repo_name stringlengths 6 67 | path stringlengths 5 185 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 1.02k 962k | license stringclasses 15
values |
|---|---|---|---|---|---|
jswanljung/iris | docs/iris/example_code/Meteorology/hovmoller.py | 6 | 1622 | """
Hovmoller diagram of monthly surface temperature
================================================
This example demonstrates the creation of a Hovmoller diagram with fine control
over plot ticks and labels. The data comes from the Met Office OSTIA project
and has been pre-processed to calculate the monthly mean sea... | lgpl-3.0 |
bderembl/mitgcm_configs | eddy_iwave/analysis/azimuthal_average.py | 1 | 9428 | #!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
import scipy.interpolate as spint
import scipy.spatial.qhull as qhull
import itertools
import MITgcmutils as mit
import f90nml
plt.ion()
def interp_weights(xyz, uvw):
naux,d = xyz.shape
tri = qhull.Delaunay(xyz)
... | mit |
cuttlefishh/papers | red-sea-single-cell-genomes/code/make_rarefaction_plots_tara.py | 1 | 11809 | #!/usr/bin/env python
import click
import numpy as np
import pandas as pd
import random
import math
import matplotlib.pyplot as plt
# Function: Randomize columns order of pandas DataFrame
def randomize_df_column_order(df):
cols = df.columns.tolist()
np.random.shuffle(cols)
df_copy = df[cols]
return d... | mit |
phoebe-project/phoebe2-docs | 2.0/tutorials/RV.py | 1 | 5401 | #!/usr/bin/env python
# coding: utf-8
# 'rv' Datasets and Options
# ============================
#
# Setup
# -----------------------------
# Let's first make sure we have the latest version of PHOEBE 2.0 installed. (You can comment out this line if you don't use pip for your installation or don't want to update to t... | gpl-3.0 |
dpaiton/OpenPV | pv-core/analysis/python/plot_fourier_kcluster.py | 1 | 20158 | """
Plots the k-means clustering
"""
import sys
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
import matplotlib.cm as cm
import PVReadWeights as rw
import PVConversions as conv
import scipy.cluster.vq as sp
import math
import radialProfile
import pylab as py
if len(sys.argv) < 3:
... | epl-1.0 |
CagataySonmez/EdgeCloudSim | scripts/sample_app5/ai_trainer/data_convertor.py | 1 | 5014 | import pandas as pd
import json
import sys
if len (sys.argv) != 5:
print('invalid arguments. Usage:')
print('python data_conventor.py config.json [edge|cloud_rsu|cloud_gsm] [classifier|regression] [train|test]')
sys.exit(1)
with open(sys.argv[1]) as json_data_file:
data = json.load(json_data_file)... | gpl-3.0 |
jwi078/incubator-airflow | airflow/hooks/presto_hook.py | 1 | 2964 | from builtins import str
from pyhive import presto
from pyhive.exc import DatabaseError
from airflow.hooks.dbapi_hook import DbApiHook
import logging
logging.getLogger("pyhive").setLevel(logging.INFO)
class PrestoException(Exception):
pass
class PrestoHook(DbApiHook):
"""
Interact with Presto through ... | apache-2.0 |
herberthudson/pynance | pynance/opt/price.py | 2 | 7070 | """
.. Copyright (c) 2014, 2015 Marshall Farrier
license http://opensource.org/licenses/MIT
Options - price (:mod:`pynance.opt.price`)
==================================================
.. currentmodule:: pynance.opt.price
"""
from __future__ import absolute_import
import pandas as pd
from ._common import _getp... | mit |
molpopgen/pylibseq | docs/conf.py | 2 | 9974 | # -*- coding: utf-8 -*-
#
# pylibseq documentation build configuration file, created by
# sphinx-quickstart on Mon Oct 19 19:11:29 2015.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# ... | gpl-3.0 |
kaiseu/pat-data-processing | component/cpu.py | 1 | 2039 | #!/usr/bin/python
# encoding: utf-8
"""
@author: xuk1
@license: (C) Copyright 2013-2017
@contact: kai.a.xu@intel.com
@file: cpu.py
@time: 8/15/2017 10:50
@desc:
"""
import numpy as np
import pandas as pd
from component import base
class Cpu(base.CommonBase):
"""
Node CPU attribute, p... | apache-2.0 |
mrshu/scikit-learn | examples/applications/plot_tomography_l1_reconstruction.py | 4 | 5464 | """
======================================================================
Compressive sensing: tomography reconstruction with L1 prior (Lasso)
======================================================================
This example shows the reconstruction of an image from a set of parallel
projections, acquired along dif... | bsd-3-clause |
aborovin/trading-with-python | lib/csvDatabase.py | 77 | 6045 | # -*- coding: utf-8 -*-
"""
intraday data handlers in csv format.
