repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
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trieste-develop | trieste-develop/docs/notebooks/scalable_thompson_sampling_using_sparse_gaussian_processes.pct.py | # -*- coding: utf-8 -*-
# %% [markdown]
# # Scalable Thompson Sampling using Sparse Gaussian Process Models
# %% [markdown]
# In our other [Thompson sampling notebook](thompson_sampling.pct.py) we demonstrate how to perform batch optimization using a traditional implementation of Thompson sampling that samples exactly... | 6,553 | 46.839416 | 703 | py |
trieste-develop | trieste-develop/docs/notebooks/recovering_from_errors.pct.py | # %% [markdown]
# # Recovering from errors during optimization
# %%
import numpy as np
import tensorflow as tf
import random
np.random.seed(1793)
tf.random.set_seed(1793)
random.seed(3)
# %% [markdown]
# Sometimes the Bayesian optimization process encounters an error from which we can recover, without the need to re... | 7,238 | 43.140244 | 628 | py |
trieste-develop | trieste-develop/docs/notebooks/deep_gaussian_processes.pct.py | # %% [markdown]
# # Using deep Gaussian processes with GPflux for Bayesian optimization.
# %%
import numpy as np
import tensorflow as tf
np.random.seed(1794)
tf.random.set_seed(1794)
# %% [markdown]
# ## Describe the problem
#
# In this notebook, we show how to use deep Gaussian processes (DGPs) for Bayesian optimiz... | 11,347 | 30.348066 | 699 | py |
trieste-develop | trieste-develop/docs/notebooks/asynchronous_nongreedy_batch_ray.pct.py | # %% [markdown]
# # Asynchronous batch Bayesian optimization
#
# As shown in [Asynchronous Bayesian Optimization](asynchronous_greedy_multiprocessing.ipynb) tutorial, Trieste provides support for running observations asynchronously. In that tutorial we used a greedy batch acquisition function called Local Penalization,... | 8,288 | 38.28436 | 804 | py |
trieste-develop | trieste-develop/docs/notebooks/code_overview.pct.py | # %% [markdown]
# # An overview of Trieste types
# %% [markdown]
# Trieste is dedicated to Bayesian optimization, the process of finding the *optimal values of an expensive, black-box objective function by employing probabilistic models over observations*. This notebook explains how the different parts of this process... | 13,431 | 54.04918 | 985 | py |
trieste-develop | trieste-develop/docs/notebooks/expected_improvement.pct.py | # %% [markdown]
# # Noise-free optimization with Expected Improvement
# %%
import numpy as np
import tensorflow as tf
np.random.seed(1793)
tf.random.set_seed(1793)
# %% [markdown]
# ## Describe the problem
#
# In this example, we look to find the minimum value of the two-dimensional Branin function over the hypercub... | 13,740 | 41.541796 | 836 | py |
trieste-develop | trieste-develop/docs/notebooks/lunar_lander_videos/generate_video.py | """This script is used to generate videos for the OpenAI Gym notebook.
First two functions, as well as constants, shall be in sync with the notebook.
At the bottom of this file there are parameters and random seeds used to generate each video.
The video and several json files will be created in this folder, with some ... | 3,532 | 34.686869 | 265 | py |
trieste-develop | trieste-develop/docs/notebooks/quickrun/quickrun.py | # Copyright 2021 The Trieste Contributors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... | 4,104 | 30.821705 | 100 | py |
ba-complement | ba-complement-master/experimental/experimental-compare.py | #!/usr/bin/env python3
"""
Script for automated experimental evaluation.
@title experimental.py
@author Vojtech Havlena, June 2019
"""
import sys
import getopt
import subprocess
import string
import re
import os
import os.path
import resource
import xml.etree.ElementTree as ET
VALIDLINE = -2
TIMELINE = -1
STATESL... | 2,684 | 23.189189 | 101 | py |
ba-complement | ba-complement-master/experimental/experimental.py | #!/usr/bin/env python3
"""
Script for automated experimental evaluation.
@title experimental.py
@author Vojtech Havlena, April 2019
"""
import sys
import getopt
import subprocess
import string
import re
import os
import os.path
import resource
VALIDLINE = -2
TIMELINE = -1
STATESLINE = -2
DELAYSIM = -4
TIMEOUT = 3... | 3,042 | 25.008547 | 108 | py |
tensiometer | tensiometer-master/.material.py | """
This is random material, do not read it :)
"""
def _vec_to_log_pdm(vec, d):
"""
"""
# get indexes:
ind = np.tril_indices(d, 0)
# initialize:
mat = np.zeros((d, d))
mat[ind] = vec
# take exponential of the diagonal to ensure positivity:
mat[np.diag_indices(d)] = np.exp(np.diagon... | 3,098 | 28.514286 | 127 | py |
tensiometer | tensiometer-master/setup.py | #!/usr/bin/env python
import re
import os
import sys
import setuptools
# warn against python 2
if sys.version_info[0] == 2:
print('tensiometer does not support Python 2, \
please upgrade to Python 3')
sys.exit(1)
# version control:
def find_version():
version_file = open(os.path.join(os.path.... | 2,749 | 33.375 | 103 | py |
tensiometer | tensiometer-master/tensiometer/gaussian_tension.py | """
This file contains the functions and utilities to compute agreement and
disagreement between two different chains using a Gaussian approximation
for the posterior.
