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 |
|---|---|---|---|---|---|
piotroxp/scibibscan | scib/lib/python3.5/site-packages/numpy/linalg/linalg.py | 32 | 75738 | """Lite version of scipy.linalg.
Notes
-----
This module is a lite version of the linalg.py module in SciPy which
contains high-level Python interface to the LAPACK library. The lite
version only accesses the following LAPACK functions: dgesv, zgesv,
dgeev, zgeev, dgesdd, zgesdd, dgelsd, zgelsd, dsyevd, zheevd, dgetr... | mit |
petosegan/scikit-learn | examples/linear_model/plot_bayesian_ridge.py | 248 | 2588 | """
=========================
Bayesian Ridge Regression
=========================
Computes a Bayesian Ridge Regression on a synthetic dataset.
See :ref:`bayesian_ridge_regression` for more information on the regressor.
Compared to the OLS (ordinary least squares) estimator, the coefficient
weights are slightly shift... | bsd-3-clause |
ZENGXH/scikit-learn | benchmarks/bench_mnist.py | 154 | 6006 | """
=======================
MNIST dataset benchmark
=======================
Benchmark on the MNIST dataset. The dataset comprises 70,000 samples
and 784 features. Here, we consider the task of predicting
10 classes - digits from 0 to 9 from their raw images. By contrast to the
covertype dataset, the feature space is... | bsd-3-clause |
lanceculnane/electricity-conservation | code/building_rf_mean.py | 1 | 1826 | import numpy as np
import pandas as pd
import datetime
from sklearn.ensemble import RandomForestRegressor
from sklearn.metrics import mean_squared_error
from sklearn.cross_validation import train_test_split
from sklearn.preprocessing import Imputer
full_pre = pd.read_csv("buildingfull.csv")
# full_pre.fillna(0, inpla... | gpl-3.0 |
ryfeus/lambda-packs | LightGBM_sklearn_scipy_numpy/source/sklearn/metrics/cluster/supervised.py | 13 | 31406 | """Utilities to evaluate the clustering performance of models.
Functions named as *_score return a scalar value to maximize: the higher the
better.
"""
# Authors: Olivier Grisel <olivier.grisel@ensta.org>
# Wei LI <kuantkid@gmail.com>
# Diego Molla <dmolla-aliod@gmail.com>
# Arnaud Fouchet ... | mit |
wukan1986/kquant_data | demo_stock/B_5min_000016/E03_merge_000905.py | 1 | 2775 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
指定数据目录，生成对应的合约行业数据
分为两种
1. 全市场数据，将部分标记上权重
2. 只对历史上成为成份股的，进行处理，由于前面已经转换了数据，这里只要跳选数据并处理即可
"""
import os
import pandas as pd
from kquant_data.config import __CONFIG_H5_STK_WEIGHT_DIR__, __CONFIG_H5_STK_DIR__, __CONFIG_TDX_STK_DIR__, \
__CONFIG_H5_STK_DIVIDEND_DIR__
... | bsd-2-clause |
NikitaRzm/ivs-lab | src/modules/Kalman/model/kalman.py | 1 | 2418 | import numpy as np
import matplotlib.pyplot as plt
# https://ru.wikipedia.org/wiki/%D0%A4%D0%B8%D0%BB%D1%8C%D1%82%D1%80_%D0%9A%D0%B0%D0%BB%D0%BC%D0%B0%D0%BD%D0%B0
def kalman(
x, P, measurement, R,
motion=np.matrix('0. 0. 0. 0.').T,
Q=np.matrix(np.eye(4)),
F=np.matrix('''
1. 0. 1. 0.;
0. 1... | mit |
stanford-gfx/Horus | Code/flashlight/quadrotorcamera3d.py | 1 | 16189 | from pylab import *
import sklearn
import sklearn.preprocessing
import transformations
import linalgutils
import trigutils
import sympy
import sympy.matrices
import sympy.physics
import sympy.physics.mechanics
import sympy.physics.mechanics.functions
import trigutils
import sympyutils
import pathutils
m = 1.0 ... | bsd-3-clause |
Alex-Ian-Hamilton/sunpy | sunpy/time/tests/test_time.py | 1 | 4400 | from __future__ import absolute_import, division, print_function
from datetime import datetime
from sunpy import time
from sunpy.time import parse_time
import numpy as np
import pandas
from sunpy.extern.six.moves import range
LANDING = datetime(1966, 2, 3)
def test_parse_time_24():
assert parse_time("2010-10-... | bsd-2-clause |
jakirkham/bokeh | examples/app/export_csv/main.py | 9 | 1472 | from os.path import dirname, join
import pandas as pd
from bokeh.layouts import row, widgetbox
from bokeh.models import ColumnDataSource, CustomJS
from bokeh.models.widgets import RangeSlider, Button, DataTable, TableColumn, NumberFormatter
from bokeh.io import curdoc
df = pd.read_csv(join(dirname(__file__), 'salary... | bsd-3-clause |
kenshay/ImageScripter | ProgramData/SystemFiles/Python/Lib/site-packages/matplotlib/_cm.py | 6 | 67361 | """
Nothing here but dictionaries for generating LinearSegmentedColormaps,
and a dictionary of these dictionaries.
