repo_name stringlengths 7 90 | path stringlengths 5 191 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 976 581k | license stringclasses 15
values |
|---|---|---|---|---|---|
marquettecomputationalsocialscience/clusteredcrimemaps | individual_work/justin/app.py | 1 | 3056 | import json
import csv
from datetime import datetime
from flask import Flask, render_template, request
from sklearn.cluster import KMeans
import numpy as np
app = Flask(__name__)
previous_data = []
prev_bool = False
colors = ['#ff7800', '#42a1f4', '#0ad81f', '#d80909', '#c407c4', 'yellow', 'black', 'white', 'brown']... | mit |
geekboxzone/lollipop_external_blktrace | btt/btt_plot.py | 43 | 11282 | #! /usr/bin/env python
#
# btt_plot.py: Generate matplotlib plots for BTT generate data files
#
# (C) Copyright 2009 Hewlett-Packard Development Company, L.P.
#
# This program 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 So... | gpl-2.0 |
IvarsKarpics/mxcube | gui/__init__.py | 1 | 4094 | #
# Project: MXCuBE
# https://github.com/mxcube
#
# This file is part of MXCuBE software.
#
# MXCuBE 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 of the License, or
# (at your... | lgpl-3.0 |
IssamLaradji/scikit-learn | sklearn/datasets/base.py | 12 | 17971 | """
Base IO code for all datasets
"""
# Copyright (c) 2007 David Cournapeau <cournape@gmail.com>
# 2010 Fabian Pedregosa <fabian.pedregosa@inria.fr>
# 2010 Olivier Grisel <olivier.grisel@ensta.org>
# License: BSD 3 clause
import os
import csv
import shutil
from os import environ
from os.pa... | bsd-3-clause |
DrSleep/tensorflow-deeplab-lfov | train.py | 1 | 6595 | """Training script for the DeepLab-LargeFOV network on the PASCAL VOC dataset
for semantic image segmentation.
This script trains the model using augmented PASCAL VOC dataset,
which contains approximately 10000 images for training and 1500 images for validation.
"""
from __future__ import print_function
import ar... | mit |
pprett/scikit-learn | sklearn/mixture/tests/test_gaussian_mixture.py | 19 | 40215 | # Author: Wei Xue <xuewei4d@gmail.com>
# Thierry Guillemot <thierry.guillemot.work@gmail.com>
# License: BSD 3 clauseimport warnings
import sys
import warnings
import numpy as np
from scipy import stats, linalg
from sklearn.covariance import EmpiricalCovariance
from sklearn.datasets.samples_generator import... | bsd-3-clause |
idoerg/BOA | src/plot/heatmap.py | 1 | 15741 | ###./imp.py deletedOrg /home/asmariyaz/Desktop/phylo_order /home/asmariyaz/Desktop/txtnames
import numpy as np
from matplotlib.colors import LinearSegmentedColormap
import matplotlib.pyplot as plt
import matplotlib as mpl
import matplotlib.cbook as cbook
from matplotlib._png import read_png
from matplotlib.offsetbox im... | gpl-3.0 |
asurve/incubator-systemml | projects/breast_cancer/breastcancer/preprocessing.py | 15 | 26035 | #-------------------------------------------------------------
#
# 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... | apache-2.0 |
jaganadhg/kaggle-rest-rev | src/latest.py | 1 | 20154 | #!/usr/bin/env python
from datetime import datetime, timedelta
from datetime import date
import numpy as np
import pandas as pd
from sklearn.ensemble import GradientBoostingRegressor, RandomForestRegressor
from sklearn.grid_search import GridSearchCV
from sklearn.metrics import r2_score, mean_squared_error
from skl... | bsd-3-clause |
alephu5/Soundbyte | environment/lib/python3.3/site-packages/pandas/sparse/panel.py | 1 | 18412 | """
Data structures for sparse float data. Life is made simpler by dealing only
with float64 data
"""
# pylint: disable=E1101,E1103,W0231
from pandas.compat import range, lrange, zip
from pandas import compat
import numpy as np
from pandas.core.index import Index, MultiIndex, _ensure_index
from pandas.core.frame imp... | gpl-3.0 |
esa/pykep | pykep/pontryagin/_leg.py | 2 | 30828 | from pykep.pontryagin._dynamics import _dynamics
from pykep.core import MU_SUN, epoch, AU
from pykep.sims_flanagan import spacecraft, sc_state
from scipy.integrate import ode
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
class leg(object):
"""I... | gpl-3.0 |
rax85/tensorflow-stuff | 1_cnn/deprecated.gen_data.py | 1 | 2608 | #!/usr/bin/python3
##
# A data set generator for the convolutional neural network example. Yes it is probably easier
# to use a mnist data set from somewhere but where's the fun in that. Instead, generate a batch
# of images using system fonts.
##
import constants
import math
import os
import random
import string
fr... | apache-2.0 |
anurag313/scikit-learn | sklearn/covariance/graph_lasso_.py | 10 | 25820 | """GraphLasso: sparse inverse covariance estimation with an l1-penalized
estimator.
