arxiv_id stringlengths 0 16 | text stringlengths 10 1.65M |
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# -*- coding: utf-8 -*-
import tensorflow as tf
import pandas as pd
import numpy as np
import os
import matplotlib.pyplot as plt
# 训练集的路径
train_file = '/media/jxnu/Files/dog_vs_cat/train'
def get_file(file_path):
cats = []
label_cats = []
dogs = []
label_dogs = []
for file in os.listdir(file_pat... | |
from deepnote.modules import Metric, Note
import numpy as np
from scipy.stats import entropy
import itertools
from .repr import MusicRepr
from .scale import Scale
def pitch_histogram_entropy(seq : MusicRepr, window : int = 1, pitch_class: bool = False, return_probs=True):
"""
seq : input sequence
window :... | |
# Copyright 2020 NXP Semiconductors
# Copyright 2020 Marco Franchi
#
# This file was copied from NXP Semiconductors PyeIQ project respecting its
# rights. All the modified parts below are according to NXP Semiconductors PyeIQ
# project`s LICENSE terms.
#
# Reference: https://source.codeaurora.org/external/imxsupport/py... | |
"""
Author: Peratham Wiriyathammabhum
"""
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy import stats
eps = np.finfo(float).eps
"""
Importance sampling is a framework. It enables estimation of an r.v. X from a black box target distribution f
using a known proposal distribution ... | |
# !/cs/usr/liorf/PycharmProjects/proj_scwgbs/venv/bin python
# !/cs/usr/liorf/PycharmProjects/proj_scwgbs/venv/bin python
import argparse
import collections
import copy
import glob
import os
import re
import sys
import numpy as np
import pandas as pd
from tqdm import tqdm
sys.path.append(os.path.dirname(os.getcwd())... | |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn
plt.style.use('ggplot')
import arch
from arch.unitroot import ADF
from statsmodels.graphics.tsaplots import plot_acf, plot_pacf
from statsmodels.tsa.seasonal import seasonal_decompose
import os
import datetime as dt
#
# dff_df_R001... | |
## Leetcode problem 210: Course schedule II.
#https://leetcode.com/problems/course-schedule-ii/
#based on topological sorting.
import numpy as np
import algorith.clr_book.ch22_elemtary_graph.graph as gr
from typing import List
class Solution():
def findOrder(self, numCourses: int, prerequisites: List[List[int]])... | |
# written by LazyGuyWithRSI
import pyautogui
import ctypes
import time
from PIL import ImageGrab
import numpy as np
import cv2 as cv
import win32api
import keyboard
from configparser import ConfigParser
# TODO HOTKEY not implemented yet
# change HOTKEY to whatever key you want (ex. 'a', 'f2') even modifiers (ex. 'ctr... | |
import multiprocessing
import re
from pyomyo import Myo, emg_mode
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import animation
import bone
import serial_utils as s
# Use device manager to find the Arduino's serial port.
COM_PORT = "COM9"
RESET_SCALE = True
LEGACY_DECODE = False # If false, will... | |
#!/usr/bin/env python
# coding: utf-8
# In[1]:
import sys
sys.path.insert(0, '../py')
from graviti import *
from numpy.linalg import norm
import numpy as np
import os
import os.path
from os import path
import sys
import glob
import h5py
import seaborn as sns
import matplotlib.pyplot as plt
import matplotlib
#matp... | |
#!/usr/bin/python
# -*- coding: latin-1 -*-
"""
Rays are stand-ins for lightrays heading from the camera through the scene.
.. moduleauthor:: Adrian Köring
"""
import numpy as np
from padvinder.util import normalize
from padvinder.util import check_finite
class Ray(object):
"""
A ray consists of a starting ... | |
#import matplotlib
#matplotlib.use('Agg')
from matplotlib.animation import FuncAnimation, writers
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import cv2
import numpy as np
skeleton_parents = [0,1,2,0,4,5,0,7,8,9,8,11,12,8,14,15] #h36m
#skeleton_parents = [0,0,1,2,0,0,5,6,7,8,0,0,11,12,1... | |
"""
Reward normalization schemes.