Documentation for each is in pyplot.colormaps(). Please update this
with the purpose and type of your colormap if you add data for one here.
"""
from __future__ import (absolute_import, division, print_... | gpl-3.0 |
johnmgregoire/JCAPRamanDataProcess | PlateAlignViaEdge_v1.py | 1 | 12112 | import sys,os, pickle, numpy, pylab, operator
import cv2
from shutil import copy as copyfile
from PyQt4.QtCore import *
from PyQt4.QtGui import *
import matplotlib.pyplot as plt
from DataParseApp import dataparseDialog
from sklearn.decomposition import NMF
projectpath=os.path.split(os.path.abspath(__file__))[0]
sys.pa... | bsd-3-clause |
deepnarainsingh/data-science-from-scratch | code/recommender_systems.py | 60 | 6291 | from __future__ import division
import math, random
from collections import defaultdict, Counter
from linear_algebra import dot
users_interests = [
["Hadoop", "Big Data", "HBase", "Java", "Spark", "Storm", "Cassandra"],
["NoSQL", "MongoDB", "Cassandra", "HBase", "Postgres"],
["Python", "scikit-learn", "sci... | unlicense |
vortex-ape/scikit-learn | sklearn/tests/test_discriminant_analysis.py | 4 | 13934 | import numpy as np
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert... | bsd-3-clause |
Nucleoos/condor-copasi | web_frontend/condor_copasi_db/views.py | 2 | 69192 | from django.shortcuts import render_to_response, redirect
import datetime, os, shutil, re, math
import logging
from django import forms
from django.db import IntegrityError
from django.contrib.auth.models import User
from django.contrib.auth import authenticate, login, logout
from django.http import HttpResponseRedire... | artistic-2.0 |
hainm/statsmodels | statsmodels/examples/ex_regressionplots.py | 34 | 4457 | # -*- coding: utf-8 -*-
"""Examples for Regression Plots
Author: Josef Perktold
"""
from __future__ import print_function
import numpy as np
import statsmodels.api as sm
import matplotlib.pyplot as plt
from statsmodels.sandbox.regression.predstd import wls_prediction_std
import statsmodels.graphics.regressionplots ... | bsd-3-clause |
Vimos/scikit-learn | examples/semi_supervised/plot_label_propagation_structure.py | 55 | 2433 | """
==============================================
Label Propagation learning a complex structure
==============================================
Example of LabelPropagation learning a complex internal structure
to demonstrate "manifold learning". The outer circle should be
labeled "red" and the inner circle "blue". Be... | bsd-3-clause |
kaylanb/SkinApp | test_bootstrap/test_bootstrap.py | 1 | 1191 | from flask import Flask
from flask import render_template, flash, redirect
import numpy as np
#forms
# from flask.ext.wtf import Form
# from wtforms import TextField, SubmitField, TextAreaField, BooleanField, SelectField,SelectMultipleField
# from wtforms.validators import Required, Optional
#other
from pandas import r... | bsd-3-clause |
sanja7s/SR_Twitter | src_general/explain_bar_plot_edge_FORMATION_REL_SIMPLE.py | 1 | 4554 | #!/usr/bin/env python
# a bar plot with errorbars
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Ellipse, Polygon
from pylab import *
width = 0.37 # the width of the bars
font = {'family' : 'sans-serif',
'variant' : 'normal',
'weight' : 'light',
... | mit |
chrsrds/scikit-learn | benchmarks/bench_tsne_mnist.py | 4 | 6009 | """
=============================
MNIST dataset T-SNE benchmark
=============================
"""
# License: BSD 3 clause
import os
import os.path as op
from time import time
import numpy as np
import json
import argparse
from joblib import Memory
from sklearn.datasets import fetch_openml
from sklearn.manifold impo... | bsd-3-clause |
TheProgrammingDuck/Europa-Challenge | Site/WPSsite/SVM.py | 1 | 1518 | from sklearn.svm import SVC
from sklearn.externals import joblib
import numpy as np
class SVM:
def __init__(self):
pass
#self.X_train = X_train
#self.X_test = X_test
#self.y_train = y_train
#self.y_test = y_test
#self.classify()
def initialise(self, X_train, X_test, y_train, y_t... | mit |
SCP-028/UGA | methylation_model/TCGA_data.py | 1 | 6815 | #!python3
"""
Download methylation data from the GDC (TCGA) database. Only works on Linux machines
because `uvloop` is used for asynchronous downloading.