For more details on the method implemented see
`arxiv 1806.04649 <https://arxiv.org/pdf/1806.04649.pdf>`_
and `arxiv 1912.04880 <https://arxiv.org/pdf/... | 51,236 | 43.246114 | 111 | py |
tensiometer | tensiometer-master/tensiometer/cosmosis_interface.py | """
File with tools to interface Cosmosis chains with GetDist.
"""
"""
For testing purposes:
chain = loadMCSamples('./../test_chains/1p2_SN1_zcut0p3_abs')
chain_root = './test_chains/DES_multinest_cosmosis'
chain_root = './chains_lcdm/chain_1x2pt_lcdm'
chain_min_root = './chains_lcdm/chain_1x2pt_lcdm_MAP.maxlike'
pa... | 15,767 | 37.179177 | 97 | py |
tensiometer | tensiometer-master/tensiometer/chains_convergence.py | """
This file contains some functions to study convergence of the chains and
to compare the two posteriors.
"""
"""
For test purposes:
from getdist import loadMCSamples, MCSamples, WeightedSamples
chain = loadMCSamples('./test_chains/DES')
chains = chain
param_names = None
import tensiometer.utilities as utils
import... | 14,904 | 36.638889 | 104 | py |
tensiometer | tensiometer-master/tensiometer/tensor_eigenvalues.py | """
This file contains a set of utilities to compute tensor eigenvalues
since there is no standard library to do so.
"""
###############################################################################
# initial imports:
from itertools import permutations
import numpy as np
import scipy.linalg
import scipy.integrate
i... | 25,511 | 32.436435 | 79 | py |
tensiometer | tensiometer-master/tensiometer/utilities.py | """
This file contains some utilities that are used in the tensiometer package.
"""
###############################################################################
# initial imports:
import numpy as np
import scipy
import scipy.special
from scipy.linalg import sqrtm
from getdist import MCSamples
####################... | 15,550 | 34.997685 | 88 | py |
tensiometer | tensiometer-master/tensiometer/experimental.py | """
Experimental features.
For test purposes:
import os, sys
import time
import gc
from numba import jit
import numpy as np
import getdist.chains as gchains
gchains.print_load_details = False
from getdist import MCSamples, WeightedSamples
import scipy
from scipy.linalg import sqrtm
from scipy.integrate import simps
f... | 4,211 | 26.350649 | 121 | py |
tensiometer | tensiometer-master/tensiometer/__init__.py | __author__ = 'Marco Raveri'
__version__ = "0.1.2"
__url__ = "https://tensiometer.readthedocs.io"
from . import gaussian_tension, mcmc_tension, cosmosis_interface
| 163 | 26.333333 | 64 | py |
tensiometer | tensiometer-master/tensiometer/tests/test_utilities.py | ###############################################################################
# initial imports:
import unittest
import tensiometer.utilities as ttu
import numpy as np
###############################################################################
class test_confidence_to_sigma(unittest.TestCase):
def setU... | 5,405 | 31.371257 | 92 | py |
tensiometer | tensiometer-master/tensiometer/tests/test_tensor_eigenvalues.py | ###############################################################################
# initial imports:
import unittest
import tensiometer.tensor_eigenvalues as te
import os
import numpy as np
###############################################################################
class test_utilities(unittest.TestCase):
... | 1,612 | 32.604167 | 79 | py |
tensiometer | tensiometer-master/tensiometer/tests/test_chains_convergence.py | ###############################################################################
# initial imports:
import unittest
import tensiometer.chains_convergence as conv
import tensiometer.utilities as ttu
from getdist import loadMCSamples
import os
import numpy as np
########################################################... | 2,635 | 38.343284 | 106 | py |
tensiometer | tensiometer-master/tensiometer/tests/test_mcmc_tension_flow.py | ###############################################################################
# initial imports:
import unittest
import tensiometer.mcmc_tension.param_diff as pd
import tensiometer.mcmc_tension.flow as mt
import tensiometer.utilities as tut
from getdist import loadMCSamples
import os
import numpy as np
##########... | 2,043 | 36.163636 | 88 | py |
tensiometer | tensiometer-master/tensiometer/tests/test_gaussian_tension.py | ###############################################################################
# initial imports:
import unittest
import tensiometer.gaussian_tension as gt
import os
import numpy as np
from getdist.gaussian_mixtures import GaussianND
from getdist import loadMCSamples
###############################################... | 3,369 | 34.473684 | 79 | py |
tensiometer | tensiometer-master/tensiometer/tests/test_cosmosis_interface.py | ###############################################################################
