arxiv_id stringlengths 0 16 | text stringlengths 10 1.65M |
|---|---|
import random
import math
import numpy as np
def del_artifical_vars(table, B, W):
use_bland = True
print_steps = True
while len(W)!=0:
# Removing aritficial variables:
# If they are not in the base we cross them over
non_basis = [i for i in W if i not in B]
if print_steps:
... | |
from __future__ import print_function
import sys
import numpy as np
import netCDF4 as nc
from .base_grid import BaseGrid
class DaitrenRunoffGrid(BaseGrid):
def __init__(self, h_grid_def, description='Daitren runoff regular grid'):
self.type = 'Arakawa A'
self.full_name = 'Daitren_runoff'
... | |
from keras.datasets import mnist
from keras.utils import to_categorical
from keras.models import Sequential
from keras.models import load_model
from keras.layers import Dense
import sys
import numpy as np
import matplotlib.pyplot as plt
import cv2
def testContours(img):
plt.figure(figsize=[10,5])
ret, thresh ... | |
'''
Short script to run on quest to create and submit a request for
forced photometry for every source in the 2018 sample
'''
import pandas as pd
import numpy as np
import glob
import subprocess
info_path="/projects/p30796/ZTF/early_Ia/2018/info/"
source_files = glob.glob(info_path+'force_phot*.fits')
for source_fi... | |
import cv2
import numpy as np
# add your video absolute path
pathv = 'C:\\your path\\v_GolfSwing_g17_c05.avi'
#or you can just ./v_GolfSwing_g17_c05.avi,but may report an error when you run the program
cap = cv2.VideoCapture(pathv)
ret, frame1 = cap.read()
prvs = cv2.cvtColor(frame1,cv2.COLOR_BGR2GRAY)
# optical flo... | |
# For plotting
# from environment.custom.knapsack.heuristic import solver
import matplotlib.pyplot as plt
import os
import numpy as np
# Import Google OR Tools Solver
# from agents.optimum_solver import solver
def plotter(data, env, agent, agent_config, opt_solver, print_details=False):
# Destructure the tup... | |
import os
import shutil
import urllib.request
from qtpy.QtWidgets import QMessageBox
from qtpy.QtCore import Qt
from specviz.plugins.loader_wizard.loader_wizard import (ASCIIImportWizard, parse_ascii,
simplify_arrays)
def test_loader_wizard(tmpdir, qtbot, monkeypatch):
... | |
# -*- coding: utf-8 -*-
# Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V. (MPG) is
# holder of all proprietary rights on this computer program.
# You can only use this computer program if you have closed
# a license agreement with MPG or you get the right to use the computer
# program from someone who is... | |
# -*- coding: utf-8 -*-
"""
Created on Fri Jan 10 14:01:21 2020
@author: Jakob
"""
###########################################################
### Imports
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import math
import networkx as nx
import time
import pickle
t1 = time.time()
fig = plt.figu... | |
import click as ck
import pandas as pd
from ont import Ontology
import dgl
from dgl import nn as dglnn
import torch as th
import numpy as np
from torch import nn
from torch.nn import functional as F
from torch import optim
from sklearn.metrics import roc_curve, auc, matthews_corrcoef
import copy
from torch.utils.data i... | |
from models import Actor, Critic
from memory import ReplayMemory
import torch
import torch.nn as nn
import numpy as np
from utils import *
from vizdoom import *
from collections import deque
import torch
from torch.autograd import Variable
import numpy as np
import random
import skimage
import skimage.transform
from m... | |
import os
import sys
import time
import random
from models import cnn
from save_plot import save_plot
from dataset import load_dataset
from model_callbacks import model_callbacks
from pycm import *
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from keras.optimizers import Adam
from sklearn.... | |
import os
import numpy as np
from optparse import OptionParser
import glob
import pandas as pd
def go_for_batch(toproc, splitSky,
dbDir, dbExtens, outDir, metricName,
nodither, nside, fieldType, band,
pixelmap_dir, npixels, proxy_level):
"""
