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87ce9cfe47d73889455de53488bd033e633a15c1 | 843 | rst | reStructuredText | README.rst | pyiron/pyiron_gui | bb0a987cfc97bf478707f3bbe9828affb2c2b6ce | [
"BSD-3-Clause"
] | null | null | null | README.rst | pyiron/pyiron_gui | bb0a987cfc97bf478707f3bbe9828affb2c2b6ce | [
"BSD-3-Clause"
] | 49 | 2021-03-23T14:12:38.000Z | 2022-03-22T00:31:28.000Z | README.rst | pyiron/pyiron_gui | bb0a987cfc97bf478707f3bbe9828affb2c2b6ce | [
"BSD-3-Clause"
] | 1 | 2021-05-29T18:48:43.000Z | 2021-05-29T18:48:43.000Z | pyiron_gui
============
.. image:: https://coveralls.io/repos/github/pyiron/pyiron_gui/badge.svg?branch=master
:target: https://coveralls.io/github/pyiron/pyiron_gui?branch=master
:alt: Coverage Status
.. image:: https://anaconda.org/conda-forge/pyiron_gui/badges/latest_release_date.svg
:target: https://anaconda.org/conda-forge/pyiron_gui/
:alt: Release_Date
.. image:: https://github.com/pyiron/pyiron_gui/workflows/Python%20package/badge.svg
:target: https://github.com/pyiron//pyiron_gui/actions
:alt: Build Status
This repository is for GUI extensions to the overall pyiron framework.
Getting started:
----------------
Test pyiron with mybinder:
.. image:: https://mybinder.org/badge_logo.svg
:target: https://mybinder.org/v2/gh/pyiron/pyiron_gui/master
:alt: mybinder
| 33.72 | 87 | 0.698695 |
c307909469eb638e570191d2da80d0ba339ccd05 | 3,097 | rst | reStructuredText | doc/esperienza-utente.rst | gianvitofanelli/manuale-operativo-design-docs | cd51ee933904653ec9ddf2b4bc584125c08eaff8 | [
"CC-BY-4.0"
] | 1 | 2022-02-14T20:02:35.000Z | 2022-02-14T20:02:35.000Z | doc/esperienza-utente.rst | gianvitofanelli/manuale-operativo-design-docs | cd51ee933904653ec9ddf2b4bc584125c08eaff8 | [
"CC-BY-4.0"
] | 11 | 2021-12-16T10:15:01.000Z | 2022-03-15T15:45:00.000Z | doc/esperienza-utente.rst | gianvitofanelli/manuale-operativo-design-docs | cd51ee933904653ec9ddf2b4bc584125c08eaff8 | [
"CC-BY-4.0"
] | 3 | 2022-01-13T12:13:32.000Z | 2022-03-15T15:35:22.000Z | Esperienza utente
=================
.. include:: /banner.rst
Si definisce "esperienza" la conoscenza che le persone acquisiscono della realtà attraverso il proprio vissuto, includendo sia aspetti di tipo sensoriale e
percettivo, che emotivo. L’esperienza di un utente, riferita alla fruizione di un servizio o prodotto, deriva quindi da un’esigenza specifica ed è definita anche in
termini di raggiungimento degli obiettivi che la hanno motivata.
La norma `ISO 9241-210:2010 <https://www.iso.org/obp/ui/#iso:std:iso:9241:-210:ed-1:v1:en>`__ definisce la *user experience* (esperienza utente, o UX) come “l’insieme di percezioni e delle reazioni della persona derivanti dall’uso
e/o dall’aspettativa d’uso di un prodotto, sistema o servizio”.
Progettare un prodotto o servizio (digitale e non) significa quindi **definire le caratteristiche fondamentali dell’esperienza che l’utente vivrà accedendovi**; la
progettazione deve tener conto dei molti aspetti che definiscono l’esperienza utente e tradurli in soluzioni e caratteristiche del *touchpoint*:
- la capacità di **rispondere ai bisogni specifici dell’utente**, definita in termini di funzionalità da supportare;
- l’**usabilità**, definita come proprietà risultante dall’interazione fra il sistema e la persona, in termini di efficienza, efficacia e soddisfazione;
- la **fruibilità in relazione al contesto** fisico, culturale, sociale nell’ambito del quale l’esperienza ha luogo;
- **l’accessibilità**;
- **l’adeguatezza rispetto alle capacità cognitive** degli utenti (semplicità d’uso, accessibilità, scalabilità rispetto al livello di conoscenza e competenza sul prodotto/servizio);
- la **rispondenza alle capacità fisiche e percettive** degli utenti (accessibilità, ergonomicità).
La progettazione dell’esperienza utente (o *user experience design*) fa quindi riferimento alla conoscenza acquisita durante la fase di ricerca e procede in parallelo con il lavoro di costruzione dell’architettura dell’informazione. Il primo importante passo della progettazione è la elaborazione di una proposta progettuale - o di più proposte alternative - dell’interfaccia utente, che ne definiscono l’impianto generale in termini di modello interattivo, *layout* e struttura dei contenuti.
L’impostazione ottimale viene individuata e validata anche attraverso sessioni di confronto con utenti e/o *stakeholder*; questa costituisce il riferimento generale dal quale si procede alla **progettazione di dettaglio delle caratteristiche dell’interazione fra utente e servizio, attraverso modalità collaborative e un approccio iterativo e incrementale**.
.. toctree::
:maxdepth: 3
:caption: Indice dei contenuti
esperienza-utente/prototipazione.rst
esperienza-utente/dai-bisogni-degli-utenti-ai-flussi-di-interazione.rst
esperienza-utente/prototipare-un-servizio.rst
esperienza-utente/il-progetto-della-interfaccia-utente.rst
esperienza-utente/progettare-e-costruire-in-alta-fedelta.rst
esperienza-utente/lo-sviluppo-della-interfaccia-utente.rst
esperienza-utente/contribuire-al-design-system-di-designers-italia.rst
| 79.410256 | 494 | 0.802067 |
6c1eec1a3f1141f92670731321f70666ef402727 | 1,015 | rst | reStructuredText | doc/src/pooling.rst | syoyo/MIOpen | 8784e34e04ca97ca7db6ece102155c1546074bea | [
"MIT"
] | 4 | 2017-07-12T12:05:37.000Z | 2018-09-07T04:00:51.000Z | doc/src/pooling.rst | syoyo/MIOpen | 8784e34e04ca97ca7db6ece102155c1546074bea | [
"MIT"
] | null | null | null | doc/src/pooling.rst | syoyo/MIOpen | 8784e34e04ca97ca7db6ece102155c1546074bea | [
"MIT"
] | 1 | 2020-11-19T11:09:35.000Z | 2020-11-19T11:09:35.000Z |
Pooling Layer
=============
The pooling layer API documentation
miopenPoolingMode_t
-------------------
.. doxygenenum:: miopenPoolingMode_t
miopenCreatePoolingDescriptor
-----------------------------
.. doxygenfunction:: miopenCreatePoolingDescriptor
miopenSet2dPoolingDescriptor
----------------------------
.. doxygenfunction:: miopenSet2dPoolingDescriptor
miopenGet2dPoolingDescriptor
----------------------------
.. doxygenfunction:: miopenGet2dPoolingDescriptor
miopenGetPoolingForwardOutputDim
--------------------------------
.. doxygenfunction:: miopenGetPoolingForwardOutputDim
miopenPoolingGetWorkSpaceSize
-----------------------------
.. doxygenfunction:: miopenPoolingGetWorkSpaceSize
miopenPoolingForward
--------------------
.. doxygenfunction:: miopenPoolingForward
miopenPoolingBackward
---------------------
.. doxygenfunction:: miopenPoolingBackward
miopenDestroyPoolingDescriptor
------------------------------
.. doxygenfunction:: miopenDestroyPoolingDescriptor
| 19.150943 | 54 | 0.636453 |
810d15374a704dbb1877c6f9671a87ebea81b5c1 | 582 | rst | reStructuredText | src/interface_py/docs/h2o4gpu.tree.tests.rst | just4jc/h2o4gpu | 76700083643ec227818c5fd29659bd426a9d06c0 | [
"ECL-2.0",
"Apache-2.0",
"BSD-3-Clause"
] | null | null | null | src/interface_py/docs/h2o4gpu.tree.tests.rst | just4jc/h2o4gpu | 76700083643ec227818c5fd29659bd426a9d06c0 | [
"ECL-2.0",
"Apache-2.0",
"BSD-3-Clause"
] | null | null | null | src/interface_py/docs/h2o4gpu.tree.tests.rst | just4jc/h2o4gpu | 76700083643ec227818c5fd29659bd426a9d06c0 | [
"ECL-2.0",
"Apache-2.0",
"BSD-3-Clause"
] | null | null | null | h2o4gpu\.tree\.tests package
============================
Submodules
----------
h2o4gpu\.tree\.tests\.test\_export module
-----------------------------------------
.. automodule:: h2o4gpu.tree.tests.test_export
:members:
:undoc-members:
:show-inheritance:
h2o4gpu\.tree\.tests\.test\_tree module
---------------------------------------
.. automodule:: h2o4gpu.tree.tests.test_tree
:members:
:undoc-members:
:show-inheritance:
Module contents
---------------
.. automodule:: h2o4gpu.tree.tests
:members:
:undoc-members:
:show-inheritance:
| 18.774194 | 46 | 0.534364 |
499b3eb11eaf0b8314d5fb82cf26aeabb8d1a33f | 769 | rst | reStructuredText | reference/rpc/getrawsnapshot.rst | cornelius/docs.unit-e.io | 2af80165cddc664ad61f912bb4c118d079cf8780 | [
"MIT"
] | 2 | 2019-04-18T06:44:14.000Z | 2019-04-23T08:15:42.000Z | reference/rpc/getrawsnapshot.rst | cornelius/docs.unit-e.io | 2af80165cddc664ad61f912bb4c118d079cf8780 | [
"MIT"
] | 3 | 2019-04-18T13:27:43.000Z | 2019-06-05T15:13:03.000Z | reference/rpc/getrawsnapshot.rst | cornelius/docs.unit-e.io | 2af80165cddc664ad61f912bb4c118d079cf8780 | [
"MIT"
] | 3 | 2019-04-17T18:05:14.000Z | 2019-11-01T19:57:42.000Z | .. Copyright (c) 2018-2019 The Unit-e developers
Distributed under the MIT software license, see the accompanying
file LICENSE or https://opensource.org/licenses/MIT.
getrawsnapshot
--------------
``getrawsnapshot``
Returns hex string that contains snapshot data
Argument #1 - snapshothash
~~~~~~~~~~~~~~~~~~~~~~~~~~
**Type:** hex, required
snapshot that must be returned.
