repo_name stringlengths 6 67 | path stringlengths 5 185 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 1.02k 962k | license stringclasses 15
values |
|---|---|---|---|---|---|
Agent007/deepchem | examples/binding_pockets/binding_pocket_datasets.py | 9 | 6311 | """
PDBBind binding pocket dataset loader.
"""
from __future__ import print_function
from __future__ import division
from __future__ import unicode_literals
import os
import numpy as np
import pandas as pd
import shutil
import time
import re
from rdkit import Chem
import deepchem as dc
def compute_binding_pocket_fea... | mit |
Artimi/waktu | waktu/waktu-gui.py | 1 | 21576 | #!/usr/bin/env python2.7
#-*- coding: UTF-8 -*-
from gi.repository import Gtk, Gdk, GLib, GObject
from waktu import Waktu
import category
from timetracker import TimeTracker
from matplotlib.figure import Figure
from matplotlib.backends.backend_gtk3agg import FigureCanvasGTK3Agg as FigureCanvas
from datetime import t... | mit |
commaai/panda | tests/automated/helpers.py | 1 | 6630 | import os
import time
import random
import _thread
import faulthandler
from functools import wraps
from panda import Panda
from panda_jungle import PandaJungle # pylint: disable=import-error
from nose.tools import assert_equal
from parameterized import parameterized, param
from .timeout import run_with_timeout
SPEED_... | mit |
LiaoPan/scikit-learn | examples/applications/plot_species_distribution_modeling.py | 254 | 7434 | """
=============================
Species distribution modeling
=============================
Modeling species' geographic distributions is an important
problem in conservation biology. In this example we
model the geographic distribution of two south american
mammals given past observations and 14 environmental
varia... | bsd-3-clause |
justinfinkle/pydiffexp | data/motif_library/gnw_generate_data.py | 1 | 9339 | import functools
import multiprocessing as mp
import operator
import os
import subprocess
import time
import itertools as it
import networkx as nx
import pandas as pd
import numpy as np
from pydiffexp.gnw.simulation import GnwNetwork, mk_ch_dir
def count_combos(dg):
combos = {0: 1, 1: 2, 2: 8}
n_in = [combos... | gpl-3.0 |
phobson/statsmodels | examples/python/contrasts.py | 33 | 8722 |
## Contrasts Overview
from __future__ import print_function
import numpy as np
import statsmodels.api as sm
# This document is based heavily on this excellent resource from UCLA http://www.ats.ucla.edu/stat/r/library/contrast_coding.htm
# A categorical variable of K categories, or levels, usually enters a regressio... | bsd-3-clause |
arjunkhode/ASP | lectures/03-Fourier-properties/plots-code/convolution-2.py | 24 | 1259 | import matplotlib.pyplot as plt
import numpy as np
from scipy.fftpack import fft, fftshift
plt.figure(1, figsize=(9.5, 7))
M = 64
N = 64
x1 = np.hanning(M)
x2 = np.cos(2*np.pi*2/M*np.arange(M))
y1 = x1*x2
mY1 = 20 * np.log10(np.abs(fftshift(fft(y1, N))))
plt.subplot(3,2,1)
plt.title('x1 (hanning)')
plt.plot(np.arange... | agpl-3.0 |
aravart/poolmate | poolmate/test/dummy.py | 2 | 1137 | import sys
import numpy as np
from sklearn.datasets import make_classification
from sklearn.metrics import zero_one_loss
from sklearn.neighbors import KNeighborsClassifier
def inline(inputfile, outputfile):
# data = np.loadtxt(sys.stdin)
data = np.loadtxt(inputfile, delimiter=',')
if np.ndim(data) == 1:
... | mit |
LiaoPan/scikit-learn | examples/cluster/plot_segmentation_toy.py | 258 | 3336 | """
===========================================
Spectral clustering for image segmentation
===========================================
In this example, an image with connected circles is generated and
spectral clustering is used to separate the circles.
In these settings, the :ref:`spectral_clustering` approach solve... | bsd-3-clause |
sugartom/tensorflow-alien | tensorflow/python/estimator/inputs/queues/feeding_queue_runner_test.py | 116 | 5164 | # Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# 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 applica... | apache-2.0 |
Myasuka/scikit-learn | examples/linear_model/plot_ols_3d.py | 350 | 2040 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Sparsity Example: Fitting only features 1 and 2
=========================================================
Features 1 and 2 of the diabetes-dataset are fitted and
plotted below. It illustrates that although feature... | bsd-3-clause |
avistous/QSTK | quicksim/strategies/MonthlyRebalancing.py | 4 | 2190 | '''
(c) 2011, 2012 Georgia Tech Research Corporation
This source code is released under the New BSD license. Please see
http://wiki.quantsoftware.org/index.php?title=QSTK_License
for license details.