Function to prepa... | |
#!/usr/bin/env python
# Copyright (c) 2009-2019 Quan Xu <qxuchn@gmail.com>
#
# This module is free software. You can redistribute it and/or modify it under
# the terms of the MIT License, see the file COPYING included with this
# distribution.
"""Build gene regulatory network"""
# Python imports
import os
import mat... | |
import time
import torch
import numpy as np
def get_model(dataset, centroids, dataset_type, n_features, n_cluster):
if dataset_type == "dense_libsvm":
return KMeans(dataset, centroids)
elif dataset_type == "sparse_libsvm":
return SparseKMeans(dataset, centroids, n_features, n_cluster)
class... | |
#!/usr/bin/env python
#
# Copyright (c) 2019 Intel Corporation
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
#
"""
This module provides a ROS autonomous agent interface to control the ego vehicle via a ROS stack
"""
import math
import os
import s... | |
import os
import json
import pickle
import argparse
import numpy as np
import pandas as pd
from tqdm import tqdm
from skimage import io as skio
if __name__ == "__main__":
"""
External parameters
"""
parser = argparse.ArgumentParser(description="Interface for downloading/exploring data from databa... | |
import numpy as np
import torch
from torchvision import datasets
from torchvision import transforms
from torch.utils.data.dataset import Dataset
class CIFAR10LabelDataset(Dataset):
def __init__(self, data, ydata, transform):
self.data = data
self.ydata = ydata
self.transform = transform
... | |
import contextlib
import os
from pathlib import Path
from typing import Callable, Union
import numpy as np
def arr2str(a: np.ndarray, format_='e', ndigits=2) -> str:
"""convert ndarray of floats to a string expression.
:param a:
:param format_:
:param ndigits:
:return:
"""
return np.arra... | |
import numpy as np
from scipy import linalg
from ..base import Preprocessor
from ..statistics import (
calculate_within_class_scatter_matrix,
calculate_between_class_scatter_matrix,
)
__all__ = [
"LinearDiscriminantAnalysis",
]
class LinearDiscriminantAnalysis(Preprocessor):
"""Linear Discriminant A... | |
#!/usr/bin/env python
"""
Usage:
python run_significance_test.py predictions1 predictions2 gold_answers
"""
import sys
import numpy as np
from statsmodels.sandbox.stats.runs import mcnemar as mcnemar_test
import csv
np.random.seed(123)
def compute_mcnemar_test(contingency_table):
assert np.shape(contingency_ta... | |
# from data_utils.ModelNetDataLoader import ModelNetDataLoader
# from data_utils.OFFDataLoader import *
import argparse
import numpy as np
import os
import torch
import logging
from tqdm import tqdm
from sklearn.metrics import confusion_matrix
import sys
import importlib
from path import Path
from data_utils.PCDLoader ... | |
import tensorflow as tf
from tensorflow.python.framework import ops
import numpy as np
import functools
from keras import backend as K
from keras.engine import Layer, InputSpec
from keras import activations
from keras import initializers
from keras import regularizers, constraints
def noisy_dense(inputs, units, bias... | |
import os
import argparse
import torch
import numpy
import random
from datetime import datetime
def format_time():
now = datetime.now() # current date and time
date_time = now.strftime("%m-%d-%H:%M:%S")
return date_time
def ensure_dir(path):
if not os.path.exists(path):
os.makedirs(path)
... | |
import codecs
import numpy as np
from utils.data_utils import SPACE, PUNCTUATION_VOCABULARY, PUNCTUATION_MAPPING
def compute_score(target_path, predicted_path):
"""Computes and prints the overall classification error and precision, recall, F-score over punctuations."""
mappings, counter, t_i, p_i = {}, 0, 0,... | |
# Uses https://github.com/kucherenko/jscpd to find code duplication
import subprocess
import os
import sys
import json
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from common import get_base_dir, get_projects_to_scan
token_range_for_cpds = np.arange(5, 20, 3)
def cpd_for_project_with_min_l... | |
import pymc3 as pm
import theano.tensor as tt
def estimate_retention_probability(observed_retained, n_items, t_steps,
beta_remembering_kwargs, beta_decay_kwargs,
id_ind=None):
"""
"""
with pm.Model() as model:
t_steps_data = p... | |
r"""
Features for testing the presence of nauty executables
"""
from sage.env import SAGE_NAUTY_BINS_PREFIX
from . import Executable
from .join_feature import JoinFeature
class NautyExecutable(Executable):
r"""
A :class:`~sage.features.Feature` which checks for nauty executables.
