.7793, rho: 0.005, sigma2: 0.017, mean tau: 0.9585: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7791 (best: 1899.7791, rho: 0.005, sigma2: 0.017, mean tau: 0.9585: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7783 (best: 1899.7783, rho: 0.005, sigma2: 0.017, mean tau: 0.9585: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7780 (best: 1899.7780, rho: 0.005, sigma2: 0.017, mean tau: 0.9585: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7772 (best: 1899.7772, rho: 0.005, sigma2: 0.017, mean tau: 0.9585: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7767 (best: 1899.7767, rho: 0.005, sigma2: 0.017, mean tau: 0.9585: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7764 (best: 1899.7764, rho: 0.005, sigma2: 0.017, mean tau: 0.9585: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7758 (best: 1899.7758, rho: 0.005, sigma2: 0.017, mean tau: 0.9585: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7755 (best: 1899.7755, rho: 0.005, sigma2: 0.017, mean tau: 0.9585: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7748 (best: 1899.7748, rho: 0.005, sigma2: 0.017, mean tau: 0.9584: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7743 (best: 1899.7743, rho: 0.005, sigma2: 0.017, mean tau: 0.9584: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7737 (best: 1899.7737, rho: 0.005, sigma2: 0.017, mean tau: 0.9584: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7733 (best: 1899.7733, rho: 0.005, sigma2: 0.017, mean tau: 0.9584: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7728 (best: 1899.7728, rho: 0.005, sigma2: 0.017, mean tau: 0.9584: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7723 (best: 1899.7723, rho: 0.005, sigma2: 0.017, mean tau: 0.9584: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7717 (best: 1899.7717, rho: 0.005, sigma2: 0.017, mean tau: 0.9584: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7714 (best: 1899.7714, rho: 0.005, sigma2: 0.017, mean tau: 0.9584: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7709 (best: 1899.7709, rho: 0.005, sigma2: 0.017, mean tau: 0.9584: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7701 (best: 1899.7701, rho: 0.005, sigma2: 0.017, mean tau: 0.9584: 59%|█████▉ | 588/1000 [00:02<00:01, 237.86it/s]
fit stat: 1899.7701 (best: 1899.7701, rho: 0.005, sigma2: 0.017, mean tau: 0.9584: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7697 (best: 1899.7697, rho: 0.005, sigma2: 0.017, mean tau: 0.9584: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7693 (best: 1899.7693, rho: 0.005, sigma2: 0.017, mean tau: 0.9583: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7688 (best: 1899.7688, rho: 0.005, sigma2: 0.017, mean tau: 0.9583: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7683 (best: 1899.7683, rho: 0.005, sigma2: 0.017, mean tau: 0.9583: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7678 (best: 1899.7678, rho: 0.005, sigma2: 0.017, mean tau: 0.9583: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7675 (best: 1899.7675, rho: 0.005, sigma2: 0.017, mean tau: 0.9583: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7670 (best: 1899.7670, rho: 0.005, sigma2: 0.017, mean tau: 0.9583: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7662 (best: 1899.7662, rho: 0.005, sigma2: 0.017, mean tau: 0.9583: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7657 (best: 1899.7657, rho: 0.005, sigma2: 0.017, mean tau: 0.9583: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7654 (best: 1899.7654, rho: 0.005, sigma2: 0.017, mean tau: 0.9583: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7649 (best: 1899.7649, rho: 0.005, sigma2: 0.017, mean tau: 0.9583: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7644 (best: 1899.7644, rho: 0.005, sigma2: 0.017, mean tau: 0.9583: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7640 (best: 1899.7640, rho: 0.005, sigma2: 0.017, mean tau: 0.9582: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7635 (best: 1899.7635, rho: 0.005, sigma2: 0.017, mean tau: 0.9582: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7631 (best: 1899.7631, rho: 0.005, sigma2: 0.017, mean tau: 0.9582: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7626 (best: 1899.7626, rho: 0.005, sigma2: 0.017, mean tau: 0.9582: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7620 (best: 1899.7620, rho: 0.005, sigma2: 0.017, mean tau: 0.9582: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7617 (best: 1899.7617, rho: 0.005, sigma2: 0.017, mean tau: 0.9582: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7612 (best: 1899.7612, rho: 0.005, sigma2: 0.017, mean tau: 0.9582: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7609 (best: 1899.7609, rho: 0.005, sigma2: 0.017, mean tau: 0.9582: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7603 (best: 1899.7603, rho: 0.005, sigma2: 0.017, mean tau: 0.9582: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7599 (best: 1899.7599, rho: 0.005, sigma2: 0.017, mean tau: 0.9582: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7594 (best: 1899.7594, rho: 0.005, sigma2: 0.017, mean tau: 0.9582: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7588 (best: 1899.7588, rho: 0.005, sigma2: 0.017, mean tau: 0.9581: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7584 (best: 1899.7584, rho: 0.005, sigma2: 0.017, mean tau: 0.9581: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7581 (best: 1899.7581, rho: 0.005, sigma2: 0.017, mean tau: 0.9581: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7576 (best: 1899.7576, rho: 0.005, sigma2: 0.017, mean tau: 0.9581: 61%|██████▏ | 613/1000 [00:02<00:01, 239.06it/s]