@author: jev
"""
from __future__ import division
import pandas as pd
import datetime as dt
import os
from extra import ProgressBar
dateFormat = "%Y%m%d" # date format for converting filenames to dates
dateTimeFormat = "%Y%m%d %H:%M:%S"... | bsd-3-clause |
mbonsma/phageParser | populate.py | 3 | 6935 | #!/usr/bin/env python
import argparse
import os
import pickle
import pandas
import requests
from Bio import Entrez, SeqIO
from lxml import html, etree
from tqdm import tqdm
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'phageAPI.settings')
import django
django.setup()
from util.acc import read_accession_file
fro... | mit |
massmutual/scikit-learn | sklearn/cluster/spectral.py | 233 | 18153 | # -*- coding: utf-8 -*-
"""Algorithms for spectral clustering"""
# Author: Gael Varoquaux gael.varoquaux@normalesup.org
# Brian Cheung
# Wei LI <kuantkid@gmail.com>
# License: BSD 3 clause
import warnings
import numpy as np
from ..base import BaseEstimator, ClusterMixin
from ..utils import check_rand... | bsd-3-clause |
ortylp/scipy | doc/source/tutorial/stats/plots/kde_plot4.py | 142 | 1457 | from functools import partial
import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
def my_kde_bandwidth(obj, fac=1./5):
"""We use Scott's Rule, multiplied by a constant factor."""
return np.power(obj.n, -1./(obj.d+4)) * fac
loc1, scale1, size1 = (-2, 1, 175)
loc2, scale2, size2 = (2, ... | bsd-3-clause |
huzq/scikit-learn | examples/neighbors/plot_nca_dim_reduction.py | 24 | 3839 | """
==============================================================
Dimensionality Reduction with Neighborhood Components Analysis
==============================================================
Sample usage of Neighborhood Components Analysis for dimensionality reduction.
This example compares different (linear) dimen... | bsd-3-clause |
tcmoore3/mdtraj | mdtraj/tests/test_topology.py | 5 | 8412 | ##############################################################################
# MDTraj: A Python Library for Loading, Saving, and Manipulating
# Molecular Dynamics Trajectories.
# Copyright 2012-2014 Stanford University and the Authors
#
# Authors: Kyle A. Beauchamp
# Contributors: Robert McGibbon, Matthew Har... | lgpl-2.1 |
costypetrisor/scikit-learn | sklearn/metrics/ranking.py | 5 | 24965 | """Metrics to assess performance on classification task given scores
Functions named as ``*_score`` return a scalar value to maximize: the higher
the better
Function named as ``*_error`` or ``*_loss`` return a scalar value to minimize:
the lower the better
"""
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.... | bsd-3-clause |
camsas/qjump-nsdi15-plotting | figure1c_3c/plot_naiad_latency_cdfs.py | 2 | 7009 | # Copyright (c) 2015, Malte Schwarzkopf
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright notice, this
# list of conditions and... | bsd-3-clause |
zaxtax/scikit-learn | examples/cluster/plot_digits_linkage.py | 369 | 2959 | """
