repo_name stringlengths 7 92 | path stringlengths 5 149 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 911 693k | license stringclasses 15
values |
|---|---|---|---|---|---|
KECB/learn | computer_vision/12_rmv_salt_pepper_median_blur.py | 1 | 1464 | import numpy as np
import cv2
import matplotlib.pyplot as plt
# load in image and add Salt and pepper noise
moon = cv2.imread('images/moon.png', 0)
######################################################## ADD SALT & PEPPER NOISE
# salt and peppering manually (randomly assign coords as either white or black)
rows, col... | mit |
mop/LTPTextDetector | scripts/pw_analyze/svmdelme.py | 1 | 5600 | import numpy as np
from sklearn.cross_validation import cross_val_score, ShuffleSplit
from sklearn.svm import LinearSVC, SVC
from sklearn.grid_search import GridSearchCV
from sklearn.metrics import precision_recall_fscore_support
import matplotlib.pyplot as plt
data = np.genfromtxt('dists_cleaned.csv', delimiter=','... | gpl-3.0 |
vorasagar7/sp17-i524 | project/S17-IR-P001/code/ansible/ansible-node/files/visualization/FinalScript.py | 4 | 15339 | #Import the necessary methods from tweepy library
from tweepy.streaming import StreamListener
from tweepy import OAuthHandler
from tweepy import Stream
import json
import pandas as pd
from textblob import TextBlob
from time import strptime
import numpy as np
import re
import time
import zipcode
import sys, errno
from n... | apache-2.0 |
mikekestemont/ruzicka | code/04latin_test_o2.py | 1 | 3340 | from __future__ import print_function
import os
import time
import json
import pickle
import sys
from itertools import product, combinations
import matplotlib
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np
from sklearn.preprocessing import LabelEncoder
from ruzicka.util... | mit |
ndingwall/scikit-learn | sklearn/dummy.py | 5 | 21753 | # Author: Mathieu Blondel <mathieu@mblondel.org>
# Arnaud Joly <a.joly@ulg.ac.be>
# Maheshakya Wijewardena <maheshakya.10@cse.mrt.ac.lk>
# License: BSD 3 clause
import warnings
import numpy as np
import scipy.sparse as sp
from .base import BaseEstimator, ClassifierMixin, RegressorMixin
from .base impo... | bsd-3-clause |
yasirkhan380/Tutorials | notebooks/fig_code/svm_gui.py | 47 | 11549 | """
==========
Libsvm GUI
==========
A simple graphical frontend for Libsvm mainly intended for didactic
purposes. You can create data points by point and click and visualize
the decision region induced by different kernels and parameter settings.
To create positive examples click the left mouse button; to create
neg... | bsd-3-clause |
maxlikely/scikit-learn | sklearn/ensemble/tests/test_partial_dependence.py | 44 | 7031 | """
Testing for the partial dependence module.
"""
import numpy as np
from numpy.testing import assert_array_equal
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import if_matplotlib
from sklearn.ensemble.partial_dependence import partial_dependence
from sklearn.ensemble.partial_dependence... | bsd-3-clause |
hrjn/scikit-learn | examples/feature_selection/plot_f_test_vs_mi.py | 75 | 1647 | """
===========================================
Comparison of F-test and mutual information
===========================================
This example illustrates the differences between univariate F-test statistics
and mutual information.
We consider 3 features x_1, x_2, x_3 distributed uniformly over [0, 1], the
targ... | bsd-3-clause |
kushalbhola/MyStuff | Practice/PythonApplication/env/Lib/site-packages/pandas/tests/indexes/multi/test_contains.py | 2 | 3306 | import numpy as np
import pytest
from pandas.compat import PYPY
import pandas as pd
from pandas import MultiIndex
import pandas.util.testing as tm
def test_contains_top_level():
midx = MultiIndex.from_product([["A", "B"], [1, 2]])
assert "A" in midx
assert "A" not in midx._engine
def test_contains_wit... | apache-2.0 |
OpenTrading/OpenTrader | setup.py | 1 | 2533 | #!/usr/bin/env python
import codecs
import os
import sys
import glob
from setuptools import setup, find_packages
try:
# http://stackoverflow.com/questions/21698004/python-behave-integration-in-setuptools-setup-py
from setuptools_behave import behave_test
except ImportError:
behave_test = None
dirname = o... | lgpl-3.0 |
WangWenjun559/Weiss | summary/sumy/sklearn/feature_selection/rfe.py | 1 | 17079 | # Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Vincent Michel <vincent.michel@inria.fr>