fit stat: 1899.7576 (best: 1899.7576, rho: 0.005, sigma2: 0.017, mean tau: 0.9581: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7571 (best: 1899.7571, rho: 0.005, sigma2: 0.017, mean tau: 0.9581: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7567 (best: 1899.7567, rho: 0.005, sigma2: 0.017, mean tau: 0.9581: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7562 (best: 1899.7562, rho: 0.005, sigma2: 0.017, mean tau: 0.9581: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7559 (best: 1899.7559, rho: 0.005, sigma2: 0.017, mean tau: 0.9581: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7555 (best: 1899.7555, rho: 0.005, sigma2: 0.017, mean tau: 0.9581: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7550 (best: 1899.7550, rho: 0.005, sigma2: 0.017, mean tau: 0.9581: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7545 (best: 1899.7545, rho: 0.005, sigma2: 0.017, mean tau: 0.9581: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7542 (best: 1899.7542, rho: 0.005, sigma2: 0.017, mean tau: 0.9581: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7535 (best: 1899.7535, rho: 0.005, sigma2: 0.017, mean tau: 0.9580: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7532 (best: 1899.7532, rho: 0.005, sigma2: 0.017, mean tau: 0.9580: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7527 (best: 1899.7527, rho: 0.005, sigma2: 0.017, mean tau: 0.9580: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7523 (best: 1899.7523, rho: 0.005, sigma2: 0.017, mean tau: 0.9580: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7518 (best: 1899.7518, rho: 0.005, sigma2: 0.017, mean tau: 0.9580: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7516 (best: 1899.7516, rho: 0.005, sigma2: 0.017, mean tau: 0.9580: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7511 (best: 1899.7511, rho: 0.005, sigma2: 0.017, mean tau: 0.9580: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7507 (best: 1899.7507, rho: 0.005, sigma2: 0.017, mean tau: 0.9580: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7502 (best: 1899.7502, rho: 0.005, sigma2: 0.017, mean tau: 0.9580: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7498 (best: 1899.7498, rho: 0.005, sigma2: 0.017, mean tau: 0.9580: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7493 (best: 1899.7493, rho: 0.005, sigma2: 0.017, mean tau: 0.9580: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7488 (best: 1899.7488, rho: 0.005, sigma2: 0.017, mean tau: 0.9580: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7485 (best: 1899.7485, rho: 0.005, sigma2: 0.017, mean tau: 0.9580: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7480 (best: 1899.7480, rho: 0.005, sigma2: 0.017, mean tau: 0.9579: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7477 (best: 1899.7477, rho: 0.005, sigma2: 0.017, mean tau: 0.9579: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7472 (best: 1899.7472, rho: 0.005, sigma2: 0.017, mean tau: 0.9579: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7468 (best: 1899.7468, rho: 0.005, sigma2: 0.017, mean tau: 0.9579: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7466 (best: 1899.7466, rho: 0.005, sigma2: 0.017, mean tau: 0.9579: 64%|██████▍ | 640/1000 [00:02<00:01, 245.45it/s]
fit stat: 1899.7466 (best: 1899.7466, rho: 0.005, sigma2: 0.017, mean tau: 0.9579: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7458 (best: 1899.7458, rho: 0.005, sigma2: 0.017, mean tau: 0.9579: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7456 (best: 1899.7456, rho: 0.005, sigma2: 0.017, mean tau: 0.9579: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7451 (best: 1899.7451, rho: 0.005, sigma2: 0.017, mean tau: 0.9579: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7448 (best: 1899.7448, rho: 0.005, sigma2: 0.017, mean tau: 0.9579: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7444 (best: 1899.7444, rho: 0.005, sigma2: 0.017, mean tau: 0.9579: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7439 (best: 1899.7439, rho: 0.005, sigma2: 0.017, mean tau: 0.9579: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7435 (best: 1899.7435, rho: 0.005, sigma2: 0.017, mean tau: 0.9579: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7432 (best: 1899.7432, rho: 0.005, sigma2: 0.017, mean tau: 0.9578: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7427 (best: 1899.7427, rho: 0.005, sigma2: 0.017, mean tau: 0.9578: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7423 (best: 1899.7423, rho: 0.005, sigma2: 0.017, mean tau: 0.9578: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7419 (best: 1899.7419, rho: 0.005, sigma2: 0.017, mean tau: 0.9578: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7416 (best: 1899.7416, rho: 0.005, sigma2: 0.017, mean tau: 0.9578: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7411 (best: 1899.7411, rho: 0.005, sigma2: 0.017, mean tau: 0.9578: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7408 (best: 1899.7408, rho: 0.005, sigma2: 0.017, mean tau: 0.9578: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7404 (best: 1899.7404, rho: 0.005, sigma2: 0.017, mean tau: 0.9578: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7399 (best: 1899.7399, rho: 0.005, sigma2: 0.018, mean tau: 0.9578: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7395 (best: 1899.7395, rho: 0.005, sigma2: 0.018, mean tau: 0.9578: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7394 (best: 1899.7394, rho: 0.005, sigma2: 0.018, mean tau: 0.9578: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7388 (best: 1899.7388, rho: 0.005, sigma2: 0.018, mean tau: 0.9578: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7385 (best: 1899.7385, rho: 0.005, sigma2: 0.018, mean tau: 0.9578: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7380 (best: 1899.7380, rho: 0.005, sigma2: 0.018, mean tau: 0.9578: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7378 (best: 1899.7378, rho: 0.005, sigma2: 0.018, mean tau: 0.9577: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7374 (best: 1899.7374, rho: 0.005, sigma2: 0.018, mean tau: 0.9577: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7368 (best: 1899.7368, rho: 0.005, sigma2: 0.018, mean tau: 0.9577: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7366 (best: 1899.7366, rho: 0.005, sigma2: 0.018, mean tau: 0.9577: 67%|██████▋ | 666/1000 [00:02<00:01, 248.51it/s]
fit stat: 1899.7366 (best: 1899.7366, rho: 0.005, sigma2: 0.018, mean tau: 0.9577: 69%|██████▉ | 691/1000 [00:02<00:01, 242.92it/s]
fit stat: 1899.7360 (best: 1899.7360, rho: 0.005, sigma2: 0.018, mean tau: 0.9577: 69%|██████▉ | 691/1000 [00:02<00:01, 242.92it/s]
fit stat: 1899.7358 (best: 1899.7358, rho: 0.005, sigma2: 0.018, mean tau: 0.9577: 69%|██████▉ | 691/1000 [00:02<00:01, 242.92it/s]
fit stat: 1899.7354 (best: 1899.7354, rho: 0.005, sigma2: 0.018, mean tau: 0.9577: 69%|██████▉ | 691/1000 [00:02<00:01, 242.92it/s]