=============================================================================
Various Agglomerative Clustering on a 2D embedding of digits
=============================================================================
An illustration of various linkage option for agglomerative clustering on
a 2D embedding of the di... | bsd-3-clause |
CarterBain/AlephNull | alephnull/transforms/batch_transform.py | 1 | 16947 | #
# 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 |
ntbrewer/DAQ_1 | kick-u3/KickPlot.py | 1 | 4859 | #!/usr/bin/python3
# /bin/python3
# #####################################################
# This script makes plots of the mtc cycle
# written to the labjack outputs for control and monitoring.
# This script can be used anywhere by changing the
# location of the python3 directive after #!.
# usage: ./KickPlot.py and u... | gpl-3.0 |
henridwyer/scikit-learn | sklearn/manifold/tests/test_mds.py | 324 | 1862 | import numpy as np
from numpy.testing import assert_array_almost_equal
from nose.tools import assert_raises
from sklearn.manifold import mds
def test_smacof():
# test metric smacof using the data of "Modern Multidimensional Scaling",
# Borg & Groenen, p 154
sim = np.array([[0, 5, 3, 4],
... | bsd-3-clause |
wclark3/machine-learning | final-project/md_sandbox/main.py | 1 | 3481 | #!/usr/bin/env python
import abc
import operator
import time
import lasagne
import numpy as np
import theano
import theano.tensor as T
from sklearn.metrics import confusion_matrix
import fileio
import perceptron
# class Batch:
# def __init__(self, batchsize, shuffle):
# self.batchsize = batchsize
# self.shuffle... | mit |
crichardson17/starburst_atlas | HighResSims/Old/Baseline_Dusty_supersolar_5solar_cutat17/Baseline_plotter.py | 1 | 12649 | ############################################################
############# Plotting File for Contour Plots ##############
################## Data read from Cloudy ###################
################ Helen Meskhidze, Fall 2015 ################
#################### Elon University #######################
#--------------... | gpl-2.0 |
aetilley/scikit-learn | sklearn/tests/test_naive_bayes.py | 142 | 17496 | import pickle
from io import BytesIO
import numpy as np
import scipy.sparse
from sklearn.datasets import load_digits, load_iris
from sklearn.cross_validation import cross_val_score, train_test_split
from sklearn.externals.six.moves import zip
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.te... | bsd-3-clause |
ch3ll0v3k/scikit-learn | examples/datasets/plot_random_multilabel_dataset.py | 93 | 3460 | """
==============================================
Plot randomly generated multilabel dataset
==============================================
This illustrates the `datasets.make_multilabel_classification` dataset
generator. Each sample consists of counts of two features (up to 50 in
total), which are differently distri... | bsd-3-clause |
Tjorriemorrie/trading | 09_scalping/features.py | 2 | 11161 | import pandas as pd
import numpy as np
from sklearn.ensemble import RandomForestClassifier
from sklearn.cross_validation import cross_val_score
import sklearn as sk
import operator
from pprint import pprint
class FeatureFactory():
def ema(self, s, n):
""" returns an n period exponential moving average for... | mit |
adammenges/statsmodels | statsmodels/datasets/elnino/data.py | 25 | 1779 | """El Nino dataset, 1950 - 2010"""
__docformat__ = 'restructuredtext'
COPYRIGHT = """This data is in the public domain."""
TITLE = """El Nino - Sea Surface Temperatures"""
SOURCE = """
National Oceanic and Atmospheric Administration's National Weather Service
ERSST.V3B dataset, Nino 1+2
http://www.cpc... | bsd-3-clause |
lthurlow/Network-Grapher | proj/external/matplotlib-1.2.1/examples/pylab_examples/fancyarrow_demo.py | 12 | 1386 | import matplotlib.patches as mpatches
import matplotlib.pyplot as plt
styles = mpatches.ArrowStyle.get_styles()
ncol=2
nrow = (len(styles)+1) // ncol
figheight = (nrow+0.5)
fig1 = plt.figure(1, (4.*ncol/1.5, figheight/1.5))
fontsize = 0.2 * 70
ax = fig1.add_axes([0, 0, 1, 1], frameon=False, aspect=1.)
ax.set_xlim(... | mit |
jasonabele/gnuradio | gr-msdd6000/src/python-examples/msdd_spectrum_sense.py | 8 | 10553 | #!/usr/bin/env python
#
# Copyright 2008 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 option)
... | gpl-3.0 |
raghavrv/scikit-learn | sklearn/datasets/samples_generator.py | 8 | 56767 | """
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 |
awanke/bokeh | examples/glyphs/trail.py | 33 | 4656 | # -*- coding: utf-8 -*-
from __future__ import print_function
from math import sin, cos, atan2, sqrt, radians
import numpy as np
import scipy.ndimage as im
from bokeh.document import Document
from bokeh.embed import file_html
from bokeh.resources import INLINE
from bokeh.browserlib import view
from bokeh.models.gl... | bsd-3-clause |
hugobowne/scikit-learn | examples/ensemble/plot_bias_variance.py | 357 | 7324 | """
============================================================
Single estimator versus bagging: bias-variance decomposition
============================================================
This example illustrates and compares the bias-variance decomposition of the
expected mean squared error of a single estimator again... | bsd-3-clause |
larsmans/scikit-learn | examples/svm/plot_svm_nonlinear.py | 61 | 1089 | """
==============
Non-linear SVM
==============
Perform binary classification using non-linear SVC
with RBF kernel. The target to predict is a XOR of the
inputs.
The color map illustrates the decision function learn by the SVC.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from sklearn impor... | bsd-3-clause |
eg-zhang/scikit-learn | benchmarks/bench_multilabel_metrics.py | 276 | 7138 | #!/usr/bin/env python
"""
A comparison of multilabel target formats and metrics over them
"""
from __future__ import division
from __future__ import print_function
from timeit import timeit
from functools import partial
import itertools
import argparse
import sys
import matplotlib.pyplot as plt
import scipy.sparse as... | bsd-3-clause |
jgphpc/linux | slurm/crayvis/crayvis_pmessmer.py | 1 | 4263 | #!/usr/bin/env python3
# Thanks goes to Peter Messmer at NVIDIA
# mll daint-gpu PyExtensions/3.6.1.1-CrayGNU-17.08
# https://github.com/eth-cscs/pyfr/issues/11
# Gray are the compute nodes
# Yellow the service nodes
# Blue the nodes allocated in the run
# Red the failed node
import matplotlib.pyplot... | gpl-2.0 |
ronojoy/BDA_py_demos | demos_ch6/demo6_2.py | 19 | 1366 | """Bayesian Data Analysis, 3rd ed
Chapter 6, demo 2
Posterior predictive checking
Binomial example - Testing sequential dependence example
"""
from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
# edit default plot settings (colours from colorbrewer2.org)
plt.rc('font', size=14)
plt.r... | gpl-3.0 |
JingheZ/shogun | applications/tapkee/faces_embedding.py | 26 | 2078 | #!/usr/bin/env python