# Gilles Louppe <g.louppe@gmail.com>
#
# License: BSD 3 clause
"""Recursive feature elimination for feature ranking"""
import warnings
import numpy as np
from ..utils import check_X_y, safe_sqr
fro... | apache-2.0 |
alekz112/statsmodels | docs/source/plots/graphics_gofplots_qqplot.py | 38 | 1911 | # -*- coding: utf-8 -*-
"""
Created on Sun May 06 05:32:15 2012
Author: Josef Perktold
editted by: Paul Hobson (2012-08-19)
"""
from scipy import stats
from matplotlib import pyplot as plt
import statsmodels.api as sm
#example from docstring
data = sm.datasets.longley.load()
data.exog = sm.add_constant(data.exog, pre... | bsd-3-clause |
Djabbz/scikit-learn | benchmarks/bench_plot_nmf.py | 90 | 5742 | """
Benchmarks of Non-Negative Matrix Factorization
"""
from __future__ import print_function
from collections import defaultdict
import gc
from time import time
import numpy as np
from scipy.linalg import norm
from sklearn.decomposition.nmf import NMF, _initialize_nmf
from sklearn.datasets.samples_generator import... | bsd-3-clause |
JeanKossaifi/scikit-learn | sklearn/datasets/lfw.py | 141 | 19372 | """Loader for the Labeled Faces in the Wild (LFW) dataset
This dataset is a collection of JPEG pictures of famous people collected
over the internet, all details are available on the official website:
http://vis-www.cs.umass.edu/lfw/
Each picture is centered on a single face. The typical task is called
Face Veri... | bsd-3-clause |
iainr/fridgid | Fridge.py | 1 | 9372 | import RPi.GPIO as GPIO
import datetime
import time
import pandas as pd
import logging
import logging.handlers
import sys
logger = logging.getLogger('fridge')
handler = logging.StreamHandler()
fHandler = logging.FileHandler('fridge.log')
formatter = logging.Formatter("%(asctime)s %(levelname)s %(message)s", "%Y-... | lgpl-3.0 |
ptkool/spark | python/pyspark/sql/tests/test_pandas_udf.py | 12 | 10115 | #
# 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 us... | apache-2.0 |
raghavrv/scikit-learn | examples/linear_model/plot_logistic.py | 73 | 1568 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Logistic function
=========================================================
Shown 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 tw... | bsd-3-clause |
perryjohnson/biplaneblade | sandia_blade_lib/prep_stn32_mesh.py | 1 | 10860 | """Write initial TrueGrid files for one Sandia blade station.
Usage
-----
start an IPython (qt)console with the pylab flag:
$ ipython qtconsole --pylab
or
$ ipython --pylab
Then, from the prompt, run this script:
|> %run sandia_blade_lib/prep_stnXX_mesh.py
or
|> import sandia_blade_lib/prep_stnXX_mesh
Au... | gpl-3.0 |
wilseypa/warped2-models | scripts/plotBags.py | 1 | 12059 | #!/usr/bin/python
# Calculates statistics and plots the bag metrics from raw data
from __future__ import print_function
import csv
import os, sys
import numpy as np
import scipy as sp
import scipy.stats as sps
import pandas as pd
import re, shutil, tempfile
import itertools, operator
import subprocess
import Gnuplot
... | mit |
kivy-garden/garden.matplotlib | backend_kivy.py | 1 | 50958 | '''
Backend Kivy
=====
.. image:: images/backend_kivy_example.jpg
:align: right
The :class:`FigureCanvasKivy` widget is used to create a matplotlib graph.
This widget has the same properties as
:class:`kivy.ext.mpl.backend_kivyagg.FigureCanvasKivyAgg`. FigureCanvasKivy
instead of rendering a static image, uses th... | mit |
buckiracer/data-science-from-scratch | dataScienceFromScratch/DataScienceFromScratch/visualizing_data.py | 58 | 5116 | import matplotlib.pyplot as plt
from collections import Counter
def make_chart_simple_line_chart(plt):
years = [1950, 1960, 1970, 1980, 1990, 2000, 2010]
gdp = [300.2, 543.3, 1075.9, 2862.5, 5979.6, 10289.7, 14958.3]
# create a line chart, years on x-axis, gdp on y-axis
plt.plot(years, gdp, color='gr... | unlicense |
stargaser/astropy | examples/io/split-jpeg-to-fits.py | 3 | 2472 | # -*- coding: utf-8 -*-
"""
=====================================================
Convert a 3-color image (JPG) to separate FITS images
=====================================================
This example opens an RGB JPEG image and writes out each channel as a separate
FITS (image) file.
This example uses `pillow <htt... | bsd-3-clause |
Averroes/statsmodels | statsmodels/tsa/statespace/tests/test_tools.py | 19 | 4268 | """
Tests for tools
Author: Chad Fulton
License: Simplified-BSD
"""
