text string |
|---|
<gh_stars>0
"""
=====================================
Linear Gaussian Models for Regression
=====================================
In this example, we use a MVN to approximate a linear function and a mixture
of MVNs to approximate a nonlinear function. We estimate p(x, y) first and
then we compute the conditional distr... |
<filename>wine-quality-prediction/code/regression_logistic.py
import csv
import numpy as np
from scipy.optimize import fmin_bfgs
import matplotlib.pyplot as plt
import pandas as pd
import pylab as pl
"""
Uses L2 Logistic Regression on the wine data. L2 Regression is used to help control overfitting.
This is shown fo... |
<filename>attitude/error/axes.py
"""
Functions for converting fit parameters into covariance
and hyperbolic axes. These all operate in axis-aligned
space---rotation into global coordinate systems should
occur after these transformations are applied.
"""
from __future__ import division
import numpy as N
from scipy.stats... |
import sys
import time
import numpy as np
import multiprocessing
from joblib import Parallel, delayed
# metrics
from scipy.spatial.distance import cdist
from sklearn.metrics import average_precision_score
def prec(actual, predicted, k):
act_set = set(actual)
if k is not None:
pred_set = se... |
<gh_stars>0
from typing import Iterable, Optional, List, Tuple
import copy
import numpy as np
import json
from scipy.linalg import expm
def swap_forward(iterable_item: Iterable,
starting_index: Optional[int] = 0):
new_sequence = copy.deepcopy(iterable_item)
for i in range(starting_index, len(i... |
import os
import numpy as np
import scipy.io as sio
from skimage import io, transform
import skimage
from src.faceutil import mesh
import argparse
import ast
import copy
import multiprocessing
import math
from config import *
from src.dataset.uv_face import uv_coords
from src.dataset.base_face import bfm, get_transfor... |
<filename>SSVDpkg_663proj21/SSVDversion2.py
## This is the first-step optimization, based on SSVDversion1.
## Based on linear algebra,
## computation about about Y, Z, and the Kronecker product are replaced.
import numpy as np
import scipy.linalg as la
def get_tilde(lam, tilde_hat, w):
"""Get the tilde vector g... |
import numpy as np
from py_wake.wind_turbines import OneTypeWindTurbines
from scipy.special import gamma
from scipy.interpolate import UnivariateSpline
from py_wake.site._site import UniformSite
power_curve = np.array([[2.99000000e+00, 0.00000000e+00],
[3.00000000e+00, 3.99687614e+01],
... |
import os
import cv2
import sys
import time
# import ssim
import imageio
import tensorflow as tf
import scipy.misc as sm
import scipy.io as sio
import numpy as np
import skimage.measure as measure
from mcnet import MCNET
from utils import *
from os import listdir, makedirs, system
from os.path import exists
from argp... |
<gh_stars>0
import pandas as pd
import numpy as np
import bisect
import os
import multiprocessing as mp
from tqdm import tqdm
from itertools import chain
from scipy import interpolate
class FemtoMesh:
def __init__(self, name):
self.data_frame = None
self.data_frame_name = name
self.chun... |
#!/usr/bin/env python3
# MIT License
#
# Copyright (c) 2020 UiL OTS labs
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to... |
<gh_stars>1-10
import numpy as np
from autograd.extend import VSpace
import scipy
class SparseArrayVSpace(VSpace):
def __init__(self, value):
self.t = type(value)
self.value = self.t(value)
self.shape = value.shape
self.dtype = value.dtype
@property
def size(self):
... |
import os
import scipy
import scipy.stats
import numpy as np
from collections import namedtuple
from functools import partial
from io import StringIO
import fitz
from lxml import etree
BLOCK_IMAGE = 1
BLOCK_TEXT = 0
Block = namedtuple("Block", ['filename','tl','br','w','h','content', 'type', 'density'])
SBlock = nam... |
from scipy.special import expit
from rbm import RBM
from sampler import VanillaSampler, PartitionedSampler
from trainer import VanillaTrainier
import numpy as np
import datasets, performance, plotter, mnist, pickle
import argparse
from warnings import warn
warn("Currently will not work. Relies on older buggy implemen... |
import sympy
import tkinter
x = sympy.Symbol('x')
print(sympy.integrate(3/x**2,(x,1,'+oo')))
class Application(tkinter.Frame):
def __init__(self, master=None):
super().__init__(master)
self.master = master
self.pack()
self.create_widgets()
def create_widgets(self):
... |
<reponame>bbrister/cudaImageWarp<gh_stars>10-100
"""
Warp an image using scipy. This is a CPU-only implementation of cudaImageWarp.py.