# 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 3 of the License, or
# (at your option) any later version.
#
# Written (W) 2011 Sergey Lisitsyn
# Copyright ... | gpl-3.0 |
AIML/scikit-learn | examples/model_selection/randomized_search.py | 201 | 3214 | """
=========================================================================
Comparing randomized search and grid search for hyperparameter estimation
=========================================================================
Compare randomized search and grid search for optimizing hyperparameters of a
random forest.
... | bsd-3-clause |
nzavagli/UnrealPy | UnrealPyEmbed/Development/Python/2015.08.07-Python2710-x64-Source-vs2015/Python27/Source/numpy-1.9.2/numpy/lib/function_base.py | 30 | 124613 | from __future__ import division, absolute_import, print_function
import warnings
import sys
import collections
import operator
import numpy as np
import numpy.core.numeric as _nx
from numpy.core import linspace, atleast_1d, atleast_2d
from numpy.core.numeric import (
ones, zeros, arange, concatenate, array, asarr... | mit |
cdegroc/scikit-learn | examples/plot_permutation_test_for_classification.py | 5 | 2319 | """
=================================================================
Test with permutations the significance of a classification score
=================================================================
In order to test if a classification score is significative a technique
in repeating the classification procedure aft... | bsd-3-clause |
rubind/SimpleBayesJLA | plot_cosmo.py | 1 | 2375 | import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import gaussian_kde
import pickle
from IPython import embed
plt.rcParams["font.family"] = "serif"
def reflect(samps, othersamps = None, reflect_cut = 0.2):
the_min = min(samps)
the_max = max(samps)
inds = np.where((samps < the_min*(1. - r... | mit |
aminert/scikit-learn | sklearn/ensemble/tests/test_gradient_boosting_loss_functions.py | 221 | 5517 | """
Testing for the gradient boosting loss functions and initial estimators.
"""
import numpy as np
from numpy.testing import assert_array_equal
from numpy.testing import assert_almost_equal
from numpy.testing import assert_equal
from nose.tools import assert_raises
from sklearn.utils import check_random_state
from ... | bsd-3-clause |
idbedead/RNA-sequence-tools | make_geo_list2.py | 2 | 2850 | import os
import pandas as pd
import shutil
import sys
import hashlib
def md5(fname):
hash_md5 = hashlib.md5()
with open(fname, "rb") as f:
for chunk in iter(lambda: f.read(4096), b""):
hash_md5.update(chunk)
return hash_md5.hexdigest()
pats = ['/Volumes/Seq_data/09142015_BU3_ips17_ra... | mit |
jreback/pandas | pandas/compat/pickle_compat.py | 1 | 7903 | """
Support pre-0.12 series pickle compatibility.
"""
import contextlib
import copy
import io
import pickle as pkl
from typing import TYPE_CHECKING, Optional
import warnings
from pandas._libs.tslibs import BaseOffset
from pandas import Index
if TYPE_CHECKING:
from pandas import DataFrame, Series
def load_redu... | bsd-3-clause |
Elarnon/mangaki | mangaki/mangaki/utils/svd.py | 2 | 5410 | from django.contrib.auth.models import User
from mangaki.models import Rating, Work, Recommendation
from mangaki.utils.chrono import Chrono
from mangaki.utils.values import rating_values
from scipy.sparse import lil_matrix
from sklearn.utils.extmath import randomized_svd
import numpy as np
from django.db import connect... | agpl-3.0 |
JeanKossaifi/scikit-learn | examples/gaussian_process/gp_diabetes_dataset.py | 223 | 1976 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
========================================================================
Gaussian Processes regression: goodness-of-fit on the 'diabetes' dataset
========================================================================
In this example, we fit a Gaussian Process model onto... | bsd-3-clause |
berkeley-stat159/project-zeta | code/linear_model_scripts_sub4.py | 3 | 25730 | # Goal for this scripts:
#
# Perform linear regression and analyze the similarity in terms of the activated brain area when recognizing different
# objects in odd and even runs of subject 1
# Load required function and modules:
from __future__ import print_function, division
import numpy as np
import numpy.linalg as ... | bsd-3-clause |
stwunsch/gnuradio | gr-utils/python/utils/plot_data.py | 59 | 5818 | #
# Copyright 2007,2008,2011 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 option)
# any later ve... | gpl-3.0 |
dustinbcox/biodatalogger | biodata_grapher.py | 1 | 1356 | #!/usr/bin/python2.7
"""
Biodata_grapher
2015-08-30
"""
import glob
import csv
import os
import matplotlib.pyplot as plt
import matplotlib
from datetime import datetime
import traceback
for filename in glob.glob('*_biodatalogger_readings.csv'):
filename_png = filename.replace('.csv', '.png')
if os.path.exist... | gpl-2.0 |
ssaeger/scikit-learn | sklearn/cross_validation.py | 7 | 67336 |
"""
The :mod:`sklearn.cross_validation` module includes utilities for cross-
validation and performance evaluation.