# initial imports:
import unittest
import tensiometer.cosmosis_interface as ci
import os
###############################################################################
class test_cosmosis_interface(unittest.TestCase):
def setUp(... | 815 | 24.5 | 79 | py |
tensiometer | tensiometer-master/tensiometer/tests/test_mcmc_tension_kde.py | ###############################################################################
# initial imports:
import unittest
import tensiometer.mcmc_tension.param_diff as pd
import tensiometer.mcmc_tension.kde as mt
import tensiometer.utilities as tut
from getdist import loadMCSamples
import os
import numpy as np
###########... | 5,748 | 41.585185 | 91 | py |
tensiometer | tensiometer-master/tensiometer/mcmc_tension/flow.py | """
"""
###############################################################################
# initial imports and set-up:
import os
import time
import gc
from numba import jit
import numpy as np
import getdist.chains as gchains
gchains.print_load_details = False
from getdist import MCSamples, WeightedSamples
import scip... | 26,170 | 49.040153 | 648 | py |
tensiometer | tensiometer-master/tensiometer/mcmc_tension/kde.py | """
"""
"""
For test purposes:
from getdist import loadMCSamples, MCSamples, WeightedSamples
chain_1 = loadMCSamples('./test_chains/DES')
chain_2 = loadMCSamples('./test_chains/Planck18TTTEEE')
chain_12 = loadMCSamples('./test_chains/Planck18TTTEEE_DES')
chain_prior = loadMCSamples('./test_chains/prior')
import ten... | 43,456 | 41.688605 | 151 | py |
tensiometer | tensiometer-master/tensiometer/mcmc_tension/param_diff.py | """
"""
"""
For test purposes:
from getdist import loadMCSamples, MCSamples, WeightedSamples
chain_1 = loadMCSamples('./test_chains/DES')
chain_2 = loadMCSamples('./test_chains/Planck18TTTEEE')
chain_12 = loadMCSamples('./test_chains/Planck18TTTEEE_DES')
chain_prior = loadMCSamples('./test_chains/prior')
import ten... | 12,497 | 42.852632 | 79 | py |
tensiometer | tensiometer-master/tensiometer/mcmc_tension/__init__.py | """
This module contains the functions and utilities to compute non-Gaussian
Monte Carlo tension estimators.
The submodule `param_diff` contains the functions and utilities to compute the distribution
of parameter differences from the parameter posterior of two experiments.
The submodule `kde` contains the functions ... | 1,111 | 37.344828 | 98 | py |
tensiometer | tensiometer-master/docs/example_notebooks/pymaxent.py | #!/usr/bin/env python
"""PyMaxEnt.py: Implements a maximum entropy reconstruction of distributions with known moments."""
__author__ = "Tony Saad and Giovanna Ruai"
__copyright__ = "Copyright (c) 2019, Tony Saad"
__credits__ = ["University of Utah Department of Chemical Engineering", "University of Utah UROP ... | 9,329 | 40.838565 | 237 | py |
tensiometer | tensiometer-master/docs/source/conf.py | # -*- coding: utf-8 -*-
#
# MyProj documentation build configuration file, created by
# sphinx-quickstart on Thu Jun 18 20:57:49 2015.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# Al... | 9,842 | 32.593857 | 190 | py |
Atari-5 | Atari-5-main/atari_util.py | import matplotlib.pyplot as plt
cmap10 = plt.get_cmap('tab10')
cmap20 = plt.get_cmap('tab20')
def color_fade(x, factor=0.5):
if len(x) == 3:
r,g,b = x
a = 1.0
else:
r,g,b,a = x
r = (1*factor+(1-factor)*r)
g = (1*factor+(1-factor)*g)
b = (1*factor+(1-factor)*b)
return (r... | 5,851 | 23.082305 | 112 | py |
Atari-5 | Atari-5-main/atari5.py | import numpy as np
import pandas
import pandas as pd
import itertools
import sklearn
import sklearn.linear_model
import statsmodels
import statsmodels.api as sm
import json
import csv
import matplotlib.pyplot as plt
import multiprocessing
import functools
import time
from sklearn.model_selection import cross_val_score
... | 25,279 | 33.301221 | 157 | py |
white_box_rarl | white_box_rarl-main/wbrarl_plotting.py |
from pathlib import Path
import numpy as np
import pickle
import matplotlib.pyplot as plt
from matplotlib import rc
from scipy import stats
rc('font', **{'family': 'serif', 'serif': ['Palatino']})
plt.rcParams['pdf.fonttype'] = 42
results_path = Path('./results/')
N_TRAIN_STEPS = 2000000
FS = 15
N_EXCLUDE = 20
TOTAL... | 12,269 | 34.877193 | 121 | py |
white_box_rarl | white_box_rarl-main/wbrarl.py | import sys
import os
import time
import random
import argparse
import multiprocessing
import pickle
import copy
from multiprocessing import freeze_support
import numpy as np
import torch
import gym
from stable_baselines3.ppo import PPO
from stable_baselines3.sac import SAC
from stable_baselines3.common.vec_env import S... | 24,786 | 43.341682 | 148 | py |
neurotron_experiments | neurotron_experiments-main/run_sim05.py | # %% Import packages
import numpy as np
from pathlib import Path
from neurotron import NeuroTron