(c) <NAME> 2018-2021
"""
import numpy as np
import scipy.ndimage as nd
import pyCudaImageWarp
import concurrent.futures
import os
from .cudaImageWarp import __check_inputs
# Place ... |
"""
Routines for the orthogonal rangefinder problem:
Given an m-by-n input matrix A, find a matrix Q with k << min(m, n)
orthogonal columns where the operator norm || A - Q Q' A ||_2 is small.
This problem can be considered where k is given or when a tolerance "tol"
is given and we require || A - Q Q'... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Aug 21 11:20:57 2020
@author: joel
"""
import numpy as np
import scipy.stats as st
import matplotlib.pyplot as plt
# Histograms
# RV lognormal
N = 10**5
log_rv = np.random.lognormal(size=N)
# RV normal with same SD
norm_rv = np.random.normal(scale=l... |
<reponame>SStroteich/stella-1<gh_stars>0
from scipy.io import netcdf
import numpy as np
import numpy.matlib
tave = 900
basedir = '/marconi_work/FUA34_MULTEI/stonge0_FUA34/rad_test/2nd_deriv/T1/'
basedir = '/marconi_work/FUA34_MULTEI/stonge0_FUA34/rad_test/2nd_deriv/rho_scan2/r0.001/'
basedir = '/marconi_work/FUA34... |
<reponame>brmprnk/lindel423<gh_stars>0
import numpy as np
import scipy.sparse as sparse
def gen_indel(sequence,cut_site):
'''This is the function that used to generate all possible unique indels and
list the redundant classes which will be combined after'''
nt = ['A','T','C','G']
up = sequence[0:cut_si... |
import numpy as np
from scipy.spatial import Delaunay
from sklearn.linear_model import LinearRegression
from collections import defaultdict
from math import inf
def closest_points(point, points, k):
K = []
for i in range(len(points)):
point2 = [points[i][0][0], points[i][1][0]] # points[i][0] + point... |
<gh_stars>1-10
from typing import Tuple, Optional, Union, Iterable, List
from numpy import ndarray
from pandas import DataFrame, Series
from scipy.optimize import fmin
from scipy.stats import rv_continuous, rv_discrete
from scipy.stats._distn_infrastructure import rv_generic
from probability.distributions.functions.c... |
<gh_stars>1-10
import numpy as np
from cv2 import cv2
from scipy import signal
#defining a few filters
vkernel = np.array([[-1, 0, 1], [-1, 0, 1], [-1, 0, 1]])
hkernel = np.array([[-1, -1, -1], [0, 0, 0], [1, 1, 1]])
testkernel = np.array([[-1, -1, -1], [-1, 8, -1], [-1, -1, -1]])
lpf = np.array([[1/9, 1/9, 1/9], [1/9... |
import napari
import time
from napari._qt.qthreading import thread_worker
from cv2.cv2 import VideoCapture
from napari.layers import Points
from skimage.color import rgb2gray
import numpy as np
from skimage import draw
camera_index = 0
def acquire_image(camera : VideoCapture):
"""
Acquires an image from a gi... |
<filename>pyavia/core/interpolate.py
"""
**pyavia.interpolate** provides functions for interpolation that are
specific to engineering tasks, for convenience or not otherwise covered by
NumPy.