from __future__ import division, absolute_import, print_function
import numpy as np
import pandas as pd
from statsmodels.tsa.statespace import tools
# from .results import results_sarimax
from numpy.testing import (
assert_equal, assert_array_eq... | bsd-3-clause |
peckhams/topoflow | topoflow/components/met_base.py | 1 | 111479 |
## Does "land_surface_air__latent_heat_flux" make sense? (2/5/13)
# Copyright (c) 2001-2014, Scott D. Peckham
#
# Sep 2014. Fixed sign error in update_bulk_richardson_number().
# Ability to compute separate P_snow and P_rain.
# Aug 2014. New CSDMS Standard Names and clean up.
# Nov 2013. Con... | mit |
liebermeister/flux-enzyme-cost-minimization | scripts/monod_curve.py | 1 | 6430 | # -*- coding: utf-8 -*-
"""
Created on Wed Oct 1 2015
@author: noore
"""
import os
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import gridspec
from scipy.optimize import curve_fit
import definitions as D
import pandas as pd
#LOW_GLUCOSE = D.LOW_CONC['glucoseExt']
LOW_GLUCOSE = 1e-3 # in mM, i... | gpl-2.0 |
aminert/scikit-learn | sklearn/linear_model/logistic.py | 105 | 56686 | """
Logistic Regression
"""
# Author: Gael Varoquaux <gael.varoquaux@normalesup.org>
# Fabian Pedregosa <f@bianp.net>
# Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Manoj Kumar <manojkumarsivaraj334@gmail.com>
# Lars Buitinck
# Simon Wu <s8wu@uwaterloo.ca>
imp... | bsd-3-clause |
Vimos/scikit-learn | sklearn/kernel_approximation.py | 7 | 18505 | """
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... | bsd-3-clause |
pysb/pysb | pysb/examples/run_earm_hpp.py | 5 | 2377 | """ Run the Extrinsic Apoptosis Reaction Model (EARM) using BioNetGen's
Hybrid-Particle Population (HPP) algorithm.
NFsim provides stochastic simulation without reaction network generation,
allowing simulation of models with large (or infinite) reaction networks by
keeping track of species counts. However, it can fa... | bsd-2-clause |
MDAnalysis/mdanalysis | package/MDAnalysis/analysis/encore/dimensionality_reduction/reduce_dimensionality.py | 1 | 9928 | # -*- Mode: python; tab-width: 4; indent-tabs-mode:nil; coding:utf-8 -*-
# vim: tabstop=4 expandtab shiftwidth=4 softtabstop=4
#
# MDAnalysis --- https://www.mdanalysis.org
# Copyright (c) 2006-2017 The MDAnalysis Development Team and contributors
# (see the file AUTHORS for the full list of names)
#
# Released under t... | gpl-2.0 |
shiquanwang/pylearn2 | pylearn2/cross_validation/tests/test_train_cv_extensions.py | 49 | 1681 | """
Tests for TrainCV extensions.
"""
import os
import tempfile
from pylearn2.config import yaml_parse
from pylearn2.testing.skip import skip_if_no_sklearn
def test_monitor_based_save_best_cv():
"""Test MonitorBasedSaveBestCV."""
handle, filename = tempfile.mkstemp()
skip_if_no_sklearn()
trainer = ya... | bsd-3-clause |
cactusbin/nyt | matplotlib/examples/user_interfaces/embedding_in_tk.py | 9 | 1419 | #!/usr/bin/env python
import matplotlib
matplotlib.use('TkAgg')
from numpy import arange, sin, pi
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2TkAgg
# implement the default mpl key bindings
from matplotlib.backend_bases import key_press_handler
from matplotlib.figure import Fig... | unlicense |
justincassidy/scikit-learn | sklearn/ensemble/tests/test_forest.py | 57 | 35265 | """
Testing for the forest module (sklearn.ensemble.forest).
"""
# Authors: Gilles Louppe,
# Brian Holt,
# Andreas Mueller,
# Arnaud Joly
# License: BSD 3 clause
import pickle
from collections import defaultdict
from itertools import product
import numpy as np
from scipy.sparse import csr_... | bsd-3-clause |
ianctse/pvlib-python | pvlib/test/test_modelchain.py | 1 | 8186 | import numpy as np
import pandas as pd
from numpy import nan
from pvlib import modelchain, pvsystem
from pvlib.modelchain import ModelChain
from pvlib.pvsystem import PVSystem
from pvlib.tracking import SingleAxisTracker
from pvlib.location import Location
from pandas.util.testing import assert_series_equal, assert_f... | bsd-3-clause |
cwu2011/scikit-learn | sklearn/preprocessing/__init__.py | 14 | 1184 | """
The :mod:`sklearn.preprocessing` module includes scaling, centering,
normalization, binarization and imputation methods.
"""
from .data import Binarizer
from .data import KernelCenterer
from .data import MinMaxScaler
from .data import MaxAbsScaler
from .data import Normalizer
from .data import RobustScaler
from .d... | bsd-3-clause |
ElDeveloper/scikit-learn | sklearn/tree/tests/test_tree.py | 13 | 52365 | """
Testing for the tree module (sklearn.tree).