"""
# Author: Gael Varoquaux <gael.varoquaux@normalesup.org>
# License: BSD 3 clause
# Copyright: INRIA
import warnings
import operator
import sys
import time
import numpy as np
from scipy import linalg
from .empirical_covariance_ im... | bsd-3-clause |
supriyagarg/pydatalab | google/datalab/contrib/mlworkbench/_local_predict.py | 2 | 13549 | # Copyright 2017 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 agre... | apache-2.0 |
benschneider/sideprojects1 | FFT_filters/digFiltSim.py | 1 | 3506 | import numpy as np
import matplotlib.pyplot as plt
from numpy import pi, sin, cos
from scipy.constants import h, e
from scipy.constants import Boltzmann as k
import Gnuplot as gp
def LPfft(sinput, lpfreq, T):
Nlp = int(lpfreq*len(sinput)*T)
fftlp = np.fft.fft(sinput) # 0,1,2,3,-3,-2,-1
fftlp[Nlp+1:-Nlp] ... | gpl-2.0 |
jeffdonahue/voc-classification | src/train_cls.py | 1 | 6190 | from __future__ import division
from __future__ import print_function
# Train and evaluate a classification model for VOC2012
import argparse
import config
import numpy as np
parser = argparse.ArgumentParser(description='Train and evaluate a classification model for VOC')
# Model parameters
parser.add_argument('proto... | bsd-2-clause |
gregreen/bayestar | scripts/maptools.py | 1 | 43776 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# maptools.py
#
# Copyright 2013-2014 Greg Green <greg@greg-UX31A>
#
# This program 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 2 of ... | gpl-2.0 |
aminert/scikit-learn | examples/ensemble/plot_ensemble_oob.py | 259 | 3265 | """
=============================
OOB Errors for Random Forests
=============================
The ``RandomForestClassifier`` is trained using *bootstrap aggregation*, where
each new tree is fit from a bootstrap sample of the training observations
:math:`z_i = (x_i, y_i)`. The *out-of-bag* (OOB) error is the average er... | bsd-3-clause |
adamrvfisher/TechnicalAnalysisLibrary | NormChaikinOpt1.py | 1 | 4370 | # -*- coding: utf-8 -*-
"""
Created on Tue Apr 4 02:25:29 2017
@author: AmatVictoriaCuramIII
"""
import numpy as np
from pandas_datareader import data
import random as rand
import pandas as pd
empty = [] #reusable list
#set up desired number of datasets for different period analysis
dataset = pd.DataFra... | apache-2.0 |
olologin/scikit-learn | examples/linear_model/plot_sgd_weighted_samples.py | 344 | 1458 | """
=====================
SGD: Weighted samples
=====================
Plot decision function of a weighted dataset, where the size of points
is proportional to its weight.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from sklearn import linear_model
# we create 20 points
np.random.seed(0)
X ... | bsd-3-clause |
noxer-org/noxer | noxer/rnn.py | 1 | 10485 | """
Learning with networks that can process sequential data.
"""
from sklearn.base import ClassifierMixin, RegressorMixin, BaseEstimator, TransformerMixin
from sklearn.preprocessing import LabelEncoder, FunctionTransformer
from sklearn.metrics import accuracy_score
from sklearn.model_selection import train_test_split
... | mit |
CforED/Machine-Learning | sklearn/decomposition/tests/test_sparse_pca.py | 160 | 6028 | # Author: Vlad Niculae
# License: BSD 3 clause
import sys
import numpy as np
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import SkipTest
from sklearn.utils.testing import ass... | bsd-3-clause |
PatrickChrist/scikit-learn | examples/decomposition/plot_ica_blind_source_separation.py | 349 | 2228 | """
=====================================
Blind source separation using FastICA
=====================================
An example of estimating sources from noisy data.
:ref:`ICA` is used to estimate sources given noisy measurements.
Imagine 3 instruments playing simultaneously and 3 microphones
recording the mixed si... | bsd-3-clause |
dsm054/pandas | pandas/tests/groupby/test_transform.py | 1 | 28755 | """ test with the .transform """
import pytest
import numpy as np
import pandas as pd
from pandas.util import testing as tm
from pandas import Series, DataFrame, Timestamp, MultiIndex, concat, date_range
from pandas.core.dtypes.common import (
ensure_platform_int, is_timedelta64_dtype)
from pandas.compat import S... | bsd-3-clause |
bokeh/bokeh | bokeh/sampledata/periodic_table.py | 1 | 1972 | #-----------------------------------------------------------------------------
# Copyright (c) 2012 - 2021, Anaconda, Inc., and Bokeh Contributors.
# All rights reserved.
#
# The full license is in the file LICENSE.txt, distributed with this software.
#-------------------------------------------------------------------... | bsd-3-clause |
alexvmarch/atomic | exatomic/widgets/widget_df.py | 3 | 3074 | # -*- coding: utf-8 -*-
# Copyright (c) 2015-2018, Exa Analytics Development Team
# Distributed under the terms of the Apache License 2.0
"""
A dataframe widget
#########################
A generic pandas dataframe widget.