Examples
~~~~~~~~
.. highlight:: shell
::
unit-e-cli getrawsnapshot 34aa7d3aabd5df086d0ff0b110fbd9d21bb4fc7163af34d08286a2e846f6be03
::
curl --user myusername --data-binary '{"jsonrpc": "1.0", "id":"curltest", "method": "getrawsnapshot", "params": [34aa7d3aabd5df086d0ff0b110fbd9d21bb4fc7163af34d08286a2e846f6be03] }' -H 'content-type: text/plain;' http://127.0.0.1:7181/
| 23.30303 | 237 | 0.706112 |
d26649d804275c8f4e4d7af61c77cfbef93e99c6 | 292 | rst | reStructuredText | docs/source2/generated/generated/statsmodels.genmod.generalized_estimating_equations.OrdinalGEE.mean_deriv_exog.rst | GreatWei/pythonStates | c4a9b326bfa312e2ae44a70f4dfaaf91f2d47a37 | [
"BSD-3-Clause"
] | 76 | 2019-12-28T08:37:10.000Z | 2022-03-29T02:19:41.000Z | docs/source2/generated/generated/statsmodels.genmod.generalized_estimating_equations.OrdinalGEE.mean_deriv_exog.rst | cluterdidiw/statsmodels | 543037fa5768be773a3ba31fba06e16a9edea46a | [
"BSD-3-Clause"
] | 11 | 2015-07-22T22:11:59.000Z | 2020-10-09T08:02:15.000Z | docs/source2/generated/generated/statsmodels.genmod.generalized_estimating_equations.OrdinalGEE.mean_deriv_exog.rst | cluterdidiw/statsmodels | 543037fa5768be773a3ba31fba06e16a9edea46a | [
"BSD-3-Clause"
] | 35 | 2020-02-04T14:46:25.000Z | 2022-03-24T03:56:17.000Z | :orphan:
statsmodels.genmod.generalized\_estimating\_equations.OrdinalGEE.mean\_deriv\_exog
==================================================================================
.. currentmodule:: statsmodels.genmod.generalized_estimating_equations
.. automethod:: OrdinalGEE.mean_deriv_exog
| 32.444444 | 82 | 0.606164 |
55e154aa65b6be0e5dbcf694e130be4e92b8fe15 | 3,877 | rst | reStructuredText | doc/arch/adr-001.rst | agdsn/pycroft | ea771141d59c88fdb8a782eafbe106240550a33a | [
"Apache-2.0"
] | 18 | 2016-04-20T19:00:56.000Z | 2021-12-19T16:43:57.000Z | doc/arch/adr-001.rst | agdsn/pycroft | ea771141d59c88fdb8a782eafbe106240550a33a | [
"Apache-2.0"
] | 461 | 2016-07-20T00:42:59.000Z | 2022-03-25T17:03:07.000Z | doc/arch/adr-001.rst | agdsn/pycroft | ea771141d59c88fdb8a782eafbe106240550a33a | [
"Apache-2.0"
] | 15 | 2016-07-15T18:46:43.000Z | 2021-03-17T20:08:39.000Z | ADR001
======
:Number: 001
:Title: Use jQuery in typescript modules exclusively
:Author: Lukas Juhrich
:Created: 2021-06-20
:Status: Proposed
.. contents:: Table of Contents
Context
-------
There's multiple ways to interact with our HTML output using Javascript:
#. Add inline Javascript in e.g. a ``{% page_script %}`` block
#. Add an ECMAscript (ES) or typescript (TS) module,
configure webpack to export it as a chunk,
and reference it in the relevant HTML pages
#. Add an ES/TS module, and import it in the ``main`` chunk.
The important differences between option one and the other two are
- In inline JS, one cannot use an
`ES2015 import <https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Statements/import>`_
to use arbitrary libraries.
However, this can indirectly be achieved by using
the `expose-loader <https://github.com/webpack-contrib/expose-loader>`_
or the `ProvidePlugin <https://webpack.js.org/plugins/provide-plugin/>`_
in webpack's config to expose certain symbols as ``window.foo``.
- In a separate module, we're able to use typescript.
- A separate module has to undergo the webpack toolchain, whereas inline JS is “cheap” in that respect.
Prior to this decision, we did a cleanup of the webpack rules,
which replaced brute-force ``ProvidePlugin`` invocations
- by specific import injections via ``imports-loader``
- or by ``window`` attribute expositions using ``expose-loader``.
This is mainly motivated by a comment of Sebastian Schrader stating that blindly
providing things via ``ProvidePlugin`` can have detrimental effects on
`tree shaking <https://webpack.js.org/guides/tree-shaking/>`_
because webpack cannot make any strong assumptions anymore about who the dependents of an exposed symbol are.
Also, most uses of these plugins can be considered workarounds for a deficiency,
since most inter-module dependencies should be realized by proper module ``import`` s and ``export`` s.
In light of this workaround, two instances of inline JS broke
because jQuery's ``$`` symbol was not accessible anymore.
In one instance, this was actually unavoidable, because ``bootstrapTable``
is only accessible as a jQuery extension function, a fact which will
`remain that way <https://github.com/wenzhixin/bootstrap-table/issues/4796#issuecomment-578567848>`_
in the forseeable future.
Decision
--------
#. New JS code that requires jQuery or jQuery extension functions shall occur in TS modules.
#. No jQuery invocations shall exist in inline JS.
#. Current jQuery invocations that exist in ES modules shall be replaced by pure-ES alternatives wherever possible,
or turned into TS code.
This does not need to happen retrospectively, but at the latest whenever these invocations are next modified.
Consequences
------------
- The ``providePlugin`` section in the webpack config does not have to be reinstantiated.
- The aforementioned, broken inline-JS took significantly more effort to fix:
We had to create a new typescript module, and to make the ``$().bootstrap`` invocations compile,
and we had to add declaration files (``.d.ts``), declaring the signature of ``bootstrapTable('refresh', params)``.
- As a consequence, code completion and documentation lookups in JS files are now aware of this extension function,
and can provide documentation and type hints.
- Every new usage of ``bootstrapTable`` functionality now requires adding type declarations,
which is a slight increase in effort as opposed to just reading the API docs.
- From a contribbutor who is not too acquainted with TS syntax, this demands a few minutes more in time investment.
This cost however does not scale linearly, as with more functions declared,
more examples to imitate exist directly in the codebase.
- Frontend developers are forced to read up on modern solutions to the problems jQuery once tried to solve.
| 49.075949 | 116 | 0.768378 |
d967dcd5e257f558f2db046cfa4bd188f720e136 | 3,773 | rst | reStructuredText | demo/demo.rst | robsiegwart/rst2html2 | a95b623622496a5676d0842bdadd2f5554b47b41 | [
"MIT"
] | null | null | null | demo/demo.rst | robsiegwart/rst2html2 | a95b623622496a5676d0842bdadd2f5554b47b41 | [
"MIT"
] | null | null | null | demo/demo.rst | robsiegwart/rst2html2 | a95b623622496a5676d0842bdadd2f5554b47b41 | [
"MIT"
] | null | null | null | ================================================================================
Quisque nec efficitur risus
================================================================================
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Praesent sit amet
tempor nisi, nec tempus enim. Donec facilisis libero suscipit ultrices lacinia.
Maecenas volutpat auctor quam, in vulputate velit dignissim scelerisque. Integer
eget cursus sapien. [Phasellus]_ in erat et tellus bibendum finibus. Maecenas eu
tincidunt libero. Aenean varius eu dolor non interdum.
Integer sed libero sollicitudin, fermentum nisl eu, porttitor arcu. Aliquam
tincidunt, ligula eu scelerisque aliquam, tortor nibh elementum quam, laoreet
pulvinar mauris massa non risus. Aenean mattis pulvinar justo, nec viverra
massa. Sed sit amet fermentum ligula.
- Phasellus
- eu lacus
- ligula
- Nullam
- urna
- magna
Duis finibus fringilla vulputate
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Quisque aliquet faucibus ultrices. Sed laoreet nunc sed ipsum commodo, ac
tincidunt ligula volutpat. Vestibulum pellentesque massa sed imperdiet sagittis.
=============== =================== =====================================
Lorem ipsum dolor sit amet, consectetur adipiscing elit.
=============== =================== =====================================
Maecenas smod neque non nibh feugiat iaculis.
Nulla finibus libero id suscipit tincidunt.
Ut quis nunc sed purus sodales viverra.
Maecenas ac enim in ligula sodales finibus.
Praesent eget libero ac nulla consequat maximus ac nec nisi.
=============== =================== =====================================
Pellentesque pellentesque sollicitudin libero, eget tincidunt nibh vestibulum
sit amet. Suspendisse sodales magna et mauris ornare ullamcorper. Fusce porta
rutrum nisi et porttitor_.
Vestibulum euismod
Nullam condimentum dolor lorem
Suspendisse sodales
Pellentesque pellentesque
Donec facilisis libero
----------------------
:suscipit nisl: Aliquam nec ex rhoncus
:nec tempus: Aenean varius eu dolor non interdum.
:eget tincidunt: Fusce porta
Orci varius natoque penatibus et magnis dis parturient montes, nascetur
ridiculus mus.
Phasellus at mollis nulla, a convallis lectus. Mauris enim
risus, pellentesque vitae felis ac, placerat laoreet purus.
Cras diam ligula, scelerisque nec magna sit amet, ornare ultrices est.
Suspendisse id sapien ante.
-- Lorem ipsum
Proin ultrices tortor diam, ut scelerisque odio eleifend ac. Donec semper augue
et ante mattis iaculis. Pellentesque auctor non dolor non efficitur. Sed
bibendum sagittis odio id vulputate. Duis posuere ullamcorper aliquet. Ut
venenatis nulla a convallis rutrum. Quisque ultricies aliquet ante ut dapibus.
Pellentesque quis eleifend mauris. Maecenas sem mi, sodales vitae tempor vitae,
hendrerit nec velit. Maecenas suscipit tincidunt nisl a viverra. ::
Etiam blandit vestibulum rhoncus. Etiam sit amet viverra mi. Donec
venenatis, sem id sodales maximus, arcu lectus facilisis urna, nec
tincidunt orci massa feugiat velit. Sed tellus odio, ullamcorper vitae
lectus vitae, pharetra posuere mauris. Morbi rhoncus mauris a arcu
tincidunt interdum. Aenean vel magna rutrum, fringilla nunc nec,
sollicitudin libero. Integer ut porta dui.
Praesent aliquet rhoncus nulla, non commodo ligula efficitur at. Integer
vestibulum lacus et elit vehicula convallis.
1. Integer accumsan blandit quam quis sagittis.
2. Praesent vestibulum mi massa, sit amet iaculis mi pulvinar in.
3. Cras sed purus non dui consectetur efficitur. Duis a justo tortor.
------
.. [Phasellus] Donec tincidunt bibendum dui
.. _porttitor: https://python.org/
| 36.990196 | 80 | 0.686721 |
7a2856818841cda986239987f79a7f97ef6b9876 | 598 | rst | reStructuredText | docs/usage.rst | smorad/python_natnet | aa0d7030584dc7f6a4be3f37f81f6c1e9b016ef8 | [
"BSD-3-Clause"
] | 11 | 2021-10-15T15:51:24.000Z | 2021-12-26T16:43:17.000Z | docs/usage.rst | smorad/python_natnet | aa0d7030584dc7f6a4be3f37f81f6c1e9b016ef8 | [
"BSD-3-Clause"
] | 6 | 2018-01-24T15:22:10.000Z | 2022-02-22T14:55:16.000Z | docs/usage.rst | smorad/python_natnet | aa0d7030584dc7f6a4be3f37f81f6c1e9b016ef8 | [
"BSD-3-Clause"
] | 12 | 2018-11-27T17:09:12.000Z | 2022-03-02T11:18:12.000Z | =====
Usage
=====
To use `natnet` in a project::
import natnet
client = natnet.Client.connect()
client.set_callback(
lambda rigid_bodies, markers, timing: print(rigid_bodies))
client.spin()
This will autodiscover your NatNet server (or complain if there is none or more than one), synchronize clocks, fetch model descriptions, subscribe to mocap frames, and call your callback each time a mocap frame arrives.
For a full example, see ``scripts\natnet-client-demo.py``.
Another example is `mje-nz/natnet_ros <https://github.com/mje-nz/natnet_ros>`_, a ROS driver based on this library.
| 35.176471 | 219 | 0.750836 |
d8f79ae01259ff173794ce01dff4be79694f24d7 | 5,298 | rst | reStructuredText | README.rst | ortsed/metalog | 851a75d7afd66a584c68543e7031a588cf50ea84 | [
"MIT"
] | 3 | 2019-10-13T02:31:54.000Z | 2020-11-02T15:23:03.000Z | README.rst | ortsed/metalog | 851a75d7afd66a584c68543e7031a588cf50ea84 | [
"MIT"
] | 3 | 2019-10-13T02:50:34.000Z | 2021-07-28T19:38:56.000Z | README.rst | ortsed/metalog | 851a75d7afd66a584c68543e7031a588cf50ea84 | [
"MIT"
] | 3 | 2021-11-22T18:48:19.000Z | 2022-01-22T07:36:34.000Z | metalog
=======
Sergey Kim, Reidar Brumer Bratvold
Metalog Distribution
--------------------
The metalog distributions constitute a new system of continuous
univariate probability distributions designed for flexibility,
simplicity, and ease/speed of use in practice. The system is comprised
of unbounded, semi-bounded, and bounded distributions, each of which
offers nearly unlimited shape flexibility compared to Pearson, Johnson,
and other traditional systems of distributions.
The package requires the following packages: **numpy, pandas, matplotlib and scipy (ver 1.3.1)**.
The following
`paper <http://www.metalogdistributions.com/images/TheMetalogDistributions.pdf>`__
and `website <http://www.metalogdistributions.com/home.html>`__ provide
a full background of the metalog distribution.