EXAMPLES::
sa... | |
# -*- coding: utf-8 -*-
"""
Created on Thu Apr 29 15:37:37 2021
Short Function to create .JPEG copies of input image tiles for model input
@author: Grant Francis
email: gfrancis@uvic.ca
"""
import os
from PIL import Image
import glob
import numpy as np
def to_jpg(lib):
total_tiles = len([name fo... | |
import os
import numpy as np
from sparse import load_npz
# This will make an average kernel matrix of (M x N) dimensions.
# If refcodes_path == comparison_refcodes_path, then M = N.
# This code must be run after `soap_matrix_generator.py`
# Note: This can be memory-intensive.
# Settings
basepath = os.getcwd() # Base... | |
from .sound import Sound
import warnings
import numpy as np
import os
import time
try:
from deepspeech import Model as DPModel
except ModuleNotFoundError:
warnings.warn("Missing some of the required libraries for running DeepSpeech.", UserWarning)
try:
import json
import vosk
from library.audio_f... | |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from matplotlib.patches import Rectangle
import matplotlib.pyplot as plt
from matplotlib.offsetbox import AnchoredOffsetbox, TextArea, DrawingArea, HPacker, VPacker
import matplotlib.lines as mlines
import oper... | |
import pytest
import cv2
import time
import numpy as np
from perception.scene.eval import SceneSensor
from perception.common.video import clip_video_to_frames, VideoWriter
from perception.common.visualize import draw_bboxes
from perception.common.utils import robot2_frame_crop_resize
VIDEO = 'data/potential_interacti... | |
import numpy as np
import chainer
import chainer.functions as F
def main():
for _ in range(1000):
inp = np.random.random((2, 3, 224, 224)).astype(np.float32)
ret = F.sqrt(F.relu(inp - 0.5)).array
assert np.sum(np.isnan(ret)) == 0
print("no error")
if __name__ == '__main__':
mai... | |
""" This module stores the FeaModel class.
This class is the highest level object in a pycalculix program.
It stores all parts, loads, constraints, mesh, problem, and results_file
objects.
"""
import matplotlib.pyplot as plt
from matplotlib.collections import PatchCollection # element plotting
import matplotlib.colo... | |
import numpy as np
from ray.rllib.utils.framework import try_import_torch
torch, nn = try_import_torch()
# Custom initialization for different types of layers
if torch:
class Linear(nn.Linear):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
def reset_paramete... | |
import numpy as np
import src.Utils.plot as plot
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import src.Planning.PotentialField as pf
if __name__ == '__main__':
obstacle_map = plot.readBMPAsNumpyArray("../map/small_obstacle_map.bmp")
h, w = obstacle_map.shape
resolution = 0.05 *... | |
#!/usr/bin/env python3
#import ev3dev.ev3 as ev3
from time import sleep
import numpy as np
def centre_line_finder(_angle2):
angle_0 = (_angle2 - 0)
angle_90 = (_angle2 - 90)
angle_180 = (_angle2 - 180)
angle_270 = (_angle2 - 270)
angle = np.array([abs(angle_0), abs(angle_90), abs(angle_180), abs... | |
#!/usr/bin/env python
# Aesara tutorial
# Solution to Exercise in section 'Configuration Settings and Compiling Modes'
import numpy as np
import aesara
import aesara.tensor as at
aesara.config.floatX = 'float32'
rng = np.random
N = 400
feats = 784
D = (rng.randn(N, feats).astype(aesara.config.floatX),
rng.randint(... | |
import pandas as pd
import quandl, math
import datetime
import time
import numpy as np
from sklearn import preprocessing, cross_validation, svm
from sklearn.linear_model import LinearRegression
import matplotlib.pyplot as plt
from matplotlib import style
import pickle
style.use('ggplot')
df = quandl.get("WIKI/GOOGL")... | |
import numpy as np
from tensorflow.keras.models import model_from_json
class Model(object):
# List of Emotions
EMOTIONS_LIST = ["Angry", "Disgust",
"Fear", "Happy",
"Neutral", "Sad",
"Surprise"]
def __init__(self, model_json, model_h5):
... | |
#!/usr/bin/env python3
"""
Script and class for creating tf.Record datasets for the KITTI visual odometry
task.