"""
import pandas as pd
from ipywidgets import Box, Dropdown, IntRangeSlider, SelectMultiple, Butt... | apache-2.0 |
programmdesign/checkmate | checkmate/tests/lib/git/test_repository.py | 1 | 3710 | """
This file is part of checkmate, a meta code checker written in Python.
Copyright (C) 2015 Andreas Dewes, QuantifiedCode UG
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as
published by the Free Software Foundation, either version 3... | agpl-3.0 |
gnieboer/tensorflow | tensorflow/examples/learn/wide_n_deep_tutorial.py | 29 | 8985 | # 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 |
IssamLaradji/scikit-learn | sklearn/tests/test_random_projection.py | 19 | 14015 | from __future__ import division
import numpy as np
import scipy.sparse as sp
from sklearn.metrics import euclidean_distances
from sklearn.random_projection import johnson_lindenstrauss_min_dim
from sklearn.random_projection import gaussian_random_matrix
from sklearn.random_projection import sparse_random_matrix
from... | bsd-3-clause |
andrewcbennett/iris | docs/iris/example_code/Meteorology/TEC.py | 12 | 1054 | """
Ionosphere space weather
========================
This space weather example plots a filled contour of rotated pole point
data with a shaded relief image underlay. The plot shows aggregated
vertical electron content in the ionosphere.
The plot exhibits an interesting outline effect due to excluding data
values be... | gpl-3.0 |
yavuzhan/carPricePrediction-ML | manipulating_sahibinden.py | 1 | 1324 | # -*- coding: utf-8 -*-
# manipulating the data for features are on a similar scale
import pandas as pd
data = pd.read_csv('C:\\Users\\Yavuzhan\\Desktop\\DataMining_codes\\sahibinden\\S_sahibinden.csv', index_col = False) # , index_col = False
df = pd.DataFrame(data)
#manipulating price
price_max = df.price.m... | gpl-3.0 |
ttm/oscEmRede | venv/share/doc/networkx-1.8.1/examples/drawing/giant_component.py | 10 | 2050 | #!/usr/bin/env python
"""
This example illustrates the sudden appearance of a
giant connected component in a binomial random graph.
Requires pygraphviz and matplotlib to draw.
"""
# Copyright (C) 2006-2008
# Aric Hagberg <hagberg@lanl.gov>
# Dan Schult <dschult@colgate.edu>
# Pieter Swart <swart@lanl.gov... | gpl-3.0 |
yl565/statsmodels | statsmodels/tsa/statespace/mlemodel.py | 1 | 113093 | """
State Space Model
Author: Chad Fulton
License: Simplified-BSD
"""
from __future__ import division, absolute_import, print_function
from statsmodels.compat.python import long
import numpy as np
import pandas as pd
from scipy.stats import norm
from .simulation_smoother import SimulationSmoother
from .kalman_smooth... | bsd-3-clause |
jklenzing/pysat | pysat/tests/test_custom.py | 2 | 13848 | import numpy as np
from nose.tools import raises
import pandas as pds
import pysat
class TestBasics():
def setup(self):
"""Runs before every method to create a clean testing setup."""
self.testInst = pysat.Instrument('pysat', 'testing', tag='10',
clean_le... | bsd-3-clause |
toastedcornflakes/scikit-learn | sklearn/linear_model/coordinate_descent.py | 2 | 81257 | # Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
# Olivier Grisel <olivier.grisel@ensta.org>
# Gael Varoquaux <gael.varoquaux@inria.fr>
#
# License: BSD 3 clause
import sys
import warnings
from abc import ABCMeta, abstractmethod
import n... | bsd-3-clause |
ChanderG/scikit-learn | sklearn/gaussian_process/tests/test_gaussian_process.py | 267 | 6813 | """
Testing for Gaussian Process module (sklearn.gaussian_process)
"""
# Author: Vincent Dubourg <vincent.dubourg@gmail.com>
# Licence: BSD 3 clause
from nose.tools import raises
from nose.tools import assert_true
import numpy as np
from sklearn.gaussian_process import GaussianProcess
from sklearn.gaussian_process ... | bsd-3-clause |
jakobworldpeace/scikit-learn | sklearn/ensemble/voting_classifier.py | 19 | 9888 | """
Soft Voting/Majority Rule classifier.
This module contains a Soft Voting/Majority Rule classifier for
classification estimators.
"""
# Authors: Sebastian Raschka <se.raschka@gmail.com>,
# Gilles Louppe <g.louppe@gmail.com>
#
# License: BSD 3 clause
import numpy as np
from ..base import BaseEstimator
f... | bsd-3-clause |
frank-tancf/scikit-learn | examples/cluster/plot_dbscan.py | 346 | 2479 | # -*- coding: utf-8 -*-
"""
===================================
Demo of DBSCAN clustering algorithm
===================================
Finds core samples of high density and expands clusters from them.