Created on Jan 1, 2011
@author:Drew Bratcher
@contact: dbratcher@gatech.edu
@summary: Contains tutorial for... | bsd-3-clause |
Lawrence-Liu/scikit-learn | examples/linear_model/plot_sgd_separating_hyperplane.py | 260 | 1219 | """
=========================================
SGD: Maximum margin separating hyperplane
=========================================
Plot the maximum margin separating hyperplane within a two-class
separable dataset using a linear Support Vector Machines classifier
trained using SGD.
"""
print(__doc__)
import numpy as n... | bsd-3-clause |
matbra/bokeh | bokeh/crossfilter/models.py | 40 | 30635 | from __future__ import absolute_import
import logging
import six
import pandas as pd
import numpy as np
from ..plotting import curdoc
from ..models import ColumnDataSource, GridPlot, Panel, Tabs, Range
from ..models.widgets import Select, MultiSelect, InputWidget
# crossfilter plotting utilities
from .plotting impo... | bsd-3-clause |
josenavas/QiiTa | qiita_pet/handlers/study_handlers/tests/test_sample_template.py | 1 | 31592 | # -----------------------------------------------------------------------------
# Copyright (c) 2014--, The Qiita Development Team.
#
# Distributed under the terms of the BSD 3-clause License.
#
# The full license is in the file LICENSE, distributed with this software.
# ------------------------------------------------... | bsd-3-clause |
mtrbean/scipy | scipy/stats/_multivariate.py | 35 | 69253 | #
# Author: Joris Vankerschaver 2013
#
from __future__ import division, print_function, absolute_import
import numpy as np
import scipy.linalg
from scipy.misc import doccer
from scipy.special import gammaln, psi, multigammaln
from scipy._lib._util import check_random_state
__all__ = ['multivariate_normal', 'dirichle... | bsd-3-clause |
samzhang111/scikit-learn | sklearn/cluster/tests/test_dbscan.py | 176 | 12155 | """
Tests for DBSCAN clustering algorithm
"""
import pickle
import numpy as np
from scipy.spatial import distance
from scipy import sparse
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing im... | bsd-3-clause |
HolgerPeters/scikit-learn | sklearn/metrics/scorer.py | 33 | 17925 | """
The :mod:`sklearn.metrics.scorer` submodule implements a flexible
interface for model selection and evaluation using
arbitrary score functions.
A scorer object is a callable that can be passed to
:class:`sklearn.model_selection.GridSearchCV` or
:func:`sklearn.model_selection.cross_val_score` as the ``scoring``
par... | bsd-3-clause |
great-expectations/great_expectations | tests/rule_based_profiler/test_profiler.py | 1 | 11083 | import datetime
import os
from typing import List, Optional
import pandas as pd
import pytest
from ruamel.yaml import YAML
from great_expectations import DataContext
from great_expectations.core import ExpectationSuite
from great_expectations.core.batch import BatchRequest
from great_expectations.rule_based_profiler.... | apache-2.0 |
dkushner/zipline | tests/risk/answer_key.py | 39 | 11989 | #
# Copyright 2014 Quantopian, Inc.
#
# 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 in wr... | apache-2.0 |
vermouthmjl/scikit-learn | examples/neighbors/plot_regression.py | 349 | 1402 | """
============================
Nearest Neighbors regression
============================
Demonstrate the resolution of a regression problem
using a k-Nearest Neighbor and the interpolation of the
target using both barycenter and constant weights.
"""
print(__doc__)
# Author: Alexandre Gramfort <alexandre.gramfort@... | bsd-3-clause |
xclxxl414/rqalpha | rqalpha/utils/arg_checker.py | 1 | 17616 | # -*- coding: utf-8 -*-
#
# Copyright 2017 Ricequant, Inc
#
# 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 ... | apache-2.0 |
ameyavilankar/social-network-recommendation | matrix-factorization/calc.py | 1 | 2773 | import numpy as np
import random
from sklearn.cross_validation import train_test_split
import numpy as np
from sklearn.metrics import roc_auc_score
# IN_FILE = "facebook.1_of_1"
IN_FILE = "facebook.1_of_1"
USER_FILE = "facebook.U.1_of_1"
ITEM_FILE = "facebook.V.1_of_1"
TRAIN_FILE = "train.txt"
# Read the data from th... | bsd-2-clause |
pratapvardhan/pandas | pandas/core/series.py | 1 | 135882 | """
Data structure for 1-dimensional cross-sectional and time series data
"""