"""
from math import sqrt
import numpy as np
class RewardNormalizer:
"""
Normalize rewards in rollouts with a gradually
updating divisor.
"""
def __init__(self, update_rate=0.05, discount=0.0, scale=1.0, epsilon=1e-5):
"""
Create a reward normal... | |
# Copyright (c) 2020 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 appl... | |
# Copyright 2019 DIVERSIS Software. All Rights Reserved.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law o... | |
import xspec
import numpy as n
import sys
nh_vals = 10**n.arange(-2,4,0.05)
z_vals = 10**n.arange(-3,0.68,0.025)
nh_val = 1000.# nh_vals[0]
redshift = 2. # z_vals[0]
def get_fraction_obs(nh_val, redshift, kev_min_erosita = 0.5, kev_max_erosita = 2.0):
print(nh_val, redshift)
kev_min_erosita_RF = kev_min_erosi... | |
#Write by Chiru Ge, contact: gechiru@126.com
# -*- coding: utf-8 -*-
## use GPU
import os
import tensorflow as tf
os.environ['CUDA_VISIBLE_DEVICES']='0'
config=tf.ConfigProto()
config.gpu_options.allow_growth= True
sess=tf.Session(config=config)
import numpy as np
import matplotlib.pyplot as plt
import scipy.io as si... | |
import re
import os
import time
import itertools as it
import numpy as np
# logger
def logger(verbose = False):
def log(*arg):
if verbose:
print(*arg)
return log
# time utils
def tic():
return time.time()
def toc(start, msg=None):
end = time.time()
print("Done en {}s".format((... | |
#!/usr/bin/env python
import argparse
import shutil
import keras
from keras.models import Sequential
import numpy as np
np.random.seed(1234)
import cPickle as pickle
import h5py
from keras.layers import Conv1D, MaxPool1D,Dense, Activation, Dropout, GaussianDropout, ActivityRegularization, Flatten
from keras.optimizers... | |
import os
import gzip
import urllib.request
import numpy as np
import time
import zipfile
import io
from scipy.io.wavfile import read as wav_read
from tqdm import tqdm
class warblr:
"""Binary audio classification, presence or absence of a bird.
`Warblr <http://machine-listening.eecs.qmul.ac.uk/bird-audio-det... | |
from typing import Any, Dict, Tuple, Union
import gym
import numpy as np
import torch
import torch.optim as opt
from torch.autograd import Variable
from ....environments import VecEnv
from ...common import RolloutBuffer, get_env_properties, get_model, safe_mean
from ..base import OnPolicyAgent
class VPG(OnPolicyAge... | |
# BSD 3-Clause License.
#
# Copyright (c) 2019-2021 Robert A. Milton. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notic... | |
import pandas as pd
from matplotlib import pyplot as plt
import numpy as np
from sklearn.preprocessing import MinMaxScaler
import random
MAXLIFE = 120
SCALE = 1
RESCALE = 1
true_rul = []
test_engine_id = 0
training_engine_id = 0
def kink_RUL(cycle_list, max_cycle):
'''
Piecewise linear functi... | |
from typing import Tuple, List, Any, Optional
from .connection import Connection
from .drone_connection import DroneConnection
from .window_manager import LocationWindowManager, TimeWindowManager
from .waypoint_manager import WaypointManager
from .event_manager import EventManager
from common.protocol import Protocol
f... | |
import itertools
from tempfile import NamedTemporaryFile
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
from bokeh.plotting import figure, output_file
def get_validation_plot(true_value, prediction):
output_file(NamedTemporaryFile().name)
x_min = min(min(true_value), min(prediction))
... | |
# Copyright 2020 Virginia Polytechnic Institute and State University.
""" OpenFOAM I/O.
These functions are accesible from ``dafi.random_field.foam``.