Will create 11 different datasets where one sequence is held out as test
data while the other 10 sequences are used for training and validation.
"""
import argparse
import numpy as np
import os
import matpl... | |
from time import sleep
import numpy as np
from robotics.openrave.utils import solve_inverse_kinematics, \
set_manipulator_conf, Conf, Traj, manip_from_pose_grasp
from robotics.openrave.motion import has_mp, mp_birrt, mp_straight_line, linear_motion_plan, manipulator_motion_plan
from robotics.openrave.transforms imp... | |
"""Climate normals daily data"""
import re
import numpy as np
import pandas as pd
def norm_get_dly():
"""Get all daily climate normals data"""
prcp = norm_get_dly_prcp()
snow = norm_get_dly_snow()
tavg = norm_get_dly_tavg()
tmax = norm_get_dly_tmax()
tmin = norm_get_dly_tmin()
by = ["id"... | |
#coding=utf-8
'''
Created on 2016-9-27
@author: dengdan
'''
import matplotlib as mpl
# mpl.use('Agg')
mpl.use('TkAgg')
import matplotlib.pyplot as plt
import numpy as np
import util
def hist(x, title = None, normed = False, show = True, save = False,
save_path = None, bin_count = 100,... | |
import numpy as np
import fenics as fe
import matplotlib.pyplot as plt
from mpl_toolkits import mplot3d
import time as ti
from ellipticCauchyPro import *
from vbiIP import *
from addNoise import *
"""
This script used for evaluating Example 1 shown in
B. Jin, A variational Bayesian method to inverse problems with im... | |
import numpy as np
import matplotlib.pyplot as plt
import itertools as itr
class AlignPlot(object):
#Class to define plot for interactive aligning of images
def __init__(self, ImgAligner):
self.ImgAligner = ImgAligner
self.fig = plt.figure()
self.ax = plt.axes([0.05, 0.05, 0.95, 0.95])
... | |
import os
import sys
import unittest
import numpy as np
import torch
from torch.nn import functional as torch_F
from src.cranet.nn import functional as cranet_F
from src import cranet
from ..utils import teq
class TestL1Loss(unittest.TestCase):
def test_l1_0(self):
for _ in range(100):
x =... | |
import sys
import numpy
import bob.io.base
import bob.io.base.test_utils
import bob.io.image
import bob.ip.facedetect
from bob.ip.skincolorfilter import SkinColorFilter
face_image = bob.io.base.load(bob.io.base.test_utils.datafile('test-face.jpg', 'bob.ip.skincolorfilter'))
detection = bob.ip.facedetect.detect_single... | |
import numpy as np
X = np.arange(28).reshape(4,7)
print(X)
print(X[::2, ::3]) | |
#!/usr/bin/env python
"""
Utility and I/O functions to read and write data files or Synapse tables.