from __future__ import division
# pylint: disable=E1101,E1103
# pylint: disable=W0703,W0622,W0613,W0201
import types
import warnings
from textwrap import dedent
import numpy as np
import numpy.ma as ma
from pandas.core.accessor import Cac... | bsd-3-clause |
mattcaldwell/zipline | zipline/data/loader.py | 2 | 12089 | #
# Copyright 2013 Quantopian, Inc.
#
# 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 in wr... | apache-2.0 |
awanke/bokeh | bokeh/tests/test_sources.py | 26 | 3245 | from __future__ import absolute_import
import unittest
from unittest import skipIf
import warnings
try:
import pandas as pd
is_pandas = True
except ImportError as e:
is_pandas = False
from bokeh.models.sources import DataSource, ColumnDataSource, ServerDataSource
class TestColumnDataSourcs(unittest.Test... | bsd-3-clause |
pablooliveira/cere | src/cere/cere_selectinv.py | 2 | 6526 | #!/usr/bin/env python
# This file is part of CERE.
#
# Copyright (c) 2013-2016, Universite de Versailles St-Quentin-en-Yvelines
#
# CERE is free software: you can redistribute it and/or modify it under
# the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation, either version 3 ... | lgpl-3.0 |
Git3251/trading-with-python | lib/cboe.py | 76 | 4433 | # -*- coding: utf-8 -*-
"""
toolset working with cboe data
@author: Jev Kuznetsov
Licence: BSD
"""
from datetime import datetime, date
import urllib2
from pandas import DataFrame, Index
from pandas.core import datetools
import numpy as np
import pandas as pd
def monthCode(month):
"""
perfo... | bsd-3-clause |
travisfcollins/gnuradio | gr-digital/examples/example_costas.py | 49 | 5316 | #!/usr/bin/env python
#
# Copyright 2011-2013 Free Software Foundation, Inc.
#
# This file is part of GNU Radio
#
# GNU Radio is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3, or (at your optio... | gpl-3.0 |
CVML/scikit-learn | sklearn/decomposition/truncated_svd.py | 199 | 7744 | """Truncated SVD for sparse matrices, aka latent semantic analysis (LSA).
"""
# Author: Lars Buitinck <L.J.Buitinck@uva.nl>
# Olivier Grisel <olivier.grisel@ensta.org>
# Michael Becker <mike@beckerfuffle.com>
# License: 3-clause BSD.
import numpy as np
import scipy.sparse as sp
try:
from scipy.sp... | bsd-3-clause |
rvraghav93/scikit-learn | sklearn/__check_build/__init__.py | 345 | 1671 | """ Module to give helpful messages to the user that did not
compile the scikit properly.
"""
import os
INPLACE_MSG = """
It appears that you are importing a local scikit-learn source tree. For
this, you need to have an inplace install. Maybe you are in the source
directory and you need to try from another location.""... | bsd-3-clause |
sarathid/Learning | Intro_to_ML/final_project/poi_id.py | 9 | 2364 | #!/usr/bin/python
import sys
import pickle
sys.path.append("../tools/")
from feature_format import featureFormat, targetFeatureSplit
from tester import dump_classifier_and_data
### Task 1: Select what features you'll use.
### features_list is a list of strings, each of which is a feature name.
### The first feature ... | gpl-3.0 |
xyguo/scikit-learn | sklearn/manifold/tests/test_t_sne.py | 26 | 21787 | import sys
from sklearn.externals.six.moves import cStringIO as StringIO
import numpy as np
import scipy.sparse as sp
from sklearn.neighbors import BallTree
from sklearn.utils.testing import assert_less_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from skle... | bsd-3-clause |
madjelan/scikit-learn | sklearn/linear_model/tests/test_least_angle.py | 57 | 16523 | from nose.tools import assert_equal
import numpy as np
from scipy import linalg
from sklearn.cross_validation import train_test_split
from sklearn.externals import joblib
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_... | bsd-3-clause |
RapidApplicationDevelopment/tensorflow | tensorflow/contrib/learn/python/learn/dataframe/tensorflow_dataframe.py | 75 | 29377 | # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# 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 applica... | apache-2.0 |
boegel/easybuild-easyconfigs | test/easyconfigs/easyconfigs.py | 1 | 65364 | ##
# Copyright 2013-2021 Ghent University
#
# This file is part of EasyBuild,
# originally created by the HPC team of Ghent University (http://ugent.be/hpc/en),
# with support of Ghent University (http://ugent.be/hpc),
# the Flemish Supercomputer Centre (VSC) (https://www.vscentrum.be),
# Flemish Research Foundation (F... | gpl-2.0 |
paultcochrane/bokeh | bokeh/compat/mplexporter/exporter.py | 32 | 12403 | """
Matplotlib Exporter
===================
This submodule contains tools for crawling a matplotlib figure and exporting
relevant pieces to a renderer.