"""
import pickle
from functools import partial
from itertools import product
import platform
import numpy as np
from scipy.sparse import csc_matrix
from scipy.sparse import csr_matrix
from scipy.sparse import coo_matrix
from sklearn.random_projection import sparse_rand... | bsd-3-clause |
fmfn/UnbalancedDataset | imblearn/ensemble/_weight_boosting.py | 2 | 11479 | from copy import deepcopy
import numpy as np
from sklearn.base import clone
from sklearn.ensemble import AdaBoostClassifier
from sklearn.ensemble._base import _set_random_states
from sklearn.utils import _safe_indexing
from ..under_sampling.base import BaseUnderSampler
from ..under_sampling import RandomUnderSampler... | mit |
apdjustino/DRCOG_Urbansim | urbandeveloper/elasticity_model_2SLS.py | 1 | 6896 | __author__ = 'JMartinez'
import numpy as np, pandas as pd, os
from synthicity.utils import misc
import pysal as py
class elasticity_model(object):
def __init__(self, dset):
self.zones = dset.zones
self.buildings_far = pd.merge(dset.buildings, dset.fars, left_on='far_id', right_index=True)
... | agpl-3.0 |
e-matteson/pipit-keyboard | extras/audio/make_audio_files.py | 1 | 2652 | #!/bin/python2
from __future__ import division
import subprocess
from time import sleep
import os
# for generating sound files
import numpy as np
import matplotlib.pyplot as plt
import scipy.io.wavfile
import scipy.signal as sig
import scipy.stats as stats
master_volume = 1
sounds = {
'A':{'filename':'tick1.wa... | gpl-3.0 |
arjunkhode/ASP | lectures/03-Fourier-properties/plots-code/symmetry-real-even.py | 26 | 1150 | import matplotlib.pyplot as plt
import numpy as np
import sys
import math
from scipy.signal import triang
from scipy.fftpack import fft, fftshift
M = 127
N = 128
hM1 = int(math.floor((M+1)/2))
hM2 = int(math.floor(M/2))
x = triang(M)
fftbuffer = np.zeros(N)
fftbuffer[:hM1] = x[hM2:]
fftbuffer[N-hM2:] = x[:hM2]
X =... | agpl-3.0 |
alexlib/openpiv-python | setup.py | 2 | 1786 | from os import path
from setuptools import setup, find_packages
# read the contents of your README file
this_directory = path.abspath(path.dirname(__file__))
# with open(path.join(this_directory, 'README.md'), encoding='utf-8') as f:
with open(path.join(this_directory, 'README.md'), encoding='utf-8') as f:
long_d... | gpl-3.0 |
evgchz/scikit-learn | sklearn/linear_model/ransac.py | 16 | 13870 | # coding: utf-8
# Author: Johannes Schönberger
#
# License: BSD 3 clause
import numpy as np
from ..base import BaseEstimator, MetaEstimatorMixin, RegressorMixin, clone
from ..utils import check_random_state, check_array, check_consistent_length
from ..utils.random import sample_without_replacement
from .base import ... | bsd-3-clause |
openworm/tracker-commons | src/Python/wcon/wcon_parser.py | 3 | 28807 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Methods
------------
reject_duplicates
Classes
------------
WCONWorms
"""
import six
import warnings
from collections import OrderedDict
from six import StringIO
from os import path
import os
import shutil
import json
import jsonschema
import zipfile
import numpy as n... | mit |
winklerand/pandas | pandas/tests/test_resample.py | 1 | 135497 | # pylint: disable=E1101
from warnings import catch_warnings
from datetime import datetime, timedelta
from functools import partial
from textwrap import dedent
import pytz
import pytest
import dateutil
import numpy as np
import pandas as pd
import pandas.tseries.offsets as offsets
import pandas.util.testing as tm
imp... | bsd-3-clause |
mjudsp/Tsallis | sklearn/manifold/tests/test_locally_linear.py | 27 | 5247 | from itertools import product
from nose.tools import assert_true
import numpy as np
from numpy.testing import assert_almost_equal, assert_array_almost_equal
from scipy import linalg
from sklearn import neighbors, manifold
from sklearn.manifold.locally_linear import barycenter_kneighbors_graph
from sklearn.utils.testi... | bsd-3-clause |
lenovor/scikit-learn | examples/mixture/plot_gmm_selection.py | 248 | 3223 | """
=================================
Gaussian Mixture Model Selection
=================================
This example shows that model selection can be performed with
Gaussian Mixture Models using information-theoretic criteria (BIC).
Model selection concerns both the covariance type
and the number of components in th... | bsd-3-clause |
xwolf12/scikit-learn | benchmarks/bench_glm.py | 297 | 1493 | """
A comparison of different methods in GLM
Data comes from a random square matrix.
"""
from datetime import datetime
import numpy as np
from sklearn import linear_model
from sklearn.utils.bench import total_seconds
if __name__ == '__main__':
import pylab as pl
n_iter = 40
time_ridge = np.empty(n_it... | bsd-3-clause |
wateraccounting/wa | Collect/CFSR/DataAccess_CFSR.py | 1 | 8868 | # -*- coding: utf-8 -*-
"""
Authors: Tim Hessels
UNESCO-IHE 2016
Contact: t.hessels@unesco-ihe.org
Repository: https://github.com/wateraccounting/wa
Module: Collect/CFSR
"""
# General modules
import pandas as pd
import os
import numpy as np
from netCDF4 import Dataset
import re
from joblib import Parallel, del... | apache-2.0 |
renyi533/tensorflow | tensorflow/python/kernel_tests/constant_op_eager_test.py | 33 | 21448 | # 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 |
andela-mfalade/python-pandas-csv-records-analysis | scripts/processor.py | 1 | 5798 | """Initiate file analysis.