fit stat: 1899.7349 (best: 1899.7349, rho: 0.005, sigma2: 0.018, mean tau: 0.9577: 69%|██████▉ | 691/1000 [00:02<00:01, 242.92it/s]
fit stat: 1899.7346 (best: 1899.7346, rho: 0.005, sigma2: 0.018, mean tau: 0.9577: 69%|██████▉ | 691/1000 [00:02<00:01, 242.92it/s]
fit stat: 1899.7341 (best: 1899.7341, rho: 0.005, sigma2: 0.018, mean tau: 0.9577: 69%|██████▉ | 691/1000 [00:02<00:01, 242.92it/s]
fit stat: 1899.7339 (best: 1899.7339, rho: 0.005, sigma2: 0.018, mean tau: 0.9577: 69%|██████▉ | 691/1000 [00:03<00:01, 242.92it/s]
fit stat: 1899.7335 (best: 1899.7335, rho: 0.005, sigma2: 0.018, mean tau: 0.9577: 69%|██████▉ | 691/1000 [00:03<00:01, 242.92it/s]
fit stat: 1899.7332 (best: 1899.7332, rho: 0.005, sigma2: 0.018, mean tau: 0.9577: 69%|██████▉ | 691/1000 [00:03<00:01, 242.92it/s]
fit stat: 1899.7327 (best: 1899.7327, rho: 0.005, sigma2: 0.018, mean tau: 0.9576: 69%|██████▉ | 691/1000 [00:03<00:01, 242.92it/s]
fit stat: 1899.7324 (best: 1899.7324, rho: 0.005, sigma2: 0.018, mean tau: 0.9576: 69%|██████▉ | 691/1000 [00:03<00:01, 242.92it/s]
fit stat: 1899.7321 (best: 1899.7321, rho: 0.005, sigma2: 0.018, mean tau: 0.9576: 69%|██████▉ | 691/1000 [00:03<00:01, 242.92it/s]
fit stat: 1899.7317 (best: 1899.7317, rho: 0.005, sigma2: 0.018, mean tau: 0.9576: 69%|██████▉ | 691/1000 [00:03<00:01, 242.92it/s]
fit stat: 1899.7312 (best: 1899.7312, rho: 0.005, sigma2: 0.018, mean tau: 0.9576: 69%|██████▉ | 691/1000 [00:03<00:01, 242.92it/s]
fit stat: 1899.7310 (best: 1899.7310, rho: 0.004, sigma2: 0.018, mean tau: 0.9576: 69%|██████▉ | 691/1000 [00:03<00:01, 242.92it/s]
fit stat: 1899.7305 (best: 1899.7305, rho: 0.004, sigma2: 0.018, mean tau: 0.9576: 69%|██████▉ | 691/1000 [00:03<00:01, 242.92it/s]
fit stat: 1899.7302 (best: 1899.7302, rho: 0.004, sigma2: 0.018, mean tau: 0.9576: 69%|██████▉ | 691/1000 [00:03<00:01, 242.92it/s]
fit stat: 1899.7300 (best: 1899.7300, rho: 0.004, sigma2: 0.018, mean tau: 0.9576: 69%|██████▉ | 691/1000 [00:03<00:01, 242.92it/s]
fit stat: 1899.7294 (best: 1899.7294, rho: 0.004, sigma2: 0.018, mean tau: 0.9576: 69%|██████▉ | 691/1000 [00:03<00:01, 242.92it/s]
fit stat: 1899.7291 (best: 1899.7291, rho: 0.004, sigma2: 0.018, mean tau: 0.9576: 69%|██████▉ | 691/1000 [00:03<00:01, 242.92it/s]
fit stat: 1899.7288 (best: 1899.7288, rho: 0.004, sigma2: 0.018, mean tau: 0.9576: 69%|██████▉ | 691/1000 [00:03<00:01, 242.92it/s]
fit stat: 1899.7285 (best: 1899.7285, rho: 0.004, sigma2: 0.018, mean tau: 0.9576: 69%|██████▉ | 691/1000 [00:03<00:01, 242.92it/s]
fit stat: 1899.7280 (best: 1899.7280, rho: 0.004, sigma2: 0.018, mean tau: 0.9576: 69%|██████▉ | 691/1000 [00:03<00:01, 242.92it/s]
fit stat: 1899.7278 (best: 1899.7278, rho: 0.004, sigma2: 0.018, mean tau: 0.9576: 69%|██████▉ | 691/1000 [00:03<00:01, 242.92it/s]
fit stat: 1899.7273 (best: 1899.7273, rho: 0.004, sigma2: 0.018, mean tau: 0.9575: 69%|██████▉ | 691/1000 [00:03<00:01, 242.92it/s]
fit stat: 1899.7268 (best: 1899.7268, rho: 0.004, sigma2: 0.018, mean tau: 0.9575: 69%|██████▉ | 691/1000 [00:03<00:01, 242.92it/s]
fit stat: 1899.7268 (best: 1899.7268, rho: 0.004, sigma2: 0.018, mean tau: 0.9575: 69%|██████▉ | 691/1000 [00:03<00:01, 242.92it/s]
fit stat: 1899.7263 (best: 1899.7263, rho: 0.004, sigma2: 0.018, mean tau: 0.9575: 69%|██████▉ | 691/1000 [00:03<00:01, 242.92it/s]
fit stat: 1899.7263 (best: 1899.7263, rho: 0.004, sigma2: 0.018, mean tau: 0.9575: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7260 (best: 1899.7260, rho: 0.004, sigma2: 0.018, mean tau: 0.9575: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7255 (best: 1899.7255, rho: 0.004, sigma2: 0.018, mean tau: 0.9575: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7252 (best: 1899.7252, rho: 0.004, sigma2: 0.018, mean tau: 0.9575: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7250 (best: 1899.7250, rho: 0.004, sigma2: 0.018, mean tau: 0.9575: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7246 (best: 1899.7246, rho: 0.004, sigma2: 0.018, mean tau: 0.9575: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7244 (best: 1899.7244, rho: 0.004, sigma2: 0.018, mean tau: 0.9575: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7239 (best: 1899.7239, rho: 0.004, sigma2: 0.018, mean tau: 0.9575: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7234 (best: 1899.7234, rho: 0.004, sigma2: 0.018, mean tau: 0.9575: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7233 (best: 1899.7233, rho: 0.004, sigma2: 0.018, mean tau: 0.9575: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7230 (best: 1899.7230, rho: 0.004, sigma2: 0.018, mean tau: 0.9575: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7225 (best: 1899.7225, rho: 0.004, sigma2: 0.018, mean tau: 0.9574: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7222 (best: 1899.7222, rho: 0.004, sigma2: 0.018, mean tau: 0.9574: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7218 (best: 1899.7218, rho: 0.004, sigma2: 0.018, mean tau: 0.9574: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7217 (best: 1899.7217, rho: 0.004, sigma2: 0.018, mean tau: 0.9574: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7212 (best: 1899.7212, rho: 0.004, sigma2: 0.018, mean tau: 0.9574: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7208 (best: 1899.7208, rho: 0.004, sigma2: 0.018, mean tau: 0.9574: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7206 (best: 1899.7206, rho: 0.004, sigma2: 0.018, mean tau: 0.9574: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7201 (best: 1899.7201, rho: 0.004, sigma2: 0.018, mean tau: 0.9574: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7198 (best: 1899.7198, rho: 0.004, sigma2: 0.018, mean tau: 0.9574: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7196 (best: 1899.7196, rho: 0.004, sigma2: 0.018, mean tau: 0.9574: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7191 (best: 1899.7191, rho: 0.004, sigma2: 0.018, mean tau: 0.9574: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7189 (best: 1899.7189, rho: 0.004, sigma2: 0.018, mean tau: 0.9574: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7184 (best: 1899.7184, rho: 0.004, sigma2: 0.018, mean tau: 0.9574: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7181 (best: 1899.7181, rho: 0.004, sigma2: 0.018, mean tau: 0.9574: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7179 (best: 1899.7179, rho: 0.004, sigma2: 0.018, mean tau: 0.9574: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7175 (best: 1899.7175, rho: 0.004, sigma2: 0.018, mean tau: 0.9574: 72%|███████▏ | 719/1000 [00:03<00:01, 251.50it/s]