"""
print(__doc__)
import numpy as np
from sklearn.cluster import DBSCAN
from sklearn import metrics
from sklearn... | bsd-3-clause |
MITHyperloopTeam/software_core | software/simulation/sandbox/python/PodPlant.py | 1 | 14538 | #!/usr/bin/python
import time, math
import numpy as np
import matplotlib.pyplot as plt
import yaml
import scipy.ndimage as ndimage
#******************************************************************************
# Tube
# Manages simulation of tube environment.
#********************************************************... | lgpl-3.0 |
r9y9/librosa | docs/examples/plot_presets.py | 3 | 3179 | # coding: utf-8
"""
=======
Presets
=======
This notebook demonstrates how to use the `presets` package to change the
default parameters for librosa.
"""
# Code source: Brian McFee
# License: ISC
##################################################
# We'll need numpy and matplotlib for this example
from __future__ imp... | isc |
datapythonista/pandas | pandas/tests/frame/methods/test_is_homogeneous_dtype.py | 4 | 1422 | import numpy as np
import pytest
import pandas.util._test_decorators as td
from pandas import (
Categorical,
DataFrame,
)
# _is_homogeneous_type always returns True for ArrayManager
pytestmark = td.skip_array_manager_invalid_test
@pytest.mark.parametrize(
"data, expected",
[
# empty
... | bsd-3-clause |
ndingwall/scikit-learn | sklearn/discriminant_analysis.py | 6 | 34470 | """
Linear Discriminant Analysis and Quadratic Discriminant Analysis
"""
# Authors: Clemens Brunner
# Martin Billinger
# Matthieu Perrot
# Mathieu Blondel
# License: BSD 3-Clause
import warnings
import numpy as np
from scipy import linalg
from scipy.special import expit
from .base import ... | bsd-3-clause |
PmagPy/PmagPy | pmagpy_tests/test_ipmag.py | 1 | 64648 | #!/usr/bin/env python
import unittest
import os
import sys
import re
import matplotlib
from matplotlib import pyplot as plt
import requests
import shutil
import random
import glob
import numpy as np
from pmagpy import pmag
from pmagpy import ipmag
from pmagpy import contribution_builder as cb
from pmagpy import conver... | bsd-3-clause |
MatthewRalston/ansible-cloudman-image | files/ipython_config.py | 15 | 14156 | # Configuration file for ipython.
c = get_config()
c.InteractiveShell.autoindent = True
c.InteractiveShell.colors = 'Linux'
c.InteractiveShell.confirm_exit = False
c.AliasManager.user_aliases = [
('ll', 'ls -l'),
('lt', 'ls -ltr'),
]
#------------------------------------------------------------------------------
#... | mit |
IBT-FMI/SAMRI | samri/utilities.py | 1 | 13239 | import multiprocessing as mp
import nibabel as nib
import nipype.interfaces.io as nio
import numpy as np
import os
import pandas as pd
from itertools import product
from joblib import Parallel, delayed
from os import path
# PyBIDS 0.6.5 and 0.10.2 compatibility
try:
from bids.grabbids import BIDSLayout
except ModuleNo... | gpl-3.0 |
e-q/scipy | scipy/integrate/_ivp/ivp.py | 21 | 27556 | import inspect
import numpy as np
from .bdf import BDF
from .radau import Radau
from .rk import RK23, RK45, DOP853
from .lsoda import LSODA
from scipy.optimize import OptimizeResult
from .common import EPS, OdeSolution
from .base import OdeSolver
METHODS = {'RK23': RK23,
'RK45': RK45,
'DOP853': ... | bsd-3-clause |
zfrenchee/pandas | pandas/io/pytables.py | 1 | 162222 | """
High level interface to PyTables for reading and writing pandas data structures
to disk
"""
# pylint: disable-msg=E1101,W0613,W0603
from datetime import datetime, date
import time
import re
import copy
import itertools
import warnings
import os
from pandas.core.dtypes.common import (
is_list_like,
is_cate... | bsd-3-clause |
petosegan/scikit-learn | doc/tutorial/text_analytics/solutions/exercise_01_language_train_model.py | 254 | 2253 | """Build a language detector model
The goal of this exercise is to train a linear classifier on text features
that represent sequences of up to 3 consecutive characters so as to be
recognize natural languages by using the frequencies of short character
sequences as 'fingerprints'.
"""
# Author: Olivier Grisel <olivie... | bsd-3-clause |
Anton04/IoT-kit | InfluxDBInterface.py | 1 | 15982 | #!/bin/python
from influxdb import InfluxDBClient
import json
import pandas as pd
import numpy
class InfluxDBlayer(InfluxDBClient):
def ProcessSeriesParameter(self,series):
#Handle indexing instead of name
if type(series) == int:
Series = self.ListSeries()
#Series.sort()
series =... | mit |
frank-tancf/scikit-learn | sklearn/metrics/cluster/tests/test_supervised.py | 41 | 8901 | import numpy as np
from sklearn.metrics.cluster import adjusted_rand_score
from sklearn.metrics.cluster import homogeneity_score
from sklearn.metrics.cluster import completeness_score
from sklearn.metrics.cluster import v_measure_score
from sklearn.metrics.cluster import homogeneity_completeness_v_measure
from sklearn... | bsd-3-clause |
billy-inn/scikit-learn | sklearn/ensemble/weight_boosting.py | 97 | 40773 | """Weight Boosting
This module contains weight boosting estimators for both classification and
regression.