from sim_setup import output_path, sim05_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Set the seed
np.random.seed(sim05_setup['seed'])
# %% Instantiate Neur... | 956 | 22.341463 | 106 | py |
neurotron_experiments | neurotron_experiments-main/plot_sim01.py | # %% Import packages
import numpy as np
from matplotlib import pyplot as plt
from pathlib import Path
from sim_setup import output_path, sim01_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Load numerical output
tron_error_loaded = np.loadtxt(output_path.jo... | 2,838 | 24.123894 | 120 | py |
neurotron_experiments | neurotron_experiments-main/run_sim07.py | # %% Import packages
import numpy as np
from pathlib import Path
from neurotron import NeuroTron
from sim_setup import output_path, sim07_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Set the seed
np.random.seed(sim07_setup['seed'])
# %% Instantiate Neur... | 956 | 22.341463 | 106 | py |
neurotron_experiments | neurotron_experiments-main/plot_sim05.py | # %% Import packages
import numpy as np
from matplotlib import pyplot as plt
from pathlib import Path
from sim_setup import output_path, sim05_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Load numerical output
tron_error_loaded = np.loadtxt(output_path.jo... | 2,830 | 24.053097 | 119 | py |
neurotron_experiments | neurotron_experiments-main/plot_sim06.py | # %% Import packages
import numpy as np
from matplotlib import pyplot as plt
from pathlib import Path
from sim_setup import output_path, sim06_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Load numerical output
tron_error_loaded = np.loadtxt(output_path.jo... | 2,830 | 24.053097 | 119 | py |
neurotron_experiments | neurotron_experiments-main/plot_tron_theta_no_attack.py | # %% Import packages
import numpy as np
from matplotlib import pyplot as plt
from pathlib import Path
from sim_setup import output_path, sim01_setup, sim02_setup, sim03_setup, sim04_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Load numerical output
tron_e... | 3,020 | 22.787402 | 108 | py |
neurotron_experiments | neurotron_experiments-main/plot_sim04.py | # %% Import packages
import numpy as np
from matplotlib import pyplot as plt
from pathlib import Path
from sim_setup import output_path, sim04_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Load numerical output
tron_error_loaded = np.loadtxt(output_path.jo... | 2,841 | 24.150442 | 120 | py |
neurotron_experiments | neurotron_experiments-main/run_sim02.py | # %% Import packages
import numpy as np
from pathlib import Path
from neurotron import NeuroTron
from sim_setup import output_path, sim02_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Set the seed
np.random.seed(sim02_setup['seed'])
# %% Instantiate Neur... | 956 | 22.341463 | 106 | py |
neurotron_experiments | neurotron_experiments-main/plot_tron_merged_theta.py | # %% Import packages
import numpy as np
from matplotlib import pyplot as plt
from pathlib import Path
from sim_setup import output_path, sim01_setup, sim02_setup, sim03_setup, sim04_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Load numerical output
tron_e... | 4,623 | 28.832258 | 108 | py |
neurotron_experiments | neurotron_experiments-main/neurotron_torch.py | # %% [markdown]
# # Settings
# %%
import torch
import matplotlib.pyplot as plt
import numpy as np
import torch.nn as nn
from sklearn.datasets import fetch_california_housing
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from torch.utils.data import DataLoader... | 8,128 | 25.478827 | 122 | py |
neurotron_experiments | neurotron_experiments-main/plot_tron_q_assist_sim.py | # %% Import packages
import numpy as np
from matplotlib import pyplot as plt
from pathlib import Path
from sim_setup import output_path
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Load numerical output
tron_neuron1_error_loaded = []
for k in range(3):
tro... | 2,981 | 20.608696 | 126 | py |
neurotron_experiments | neurotron_experiments-main/plot_merged_sim05.py | # %% Import packages
import numpy as np
from matplotlib import pyplot as plt
from pathlib import Path
from sim_setup import output_path, sim05_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Load numerical output
tron_error_loaded = np.loadtxt(output_path.jo... | 2,834 | 23.025424 | 104 | py |
neurotron_experiments | neurotron_experiments-main/sim_setup.py | # %% Import packages
import numpy as np
from pathlib import Path
# %% Set output path
output_path = Path().joinpath('output')
# %% Setup for simulation 1: data ~ normal(mu=0, sigma=1), varying theta_{*}
sim01_setup = {
'sample_data' : lambda s : np.random.normal(loc=0.0, scale=1.0, size=s),
'filterlist' :... | 5,716 | 38.157534 | 84 | py |
neurotron_experiments | neurotron_experiments-main/plot_merged_sim01.py | # %% Import packages
import numpy as np