fit stat: 1899.7175 (best: 1899.7175, rho: 0.004, sigma2: 0.018, mean tau: 0.9574: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7173 (best: 1899.7173, rho: 0.004, sigma2: 0.018, mean tau: 0.9573: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7170 (best: 1899.7170, rho: 0.004, sigma2: 0.018, mean tau: 0.9573: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7166 (best: 1899.7166, rho: 0.004, sigma2: 0.018, mean tau: 0.9573: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7161 (best: 1899.7161, rho: 0.004, sigma2: 0.018, mean tau: 0.9573: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7159 (best: 1899.7159, rho: 0.004, sigma2: 0.018, mean tau: 0.9573: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7155 (best: 1899.7155, rho: 0.004, sigma2: 0.018, mean tau: 0.9573: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7153 (best: 1899.7153, rho: 0.004, sigma2: 0.018, mean tau: 0.9573: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7148 (best: 1899.7148, rho: 0.004, sigma2: 0.018, mean tau: 0.9573: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7145 (best: 1899.7145, rho: 0.004, sigma2: 0.018, mean tau: 0.9573: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7145 (best: 1899.7145, rho: 0.004, sigma2: 0.018, mean tau: 0.9573: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7141 (best: 1899.7141, rho: 0.004, sigma2: 0.018, mean tau: 0.9573: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7136 (best: 1899.7136, rho: 0.004, sigma2: 0.018, mean tau: 0.9573: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7134 (best: 1899.7134, rho: 0.004, sigma2: 0.018, mean tau: 0.9573: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7129 (best: 1899.7129, rho: 0.004, sigma2: 0.018, mean tau: 0.9573: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7128 (best: 1899.7128, rho: 0.004, sigma2: 0.018, mean tau: 0.9573: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7126 (best: 1899.7126, rho: 0.004, sigma2: 0.018, mean tau: 0.9573: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7123 (best: 1899.7123, rho: 0.004, sigma2: 0.018, mean tau: 0.9572: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7120 (best: 1899.7120, rho: 0.004, sigma2: 0.018, mean tau: 0.9572: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7115 (best: 1899.7115, rho: 0.004, sigma2: 0.018, mean tau: 0.9572: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7113 (best: 1899.7113, rho: 0.004, sigma2: 0.018, mean tau: 0.9572: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7108 (best: 1899.7108, rho: 0.004, sigma2: 0.018, mean tau: 0.9572: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7106 (best: 1899.7106, rho: 0.004, sigma2: 0.018, mean tau: 0.9572: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7104 (best: 1899.7104, rho: 0.004, sigma2: 0.018, mean tau: 0.9572: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7100 (best: 1899.7100, rho: 0.004, sigma2: 0.018, mean tau: 0.9572: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7097 (best: 1899.7097, rho: 0.004, sigma2: 0.018, mean tau: 0.9572: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7094 (best: 1899.7094, rho: 0.004, sigma2: 0.018, mean tau: 0.9572: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7092 (best: 1899.7092, rho: 0.004, sigma2: 0.018, mean tau: 0.9572: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7089 (best: 1899.7089, rho: 0.004, sigma2: 0.018, mean tau: 0.9572: 74%|███████▍ | 745/1000 [00:03<00:01, 253.80it/s]
fit stat: 1899.7089 (best: 1899.7089, rho: 0.004, sigma2: 0.018, mean tau: 0.9572: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7085 (best: 1899.7085, rho: 0.004, sigma2: 0.018, mean tau: 0.9572: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7083 (best: 1899.7083, rho: 0.004, sigma2: 0.018, mean tau: 0.9572: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7080 (best: 1899.7080, rho: 0.004, sigma2: 0.018, mean tau: 0.9572: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7075 (best: 1899.7075, rho: 0.004, sigma2: 0.018, mean tau: 0.9572: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7074 (best: 1899.7074, rho: 0.004, sigma2: 0.018, mean tau: 0.9571: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7073 (best: 1899.7073, rho: 0.004, sigma2: 0.018, mean tau: 0.9571: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7068 (best: 1899.7068, rho: 0.004, sigma2: 0.018, mean tau: 0.9571: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7064 (best: 1899.7064, rho: 0.004, sigma2: 0.018, mean tau: 0.9571: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7061 (best: 1899.7061, rho: 0.004, sigma2: 0.018, mean tau: 0.9571: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7058 (best: 1899.7058, rho: 0.004, sigma2: 0.018, mean tau: 0.9571: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7056 (best: 1899.7056, rho: 0.004, sigma2: 0.018, mean tau: 0.9571: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7052 (best: 1899.7052, rho: 0.004, sigma2: 0.018, mean tau: 0.9571: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7050 (best: 1899.7050, rho: 0.004, sigma2: 0.018, mean tau: 0.9571: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7046 (best: 1899.7046, rho: 0.004, sigma2: 0.018, mean tau: 0.9571: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7043 (best: 1899.7043, rho: 0.004, sigma2: 0.018, mean tau: 0.9571: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7040 (best: 1899.7040, rho: 0.004, sigma2: 0.018, mean tau: 0.9571: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7039 (best: 1899.7039, rho: 0.004, sigma2: 0.018, mean tau: 0.9571: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7036 (best: 1899.7036, rho: 0.004, sigma2: 0.018, mean tau: 0.9571: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7034 (best: 1899.7034, rho: 0.004, sigma2: 0.018, mean tau: 0.9571: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7031 (best: 1899.7031, rho: 0.004, sigma2: 