The module structure is the following:
- The ``BaseWeightBoosting`` base class implements a common ``fit`` method
for all the estimators in the module. Regression and classification
only differ from each ot... | bsd-3-clause |
pm2111/Heart-Defibrillation-Project | python plotting 2/series_heatmaps.py | 1 | 1591 | import numpy as np
import matplotlib.pyplot as plt
import os
path = "/Users/petermarinov/msci project/plotting python 2/sequence of averaged frames light apd short sim/nu_0.2"
filenames = []
for f in os.listdir(path):
if not f.startswith('.'):
filenames.append(f)
horizontal = 100
total_... | mit |
zhuango/python | pandasLearning/lrModel_forCom_Q3.py | 2 | 2568 | import sklearn
from sklearn import linear_model
from sklearn import tree
from sklearn.datasets import load_iris
import pandas as pd
import numpy as np
from sklearn.metrics import accuracy_score
from sklearn import preprocessing
from sklearn import neural_network
def standard(tasks, attri):
scaler = preprocessing.S... | gpl-2.0 |
shirtsgroup/pygo | analysis/figure_generation/Fig8_plot_dGf_boot.py | 1 | 5649 | #!/usr/bin/python2.4
import numpy
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib
import cPickle
import optparse
import plot_dG_solution
import pdb
def read_boot(file):
f = open(file,'rb')
temp = cPickle.load(f)
X = cPickle.load(f)
dX = cPickle.load(f)
f.close()
re... | gpl-2.0 |
XuesongYang/end2end_dialog | BaselineModel.py | 1 | 20518 | # -*- coding: UTF-8 -*-
''' Baseline system using CRFtagger and SVM to perform NLU and SAP, respectively.
Training Process: training two models separately.
Test Process: raw text --> CRFtagger with lexical features --> user tag sequence
--> reshape into binary vecor --> OneVsRestClassifier(Li... | mit |
dilawar/moose-full | moose-examples/traub_2005/py/vclamptest.py | 2 | 4847 | # vclamptest.py ---
#
# Filename: vclamptest.py
# Description:
# Author:
# Maintainer:
# Created: Wed Feb 6 16:25:52 2013 (+0530)
# Version:
# Last-Updated: Tue Jun 11 17:30:34 2013 (+0530)
# By: subha
# Update #: 148
# URL:
# Keywords:
# Compatibility:
#
#
# Commentary:
#
# Set up a voltag... | gpl-2.0 |
valexandersaulys/airbnb_kaggle_contest | venv/lib/python3.4/site-packages/sklearn/kernel_approximation.py | 258 | 17973 | """
The :mod:`sklearn.kernel_approximation` module implements several
approximate kernel feature maps base on Fourier transforms.
"""
# Author: Andreas Mueller <amueller@ais.uni-bonn.de>
#
# License: BSD 3 clause
import warnings
import numpy as np
import scipy.sparse as sp
from scipy.linalg import svd
from .base im... | gpl-2.0 |
bleepr/bleepr-manage | modules/data_visualiser.py | 1 | 3926 | from __future__ import print_function
from operator import add
import csv
import numpy as np
import matplotlib as mpl
mpl.use('Agg') # Allows it to work without X server
import matplotlib.pyplot as plt
from scipy.misc import imread
class DataVisualiser(object):
def __init__(self):
return None
def get... | mit |
azvoleff/chitwanabm | chitwanabm/runmodel.py | 1 | 21421 | #!/usr/bin/env python
# Copyright 2008-2013 Alex Zvoleff
#
# This file is part of the chitwanabm agent-based model.
#
# chitwanabm 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 of the Licen... | gpl-3.0 |
jaklinger/nesta_dataflow | collect_data/utils/common/browser.py | 1 | 3506 | '''
browser
-------
'''
import logging
import pandas as pd
from pyvirtualdisplay import Display
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions
from utils.common.timer import t... | mit |
sdsc/xsede_stats | tacc_stats/analysis/plot/masterplot.py | 1 | 7750 | import sys
from plots import Plot
from tacc_stats.analysis.gen import tspl_utils
from matplotlib.figure import Figure
import numpy
class MasterPlot(Plot):
k1={'amd64' :
['amd64_core','amd64_core','amd64_sock','lnet','lnet',
'ib_sw','ib_sw','cpu'],
'intel_pmc3' : ['intel_pmc3', 'intel_pmc3', 'inte... | lgpl-2.1 |
carlosmccosta/robot_localization_tools | scripts/path_plotter_3d.py | 2 | 8406 | #!/usr/bin/env python
# coding=UTF-8
import argparse
import ntpath
import sys
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as tk
from mpl_toolkits.mplot3d import axis3d
from math import atan2, asin
from numpy import rad2deg
def str2bool(v):
return v.lower() in ("yes", "true", "t", ... | bsd-3-clause |
ch3ll0v3k/scikit-learn | sklearn/feature_extraction/hashing.py | 183 | 6155 | # Author: Lars Buitinck <L.J.Buitinck@uva.nl>
# License: BSD 3 clause
import numbers
import numpy as np
import scipy.sparse as sp
from . import _hashing
from ..base import BaseEstimator, TransformerMixin
def _iteritems(d):
"""Like d.iteritems, but accepts any collections.Mapping."""