Using the Package
-----------------
This Python package was transfered from
`RMetalog <https://github.com/isaacfab/RMetalog>`__ package by Isaac J.
Faber and therefore shares the same R-based structure.
The
`data <https://www.sciencebase.gov/catalog/item/5b45380fe4b060350a140b7b>`__
used for demonstration are body length of salmon and were collected in
2008-2010:
::
import numpy as np
import pandas as pd
salmon = pd.read_csv("Chinook and forage fish lengths.csv")
# Filtered data for eelgrass vegetation and chinook salmon
salmon = salmon[(salmon['Vegetation'] == 'Eelgrass') & (salmon['Species'] == 'Chinook_salmon')]
salmon = np.array(salmon['Length'])
To import package with metalog distribution run the code:
::
from metalog import metalog
To **fit the data to metalog distribution** one should use function
``metalog.fit()``. It has the following arguments:
- ``x``: data.
- ``bounds``: bounds of metalog distribution. Depending on
``boundedness`` argument can take zero, one or two values.
- ``boundedness``: boundedness of metalog distribution. Can take values
``'u'`` for unbounded, ``'sl'`` for semi-bounded lower, ``'su'`` for
semi-bounded upper and ``'b'`` for bounded on both sides.
- ``term_limit``: maximum number of terms to specify the metalog
distribution. Can take values from 3 to 30.
- ``term_lower_bound``: the lowest number of terms to specify the
metalog distribution. Must be greater or equal to 2 and less than
``term_limit``. The argument is optional. Default value is 2.
- ``step_len``: size of steps to summarize the distribution. The
argument is optional. Default value is 0.01.
- ``probs``: probabilities corresponding to data. The argument is
optional. Default value is ``numpy.nan``.
- ``fit_method``: fit method ``'OLS'``, ``'LP'`` or ``'any'``. The
argument is optional. Default value is ``'any'``.
- ``save_data``: if ``True`` then data will be saved for future update.
The argument is optional. Default values is ``False``.
Fit metalog distribution to data and store the result to variable
``metalog_salmon``. The distribution is bounded on both sides: from 0 to
200. Term limit is set to 10:
::
metalog_salmon = metalog.fit(x=salmon, boundedness='b', bounds=[0, 200], term_limit=10)
To get **summary of distribution** call the following function with only
one argument ``m`` - the variable that stores fitted metalog
distribution:
::
metalog.summary(m=metalog_salmon)
Output:
::
-----------------------------------------------
SUMMARY OF METALOG DISTRIBUTION OBJECT
-----------------------------------------------
PARAMETERS
Term Limit: 10
Term Lower Bound: 2
Boundedness: b
Bounds (only used based on boundedness): [0, 200]
Step Length for Distribution Summary: 0.01
Method Use for Fitting: any
Number of Data Points Used: 138
Original Data Saved: False
VALIDATION AND FIT METHOD
term valid method
2 2 yes OLS
3 3 yes OLS
4 4 yes OLS
5 5 yes OLS
6 6 yes OLS
7 7 yes OLS
8 8 yes OLS
9 9 yes OLS
10 10 yes OLS
It's possible **to plot corresponding PDF and CDF** of metalog
distribution:
::
metalog.plot(m=metalog_salmon)
Output:
.. figure:: https://raw.githubusercontent.com/kimsergeo/metalog/master/figures/figure_1.png
:alt: pdf\_cdf
**To draw samples** from distribution use ``metalog.r()`` function where
``n`` is number of samples and ``term`` specifies the terms of
distribution to sample from:
::
metalog.r(m=metalog_salmon, n=5, term=10)
Output:
::
array([73.81897286, 86.74055734, 84.22509619, 83.80426247, 97.79800677])
**To get densities** based on quantiles type ``metalog.d()`` function
where ``q`` is vector of quantiles:
::
metalog.d(m=metalog_salmon, q=[50, 110, 150], term=10)
Output:
::
array([0.00038265, 0.00712032, 0.00373991])
**To calculate probabilities** based on quantiles use ``metalog.p()``
function:
::
metalog.p(m=metalog_salmon, q=[50, 110, 150], term=10)
Output:
::
array([0.00275336, 0.82349578, 0.98686581])
Finally, **to get quantiles** from probabilites input ``metalog.q()``:
::
metalog.q(m=metalog_salmon, y=[0.00275336, 0.82349578, 0.98686581], term=10)
Output:
::
array([ 50.02583336, 109.99861143, 149.99737059])
| 27.030612 | 99 | 0.674783 |
71de293a1132efac944790c894bc703e0a80ea62 | 175 | rst | reStructuredText | source/javascript/phonegap/index.rst | pkimber/my-memory | 2ab4c924f1d2869e3c39de9c1af81094b368fb4a | [
"Apache-2.0"
] | null | null | null | source/javascript/phonegap/index.rst | pkimber/my-memory | 2ab4c924f1d2869e3c39de9c1af81094b368fb4a | [
"Apache-2.0"
] | null | null | null | source/javascript/phonegap/index.rst | pkimber/my-memory | 2ab4c924f1d2869e3c39de9c1af81094b368fb4a | [
"Apache-2.0"
] | null | null | null | PhoneGap
********
PhoneGap is an open source development tool for building fast, easy mobile apps
with JavaScript.
Contents
.. toctree::
:maxdepth: 1
links
issues
| 13.461538 | 79 | 0.702857 |
0cd1103b2bb1fe0f12ce6ce2d648f181bb3cea98 | 318 | rst | reStructuredText | docs/installation.rst | 1arshan/django-jsonform | 40f38f73a573027ebd973272462eb7ab6156e231 | [
"BSD-3-Clause"
] | null | null | null | docs/installation.rst | 1arshan/django-jsonform | 40f38f73a573027ebd973272462eb7ab6156e231 | [
"BSD-3-Clause"
] | null | null | null | docs/installation.rst | 1arshan/django-jsonform | 40f38f73a573027ebd973272462eb7ab6156e231 | [
"BSD-3-Clause"
] | 1 | 2021-09-03T18:22:35.000Z | 2021-09-03T18:22:35.000Z | Installation
============
Install using pip:
.. code-block:: sh
$ pip install django-jsonform
Update your project's settings:
.. code-block:: python
# settings.py
INSTALLED_APPS = [
# ...
'django_jsonform'
]
Next, go to :doc:`quickstart` page for basic usage instructions. | 13.826087 | 64 | 0.603774 |
00ca6597db0a5dcaa615095672ddbc4c72331113 | 23,396 | rst | reStructuredText | releasenotes.rst | nasefbasdf/enaml | 26544b0e736f4c38135c5cf1fbbbb445a9884363 | [
"BSD-3-Clause-Clear"
] | null | null | null | releasenotes.rst | nasefbasdf/enaml | 26544b0e736f4c38135c5cf1fbbbb445a9884363 | [
"BSD-3-Clause-Clear"
] | null | null | null | releasenotes.rst | nasefbasdf/enaml | 26544b0e736f4c38135c5cf1fbbbb445a9884363 | [
"BSD-3-Clause-Clear"
] | null | null | null | Enaml Release Notes
===================
0.10.3 - unreleased
-------------------
- add support for tiling and cascading to MdiArea PR # 259
- fix issue # 174 (MdiWindow not automatically shown when added) PR # 259
- add minimal workbench documentation PR # 258
- add support for font-stretch PR # 258
- remove dependency on future to reduce import time PR #255
- add constraints to enforce image aspect ratio in ImageView PR #254
- improvements to the scintilla widget and live editor PR #243
0.10.2 - 28/01/2018
-------------------
- fix import of QScintilla under PyQt5 PR #230
- add support for importing enaml files from zip archives #232
- fix menu item ordering under Python 3 #233
- fix repr of declarative function objects #235
- properly reset layout_container member in qt backend after a widget has been
reparented #240
- fix calls to explicit_warn which could lead to global vars corruption #247
- add a text align member to Field to control text alignment #249
- fix the parsing rules for function definitions #252
- several improvements to the handling of comprehensions and lambdas #242 #245
0.10.1 - 13/11/2017
-------------------
- fix mistake in setup.py file preventing conda package building
0.10.0 - 12/11/2017
-------------------
- add support for Qt5 (based on QtPy) PR #228
- add support for Python 3 (3.3, 3.4, 3.5, 3.6) (f-strings are not supported) PR #227
- refactor the parser to be based on classes PR #227
- move every parser/lexer related module in the parser package PR #227
- support for dict and set comprehensions in enaml files PR #227
0.9.8 - 08/04/2014
------------------
- Add drag and drop support. 56a2127e714c_
- Remove the Wx backend and free the people from their misery. bab233ff9782_
.. _56a2127e714c: https://github.com/nucleic/enaml/commit/56a2127e714cef2a22b65b00f2afd6b8024f36ec
.. _bab233ff9782: https://github.com/nucleic/enaml/commit/bab233ff9782011185730f9dcaccd7113817a297
0.9.7 - 05/18/2014
------------------
- Add an IPythonConsole widget.
- Add support for widgets in tool bars and menus.
- Add a ToolButton widget.
- Removed the 'focus_policy' attribute.
- Removed the 'show_focus_rect' attribute.
- Fix bugs #122, #123, #124, #131, #145
0.9.6 - 05/08/2014
------------------
- Add a declarative function syntax to the grammar.
- Add a comprehensive focus API. 1090b3f35a9c_
.. _1090b3f35a9c: https://github.com/nucleic/enaml/commit/1090b3f35a9c90b6496864907b816a507951ffb5
0.9.5 - 04/28/2014
------------------
- Allow pressing escape while dragging a floating dock window. e732d2bb3c6c_
- Fix line ending issues in live editor on old versions of OSX (thanks to JF). 0a54944728ae_
.. _e732d2bb3c6c: https://github.com/nucleic/enaml/commit/e732d2bb3c6c905cd7f2fe92171e2eab46d8d0e4
.. _0a54944728ae: https://github.com/nucleic/enaml/commit/0a54944728ae8a688310bb68177092b13baa6c62
0.9.4 - 03/13/2014
------------------
- Allow enamldef objects to be properly pickled. db99d02fa377_
.. _db99d02fa377: https://github.com/nucleic/enaml/commit/db99d02fa3773ac99f5e02709037e6ba0df952af
0.9.3 - 03/10/2014
------------------
- Return the value of the command handler from CorePlugin.invoke_command. 5322bd1d2a67_
- Automatically request relayout when widget visibility changes. 5d24f8ab13cb_
- Add knobs for controlling Form row and column spacing. cdb747d8d1fa_
- Add VGroup and HGroup convenience layout factories. aed5ddd623d1_
- Add a 'factory' layout helper. 41480f2694d2_
.. _5322bd1d2a67: https://github.com/nucleic/enaml/commit/5322bd1d2a675348f50df1adc0479f6aa4b406dd
.. _5d24f8ab13cb: https://github.com/nucleic/enaml/commit/5d24f8ab13cb23385ce22701389920779b3dc546
.. _cdb747d8d1fa: https://github.com/nucleic/enaml/commit/cdb747d8d1fa49732d95f7b4b358f4da9820477a
.. _aed5ddd623d1: https://github.com/nucleic/enaml/commit/aed5ddd623d1a4041dd9349af5baf4a56f5863dd
.. _41480f2694d2: https://github.com/nucleic/enaml/commit/41480f2694d27cecbc97cc347f60000e205d4c8f
0.9.2 - 02/20/2014
------------------
- Update the layout (if needed) when changing fonts.
- Minor code cleanup and documentation updates.