"""
import asyncio
import glob
import logging
import os
import re
import sys
import pandas as pd
import requests
import aiohttp
import uvloop
ROOTPATH = os.path.di... | apache-2.0 |
RobertABT/heightmap | build/matplotlib/lib/mpl_toolkits/mplot3d/axes3d.py | 4 | 83550 | #!/usr/bin/python
# axes3d.py, original mplot3d version by John Porter
# Created: 23 Sep 2005
# Parts fixed by Reinier Heeres <reinier@heeres.eu>
# Minor additions by Ben Axelrod <baxelrod@coroware.com>
# Significant updates and revisions by Ben Root <ben.v.root@gmail.com>
"""
Module containing Axes3D, an object which... | mit |
johndpope/tensorflow | tensorflow/python/estimator/inputs/pandas_io_test.py | 89 | 8340 | # Copyright 2015 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 |
jpautom/scikit-learn | sklearn/model_selection/_split.py | 7 | 55305 | """
The :mod:`sklearn.model_selection._split` module includes classes and
functions to split the data based on a preset strategy.
"""
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>,
# Gael Varoquaux <gael.varoquaux@normalesup.org>,
# Olivier Girsel <olivier.grisel@ensta.org>
# Ragha... | bsd-3-clause |
elendiastarman/jaw-tracking | jawTracking_consistentPointOrdering.py | 1 | 15768 | import numpy as np
import matplotlib.pyplot as plt
from math import sqrt, cos, sin, pi, copysign
from time import clock
from copy import deepcopy
class Blob:
def __init__(self,x,y,r):
self.x = x
self.y = y
self.r = r
self.path = [(x,y)]
def addToPath(self,nx,ny):
... | mit |
StudTeam6/competition | sw/airborne/test/math/compare_utm_enu.py | 77 | 2714 | #!/usr/bin/env python
from __future__ import division, print_function, absolute_import
import sys
import os
PPRZ_SRC = os.getenv("PAPARAZZI_SRC", "../../../..")
sys.path.append(PPRZ_SRC + "/sw/lib/python")
from pprz_math.geodetic import *
from pprz_math.algebra import DoubleRMat, DoubleEulers, DoubleVect3
from math ... | gpl-2.0 |
albertbup/DeepBeliefNet | dbn/tensorflow/models.py | 3 | 21558 | import atexit
from abc import ABCMeta
import numpy as np
import tensorflow as tf
from sklearn.base import ClassifierMixin, RegressorMixin
from ..models import AbstractSupervisedDBN as BaseAbstractSupervisedDBN
from ..models import BaseModel
from ..models import BinaryRBM as BaseBinaryRBM
from ..models import Unsuperv... | mit |
SXBK/kaggle | amazon/vgg_tsf.py | 1 | 3156 |
'''Transform Learning using vgg16 models
'''
from __future__ import absolute_import
from __future__ import print_function
from keras.preprocessing.image import ImageDataGenerator
from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation, Flatten, normalization
from keras.layers.advanced_a... | gpl-3.0 |
cbosoft/pyproflosim | main.py | 1 | 1534 | import matplotlib.pyplot as plt
import networkx as nx
from data import components
from colours import col
from process import Process, ProcessNode, NodeType, UnitType
from vis import draw
from chemical_component import ChemicalComponent
def main():
G = nx.DiGraph()
G.add_edge(0,1,
data={
... | gpl-3.0 |
jrbadiabo/Coursera-Stanford-ML-Class | Python_Version/Ex2.Logistic_Regression/ml.py | 1 | 2666 | import numpy as np
from matplotlib import pyplot as plt
from pandas import Series
from mpl_toolkits.mplot3d import axes3d
def plotData(X,y):
pos = X[np.where(y==1,True,False).flatten()]
neg = X[np.where(y==0,True,False).flatten()]
plt.plot(pos[:,0], pos[:,1], '+', markersize=7, markeredgecolor='black', ma... | mit |
nulman/REM | server/internals_db.py | 1 | 1787 | """
@editor: Liran Funaro <funaro@cs.technion.ac.il>
@author: Alex Nulman <anulman@cs.haifa.ac.il>
"""
import sqlite3
import os
from contextlib import closing
import pandas as pd
import json
class InternalsDB:
TABLE = '''CREATE TABLE IF NOT EXISTS "presets" (
`items` TEXT,
`json` ... | gpl-3.0 |
tclose/PyPe9 | pype9/cmd/plot.py | 2 | 1904 | """
Simple tool for plotting the output of PyPe9 simulations using Matplotlib_.
Since Pype9 output is stored in Neo_ format, it can be used to plot generic
Neo_ files but it also includes handling of Pype9-specific annotations, such as
regime transitions.