Authors:
- Arno Klein, 2015-2016 (arno@childmind.org) http://binarybottle.com
Copyright 2015-2016, Sage Bionetworks (sagebase.org), with later modifications:
Copyright 2016, Child Mind Institute (childmind.org), ... | |
# Import all the bits and bobs we'll need
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import slippi
import time
from datetime import datetime
import os
import sys
import matplotlib.image as mpimg
import matplotlib
import gc
# from slippi import Game
# from slippi import Game1F... | |
#!/usr/bin/env python3
import cv2
import hashlib
import imghdr
import numpy as np
import os
from PIL import Image, ImageDraw
from preprocess import (
image_resize,
file_as_bytes,
hash_file,
rename_files,
is_transparent,
append_background,
blacklist,
update_classes
)
from random import r... | |
import timeit
import matplotlib.pyplot as plt
import numpy as np
from gefest.core.geometry.geometry_2d import Geometry2D, create_circle
from gefest.core.opt.analytics import EvoAnalytics
from gefest.core.opt.optimize import optimize
from gefest.core.opt.setup import Setup
from gefest.core.structure.domain import Doma... | |
from typing import Dict, Optional, Any
import torch
from scipy.stats import wasserstein_distance
import torchmetrics
# This implementation is based on scipy.stats.wasserstein_metric.
# There are solvers for differentiable approximations with GPU acceleration
# the geomloss package: https://www.kernel-operations.io/g... | |
# Do objects move in 2 directions at once?
If a velocity vector of an object can be divided into an x and y component relative to a second object's position, and both objects have gravity that attracts both objects to each other. We then know that the object is not moving in a straight path. How is the object able to ... | |
#### 12th Standard Physics English Medium Electrostatics Reduced Syllabus Important Questions with Answer key 2021
12th Standard
Reg.No. :
•
•
•
•
•
•
Physics
Time : 01:00:00 Hrs
Total Marks : 100
Multiple Choice Questions
15 x 1 = 15
1. Which charge configuration produces a uniform electric field?
(a)
point Char... | |
1 echo -n "Hi . How are you?" | tl -name Shane
## This is similar to python f-strings
1 2 3 name = "Eric" age = 74 print(f"Hello, {name}. You are {age}.")
Hello, Eric. You are 74.
In fact, I should make an f-strings-based utility.
## Build the replace-substring script
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1... | |
Lesson 2
# Basic syntax
0
Now that you have a grip on the basics, we're going to dive deeper into the following areas:
1. Variables and variable definition
2. MATLAB as a calculator
3. Data types and formats
4. Operators and special characters
6. User input from the keyboard
7. Displaying the variable as outpu... | |
## [FIXED] Change Live Histogram not available during stacking
A place to report problems and bugs in SharpCap
Forum rules
Please include the following details in any bug report:
* Version of SharpCap
* Camera and other hardware being user
* Operating system version
* Contents of the SharpCap log after the problem h... | |
# Linear Approximation Calculator
Linear Approximation Calculator is a free online tool that displays the linear approximation for the given function. BYJU’S online linear approximation calculator tool makes the calculation faster, and it displays the linear approximation in a fraction of seconds.
## How to Use the L... | |
# Identifying structure of student essays
## overview
Students must be able to read scientific texts with deep understanding and create coherent explanations that connect causes to events. Can we use Natural Language Processing to evaluate whether they're doing that based on essays they write?
## research questions
... | |
This function works by bundling source package, and then uploading to https://win-builder.r-project.org/. Once building is complete you'll receive a link to the built package in the email address listed in the maintainer field. It usually takes around 30 minutes. As a side effect, win-build also runs R CMD check on the... | |
# Sequences and Series
#### Sequences
A sequence is an ordered list of numbers such as $a_1, a_2, a_3, \dots$ formed according to a definite rule. Each member in this ordered list is called and "element" or "term" of the sequence. The sequence is defined by the number of terms it contains as either finite or infinite... | |
# Find the equation of the streamline passing through the point $$(5,3)$$ at t =3 seconds.
A velocity field is given by $$V=3yt\hat{i}+5x\hat{j}$$. Find the equation of the streamline passing through the point $$(5,3)$$ at $$t =3$$. Units of $$x,y$$ are in meters and time-$$t$$ is in seconds.