0.9.1 - 02/11/2014
------------------
- Add the workbench plugin framework. 2ab09c6782b4_
- Fix idiosyncrasies in layout. 5a9f529671dd_
- Add a VTKCanvas control. b04262195c27_
- Add ability to veto a window close. bbd9aa1be9f2_
- Fix issues #64 #119 #120 #128 #129
.. _2ab09c6782b4: https://github.com/nucleic/enaml/commit/2ab09c6782b4d4d5002bb4cfee7f4dbeb6102187
.. _5a9f529671dd: https://github.com/nucleic/enaml/commit/5a9f529671dd1af8ed81e202b70738d0aee10a0d
.. _b04262195c27: https://github.com/nucleic/enaml/commit/b04262195c27cb43e7e2836b576ce8ba01a9a356
.. _bbd9aa1be9f2: https://github.com/nucleic/enaml/commit/bbd9aa1be9f2f02315b651cc18cb2222d7ff67d1
0.9.0 - 01/13/2014
------------------
- Fix issue #78. f0d1fc7da0d7_
- Update the layout engine to use the Kiwi solver. d41729049f63_
.. _f0d1fc7da0d7: https://github.com/nucleic/enaml/commit/f0d1fc7da0d7bc9c184119e983da266422635a0b
.. _d41729049f63: https://github.com/nucleic/enaml/commit/d41729049f637def16f7bc9685dc685a8c780032
0.8.9 - 11/25/2013
------------------
- Add ability to query window minimized/maximized state. 713feb85952a_
- Implement 'always_on_top' window flag. 3ac3e6955579_
- A handful of bug fixes.
.. _713feb85952a: https://github.com/nucleic/enaml/commit/713feb85952ab93094d6f06a8af457871355207c
.. _3ac3e6955579: https://github.com/nucleic/enaml/commit/3ac3e6955579595c1c2ce2a74e79c1f96fe4a21e
0.8.8 - 11/7/2013
-----------------
- Add a task dialog mini-framework and a MessageBox stlib component. 5583808f293a_
.. _5583808f293a: https://github.com/nucleic/enaml/commit/5583808f293a881ea52b00907fd3d85cc2b3e7b0
0.8.7 - 11/4/2013
-----------------
- Add an alerting api for dock items in a dock area. ba766d773090_
.. _ba766d773090: https://github.com/nucleic/enaml/commit/ba766d7730908c7370727da8713a74f7d1380ed2
0.8.6 - 10/30/2013
------------------
- Add 'limit_width' and 'limit_height' virtual constraints. 8722be90844e_
.. _8722be90844e: https://github.com/nucleic/enaml/commit/8722be90844ed68809de792b818cd399bbb8bfa2
0.8.5 - 10/29/2013
------------------
- Add support for style sheets to the DockArea. 5e38c591ad55_
.. _5e38c591ad55: https://github.com/nucleic/enaml/commit/5e38c591ad55683d367b652460f70b75f3f087b2
0.8.4 - 10/28/2013
------------------
- Add a size hint mode switch to Notebook and Stack. 330c7a337c32d_
.. _330c7a337c32d: https://github.com/nucleic/enaml/commit/330c7a337c32d1b15a8d8d50acfc4ea208fd5330
0.8.3 - 10/25/2013
------------------
- Add support for style sheets. 77e2a0afbd56_
- Fix a bug with a null widget and the notebook selected tab. 64cfe8789838_
.. _77e2a0afbd56: https://github.com/nucleic/enaml/commit/77e2a0afbd56489fe457c13c0b3e12e0187393ce
.. _64cfe8789838: https://github.com/nucleic/enaml/commit/64cfe87898382b9a76a0450914d40272b6fa6d02
0.8.2 - 10/11/2013
------------------
- Add a DynamicTemplate declarative object. ede76a778a86_
- Add 'window' mode to PopupView. f37263fd7b7d_
- Add 'selected_tab' attribute to the Notebook. 45ca092e7222_
- Overhaul of the docs and doc build system.
- Various bug fixes and performance improvements.
.. _ede76a778a86: https://github.com/nucleic/enaml/commit/ede76a778a864dbb79636f38a15fd6b24e975228
.. _f37263fd7b7d: https://github.com/nucleic/enaml/commit/f37263fd7b7db22c0a404660ccaea3f444b8a171
.. _45ca092e7222: https://github.com/nucleic/enaml/commit/45ca092e722209163c4dad81741d2f09595efade
0.8.1 - 09/25/2013
------------------
- Update the PopupView to automatically reposition on-screen. 3225683f9411_
- Minor bug fixes.
- Added an ImageView example.
.. _3225683f9411: https://github.com/nucleic/enaml/commit/3225683f9411266d98b050be252440c7f5a1e892
0.8.0 - 09/20/2013
------------------
- Added templates to the language.
- Added aliases to the language.
- Removed the compatibility code scheduled for removal.
- Added a completely new declarative expression engine.
0.7.20 - 08/12/2013
-------------------
- Bugfix area layout traversal. 308164fd5134_
- Allow alpha hex colors. d9605cc55bb5_
- Add a declarative Timer object. 13259258e6fd_
- Added a Scintilla widget.
- Added the applib sub-package.
- Added live editor components to the applib.
- Added an 'auto_sync' submit trigger to Field. 1926cde5e64b_
.. _308164fd5134: https://github.com/nucleic/enaml/commit/308164fd513416ffb52a38db9b5b7039942e32f2
.. _d9605cc55bb5: https://github.com/nucleic/enaml/commit/d9605cc55bb546f1a2593df0865687678de182f1
.. _13259258e6fd: https://github.com/nucleic/enaml/commit/13259258e6fdb62181a26b24cef9d69f70c37ac3
.. _1926cde5e64b: https://github.com/nucleic/enaml/commit/1926cde5e64ba3b4227886268869b10e755d5c0b
0.7.19 - 07/22/2013
-------------------
- Added dock layout ops for extending/retracting from dock bars. 00ee34a102f_
- Added methods for manipulating window geometry. bebba0a82fa_
.. _00ee34a102f: https://github.com/nucleic/enaml/commit/00ee34a102fd28c1861a82f784699844c5537c6c
.. _bebba0a82fa: https://github.com/nucleic/enaml/commit/bebba0a82face4000a28bdff73e4df71fcbeb356
0.7.18 - 07/20/2013
-------------------
- Production release of dock area toolbars.
- Updates to dock layout specification with compatibility env setting.
- Resizable slide-out dock bar items.
- Pin buttons on dock items.
- Improved procedural dock layout modification api.
- Added a base Frame class which supplies borders for subclasses. d1316f40248_
- Fixed container ref-cycle issue on widget destruction. 03a5e53038f_
.. _d1316f40248: https://github.com/nucleic/enaml/commit/d1316f40248eaef807705ccc9954f43eebece954
.. _03a5e53038f: https://github.com/nucleic/enaml/commit/03a5e53038f2aac1d187d9bb2c27c86c2b1d9caf
0.7.17 - 07/03/2013
-------------------
- Added easier to use operator hooks. 2aaf3c96fc8_
- Added support for PySide. 0d18a21754e_
- Add cursor anchor mode to PopupView. 74ddd47197e_
- Initial feedback release of dock area toolbars.
.. _2aaf3c96fc8: https://github.com/nucleic/enaml/commit/2aaf3c96fc89bc064e52a83ef416c752a5bbedf5
.. _0d18a21754e: https://github.com/nucleic/enaml/commit/0d18a21754ee9b071b0986289ddfdb380ab016fc
.. _74ddd47197e: https://github.com/nucleic/enaml/commit/74ddd47197ef9330e69cf9cb137aeb45a0204d07
0.7.16 - 06/19/2013
-------------------
- Add a more useful file dialog as FileDialogEx. 390868cccb_
- Add a color selection dialog as ColorDialog. d722a876e9_
- Persist the linked state of floating dock items in a saved layout. adc9dec8db_
- Add a right click event to the dock item title bar. 812e97aebcf_
- Make the dock item title user editable. 54b68881529_
- Make the visibility of the dock item title bar configurable. 54b68881529_
- Toggle the maximized state of a dock item on title bar double click. 4ffe9d6b68e_
- Add a RawWidget widget to easily embed external widgets into Enaml. e9d25a29e77_
.. _390868cccb: https://github.com/nucleic/enaml/commit/390868cccb718dc33b48d2943d7150826daf0886
.. _d722a876e9: https://github.com/nucleic/enaml/commit/d722a876e9309bff81b78324c6553e73a4b5c6ab
.. _adc9dec8db: https://github.com/nucleic/enaml/commit/adc9dec8dbf562f1e365573739532ca7bdd1dda4
.. _812e97aebcf: https://github.com/nucleic/enaml/commit/812e97aebcf2e06142b516383097d5fb51d8872b
.. _54b68881529: https://github.com/nucleic/enaml/commit/54b688815295b3d1181986a6b91784ff68e9ae72
.. _4ffe9d6b68e: https://github.com/nucleic/enaml/commit/4ffe9d6b68ed55496ef9491aa13d62805aa59543
.. _e9d25a29e77: https://github.com/nucleic/enaml/commit/e9d25a29e77c7177cef3dd85733867faddb6eac1
0.7.15 - 06/12/2013
-------------------
- Fix a bug in parsing elif blocks. e25363b005_
.. _e25363b005: https://github.com/nucleic/enaml/commit/e25363b00581ece64aad02fee369119e8393b5ce
0.7.14 - 06/05/2013
-------------------
- Make the translucent background of PopupView configurable. 0731314117_
- Add a 'live_drag' flag to the DockArea. 0cd6889b2c_
.. _0731314117: https://github.com/nucleic/enaml/commit/0731314117c2c9cbd29f7e285b487f6cb30754e0
.. _0cd6889b2c: https://github.com/nucleic/enaml/commit/0cd6889b2c0b9c086605fce5322c07c7ee92e448
0.7.13 - 05/31/2013
-------------------
- Feature improvements and fixes to snappable dock frames. 693a6f363a_
- Add a 'link_activated' event to the Label widget. 269b386639_
.. _693a6f363a: https://github.com/nucleic/enaml/commit/693a6f363a6be6751734c64e1e1c0454dcdc1325
.. _269b386639: https://github.com/nucleic/enaml/commit/269b3866397ed126dd11083f1be99ba6296d5892
0.7.12 - 05/29/2013
-------------------
- Make floating dock windows snappable and linkable. de3ced381e_
.. _de3ced381e: https://github.com/nucleic/enaml/commit/de3ced381e3b4dde88bb59fdab5399eb7173ceba
0.7.11 - 05/28/2013
-------------------
- Claw back the direct exposure of the Qt stylesheets. 947760ebcd_
.. _947760ebcd: https://github.com/nucleic/enaml/commit/947760ebcd68f351f268913ebbd396a6da24f06d
0.7.10 - 05/26/2013
-------------------
- Expose the Qt stylesheet directly for the dock area. 5877335bcf_
- Add the ability to style the various dock area buttons. 5877335bcf_
.. _5877335bcf: https://github.com/nucleic/enaml/commit/5877335bcf8fd09c9d066a17905b4d92ca24de8d
0.7.9 - 05/24/2013
------------------
- Make the close button on dock items configurable. d839fb0c2b_
- Expose a public api for manipulating the dock layout. e269adbdb2_
- Expose user configurable dock area styles. 4c05d5953f_
.. _4c05d5953f: https://github.com/nucleic/enaml/commit/4c05d5953fd0cbefdb66ca502ff662d259955ee1
.. _e269adbdb2: https://github.com/nucleic/enaml/commit/e269adbdb23ecfd6c6728af3ca8857e20d40415f
.. _d839fb0c2b: https://github.com/nucleic/enaml/commit/d839fb0c2bd096a6580d8ab887dfc6787928bcd5
0.7.8 - 05/20/2013
------------------
- Add support for maximizing a docked item within a DockArea. a051862ce5_
- Update the popup view to use a 45 degree angled arrow. f3edc88fe1_
- Miscellaneous updates and bug fixes to the DockArea.