"""
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>,
# Gael Varoquaux <gael.varoquaux@normalesup.org>,
# Olivier Grisel <olivier.grisel@ensta.org>
# License: BSD 3 clause
fro... | bsd-3-clause |
janhahne/nest-simulator | pynest/nest/tests/test_spatial/test_plotting.py | 12 | 5748 | # -*- coding: utf-8 -*-
#
# test_plotting.py
#
# This file is part of NEST.
#
# Copyright (C) 2004 The NEST Initiative
#
# NEST 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 the License, ... | gpl-2.0 |
RRCKI/pilot | ATLASSiteInformation.py | 1 | 42230 | # Class definition:
# ATLASSiteInformation
# This class is the ATLAS site information class inheriting from SiteInformation
# Instances are generated with SiteInformationFactory via pUtil::getSiteInformation()
# Implemented as a singleton class
# http://stackoverflow.com/questions/42558/python-and-the-singlet... | apache-2.0 |
yavalvas/yav_com | build/matplotlib/examples/pylab_examples/transoffset.py | 13 | 1666 | #!/usr/bin/env python
'''
This illustrates the use of transforms.offset_copy to
make a transform that positions a drawing element such as
a text string at a specified offset in screen coordinates
(dots or inches) relative to a location given in any
coordinates.
Every Artist--the mpl class from which classes such as
T... | mit |
niknow/scipy | doc/source/tutorial/examples/normdiscr_plot1.py | 84 | 1547 | import numpy as np
import matplotlib.pyplot as plt
from scipy import stats
npoints = 20 # number of integer support points of the distribution minus 1
npointsh = npoints / 2
npointsf = float(npoints)
nbound = 4 #bounds for the truncated normal
normbound = (1 + 1 / npointsf) * nbound #actual bounds of truncated normal
... | bsd-3-clause |
mit-crpg/openmc | tests/regression_tests/mgxs_library_condense/test.py | 7 | 2471 | import hashlib
import openmc
import openmc.mgxs
from openmc.examples import pwr_pin_cell
from tests.testing_harness import PyAPITestHarness
class MGXSTestHarness(PyAPITestHarness):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
# Initialize a two-group structure
... | mit |
f3r/scikit-learn | sklearn/naive_bayes.py | 29 | 28917 | # -*- coding: utf-8 -*-
"""
The :mod:`sklearn.naive_bayes` module implements Naive Bayes algorithms. These
are supervised learning methods based on applying Bayes' theorem with strong
(naive) feature independence assumptions.
"""
# Author: Vincent Michel <vincent.michel@inria.fr>
# Minor fixes by Fabian Pedre... | bsd-3-clause |
rudhir-upretee/Sumo17_With_Netsim | tools/projects/TaxiFCD_Krieg/src/taxiQuantity/QuantityOverDay.py | 1 | 2316 | # -*- coding: Latin-1 -*-
"""
@file QuantityOverDay.py
@author Sascha Krieg
@author Daniel Krajzewicz
@author Michael Behrisch
@date 2008-04-01
Counts for an given interval all unique taxis in an FCD file and draws the result as a bar chart.
SUMO, Simulation of Urban MObility; see http://sumo.sourceforge.ne... | gpl-3.0 |
Aghosh993/QuadcopterCodebase | GroundSoftware/csv_display.py | 1 | 1948 | #!/usr/bin/python3
import matplotlib as mp
import numpy as np
import matplotlib.pyplot as plt
import argparse
message_set = "sf11_bno055 v_z ahrs_rp yaw_height flow bno055_att esc_cmds"
def plot_file(file):
fig = plt.figure()
input_data = np.loadtxt(file, delimiter=', ')
col = input_data.shape[1]
xdata = input_... | gpl-3.0 |
bzero/arctic | tests/util.py | 2 | 1376 | from contextlib import contextmanager
from cStringIO import StringIO
from dateutil.rrule import rrule, DAILY
import dateutil
from datetime import datetime as dt
import pandas
import numpy as np
import sys
def read_str_as_pandas(ts_str):
labels = [x.strip() for x in ts_str.split('\n')[0].split('|')]
pd = panda... | lgpl-2.1 |
rmeertens/paparazzi | sw/misc/attitude_reference/att_ref_gui.py | 49 | 12483 | #!/usr/bin/env python