"""
# standard library imports
import numpy as np
import os
import shutil
import re
import tempfile
import subprocess
# global variables
NDIM = {'scalar': 1,
... | |
"""Collection of region proposal related utils
The codes were largely taken from the original py-faster-rcnn
(https://github.com/rbgirshick/py-faster-rcnn), and translated
into TensorFlow. Especially, each part was from the following:
1. _whctrs, _mkanchors, _ratio_enum, _scale_enum, get_anchors
- ${py-faster-rcnn}/... | |
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
import tensorflow as tf
import umap
from tensorflow.keras.callbacks import EarlyStopping, ModelCheckpoint
from tensorflow.keras.layers import Dense, Input
from tensorflow.keras.models import Model, load_model
from sklearn impor... | |
import numpy as np
import condition
import output
import solver
if __name__ == '__main__':
md = 202
nd = 202
u = np.zeros((md, nd))
v = np.zeros((md, nd))
p = np.zeros((md, nd))
u_old = np.zeros((md, nd))
v_old = np.zeros((md, nd))
xp = np.zeros(md)
yp = np.zeros(nd)
# setu... | |
# -*- coding: utf-8 -*-
"""Discrete wavelet transform."""
import math
import numpy as np
import pandas as pd
from sktime.datatypes import convert
from sktime.transformations.base import BaseTransformer
__author__ = "Vincent Nicholson"
class DWTTransformer(BaseTransformer):
"""Discrete Wavelet Transform Transfo... | |
# This function is copied from https://github.com/Rubikplayer/flame-fitting
'''
Copyright 2015 Matthew Loper, Naureen Mahmood and the Max Planck Gesellschaft. All rights reserved.
This software is provided for research purposes only.
By using this software you agree to the terms of the SMPL Model license here ht... | |
# -*- coding: utf-8 -*-
"""
@author: A. Popova
"""
import numpy as np
#old_settings = np.seterr(all='ignore')
def fact(x):
res = 1
for i in range(int(x)):
res *= (i+1.)
return res
data_ = np.genfromtxt(r'in_out/Submatrix.dat')
m = len(data_)
Nu = int(10*m)
dnu = 2*np.pi/Nu
M = np.zeros((m... | |
# -*- coding: utf-8 -*-
"""
Interfaz gráfica para el movimiento armónico de un edificio, de forma similar
a un terremoto.
@author: Anthony Gutiérrez
"""
import numpy as np
import tkinter as tk
from matplotlib.animation import FuncAnimation
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
from matplotlib... | |
import os
import numpy as np
import torch
from tqdm import tqdm
from zs3.dataloaders import make_data_loader
from zs3.modeling.deeplab import DeepLab
from zs3.modeling.sync_batchnorm.replicate import patch_replication_callback
from zs3.dataloaders.datasets import DATASETS_DIRS
from zs3.utils.calculate_weigh... | |
#%% Imports
import pandas as pd
import numpy as np
#import neuprint as npr
from neuprint import Client, fetch_traced_adjacencies, fetch_adjacencies
from neuprint import fetch_synapse_connections
from neuprint import fetch_synapse_connections, NeuronCriteria as NC, SynapseCriteria as SC
from neuprint.utils import conne... | |
import gym
import numpy as np
import pytest
from push_ups import spaces
@pytest.fixture
def env():
return gym.make("CartPole-v1")
def test_equal_spaces(env):
space_1 = spaces.BoxSpace(env.observation_space)
space_2 = spaces.DiscreteSpace(env.action_space)
assert space_1 == space_1
assert space... | |
import os
import numpy as np
import pandas as pd
import xarray as xr
import datetime
import time
import cftime
import warnings
import requests
import shutil
def set_bnds_as_coords(ds):
new_coords_vars = [var for var in ds.data_vars if 'bnds' in var or 'bounds' in var]
ds = ds.set_coords(new_coords_vars)
re... | |
import torch
import numpy as np
import logging
import os
import torch.nn.functional as F
## Get the same logger from main"
logger = logging.getLogger("anti-spoofing")
def train(args, model, device, train_loader, optimizer, epoch):
model.train()
for batch_idx, (_, X1, X2, target) in enumerate(train_loader):
... | |
import numpy as np
import math
import pandas as pd
from random import shuffle
from matplotlib import pyplot as plt
import matplotlib.pyplot as plt
import matplotlib.pyplot as pause
from mpl_toolkits.mplot3d import Axes3D
from time import sleep
import matplotlib.animation as animation
import sys
# DEFAULT P... | |
import numpy as np
# import _proj as proj_lib
import scipy.sparse as sparse
import scipy.sparse.linalg as splinalg
ZERO = "f"
POS = "l"
SOC = "q"
PSD = "s"
EXP = "ep"
EXP_DUAL = "ed"
POWER = "p"