.. _a051862ce5: https://github.com/nucleic/enaml/commit/a051862ce5dbe2240295c4ae9fc19187554a928f
.. _f3edc88fe1: : https://github.com/nucleic/enaml/commit/f3edc88fe163cbe02b08b5215f78de0fbd1ac61b
0.7.7 - 05/09/2013
------------------
- Add support for floating "dock rafts" in the DockArea. 402330dcaf_
- Add a PopupView widget to support transparent popups and growl-style notifications. a5117121bf_
.. _402330dcaf: https://github.com/nucleic/enaml/commit/402330dcafefaf8470db74bf632d58f039fc4a4f
.. _a5117121bf: https://github.com/nucleic/enaml/commit/a5117121bf5e553a6d5953685605494d676d1661
0.7.6 - 04/25/2013
------------------
- Add an advanced DockArea widget. 3ed122b110_
- Add popup() functionality to the Menu widget. 5363a56f33_
.. _3ed122b110: https://github.com/nucleic/enaml/commit/3ed122b11050ee72383aa0ef08ca2537ec7eb841
.. _5363a56f33: https://github.com/nucleic/enaml/commit/5363a56f336e7302d6c2876e0b630794b9f751ae
0.7.5 - 04/09/2013
------------------
- Fix a bug in the Wx main window implementation. 39f6baee49_
.. _39f6baee49: https://github.com/nucleic/enaml/commit/39f6baee49ddb601f8fde5b222fadf4053075a73
0.7.4 - 04/04/2013
------------------
- Add border support for Container on the Qt backend. 505662d5f1_
- Workaround a logic bug in Wx's handling of modal windows. 56a1e00112_
- Workaround a Wx segfault during window destruction. a8525788c9_
.. _505662d5f1: https://github.com/nucleic/enaml/commit/505662d5f1ad0bdf50a4439873a252c2367dc418
.. _56a1e00112: https://github.com/nucleic/enaml/commit/56a1e001127f12ea971b11343e58711466af1895
.. _a8525788c9: https://github.com/nucleic/enaml/commit/a8525788c9a8ccf50c657fefc85db66d0a78abf9
0.7.3 - 04/03/2013
------------------
- Added support for adding/removing models in a ViewTable. 5bc1809340_
- Added an ObjectCombo control which is a more flexible combo box. 51f3a3c6d3_
- Emit useful error messages when a backend does not implement a control. b264b3b927_
.. _5bc1809340: https://github.com/nucleic/enaml/commit/5bc1809340543aa7184a96cd7a1da3daa37c19dd
.. _51f3a3c6d3: https://github.com/nucleic/enaml/commit/51f3a3c6d3e6fe8c076a8baa26c33ada895beb18
.. _b264b3b927: https://github.com/nucleic/enaml/commit/b264b3b927b979fb83766e82656f70d0023c6a48
0.7.2 - 04/02/2013
------------------
- Added first real cut at a model-viewer grid-based control. de0d8e35ae_
- Fix a bug in size hinting during complex relayouts. 963cee88d0_
- Added hooks for proxy-specific customization. 3e045dfb18_
.. _de0d8e35ae: https://github.com/nucleic/enaml/commit/de0d8e35aee42d5eda63ad0bef0b8eb0adf299f5
.. _963cee88d0: https://github.com/nucleic/enaml/commit/963cee88d09e2e0ff0c9c4d41b2ac2e8ee6f4ab6
.. _3e045dfb18: https://github.com/nucleic/enaml/commit/3e045dfb18ee74000106c7559626449102930010
0.7.1 - 03/28/2013
------------------
- Updated compiler infrastructure to produce more extensible parse trees.
- Various bug fixes.
0.7.0 - 03/20/2013
------------------
- First release under new nucleic org.
- Rewrite of entire framework to sit on top of Atom instead of Traits.
- Vastly improved backend architecture.
- Improved compile-time operator binding.
0.6.8 - 02/14/2013
------------------
- Added ability to change the Z order of a window and a flag to make it stay on top. d6f618101f_
- Added a multiline text entry widget. dde4bd3409_
- Bugfix when ImageView is used in a ScrollArea. 67133d3fec_
.. _d6f618101f: https://github.com/enthought/enaml/commit/d6f618101f281aec8fd124fc5d7faf51066ffc99
.. _dde4bd3409: https://github.com/enthought/enaml/commit/dde4bd34097c59d982ebf5121e0a111b88c1a3f8
.. _67133d3fec: https://github.com/enthought/enaml/commit/67133d3fec03c567dab38aa9123002cab4f6215b
0.6.7 - 01/23/2013
------------------
- Added a `root_object()` method on the `Object` class which returns the root of the object tree. d9b4830963_
- Properly handle window modality on the Qt backend. 28f2433814_
- Add a `destroy_on_close` flag to the `Window` class. 2a63e8cefd_
- Prevent Wx from destroying top-level windows by default. 8e298e768e_
- Add support for adding windows to a session at run-time. c090c0fad6_
- Fix the lifetime bug with the `FileDialog`. 8e354de858_
.. _d9b4830963: https://github.com/enthought/enaml/commit/d9b48309631ed315b67ddf9c4222a2efcf4858ee
.. _28f2433814: https://github.com/enthought/enaml/commit/28f243381439ce1ce263cad2672b62a96bc87a0c
.. _2a63e8cefd: https://github.com/enthought/enaml/commit/2a63e8cefde29416291536ec6c02a05b612e11b1
.. _8e298e768e: https://github.com/enthought/enaml/commit/8e298e768eb45248cc98f682c9cc3b3f473b2a29
.. _c090c0fad6: https://github.com/enthought/enaml/commit/c090c0fad64a30936fc79774f8e851dca46076b6
.. _8e354de858: https://github.com/enthought/enaml/commit/8e354de858a6ee5deeda96dafa6322579c5514a6
0.6.6 - 01/10/2013
------------------
- Fix the broken unittests and make them Python 2.6 safe. 2c1d7f01d_
.. _22c1d7f01d: https://github.com/enthought/enaml/commit/22c1d7f01d844979c166e2f156d18a553f2c0152
0.6.5 - 01/10/2013
------------------
- Add a stretch factor to the Splitter widget. c2272cf1ef_
- Fix bugs in the Wx splitter implementation. dfa542ba3d_
.. _c2272cf1ef: https://github.com/enthought/enaml/commit/c2272cf1eff3e667c6ea1d255cc9c13c14745872
.. _dfa542ba3d: https://github.com/enthought/enaml/commit/dfa542ba3d36d6b968bffb1dcd1e0ed96ddbcf3b
0.6.4 - 01/07/2013
------------------
- Add support for icons on notebook pages on the Qt backend. b6426b7ae9_
- Add support for popup menus in the Wx backend (Qt is already supported). 153f3124b2_
- Add simpler way of building the optional C++ extensions. 4eebd59ae5_
- Update enaml-run to play nice with ETS_TOOLKIT. f864975a87_
.. _f864975a87: https://github.com/enthought/enaml/commit/f864975a872189a76dc8a2cf9e2469a78320a906
.. _4eebd59ae5: https://github.com/enthought/enaml/commit/4eebd59ae51df08d255ffe3860db821781f40579
.. _153f3124b2: https://github.com/enthought/enaml/commit/153f3124b2c62f2a5e7695e7ea1a8dff067f2fc5
.. _b6426b7ae9: https://github.com/enthought/enaml/commit/b6426b7ae9bcab9f8549fa635216c6cfd39ee29b
0.6.3 - 12/11/2012
------------------
- Fix critical bug related to traits Disallow and the `attr` keyword. 25755e2bbd_
.. _25755e2bbd: https://github.com/enthought/enaml/commit/25755e2bbd5e2e38e42d30776e1864d52c992af3
0.6.2 - 12/11/2012
------------------
- Fix critical bug for broken dynamic scoping. a788869ab0_
.. _a788869ab0: https://github.com/enthought/enaml/commit/a788869ab0a410c478cbe4cc066fc8ee35b266b8
0.6.1 - 12/10/2012
------------------
- Fix critical bug in compiler and expression objects. dfb6f648a1_
.. _dfb6f648a1: https://github.com/enthought/enaml/commit/dfb6f648a15370249b0a57433b8839a4caba7d35
0.6.0 - 12/10/2012
------------------
- Add Icon and Image support using a lazy loading resource sub-framework. 77d5ca3b01_
- Add a traitsui support via the TraitsItem widget (care of Steven Silvester). 9cb9126da1_
- Add matplotlib support via the MPLCanvas widget (care of Steven Silvester). eaa6294566_
- Updated Session api which is more intuitive and easier to use.
- Updated Object api which is more intuitive and easier to use.
- Object lifecycle reflected in a `state` attribute.
- Huge reduction in memory usage when creating large numbers of objects.
- Huge reduction in time to create large numbers of objects.
- New widget registry make it easier to register custom widgets. cc791a52d7_
- Better and faster code analysis via code tracers. 4eceb09f70_
- Fix a parser bug related to relative imports. 3e43e73e90_
- Various other tweaks, bugfixes, and api cleanup.
.. _77d5ca3b01: https://github.com/enthought/enaml/commit/77d5ca3b0135fa982663d4ce9cf801119617c611
.. _eaa6294566: https://github.com/enthought/enaml/commit/eaa62945663fa9c96aee822c9f31ef966c88fd62
.. _9cb9126da1: https://github.com/enthought/enaml/commit/9cb9126da1e590814ad6dbee9a732c9add185ed6
.. _cc791a52d7: https://github.com/enthought/enaml/commit/cc791a52d772b07c7482427b5b60dcff9d5436c1
.. _4eceb09f70: https://github.com/enthought/enaml/commit/4eceb09f707e7795182013b9f874abf0afbaab41
.. _3e43e73e90: https://github.com/enthought/enaml/commit/3e43e73e90bd392a63a1faa53f821672fdb8c44f
0.5.1 - 11/19/2012
------------------
- Fix a method naming bug in QSingleWidgetLayout. 7a4c9de7e6_
- Fix a test height computation bug in QFlowLayout. a962d2ae78_
- Invalidate the QFlowLayout on layout request. 1e91a54245_
- Dispatch child events immediately when possible. e869f7124f_
- Destroy child widgets after the children change event is emitted. c695ae35ee_
- Add a preliminary WebView widget. 27faa381dc_
.. _27faa381dc: https://github.com/enthought/enaml/commit/27faa381dc5dd6c5cc41a0826df35b71339d3e7e
.. _c695ae35ee: https://github.com/enthought/enaml/commit/c695ae35ee9fcf35964df88831de0d3b30883f78
.. _e869f7124f: https://github.com/enthought/enaml/commit/e869f7124f0e13bea7f35d5f5a91bc89dc1dcd4e
.. _1e91a54245: https://github.com/enthought/enaml/commit/1e91a542452662ebd3dfe9d5a854ec2277f4415d
.. _a962d2ae78: https://github.com/enthought/enaml/commit/a962d2ae78488398cbe50d4ad16bd1cd90a1060b
.. _7a4c9de7e6: https://github.com/enthought/enaml/commit/7a4c9de7e6342b65efd6e3e841be0adfad286d99
0.5.0 - 11/16/2012
------------------
- Merge the feature-async branch into mainline. f86dad8f6e_
- First release with release notes. 8dbed4b9cd_
.. _8dbed4b9cd: https://github.com/enthought/enaml/commit/8dbed4b9cd16d8c9f71ea63dfd92494176fdf753
.. _f86dad8f6e: https://github.com/enthought/enaml/commit/f86dad8f6e3fe0bf07a2cf59765aaa3b934fa233
| 46.145957 | 109 | 0.77462 |
bdd61d7dc114ca017d636ae44150c944535756b7 | 3,604 | rst | reStructuredText | docs/supported-services/cloudwatchevents.rst | yoshutch/handel | 00fc6a802c1ef889a4c2ad4d5045a6ce013b38c5 | [
"Apache-2.0"
] | null | null | null | docs/supported-services/cloudwatchevents.rst | yoshutch/handel | 00fc6a802c1ef889a4c2ad4d5045a6ce013b38c5 | [
"Apache-2.0"
] | null | null | null | docs/supported-services/cloudwatchevents.rst | yoshutch/handel | 00fc6a802c1ef889a4c2ad4d5045a6ce013b38c5 | [
"Apache-2.0"
] | null | null | null | .. _cloudwatchevents:
CloudWatch Events
=================
This document contains information about the CloudWatch Events service supported in Handel. This Handel service provisions a CloudWatch Events rule, which can then be integrated with services like Lambda to invoke them when events fire.
.. IMPORTANT::
This service only offers limited tagging support. Cloudwatch events will not be tagged, but the Cloudformation stack used to create them will be. See :ref:`tagging-unsupported-resources`.
Parameters
----------
.. list-table::
:header-rows: 1
* - Parameter
- Type
- Required
- Default
- Description
* - type
- string
- Yes
-
- This must always be *cloudwatchevent* for this service type.
* - description
- string
- No
- Handel-created rule.
- The event description.
* - schedule
- string
- No
-
- The cron or rate string specifying the schedule on which to fire the event. See the `Scheduled Events <http://docs.aws.amazon.com/AmazonCloudWatch/latest/events/ScheduledEvents.html>`_ document for information on the syntax of these schedule expressions.