from matplotlib import pyplot as plt
from pathlib import Path
from sim_setup import output_path, sim01_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Load numerical output
tron_error_loaded = np.loadtxt(output_path.jo... | 2,851 | 23.169492 | 112 | py |
neurotron_experiments | neurotron_experiments-main/plot_sim08.py | # %% Import packages
import numpy as np
from matplotlib import pyplot as plt
from pathlib import Path
from sim_setup import output_path, sim08_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Load numerical output
tron_error_loaded = np.loadtxt(output_path.jo... | 2,833 | 24.079646 | 119 | py |
neurotron_experiments | neurotron_experiments-main/plot_merged_sim03.py | # %% Import packages
import numpy as np
from matplotlib import pyplot as plt
from pathlib import Path
from sim_setup import output_path, sim03_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Load numerical output
tron_error_loaded = np.loadtxt(output_path.jo... | 2,851 | 23.169492 | 112 | py |
neurotron_experiments | neurotron_experiments-main/plot_sim07.py | # %% Import packages
import numpy as np
from matplotlib import pyplot as plt
from pathlib import Path
from sim_setup import output_path, sim07_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Load numerical output
tron_error_loaded = np.loadtxt(output_path.jo... | 2,830 | 24.053097 | 119 | py |
neurotron_experiments | neurotron_experiments-main/plot_merged_sim08.py | # %% Import packages
import numpy as np
from matplotlib import pyplot as plt
from pathlib import Path
from sim_setup import output_path, sim08_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Load numerical output
tron_error_loaded = np.loadtxt(output_path.jo... | 2,834 | 23.025424 | 104 | py |
neurotron_experiments | neurotron_experiments-main/run_sim03.py | # %% Import packages
import numpy as np
from pathlib import Path
from neurotron import NeuroTron
from sim_setup import output_path, sim03_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Set the seed
np.random.seed(sim03_setup['seed'])
# %% Instantiate Neur... | 956 | 22.341463 | 106 | py |
neurotron_experiments | neurotron_experiments-main/plot_merged_sim06.py | # %% Import packages
import numpy as np
from matplotlib import pyplot as plt
from pathlib import Path
from sim_setup import output_path, sim06_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Load numerical output
tron_error_loaded = np.loadtxt(output_path.jo... | 2,834 | 23.025424 | 104 | py |
neurotron_experiments | neurotron_experiments-main/run_sim08.py | # %% Import packages
import numpy as np
from pathlib import Path
from neurotron import NeuroTron
from sim_setup import output_path, sim08_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Set the seed
np.random.seed(sim08_setup['seed'])
# %% Instantiate Neur... | 956 | 22.341463 | 106 | py |
neurotron_experiments | neurotron_experiments-main/run_sim01.py | # %% Import packages
import numpy as np
from pathlib import Path
from neurotron import NeuroTron
from sim_setup import output_path, sim01_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Set the seed
np.random.seed(sim01_setup['seed'])
# %% Instantiate Neur... | 956 | 22.341463 | 106 | py |
neurotron_experiments | neurotron_experiments-main/plot_merged_sim07.py | # %% Import packages
import numpy as np
from matplotlib import pyplot as plt
from pathlib import Path
from sim_setup import output_path, sim07_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Load numerical output
tron_error_loaded = np.loadtxt(output_path.jo... | 2,834 | 23.025424 | 104 | py |
neurotron_experiments | neurotron_experiments-main/plot_merged_sim04.py | # %% Import packages
import numpy as np
from matplotlib import pyplot as plt
from pathlib import Path
from sim_setup import output_path, sim04_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Load numerical output
tron_error_loaded = np.loadtxt(output_path.jo... | 2,851 | 23.169492 | 112 | py |
neurotron_experiments | neurotron_experiments-main/run_sim04.py | # %% Import packages
import numpy as np
from pathlib import Path
from neurotron import NeuroTron
from sim_setup import output_path, sim04_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Set the seed
np.random.seed(sim04_setup['seed'])
# %% Instantiate Neur... | 956 | 22.341463 | 106 | py |
neurotron_experiments | neurotron_experiments-main/run_tron_q_assist_sim.py | #%% -*- coding: utf-8 -*-
"""NC submission Neurotron q assist
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1Grqd8YloStHVD0eoAnUtOJ3jSxX1A8rA
#Introduction
"""
# %% Import packages
import numpy as np
import random
from random import sample
import ... | 10,704 | 39.703422 | 146 | py |
neurotron_experiments | neurotron_experiments-main/plot_tron_merged_beta.py | # %% Import packages
import numpy as np
from matplotlib import pyplot as plt
