| PS> time { ping -n 1 google.com } -Samples 10 -Silent | |
| .......... | |
| Avg: 62.1674ms | |
| Min: 56.9945ms | |
| Max: 87.9602ms | |
| PS> time { ping -n 1 google.com } -Samples 10 -Silent -Long | |
| .......... | |
| Avg: 00:00:00.0612480 | |
| Min: 00:00:00.0572167 |
| #!/usr/bin/env python | |
| """ | |
| simple example script for running and testing notebooks. | |
| Usage: `ipnbdoctest.py foo.ipynb [bar.ipynb [...]]` | |
| Each cell is submitted to the kernel, and the outputs are compared with those stored in the notebook. | |
| """ | |
| # License: Public Domain, but credit is nice (Min RK). |
Locate the section for your github remote in the .git/config file. It looks like this:
[remote "origin"]
fetch = +refs/heads/*:refs/remotes/origin/*
url = git@github.com:joyent/node.git
Now add the line fetch = +refs/pull/*/head:refs/remotes/origin/pr/* to this section. Obviously, change the github url to match your project's URL. It ends up looking like this:
| """ | |
| ========================================================= | |
| circular data analysis functions | |
| ========================================================= | |
| """ | |
| # Authors : Anne Kosem and Alexandre Gramfort | |
| # License : Simplified BSD |
Last Update: May 13, 2019
Offline Version
| julia> using Series, MarketData, FactCheck | |
| julia> @time fast = fastmoving(Cl, mean, 60); | |
| elapsed time: 0.305857977 seconds (72646744 bytes allocated) | |
| julia> @time slow = moving(Cl, mean, 60); | |
| elapsed time: 4.925385985 seconds (2079575504 bytes allocated) | |
| julia> @fact fast[end].value => roughly(slow[end].value) | |
| Success :: :(fast[end].value) => :(roughly(slow[end].value)) |
| #!/usr/bin/env python | |
| # -*- coding: utf-8 -*- | |
| """Implements Partial Directed Coherence and Direct Transfer Function | |
| using MVAR processes. | |
| Reference | |
| --------- | |
| Luiz A. Baccala and Koichi Sameshima. Partial directed coherence: | |
| a new concept in neural structure determination. |
| def circular_linear_correlation(alpha, x): | |
| # Authors: Jean-Remi King <jeanremi.king@gmail.com> | |
| # Niccolo Pescetelli <niccolo.pescetelli@gmail.com> | |
| # | |
| # Licence : BSD-simplified | |
| """ | |
| Parameters | |
| ---------- | |
| alpha : numpy.array, shape (n_angles, n_dims) |
| # Python | |
| import mne | |
| import numpy as np | |
| from matplotlib import pyplot as plt | |
| # Channel positions | |
| ch_names = ['A1', 'A2', 'A3', 'A4', 'A5', 'A6', 'A7', 'A8', 'A9', 'A10', 'A11', 'A12', 'A13', 'A14', 'A15', 'A16', 'A17', 'A18', 'A19', 'A20', 'A21', 'A22', 'A23', 'A24', 'A25', 'A26', 'A27', 'A28', 'A29', 'A30', 'A31', 'A32', 'B1', 'B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B8', 'B9', 'B10', 'B11', 'B12', 'B13', 'B14', 'B15', 'B16', 'B17', 'B18', 'B19', 'B20', 'B21', 'B22', 'B23', 'B24', 'B25', 'B26', 'B27', 'B28', 'B29', 'B30', 'B31', 'B32', 'C1', 'C2', 'C3', 'C4', 'C5', 'C6', 'C7', 'C8', 'C9', 'C10', 'C11', 'C12', 'C13', 'C14', 'C15', 'C16', 'C17', 'C18', 'C19', 'C20', 'C21', 'C22', 'C23', 'C24', 'C25', 'C26', 'C27', 'C28', 'C29', 'C30', 'C31', 'C32', 'D1', 'D2', 'D3', 'D4', 'D5', 'D6', 'D7', 'D8', 'D9', 'D10', 'D11', 'D12', 'D13', 'D14', 'D15', 'D16', 'D17', 'D18', 'D19', 'D20', 'D21', 'D22', 'D23', 'D24', 'D25', 'D26', 'D27', 'D28', 'D29', 'D30', 'D31', 'D32'] | |
| montage = mne.channels.read_montage('biosemi128') | |
| info |
| # from https://gist.github.com/MattDMo/6cb1dfbe8a124e1ca5af | |
| import os | |
| import json | |
| import socket | |
| import threading | |
| activate_this = os.environ.get("SUBLIMEREPL_ACTIVATE_THIS", None) | |
| # turn off pager |