This module is used to find the discrepancies between two given files
"""
import argparse
import csv
import logging
import pandas as pd
logger = logging.getLogger(__file__)
logging.basicConfig(level=logging.DEBUG)
mathching_records_path = 'matching_records.csv'
non_mathching_records_path... | mit |
yyjiang/scikit-learn | sklearn/neighbors/tests/test_kd_tree.py | 129 | 7848 | import numpy as np
from numpy.testing import assert_array_almost_equal
from sklearn.neighbors.kd_tree import (KDTree, NeighborsHeap,
simultaneous_sort, kernel_norm,
nodeheap_sort, DTYPE, ITYPE)
from sklearn.neighbors.dist_metrics import Dista... | bsd-3-clause |
MatthieuBizien/scikit-learn | sklearn/manifold/setup.py | 24 | 1279 | import os
from os.path import join
import numpy
from numpy.distutils.misc_util import Configuration
from sklearn._build_utils import get_blas_info
def configuration(parent_package="", top_path=None):
config = Configuration("manifold", parent_package, top_path)
libraries = []
if os.name == 'posix':
... | bsd-3-clause |
pllim/ginga | ginga/rv/plugins/Preferences.py | 1 | 63607 | # This is open-source software licensed under a BSD license.
# Please see the file LICENSE.txt for details.
"""
Make changes to channel settings graphically in the UI.
**Plugin Type: Local**
``Preferences`` is a local plugin, which means it is associated with a
channel. An instance can be opened for each channel.
*... | bsd-3-clause |
yavalvas/yav_com | build/matplotlib/doc/mpl_examples/event_handling/viewlims.py | 6 | 2880 | # Creates two identical panels. Zooming in on the right panel will show
# a rectangle in the first panel, denoting the zoomed region.
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
# We just subclass Rectangle so that it can be called with an Axes
# instance, causing the r... | mit |
abhiver222/perkt | face_recognition.py | 2 | 5724 | import cv2
import sys
#import matplotlib.pyplot as pt
import numpy as np
import numpy.linalg as la
import math as mt
#Content of out eigens
<<<<<<< HEAD:face_recognition.py
# there would be five images of each person
# the collumns would be the frob norm of each type
# 4 rows for each person
# 1)Smiling
# 2)Sad
# 3)Se... | mit |
Unidata/MetPy | v0.11/startingguide-1.py | 4 | 1432 | import matplotlib.pyplot as plt
import numpy as np
import metpy.calc as mpcalc
from metpy.plots import SkewT
from metpy.units import units
fig = plt.figure(figsize=(9, 9))
skew = SkewT(fig)
# Create arrays of pressure, temperature, dewpoint, and wind components
p = [902, 897, 893, 889, 883, 874, 866, 857, 849, 841, 8... | bsd-3-clause |
joegomes/deepchem | deepchem/models/tests/test_overfit.py | 1 | 35451 | """
Tests to make sure deepchem models can overfit on tiny datasets.
"""
from __future__ import print_function
from __future__ import division
from __future__ import unicode_literals
__author__ = "Bharath Ramsundar"
__copyright__ = "Copyright 2016, Stanford University"
__license__ = "MIT"
import os
import tempfile
im... | mit |
mattsmart/biomodels | oncogenesis_dynamics/firstpassage.py | 1 | 15435 | import matplotlib.pyplot as plt
import numpy as np
import time
from os import sep
from multiprocessing import Pool, cpu_count
from constants import OUTPUT_DIR, PARAMS_ID, PARAMS_ID_INV, COLOURS_DARK_BLUE
from data_io import read_varying_mean_sd_fpt_and_params, collect_fpt_mean_stats_and_params, read_fpt_and_params,\
... | mit |
soylentdeen/Graffity | src/Vibrations/VibrationExplorer.py | 1 | 5531 | import sys
sys.path.append('../')
import numpy
import Graffity
import CIAO_DatabaseTools
import astropy.time as aptime
from matplotlib import pyplot
import colorsys
def getFreqs():
while True:
retval = []
enteredText = raw_input("Enter a comma separated list of frequencies: ")
try:
... | mit |
eoinmurray/icarus | Experiments/power_dep.py | 1 | 1341 |
import os,sys
parentdir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.insert(0,parentdir)
import numpy as np
import matplotlib.pyplot as plt
from constants import Constants
import Icarus.Experiment as Experiment
if __name__ == "__main__":
"""
Runs power dependance.