* - event_pattern
- string
- No
-
- The list of event patterns on which to fire the event. In this field you just specify an `Event Pattern <http://docs.aws.amazon.com/AmazonCloudWatch/latest/events/CloudWatchEventsandEventPatterns.html>`_ in YAML syntax.
* - state
- string
- No
- enabled
- What state the rule should be in. Allowed values: 'enabled', 'disabled'
* - tags
- :ref:`tagging-resources`
- No
-
- Tags to be applied to the Cloudformation stack which provisions this resource.
Example Handel Files
--------------------
.. _cloudwatch-scheduled-lambda-example:
Scheduled Lambda
~~~~~~~~~~~~~~~~
This Handel file shows a CloudWatch Events service being configured, producing to a Lambda on a schedule:
.. code-block:: yaml
version: 1
name: my-scheduled-lambda
environments:
dev:
function:
type: lambda
path_to_code: .
handler: app.handler
runtime: nodejs6.10
schedule:
type: cloudwatchevent
schedule: rate(1 minute)
event_consumers:
- service_name: function
event_input: '{"some": "param"}'
EBS Events Lambda
~~~~~~~~~~~~~~~~~
This Handel file shows a CloudWatch Events service being configured, producing to a Lambda when an EBS volume is created:
.. code-block:: yaml
version: 1
name: my-event-lambda
environments:
dev:
function:
type: lambda
path_to_code: .
handler: app.handler
runtime: nodejs6.10
schedule:
type: cloudwatchevent
event_pattern:
source:
- aws.ec2
detail-type:
- EBS Volume Notification
detail:
event:
- createVolume
event_consumers:
- service_name: function
Depending on this service
-------------------------
The CloudWatch Events service cannot be referenced as a dependency for another Handel service. This service is intended to be used as a producer of events for other services.
Events produced by this service
-------------------------------
The CloudWatch Events service currently produces events for the following services types:
* Lambda
Events consumed by this service
-------------------------------
The CloudWatch Events service does not consume events from other Handel services.
| 28.603175 | 261 | 0.63485 |
1323a31c4b8f9f403805be40f5c1104e71d98816 | 36,983 | rst | reStructuredText | docs/source/tutorials_iscan.rst | MontrealCorpusTools/iscan-server | 1ba1fba87a9e2a1a3b29b6df1c485a45535ea071 | [
"MIT"
] | 5 | 2018-12-27T10:52:56.000Z | 2021-04-26T07:13:52.000Z | docs/source/tutorials_iscan.rst | MontrealCorpusTools/polyglot-server | 1ba1fba87a9e2a1a3b29b6df1c485a45535ea071 | [
"MIT"
] | 128 | 2018-06-18T17:20:25.000Z | 2018-10-11T21:32:44.000Z | docs/source/tutorials_iscan.rst | MontrealCorpusTools/ISCAN | 1ba1fba87a9e2a1a3b29b6df1c485a45535ea071 | [
"MIT"
] | null | null | null | .. _`Montreal Forced Aligner`: https://github.com/MontrealCorpusTools/Montreal-Forced-Aligner
.. _`CSV for speaker information`: http://spade.glasgow.ac.uk/wp-content/uploads/2018/07/speaker_info.csv
.. _`Lexicon CSV`: http://spade.glasgow.ac.uk/wp-content/uploads/2018/10/iscan_lexicon.csv
.. _`Enriching`: https://polyglot-server.readthedocs.io/en/latest/enrichment_iscan.html
.. _`Enrichment`: https://polyglot-server.readthedocs.io/en/latest/enrichment_iscan.html
.. _`Praat script`: https://raw.githubusercontent.com/MontrealCorpusTools/SPADE/master/Common/sibilant_jane_optimized.praat
.. _`FAVE`: https://github.com/JoFrhwld/FAVE/wiki/FAVE-align
.. _`ISCAN_Prototypes`: http://spade.glasgow.ac.uk/wp-content/uploads/2018/08/ICECAN_prototypes.csv
.. _tutorials_iscan:
***************
ISCAN Tutorials
***************
The ISCAN system is a system for going from a raw speech corpus to a data file (CSV) ready for further analysis (e.g. in R), which conceptually consists of a pipeline of four steps:
1. **Importing the corpus into ISCAN**
Result: a structured database of linguistic objects (words, phones, sound files).
2. **Enriching the database**
Result: Further linguistic objects (utterances, syllables), and information about objects (e.g. speech rate, word frequencies).
3. **Querying the database**
Result: A set of linguistic objects of interest (e.g. utterance-final word-initial syllables),
4. **Exporting the results**
Result: A CSV file containing information about the set of objects of interest
Preliminaries
=============
Access
------
Before you can begin the tutorial, you will need access to log in to
the ISCAN server via your web browser. To log in to the McGill ISCAN
server via your web browser visit
https://roquefort.linguistics.mcgill.ca, press the ‘Log in’ button on
the top right of the screen and enter the username and password
provided.
**NWAV 2018 Workshop**: the workshop organizers will give you a username
and password.
**After NWAV 2018 Workshop**: Please contact
savanna.willerton@mail.mcgill.ca to request access to one of the ISCAN
tutorial accounts.
.. To use ISCAN you need to get a username and password from whoever the administrator for the server is. For now, the only ISCAN server is at McGill, so the first step is to contact Vanna (On Slack in the #iscan-help channel or email to savanna.willerton@mail.mcgill.ca) to request access, who will provide you with a username and password.
Questions, Bugs, Suggestions
----------------------------
If at any point while using ISCAN you get stuck, have a question,
encounter a bug (like a button which doesn’t work), or you see some
way in which you believe the user interface could be improved to make
usage more clear/smooth/straightforward/etc, then please `file an issue <https://github.com/MontrealCorpusTools/iscan-server/issues/>`_
on the ISCAN GitHub repository.
There is also a Slack channel you can join if you have quick questions
or would like real-time help. Please contact
savanna.willerton@mail.mcgill.ca for access.
.. TODO: public-facing page on "Getting Help and Giving Feedback" (we
currently only have a project-internal page). please see ISCAN – Getting Help and Giving Feedback (link TODO).
Dataset
--------
These tutorials use a tutorial corpus, which is (as of Oct 15, 2018) a
small subset of `ICE-Canada
<https://dataverse.library.ualberta.ca/dataverse/VOICE>`_ containing
speech from all "S2A" files (two male Canadian English speakers).
These files can be downloaded from the ICE Canada site, but doing so
is not necessary for these tutorials!
Tutorial 1: Polysyllabic shortening
===================================
Motivation
----------
Polysyllabic shortening refers to the "same" rhythmic unit (syllable or vowel) becoming shorter as the size of the containing domain (word or prosodic domain) increases. Two classic examples:
* English: stick, sticky, stickiness (Lehiste, 1972)
* French: pâte, pâté, pâtisserie (Grammont, 1914)
Polysyllabic shortening is often – but not always – defined as being restricted to accented syllables. (As in the English, but not the French example.) Using ISCAN, we can check whether a simple version of polysyllabic shortening holds in the tutorial corpus, namely:
* Considering all utterance-final words, does the initial vowel duration decrease as word length increases?
Step 1: Import
--------------
This tutorial will use the tutorial corpus available for you,
available under the title 'iscan-tutorial-X' (where X is a number). The data for this corpus was parsed using the `Montreal Forced Aligner`_, with the result being one Praat TextGrid per sound file, aligned with word and phone boundaries. These files are stored on a remote server, and so do not require you to upload any audio or TextGrid files.
The first step of this analysis is to create a *Polyglot DB* object of the corpus which is suitable for analysis. This is performed in two steps:
+ *Importing* the dataset using ISCAN, using the phone, word, and speaker information contained in the corpus
+ *Enriching* the dataset to include additional information about (e.g., syllables, utterances), as well as properties about these objects (e.g., speech rate)
To import the corpus into ISCAN, select 'iscan-tutorial-x' corpus
(replacing "x" with the number you're using) from the dropdown menu under the 'Corpora' tab in the navigation bar. Next, click the 'Import' button. This will import the corpus into ISCAN and return a structured database of objects: words, phones, and sound files), that will be interacted with in the following steps.
Step 2: Enrichment
------------------
Now that the corpus has been imported as a database, it is now
necessary to *enrich* the database with information about linguistic
objects, such as word frequency, speech rate, vowel duration, and so
on. You can see the `Enrichment`_ page to learn more about what enrichments
are possible, but in this tutorial we will just use a subset.
First, select the 'iscan-tutorial-x' under the 'Corpora' menu, which presents all of the current information available for this specific corpus. To start enrichment, click the 'create, edit, and run enrichments' button. This page is referred to as the *Enrichment view*. At first, this page will contain an empty table - as enrichments are added, this table will be populated to include each of these enrichment objects. On the right hand side of the page are a list of new enrichments that can be created for this database.
Here, we will walk through each enrichment that is necessary for
examining vowel duration to address our question ("Considering all
utterance final...").
**Syllables**
Syllables are encoded in two steps. First, the set of syllabic segments in the phonological inventory have to be specified. To encode the syllabic segments:
1. Select 'Phone Subset' button under the 'Create New Enrichments' header
2. Select the 'Select Syllabics' preset option
3. Name the environment 'syllabics'
4. Select 'Save subset'
This will return you to the Enrichment view page. Here, press the 'Run' button listed under 'Actions'. Once syllabic segments have been encoded as such, you can encode the syllables themselves.
1. Under the ‘Annotation levels’ header, press the ‘Syllables’ button
2. Select *Max Onset* from the Algorithm dropdown menu
3. Select *syllabics* from the Phone Subset menu
4. Name the enrichment 'syllables'
5. Select 'Save enrichment'
Upon return to the Enrichment view, hit ‘Run’ on the new addition to the table.
**Speakers**
To enrich the database with speaker information:
1. Select the 'Properties from a CSV' option
2. Select 'Speaker CSV' from the 'Analysis' dropdown menu. The `CSV for speaker information`_ is available for download.
3. Upload the tutorial corpus 'speaker_info.csv' file from your local machine.
4. Select 'Save Enrichment' and then 'Run' from the Enrichment view.
**Lexicon**
As with the speaker information, lexical information can be uploaded
in an analogous way. Download the `Lexicon CSV`_, for the tutorial
corpus, select 'Lexicon CSV' from the dropdown menu, save the enrichment, and run it.
**Utterances**
For our purposes, we define an utterance as a stretch of speech
separated by pauses. So now we will specify a minimum duration of pause that separates utterances (150ms is typically a good default).
First, select 'pauses' from 'Annotation levels', and select '<SIL>' as the unit representing pauses. As before, select 'Save enrichment' and then 'run'.
With the positions of pauses encoded, we are now able to encode information about utterances:
1. Under the ‘Annotation levels’ header, select ‘utterances’.
2. Name the new addition ‘utterance’
3. Enter *150* in the box next to ‘Utterance gap(ms)’
4. Select ‘Save enrichment’, and then ‘Run’ in the Enrichment view.
**Speech rate**
To encode speech rate information, select 'Hierarchical property' from
the Enrichment view. This mode allows you to encode rates, counts or
positions, based on certain hierarchical properties (e.g., utterances,
words). (For example: number of syllables in a word; Here select the following attributes:
1. Enter "speech_rate" as the property name
2. From the Property type menu, select *rate*
3. From the Higher annotation menu, select *utterance*
4. From the Lower annotation menu, select *syllable*
And then, as with previous enrichments, select 'Save enrichment' and then run.
**Stress**
Finally, to encode the stress position within each word:
* Select 'Stress from word property' from the Enrichment view menu.
* From the 'wordproperty' dropdown box, select 'stress_pattern'.
* Select 'Save enrichment' and run the enrichment in the Enrichment view.
Step 3: Query
---------------------
Now that the database has been enriched with all of the properties
necessary for analysis, it is now necessary to construct a **query**. Queries enable us to search the database for particular set of linguistic objects of interest.
First, return to the Corpus Summary view by selecting 'iscan-tutorial-x' from the top navigation header. In this view, there is a series of property categories which you can navigate through to add filters to your search.