Asked on 5th May 2021 in... | |
Friday, March 21, 2008 ... //
Three preprints on cosmoclimatology
During the last week, there have been three cosmoclimatological preprints by two teams on the arXiv. Rusov et al. (Ukraine) argue that all observed climate change at the timescale of millenia and millions of years can be explained by two factors, namel... | |
## The Annals of Probability
### Continuity of $l^2$-Valued Ornstein-Uhlenbeck Processes
#### Abstract
A stationary $l^2$-valued Ornstein-Uhlenbeck process is considered which is given formally by $dX_t = -AX_t dt + \sqrt 2a dB_t$, where $A$ is a positive self-adjoint operator on $l^2, B_t$ is a cylindrical Brownian... | |
0
Research Papers
# Mesoscopic Investigation of the Heterogeneities Induced by Channel-Die Compression
[+] Author and Article Information
Michel G. Darrieulat
Ecole Nationale Supérieure des Mines de Saint-Etienne, Centre “Sciences des Matériaux et des Structures,” UMR CNRS No. 5146, 158 cours Fauriel, 42023 Saint-Et... | |
Article Contents
Article Contents
# Upper risk bounds in internal factor models with constrained specification sets
• For the class of (partially specified) internal risk factor models we establish strongly simplified supermodular ordering results in comparison to the case of general risk factor models. This allows u... | |
# Recent questions tagged youngs-double-slit-experiment
Questions from:
### In a Young's double slit experiment separation between two consecutive dark. fringes is $1.2 \;mm$, wave length $\lambda$ of light is $600 \;nm$ Distance between source and screen $D= 1 m$, the separation between slits is
To see more, click ... | |
# SICP Solutions
### Chapter 4, Metalinguistic Abstraction
#### Exercise 4.28
Because operator might be a thunk, or allow me to call it delayed expression! For eg:
Consider tha ‘lambda’ passed as an argument.
Let’s first view how a map procedure might look:
With normal order evaluation, proc is a thunk and it con... | |
# Convex optimization
## Unconstrained
1. Toolbox ⟹ CVX
• CVX: package if you to get the solution to such a problem: $\begin{cases} \sup c^T x Ax = b x ≥ 0 \end{cases}$
2. Ellipsoid
• in 1D: dichotomy
• in higher dimension: $E_k ≝ \lbrace (x - x_k)^T P_k^{-1} (x - x_k) ≤ 1 \rbrace$ where $P_k$ is positive def.
• ex... | |
# How do you test the improper integral int x^-2 dx from [2,oo) and evaluate if possible?
Apr 13, 2017
${\int}_{2}^{\infty} {x}^{-} 2 \mathrm{dx} = \frac{1}{2}$
#### Explanation:
We will find the antiderivative of ${x}^{-} 2$ as normal. When we "evaluate" at infinity, we will take the limit of the antiderivative at... | |
# DRIVE: Digital Retinal Images for Vessel Extraction Dataset¶
This package is part of the signal-processing and machine learning toolbox Bob. It provides an interface for the DRIVE Dataset. This package does not contain the original data files, which need to be obtained through the link above.
The DRIVE database has... | |
## zmudz one year ago Let $$n$$ be a positive integer. Show that the smallest integer greater than $$(\sqrt{3} + 1)^{2n}$$is divisible by $$2^{n+1}.$$ Hint: Prove that $$\lceil (\sqrt{3}+1)^{2n} \rceil = (\sqrt{3}+1)^{2n} + (\sqrt{3}-1)^{2n}.$$
1. amilapsn
you can use mathematical induction with binomial expansion.
... | |
Refer to the figure shown. An $$E$$-$$V$$ battery and infinitely many solenoids of $$1!$$, $$2!$$, $$3!$$ and so on. The number of loops is connected in parallel. Another circuit has each of the infinite number of corresponding identical solenoids having $$N$$ loops and internal resistance $$R$$ connected in parallel. ... | |
Q
If the same wedge is made rough then the time taken by body to come down becomes n times more (nt)
Then find the Coefficient of Friction between body and wedge in term of n?
Views
For the below figure
The distance S is the same.