"""
# Last updated: 20 January 2021 by <NAME>
from __future__ import annotations
from collections import Sequence
from copy im... |
import numpy as np
import time
import cv2
from scipy.signal import argrelextrema
class Analyzer():
def __init__(self):
self.avg_bpm = self.cnt = self.fps = self.bpm = self.breathes = 0
self.up = self.down = -1
self.index = 1
self.incoming_frame = self.outgoing_frame = np.zeros((10, 10))
self.face = False
... |
<filename>jax/_src/third_party/scipy/linalg.py<gh_stars>1-10
import scipy.linalg
from jax import jit, lax
from jax._src.numpy import lax_numpy as jnp
from jax._src.numpy.linalg import norm
from jax._src.numpy.util import _wraps
from jax._src.scipy.linalg import rsf2csf, schur
@jit
def _algorithm_11_1_1(F, T):
# Alg... |
#shape update shape
import sys
# set the input file path, you have to change this path
mod_path = '/Users/Simo//Documents/energyanalytics/energyanalytics/disaggregation'
if not (mod_path in sys.path):
sys.path.insert(0, mod_path)
mod_path = '/Users/Simo//Documents/energyanalytics/energyanalytics/disaggregation... |
import os
import numpy as np
import bluefog.torch as bf
import matplotlib.pyplot as plt
import torch
import scipy.io as sio
# Generate different A and b through different seed.
bf.init()
torch.manual_seed(12345 * bf.rank())
def generate_data(m, d):
A = torch.randn(m, d).to(torch.double)
ns = 0.1 * torch.ran... |
<gh_stars>1-10
import logging
import numpy as np
from scipy.fftpack import fft2, fftshift, ifftshift
from pattern.utils import field2intensity
__all__ = ["Field"]
logger = logging.getLogger(__name__)
class Field(object):
"""
Field describes how the final product is formed, including system s... |
import numpy as np
import matplotlib.pyplot as plt
from scipy import integrate
import numba
from numba import jit
u_inf = 1
# defines the cylinder
R = 1.0
theta = np.linspace(0, 2 * np.pi, 100)
# coordinates of the cylinder
x_cylinder, y_cylinder = R * np.cos(theta), R * np.sin(theta)
size = 4
plt.figure(figsize=... |
import numpy as np
import scipy
import copy
import scipy.sparse
class LaplacianRigidEnergy:
def __init__(self, mesh, vertices, cregu):
self.cT = scipy.sparse.kron(
mesh.adjacencies.Laplacian.T * mesh.adjacencies.Laplacian,
scipy.sparse.eye(3),
).tocsr()
self.Vref = ... |
"""Definition of volume phase scattering functions"""
import numpy as np
import sympy as sp
from functools import partial, update_wrapper
from .scatter import Scatter
from .rtplots import polarplot
class Volume(Scatter):
"""basic volume class"""
def __init__(self, **kwargs):
self.omega = kwargs.pop(... |
<filename>Investigation/condition_functions.py
# -*- coding: utf-8 -*-
"""
Created on Fri Nov 15 07:11:05 2019
@author: thele
"""
import scipy.signal as signal
import pickle
import numpy as np
from .scoring.Last_score import final_score_cls
from skimage.feature import blob_log
import time
def mock_peak_check(anchor,... |
import logging
import os
import sys
from collections import Counter
import SimpleITK as sitk
import matplotlib.patches as mpatches
import matplotlib.pyplot as plt
import matplotlib.transforms as transforms
import numpy as np
from matplotlib.ticker import PercentFormatter
from sklearn.metrics import confusion_matrix
f... |
from typing import Dict, Union
from scipy.stats._distn_infrastructure import rv_frozen
class Surveyor:
"""Represents an individual who will participate in the survey.
Parameters
----------
name : str
Unique name for the surveyor
team_name : str
Name of the parent team
surveyo... |
<gh_stars>1-10
from typing import Dict, Union, Iterable, Callable, Sequence, List
import itertools
import re
import sympy as sp
import pycparser.c_ast as c_ast
import checkdp.transform.constants as constants
from checkdp.transform.typesystem import TypeSystem
from checkdp.transform.random_distance import AlignmentIndex... |
<reponame>Guydada/MIND-Recommender-System-Ptoject-Pytorch-TF-IDF--Deep-Learning<filename>mind.py<gh_stars>1-10
import os
import pickle
from collections import OrderedDict
from typing import Union
import click_spinner
import torch
import typer
import numpy as np
from sklearn.feature_extraction.text import TfidfVectorize... |
<gh_stars>0
"""
*Audio Interval*
A difference between two audio frequencies.