from pathlib import Path
from sim_setup import output_path, sim05_setup, sim06_setup, sim07_setup, sim08_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Load numerical output
tron_e... | 4,409 | 27.451613 | 108 | py |
neurotron_experiments | neurotron_experiments-main/run_sim06.py | # %% Import packages
import numpy as np
from pathlib import Path
from neurotron import NeuroTron
from sim_setup import output_path, sim06_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Set the seed
np.random.seed(sim06_setup['seed'])
# %% Instantiate Neur... | 956 | 22.341463 | 106 | py |
neurotron_experiments | neurotron_experiments-main/neurotron.py | import numpy as np
class NeuroTron:
def __init__(self, sample_data=None, w_star=None, d=None, eta_tron=None, eta_sgd=None, b=None, width=None, filter=None):
self.sample_data = sample_data
self.reset(w_star, d, eta_tron, b, width, filter)
def reset(self, w_star, d, eta_tron, b, width, filter, ... | 5,583 | 33.68323 | 124 | py |
neurotron_experiments | neurotron_experiments-main/plot_merged_sim02.py | # %% Import packages
import numpy as np
from matplotlib import pyplot as plt
from pathlib import Path
from sim_setup import output_path, sim02_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Load numerical output
tron_error_loaded = np.loadtxt(output_path.jo... | 2,851 | 23.169492 | 112 | py |
neurotron_experiments | neurotron_experiments-main/plot_sim03.py | # %% Import packages
import numpy as np
from matplotlib import pyplot as plt
from pathlib import Path
from sim_setup import output_path, sim03_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Load numerical output
tron_error_loaded = np.loadtxt(output_path.jo... | 2,838 | 24.123894 | 120 | py |
neurotron_experiments | neurotron_experiments-main/plot_sim02.py | # %% Import packages
import numpy as np
from matplotlib import pyplot as plt
from pathlib import Path
from sim_setup import output_path, sim02_setup
# %% Create output path if it does not exist
output_path.mkdir(parents=True, exist_ok=True)
# %% Load numerical output
tron_error_loaded = np.loadtxt(output_path.jo... | 2,838 | 24.123894 | 120 | py |
presto | presto-master/setup.py | from __future__ import print_function
import os
import sys
import numpy
# setuptools has to be imported before numpy.distutils.core
import setuptools
from numpy.distutils.core import Extension, setup
version = "4.0"
define_macros = []
undef_macros = []
extra_compile_args = ["-DUSEFFTW"]
include_dirs = [numpy.get_inc... | 3,895 | 40.010526 | 96 | py |
presto | presto-master/python/presto_src/prestoswig.py | # This file was automatically generated by SWIG (http://www.swig.org).
# Version 4.1.0
#
# Do not make changes to this file unless you know what you are doing--modify
# the SWIG interface file instead.
from sys import version_info as _swig_python_version_info
if _swig_python_version_info < (2, 7, 0):
raise Runtime... | 22,317 | 45.11157 | 215 | py |
presto | presto-master/python/presto_src/__init__.py | from __future__ import print_function
from __future__ import absolute_import
from builtins import input
from builtins import range
from .prestoswig import *
import os.path
import numpy as np
from presto import Pgplot
from presto import psr_utils
def val_with_err(value, error, length=0, digits=2, latex=0):
"""
... | 27,908 | 36.562584 | 86 | py |
presto | presto-master/python/binresponses/monte_short.py | from __future__ import print_function
from builtins import range
from time import clock
from math import *
from Numeric import *
from presto import *
from miscutils import *
from Statistics import *
import Pgplot
# Some admin variables
showplots = 0 # True or false
showsumplots = 0 # True or false
debugou... | 3,677 | 36.530612 | 79 | py |
presto | presto-master/python/binresponses/monte_ffdot.py | from __future__ import print_function
from builtins import range
from time import clock
from math import *
from Numeric import *
from presto import *
from miscutils import *
from Statistics import *
# Some admin variables
parallel = 0 # True or false
showplots = 0 # True or false
debugout = 0 ... | 7,526 | 40.585635 | 85 | py |
presto | presto-master/python/binresponses/monte_sideb.py | from __future__ import print_function
from builtins import range
from time import clock
from math import *
from Numeric import *
from presto import *
from miscutils import *
from Statistics import *
from random import expovariate
import RNG
global theo_sum_pow, b_pows, bsum_pows, newpows, noise, fftlen
# Some admin v... | 9,594 | 37.075397 | 97 | py |
presto | presto-master/python/binresponses/montebinresp.py | from __future__ import print_function
from builtins import range
from time import clock
from math import *
from Numeric import *
from presto import *
from miscutils import *
from Statistics import *