"""
constants = ... | mit |
openai/baselines | baselines/results_plotter.py | 1 | 3455 | import numpy as np
import matplotlib
matplotlib.use('TkAgg') # Can change to 'Agg' for non-interactive mode
import matplotlib.pyplot as plt
plt.rcParams['svg.fonttype'] = 'none'
from baselines.common import plot_util
X_TIMESTEPS = 'timesteps'
X_EPISODES = 'episodes'
X_WALLTIME = 'walltime_hrs'
Y_REWARD = 'reward'
Y_... | mit |
Sixshaman/networkx | doc/make_gallery.py | 35 | 2453 | """
Generate a thumbnail gallery of examples.
"""
from __future__ import print_function
import os, glob, re, shutil, sys
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot
import matplotlib.image
from matplotlib.figure import Figure
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCa... | bsd-3-clause |
hainm/scikit-learn | examples/cluster/plot_kmeans_assumptions.py | 270 | 2040 | """
====================================
Demonstration of k-means assumptions
====================================
This example is meant to illustrate situations where k-means will produce
unintuitive and possibly unexpected clusters. In the first three plots, the
input data does not conform to some implicit assumptio... | bsd-3-clause |
kcarnold/autograd | examples/fluidsim/fluidsim.py | 2 | 4623 | from __future__ import absolute_import
from __future__ import print_function
import autograd.numpy as np
from autograd import value_and_grad
from scipy.optimize import minimize
from scipy.misc import imread
import matplotlib
import matplotlib.pyplot as plt
import os
from builtins import range
# Fluid simulation code... | mit |
jenshnielsen/basemap | examples/maskoceans.py | 4 | 1922 | from mpl_toolkits.basemap import Basemap, shiftgrid, maskoceans, interp
import numpy as np
import matplotlib.pyplot as plt
# example showing how to mask out 'wet' areas on a contour or pcolor plot.
topodatin = np.loadtxt('etopo20data.gz')
lonsin = np.loadtxt('etopo20lons.gz')
latsin = np.loadtxt('etopo20lats.gz')
#... | gpl-2.0 |
Juanlu001/pfc | demo/plot_h.py | 1 | 6084 | #******************************************************************************
# *
# * ** * * * * *
# * * * * * * * * * *
... | gpl-3.0 |
wogsland/QSTK | build/lib.linux-x86_64-2.7/QSTK/qstkstudy/Events.py | 5 | 1878 | # (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 October <day>, 2011
#
#@author: Vishal Shekhar
#@contact: mailvishalshekhar@gmail.com
#@summary: Examp... | bsd-3-clause |
SitiBanc/1061_NCTU_IOMDS | 1025/Homework 5/HW5_5.py | 1 | 5472 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Oct 26 21:05:37 2017
@author: sitibanc
"""
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
# =============================================================================
# Read CSV
# =============================================... | apache-2.0 |
Unidata/MetPy | v0.12/_downloads/7b1d8e864fd4783fdaff1a83cdf9c52f/Find_Natural_Neighbors_Verification.py | 6 | 2521 | # Copyright (c) 2016 MetPy Developers.
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
"""
Find Natural Neighbors Verification
===================================
Finding natural neighbors in a triangulation
A triangle is a natural neighbor of a point if that point i... | bsd-3-clause |
mxjl620/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 |
pfnet/chainer | examples/wavenet/train.py | 6 | 5955 | import argparse
import os
import pathlib
import warnings
import numpy
import chainer
from chainer.training import extensions
import chainerx
from net import EncoderDecoderModel
from net import UpsampleNet
from net import WaveNet
from utils import Preprocess
import matplotlib
matplotlib.use('Agg')
parser = argpars... | mit |
JFriel/honours_project | networkx/build/lib/networkx/convert_matrix.py | 10 | 33329 | """Functions to convert NetworkX graphs to and from numpy/scipy matrices.
The preferred way of converting data to a NetworkX graph is through the
graph constuctor. The constructor calls the to_networkx_graph() function
which attempts to guess the input type and convert it automatically.
Examples
--------
Create a 10... | gpl-3.0 |
shahankhatch/scikit-learn | examples/text/document_clustering.py | 230 | 8356 | """
=======================================
Clustering text documents using k-means
=======================================
This is an example showing how the scikit-learn can be used to cluster
documents by topics using a bag-of-words approach. This example uses
a scipy.sparse matrix to store the features instead of ... | bsd-3-clause |
mganeva/mantid | Framework/PythonInterface/mantid/plots/modest_image/modest_image.py | 1 | 10141 | # v0.2 obtained on March 12, 2019
"""
Modification of Chris Beaumont's mpl-modest-image package to allow the use of
set_extent.