"""
import warnings
import io
from . import utils
import matplotlib
from matplotlib import transforms
from matplotlib.backends.backend_agg import FigureCanvasAgg
clas... | bsd-3-clause |
sdrendall/mea_analysis | pymea/filter_supplement.py | 2 | 4308 | import pandas as pd
import itertools as it
import seaborn as sns
import numpy as np
from pymea import matlab_compatibility as mc
from matplotlib import pyplot as plt
from matplotlib import mlab as mlab
import random
from datetime import datetime, timedelta
def filter_neurons_homeostasis(cat_table, baseline_table, stim... | mit |
f3r/scikit-learn | examples/model_selection/plot_train_error_vs_test_error.py | 349 | 2577 | """
=========================
Train error vs Test error
=========================
Illustration of how the performance of an estimator on unseen data (test data)
is not the same as the performance on training data. As the regularization
increases the performance on train decreases while the performance on test
is optim... | bsd-3-clause |
junbochen/pylearn2 | pylearn2/scripts/datasets/browse_norb.py | 44 | 15741 | #!/usr/bin/env python
"""
A browser for the NORB and small NORB datasets. Navigate the images by
choosing the values for the label vector. Note that for the 'big' NORB
dataset, you can only set the first 5 label dimensions. You can then cycle
through the 3-12 images that fit those labels.
"""
import sys
import os
imp... | bsd-3-clause |
asurve/systemml | src/main/python/tests/test_mllearn_numpy.py | 12 | 8831 | #!/usr/bin/python
#-------------------------------------------------------------
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this f... | apache-2.0 |
NelisVerhoef/scikit-learn | examples/cluster/plot_kmeans_stability_low_dim_dense.py | 338 | 4324 | """
============================================================
Empirical evaluation of the impact of k-means initialization
============================================================
Evaluate the ability of k-means initializations strategies to make
the algorithm convergence robust as measured by the relative stan... | bsd-3-clause |
hsuantien/scikit-learn | sklearn/datasets/tests/test_samples_generator.py | 67 | 14842 | from __future__ import division
from collections import defaultdict
from functools import partial
import numpy as np
from sklearn.externals.six.moves import zip
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_almost_equal
fr... | bsd-3-clause |
gsmcmullin/libswiftnav | python/docs/extensions/ipython_directive.py | 31 | 27191 | # -*- coding: utf-8 -*-
"""Sphinx directive to support embedded IPython code.
This directive allows pasting of entire interactive IPython sessions, prompts
and all, and their code will actually get re-executed at doc build time, with
all prompts renumbered sequentially. It also allows you to input code as a pure
pytho... | lgpl-3.0 |
ewulczyn/ewulczyn.github.io | ipython/How_Naive_AB_Testing_Goes_Wrong/abtest_util.py | 1 | 3278 | import matplotlib.pyplot as plt
import numpy as np
from numpy.random import multinomial
from numpy.random import beta as beta_dist
from pprint import pprint
import pandas as pd
from statsmodels.stats.power import tt_ind_solve_power
class SimStream(object):
"""
Encapsulates a simulated stream
of banner d... | mit |
jardians/sp17-i524 | project/S17-IR-P012/code/binarize.py | 21 | 1096 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Tue Apr 4 15:56:31 2017
I524 Project: OCR
Preprocessing
Binarization
@author: saber
"""
import numpy as np
import cv2
import matplotlib.pyplot as plt
image_path = 'sample1.png'
image_arr = cv2.imread(image_path, 0)
plt.figure(1)
plt.subplot(311)
# Plot hi... | apache-2.0 |
PortfolioEffect/PortfolioEffectHFT-Python | hft/portfolio.py | 2 | 38495 | """
This module provides a container class for storing portfolio parameters.
"""
from position import *
import matplotlib.pyplot as plt
import sys
import numpy as np
#
# Portfolio Methods
#
class Portfolio:
"""Container class for storing portfolio parameters."""
def __init__(self, fromTime=None, toTime=N... | gpl-3.0 |
lab3000/deeplearngene | src/clade.py | 1 | 3650 | import numpy as np
import os
import pandas as pd
import random
class Clade:
"""Class for loading data and defining, compiling, and fitting a
a population of keras models for genetic algorithm-driven optimization
of high-performing model architectures"""
def __init__(self, config, current_generation=0... | gpl-3.0 |
ledo01/Bulle-simulation | animation.py | 1 | 1358 | import numpy as np # Manipulation des arraysm
import matplotlib
matplotlib.use("Agg")
from matplotlib.pyplot import * # Graphiques
import matplotlib.animation as manimation
FFMpegWriter = manimation.writers['ffmpeg']
metadata = dict(title='Movie Test', artist='Matplotlib',comment='Movie support!')