"""
from __future__ import annotations
from dataclasses import dataclass
from enum import Enum
from fractions import Fraction
from ._ratio import FrequencyRatio
__all__ = ["Interval"]
class AudioInterval:
pass
# class _Inte... |
"""
This file is part of Seten which is released under the MIT License (MIT).
See file LICENSE or go to https://github.com/gungorbudak/seten-cli/blob/master/LICENSE
for full license details.
"""
import random
import numpy as np
from scipy import stats
from seten.multi_comp import fdr_correction
from seten.multi_comp im... |
<filename>src/optimize.py
import numpy as np
import scipy as sp
from functools import partial
from sklearn import metrics
from collections import Counter
class OptimizedRounder(object):
def __init__(self):
self.coef_ = 0
def _kappa_loss(self, coef, X, y):
X_p = np.copy(X)
for i, pred i... |
<reponame>MatthewRalston/ecopy
import numpy as np
from pandas import DataFrame, Series
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from scipy.stats import pearsonr
from ..regression import isotonic
from ..ordination import pca, pcoa
class MDS(object):
'''
Docstring for function ecopy.pca
===... |
<filename>libs/cvae.py
'''
Copyright (c) 2020. IIP Lab, Wuhan University
Author: <NAME>
'''
import os
import sys
sys.path.append("libs")
import numpy as np
import scipy as sp
import scipy.io as sio
from tensorflow.keras import optimizers
from layers import mse
class CollaborativeVAE():
def __i... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
# CODE NAME HERE
# CODE DESCRIPTION HERE
Created on 2020-04-05 11:44:00
@author: cook
"""
import numpy as np
import os
from scipy.signal import medfilt,convolve2d
from astropy.table import Table
from astropy.io import fits
import argparse
from apero import core
from... |
"""
This Module being called from .sh script for the problem 1
Runs the pre-trained GAN, DCGAN model and saves the generated 32 fake images
"""
# general
import random
import os
import numpy as np
# dl related
import torch
# custom modules
import parser
from generator import Generator
#from discriminator import Dis... |
'''
Defines the UnitarySequenceEntry class.
'''
import numpy as np
import scipy.sparse
from typing import List
from .unitary import Unitary
class UnitarySequenceEntry:
'''
Represents an entry in a unitary sequence applied to
a specific subset of qubits in a system.
:param unitary: The unitary operat... |
# coding: utf-8
# DO NOT EDIT
# Autogenerated from the notebook glm_weights.ipynb.
# Edit the notebook and then sync the output with this file.
#
# flake8: noqa
# DO NOT EDIT
# # 加权广义线性模型
import numpy as np
import pandas as pd
import statsmodels.formula.api as smf
import statsmodels.api as sm
# ## 加权GLM：泊松响应数据
#
# ... |
# Licensed under an MIT open source license - see LICENSE
from __future__ import print_function, absolute_import, division
import numpy as np
from scipy.stats import binned_statistic
import astropy.units as u
from astropy.coordinates import Angle
from scipy.stats import t as t_dist
def pspec(psd2, nbins=None, return... |
from tqdm import tqdm
import sklearn
from scipy.stats import binom_test
import numpy as np
import logging
import cPickle as pickle
import random
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style("whitegrid")