In this case, we want to make a query for:
* Word-initial stressed syllables
* only in words at the end of utterances (fixed prosodic position)
Here, find the selection titled 'Syllables' and select 'New Query'. To make sure we select the correctly positioned syllables, apply the following filters:
Under **syllable** properties:
* Left aligned with: *word*
* Under 'add filter', select 'stress' from the dropdown box, and enter '1' in the text box. This will only select syllables with primary stress in this position.
Under **word** properties:
* Right aligned with: *utterance*
.. warning::
Note that if right alignment with utterances is specified for syllables in this query, this will inadvertently
restrict the query to monosyllabic words, as aligning with a higher linguistic type (in this case,
utterances) implicitly aligns it to an intermediate linguistic type (in this case, words).
Provide a name for this query (e.g., 'syllable_duration') and select 'Save and run query'.
Step 4: Export
---------------------
This query has found all word-initial stressed syllables for words in utterance-final position. We now want to export information about these linguistic objects to a CSV file. We want it to contain everything we need to examine how vowel duration (in seconds) depends on word length. Here we may check all boxes which will be relevant to our later analysis to add these columns to our CSV file. The preview at the bottom of the page will be updated as we select new boxes:
1. Under the **SYLLABLE** label, select:
* label
* duration
2. Under the **WORD** label, select:
* label
* begin
* end
* num_syllables
* stress_pattern
3. Under the **UTTERANCES** label, select:
* speech_rate
4. Under the **SPEAKER** label, select:
* name
5. Under the **SOUND FILE** label, select:
* name
Once you have checked all relevant boxes, select 'Export to CSV'. Your results will be exported to a CSV file on your computer. The name will be the one you chose to save plus "export.csv". In our case, the resulting file will be called "syllable_duration export.csv".
Examining & analysing the data
------------------------------
Now that the CSV has been exported, it can be analyzed to
address whether polysyllabic shortening holds in the tutorial corpus.
This part does not involve ISCAN, so it's not necessary to actually
carry out the steps below unless you want to (and have R installed and
are familiar with using it).
In **R**, load the data as follows:
.. code-block:: R
library(tidyverse)
dur <- read.csv('syllable_duration export.csv')
You may need to first install the `tidyverse` library using ``install.packages('tidyverse')``. If you are unable to install tidyverse, you may also use ``library(ggplot2)`` instead (note: if you do this, please use ``subset()`` instead of ``filter()`` for the remaining steps).
First, by checking how many word (types) there are for each number of syllables in the CSV, we can see that only 1 word has 4 syllables:
.. code-block:: R
group_by(dur, word_num_syllables) %>% summarise(n_distinct(word_label))
# word_num_syllables `n_distinct(word_label)`
# <int> <int>
# 1 1 109
# 2 2 34
# 3 3 7
# 4 4 1
We remove the word with 4 syllables, since we can't generalize based on one word type:
.. code-block:: R
dur <- filter(dur, word_num_syllables < 4)
Similarly, it is worth checking the distribution of syllable durations to see if there are any extreme values:
.. code-block:: R
ggplot(dur, aes(x = syllable_duration)) +
geom_histogram() +
xlab("Syllable duration")
.. image:: images/syll_hist_2.png
:width: 400
As we can see here, there is one observation which appears to be some kind of outlier, which perhaps are the result of pragmatic lengthening or alignment error. To exclude this from analysis:
.. code-block:: R
dur <- filter(dur, syllable_duration < 0.6)
Plot of the duration of the initial stressed syllable as a function of word duration (in syllables):
.. code-block:: R
ggplot(dur, aes(x = factor(word_num_syllables), y = syllable_duration)) +
geom_boxplot() +
xlab("Number of syllables") + ylab("Syllable duration") +
scale_y_sqrt()
.. image:: images/syll_dur_3.png
:width: 400
Here it's possible to see that there is a consistent shortening effect based on the number of syllables in the word, where the more syllables in a word the shorter the initial stressed syllable becomes.
Tutorial 2: Vowel formants
==========================
Vowel quality is well known to vary according to a range of social and linguistic factors (Labov, 2001). The precursor to any sociolinguistic and/or phonetic analysis of acoustic vowel quality is the successful identification, measurement, extraction, and visualization of the particular vowel variables for the speakers under consideration. It is often useful to consider vowels in terms of their overall patterning together in the acoustic vowel space.
In this tutorial, we will use ISCAN to measure the first and second
formants for the two speakers in the tutorial corpus, for the following vowels (keywords after Wells, 1982): FLEECE, KIT, FACE, DRESS, TRAP/BATH, PRICE, MOUTH, STRUT, NURSE, LOT/PALM, CLOTH/THOUGHT, CHOICE, GOAT, FOOT, GOOSE. We will only consider vowels whose duration is longer than 50ms, to avoid including reduced tokens. This tutorial assumes you have completed the *import* and *enrichment* sections from the previous tutorial, and so will only include the information specific to analysing formants.
Step 1: Enrichment
------------------
**Stressed vowels**
First, the set of stress vowels in the phonological inventory have to be specified. To encode these:
1. Select 'Phone Subset' button under the 'Create New Enrichments' header
2. Select the 'Select Stressed Vowels' preset option
3. Name the environment 'stressed_vowels'
4. Select 'Save subset'
This will return you to the Enrichment view page. Here, press the 'Run' button listed under 'Actions'.
**Acoustics**
Now we will compute vowel formants for all stressed syllables using an algorithm similar to `FAVE`_.
For this last section, you will need a vowel prototype file. For the
purposes of this tutorial, the file for the tutorial corpus is
provided here:
.. This one is also normally accessed after you've checked out the
tutorial corpus from the master SPADE Git repositories held on the McGill Roquefort server. Again, for the purposes of the tutorial, it is provided below.
`ISCAN_Prototypes`_
Please save the file to your computer.
From the Enrichment View, under the 'Acoustics' header, select 'Formant Points'. As usual, this will bring you to a new page. From the **Phone class** menu, select *stressed_vowels*. Using the 'Choose Vowel Prototypes CSV' button, upload the ICECAN_prototypes.csv file you saved. For **Number of iterations**, type 3 and for **Min Duration (ms)** type 50ms.
Finally, hit the 'Save enrichment' button. Then click 'Run' from the Enrichment View.
Step 2: Query
-------------
The next step is to search the dataset to find a set of linguistic objects of interest. In our case, we're looking for all stressed vowels, and we will get formants for each of these. Let's see how to do this using the **Query view**.
First, return to the 'iscan-tutorial-x' Corpus Summary view, then navigate to the 'Phones' section and select **New Query**. This will take you to a new page, called the Query view, where we can put together and execute searches. In this view, there is a series of property categories which you can navigate through to add filters to your search. Under 'Phone Properties', there is a dropdown menu with search options labelled 'Subset'. Select 'stressed_vowels'. You may select 'Add filter' if you would like to see more options to narrow down your search.
The selected filter settings will be saved for further use. It will
automatically be saved as 'New phone query', but let's change that to
something more memorable, say 'Tutorial corpus Formants'. When you are done, click the 'Save and run query' button. The search may take a while, especially for large datasets, but should not take more than a couple of minutes for this small subset of the ICE-Can corpus we're using for the tutorials.
Step 3: Export
--------------
Now that we have made our query and extracted the set of objects of interest, we'll want to export this to a CSV file for later use and further analysis (i.e. in R, MatLab, etc.)
Once you hit 'Save query', your search results will appear below the search window. Since we selected to find all stressed vowels only, a long list of phone tokens (every time a stressed vowel occurs in the dataset) should now be visible. This list of objects may not be useful to our research without some further information, so let's select what information will be visible in the resulting CSV file using the window next to the search view.
Here we may check all boxes which will be relevant to our later analysis to add these columns to our CSV file. The preview at the bottom of the page will be updated as we select new boxes:
Under the **Phone** header, select:
* label
* begin
* end
* F1
* F2
* F3
* B1 (The bandwidth of Formant 1)
* B2 (The bandwidth of Formant 2)
* B3 (The bandwidth of Formant 3)
* num_formants
Under the **Syllable** header, select:
* stress
* position_in_word
Under the **Word** header, select:
* label
* stress_pattern
Under the **Utterance** header, select:
* speech_rate
Under the **Speaker** header, select:
* name
Under the **Sound File** header, select:
* name
Once you have checked all relevant boxes, select 'Export to CSV'. Your results will be exported to a CSV file on your computer. The name will be the one you chose to save plus "export.csv". In our case, the resulting file will be called "Tutorial Formants export.csv".
Step 4. Examining & analysing the data
--------------------------------------
With the tutorial complete, we should now have a CSV file saved on our
personal machine containing information about the set of objects we
queried for and all other relevant information.
We now examine this data. This part doesn't use ISCAN, so it's not necessary to actually
carry out the steps below unless you want to.
In R, load the data as follows:
.. code-block:: R
library(tidyverse)
v <- read.csv("Tutorial Formants export.csv")
Rename the variable containing the vowel labels to ‘Vowel’, and reorder the vowels so that they pattern according to usual representation in acoustic/auditory vowel space:
.. code-block:: R
v$Vowel <- v$phone_label
v$Vowel = factor(v$Vowel, levels = c('IY1', 'IH1', 'EY1', 'EH1', 'AE1', 'AY1','AW1', 'AH1', 'ER1', 'AA1', 'AO1', 'OY1', 'OW1', 'UH1', 'UW1'))
Plot the vowels for the two speakers in this sound file:
.. code-block:: R
ggplot(v, aes(x = phone_F2, y = phone_F1, color=Vowel)) +
geom_point() +
facet_wrap(~speaker_name) +
scale_colour_hue(labels = c("FLEECE", "KIT", "FACE", "DRESS", "TRAP/BATH", "PRICE", "MOUTH", "STRUT", "NURSE", "LOT/PALM", "CLOTH/THOUGHT", "CHOICE", "GOAT", "FOOT", "GOOSE")) +
scale_y_reverse() +
scale_x_reverse() +
xlab("F2(Hz)") +
ylab("F1(Hz)")
.. image:: images/vowels.png
:width: 800
Tutorial 3: Sibilants
=====================
Sibilants, and in particular, /s/, have been observed to show interesting sociolinguistic variation according to a range of intersecting factors, including gendered, class, and ethnic identities (Stuart-Smith, 2007; Levon, Maegaard and Pharao, 2017). Sibilants - /s ʃ z ʒ/ - also show systematic variation according to place of articulation (Johnson, 2003). Alveolar fricatives /s z/ as in send, zen, are formed as a jet of air is forced through a narrow constriction between the tongue tip/blade held close to the alveolar ridge, and the air strikes the upper teeth as it escapes, resulting in high pitched friction. The post-alveolar fricatives /ʃ ʒ/, as in 'sheet', 'Asia', have a more retracted constriction, the cavity in front of the constriction is a bit longer/bigger, and the pitch is correspondingly lower. In many varieties of English, the post-alveolar fricatives also have some lip-rounding, reducing the pitch further.
Acoustically, sibilants show a spectral ‘mountain’ profile, with peaks and troughs reflecting the resonances of the cavities formed by the articulators (Jesus and Shadle, 2002). The frequency of the main spectral peak, and/or main area of acoustic energy (Centre of Gravity), corresponds quite well to shifts in place of articulation, including quite fine-grained differences, such as those which are interesting for sociolinguistic analysis: alveolars show higher frequencies, more retracted post-alveolars show lower frequencies.
As with the previous tutorials, we will use ISCAN to select all
sibilants from the imported sound file for the two speakers in the
tutorial corpus, and take a set of acoustic spectral measures including spectral peak, which we will then export as a CSV, for inspection.
Step 1: Enrichment
------------------
It is not necessary to re-enrich the corpus with the elements from the previous tutorial, and so here will only include the enrichments necessary to analyse sibilants.
**Sibilants**
Start by looking at the options under 'Create New Enrichments', press the 'Phone Subset' button under the 'Subsets' header. Here we select and name subsets of phones. If we wish to search for sibilants, we have two options for this corpus:
* For our subset of ICE-Can we have the option to press the pre-set button 'Select sibilants'.
* For some datasets the 'Select sibilants' button will not be available. In this case you may manually select a subset of phones of interest.
Then choose a name for the subset (in this case 'sibilants' will be filled in automatically) and click 'Save subset'. This will return you to the Enrichment view where you will see the new enrichment in your table. In this view, press 'Run' under 'Actions'.