writer = FFMpegWrite... | mit |
Mega-DatA-Lab/mxnet | example/reinforcement-learning/ddpg/strategies.py | 42 | 2473 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | apache-2.0 |
yorkerlin/shogun | examples/undocumented/python_modular/graphical/classifier_perceptron_graphical.py | 26 | 2311 | #!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
import latex_plot_inits
parameter_list = [[20, 5, 1., 1000, 1, None, 5], [100, 5, 1., 1000, 1, None, 10]]
def classifier_perceptron_graphical(n=100, distance=5, learn_rate=1., max_iter=1000, num_threads=1, seed=None, nperceptrons=5):
from mods... | gpl-3.0 |
claraya/SMRx | mapColor.py | 1 | 21901 | #!/usr/bin/env python
# This is a PyMol script that colors atoms/residues in a PDB structure using an input file and a target column.
# Note: Input must contain a target values column, position numbers, and a position adjustment factor if necessary.
# Usage: First, load the script within PyMol as follows:
#
# ... | mit |
tcheehow/MissionPlanner | Lib/site-packages/numpy/fft/fftpack.py | 59 | 39653 | """
Discrete Fourier Transforms
Routines in this module:
fft(a, n=None, axis=-1)
ifft(a, n=None, axis=-1)
rfft(a, n=None, axis=-1)
irfft(a, n=None, axis=-1)
hfft(a, n=None, axis=-1)
ihfft(a, n=None, axis=-1)
fftn(a, s=None, axes=None)
ifftn(a, s=None, axes=None)
rfftn(a, s=None, axes=None)
irfftn(a, s=None, axes=None... | gpl-3.0 |
mattgiguere/scikit-learn | sklearn/utils/tests/test_shortest_path.py | 42 | 2894 | from collections import defaultdict
import numpy as np
from numpy.testing import assert_array_almost_equal
from sklearn.utils.graph import (graph_shortest_path,
single_source_shortest_path_length)
def floyd_warshall_slow(graph, directed=False):
N = graph.shape[0]
#set nonzer... | bsd-3-clause |
ltiao/scikit-learn | sklearn/metrics/cluster/tests/test_bicluster.py | 394 | 1770 | """Testing for bicluster metrics module"""
import numpy as np
from sklearn.utils.testing import assert_equal, assert_almost_equal
from sklearn.metrics.cluster.bicluster import _jaccard
from sklearn.metrics import consensus_score
def test_jaccard():
a1 = np.array([True, True, False, False])
a2 = np.array([T... | bsd-3-clause |
jingwangian/tutorial | python/pandas_tutorial/test1.py | 1 | 1059 | #!/usr/bin/env python3
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import math
import os
import random
import re
import sys
numbers = "0123456789"
lower_case = "abcdefghijklmnopqrstuvwxyz"
upper_case = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
special_characters = "!@#$%^&*()-+"
# Complete the minimu... | gpl-3.0 |
songjs1993/DeepLearning | 5Project/disease_classification/Disease_LeNet2.py | 1 | 12541 | # Auther: Alan
"""
"""
import tensorflow as tf
import random
import os
import scipy.io as sio
# import matplotlib.pyplot as plt # plt
import matplotlib.image as mpimg # mpimg
import numpy as np
# import Image
import math
from PIL import Image
import xlrd
class Disease:
def __init__(self):
print("init")
... | apache-2.0 |
ClimbsRocks/scikit-learn | sklearn/tests/test_multioutput.py | 39 | 6609 | import numpy as np
import scipy.sparse as sp
from sklearn.utils import shuffle
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import assert_raises_regex
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing impor... | bsd-3-clause |
davidwaroquiers/pymatgen | pymatgen/analysis/diffraction/tem.py | 1 | 27148 | # coding: utf-8
# Copyright (c) Pymatgen Development Team.
# Distributed under the terms of the MIT License.
# Credit to Dr. Shyue Ping Ong for the template of the calculator
"""
This module implements a TEM pattern calculator.
"""
import json
import os
from collections import namedtuple
from fractions import Fractio... | mit |
theoryno3/scikit-learn | benchmarks/bench_sparsify.py | 323 | 3372 | """
Benchmark SGD prediction time with dense/sparse coefficients.
Invoke with
-----------
$ kernprof.py -l sparsity_benchmark.py
$ python -m line_profiler sparsity_benchmark.py.lprof
Typical output
--------------
input data sparsity: 0.050000
true coef sparsity: 0.000100
test data sparsity: 0.027400
model sparsity:... | bsd-3-clause |
guziy/basemap | examples/polarmaps.py | 2 | 2869 | from __future__ import (absolute_import, division, print_function)
# make plots of etopo bathymetry/topography data on
# various map projections, drawing coastlines, state and
# country boundaries, filling continents and drawing
# parallels/meridians
# illustrates special-case polar-centric projections.
from mpl_too... | gpl-2.0 |
farthir/msc-project | snippets/average_net_output_sam.py | 1 | 2689 | import sys
import math
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib import rcParams
def main():
input_filename = sys.argv[1]
num_networks = int(sys.argv[2])
df = pd.read_csv('results/%s.csv' % input_filename).round(10)
new_df = pd.DataFrame(dtype=float)
duplicate = df.dupl... | mit |
wolfram74/numerical_methods_iserles_notes | venv/lib/python2.7/site-packages/numpy/lib/recfunctions.py | 41 | 35014 | """
Collection of utilities to manipulate structured arrays.
Most of these functions were initially implemented by John Hunter for
matplotlib. They have been rewritten and extended for convenience.