"""
from argparse import ArgumentParser
from pype9.utils.argumen... | mit |
andaag/scikit-learn | sklearn/cluster/birch.py | 207 | 22706 | # Authors: Manoj Kumar <manojkumarsivaraj334@gmail.com>
# Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Joel Nothman <joel.nothman@gmail.com>
# License: BSD 3 clause
from __future__ import division
import warnings
import numpy as np
from scipy import sparse
from math import sqrt
fro... | bsd-3-clause |
mmottahedi/neuralnilm_prototype | scripts/e491.py | 2 | 6823 | from __future__ import print_function, division
import matplotlib
import logging
from sys import stdout
matplotlib.use('Agg') # Must be before importing matplotlib.pyplot or pylab!
from neuralnilm import (Net, RealApplianceSource,
BLSTMLayer, DimshuffleLayer,
Bidirectiona... | mit |
kashif/scikit-learn | examples/linear_model/plot_logistic.py | 312 | 1426 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Logit function
=========================================================
Show in the plot is how the logistic regression would, in this
synthetic dataset, classify values as either 0 or 1,
i.e. class one or two, u... | bsd-3-clause |
gatieme/AderXCoding | technology/machine_learning/ID3/id3plot.py | 1 | 3306 | # -*- coding: utf-8 -*
# -*- coding: utf-8 -*-
'''
Created on 2015年7月27日
@author: pcithhb
'''
import matplotlib.pyplot as plt
decisionNode = dict(boxstyle="sawtooth", fc="0.8")
leafNode = dict(boxstyle="round4", fc="0.8")
arrow_args = dict(arrowstyle="<-")
#获取叶节点的数目
def getNumLeafs(myTree):
numLeafs = 0
fir... | gpl-2.0 |
aravindhv10/CPP_Wrappers | NewData/SRC/MXNET_VAE/START.py | 1 | 4386 | #!/usr/bin/python3
from __future__ import division, print_function, absolute_import
import numpy as np
import mxnet as mx
from mxnet import nd, autograd, gluon
from mxnet.gluon import nn
import matplotlib.pyplot as plt
import os
ctx = mx.cpu()
data_ctx = ctx
model_ctx = ctx
batch_size = 200
width=40
num_inputs = widt... | gpl-2.0 |
AdityaSoni19031997/Machine-Learning | kaggle/ieee_fraud_detection/src/aditya/2018_08_19_early_eda_experiments.py | 1 | 42777 |
# coding: utf-8
# In[853]:
# for C4, C6, C7, C8, C10 outliers, lookit cat variables to see if we can identify groupings...
#C8,c10 we can kinda tell, 0.51
# C12=0.553
# Hard winsorize:
traintr.loc[traintr.D4>484,'D4'] = 485
testtr.loc[testtr.D4>484,'D4'] = 485
data.loc[data.D4>484,'D4'] = np.nan
test_cvs(data, 'D... | mit |
francisco-dlp/hyperspy | doc/sphinxext/docscrape_sphinx.py | 11 | 7840 | import re
import inspect
import textwrap
import pydoc
import sphinx
from docscrape import NumpyDocString, FunctionDoc, ClassDoc
import collections
class SphinxDocString(NumpyDocString):
def __init__(self, docstring, config={}):
self.use_plots = config.get('use_plots', False)
NumpyDocString.__init... | gpl-3.0 |
Mixpap/MasterThesis | Notebooks/f.py | 1 | 14430 | import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
import matplotlib.gridspec as gridspec
import seaborn
#import yt
import pyPLUTO as pp
from astropy.io import ascii
import os
import sys
from ipywidgets import interactive, widgets,fixed
from IPython.display import Audio, display
import matplotl... | mit |
Vijaysai005/KProject | vijay/DBSCAN/dbscan.py | 1 | 5973 | # usr/bin/env python
# -*- coding: utf-8 -*-
"""
Created on Wed Jul 06 13:15:05 2017
@author: Vijayasai S
"""
# Use python3
import csv, time, numpy as np, pandas as pd, matplotlib.pyplot as plt
from sklearn.cluster import DBSCAN
from . import load_data
def loadData(filename, *args):
# Loading data from csv fil... | gpl-3.0 |
awanke/bokeh | bokeh/server/tests/config/test_blaze_config.py | 29 | 1202 | from __future__ import absolute_import
import numpy as np
import pandas as pd
qty=10000
gauss = {'oneA': np.random.randn(qty),
'oneB': np.random.randn(qty),
'cats': np.random.randint(0,5,size=qty),
'hundredA': np.random.randn(qty)*100,
'hundredB': np.random.randn(qty)*100}
gauss =... | bsd-3-clause |
tlhr/plumology | plumology/vis.py | 1 | 16471 | """vis - Visualisation and plotting tools"""
from typing import Union, Sequence, Optional, List, Tuple
import sys
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.collections import RegularPolyCollection
from matplotlib.colors import LinearSegmentedColormap, ListedColormap
from ... | mit |
akrherz/idep | scripts/plots/slope_histogram.py | 2 | 1337 | """Plot a histogram of slopes used in DEP"""
from __future__ import print_function
import os
import glob
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from pyiem.dep import read_slp
def read_data():
"""Do intensive stuff"""
os.chdir("/i/0/slp")
res = []
for huc8 in glob.glob(... | mit |
bigdataelephants/scikit-learn | examples/plot_multioutput_face_completion.py | 330 | 3019 | """
==============================================
Face completion with a multi-output estimators
==============================================
This example shows the use of multi-output estimator to complete images.
The goal is to predict the lower half of a face given its upper half.