from argparse import ArgumentParser
from path import Path
from deepx.sequence import Characte... |
# To Train and Test an AI using the German Traffic Sign Recognition "Benchmark"-Dataset
# Requires the German Traffic Sign Recogintion Benchmark somewhere around you can point a path to
# can be found under http://benchmark.ini.rub.de/?section=gtsdb&subsection=dataset
# but is annoyingly strong wrapped.
import matplo... |
<reponame>jppaiement/fSEIR_simulator
import networkx as nx
import matplotlib.pyplot as plt
import matplotlib
import getopt
import os
import random
import sys
import time
import cartopy.crs as ccrs
import seaborn as sns
import csv
import numpy as np
import pandas as pd
from sklearn.metrics import r2_score
from sklearn.... |
import numpy as np
from skimage import transform, color, restoration, feature
from sklearn.preprocessing import PolynomialFeatures
from sklearn.linear_model import LinearRegression
from scipy import optimize
from scipy import stats
import cv2
from matplotlib import pyplot as plt
def float_to_uint8(frame):
'''
... |
#!/usr/bin/env python
import rospy
from geometry_msgs.msg import PoseStamped
from styx_msgs.msg import Lane, Waypoint
from std_msgs.msg import Int32
from scipy.spatial import KDTree
from sensor_msgs.msg import Image
import cv2
import cv_bridge
import numpy as np
import time
import math
LOOP_HERTZ = 10
class Doernbac... |
<gh_stars>10-100
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
SeedEditor for organ segmentation
Example:
$ seed_editor_qp.py -f head.mat
"""
# import unittest
from optparse import OptionParser
from PyQt5.QtWidgets import *
from scipy.io import loadmat
import numpy as np
import sys
from scipy.spatial import Dela... |
def mix_norm_cdf(x,means,std,weights=-1) :
# calculate cdf(x) of a mixture of normal distributions with
# means: an array containing the mean of each distributions
# std: an array len(means) containing the std deviation of each normal _or_
# a single value which is a common standard deviation for each nor... |
import scipy.misc as misc
import torch
import copy
import torchvision.models as models
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
# FCN Net model class for semantic segmentation
##############################################This is a standart FCN with the lat layer split into prediction o... |
<gh_stars>1-10
"""Implements multinomial and mixed logit models."""
# pylint: disable=invalid-name
import numpy as np
from scipy.stats import t
from time import time
from abc import ABC
import warnings
"""
Notations
---------
N : Number of choice situations
P : Number of observations per panel
J : Number ... |
from file_util import read_first_line_as_integers
from functools import reduce
import statistics
def task1(crab_positions: list[int]) -> int:
median = statistics.median(crab_positions)
return int(sum(map(lambda x: abs(x - median), crab_positions)))
def task2(crab_positions: list[int]) -> int:
crab_posit... |
<reponame>gregstarr/trough
import xarray as xr
import numpy as np
from pathlib import Path
from datetime import datetime, timedelta
from apexpy import Apex
from scipy.interpolate import interp1d
import logging
import warnings
try:
import h5py
except ImportError as imp_err:
warnings.warn(f"Packages required for... |
# ======================================================================
# Copyright CERFACS (October 2018)
# Contributor: <NAME> (<EMAIL>)
#
# This software is governed by the CeCILL-B license under French law and
# abiding by the rules of distribution of free software. You can use,
# modify and/or redistribute ... |
<filename>fun stuff/chart data.py
import math
import statistics
tbl1 = [[-0.01, 0.02, 0.04],
[0.22, 0.22, 0.25],
[1.06, 1.14, 1.00],
[2.15, 1.94, 2.06],
[6.96, 7.85, 7.93],
[10.3, 10.3, 11.0],
[16.8, 15.7, 18.6],
[18.4, 18.3, 17.3],
[19.9, 18.9, 19.5],
[21.0, 21.6, 20.0]]
means = []
sd = []
N = 4
for i in range(len... |
"""
Generate new images
"""
import os
import numpy as np
import torch
import torchvision
import argparse as ap
from matplotlib import pyplot as plt
import pickle as pkl
import pandas as pd
from scipy.misc import imsave
def build_parser():
parser = ap.ArgumentParser()
parser.add_argument('--model', '-m', help... |
import tensorflow as tf
tf.set_random_seed(42)
import numpy as np
from scipy import integrate
import neural_networks
import kovasznay_flow_problem
import matplotlib.pyplot as plt
import sys, getopt
class sampling_from_dataset:
def __init__(self, filepath, total_samples):
self.filepath = filepath
self.total_sam... |
<reponame>sylvain2002/CBM101<gh_stars>0
# Importing the needed python packages
import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import odeint
import time
import sys
from pylab import *
from matplotlib.patches import Rectangle
# Defining the right hand side of the ODEs (rate of changes of predat... |
<filename>grb/attack/speit.py
import random
import numpy as np
import scipy.sparse as sp
import torch
import torch.nn.functional as F
import grb.utils as utils
from grb.attack.base import InjectionAttack
from grb.evaluator import metric
class SPEIT(InjectionAttack):
def __init__(self,
lr,
... |
import numpy as np
import pytest
from numpy.testing import assert_allclose
from ..linalg.cholesky import ChoInv, ChoInvPivot, cholesky_factor, fixed_cholesky
from ..linalg.cholesky import jit_cholesky, _check_cholesky_inputs, pivot_cholesky, _pivot_transpose
from ..linalg.linalg_utils import calc_Ainv, calc_A_deriv, ca... |
#! /usr/bin/env python3
# Copyright 2021 OVHCloud
#
# 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 app... |
from fractions import Fraction
def sqrt2(it):
dem = 2
for i in range(it):
dem = 2 + Fraction(1, dem)
return(str(1 + 1/dem).split('/'))
cont = 0
for i in range(1, 1000+1):
N = sqrt2(i)
if len(N[0]) > len(N[1]):
cont += 1
print(cont) |
<filename>content/downloads/code/minesweeper.py
"""
Matplotlib Minesweeper
----------------------
A simple Minesweeper implementation in matplotlib.
Author: <NAME> <<EMAIL>>, Dec. 2012
License: BSD
"""
import numpy as np
from itertools import product
from scipy.signal import convolve2d
import matplotlib.pyplot as plt
... |
<gh_stars>1-10
"""Example 05
Section: Rectangular 230 x 500
Compression steel: 3 layer, Tension steel: 2 layers
Output: xu and report of the section.
"""
from scipy.optimize import brentq
from rcdesign.is456.stressblock import LSMStressBlock
from rcdesign.is456.concrete import Concrete
from rcdesign.is456.rebar impor... |
<filename>gw_processing.py
from typing import List
import numpy as np
from pycbc.types import TimeSeries
from scipy.signal.windows import tukey
from gw_data import SIGNAL_DELTA_T, N_SIGNALS
def timeseries_from_signal(sig: np.ndarray) -> TimeSeries:
return TimeSeries(sig, epoch=0, delta_t=SIGNAL_DELTA_T)
def t... |
<filename>RSpring/rtr_copilot/inverted_pendulum_rtr_ompl/inv_pen_sim.py<gh_stars>1-10
from numpy import sin, cos
import numpy as np
import matplotlib.pyplot as plt
import scipy.integrate as integrate
import matplotlib.animation as animation
import math
xaxis = 5
class DoublePendulum:
"""Double Pendulum Class
... |
<filename>models/lrp_modules.py<gh_stars>1-10
"""
This module implements PyTorch Modules that support LRP. This is done by
re-implementing the forward pass in NumPy and then implementing a custom
backward pass using LRP rules.
"""
from abc import ABC, abstractmethod
from typing import Tuple
import numpy as np
from sci... |
<reponame>sometimescasey/pca_animations
'''
Question 1 Skeleton Code
Here you should implement and evaluate the Conditional Gaussian classifier.
<NAME>
998816973
'''
import data
import numpy as np
import matplotlib.pyplot as plt
from scipy.misc import logsumexp
from PIL import Image, ImageFilter
def ... |
import re
import sys
import numpy as np
import scipy.sparse as sparse
class ProgressBar(object):
def __init__(self, N, length=40):
# Protect against division by zero (N = 0 results in full bar being printed)
self.N = max(1, N)
self.nf = float(self.N)
self.length = length
... |
<filename>echem_testphoto.py
import time, copy
import os, os.path
import sys
import numpy
from PyQt4.QtCore import *
from PyQt4.QtGui import *
from scipy import optimize
from echem_plate_ui import *
from echem_plate_math import *
homepath='C:/Users/Gregoire/Documents/CaltechWork/echemdrop/20130301_CuZnSnFe_Plate3_365... |
<gh_stars>0
import scipy.io
from tkinter.filedialog import askopenfilename
import time
import numpy as np
from copy import deepcopy
#import h5py
from functools import partial
from numpy import array, ndarray
class ModelicaDataItem(object):
def __init__(self, name, data):
self.name = name
self.dat... |
from pathlib import Path
import torch
from torch.utils.data import Dataset
import os, sys
from PIL import Image
import datasets.transforms_w_depth as T
from scipy import io
import numpy as np
#import matplotlib.pyplot as plt
def box_cxcywh_to_xyxy(x):
"""Convert the coordinate format."""