And using this concept we get
$\mu=tan\theta\left[1-\frac{1}{n^{2}} \right ]$
Wher... | |
1 .
Which of the following will come next in the following series ?
a z a b y a b c x a b c d w a b c d
[ A ] f [ B ] u [ C ] a [ D ] v [ E ] e
Answer : Option E Explanation : | |
# Homework Help: Quantum Harmonic Oscillator ladder operator
1. Apr 2, 2013
### bobred
1. The problem statement, all variables and given/known data
What is the effect of the sequence of ladder operators acting on the ground eigenfunction $\psi_0$
2. Relevant equations
$\hat{A}^\dagger\hat{A}\hat{A}\hat{A}^\dagger\p... | |
# Omit Canary Hosts Predicate¶
This extension may be referenced by the qualified name envoy.retry_host_predicates.omit_canary_hosts
Note
This extension is intended to be robust against untrusted downstream traffic. It assumes that the upstream is trusted.
## config.retry.omit_canary_hosts.v2.OmitCanaryHostsPredicat... | |
1.9 Waves (Page 3/7)
Page 3 / 7
Earthquake waves under Earth’s surface also have both longitudinal and transverse components (called compressional or P-waves and shear or S-waves, respectively). These components have important individual characteristics—they propagate at different speeds, for example. Earthquakes a... | |
## The difference and sum of projectors.(English)Zbl 1060.15011
The authors give simple proofs, without reference to rank theory for matrices, of some results on the non-singularity of the difference $$P-Q$$ of projections $$P$$ and $$Q$$ obtained by J. Gross and G. Trenkler [SIAM J. Matrix Anal. Appl. 21, No. 2, 390–... | |
# xcube=64
## Simple and best practice solution for xcube=64 equation. Check how easy it is, and learn it for the future. Our solution is simple, and easy to understand, so dont hesitate to use it as a solution of your homework.
If it's not what You are looking for type in the equation solver your own equation and le... | |
Lecture 2: Sampling Triangles (43)
shannonhu-144
V dot N is |V||N|cos(theta), where theta is the angle between N and V. If V dot N is greater than 0, then theta must be less than 90, so P must be on the same half-plane as N. If V dot N is 0, then theta is 90, so P must be on the line. If V dot N is negative, then thet... | |
# 13.4: Accounting for Product Warranties
Learning Objectives
At the end of this section, students should be able to meet the following objectives:
1. Explain the difference between an embedded and an extended product warranty.
2. Account for the liability and expense incurred by a company that provides its customer... | |
# Length of time in a satellite spends in Earths shadow
I have come across a problem that has had me stumped for a while now.
A spacecraft is in a Sun-synchronous Earth orbit with a =1.40 R⊕ and e = 0.2. The argument of periapsis is ω = 0◦ , and the Right Ascension of the Ascending Node, Ω, is equal to the Sun’s Righ... | |
# DMGT
ISSN 1234-3099 (print version)
ISSN 2083-5892 (electronic version)
# IMPACT FACTOR 2018: 0.741
SCImago Journal Rank (SJR) 2018: 0.763
Rejection Rate (2017-2018): c. 84%
# Discussiones Mathematicae Graph Theory
Article in press
Authors:
C.J. Jayawardene, D. Narváez, S.P. Radziszowski
Title:
Star-critic... | |
### Show Posts
This section allows you to view all posts made by this member. Note that you can only see posts made in areas you currently have access to.
### Messages - Junhong Zhou
Pages: [1]
1
##### Quiz 2 / Quiz2-6101 6D
« on: October 02, 2020, 02:22:25 PM »
Problem(3pt). Find all points of continuity of the giv... | |
# The radio structure of the peculiar narrow-line Seyfert 1 galaxy candidate J1100+4421 [GA]
Narrow-line Seyfert 1 galaxies (NLS1) are an intriguing subclass of active galactic nuclei. Their observed properties indicate low central black hole mass and high accretion rate. The extremely radio-loud NLS1 sources often sh... | |
# distribution of iid sequence of integrable random variables
I came across an interesting problem in Jacod's probability book. But have no idea how to approach it. Should I approach it using induction? Any ideas?