"""
from __future__ import division, absolute_import, print_function
import sys
import itertools
import numpy as np
im... | mit |
maggieli96/35-Final-Project | Machine Learning/training_tuning.py | 1 | 4837 | import numpy as np
from sklearn import cross_validation
from sklearn import tree
from sklearn.neighbors import KNeighborsClassifier
from data_processing_ml import *
def ten_fold_CV(classifier, x_train, y_train):
""" This function takes three arguments:
1) classifier, an just initialized classifier we ... | mit |
gverdian/cuda-convnet2 | convdata.py | 174 | 14675 | # Copyright 2014 Google Inc. All rights reserved.
#
# 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... | apache-2.0 |
bsipocz/statsmodels | statsmodels/tools/print_version.py | 23 | 7951 | #!/usr/bin/env python
from __future__ import print_function
from statsmodels.compat.python import reduce
import sys
from os.path import dirname
def safe_version(module, attr='__version__'):
if not isinstance(attr, list):
attr = [attr]
try:
return reduce(getattr, [module] + attr)
except Att... | bsd-3-clause |
ingokegel/intellij-community | python/helpers/pydev/_pydevd_bundle/pydevd_utils.py | 6 | 21002 | from __future__ import nested_scopes
import os
import traceback
import warnings
import pydevd_file_utils
try:
from urllib import quote
except:
from urllib.parse import quote # @UnresolvedImport
try:
from collections import OrderedDict
except:
OrderedDict = dict
import inspect
from _pydevd_bundle.p... | apache-2.0 |
cbclab/MDT | mdt/visualization/maps/base.py | 1 | 70091 | import warnings
from copy import copy, deepcopy
import numbers
import matplotlib.font_manager
import nibabel
import numpy as np
import yaml
import mdt
import mdt.visualization.layouts
from mdt.lib.nifti import load_nifti, NiftiInfoDecorated
from mdt.visualization.dict_conversion import StringConversion, \
SimpleCl... | lgpl-3.0 |
glouppe/scikit-learn | sklearn/feature_selection/tests/test_feature_select.py | 103 | 22297 | """
Todo: cross-check the F-value with stats model
"""
from __future__ import division
import itertools
import warnings
import numpy as np
from scipy import stats, sparse
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_raises... | bsd-3-clause |
HrWangChengdu/CS231n | assignment3_tianjun/exp_gradient.py | 1 | 5907 | # As usual, a bit of setup
import time, os, json
import numpy as np
import skimage.io
import matplotlib.pyplot as plt
from cs231n.classifiers.pretrained_cnn import PretrainedCNN
from cs231n.data_utils import load_tiny_imagenet
from cs231n.image_utils import blur_image, deprocess_image
#%matplotlib inline
plt.rcParam... | mit |
hmtai6/universe_NeonRace-v0 | src/test_env.py | 1 | 1949 | import argparse
import logging
import sys
import cv2
import matplotlib.pyplot as plt
import gym
import universe # register the universe environments
from universe import wrappers
import numpy as np
import tensorflow as tf
import gym, time, random, threading
from keras.models import *
from keras.layers import *
fr... | mit |
FAB4D/humanitas | analysis/preproc/merge_series.py | 1 | 6091 | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import os
description = '''
This script merges series of the same product within each region.
Also for plotting.
Author: Ching-Chia
'''
wholesale_daily = True
retail_daily = False
retail_weekly = False
output_by_city = F... | bsd-3-clause |
iismd17/scikit-learn | sklearn/linear_model/ridge.py | 60 | 44642 | """
Ridge regression
"""
# Author: Mathieu Blondel <mathieu@mblondel.org>
# Reuben Fletcher-Costin <reuben.fletchercostin@gmail.com>
# Fabian Pedregosa <fabian@fseoane.net>
# Michael Eickenberg <michael.eickenberg@nsup.org>
# License: BSD 3 clause
from abc import ABCMeta, abstractmethod
impor... | bsd-3-clause |
shahankhatch/scikit-learn | sklearn/semi_supervised/tests/test_label_propagation.py | 307 | 1974 | """ test the label propagation module """
import nose
import numpy as np
from sklearn.semi_supervised import label_propagation
from numpy.testing import assert_array_almost_equal
from numpy.testing import assert_array_equal
ESTIMATORS = [
(label_propagation.LabelPropagation, {'kernel': 'rbf'}),
(label_propa... | bsd-3-clause |
r-mart/scikit-learn | sklearn/cluster/tests/test_k_means.py | 63 | 26190 | """Testing for K-means"""
import sys
import numpy as np
from scipy import sparse as sp
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import SkipTest
from sklearn.utils.testing i... | bsd-3-clause |
alvarofierroclavero/scikit-learn | examples/linear_model/plot_logistic_l1_l2_sparsity.py | 384 | 2601 | """
==============================================
L1 Penalty and Sparsity in Logistic Regression
==============================================
Comparison of the sparsity (percentage of zero coefficients) of solutions when
L1 and L2 penalty are used for different values of C. We can see that large
values of C give mo... | bsd-3-clause |
crisbarros/trading-with-python | lib/backtest.py | 74 | 7381 | #-------------------------------------------------------------------------------