# Some admin variables
parallel = 0 # True or false
showplots = 1 # True or false
debugout = 1 ... | 12,905 | 46.623616 | 85 | py |
presto | presto-master/python/binopttest/comb.py | from __future__ import print_function
from builtins import range
from Numeric import *
from presto import *
from LeastSquares import leastSquaresFit
from orbitstuff import *
# Observation parameters
dt = 0.000125 # The duration of each data sample
N = 2**28 # The number of points in the observation
T =... | 1,549 | 31.978723 | 71 | py |
presto | presto-master/python/binopttest/bindata.py | from __future__ import print_function
from future import standard_library
standard_library.install_aliases()
from builtins import range
def catvar(col):
ret = []
global a, b, c, d, e
for i in range(shape(a)[0]):
ret.append(a[i][col])
for i in range(shape(b)[0]):
ret.append(b[i][col])
... | 5,131 | 34.638889 | 81 | py |
presto | presto-master/python/binopttest/montebinopt.py | from __future__ import print_function
from future import standard_library
standard_library.install_aliases()
from builtins import str
from builtins import input
from builtins import range
import math, string, Numeric, presto, random, sys, pickle
from LeastSquares import leastSquaresFit
from orbitstuff import *
# Some ... | 8,294 | 34.448718 | 81 | py |
presto | presto-master/python/presto/sifting.py | #!/usr/bin/env python
from __future__ import print_function
from __future__ import absolute_import
from builtins import zip, str, range, object
from operator import attrgetter
import sys, re, os, copy
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import os.path
import glob
from presto import info... | 54,077 | 39.146993 | 99 | py |
presto | presto-master/python/presto/infodata.py | from builtins import object
## Automatically adapted for numpy Apr 14, 2006 by convertcode.py
class infodata(object):
def __init__(self, filenm):
self.breaks = 0
for line in open(filenm, encoding="latin-1"):
if line.startswith(" Data file name"):
self.basenm = line.split... | 6,965 | 47.041379 | 98 | py |
presto | presto-master/python/presto/binary_psr.py | from __future__ import print_function
from __future__ import absolute_import
from builtins import object
import numpy as Num
from presto import parfile, psr_utils
from presto.psr_constants import *
def myasarray(a):
if type(a) in [type(1.0),type(1),type(1),type(1j)]:
a = Num.asarray([a])
if len(a) == 0... | 10,195 | 38.366795 | 84 | py |
presto | presto-master/python/presto/parfile.py | from __future__ import print_function
from __future__ import absolute_import
from builtins import object
import six
import math, re
from presto import psr_utils as pu
from presto import psr_constants as pc
try:
from slalib import sla_ecleq, sla_eqecl, sla_eqgal
slalib = True
except ImportError:
slalib = Fal... | 10,504 | 41.703252 | 96 | py |
presto | presto-master/python/presto/events.py | from __future__ import print_function
import bisect
from presto.psr_constants import PI, TWOPI, PIBYTWO
from presto.simple_roots import newton_raphson
from scipy.special import iv, chdtri, ndtr, ndtri
from presto.cosine_rand import *
import numpy as np
def sine_events(pulsed_frac, Nevents, phase=0.0):
"""
sin... | 18,498 | 40.947846 | 89 | py |
presto | presto-master/python/presto/pypsrcat.py | from __future__ import print_function
from __future__ import absolute_import
from builtins import object
from operator import attrgetter
import struct
import os.path
import math
import csv
import astropy.coordinates as c
import astropy.units as u
from presto import presto
import presto.psr_utils as pu
import presto.psr... | 16,621 | 44.539726 | 676 | py |
presto | presto-master/python/presto/mpfit.py | """
Perform Levenberg-Marquardt least-squares minimization, based on MINPACK-1.
AUTHORS
The original version of this software, called LMFIT, was written in FORTRAN
as part of the MINPACK-1 package by XXX.
Craig Markwardt converted the FORTRAN code to IDL. The information for ... | 88,531 | 38.190792 | 97 | py |
presto | presto-master/python/presto/sigproc.py | #!/usr/bin/env python
from __future__ import print_function
from __future__ import absolute_import
from builtins import zip
import os
import struct
import sys
import math
import warnings
from presto.psr_constants import ARCSECTORAD
telescope_ids = {"Fake": 0, "Arecibo": 1, "ARECIBO 305m": 1,
"Ooty": ... | 7,132 | 31.130631 | 92 | py |
presto | presto-master/python/presto/waterfaller.py | ../../bin/waterfaller.py | 24 | 24 | 24 | py |
presto | presto-master/python/presto/spectra.py | from builtins import str
from builtins import range
from builtins import object
import copy
import numpy as np
import scipy.signal
from presto import psr_utils
class Spectra(object):
"""A class to store spectra. This is mainly to provide
reusable functionality.