The first column of images sho... | bsd-3-clause |
galad-loth/DescHash | AnchorGraphHash.py | 1 | 3513 | import numpy as npy
from sklearn.decomposition import PCA
from sklearn.cluster import KMeans
from LoadData import ReadFvecs
from Utils import KernelRBF, GetRetrivalMetric , GetKnnIdx, GetCompactCode
import pdb
def GetAnchorData(data, nAnchor, mode=0):
'''
Generate anchor data by random sampling or k... | apache-2.0 |
glennq/scikit-learn | examples/cluster/plot_face_segmentation.py | 71 | 2839 | """
===================================================
Segmenting the picture of a raccoon face in regions
===================================================
This example uses :ref:`spectral_clustering` on a graph created from
voxel-to-voxel difference on an image to break this image into multiple
partly-homogeneous... | bsd-3-clause |
e-q/scipy | scipy/cluster/hierarchy.py | 1 | 147998 | """
Hierarchical clustering (:mod:`scipy.cluster.hierarchy`)
========================================================
.. currentmodule:: scipy.cluster.hierarchy
These functions cut hierarchical clusterings into flat clusterings
or find the roots of the forest formed by a cut by providing the flat
cluster ids of each ... | bsd-3-clause |
emtpb/pyfds | setup.py | 1 | 1215 | from setuptools import setup
from os import path
here = path.abspath(path.dirname(__file__))
with open(path.join(here, 'README.rst')) as readme_file:
long_description = readme_file.read()
setup(
name='pyfds',
description='Modular field simulation tool using finite differences.',
long_description=long... | bsd-3-clause |
fspaolo/scikit-learn | examples/tree/plot_tree_regression_multioutput.py | 7 | 1768 | """
===================================================================
Multi-output Decision Tree Regression
===================================================================
An example to illustrate multi-output regression with decision tree.
The :ref:`decision trees <tree>`
is used to predict simultaneously the ... | bsd-3-clause |
emanuetre/crossmodal | SCM_experiment.py | 1 | 1971 | # Experiment to perform semantic correlation matching (SCM)
# take care of some imports
from scipy.io import loadmat
import numpy as np
from sklearn.metrics import label_ranking_average_precision_score, average_precision_score
from crossmodal import correlation_matching, semantic_matching
# read features data from... | isc |
chreman/isis-praktikum | sustainabilitylsa.py | 1 | 20232 | #
import string
import glob
import time
import xml.etree.ElementTree as ET
from itertools import chain
# Import reader
import xlrd
import csv
import requests
# Import data handlers
import collections
# Import Network Analysis Tools
import networkx as nx
import igraph as ig
# Import language processing tools
from g... | mit |
gt-ros-pkg/hrl-haptic-manip | hrl_fabric_based_tactile_sensor/src/hrl_fabric_based_tactile_sensor/tactile_sensor_model.py | 1 | 11343 | #!/usr/bin/python
# Charlie Kemp's initial attempt to model the force -> digital signal
# curves for a single taxel.
#
# + First version written on June 4, 2012.
# + Cleaned up, documented, and made minor edits June 5, 2012
import matplotlib.pylab as pl
def logistic(t):
return(1.0/(1.0 + pl.exp(-t)))
def norm... | apache-2.0 |
mgaillard/CNNFeaturesRobustness | features_extractor/image_features.py | 1 | 32581 | """
A class that extract features from images in a directory.
"""
from os import listdir
from os.path import isfile, join
from keras.preprocessing import image
from keras.models import Model
from keras.layers.pooling import GlobalAveragePooling2D, GlobalMaxPooling2D
import keras.applications.vgg16 as app_vgg16
import ... | gpl-3.0 |
elkingtonmcb/seldon-server | external/predictor/python/seldon/pipeline/pipelines.py | 5 | 11288 | import seldon.fileutil as fu
import json
from sklearn.externals import joblib
import os.path
import logging
import shutil
import unicodecsv
class Feature_transform(object):
"""Base feature transformation class with method defaults
"""
def __init__(self):
self.pos = 0
self.input_feature = "... | apache-2.0 |
saiwing-yeung/scikit-learn | sklearn/linear_model/tests/test_bayes.py | 299 | 1770 | # Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
#
# License: BSD 3 clause
import numpy as np
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import SkipTest
from sklearn.linear_model.bayes import BayesianRidge, ARDRegres... | bsd-3-clause |
f3r/scikit-learn | examples/text/hashing_vs_dict_vectorizer.py | 284 | 3265 | """
===========================================
FeatureHasher and DictVectorizer Comparison
===========================================
Compares FeatureHasher and DictVectorizer by using both to vectorize
text documents.