# [x_center, y_center... |
<gh_stars>0
import numpy as np
from scipy.optimize import linprog
c = np.array([2, -1, 1, 0, 0, 0]) * -1
A_eq = [
[2, 1, -2, 1, 0, 0],
[4, -1, 2, 0, -1, 0],
[2, 3, -1, 0, 0, -1]
]
b_eq = [8, 2, 4]
def callback(xk, **kwargs):
np.set_printoptions(precision=3)
np.set_printoptions(suppress=True)
... |
<reponame>UASLab/OpenFlightAnalysis
"""
University of Minnesota
Aerospace Engineering and Mechanics - UAV Lab
Copyright 2019 Regents of the University of Minnesota
See: LICENSE.md for complete license details
Author: <NAME>
"""
import numpy as np
import AirData
# Constants
#%%
# Define the Cost Function for the Op... |
import os, sys
from statistics import stdev
solvers = ['cvc4', 'z3'] # TODO If adding a new solver, add it here
theories = ['qf_slia'] # TODO If adding a new theory, add it here
# The buckets for the features to be created
# For example, if buckets = [9, 10, 100],
# four features will be returned:
# -- Number o... |
from train_helper import run_multi_bleu, Meteor
from collections import Counter
from tqdm import tqdm
import statistics
import rouge
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--references', type=str, default=None)
parser.add_argument('--generations', type=str, default=None)
args = pars... |
<filename>embedd.py<gh_stars>1-10
import argparse
import numpy as np
import glob
import torch
import torch.nn.functional as F
import os
import sys
import pathlib
from kaldi_io import read_mat_scp, open_or_fd, write_vec_flt
import model as model_
import scipy.io as sio
from utils.utils import *
from librosa.feature impo... |
<reponame>kechunl/histoapp_tools
#!/usr/bin/env python3
# Copyright (c) <NAME> 2011, Germany. All rights reserved.
# Transforms points based on the transformation in a sqreg file.
import os
import sqlite3
import numpy as np
import scipy.interpolate
def deformation_from_file_no_interp(filepath: str):
if not os... |
import json
from train_mountaincar import fqi, warm_start, transfer_learning
import configargparse
import torch
import torch.optim as optim
import scipy
import sys
sys.path.append('../')
from environments import MountainCarEnv, Continuous_MountainCarEnv
from models.agents import NFQAgent
from models.networks import NF... |
<reponame>stefanches7/gin-train<filename>gin_train/metrics.py
import sklearn.metrics as skm
import pandas as pd
import numpy as np
from collections import OrderedDict
import gin
# --------------------------------------------
# Combined metrics
@gin.configurable
class BootstrapMetric:
def __init__(self, metric, n... |
<gh_stars>1-10
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed May 29 16:40:20 2019
@author: gparkes
"""
import numpy as np
from scipy import integrate, ndimage
import matplotlib.pyplot as plt
def task_1():
x = 10. / 100. # x is a constant because we are dealing with a cubical container.