0.018, mean tau: 0.9571: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7026 (best: 1899.7026, rho: 0.004, sigma2: 0.018, mean tau: 0.9571: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7024 (best: 1899.7024, rho: 0.004, sigma2: 0.018, mean tau: 0.9571: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7023 (best: 1899.7023, rho: 0.004, sigma2: 0.018, mean tau: 0.9570: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7020 (best: 1899.7020, rho: 0.004, sigma2: 0.018, mean tau: 0.9570: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7015 (best: 1899.7015, rho: 0.004, sigma2: 0.018, mean tau: 0.9570: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7014 (best: 1899.7014, rho: 0.004, sigma2: 0.018, mean tau: 0.9570: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7010 (best: 1899.7010, rho: 0.004, sigma2: 0.018, mean tau: 0.9570: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7008 (best: 1899.7008, rho: 0.004, sigma2: 0.018, mean tau: 0.9570: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7003 (best: 1899.7003, rho: 0.004, sigma2: 0.018, mean tau: 0.9570: 77%|███████▋ | 773/1000 [00:03<00:00, 261.37it/s]
fit stat: 1899.7003 (best: 1899.7003, rho: 0.004, sigma2: 0.018, mean tau: 0.9570: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.7002 (best: 1899.7002, rho: 0.004, sigma2: 0.018, mean tau: 0.9570: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.7000 (best: 1899.7000, rho: 0.004, sigma2: 0.018, mean tau: 0.9570: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6997 (best: 1899.6997, rho: 0.004, sigma2: 0.018, mean tau: 0.9570: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6995 (best: 1899.6995, rho: 0.004, sigma2: 0.018, mean tau: 0.9570: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6992 (best: 1899.6992, rho: 0.004, sigma2: 0.018, mean tau: 0.9570: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6987 (best: 1899.6987, rho: 0.004, sigma2: 0.018, mean tau: 0.9570: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6986 (best: 1899.6986, rho: 0.004, sigma2: 0.018, mean tau: 0.9570: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6982 (best: 1899.6982, rho: 0.004, sigma2: 0.018, mean tau: 0.9570: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6981 (best: 1899.6981, rho: 0.004, sigma2: 0.018, mean tau: 0.9570: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6978 (best: 1899.6978, rho: 0.004, sigma2: 0.018, mean tau: 0.9570: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6974 (best: 1899.6974, rho: 0.004, sigma2: 0.018, mean tau: 0.9570: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6971 (best: 1899.6971, rho: 0.004, sigma2: 0.018, mean tau: 0.9569: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6969 (best: 1899.6969, rho: 0.004, sigma2: 0.018, mean tau: 0.9569: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6967 (best: 1899.6967, rho: 0.004, sigma2: 0.018, mean tau: 0.9569: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6964 (best: 1899.6964, rho: 0.004, sigma2: 0.018, mean tau: 0.9569: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6962 (best: 1899.6962, rho: 0.004, sigma2: 0.018, mean tau: 0.9569: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6957 (best: 1899.6957, rho: 0.004, sigma2: 0.018, mean tau: 0.9569: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6956 (best: 1899.6956, rho: 0.004, sigma2: 0.018, mean tau: 0.9569: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6953 (best: 1899.6953, rho: 0.004, sigma2: 0.018, mean tau: 0.9569: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6951 (best: 1899.6951, rho: 0.004, sigma2: 0.018, mean tau: 0.9569: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6949 (best: 1899.6949, rho: 0.004, sigma2: 0.018, mean tau: 0.9569: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6947 (best: 1899.6947, rho: 0.004, sigma2: 0.018, mean tau: 0.9569: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6943 (best: 1899.6943, rho: 0.004, sigma2: 0.018, mean tau: 0.9569: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6940 (best: 1899.6940, rho: 0.004, sigma2: 0.018, mean tau: 0.9569: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6937 (best: 1899.6937, rho: 0.004, sigma2: 0.018, mean tau: 0.9569: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6935 (best: 1899.6935, rho: 0.004, sigma2: 0.018, mean tau: 0.9569: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6934 (best: 1899.6934, rho: 0.004, sigma2: 0.018, mean tau: 0.9569: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6931 (best: 1899.6931, rho: 0.004, sigma2: 0.018, mean tau: 0.9569: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6929 (best: 1899.6929, rho: 0.004, sigma2: 0.018, mean tau: 0.9569: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6925 (best: 1899.6925, rho: 0.004, sigma2: 0.018, mean tau: 0.9569: 80%|████████ | 802/1000 [00:03<00:00, 267.80it/s]
fit stat: 1899.6925 (best: 1899.6925, rho: 0.004, sigma2: 0.018, mean tau: 0.9569: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6921 (best: 1899.6921, rho: 0.004, sigma2: 0.018, mean tau: 0.9568: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6919 (best: 1899.6919, rho: 0.004, sigma2: 0.018, mean tau: 0.9568: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6917 (best: 1899.6917, rho: 0.004, sigma2: 0.018, mean tau: 0.9568: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6915 (best: 1899.6915, rho: 0.004, sigma2: 0.018, mean tau: 0.9568: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6913 (best: 1899.6913, rho: 0.004, sigma2: 0.018, mean tau: 0.9568: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6910 (best: 1899.6910, rho: 0.004, sigma2: 0.018, mean tau: 0.9568: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6907 (best: 1899.6907, rho: 0.004, sigma2: 0.018, mean tau: 0.9568: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6906 (best: 1899.6906, rho: 0.004, sigma2: 0.018, mean tau: 0.9568: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6902 (best: 1899.6902, rho: 0.004, sigma2: 0.018, mean tau: 0.9568: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6901 (best: 1899.6901, rho: 0.004, sigma2: 0.018, mean tau: 0.9568: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6898 (best: 1899.6898, rho: 