# The ordering of CONES matches SCS.
CONES = [ZERO, POS, SOC, PSD, EXP, EXP_DUAL, POWER]
def parse_cone_dict(cone_dict):
... | |
'''Trains a simple convnet on the MNIST dataset.
based on a keras example by fchollet
Find a way to improve the test accuracy to almost 99%!
FYI, the number of layers and what they do is fine.
But their parameters and other hyperparameters could use some work.
'''
import numpy as np
np.random.seed(1337) # for reprodu... | |
class A:
def __init__(self):
pass
def f1(self, a):
b = 1
c = 2
result = a**b + a**c
return result
def f2(self, a):
b = 1
c = 2
result = a**b + a**c
return result
def f3(self, a):
b = 1
c = 2
... | |
import torch
from torch.utils.data import Dataset
import numpy as np
from .grid_generator import SampleSpec
DEFAULT_PAIRS = 4
DEFAULT_CLASSES = 4
sample_spec = SampleSpec(num_pairs=DEFAULT_PAIRS, num_classes=DEFAULT_CLASSES, im_dim=76, min_cell=15, max_cell=18)
def set_sample_spec(num_pairs, num_classes, reset_every... | |
#!/usr/bin/env python3
import sys
import mpmath as mp
import psr_common
mp.dps=250
mp.mp.dps = 250
if len(sys.argv) != 2:
print("Usage: generate_constants.py outbase")
quit(1)
outbase = sys.argv[1]
constants = {}
# All constants to generate
# variable base value ... | |
"""
Configuration file for pytest, containing global ("session-level") fixtures.
"""
import pytest
from astropy.utils.data import download_file
import vip_hci as vip
@pytest.fixture(scope="session")
def example_dataset():
"""
Download example FITS cube from github + prepare HCIDataset object.
Returns... | |
"""
Copyright (c) 2017 - Philip Paquette
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 use, copy, modify, merge, publish, distribu... | |
import random
from typing import Callable, Dict, List
import albumentations as alb
import numpy as np
import torch
from torch.utils.data import Dataset
from virtex.data.tokenizers import SentencePieceBPETokenizer
from virtex.data import transforms as T
from .arch_captions import ArchCaptionsDatasetRaw
class ArchCap... | |
# -*- coding: utf-8 -*-
"""Ramdom_Search_Classes.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1bJw4Q1F3TYv8okhNqNTtw5CdCFH7-vrh
"""
import numpy as np
import tensorflow as tf
import keras
from keras import models
from keras import layers
from... | |
import unittest
import numpy as np
from photonai_graph.GraphConstruction.graph_constructor_threshold import GraphConstructorThreshold
class ThresholdTests(unittest.TestCase):
def setUp(self):
self.X4d_adjacency = np.ones((20, 20, 20, 1))
self.X4d_features = np.random.rand(20, 20, 20, 1)
s... | |
#!/usr/bin/python3
import argparse
import os
import time
from functools import partial
import numpy as np
import oneflow as flow
from oneflow import nn
from modeling import BertForPreTraining
from utils.ofrecord_data_utils import OfRecordDataLoader
def save_model(module: nn.Module, checkpoint_path: str, epoch: int,... | |
"""