return d.iteritems() if... | bsd-3-clause |
jreback/pandas | pandas/tests/indexes/base_class/test_setops.py | 2 | 8588 | from datetime import datetime
import numpy as np
import pytest
import pandas as pd
from pandas import Index, Series
import pandas._testing as tm
from pandas.core.algorithms import safe_sort
class TestIndexSetOps:
@pytest.mark.parametrize(
"method", ["union", "intersection", "difference", "symmetric_diff... | bsd-3-clause |
ky822/Data_Bootcamp | Code/Python/imf_weo_all.py | 2 | 1562 | """
Messing around with the IMF's WEO dataset. The first section is an exploration
of various methods of reading data from a url.
Once we've read in the data, we can slice as needed.
Note: data file is labeled xls but it's really tab-delimited text.
Prepared for the NYU Course "Data Bootcamp."
More at https... | mit |
ambikeshwar1991/gnuradio-3.7.4 | gr-filter/examples/synth_filter.py | 58 | 2552 | #!/usr/bin/env python
#
# Copyright 2010,2012,2013 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 ... | gpl-3.0 |
AndersenLab/cegwas-web | base/views/tools/indel_primer.py | 2 | 11500 | import io
import re
import json
import tabix
import arrow
import requests
import numpy as np
import pandas as pd
from cyvcf2 import VCF
from flask import (Blueprint,
jsonify,
render_template,
request,
abort,
Response)
from fl... | mit |
sdrogers/ms2ldaviz | ms2ldaviz/compute_pca.py | 1 | 1576 | import os
import pickle
import numpy as np
import sys
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "ms2ldaviz.settings")
import django
django.setup()
from sklearn.decomposition import PCA
import jsonpickle
from basicviz.models import MultiFileExperiment,MultiLink,Experiment,Document,Feature,FeatureInstance,Mass2... | mit |
thirdwing/mxnet | example/autoencoder/data.py | 27 | 1272 | # 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 |
AlwaysLearningDeeper/Project | src/dqn/DQN_unstructuredMemory.py | 2 | 11776 | import gym,time,copy,re
import numpy as np
import tensorflow as tf
from matplotlib import pyplot as plt
import cv2
import matplotlib
from Replay_Memory import Replay_Memory
tf.logging.set_verbosity(tf.logging.INFO)
MEMORY_LENGTH = 4
ACTIONS = 4
LEARNING_RATE_SGD = 0.0001
LEARNING_RATE_RMSPROP = .0001
FINAL_EXPLORAT... | mit |
almarklein/bokeh | examples/charts/bar.py | 1 | 1383 | from collections import OrderedDict
import numpy as np
import pandas as pd
from bokeh.charts import Bar
from bokeh.plotting import output_file, show, VBox
from bokeh.sampledata.olympics2014 import data as original_data
data = {d['abbr']: d['medals'] for d in original_data['data'] if d['medals']['total'] > 0}
countr... | bsd-3-clause |
HopeFOAM/HopeFOAM | ThirdParty-0.1/ParaView-5.0.1/Applications/ParaView/Testing/Python/TestPythonViewMatplotlibScript.py | 1 | 1798 | # Set up a basic scene for rendering.
from paraview.simple import *
import os
import sys
script = """
import paraview.numpy_support
# Utility to get next color
def getNextColor():
colors = 'bgrcmykw'
for c in colors:
yield c
# This function must be defined. It is where specific data arrays are requested.
def... | gpl-3.0 |
QudevETH/PycQED_py3 | pycqed/analysis/multiplexed_RO_analysis.py | 1 | 11620 | # Based on Niels analysis
from os.path import join
from pycqed.analysis import measurement_analysis as ma
import numpy as np
import pylab
# %matplotlib inline
from matplotlib import pyplot as plt
from numpy.linalg import inv
def two_qubit_ssro_fidelity(label, fig_format='png',
qubit_labels... | mit |
eliben/deep-learning-samples | linear-regression/multiple_linear_regression.py | 1 | 9333 | # Example of solving multivariate linear regression in Python.