0.004, sigma2: 0.018, mean tau: 0.9568: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6897 (best: 1899.6897, rho: 0.004, sigma2: 0.018, mean tau: 0.9568: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6893 (best: 1899.6893, rho: 0.004, sigma2: 0.018, mean tau: 0.9568: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6890 (best: 1899.6890, rho: 0.004, sigma2: 0.018, mean tau: 0.9568: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6887 (best: 1899.6887, rho: 0.004, sigma2: 0.018, mean tau: 0.9568: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6884 (best: 1899.6884, rho: 0.004, sigma2: 0.018, mean tau: 0.9568: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6884 (best: 1899.6884, rho: 0.004, sigma2: 0.018, mean tau: 0.9568: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6881 (best: 1899.6881, rho: 0.004, sigma2: 0.018, mean tau: 0.9568: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6877 (best: 1899.6877, rho: 0.004, sigma2: 0.018, mean tau: 0.9568: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6876 (best: 1899.6876, rho: 0.004, sigma2: 0.018, mean tau: 0.9567: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6874 (best: 1899.6874, rho: 0.004, sigma2: 0.018, mean tau: 0.9567: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6870 (best: 1899.6870, rho: 0.004, sigma2: 0.018, mean tau: 0.9567: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6868 (best: 1899.6868, rho: 0.004, sigma2: 0.018, mean tau: 0.9567: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6865 (best: 1899.6865, rho: 0.004, sigma2: 0.018, mean tau: 0.9567: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6865 (best: 1899.6865, rho: 0.004, sigma2: 0.018, mean tau: 0.9567: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6862 (best: 1899.6862, rho: 0.004, sigma2: 0.018, mean tau: 0.9567: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6858 (best: 1899.6858, rho: 0.004, sigma2: 0.018, mean tau: 0.9567: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6857 (best: 1899.6857, rho: 0.004, sigma2: 0.018, mean tau: 0.9567: 83%|████████▎ | 832/1000 [00:03<00:00, 276.40it/s]
fit stat: 1899.6857 (best: 1899.6857, rho: 0.004, sigma2: 0.018, mean tau: 0.9567: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6853 (best: 1899.6853, rho: 0.004, sigma2: 0.018, mean tau: 0.9567: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6851 (best: 1899.6851, rho: 0.004, sigma2: 0.018, mean tau: 0.9567: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6848 (best: 1899.6848, rho: 0.004, sigma2: 0.018, mean tau: 0.9567: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6847 (best: 1899.6847, rho: 0.004, sigma2: 0.018, mean tau: 0.9567: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6844 (best: 1899.6844, rho: 0.004, sigma2: 0.018, mean tau: 0.9567: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6841 (best: 1899.6841, rho: 0.004, sigma2: 0.018, mean tau: 0.9567: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6840 (best: 1899.6840, rho: 0.004, sigma2: 0.018, mean tau: 0.9567: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6837 (best: 1899.6837, rho: 0.003, sigma2: 0.018, mean tau: 0.9567: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6835 (best: 1899.6835, rho: 0.003, sigma2: 0.018, mean tau: 0.9567: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6831 (best: 1899.6831, rho: 0.003, sigma2: 0.018, mean tau: 0.9567: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6831 (best: 1899.6831, rho: 0.003, sigma2: 0.018, mean tau: 0.9567: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6829 (best: 1899.6829, rho: 0.003, sigma2: 0.018, mean tau: 0.9567: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6826 (best: 1899.6826, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6824 (best: 1899.6824, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6823 (best: 1899.6823, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6819 (best: 1899.6819, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6816 (best: 1899.6816, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6815 (best: 1899.6815, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6813 (best: 1899.6813, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6810 (best: 1899.6810, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6808 (best: 1899.6808, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6805 (best: 1899.6805, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6803 (best: 1899.6803, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6801 (best: 1899.6801, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6798 (best: 1899.6798, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6797 (best: 1899.6797, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6794 (best: 1899.6794, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 86%|████████▌ | 860/1000 [00:03<00:00, 265.47it/s]
fit stat: 1899.6794 (best: 1899.6794, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6792 (best: 1899.6792, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6792 (best: 1899.6792, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6787 (best: 1899.6787, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6785 (best: 1899.6785, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6783 (best: 1899.6783, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6781 (best: 1899.6781, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6779 (best: 1899.6779, rho: 0.003, sigma2: 0.018, mean tau: 0.9566: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6776 (best: 1899.6776, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6774 (best: 1899.6774, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6772 (best: 1899.6772, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6770 (best: 1899.6770, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6768 (best: 1899.6768, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6766 (best: 1899.6766, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6764 (best: 1899.6764, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6763 (best: 1899.6763, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6760 (best: 1899.6760, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6757 (best: 1899.6757, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6754 (best: 1899.6754, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6753 (best: 1899.6753, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6750 (best: 1899.6750, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6748 (best: 1899.6748, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6747 (best: 1899.6747, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6744 (best: 1899.6744, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6742 (best: 1899.6742, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6740 (best: 1899.6740, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 89%|████████▊ | 887/1000 [00:03<00:00, 242.95it/s]