Calculates zonal-mean eddy rms of meridional wind on a given model
level for aquaplanet model data
"""
import numpy as np
import xarray as xr
from ds21grl.misc import get_dim_exp,get_eddy,daysinmonths,get_season_daily
from ds21grl.read_aqua import read_xt_ml_daily
from ds21grl... | |
from sympy import Mul, Add, Rational, Float, Integer, Pow, Function
from .util import ScalarSymbol, FunctionSymbol
import keras
import tensorflow as tf
import numpy as np
class MetaLayer(object):
def __init__(self,type_key=None, name=None,input_key=None,output_key=None,options=None):
self.type_key = type_... | |
from colorsys import rgb_to_hls
from PIL import Image
import matplotlib.pyplot as plt
import numpy as np
from math import sqrt
import json
#TODO: rename file
#TODO: look at turning this into a module instead of a class
#TODO: figure out gamma correction to get relative luminance for colormap y-axis
#TODO: [POTENTIALL... | |
import h5py
import numpy as np
import pandas as pd
import transforms3d
import random
import math
def augment_cloud(Ps, args, return_augmentation_params=False):
"""" Augmentation on XYZ and jittering of everything """
# Ps is a list of point clouds
M = transforms3d.zooms.zfdir2mat(1) # M is 3*3 identity ma... | |
import gym
import numpy as np
import random
from collections import deque
from tensorflow.keras import models, layers, optimizers
import matplotlib.pyplot as plt
class DQN:
def __init__(self, env):
self.env = env
# replay buffer
self.buffer = deque(maxlen=10000)
self.discount = 1
... | |
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import pandas as pd
import numpy as np
from colormap import rgb2hex
class Ibcs():
def ibcs_grid(self,fig
,major_ticks1
,major_ticks2
,perc_ticks
,m_gr
,t_gr
,l_gr
... | |
__all__ = [
'TableToTimeGrid',
'ReverseImageDataAxii',
'TranslateGridOrigin',
]
__displayname__ = 'Transform'
import numpy as np
import vtk
from vtk.numpy_interface import dataset_adapter as dsa
from .. import _helpers, interface
from ..base import FilterBase
############################################... | |
from . import datafetcher
import matplotlib.pyplot as plt
from datetime import datetime, timedelta
from floodsystem.stationdata import build_station_list
from floodsystem.station import MonitoringStation
import numpy as np
from floodsystem.analysis import polyfit
import matplotlib
def plot_water_levels(station, dates,... | |
#Exercícios Numpy-03
#*******************
import numpy as np
arr=np.zeros(10)
print('arr=',arr) | |
import requests
from bs4 import BeautifulSoup
from calendar import monthrange
from datetime import datetime
import pandas as pd
import numpy as np
from sklearn.preprocessing import MinMaxScaler
from utils import getLogger
from ArticleParser import ArticleParser
logger = getLogger("ScrapeDaily")
class ScrapeDaily:
... | |
# Copyright 2021 Lawrence Livermore National Security, LLC
"""
This script is used by cmec-driver to run the ASoP-Coherence metrics.