#
# Uses only Numpy, with Matplotlib for plotting.
#
# Eli Bendersky (http://eli.thegreenplace.net)
# This code is in the public domain
from __future__ import print_function
import csv
import matplotlib.pyplot as plt
import numpy as np
from timer import Ti... | unlicense |
GbalsaC/bitnamiP | venv/lib/python2.7/site-packages/numpy/lib/npyio.py | 6 | 63502 | __all__ = ['savetxt', 'loadtxt', 'genfromtxt', 'ndfromtxt', 'mafromtxt',
'recfromtxt', 'recfromcsv', 'load', 'loads', 'save', 'savez',
'savez_compressed', 'packbits', 'unpackbits', 'fromregex', 'DataSource']
import numpy as np
import format
import sys
import os
import sys
import itertools
import ... | agpl-3.0 |
Vvucinic/Wander | venv_2_7/lib/python2.7/site-packages/pandas/io/tests/test_stata.py | 9 | 46598 | # -*- coding: utf-8 -*-
# pylint: disable=E1101
from datetime import datetime
import datetime as dt
import os
import warnings
import nose
import struct
import sys
from distutils.version import LooseVersion
import numpy as np
import pandas as pd
from pandas.compat import iterkeys
from pandas.core.frame import DataFra... | artistic-2.0 |
bobflagg/sentiment-analysis | fsa/etl/etl.py | 1 | 3683 | # -*- coding: utf-8 -*-
"""
Created on Tue Dec 13 17:08:34 2016
@author: birksworks
"""
import os
import pandas as pd
import pyprind
SOURCE_DIRECTORY = '/home/code/nlp/sentiment-analysis-text-classification/text_convnet/data'
TARGET_DIRECTORY = '/home/code/nlp/sentiment-analysis-text-classification/sentiment-analysi... | gpl-3.0 |
bzero/statsmodels | statsmodels/graphics/tests/test_mosaicplot.py | 17 | 18878 | from __future__ import division
from statsmodels.compat.python import iterkeys, zip, lrange, iteritems, range
from numpy.testing import assert_, assert_raises, dec
from numpy.testing import run_module_suite
# utilities for the tests
from statsmodels.compat.collections import OrderedDict
from statsmodels.api import d... | bsd-3-clause |
uglyboxer/linear_neuron | net-p3/lib/python3.5/site-packages/matplotlib/backends/backend_agg.py | 10 | 21106 | """
An agg http://antigrain.com/ backend
Features that are implemented
* capstyles and join styles
* dashes
* linewidth
* lines, rectangles, ellipses
* clipping to a rectangle
* output to RGBA and PNG, optionally JPEG and TIFF
* alpha blending
* DPI scaling properly - everything scales properly (dashes, linew... | mit |
MohammedWasim/scikit-learn | examples/cluster/plot_feature_agglomeration_vs_univariate_selection.py | 218 | 3893 | """
==============================================
Feature agglomeration vs. univariate selection
==============================================
This example compares 2 dimensionality reduction strategies:
- univariate feature selection with Anova
- feature agglomeration with Ward hierarchical clustering
Both metho... | bsd-3-clause |
2039/skule | Project 1 - Problem 1 d.py | 1 | 3654 | import numpy as np
import math as m
import matplotlib.pyplot as plt
#N signifies the number of candidates interviewed.
N = range(16,45+1)
#The optimal cutoff point is 11 because the expected value of N is 30, given N is uniformly distributed.
#K = range(1,15+1)
#The computed optimal value for k was 10.
K = range(10,... | mit |
jswanljung/iris | lib/iris/symbols.py | 16 | 7823 | # (C) British Crown Copyright 2010 - 2015, Met Office
#
# This file is part of Iris.
#
# Iris 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 of the License, or
# (at your option) any l... | lgpl-3.0 |
rbrecheisen/pyminer | pyminer/network/selectors.py | 1 | 3162 | __author__ = 'Ralph'
import pandas as pd
from base import Node
from base import InputPort
from base import OutputPort
class Selector(Node):
def __init__(self, name):
super(Selector, self).__init__(name)
self.add_input_port(
InputPort(name='input', data_type=pd.DataFrame))
s... | apache-2.0 |
bundgus/python-playground | matplotlib-playground/examples/pylab_examples/centered_ticklabels.py | 2 | 1674 | # sometimes it is nice to have ticklabels centered. mpl currently
# associates a label with a tick, and the label can be aligned
# 'center', 'left', or 'right' using the horizontal alignment property:
#
#
# for label in ax.xaxis.get_xticklabels():
# label.set_horizontalalignment('right')
#
#
# but this doesn't... | mit |
YzPaul3/h2o-3 | py2/testdir_single_jvm/test_GLM_hastie_shuffle.py | 20 | 5925 | import unittest, time, sys, random, copy
sys.path.extend(['.','..','../..','py'])
import h2o2 as h2o
import h2o_cmd, h2o_import as h2i, h2o_jobs, h2o_glm, h2o_util
from h2o_test import verboseprint, dump_json, OutputObj
# Dataset created from this:
# Elements of Statistical Learning 2nd Ed.; Hastie, Tibshirani, Friedm... | apache-2.0 |
OGGM/oggm | oggm/core/centerlines.py | 2 | 80871 | """ Compute the centerlines according to Kienholz et al (2014) - with
modifications.
The output is a list of Centerline objects, stored as a list in a pickle.
The order of the list is important since the lines are
sorted per order (hydrological flow level), from the lower orders (upstream)
to the higher orders (downst... | bsd-3-clause |
shoyer/xarray | xarray/tests/__init__.py | 1 | 5117 | import importlib
import platform
import re
import warnings
from contextlib import contextmanager
from distutils import version
from unittest import mock # noqa: F401
import numpy as np
import pytest
from numpy.testing import assert_array_equal # noqa: F401
from pandas.testing import assert_frame_equal # noqa: F401
... | apache-2.0 |
kesre/slask | plugins/gif.py | 2 | 2392 | """!gif <search term> return a random result from the google gif search result for <search term>"""
from urllib import quote
import re
import requests
from random import randint, choice, shuffle
def gif(searchterm_raw):
# There's a chance of pandas today
eggs = ['panda', 'nick cage']
if randint(0, 100) ... | mit |
mgahsan/QuantEcon.py | examples/optgrowth_v0.py | 7 | 2024 | """
Filename: optgrowth_v0.py
Authors: John Stachurski and Thomas Sargent
A first pass at solving the optimal growth problem via value function
iteration. A more general version is provided in optgrowth.py.