The example demonstrates syntax and speed only; it doesn't actually do
anything useful with the e... | bsd-3-clause |
StratsOn/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 |
biocore/American-Gut | americangut/plots.py | 5 | 4518 | #!/usr/bin/env python
from __future__ import division
import matplotlib.pyplot as plt
from matplotlib.font_manager import FontProperties
from numpy import cumsum, arange
__author__ = "Sam Way"
__copyright__ = "Copyright 2013, The American Gut Project"
__credits__ = ["Sam Way"]
__license__ = "BSD"
__version__ = "unve... | bsd-3-clause |
canaltinova/servo | tests/heartbeats/process_logs.py | 139 | 16143 | #!/usr/bin/env python
# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at http://mozilla.org/MPL/2.0/.
import argparse
import matplotlib.pyplot as plt
import numpy as np
import os
from os import path
... | mpl-2.0 |
yebrahim/pydatalab | google/datalab/data/_csv_file.py | 6 | 7141 | # Copyright 2016 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 agreed ... | apache-2.0 |
lukebarnard1/bokeh | examples/glyphs/colors.py | 25 | 8920 | from __future__ import print_function
from math import pi
import pandas as pd
from bokeh.models import Plot, ColumnDataSource, FactorRange, CategoricalAxis, TapTool, HoverTool, OpenURL
from bokeh.models.glyphs import Rect
from bokeh.document import Document
from bokeh.embed import file_html
from bokeh.resources impor... | bsd-3-clause |
mwv/scikit-learn | sklearn/datasets/samples_generator.py | 103 | 56423 | """
Generate samples of synthetic data sets.
"""
# Authors: B. Thirion, G. Varoquaux, A. Gramfort, V. Michel, O. Grisel,
# G. Louppe, J. Nothman
# License: BSD 3 clause
import numbers
import array
import numpy as np
from scipy import linalg
import scipy.sparse as sp
from ..preprocessing import MultiLabelBin... | bsd-3-clause |
zorroblue/scikit-learn | sklearn/linear_model/tests/test_huber.py | 26 | 7588 | # Authors: Manoj Kumar mks542@nyu.edu
# License: BSD 3 clause
import numpy as np
from scipy import optimize, sparse
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_a... | bsd-3-clause |
Aufuray/ross-sea-project | app/models/image_nd.py | 1 | 3950 | import os
import sys
import numpy as np
from matplotlib import pyplot as plt
from tools import data
class ImageND(object):
SENSOR = None
def __init__(self, filename, dimensions=3):
if dimensions < 3:
print "The image doesn't have the minimum of 3 dimensions"
sys.exit(1)
... | mit |
NixaSoftware/CVis | venv/lib/python2.7/site-packages/pandas/tests/io/formats/test_to_html.py | 2 | 48009 | # -*- coding: utf-8 -*-
import re
from textwrap import dedent
from datetime import datetime
from distutils.version import LooseVersion
import pytest
import numpy as np
import pandas as pd
from pandas import compat, DataFrame, MultiIndex, option_context, Index
from pandas.compat import u, lrange, StringIO
from pandas.... | apache-2.0 |
ctoher/pymatgen | pymatgen/analysis/diffraction/xrd.py | 2 | 14724 | # coding: utf-8
from __future__ import division, unicode_literals
"""
This module implements an XRD pattern calculator.
"""
from six.moves import filter
from six.moves import map
from six.moves import zip
__author__ = "Shyue Ping Ong"
__copyright__ = "Copyright 2012, The Materials Project"
__version__ = "0.1"
__mai... | mit |
kdebrab/pandas | pandas/tests/io/parser/na_values.py | 3 | 12848 | # -*- coding: utf-8 -*-
"""
Tests that NA values are properly handled during
parsing for all of the parsers defined in parsers.py
"""
import numpy as np
from numpy import nan
import pandas.io.common as com
import pandas.util.testing as tm
from pandas import DataFrame, Index, MultiIndex
from pandas.compat import Str... | bsd-3-clause |
ravindrapanda/tensorflow | tensorflow/examples/learn/iris_custom_model.py | 43 | 3449 | # 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 appl... | apache-2.0 |
krishauser/Klampt | Python/klampt/vis/colorize.py | 1 | 16675 | """Colorize an object to show heatmaps, false color images, etc.
"""
from OpenGL.raw.GL.VERSION.GL_1_1 import GL_NONE
from ..robotsim import *
from ..math import vectorops
try:
import numpy as np
except Exception:
HAVE_NUMPY = False
def colorize(object,value,colormap=None,feature=None,vrange=None,lighting=No... | bsd-3-clause |
aarora79/sitapt | sitapt/analyze/network_layer.py | 1 | 4309 | #!/usr/bin/env python
#title :network_layer.py
#description :Top level file for db module in the SITAPT package
#author :aarora79
#date :20151003
#version :0.1
#usage :python dbif.py
#notes :
#python_version :2.7.10
#========================================... | isc |
mwv/scikit-learn | examples/ensemble/plot_adaboost_regression.py | 311 | 1529 | """
======================================
Decision Tree Regression with AdaBoost
======================================
A decision tree is boosted using the AdaBoost.R2 [1] algorithm on a 1D
sinusoidal dataset with a small amount of Gaussian noise.