It is based on the workflow in asop_coherence_example.py and
can be called with the aruments listed below. If no configuration file
with module settings is provided, the settings will be ... | |
# Copyright (C) 2019 Klaus Spanderen
#
# This file is part of QuantLib, a free-software/open-source library
# for financial quantitative analysts and developers - http://quantlib.org/
#
# QuantLib is free software: you can redistribute it and/or modify it under the
# terms of the QuantLib license. You should have rece... | |
# -*- coding: utf-8 -*-
"""
Created on Fri Aug 25 15:31:20 2017
@author: Sadhna Kathuria
"""
## calculate pi using monte carlo simulation
import numpy as np
import matplotlib.pyplot as plt
nums = 1000
iter = 100
#def pi_run(nums,iter):
pi_avg =0
pi_val_list =[]
for i in range(iter):
value = 0
x=np.ran... | |
from flask import Flask,render_template,request,redirect,url_for
import easygui
import sqlite3 as sql
import csv
import random
import math
import numpy as np
from pysqlcipher import dbapi2 as sqlcipher
from sklearn import tree
app=Flask(__name__)
@app.route("/")
def index():
#if request.method== 'POST':
return ren... | |
import numpy as np
import matplotlib.pyplot as plt
N=10000
normal_values = np.random.normal(size=N)
'''
normal_values = np.random.beta(9,0.5, size=N)
'''
dummy, bins, dummy = plt.hist(normal_values, np.sqrt(N), normed=True,
lw=1)
sigma = 1
mu = 0
plt.plot(bins, 1/(sigma * np.sqrt(2 * np.pi)) * np.exp( - (bins -
mu)**... | |
__author__ = 'sibirrer'
from lenstronomy.LensModel.Profiles.cored_density import CoredDensity
import numpy as np
import numpy.testing as npt
import pytest
class TestCoredDensity(object):
"""
tests the Gaussian methods
"""
def setup(self):
self.model = CoredDensity()
def test_function(se... | |
import datetime as dt
import numpy as np
import pandas as pd
import sqlite3
from epl.query import create_and_query, create_conn
def result_calculator(match_results, res_type):
"""
Function to output the league table for a set of matches including MP, GF, GA and points
match_results: dataframe of match re... | |
#!/usr/bin/env python
# native Python imports
import os.path
import sys
import numpy as np
# third-party imports
import cyvcf as vcf
# geminicassandra modules
import version
from ped import load_ped_file
import gene_table
import infotag
from database_cassandra import insert, batch_insert, create_tables
import annota... | |
import unittest
import numpy as np
from pyfiberamp.fibers import YbDopedDoubleCladFiber
from pyfiberamp.steady_state import SteadyStateSimulation
class YbDoubleCladWithGuessTestCase(unittest.TestCase):
@classmethod
def setUpClass(cls):
Yb_number_density = 3e25
core_r = 5e-6
backgroun... | |
#!/usr/bin/python
# -*- coding: utf-8 -*-
import threading
import curses
import FontManager
import numpy as np
import PacketFormat as PF
WIN_WIDTH = 256
WIN_HEIGHT = 32
POLLING_SEC = 0.050
SCROLL_SEC = POLLING_SEC * 1.5
class ScreenThread(threading.Thread):
def __init__(self, dev_so):
"""
・ホストと通信... | |
# Copyright 2017 Rice UniversityDAPIInvoke.split_api_call(value2add)
#
# 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 a... | |
import neural_network_lyapunov.examples.quadrotor2d.quadrotor_2d as\
quadrotor_2d
import neural_network_lyapunov.relu_system as relu_system
import neural_network_lyapunov.lyapunov as lyapunov
import neural_network_lyapunov.feedback_system as feedback_system
import neural_network_lyapunov.train_lyapunov as train_lya... | |
#!/usr/bin/env python -u
# Validation script for GASKAP HI data
#
# Author James Dempsey
# Date 23 Nov 2019
from __future__ import print_function, division
import argparse
import csv
import datetime
import glob
import math
import os
import re
from string import Template
import shutil
import time
import warnings
i... | |
# /usr/bin/env python3
import numpy as np
import pandas as pd
def operaciones():
#debido a quee pandas necesita de Numpys este puede usar los uFuncs de Numpy
#np.sin,cos,tans,arctan.arcsin,exp
ser= pd.Series(np.random.randint(1,90,size=8))
df= pd.DataFrame(np.random.randint(1,90,size=(4,5)),index=['a... | |
import copy
import os
import numpy as np
import pandas as pd
from scipy import optimize
# code models
from src.toric_model import Toric_code
from src.planar_model import Planar_code
from src.xzzx_model import xzzx_code
from src.rotated_surface_model import RotSurCode
# decoders
from decoders import MCMC, single_temp,... | |
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
Tests for the core module.