"""
from __future__ import division # Omit for Python 3.x
import matplotlib.pyplot as plt
import numpy as np
... | bsd-3-clause |
BorisJeremic/Real-ESSI-Examples | analytic_solution/test_cases/Contact/Interface_Mesh_Types/Interface_1/HardContact_NonLinHardShear/Interface_Test_Normal_Plot.py | 30 | 2779 | #!/usr/bin/python
import h5py
import matplotlib.pylab as plt
import matplotlib as mpl
import sys
import numpy as np;
import matplotlib;
import math;
from matplotlib.ticker import MaxNLocator
plt.rcParams.update({'font.size': 28})
# set tick width
mpl.rcParams['xtick.major.size'] = 10
mpl.rcParams['xtick.major.width']... | cc0-1.0 |
alephu5/Soundbyte | environment/lib/python3.3/site-packages/pandas/stats/interface.py | 2 | 4506 | from pandas.core.api import Series, DataFrame, Panel, MultiIndex
from pandas.stats.ols import OLS, MovingOLS
from pandas.stats.plm import PanelOLS, MovingPanelOLS, NonPooledPanelOLS
import pandas.stats.common as common
def ols(**kwargs):
"""Returns the appropriate OLS object depending on whether you need
simp... | gpl-3.0 |
nelango/ViralityAnalysis | model/lib/sklearn/neighbors/graph.py | 208 | 7031 | """Nearest Neighbors graph functions"""
# Author: Jake Vanderplas <vanderplas@astro.washington.edu>
#
# License: BSD 3 clause (C) INRIA, University of Amsterdam
import warnings
from .base import KNeighborsMixin, RadiusNeighborsMixin
from .unsupervised import NearestNeighbors
def _check_params(X, metric, p, metric_... | mit |
kjs73/pele | playground/hs_wca_cell_lists/hs_wca_cell_lists.py | 5 | 21971 | from __future__ import division
import numpy as np
from pele.potentials import HS_WCA
from pele.optimize import ModifiedFireCPP, LBFGS_CPP
import time
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
import matplotlib
from matplotlib.patches import Circle
import pylab
from scipy.o... | gpl-3.0 |
xzh86/scikit-learn | examples/ensemble/plot_adaboost_hastie_10_2.py | 355 | 3576 | """
=============================
Discrete versus Real AdaBoost
=============================
This example is based on Figure 10.2 from Hastie et al 2009 [1] and illustrates
the difference in performance between the discrete SAMME [2] boosting
algorithm and real SAMME.R boosting algorithm. Both algorithms are evaluate... | bsd-3-clause |
joergdietrich/astropy | astropy/visualization/wcsaxes/formatter_locator.py | 2 | 15163 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
from __future__ import print_function, division, absolute_import
# This file defines the AngleFormatterLocator class which is a class that
# provides both a method for a formatter and one for a locator, for a given
# label spacing. The advantage of keepi... | bsd-3-clause |
Achuth17/scikit-learn | sklearn/linear_model/tests/test_omp.py | 272 | 7752 | # Author: Vlad Niculae
# Licence: 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 |
Eric89GXL/mne-python | mne/utils/_testing.py | 4 | 18309 | # -*- coding: utf-8 -*-
"""Testing functions."""
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
#
# License: BSD (3-clause)
from contextlib import contextmanager
from distutils.version import LooseVersion
from functools import partial, wraps
import os
import inspect
from io import StringIO
from shutil imp... | bsd-3-clause |
anna-effeindzourou/trunk | examples/FluidCouplingPFV/drainage-2PFV-Yuan_and_Chareyre_2017.py | 2 | 5480 | # encoding: utf-8
# This script demonstrates a simple case of drainage simulation using the "2PFV" two-phase model implemented in UnsaturatedEngine.
# The script was used to generate the result and supplementary material (video) of [1]. The only difference is the problem size (40k particles in the paper vs. 1k (default... | gpl-2.0 |
ilri/azizi.ilri.org | freezerweb/cgi-bin/freezer_plot.py | 1 | 1511 | #!/usr/bin/env python
#import matplotlib functions and set it to output files instead of printing to an X window
import matplotlib
matplotlib.use('Agg')
from pylab import figure, show, xlabel, ylabel, title
from matplotlib.dates import HourLocator, MinuteLocator, DateFormatter
import sys
import cgi
#import our databa... | gpl-3.0 |
nwilming/ocupy | doc/conf.py | 1 | 7299 | # -*- coding: utf-8 -*-
#
# res.analysis documentation build configuration file, created by
# sphinx-quickstart on Wed Dec 22 16:29:57 2010.
#
# 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.
#
... | gpl-2.0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.