299 boosts (300 decision trees) is compared with a single decision tr... | bsd-3-clause |
DistrictDataLabs/intro-to-nltk | exercises/summarize.py | 3 | 3816 | # summarize
# Uses TFIDF to extract relevent sentences from text.
#
# Author: Benjamin Bengfort <benjamin@bengfort.com>
# Created: Sun Oct 26 16:06:36 2014 -0400
#
# ID: summarize.py [] benjamin@bengfort.com $
"""
Uses TFIDF to extract relevent sentences from text.
Based off of Charlie Greenbacker's example from "... | mit |
MatthieuBizien/scikit-learn | sklearn/linear_model/__init__.py | 83 | 3139 | """
The :mod:`sklearn.linear_model` module implements generalized linear models. It
includes Ridge regression, Bayesian Regression, Lasso and Elastic Net
estimators computed with Least Angle Regression and coordinate descent. It also
implements Stochastic Gradient Descent related algorithms.
"""
# See http://scikit-le... | bsd-3-clause |
lthurlow/Network-Grapher | proj/external/matplotlib-1.2.1/doc/mpl_examples/pylab_examples/image_masked.py | 12 | 1768 | #!/usr/bin/env python
'''imshow with masked array input and out-of-range colors.
The second subplot illustrates the use of BoundaryNorm to
get a filled contour effect.
'''
from pylab import *
from numpy import ma
import matplotlib.colors as colors
delta = 0.025
x = y = arange(-3.0, 3.0, delta)
X, Y = meshgri... | mit |
BoltzmannBrain/nupic.research | projects/sound_encoder/live_sound_encoding_demo.py | 12 | 2494 | #!/usr/bin/env python
# ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2015, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions ... | agpl-3.0 |
virneo/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/backends/backend_qt4.py | 69 | 20664 | from __future__ import division
import math
import os
import sys
import matplotlib
from matplotlib import verbose
from matplotlib.cbook import is_string_like, onetrue
from matplotlib.backend_bases import RendererBase, GraphicsContextBase, \
FigureManagerBase, FigureCanvasBase, NavigationToolbar2, IdleEvent, curso... | agpl-3.0 |
M-R-Houghton/euroscipy_2015 | 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... | mit |
wilsonianb/nacl_contracts | site_scons/site_tools/naclsdk.py | 2 | 26336 | #!/usr/bin/python
# Copyright (c) 2012 The Native Client Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
"""NaCl SDK tool SCons."""
import __builtin__
import re
import os
import shutil
import sys
import SCons.Scanner
import SCons.Scri... | bsd-3-clause |
jlegendary/scikit-learn | doc/conf.py | 210 | 8446 | # -*- coding: utf-8 -*-
#
# scikit-learn documentation build configuration file, created by
# sphinx-quickstart on Fri Jan 8 09:13:42 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.
... | bsd-3-clause |
anomam/pvlib-python | pvlib/tests/test_numerical_precision.py | 1 | 4290 | """
Test numerical precision of explicit single diode calculation using symbolic
mathematics. SymPy is a computer algebra system, that uses infinite precision
symbols instead of standard floating point and integer computer number types.
http://docs.sympy.org/latest/modules/evalf.html#accuracy-and-error-handling
This m... | bsd-3-clause |
kalvdans/scipy | scipy/stats/_multivariate.py | 12 | 112182 | #
# Author: Joris Vankerschaver 2013
#
from __future__ import division, print_function, absolute_import
import math
import numpy as np
import scipy.linalg
from scipy.misc import doccer
from scipy.special import gammaln, psi, multigammaln, xlogy, entr
from scipy._lib._util import check_random_state
from scipy.linalg.bl... | bsd-3-clause |
dropofwill/author-attr-experiments | multidoc_mnb.py | 1 | 3904 | from sklearn import datasets
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.cross_validation import train_test_split
from sklearn.cross_validation import cross_val_score
from sklearn.cross_validation import ShuffleSplit
from sklearn.... | unlicense |
imperial-genomics-facility/data-management-python | igf_data/utils/fileutils.py | 1 | 23415 | #!/usr/bin/env python
import pandas as pd
import os,subprocess,hashlib,string,re
import tarfile,fnmatch
from shlex import quote
from datetime import datetime
from dateutil.parser import parse
from tempfile import mkdtemp,gettempdir
from shutil import rmtree, move, copy2,copytree
def move_file(source_path,des... | apache-2.0 |
ambikeshwar1991/sandhi-2 | module/gr36/gr-filter/examples/fmtest.py | 12 | 7793 | #!/usr/bin/env python
#
# Copyright 2009,2012 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 |
caryan/PyBio | TnSeq/PySyntenyPlot.py | 1 | 4310 | # Copyright 2013 Colm Ryan colm@colmryan.org
# License GPL v3 (http://www.gnu.org/licenses/gpl.txt)
'''
Created on Jul 5, 2011
Do some arrow synteny plots for Veronica
@author: caryan
'''
from __future__ import division
#Let's write to SVG style graphics