"""
import numpy as np
from numpy.testing import assert_allclose
import pytest
from ..core import Segment, SegmentationImage
try:
import matplotlib # noqa
HAS_MATPLOTLIB = True
except ImportError:
HAS_MATPLOTL... | |
from time import perf_counter
import warnings
import torch
import torch.nn.functional as F
import numpy as np
from mmdet.datasets.builder import PIPELINES
from mmdet.datasets.pipelines.compose import Compose
@PIPELINES.register_module()
class Timer(Compose):
"""Times a list of transforms and stores result in img... | |
from detectron2 import model_zoo
from detectron2.config import get_cfg
from detectron2.engine import DefaultPredictor
import os, cv2, json
import numpy as np
from progress.bar import Bar
from PIL import Image, ImageDraw
from detectron2.utils.visualizer import Visualizer
from detectron2.data import MetadataCatalog
i... | |
import cv2
import face_recognition
import numpy as np
import pickle
_KNOWN_FACE_ENCODINGS_FILE = 'known-face-encodings.pkl'
_KNOWN_FACE_IDS_FILE = 'known-face-ids.pkl'
# the two lists are parallel. meaning,
# face_encoding at index 0 of 'known_face_encodings' belongs to the face_id at index 0 of 'known_face_ids'
# k... | |
"""
Core MagGeo_Sequential Model
Created on Thur Feb 17, 22
@author: Fernando Benitez-Paez
"""
import datetime as dt
from datetime import timedelta
import sys,os
from matplotlib.pyplot import pause
import pandas as pd
import numpy as np
from tqdm import tqdm
import click
from yaml import load, SafeLoader
from virescl... | |
import numpy as np
import json
import scipy.interpolate
import matplotlib.pyplot as plt
from collections import OrderedDict
from pprint import pprint
import matplotlib
import argparse
##################################################################################################################
## This script allow... | |
from multiprocessing import Pool
from numpy import array
from ..array_array import apply, separate_and_apply
def apply_with_vector(ve, ma, fu, se=False, n_jo=1):
if se:
ap = separate_and_apply
else:
ap = apply
po = Pool(processes=n_jo)
re_ = array(po.starmap(ap, ([ve, ro, fu] f... | |
import scipy
from scipy.misc import imsave
import os
import cv2
import numpy as tf
# Removes items that appear in a listmore than once
def remove_duplicates(image_list):
return list(set(image_list))
# Gets a list of all images (including if it's used multiple times)
def find_images(list_of_folders):
length ... | |
# Basic libs
import os, time, glob, random, pickle, copy, torch
import open3d as o3d
import numpy as np
import open3d
from scipy.spatial.transform import Rotation
from torchvision.transforms import transforms
# Dataset parent class
from torch.utils.data import Dataset
from collections import namedtuple
from common.cam... | |
import numpy as onp
import legate.numpy as np
import timeit
import deriche_numpy as np_impl
def kernel(alpha, imgIn):
k = (1.0 - np.exp(-alpha)) * (1.0 - np.exp(-alpha)) / (
1.0 + alpha * np.exp(-alpha) - np.exp(2.0 * alpha))
a1 = a5 = k
a2 = a6 = k * np.exp(-alpha) * (alpha - 1.0)
a3 = a7 =... | |
import pymysql
import datetime
from pandas import DataFrame
import numpy as np
from dbutils.steady_db import connect
class RankDB():
"""
a mariadb wrapper for the following tables:
- stock_data
- corporate_data
- corporate_financials
- model_event_queue
- top_performers... | |
"""