"""
from __future__ import print_function, division
import matplotlib
rcParams = matplotlib.rcParams
import matplotlib.image as mi
import matplotlib.colors as mcolors
import matplotlib.cbook... | gpl-3.0 |
xebitstudios/Kayak | examples/poisson_glm.py | 3 | 1224 | import numpy as np
import numpy.random as npr
import matplotlib.pyplot as plt
import sys
sys.path.append('..')
import kayak
N = 10000
D = 5
P = 1
learn = 0.00001
batch_size = 500
# Random inputs.
X = npr.randn(N,D)
true_W = npr.randn(D,P)
lam = np.exp(np.dot(X, true_W))
Y = npr.poisson(lam)
kyk_batcher = k... | mit |
rohanp/scikit-learn | sklearn/neighbors/tests/test_neighbors.py | 23 | 45330 | from itertools import product
import pickle
import numpy as np
from scipy.sparse import (bsr_matrix, coo_matrix, csc_matrix, csr_matrix,
dok_matrix, lil_matrix)
from sklearn import metrics
from sklearn.model_selection import train_test_split
from sklearn.model_selection import cross_val_scor... | bsd-3-clause |
DistrictDataLabs/django-data-product | irisfinder/views.py | 1 | 1948 | from django.shortcuts import render
import datetime
from models import Iris, SVMModels
from forms import UserIrisData
import sklearn
from sklearn import svm
from sklearn.cross_validation import train_test_split
import numpy as np
from django.conf import settings
import cPickle
import scipy
from pytz import timezone
imp... | apache-2.0 |
ndardenne/pymatgen | pymatgen/io/abinit/tasks.py | 2 | 166549 | # coding: utf-8
# Copyright (c) Pymatgen Development Team.
# Distributed under the terms of the MIT License.
"""This module provides functions and classes related to Task objects."""
from __future__ import division, print_function, unicode_literals, absolute_import
import os
import time
import datetime
import shutil
i... | mit |
tmeits/pybrain | pybrain/auxiliary/gaussprocess.py | 25 | 9240 | from __future__ import print_function
__author__ = 'Thomas Rueckstiess, ruecksti@in.tum.de; Christian Osendorfer, osendorf@in.tum.de'
from scipy import r_, exp, zeros, eye, array, asarray, random, ravel, diag, sqrt, sin, cos, sort, mgrid, dot, floor
from scipy import c_ #@UnusedImport
from scipy.linalg import solve,... | bsd-3-clause |
cosmoharrigan/pylearn2 | pylearn2/gui/tangent_plot.py | 44 | 1730 | """
Code for plotting curves with tangent lines.
"""
__author__ = "Ian Goodfellow"
try:
from matplotlib import pyplot
except Exception:
pyplot = None
from theano.compat.six.moves import xrange
def tangent_plot(x, y, s):
"""
Plots a curve with tangent lines.
Parameters
----------
x : lis... | bsd-3-clause |
dremio/arrow | integration/integration_test.py | 4 | 33972 | # 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 |
harisbal/pandas | pandas/tests/series/test_missing.py | 1 | 51950 | # coding=utf-8
# pylint: disable-msg=E1101,W0612
from datetime import datetime, timedelta
from distutils.version import LooseVersion
import numpy as np
from numpy import nan
import pytest
import pytz
from pandas._libs.tslib import iNaT
from pandas.compat import range
from pandas.errors import PerformanceWarning
impo... | bsd-3-clause |
pandegroup/osprey | osprey/strategies.py | 2 | 12612 | from __future__ import print_function, absolute_import, division
import sys
import inspect
import socket
import numpy as np
from sklearn.utils import check_random_state
from sklearn.model_selection import ParameterGrid
try:
from hyperopt import (Trials, tpe, fmin, STATUS_OK, STATUS_RUNNING,
... | apache-2.0 |
rhoscanner-team/pcd-plotter | delaunay_example.py | 1 | 1435 | import numpy as np
from scipy.spatial import Delaunay
points = np.random.rand(30, 2) # 30 points in 2-d
tri = Delaunay(points)
# Make a list of line segments:
# edge_points = [ ((x1_1, y1_1), (x2_1, y2_1)),
# ((x1_2, y1_2), (x2_2, y2_2)),
# ... ]
edge_points = []
edges = set()
def ad... | gpl-2.0 |
remenska/rootpy | rootpy/plotting/contrib/plot_corrcoef_matrix.py | 5 | 12192 | # Copyright 2012 the rootpy developers
# distributed under the terms of the GNU General Public License
from __future__ import absolute_import
from ...extern.six.moves import range
from ...extern.six import string_types
__all__ = [
'plot_corrcoef_matrix',
'corrcoef',
'cov',
]
def plot_corrcoef_matrix(mat... | gpl-3.0 |
nathanshartmann/portuguese_word_embeddings | sentence_similarity.py | 1 | 3369 |
"""
This script evaluates a embedding model in a semantic similarity perspective.
It uses the dataset of ASSIN sentence similarity shared task and the method
of Hartmann which achieved the best results in the competition.