"""
def __init__(self, freqs, dt, da... | 12,864 | 36.616959 | 88 | py |
presto | presto-master/python/presto/psr_utils.py | from __future__ import print_function
from __future__ import absolute_import
from builtins import str
from builtins import range
import bisect
import numpy as Num
import numpy.fft as FFT
from scipy.special import ndtr, ndtri, chdtrc, chdtri, fdtrc, i0, kolmogorov
from scipy.optimize import leastsq
import scipy.optimize... | 75,060 | 36.399601 | 112 | py |
presto | presto-master/python/presto/psr_constants.py | ## Automatically adapted for numpy Apr 14, 2006 by convertcode.py
ARCSECTORAD = float('4.8481368110953599358991410235794797595635330237270e-6')
RADTOARCSEC = float('206264.80624709635515647335733077861319665970087963')
SECTORAD = float('7.2722052166430399038487115353692196393452995355905e-5')
RADTOSEC = float('1... | 1,369 | 51.692308 | 77 | py |
presto | presto-master/python/presto/prepfold.py | from __future__ import print_function
from __future__ import absolute_import
from builtins import range
from builtins import object
import sys
import numpy as Num
import copy, random, struct
from presto import psr_utils, infodata, polycos, Pgplot
import six
import numbers
from presto.bestprof import bestprof
from prest... | 41,422 | 46.071591 | 103 | py |
presto | presto-master/python/presto/injectpsr.py | #!/usr/bin/env python
"""Inject a fake pulsar into real data, creating
a filterbank file.
Patrick Lazarus, June 26, 2012
"""
from __future__ import print_function
from builtins import zip
from builtins import object
import sys
import argparse
import warnings
import copy
import numpy as np
import scipy.integrate
impo... | 48,769 | 37.371361 | 94 | py |
presto | presto-master/python/presto/fftfit.py | from _fftfit import * | 21 | 21 | 21 | py |
presto | presto-master/python/presto/Pgplot.py | """
Routine for easy to use 1-D and 2-D plotting using 'PGPLOT'
and the Python 'PPGPLOT' package
Written by Scott M. Ransom (ransom@cfa.harvard.edu)
last revision: 01 Jul 2000
'PGPLOT' was writtten by Tim Pearson <tjp@astro.caltech.edu>,
and can be found at http://astro.caltech.edu/~tjp/pgplot/
... | 29,817 | 41.965418 | 81 | py |
presto | presto-master/python/presto/polycos.py | from __future__ import absolute_import
from builtins import range
from builtins import object
import os
import sys
import subprocess
from presto import parfile
import numpy as Num
# Constants
NUMCOEFFS_DEFAULT = 12
SPAN_DEFAULT = 60 # span of each polyco in minutes
# Telescope name to TEMPO observatory code conversi... | 10,605 | 36.878571 | 92 | py |
presto | presto-master/python/presto/kuiper.py | from __future__ import print_function
from __future__ import absolute_import
from builtins import range
import numpy as num
from presto import Pgplot
from functools import reduce
def noverk(n,k):
# This is the combinations formula
return float(reduce(lambda a,b: a*(n-b)/(b+1), range(k),1))
def Tt(t, z, N):
... | 4,426 | 32.793893 | 87 | py |
presto | presto-master/python/presto/residuals.py | from __future__ import print_function
from builtins import range
from builtins import object
import struct
import numpy as Num
#
# From the TEMPO Documentation:
#
# The file resid2.tmp contains residuals, etc. in inary format.
# Each record contains eight real*8 values:
# --TOA (MJD, referenced to solar sy... | 3,668 | 38.451613 | 97 | py |
presto | presto-master/python/presto/__init__.py | 0 | 0 | 0 | py | |
presto | presto-master/python/presto/simple_roots.py | from __future__ import print_function
from builtins import range
# 'Safe' Newton-Raphson and Secant method
# for numerical root-finding
#
# Written by Scott M. Ransom <sransom@nrao.edu>
def bisect(func, lox, hix, TOL=1e-14, MAXIT=200):
"""
bisect(func, lox, hix, TOL=1e-14, MAXIT=200):
Try to find a r... | 3,967 | 29.75969 | 78 | py |
presto | presto-master/python/presto/bestprof.py | from builtins import object
## Automatically adapted for numpy Apr 14, 2006 by convertcode.py
import numpy as num
def get_epochs(line):
i, f = line.split("=")[-1].split(".")
f = "0."+f
epochi = float(i)
epochf = float(f)
# Check to see if it is very close to 1 sec
# If it is, assume the epoch ... | 5,982 | 42.671533 | 93 | py |
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