#
# Copyright (C) 2014 Antoine Drouin
#
# This file is part of paparazzi.
#
# paparazzi 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, or (at your option)
# any later ... | gpl-2.0 |
marcoitur/Freecad_test | src/Mod/Plot/plotSeries/TaskPanel.py | 26 | 17784 | #***************************************************************************
#* *
#* Copyright (c) 2011, 2012 *
#* Jose Luis Cercos Pita <jlcercos@gmail.com> *
#* ... | lgpl-2.1 |
grlee77/scipy | scipy/signal/ltisys.py | 12 | 128865 | """
ltisys -- a collection of classes and functions for modeling linear
time invariant systems.
"""
#
# Author: Travis Oliphant 2001
#
# Feb 2010: Warren Weckesser
# Rewrote lsim2 and added impulse2.
# Apr 2011: Jeffrey Armstrong <jeff@approximatrix.com>
# Added dlsim, dstep, dimpulse, cont2discrete
# Aug 2013: Jua... | bsd-3-clause |
jwbuurlage/Zee | script/plot.py | 1 | 2256 | #!/usr/bin/python3
# plot.py reads descriptive.mtx, .plt, ... files and plots these` using matplotlib
#
# FIXME: REQUIRES USETEX, PNGDVI, etc.
# TODO: zplot support
import argparse
import os
import yaml
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.patches as patches
import matplotlib.ticker a... | gpl-3.0 |
rubikloud/scikit-learn | examples/decomposition/plot_ica_vs_pca.py | 306 | 3329 | """
==========================
FastICA on 2D point clouds
==========================
This example illustrates visually in the feature space a comparison by
results using two different component analysis techniques.
:ref:`ICA` vs :ref:`PCA`.
Representing ICA in the feature space gives the view of 'geometric ICA':
ICA... | bsd-3-clause |
maxvonhippel/q2-diversity | q2_diversity/tests/test_core_metrics.py | 1 | 1666 | # ----------------------------------------------------------------------------
# Copyright (c) 2016-2017, QIIME 2 development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ------------------------------------------------... | bsd-3-clause |
Chilipp/nc2map | _maps_old.py | 1 | 61976 | # -*- coding: utf-8 -*-
import glob
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
from itertools import izip, chain, permutations, product
from collections import OrderedDict
from mapos import mapBase, fieldplot, windplot, returnbounds, round_... | gpl-2.0 |
NunoEdgarGub1/scikit-learn | examples/cluster/plot_kmeans_silhouette_analysis.py | 242 | 5885 | """
===============================================================================
Selecting the number of clusters with silhouette analysis on KMeans clustering
===============================================================================
Silhouette analysis can be used to study the separation distance between the... | bsd-3-clause |
fabioticconi/scikit-learn | examples/bicluster/plot_spectral_coclustering.py | 127 | 1732 | """
==============================================
A demo of the Spectral Co-Clustering algorithm
==============================================
This example demonstrates how to generate a dataset and bicluster it
using the Spectral Co-Clustering algorithm.
The dataset is generated using the ``make_biclusters`` funct... | bsd-3-clause |
datapythonista/pandas | pandas/tests/arrays/integer/test_comparison.py | 9 | 4005 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
from pandas.tests.extension.base import BaseOpsUtil
class TestComparisonOps(BaseOpsUtil):
def _compare_other(self, data, op_name, other):
op = self.get_op_from_name(op_name)
# array
result = pd.Series(op(da... | bsd-3-clause |
manashmndl/scikit-learn | sklearn/feature_extraction/tests/test_dict_vectorizer.py | 276 | 3790 | # Authors: Lars Buitinck <L.J.Buitinck@uva.nl>
# Dan Blanchard <dblanchard@ets.org>
# License: BSD 3 clause
from random import Random
import numpy as np
import scipy.sparse as sp
from numpy.testing import assert_array_equal
from sklearn.utils.testing import (assert_equal, assert_in,
... | bsd-3-clause |
INM-6/hybridLFPy | examples/example_brunel_alpha_topo_exp.py | 1 | 24733 | #!/usr/bin/env python
'''
Hybrid LFP scheme example script, applying the methodology with a model
implementation similar to:
Nicolas Brunel. "Dynamics of Sparsely Connected Networks of Excitatory and
Inhibitory Spiking Neurons". J Comput Neurosci, May 2000, Volume 8,
Issue 3, pp 183-208
But the network is implemented... | gpl-3.0 |
robbymeals/scikit-learn | sklearn/decomposition/base.py | 313 | 5647 | """Principal Component Analysis Base Classes"""
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# Denis A. Engemann <d.engemann@fz-juelich.de>
# Kyle Kastner <kastnerkyle@gmail.com>
#
# Licen... | bsd-3-clause |
Fireblend/scikit-learn | examples/manifold/plot_compare_methods.py | 259 | 4031 | """
=========================================
Comparison of Manifold Learning methods
=========================================
An illustration of dimensionality reduction on the S-curve dataset
with various manifold learning methods.