ASSIN shared-task website:
http://propor2016.di.fc.ul.pt/?page_id=381
Paper of Hartmann can be ... | gpl-3.0 |
hetajen/vnpy161 | vn.trader/ctaStrategy/ctaBacktesting.py | 1 | 40890 | # encoding: UTF-8
'''
本文件中包含的是CTA模块的回测引擎，回测引擎的API和CTA引擎一致，
可以使用和实盘相同的代码进行回测。
History
<id> <author> <description>
2017051200 hetajen 样例：策略回测和优化
'''
from __future__ import division
'''2017051200 Add by hetajen begin'''
import time
'''2017051200 Add by hetajen end'''
from datetime import d... | mit |
kylerbrown/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 |
aureooms/networkx | examples/algorithms/blockmodel.py | 12 | 3014 | #!/usr/bin/env python
# encoding: utf-8
"""
Example of creating a block model using the blockmodel function in NX. Data used is the Hartford, CT drug users network:
@article{,
title = {Social Networks of Drug Users in {High-Risk} Sites: Finding the Connections},
volume = {6},
shorttitle = {Social Networks of Drug ... | bsd-3-clause |
sauloal/cnidaria | scripts/venv/lib/python2.7/site-packages/matplotlib/testing/compare.py | 11 | 12935 | """
Provides a collection of utilities for comparing (image) results.
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import hashlib
import os
import shutil
import numpy as np
import matplotlib
from matplotlib.compat import subprocess
from... | mit |
ishank08/scikit-learn | sklearn/datasets/tests/test_base.py | 16 | 9390 | import os
import shutil
import tempfile
import warnings
import numpy
from pickle import loads
from pickle import dumps
from sklearn.datasets import get_data_home
from sklearn.datasets import clear_data_home
from sklearn.datasets import load_files
from sklearn.datasets import load_sample_images
from sklearn.datasets im... | bsd-3-clause |
lucidfrontier45/scikit-learn | sklearn/utils/tests/test_extmath.py | 2 | 8819 | # Authors: Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# License: BSD
import numpy as np
from scipy import sparse
from scipy import linalg
from scipy import stats
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from sk... | bsd-3-clause |
DGrady/pandas | asv_bench/benchmarks/io_sql.py | 7 | 4120 | import sqlalchemy
from .pandas_vb_common import *
import sqlite3
from sqlalchemy import create_engine
#-------------------------------------------------------------------------------
# to_sql
class WriteSQL(object):
goal_time = 0.2
def setup(self):
self.engine = create_engine('sqlite:///:memory:')
... | bsd-3-clause |
merenlab/anvio | anvio/drivers/MODELLER.py | 1 | 40930 | # coding: utf-8
"""
Interface to MODELLER (https://salilab.org/modeller/).
"""
import os
import anvio
import shutil
import argparse
import subprocess
import pandas as pd
import anvio.utils as utils
import anvio.fastalib as u
import anvio.terminal as terminal
import anvio.constants as constants
import anvio.filesnpath... | gpl-3.0 |
shahankhatch/scikit-learn | sklearn/decomposition/dict_learning.py | 104 | 44632 | """ Dictionary learning
"""
from __future__ import print_function
# Author: Vlad Niculae, Gael Varoquaux, Alexandre Gramfort
# License: BSD 3 clause
import time
import sys
import itertools
from math import sqrt, ceil
import numpy as np
from scipy import linalg
from numpy.lib.stride_tricks import as_strided
from ..b... | bsd-3-clause |
ChinaQuants/zipline | zipline/utils/data.py | 31 | 12761 | #
# 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 |
PennyDreadfulMTG/Penny-Dreadful-Tools | decksite/charts/chart.py | 1 | 2940 | import os.path
import pathlib
from typing import Dict
import matplotlib as mpl
# This has to happen before pyplot is imported to avoid needing an X server to draw the graphs.
# pylint: disable=wrong-import-position
mpl.use('Agg')
import matplotlib.pyplot as plt
import seaborn as sns
from decksite.data import deck
fro... | gpl-3.0 |
ajdawson/windspharm | examples/iris/rws_example.py | 1 | 2190 | """Compute Rossby wave source from the long-term mean flow.
This example uses the iris interface.
Additional requirements for this example:
* iris (http://scitools.org.uk/iris/)
* matplotlib (http://matplotlib.org/)
* cartopy (http://scitools.org.uk/cartopy/)
"""
import warnings
import cartopy.crs as ccrs
import i... | mit |
gkulkarni/JetMorphology | fitjet_3d.py | 1 | 5370 | """
File: fitjet_3d.py
Fits a geometric model to mock jet data. Uses image subtraction;
otherwise same as fitjet.py
"""
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib import cm
import scipy.optimize as op
import emcee
import triangle
import sys
# These mock data are pr... | mit |
ahoyosid/scikit-learn | sklearn/utils/arpack.py | 265 | 64837 | """
This contains a copy of the future version of
scipy.sparse.linalg.eigen.arpack.eigsh
It's an upgraded wrapper of the ARPACK library which
allows the use of shift-invert mode for symmetric matrices.
Find a few eigenvectors and eigenvalues of a matrix.
Uses ARPACK: http://www.caam.rice.edu/software/ARPACK/
"""
#... | bsd-3-clause |
sdbonin/SOQresearch | SOQswapRK4.py | 1 | 8364 | # -*- coding: utf-8 -*-
"""
This code uses a loop along with our set of coupled differential equations and
matrix math to create arrays of 4-vector quaternions.
The old plotting functions need to be updated and incorperated into the end of
this code or a better visualization solution needs to be found.
"""
... | mit |
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