fit stat: 1899.6740 (best: 1899.6740, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6737 (best: 1899.6737, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6736 (best: 1899.6736, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6733 (best: 1899.6733, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6732 (best: 1899.6732, rho: 0.003, sigma2: 0.018, mean tau: 0.9565: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6730 (best: 1899.6730, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6729 (best: 1899.6729, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6726 (best: 1899.6726, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6724 (best: 1899.6724, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6722 (best: 1899.6722, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6720 (best: 1899.6720, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6716 (best: 1899.6716, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6715 (best: 1899.6715, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6715 (best: 1899.6715, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6713 (best: 1899.6713, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6709 (best: 1899.6709, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6708 (best: 1899.6708, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6705 (best: 1899.6705, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6703 (best: 1899.6703, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6700 (best: 1899.6700, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6700 (best: 1899.6700, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6697 (best: 1899.6697, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6696 (best: 1899.6696, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6693 (best: 1899.6693, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6691 (best: 1899.6691, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 91%|█████████ | 912/1000 [00:03<00:00, 230.52it/s]
fit stat: 1899.6691 (best: 1899.6691, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 94%|█████████▎| 936/1000 [00:03<00:00, 227.37it/s]
fit stat: 1899.6689 (best: 1899.6689, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 94%|█████████▎| 936/1000 [00:03<00:00, 227.37it/s]
fit stat: 1899.6688 (best: 1899.6688, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 94%|█████████▎| 936/1000 [00:03<00:00, 227.37it/s]
fit stat: 1899.6685 (best: 1899.6685, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 94%|█████████▎| 936/1000 [00:03<00:00, 227.37it/s]
fit stat: 1899.6683 (best: 1899.6683, rho: 0.003, sigma2: 0.018, mean tau: 0.9564: 94%|█████████▎| 936/1000 [00:03<00:00, 227.37it/s]
fit stat: 1899.6681 (best: 1899.6681, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 94%|█████████▎| 936/1000 [00:03<00:00, 227.37it/s]
fit stat: 1899.6678 (best: 1899.6678, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 94%|█████████▎| 936/1000 [00:03<00:00, 227.37it/s]
fit stat: 1899.6678 (best: 1899.6678, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 94%|█████████▎| 936/1000 [00:03<00:00, 227.37it/s]
fit stat: 1899.6675 (best: 1899.6675, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 94%|█████████▎| 936/1000 [00:04<00:00, 227.37it/s]
fit stat: 1899.6674 (best: 1899.6674, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 94%|█████████▎| 936/1000 [00:04<00:00, 227.37it/s]
fit stat: 1899.6671 (best: 1899.6671, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 94%|█████████▎| 936/1000 [00:04<00:00, 227.37it/s]
fit stat: 1899.6669 (best: 1899.6669, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 94%|█████████▎| 936/1000 [00:04<00:00, 227.37it/s]
fit stat: 1899.6669 (best: 1899.6669, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 94%|█████████▎| 936/1000 [00:04<00:00, 227.37it/s]
fit stat: 1899.6666 (best: 1899.6666, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 94%|█████████▎| 936/1000 [00:04<00:00, 227.37it/s]
fit stat: 1899.6666 (best: 1899.6666, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 94%|█████████▎| 936/1000 [00:04<00:00, 227.37it/s]
fit stat: 1899.6664 (best: 1899.6664, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 94%|█████████▎| 936/1000 [00:04<00:00, 227.37it/s]
fit stat: 1899.6660 (best: 1899.6660, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 94%|█████████▎| 936/1000 [00:04<00:00, 227.37it/s]
fit stat: 1899.6658 (best: 1899.6658, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 94%|█████████▎| 936/1000 [00:04<00:00, 227.37it/s]
fit stat: 1899.6656 (best: 1899.6656, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 94%|█████████▎| 936/1000 [00:04<00:00, 227.37it/s]
fit stat: 1899.6655 (best: 1899.6655, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 94%|█████████▎| 936/1000 [00:04<00:00, 227.37it/s]
fit stat: 1899.6653 (best: 1899.6653, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 94%|█████████▎| 936/1000 [00:04<00:00, 227.37it/s]
fit stat: 1899.6650 (best: 1899.6650, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 94%|█████████▎| 936/1000 [00:04<00:00, 227.37it/s]
fit stat: 1899.6648 (best: 1899.6648, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 94%|█████████▎| 936/1000 [00:04<00:00, 227.37it/s]
fit stat: 1899.6647 (best: 1899.6647, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 94%|█████████▎| 936/1000 [00:04<00:00, 227.37it/s]