a =... |
<gh_stars>1-10
import os
import numpy as np
from scipy import signal, misc
import functions
basePath = './'
print(os.listdir(basePath))
print('Loading train_data')
ST = np.load(basePath+"/train_data/ST_full.npy")
print(ST.shape)
STU = np.unique(ST,axis=0)
del ST
print(STU.shape)
STS = np.split(STU,2,axis=1)
del STU... |
import time
import copy
import pathlib
import pickle
import hjson
import gym
import numpy as np
from mujoco_py import load_model_from_path, MjSim, MjViewer
from motor_skills.envs.mj_jaco import MjJacoEnv
from mujoco_py import cymj
from scipy.spatial.transform import Rotation as R
from motor_skills.cip.ImpedanceCIP im... |
<reponame>ddland/TIS-TN-python
#!/usr/bin/env python
import logging
try:
from sympy import pi, cos, sin, sqrt, arg, exp, Abs, S
from sympy import integrate, Rational, nfloat, conjugate, Symbol
from sympy.functions.special.delta_functions import Piecewise
except ImportError as e:
print("sympy kon niet ... |
<gh_stars>10-100
import numpy as np
from scipy import ndimage
def get_morphological_patch(dimension, shape):
"""
:param dimension: dimension of the image (NOT the shape).
:param shape: circle or square.
:return: morphological patch as ndimage
"""
if shape == 'circle':
morpho_patch = nd... |
'''Plotting library for CluStR '''
import os
import clustr
import corner
import PyPDF2
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import scipy.stats as stats
from matplotlib.ticker import LogFormatter, ScalarFormatter, FormatStrFormatter
#import seaborn as ssb
#plt.style.use('seaborn')
#matpl... |
#!/usr/bin/env python
"""
Calculate the distances between fixed-dimensional vectors and write to file.
Author: <NAME>
Contact: <EMAIL>
Date: 2014-2015
"""
from scipy.spatial.distance import pdist
import argparse
import datetime
import sys
import scipy.linalg
import numpy as np
blas_norm, = scipy.linalg.get_blas_fun... |
#TODO: change counterID to triple (gene,mut,mutval) ID
from neuron import h
import matplotlib
matplotlib.use('Agg')
import numpy
from pylab import *
import mytools
import pickle
import time
import sys
import scipy.io
morphology_file = "morphologies/cell1.asc"
biophys_file = "models/L5PCbiophys3.hoc"
template_file = "... |
import numpy as np
import pandas as pd
from scipy.spatial.distance import cdist
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
from plotutils import set_style, savefig
def poisson_disc_sample(array_radius, fixation_radius, radius, candidates):
"""Find positions using poisson-disc ... |
import numpy as np
import scipy.optimize
import pandas as pd
import scipy.io
import scipy
import scipy.sparse
import time
import cvxopt
# import time
#Helper functions
def prox(eta_0, y, B):
"""Prox_{-eta_0 f}(y) = argmin_x {-f(x) + \frac{1}{2\eta_0}\|x-y\|^2} where
f = x^T B x,
B = block_diag(N_m diag(\b... |
'''
Simple script that reads .wav-files from the UrbanSound8K_modified_v2 dataset
into a python array using scipy's wavfile library and stores them in three
labeled python arrays for TRAINING, VALIDATION, and TESTING. Then it exports
these using pickle.
@date 2017-07-01
'''
import sys
import pickle
from scipy.io impo... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import geocoder
import numpy as np
import scipy.ndimage as ndimage
import scipy.ndimage.filters as filters
import matplotlib.pyplot as plt
from utils import create_divisions
"""
Copyright 2019 <NAME>
Licensed under the Apache License, Version 2.0 (the "L... |
<reponame>tanxicccc/rsopt
import numpy as np
from scipy.constants import c as clight
def dummy(H):
return 0
def calculate_emittance(bunch):
x = bunch.x
xp = bunch.ux
y = bunch.y
yp = bunch.uy
enx = np.sqrt(np.average(x**2) * np.average(xp**2) - np.average(x * xp)**2)
eny = np.sqrt(n... |
#%%
from pikapi.orientation_estimator import RotationEstimator
rotation_estimator = RotationEstimator(0.70, True)
import numpy as np
rotation_estimator.process_gyro(np.array([-0.00346511, -0.00172339, -0.00172537]), 0.1)
rotation_estimator.process_accel(np.array([0.00913589, -0.02, -9.00]))
rotation_estimator.get_t... |
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