# Test uzf for the vs2d comparison problem in the uzf documentation except in
# this case there are 15 gwf and uzf cells, rather than just one cell.
"""
import os
import numpy as np
try:
import pymake
except:
msg = "Error. Pymake package is not available.\n"
msg += "Try installing using the following... | |
from tqdm import tqdm
import numpy as np
from polaris2.micro.micro import det
from polaris2.geomvis import R3S2toR, utilmpl, phantoms
import logging
log = logging.getLogger('log')
N = 80
log.info('Making '+str(N)+' frames')
for i in tqdm(range(N)):
xp, yp, zp = phantoms.sphere_spiral(i/(N-1))
obj = R3S2toR.xyz... | |
import numpy as np
from scipy.optimize import linear_sum_assignment as linear_assignment
# from sklearn.metrics import normalized_mutual_info_score, adjusted_rand_score
# nmi = normalized_mutual_info_score
# ari = adjusted_rand_score
def acc(y_true, y_pred):
"""
Calculate clustering accuracy. Require scikit-... | |
import matplotlib.pyplot as plt
import numpy as np
from fast_image_classification.preprocessing_utilities import read_img_from_path
from fast_image_classification.training_utilities import get_seq
def plot_figures(names, figures, nrows=1, ncols=1):
"""Plot a dictionary of figures.
Parameters
----------
... | |
# License: MIT
from typing import List
import numpy as np
from openbox.utils.config_space import Configuration, ConfigurationSpace
WAITING = 'waiting'
RUNNING = 'running'
COMPLETED = 'completed'
PROMOTED = 'promoted'
def sample_configuration(configuration_space: ConfigurationSpace, excluded_configs: List[Configurat... | |
import sys
if sys.version_info < (3, 6):
sys.stdout.write(
"Minkowski Engine requires Python 3.6 or higher. Please use anaconda https://www.anaconda.com/distribution/ for isolated python environment.\n"
)
sys.exit(1)
try:
import torch
except ImportError:
raise ImportError('Pytorch not found... | |
#!/usr/bin/env python3
# -*- coding:utf-8 -*-
from typing import Dict, Optional, Union
import numpy
import torch
import torch.nn.functional as F
from allennlp.common import Params
from allennlp.common.checks import ConfigurationError
from allennlp.data import Vocabulary
from allennlp.models.model import Model
from al... | |
# Copyright (c) FULIUCANSHENG.
# Licensed under the MIT License.
import os
import sys
import json
import argparse
import logging
import numpy as np
import pandas as pd
submission_files = {
"cola": "CoLA.tsv",
"sst2": "SST-2.tsv",
"mrpc": "MRPC.tsv",
"stsb": "STS-B.tsv",
"mnli": "MNLI-m.tsv",
"... | |
# import fitz
import pytesseract
from PIL import Image
import io
import cv2
import numpy as np
from pdf2image import convert_from_bytes
import re
from core import logging
logger = logging.getLogger(__name__)
def de_skew(image, show=False, delta=0):
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
gray = 255 - g... | |
import numpy as np
import cv2
from matplotlib import pyplot as plt
"""
@X: input data
@k: number of clusters
"""
def kmeans_wrapper(X, k, image_as_input = False):
if not image_as_input:
X = np.float32(X)
else:
orig_shape = X.shape
# flatten the image into a vector of BGR entries
... | |
import numpy as np
import os
import re
import cPickle
class read_cifar10(object):
def __init__(self, data_path=None, is_training=True):
self.data_path = data_path
self.is_training = is_training
def load_data(self):
files = os.listdir(self.data_path)
if self.is_training is True:
pattern = ... | |
import copy
import math
import pdb
import random
import timeit
import cPickle as pickle
import numpy as np
from poim import *
import poim
from shogun.Features import *
from shogun.Kernel import *
from shogun.Classifier import *
from shogun.Evaluation import *
from shutil import *
dna = ['A', 'C', 'G', 'T']
def simula... | |
"""Starting from a halo mass at z=0, the two functions below give descriptions for
how halo mass and Vmax smoothly evolve across time.
"""
from numba import njit
from math import log10, exp
__all__ = ('halo_mass_vs_redshift', 'vmax_vs_mhalo_and_redshift')
@njit
def halo_mass_vs_redshift(halo_mass_at_z0, redshift, h... | |
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 16 15:03:37 2016
keshengxuu@gmail.com
@author: keshengxu
"""
import numpy as np
from scipy.stats import norm
from scipy import integrate
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import os.path
from matplotlib import colors
import matplotlib.g... |
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