# Name: backtest
# Purpose: perform routine backtesting tasks.
# This module should be useable as a stand-alone library outide of the TWP package.
#
# Author: Jev Kuznetsov
#
# Created: 03/07/2014
... | bsd-3-clause |
alexeyum/scikit-learn | sklearn/linear_model/tests/test_omp.py | 76 | 7752 | # Author: Vlad Niculae
# License: BSD 3 clause
import numpy as np
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equa... | bsd-3-clause |
devanshdalal/scikit-learn | examples/linear_model/plot_robust_fit.py | 147 | 3050 | """
Robust linear estimator fitting
===============================
Here a sine function is fit with a polynomial of order 3, for values
close to zero.
Robust fitting is demoed in different situations:
- No measurement errors, only modelling errors (fitting a sine with a
polynomial)
- Measurement errors in X
- M... | bsd-3-clause |
tosolveit/scikit-learn | sklearn/metrics/pairwise.py | 49 | 44088 | # -*- coding: utf-8 -*-
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Mathieu Blondel <mathieu@mblondel.org>
# Robert Layton <robertlayton@gmail.com>
# Andreas Mueller <amueller@ais.uni-bonn.de>
# Philippe Gervais <philippe.gervais@inria.fr>
# Lars Buitinck ... | bsd-3-clause |
dssg/wikienergy | disaggregator/build/pandas/pandas/tests/test_expressions.py | 4 | 16414 | # -*- coding: utf-8 -*-
from __future__ import print_function
# pylint: disable-msg=W0612,E1101
import nose
import re
from numpy.random import randn
import operator
import numpy as np
from numpy.testing import assert_array_equal
from pandas.core.api import DataFrame, Panel
from pandas.computation import expressions... | mit |
neilswainston/development-py | synbiochemdev/ms/test/analyse.py | 1 | 1333 | '''
synbiochem (c) University of Manchester 2017
All rights reserved.
@author: neilswainston
'''
# pylint: disable=invalid-name
import re
import sys
import pandas as pd
def analyse(df):
'''analyse.'''
result_df = df.groupby(['plasmid',
'strain',
'trea... | mit |
keras-team/keras-tuner | setup.py | 1 | 2018 | # Copyright 2019 The Keras Tuner Authors
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... | apache-2.0 |
trankmichael/scikit-learn | sklearn/utils/setup.py | 296 | 2884 | import os
from os.path import join
from sklearn._build_utils import get_blas_info
def configuration(parent_package='', top_path=None):
import numpy
from numpy.distutils.misc_util import Configuration
config = Configuration('utils', parent_package, top_path)
config.add_subpackage('sparsetools')
... | bsd-3-clause |
Averroes/statsmodels | statsmodels/sandbox/tests/test_predict_functional.py | 29 | 12873 | from statsmodels.sandbox.predict_functional import predict_functional
import numpy as np
import pandas as pd
import statsmodels.api as sm
from numpy.testing import dec
# If true, the output is written to a multi-page pdf file.
pdf_output = False
try:
import matplotlib.pyplot as plt
import matplotlib
have_... | bsd-3-clause |
myuuuuun/various | ContinuousAlgorithm/HW3/HW3-1.py | 2 | 4385 | #-*- encoding: utf-8 -*-
"""
solve ordinary differential equations
Copyright (c) 2016 @myuuuuun
Released under the MIT license.
"""
import math
import numpy as np
import pandas as pd
import functools
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.cm as cm
EPSIRON = 1.0e-8
np.set_printoption... | mit |
mne-tools/mne-python | mne/io/fiff/tests/test_raw_fiff.py | 4 | 72663 | # -*- coding: utf-8 -*-
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Denis Engemann <denis.engemann@gmail.com>
#
# License: BSD (3-clause)
from copy import deepcopy
from functools import partial
from io import BytesIO
import os
import os.path as op
import pathlib
import pickle
import shutil
imp... | bsd-3-clause |
weixuanfu2016/tpot | tpot/config/classifier_sparse.py | 3 | 3726 | # -*- coding: utf-8 -*-
"""This file is part of the TPOT library.
TPOT was primarily developed at the University of Pennsylvania by:
- Randal S. Olson (rso@randalolson.com)
- Weixuan Fu (weixuanf@upenn.edu)
- Daniel Angell (dpa34@drexel.edu)
- and many more generous open source contributors
TPOT is f... | lgpl-3.0 |
richardliaw/ray | rllib/contrib/bandits/examples/LinTS_train_wheel_env.py | 2 | 1504 | """ Example of using Linear Thompson Sampling on WheelBandit environment.
For more information on WheelBandit, see https://arxiv.org/abs/1802.09127 .