fit stat: 1899.6647 (best: 1899.6647, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6646 (best: 1899.6646, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6643 (best: 1899.6643, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6642 (best: 1899.6642, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6639 (best: 1899.6639, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6637 (best: 1899.6637, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6635 (best: 1899.6635, rho: 0.003, sigma2: 0.018, mean tau: 0.9563: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6632 (best: 1899.6632, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6631 (best: 1899.6631, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6631 (best: 1899.6631, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6628 (best: 1899.6628, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6627 (best: 1899.6627, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6626 (best: 1899.6626, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6624 (best: 1899.6624, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6621 (best: 1899.6621, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6619 (best: 1899.6619, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6617 (best: 1899.6617, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6614 (best: 1899.6614, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6613 (best: 1899.6613, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6613 (best: 1899.6613, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6610 (best: 1899.6610, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6608 (best: 1899.6608, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6608 (best: 1899.6608, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6605 (best: 1899.6605, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6604 (best: 1899.6604, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 96%|█████████▌| 959/1000 [00:04<00:00, 226.64it/s]
fit stat: 1899.6604 (best: 1899.6604, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 98%|█████████▊| 983/1000 [00:04<00:00, 228.75it/s]
fit stat: 1899.6602 (best: 1899.6602, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 98%|█████████▊| 983/1000 [00:04<00:00, 228.75it/s]
fit stat: 1899.6600 (best: 1899.6600, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 98%|█████████▊| 983/1000 [00:04<00:00, 228.75it/s]
fit stat: 1899.6597 (best: 1899.6597, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 98%|█████████▊| 983/1000 [00:04<00:00, 228.75it/s]
fit stat: 1899.6597 (best: 1899.6597, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 98%|█████████▊| 983/1000 [00:04<00:00, 228.75it/s]
fit stat: 1899.6595 (best: 1899.6595, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 98%|█████████▊| 983/1000 [00:04<00:00, 228.75it/s]
fit stat: 1899.6593 (best: 1899.6593, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 98%|█████████▊| 983/1000 [00:04<00:00, 228.75it/s]
fit stat: 1899.6591 (best: 1899.6591, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 98%|█████████▊| 983/1000 [00:04<00:00, 228.75it/s]
fit stat: 1899.6589 (best: 1899.6589, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 98%|█████████▊| 983/1000 [00:04<00:00, 228.75it/s]
fit stat: 1899.6588 (best: 1899.6588, rho: 0.003, sigma2: 0.018, mean tau: 0.9562: 98%|█████████▊| 983/1000 [00:04<00:00, 228.75it/s]
fit stat: 1899.6584 (best: 1899.6584, rho: 0.003, sigma2: 0.018, mean tau: 0.9561: 98%|█████████▊| 983/1000 [00:04<00:00, 228.75it/s]
fit stat: 1899.6584 (best: 1899.6584, rho: 0.003, sigma2: 0.018, mean tau: 0.9561: 98%|█████████▊| 983/1000 [00:04<00:00, 228.75it/s]
fit stat: 1899.6581 (best: 1899.6581, rho: 0.003, sigma2: 0.018, mean tau: 0.9561: 98%|█████████▊| 983/1000 [00:04<00:00, 228.75it/s]
fit stat: 1899.6581 (best: 1899.6581, rho: 0.003, sigma2: 0.018, mean tau: 0.9561: 98%|█████████▊| 983/1000 [00:04<00:00, 228.75it/s]
fit stat: 1899.6578 (best: 1899.6578, rho: 0.003, sigma2: 0.018, mean tau: 0.9561: 98%|█████████▊| 983/1000 [00:04<00:00, 228.75it/s]
fit stat: 1899.6577 (best: 1899.6577, rho: 0.003, sigma2: 0.018, mean tau: 0.9561: 98%|█████████▊| 983/1000 [00:04<00:00, 228.75it/s]
fit stat: 1899.6576 (best: 1899.6576, rho: 0.003, sigma2: 0.018, mean tau: 0.9561: 98%|█████████▊| 983/1000 [00:04<00:00, 228.75it/s]
fit stat: 1899.6573 (best: 1899.6573, rho: 0.003, sigma2: 0.018, mean tau: 0.9561: 98%|█████████▊| 983/1000 [00:04<00:00, 228.75it/s]
fit stat: 1899.6573 (best: 1899.6573, rho: 0.003, sigma2: 0.018, mean tau: 0.9561: 100%|██████████| 1000/1000 [00:04<00:00, 235.37it/s]
0%| | 0/200 [00:00<?, ?it/s]
0%| | 0/200 [00:00<?, ?it/s]
0%| | 0/200 [00:00<?, ?it/s]
LL: -6804.7915: 0%| | 0/200 [00:00<?, ?it/s]
LL: -6804.7915: 0%| | 1/200 [00:00<02:56, 1.13it/s]
LL: -6804.7915: 0%| | 1/200 [00:01<02:56, 1.13it/s]
LL: -6804.7915: 1%| | 2/200 [00:01<01:30, 2.18it/s]
LL: -6804.7915: 1%| | 2/200 [00:01<01:30, 2.18it/s]
LL: -6804.7915: 2%|▏ | 3/200 [00:01<01:01, 3.21it/s]
LL: -6804.7910: 2%|▏ | 3/200 [00:01<01:01, 3.21it/s]
LL: -6804.7910: 2%|▏ | 4/200 [00:01<00:48, 4.02it/s]
LL: -6804.7910: 2%|▏ | 4/200 [00:01<00:48, 4.02it/s]
LL: -6804.7910: 2%|▎ | 5/200 [00:01<00:40, 4.80it/s]
LL: -6804.7910: 2%|▎ | 5/200 [00:01<00:40, 4.80it/s]
LL: -6804.7910: 3%|▎ | 6/200 [00:01<00:36, 5.39it/s]
LL: -6804.7910: 3%|▎ | 6/200 [00:01<00:36, 5.39it/s]
LL: -6804.7910: 4%|▎ | 7/200 [00:01<00:33, 5.76it/s]
LL: -6804.7910: 4%|▎ | 7/200 [00:01<00:33, 5.76it/s]
LL: -6804.7910: 4%|▍ | 8/200 [00:01<00:30, 6.21it/s]
LL: -6804.7910: 4%|▍ | 8/200 [00:02<00:30, 6.21it/s]
LL: -6804.7910: 4%|▍ | 9/200 [00:02<00:28, 6.63it/s]
LL: -6804.7910: 4%|▍ | 9/200 [00:02<00:28, 6.63it/s]
LL: -6804.7910: 5%|▌ | 10/200 [00:02<00:27, 6.85it/s]
LL: -6804.7910: 5%|▌ | 10/200 [00:02<00:27, 6.85it/s]
LL: -6804.7910: 6%|▌ | 11/200 [00:02<00:26, 7.00it/s]
LL: -6804.7910: 6%|▌ | 11/200 [00:02<00:26, 7.00it/s]
LL: -6804.7910: 6%|▌ | 12/200 [00:02<00:26, 7.05it/s]
LL: -6804.7910: 6%|▌ | 12/200 [00:02<00:26, 7.05it/s]
LL: -6804.7910: 6%|▋ | 13/200 [00:02<00:25, 7.23it/s]
LL: -6804.7910: 6%|▋ | 13/200 [00:02<00:25, 7.23it/s]
LL: -6804.7910: 7%|▋ | 14/200 [00:02<00:25, 7.33it/s]
LL: -6804.7910: 7%|▋ | 14/200 [00:02<00:25, 7.33it/s]
LL: -6804.7910: 8%|▊ | 15/200 [00:02<00:24, 7.46it/s]
LL: -6804.7905: 8%|▊ | 15/200 [00:02<00:24, 7.46it/s]
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Total running time of the script: (0 minutes 48.202 seconds)