#import matplotlib
#matplotlib.use('svg')
import matplotli... | gpl-3.0 |
teonlamont/mne-python | mne/decoding/tests/test_receptive_field.py | 2 | 21429 | # Authors: Chris Holdgraf <choldgraf@gmail.com>
#
# License: BSD (3-clause)
import os.path as op
import pytest
import numpy as np
from numpy.testing import assert_array_equal, assert_allclose, assert_equal
from mne import io, pick_types
from mne.fixes import einsum
from mne.utils import requires_version, run_tests_i... | bsd-3-clause |
vivekmishra1991/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 |
pianomania/scikit-learn | benchmarks/bench_plot_ward.py | 117 | 1283 | """
Benchmark scikit-learn's Ward implement compared to SciPy's
"""
import time
import numpy as np
from scipy.cluster import hierarchy
import matplotlib.pyplot as plt
from sklearn.cluster import AgglomerativeClustering
ward = AgglomerativeClustering(n_clusters=3, linkage='ward')
n_samples = np.logspace(.5, 3, 9)
n... | bsd-3-clause |
NINAnor/QGIS | python/plugins/processing/algs/qgis/QGISAlgorithmProvider.py | 1 | 10160 | # -*- coding: utf-8 -*-
"""
***************************************************************************
QGISAlgorithmProvider.py
---------------------
Date : December 2012
Copyright : (C) 2012 by Victor Olaya
Email : volayaf at gmail dot com
***************... | gpl-2.0 |
madscatt/zazzie | src/sassie/calculate/sascalc_pbc/scatteringCalc.py | 2 | 3946 | '''
Full exponential calculator.
This one takes only one pdb/dcd pair. Has the same inputs as debye.py
output is I[frame][Q] as a .npy file, which can be loaded with np.load
Also outputs Q_list.npy
O(num GV * N^2)
'''
from __future__ import division
import matplotlib.pyplot as plt
import numpy as np
import sasmol.sasmo... | gpl-3.0 |
Panchatantra/EQSignal | libeqs/eqspy.py | 1 | 7675 | from enum import Enum
from ctypes import POINTER, c_int, c_double, byref
from eqs_wrapper import libeqs
import numpy as np
import matplotlib.pyplot as plt
plt.style.use('ggplot')
def plotTH(t, acc, vel, dsp, title="Time History Curves"):
plt.figure(title,(8,6))
plt.subplot(3,1,1)
plt.plot(t,acc)
plt.... | mit |
jesse-norris/ml | lr/mclr.py | 1 | 4060 | import os, sys, time
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import minimize
### "ex3data1.csv" contains 5,000 samples of 401 element arrays
### These correspond to 20x20 pixel images (400 elements) and 1 classification
### The images are written numbers and the classifications ar... | gpl-3.0 |
dsm054/pandas | pandas/tests/frame/test_mutate_columns.py | 1 | 9750 | # -*- coding: utf-8 -*-
from __future__ import print_function
import pytest
from pandas.compat import range, lrange
import numpy as np
from pandas.compat import PY36
from pandas import DataFrame, Series, Index, MultiIndex
from pandas.util.testing import assert_frame_equal
import pandas.util.testing as tm
from pand... | bsd-3-clause |
edhuckle/statsmodels | statsmodels/datasets/tests/test_utils.py | 26 | 1697 | import os
import sys
from statsmodels.datasets import get_rdataset, webuse, check_internet
from numpy.testing import assert_, assert_array_equal, dec
cur_dir = os.path.dirname(os.path.abspath(__file__))
def test_get_rdataset():
# smoke test
if sys.version_info[0] >= 3:
#NOTE: there's no way to test bo... | bsd-3-clause |
Achuth17/scikit-learn | sklearn/feature_selection/tests/test_feature_select.py | 143 | 22295 | """
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 |
weissercn/MLTools | Dalitz_simplified/evaluation_of_optimised_classifiers/miranda_Dalitz/miranda_Dalitz_evaluation_of_optimised_classifiers.py | 1 | 4772 | import sys
sys.path.insert(0,'../..')
import classifier_eval_simplified
"""
This script can be used to get the p value for the Miranda method (=chi squared). It takes input files with column vectors corresponding to
features and lables.
"""
print(__doc__)
import sys
sys.path.insert(0,'../..')
import os
from scipy... | mit |
lucidfrontier45/scikit-learn | sklearn/utils/__init__.py | 2 | 9822 | """
The :mod:`sklearn.utils` module includes various utilites.
"""
import numpy as np
from scipy.sparse import issparse
import warnings
from .murmurhash import murmurhash3_32
from .validation import (as_float_array, check_arrays, safe_asarray,
assert_all_finite, array2d, atleast2d_or_csc,
... | bsd-3-clause |
potash/scikit-learn | examples/feature_stacker.py | 80 | 1911 | """
=================================================
Concatenating multiple feature extraction methods
=================================================
In many real-world examples, there are many ways to extract features from a
dataset. Often it is beneficial to combine several methods to obtain good
performance. Th... | bsd-3-clause |
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