For a discussion and comparison of these algorithms, see the
:ref:`manifold module... | bsd-3-clause |
Unidata/MetPy | v0.6/_downloads/meteogram_metpy.py | 2 | 9460 | # Copyright (c) 2017 MetPy Developers.
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
"""
Meteogram
=========
Plots time series data as a meteogram.
"""
import datetime as dt
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
from metpy.ca... | bsd-3-clause |
jjx02230808/project0223 | examples/feature_stacker.py | 50 | 1910 | """
=================================================
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 |
metinsay/docluster | docluster/models/word_embedding/word2vec.py | 1 | 14211 | import collections
import math
import multiprocessing
import os
import random
import threading
from copy import deepcopy
import pandas as pd
import numpy as np
import tensorflow as tf
from docluster.core import Model
from docluster.core.document_embedding import TfIdf
from docluster.core.preprocessing import Preproce... | mit |
ttchin/FaceDetected | FaceTrain.py | 1 | 8343 | #! encoding: UTF-8
#%%
from __future__ import print_function
import random
import numpy as np
from sklearn.cross_validation import train_test_split
from keras.preprocessing.image import ImageDataGenerator
from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation, Flatten
from keras.layers... | mit |
alpha-beta-soup/errorgeopy | errorgeopy/utils.py | 1 | 14060 | """Utility functions for ErrorGeoPy. Inteded to be private functions, their
call signatures are not considered strictly static.
.. moduleauthor Richard Law <richard.m.law@gmail.com>
"""
import numpy as np
from collections import namedtuple
from functools import partial, wraps
from itertools import compress
import ins... | mit |
kmunve/pysenorge | pysenorge/io/bil.py | 1 | 5484 | __docformat__ = "reStructuredText"
'''
Binary (.bil) input/output class.
:Author: kmu
:Created: 14. okt. 2010
'''
# Built-in
import os, sys
sys.path.append(os.path.abspath('../..'))
# Additional
from numpy import zeros, fromfile, int8, int16, uint8, uint16, float32, nan
# Own
from pysenorge.converters... | gpl-3.0 |
MonoCloud/zipline | zipline/utils/tradingcalendar_tse.py | 17 | 10125 | #
# 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 |
Paul-St-Young/share | algorithms/iso3d/hf/chf.py | 1 | 3892 | #!/usr/bin/env python
import os
import numpy as np
def show_moR(moR):
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D # enable 3D projection
from qharv.inspect import volumetric,crystal
fig = plt.figure()
iplot = 0
for iorb in mo_to_plot:
iplot += 1
val = moR[:,iorb].resh... | mit |
LouisePaulDelvaux/openfisca-france-data | openfisca_france_data/input_data_builders/build_openfisca_indirect_taxation_survey_data/step_0_4_homogeneisation_revenus_menages.py | 1 | 15961 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
# OpenFisca -- A versatile microsimulation software
# By: OpenFisca Team <contact@openfisca.fr>
#
# Copyright (C) 2011, 2012, 2013, 2014, 2015 OpenFisca Team
# https://github.com/openfisca
#
# This file is part of OpenFisca.
#
# OpenFisca is free software; you can redist... | agpl-3.0 |
KirstieJane/BrainsForPublication | scripts/show_cluster_in_volume.py | 3 | 18141 | #!/usr/bin/env python
#=============================================================================
# Created by Michael Notter
# at OHBM 2016 Brainhack in Lausanne, June 2016
# Edited with more comments by Kirstie Whitaker
# at Cambridge Brainhack-Global 2017, March 2017
# Contact: kw401@cam.ac.uk
#=================... | mit |
PalNilsson/pilot2 | pilot/info/storagedata.py | 1 | 6509 | # 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
#
# Authors:
# - Alexey Anisenkov, anisyonk@cern.ch, 2018
# - Paul Nilsson, paul.nilsson@cern.ch, 20... | apache-2.0 |
davek44/Basset | src/dev/basset_conv2.py | 1 | 5911 | #!/usr/bin/env python
from optparse import OptionParser
import os
import random
import subprocess
import h5py
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
################################################################################
# basset_conv2.py
#
# Visualize the 2nd convolution la... | mit |
gabrevaya/Canto5 | main.py | 2 | 2355 | '''
Función principal. Obtiene silabas separadas y caracterizadas desde un archivo wav.