"""
import numpy as np
from matplotlib import pyplot as plt
from ray.rllib.contrib.bandits.agents import LinTSTrainer
from ray.rllib.contrib.bandits.envs import Whee... | apache-2.0 |
ajayhk/quant | algos/contest_ph_bup1_sup5_nofundamentals.py | 1 | 13111 | """
Trading Strategy using Fundamental Data
1. Take list of only pharma stocks
2. Finalize number of stocks to track and buy
3. Buy the stock if it is showing potential of rising. Buy if it is 1% more than last 5 minute's price
4. Sell the stock if it rises 5% above the cost price
5. Dont b... | apache-2.0 |
wvangeit/AllenSDK | allensdk/test/api/cache_tests.py | 1 | 2559 | import unittest
from mock import MagicMock
from allensdk.api.cache import Cache
from allensdk.api.queries.rma_api import RmaApi
import allensdk.core.json_utilities as ju
import pandas as pd
import pandas.io.json as pj
class CacheTests(unittest.TestCase):
def __init__(self, *args, **kwargs):
super(CacheTes... | gpl-3.0 |
stefanhenneking/mxnet | example/ssd/dataset/pycocotools/coco.py | 29 | 19564 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | apache-2.0 |
szaiser/pandas-qt | pandasqt/models/SupportedDtypes.py | 4 | 5656 | import numpy as np
from pandasqt.compat import QtCore
class SupportedDtypesTranslator(QtCore.QObject):
"""Represents all supported datatypes and the translations (i18n).
"""
def __init__(self, parent=None):
"""Constructs the object with the given parent.
Args:
parent (QtCore.Q... | mit |
aasensio/pyiacsun | pyiacsun/atlas/Delbouille73.py | 1 | 1381 | # cdiazbas@iac.es
def Delbouille73(ini, endi, atlasdir=None):
"""
Extract spectral data from the original disk-center
intensity atlas recorded at the Jungfraujoch Observatory:
Delbouille, Neven, Roland (1973)
Wavelength range: 3000 - 10.000 A
Wavelength step (visible): 0.002 A
... | mit |
Srisai85/scikit-learn | sklearn/metrics/scorer.py | 211 | 13141 | """
The :mod:`sklearn.metrics.scorer` submodule implements a flexible
interface for model selection and evaluation using
arbitrary score functions.
A scorer object is a callable that can be passed to
:class:`sklearn.grid_search.GridSearchCV` or
:func:`sklearn.cross_validation.cross_val_score` as the ``scoring`` parame... | bsd-3-clause |
valexandersaulys/airbnb_kaggle_contest | venv/lib/python3.4/site-packages/numpy/lib/recfunctions.py | 148 | 35012 | """
Collection of utilities to manipulate structured arrays.
Most of these functions were initially implemented by John Hunter for
matplotlib. They have been rewritten and extended for convenience.
"""
from __future__ import division, absolute_import, print_function
import sys
import itertools
import numpy as np
im... | gpl-2.0 |
leesavide/pythonista-docs | Documentation/matplotlib/mpl_examples/pylab_examples/fill_betweenx_demo.py | 12 | 1576 | import matplotlib.mlab as mlab
from matplotlib.pyplot import figure, show
import numpy as np
## Copy of fill_between.py but using fill_betweenx() instead.
x = np.arange(0.0, 2, 0.01)
y1 = np.sin(2*np.pi*x)
y2 = 1.2*np.sin(4*np.pi*x)
fig = figure()
ax1 = fig.add_subplot(311)
ax2 = fig.add_subplot(312, sharex=ax1)
ax3... | apache-2.0 |
calum-chamberlain/EQcorrscan | eqcorrscan/utils/plotting.py | 1 | 89233 | """
Utility code for most of the plots used as part of the EQcorrscan package.
:copyright:
EQcorrscan developers.
:license:
GNU Lesser General Public License, Version 3
(https://www.gnu.org/copyleft/lesser.html)
"""
import numpy as np
import logging
import datetime as dt
import copy
import os
import matp... | gpl-3.0 |
gph82/PyEMMA | pyemma/plots/markovtests.py | 1 | 5109 |
# This file is part of PyEMMA.
#
# Copyright (c) 2015, 2014 Computational Molecular Biology Group, Freie Universitaet Berlin (GER)
#
# PyEMMA is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation, either vers... | lgpl-3.0 |
andyraib/data-storage | python_scripts/env/lib/python3.6/site-packages/pandas/io/tests/parser/test_textreader.py | 7 | 12917 | # -*- coding: utf-8 -*-
"""
Tests the TextReader class in parsers.pyx, which
is integral to the C engine in parsers.py
"""
from pandas.compat import StringIO, BytesIO, map
from pandas import compat
import os
import sys
import nose
from numpy import nan
import numpy as np
from pandas import DataFrame
from pandas.io... | apache-2.0 |
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