Let $X_1, X_2, \cdots$ be an infinite sequence of iid sequence of integrable random variables and let $N... | |
## Class files
List are basic elements in a document, when used correctly they keep concepts organized and structured. This article explains how to create and modify numbered and unnumbered lists in L a T e X .
# Introduction
Lists are actually very simple to create.
List are really easy to create
\begin{itemize}
... | |
by _Mayday_
Tags: photography
PF Gold
P: 7,368
Quote by ~christina~ Nice panorama, turbo
Thanks, ~~! Next time I get a clear day, I'll take the 5-minute trip over to that hill and shoot it again with manual settings and my new Manfrotto 808RC4 tripod head. I've had a really nice, heavy Bogen tripod sitting around unus... | |
## Thursday, 6 September 2012
### A clarifying view of Weyl's criterion
Consider an arbitrary sequence $(x_n)$ on the circle $\mathbf{T} = \mathbf{R}/\mathbf{Z}$. If $(x_n)$ is sufficiently well behaved, then often it will have a sort of limiting distribution, which would be usefully represented by a measure $\mu$. F... | |
Krishna
0
Step 1: Use the relationship between circumference and radius to find the radius of the circle.
NOTE: Circumference C = 2 \pi r
r = \frac{C}{2*\pi}
Find the radius of the circle
EXAMPLE: r = \frac{C}{2*\pi} r = \frac{22}{2*\pi} (since \pi = \frac{22}{7} = 3.14)
r = \frac{7}{2}
Step 2: Calculate the ar... | |
# Math Help - Test
1. ## Test
. . $\Large\begin{array}{c} \curlyvee\!\! \curlyvee\!\! \curlyvee\! \curlyvee \\ [-3.6mm] \curlywedge\!\! \curlywedge\!\! \curlywedge\! \curlywedge \\ [-3.3mm] \curlyvee\!\! \curlyvee\!\! \curlyvee\! \curlyvee \\ [-3.6mm] \curlywedge\!\! \curlywedge\!\! \curlywedge\! \curlywedge \end{arr... | |
# Sum of Products Help
1. Sep 3, 2009
### tstuddud
I don't quite understand the method to solve this type of question.
Let x=(-3,2,5), y=(2,4,-5), and z=(1,6,7). Calculate:
File size:
1.7 KB
Views:
59
File size:
1.7 KB
Views:
58
2. Sep 3, 2009
### NJunJie
I view such qns playing with 'arrays' and 'susbstituion'.... | |
# Dumb conversion question
I'm sorry for posting this, but I'm really confused by the following.
The problem states to use units of 1000 TOE("tons of oil equivelent, where 1 ton = 1000 kg) So if I'm given 1698 kg oil equivalent, I need to divide by 1000 twice to get to the units of 1000 TOE?
Thanks. | |
# Ampersand should be escaped on export
Bug #533726 reported by arno_b on 2010-03-07
This bug affects 1 person
Affects Status Importance Assigned to Milestone
Medium
### Bug Description
Ampersand characters (&) are not escaped in the generated Latex code, this
has to be done manually.
arno_b (arno.b) on 2010-03-07
... | |
# Data Misfit¶
The data misfit using an l_2 norm is:
$\mu_\text{data} = {1\over 2}\left| \mathbf{W}_d (\mathbf{d}_\text{pred} - \mathbf{d}_\text{obs}) \right|_2^2$
If the field, u, is provided, the calculation of the data is fast:
\begin{align}\begin{aligned}\mathbf{d}_\text{pred} = \mathbf{Pu(m)}\\\mathbf{R} = \ma... | |
Implied volatility: general properties and asymptotics
open access
Abstract
This thesis investigates implied volatility in general classes of stock price models. To begin with, we take a very general view. We find that implied volatility is always, everywhere, and for every expiry well-defined only if the stock price ... |
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