'''
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
from envolvente import envolvente
from read_wav import read_wav
from get_files_paths import get_files_paths
from find_syllables import find_syllables
f... | gpl-3.0 |
jhonatanoliveira/pgmpy | pgmpy/estimators/ConstraintBasedEstimator.py | 5 | 24197 | #!/usr/bin/env python
from warnings import warn
from itertools import combinations
from pgmpy.base import UndirectedGraph
from pgmpy.models import BayesianModel
from pgmpy.estimators import StructureEstimator
from pgmpy.independencies import Independencies, IndependenceAssertion
class ConstraintBasedEstimator(Struc... | mit |
hlin117/statsmodels | statsmodels/sandbox/nonparametric/kdecovclass.py | 33 | 5703 | '''subclassing kde
Author: josef pktd
'''
import numpy as np
import scipy
from scipy import stats
import matplotlib.pylab as plt
class gaussian_kde_set_covariance(stats.gaussian_kde):
'''
from Anne Archibald in mailinglist:
http://www.nabble.com/Width-of-the-gaussian-in-stats.kde.gaussian_kde---td1955892... | bsd-3-clause |
markomanninen/strongs | isopsephy/search.py | 5 | 1537 | #!/usr/local/bin/python
# -*- coding: utf-8 -*-
# file: search.py
def find_cumulative_indices(list_of_numbers, search_sum):
"""
find_cumulative_indices([70, 58, 81, 909, 70, 215, 70, 1022, 580, 930, 898], 285) ->
[[4, 5],[5, 6]]
"""
u = 0
y = 0
result = []
for idx, val in enumerate(lis... | mit |
jstoxrocky/statsmodels | statsmodels/datasets/randhie/data.py | 25 | 2667 | """RAND Health Insurance Experiment Data"""
__docformat__ = 'restructuredtext'
COPYRIGHT = """This is in the public domain."""
TITLE = __doc__
SOURCE = """
The data was collected by the RAND corporation as part of the Health
Insurance Experiment (HIE).
http://www.rand.org/health/projects/hie.html
This ... | bsd-3-clause |
openpathsampling/openpathsampling | openpathsampling/tests/test_histogram.py | 2 | 11957 | from __future__ import division
from __future__ import absolute_import
from past.utils import old_div
from builtins import object
from .test_helpers import assert_items_almost_equal, assert_items_equal
import pytest
import logging
logging.getLogger('openpathsampling.initialization').setLevel(logging.CRITICAL)
logging.g... | mit |
rafiqsaleh/VERCE | verce-hpc-pe/src/postproc.py | 2 | 8125 | from verce.GenericPE import GenericPE, NAME
import os
class WatchDirectory(GenericPE):
OUTPUT_NAME='output'
def __init__(self, directory):
GenericPE.__init__(self)
self.outputconnections = { WatchDirectory.OUTPUT_NAME : { NAME : WatchDirectory.OUTPUT_NAME }}
self.directory = directory
... | mit |
xuewei4d/scikit-learn | sklearn/mixture/_bayesian_mixture.py | 7 | 33397 | """Bayesian Gaussian Mixture Model."""
# Author: Wei Xue <xuewei4d@gmail.com>
# Thierry Guillemot <thierry.guillemot.work@gmail.com>
# License: BSD 3 clause
import math
import numpy as np
from scipy.special import betaln, digamma, gammaln
from ._base import BaseMixture, _check_shape
from ._gaussian_mixture im... | bsd-3-clause |
abulak/TDA-Cause-Effect-Pairs | identify_outliers.py | 1 | 6251 | import os
import sys
import numpy as np
import numpy.ma as ma
import logging
from sklearn.neighbors import NearestNeighbors
import scipy.spatial as spsp
def standardise(points):
"""
Standardise points, i.e. mean = 0 and standard deviation = 1 in both
dimensions
:param points: np.array
:return: n... | gpl-2.0 |
poryfly/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 |
mjlong/openmc | tests/test_mgxs_library_nuclides/test_mgxs_library_nuclides.py | 2 | 2643 | #!/usr/bin/env python
import os
import sys
import glob
import hashlib
sys.path.insert(0, os.pardir)
from testing_harness import PyAPITestHarness
import openmc
import openmc.mgxs
class MGXSTestHarness(PyAPITestHarness):
def _build_inputs(self):
# The openmc.mgxs module needs a summary.h5 file
sel... | mit |
PaddlePaddle/models | PaddleCV/gan/trainer/CGAN.py | 1 | 8924 | #copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve.
#
#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 l... | apache-2.0 |
woozzu/pylearn2 | pylearn2/scripts/datasets/browse_norb.py | 44 | 15741 | #!/usr/bin/env python
"""
A browser for the NORB and small NORB datasets. Navigate the images by
choosing the values for the label vector. Note that for the 'big' NORB
dataset, you can only set the first 5 label dimensions. You can then cycle
through the 3-12 images that fit those labels.
"""
import sys
import os
imp... | bsd-3-clause |
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