**Acoustics**
For this section, you will need a special praat script saved in the MontrealCorpusTools/SPADE GitHub repository which takes a few spectral measures (including peak and spectral slope) for a given segment of speech. With this script, ISCAN will take these measures for each sibilant in the corpus. A link is provided below, please save the ``sibilant_jane_optimized.praat`` file to your computer: `Praat script`_
From the Enrichment View, press the 'Custom Praat Script' button under the 'Acoustics' header. As usual, this will bring you to a new page. First, upload the saved file 'sibilant_jane_optimized.praat' from your computer using 'Choose Praat Script' button. Under the **Phone class** dropdown menu, select *sibilant*.
Finally, hit the 'Save enrichment' button, and 'Run' from the Enrichment View.
**Hierarchical Properties**
Next, from the **Enrichment View** press the 'Hierarchical property' button under 'Annotation properties' header. This will bring you to a page with four drop down menus (Higher linguistic type, Lower linguistic type, Subset of lower linguistic type, and Property type) where we can encode speech rates, number of syllables in a word, and phone position.
While adding each enrichment below, remember to choose an appropriate name for the enrichment, hit the 'save enrichment' button, and then click 'Run' in the Enrichment View.
*Syllable Count 1 (Number of Syllables in a Word)*
1. Enter "num_syllables" as the property name
2. From the Property type menu, select *count*
3. From the Higher annotation menu, select *word*
4. From the Lower annotation menu, select *syllable*
*Syllable Count 2 (Number of Syllables in an Utterance)*
1. Enter "num_syllables" as the property name
2. From the Property type menu, select *count*
3. From the Higher annotation menu, select *utterance*
4. From the Lower annotation menu, select *syllable*
*Phone Count (Number of Phones per Word)*
1. Enter "num_phones" as the property name
2. From the Property type menu, select *count*
3. From the Higher annotation menu, select *word*
4. From the Lower annotation menu, select *phone*
*Word Count (Number of Words in an Utterance)*
1. Enter "num_words" as the property name
2. From the Property type menu, select *count*
3. From the Higher annotation menu, select *utterance*
4. From the Lower annotation menu, select *word*
*Phone Position*
1. Enter "position_in_syllable" as the property name
2. From the Property type menu, select *position*
3. From the Higher annotation menu, select *syllable*
4. From the Lower annotation menu, select *phone*
Step 2: Query
-------------
The next step is to search the dataset to find a set of linguistic objects of interest. In our case, we're looking for all sibilants. Let's see how to do this using the **Query view**.
First, return to the 'iscan-tutorial-X' Corpus Summary view, then navigate to the 'Phones' section and select **New Query**. This will take you to a new page, called the Query view, where we can put together and execute searches. In this view, there is a series of property categories which you can navigate through to add filters to your search. Under 'Phone Properties', there is a dropdown menu labelled **'Subset'**. Select 'sibilants'. You may select 'Add filter' if you would like to see more options to narrow down your search.
.. image:: images/Screenshot-from-2018-10-04-10-12-52-300x151.png
:width: 400
The selected filter settings will be saved for further use. It will automatically be saved as 'New phone query', but let's change that to something more memorable, say 'SibilantsTutorial'. When you are done, click the 'Run query' button. The search may take a while, especially for large datasets.
Step 3: Export
--------------
Now that we have made our query and extracted the set of objects of interest, we'll want to export this to a CSV file for later use and further analysis (i.e. in R, MatLab, etc.)
Once you hit 'Run query', your search results will appear below the search window. Since we selected to find all sibilants only, a long list of phone tokens (every time a sibilant occurs in the dataset) should now be visible. This list of sibilants may not be useful to our research without some further information, so let's select what information will be visible in the resulting CSV file using the window next to the search view.
G
Here we may check all boxes which will be relevant to our later analysis to add these columns to our CSV file. The preview at the bottom of the page will be updated as we select new boxes:
.. image:: images/Screenshot-from-2018-10-04-11-41-32-300x111.png
:width: 400
Under the **Phone** header, select:
* label
* begin
* end
* cog
* peak
* slope
* spread
Under the **Syllable** header, select:
* stress
Under the **Word** header, select:
* label
Under the **Utterance** header, select:
* speech_rate
Under the **Speaker** header, select:
* name
Under the **Sound File** header, select:
* name
Once you have checked all relevant boxes, click the 'Export to CSV' button. Your results will be exported to a CSV file on your computer. The name will be the one you chose to save for the Query plus "export.csv". In our case, the resulting file will be called "SibilantsTutorial export.csv".
Step 4: Examining & analysing the data
--------------------------------------
With the tutorial complete, we should now have a CSV file saved on our
personal machine containing information about the set of objects we
queried for and all other relevant information.
We now examine this data. This part doesn't use ISCAN, so it's not necessary to actually
carry out the steps below unless you want to.
First, open the CSV in R:
.. code-block:: R
s <- read.csv("SibilantsTutorial export.csv")
Check that the sibilants have been exported correctly:
.. code-block:: R
levels(s$phone_label)
Change the column name to 'sibilant':
.. code-block:: R
s$sibilant <- s$phone_label
Check the counts for the different voiceless/voiced sibilants - /ʒ/ is rare!
.. code-block:: R
summary(s$sibilant)
# S SH Z ZH
# 2268 187 1296 3
Reorder the sibilants into a more intuitive order (alveolars then post-alveolars):
.. code-block:: R
s$sibilant <- factor(s$sibilant, levels = c('S', 'Z', 'SH', 'ZH'))
Finally, plot the sibilants for the two speakers:
.. code-block:: R
ggplot(s, aes(x = factor(sibilant), y = phone_peak)) +
geom_boxplot() +
xlab("Spectral Peak (Hz)") +
ylab("sibilant") +
scale_y_sqrt() +
facet_wrap(~speaker_name)
.. image:: images/sibilants.png
:width: 800
Tutorial 4: Custom scripts
==========================
Often in studies it is necessary to perform highly specialized analyses.
As ISCAN can't possibly provide every single analysis that anyone could ever want, there is a way to perform analyses outside of ISCAN, and then bring them in.
This is the purpose of the 'Custom Properties from a Query-generated CSV' enrichment.
Using it is relatively straightforward, although it requires some prelimanary steps to get the data in the right format before using.
It also requires access to the original sound files of a corpus if you wish to use these in your analysis.
In this tutorial we will be using an R script, but you can use any script or software that you so choose.
Step 1: Necessary Enrichments
-----------------------------
The only necessary enrichment to do in this tutorial is to encode a sibilant subset of phones.
To do this, start at the 'iscan-tutorial-X' corpus summary view, and click on the 'Create, run and edit enrichments' button in the centre column.
Then, click on 'Phone Subset'.
At the enrichment page, click on the select sibilants button, then name the subset 'sibilants' and save the subset.
Finally, at the main enrichment page, run the sibilant enrichment.
Step 2: Running a phone query
-----------------------------
Now that we have all the enrichments we need, we can go to the **Query View**.
Starting at the 'iscan-tutorial-X' corpus summary view, navigate to the phones section of the left-most column and click "new Phone Query".
From there, the you'll have the option to choose various different filters to select a subset of phones.
For this tutorial we're looking at sibilants, so all you need to do is select the sibilants subset from the first drop-down menu from the centre menu.
Feel free to also re-name the query to anything you'd like, for example 'sibilant ID query'.
From there, click on 'Run query' and wait for the query to finish.
Step 3: Exporting phone IDs
---------------------------
Once the query has finished, a new pane will appear to the right of the window.
This pane will contain a list of different properties of the phones found, and properties of the syllables, words, and utterances that a phone is in.
These are the columns that will be included in the CSV that you will download from ISCAN.
For the script, we will need a couple different columns.
Under the **Phone** header, select:
* label
* begin
* end
* id
Under the **Sound File** header, select:
* name
Once all these columns have been selected, click the "Generate CSV Export File" in the row of buttons in the centre of the screen, above the results of the query.
This may take a second or two to run, then once it's available, click on the "Save CSV export file" and save the file somewhere convenient on your computer.
An important thing to note for this section is that while you can rename columns for export, you should not rename the ID column if you intend on importing this CSV later.
By default, a phone ID column will be labeled "phone_id".
When importing, ISCAN looks for a column that ends with "_id" and then uses the first half of the name of that column to know what these IDs represent(in this case, phones).
You also should not have multiple ID columns in your import CSV, although if you do, ISCAN will use the first ID column only.
Step 4: Running the R script
----------------------------
The script and associated files can be downloaded `here <https://github.com/MontrealCorpusTools/ISCAN/blob/master/docs/source/r-scripts/spectral-R-demo.zip?raw=true>`_.
This script estimates spectral features in R (Reidy, 2015).
In order to get this script running on your computer, you will have to make a few minor edits once you have extracted the ZIP file.
Open up 'iscan-token-spectral-demo.R' in your text editor.
At the top of the file, there will be two file paths defined.
Change 'sound_file_directory' to the file path of where you have the sound files of the tutorial corpus.
Then, change 'corpus_directory' to be the file path of the CSV that you downloaded from ISCAN.
I have it as a relative path, but you can of course make it an absolute path.
.. code-block:: R
sound_file_directory <- "/home/michael/Documents/Work/test_corpus"
corpus_data <- read.csv("../sibilants_export.csv")
This script also assumes you have not renamed any of the columns that you exported.
If you did change any columns' name, you will have to look through the script and change the following lines to the names of the corresponding columns.
.. code-block:: R
sound_file <- paste(corpus_data[row, "sound_file_name"], '.wav', sep="")
begin <- corpus_data[row, "phone_begin"]
end <- corpus_data[row, "phone_end"]
Finally, you can run the script in R, and it will create a new CSV file, 'spectral_sibilants.csv' that we will import to ISCAN.
Step 4: Importing the CSV
-------------------------
Back in ISCAN, go to the enrichments page for your tutorial corpus.
Under 'Annotation properties', click on the 'Custom Properties from a Query-generated CSV' button.
From this page, click on the "browse" button and navigate to the 'spectral_sibilants.csv' generated in the last step.
Select it for upload, then click on "Upload CSV".
This may take a second or two, so be patient.
After this, a new list of properties will appear which come from the columns of the CSV.
Scroll down, and select all the features that start with 'spectral'.
Then, click 'save enrichment', and from the main enrichment page, run the enrichment labelled 'Enrich phone from "spectral_sibilants.csv"'.
Now you're done!
ISCAN will now have all of the values calculated by the R script associated with all the sibilants in the corpus.
You can test this out by going to the phone query you created earlier.
You should see all these new properties in the column selection pane, although you may need to click "Refresh Query" before the values appear.
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===============================
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.. include:: meta-microsoft.rst
Check with ``useauth`` if the authentication using the Microsoft identity platform is enabled and configured.
| 28.8 | 109 | 0.784722 |
477ff86210c31331ad28352f975cf214a63be5fa | 9,200 | rst | reStructuredText | twenty_newsgroup.rst | krispingal/topic_modeling | 5fa5fd2dd06804fba8b6ab5b333015bbc914f1a7 | [
"MIT"
] | null | null | null | twenty_newsgroup.rst | krispingal/topic_modeling | 5fa5fd2dd06804fba8b6ab5b333015bbc914f1a7 | [
"MIT"
] | null | null | null | twenty_newsgroup.rst | krispingal/topic_modeling | 5fa5fd2dd06804fba8b6ab5b333015bbc914f1a7 | [
"MIT"
] | null | null | null | 20 newsgroups
=============
The following are the 20 newsgroups:
1. alt.atheism
2. comp.graphics
3. comp.os.ms-windows.misc
4. comp.sys.ibm.pc.hardware
5. comp.sys.mac.hardware
6. comp.windows.x
7. misc.forsale
8. rec.autos
9. rec.motorcycles
10. rec.sport.baseball
11. rec.sport.hockey
12. sci.crypt
13. sci.electronics
14. sci.med
15. sci.space
16. soc.religion.christian
17. talk.politics.guns
18. talk.politics.mideast
19. talk.politics.misc
20. talk.religion.misc
The following is a sample document present in dataset: This was taken from topic sci.electronics.
Xref: cantaloupe.srv.cs.cmu.edu rec.music.marketplace:4394 misc.forsale:74726 misc.wanted:30876 comp.music:12525 sci.electronics:52720 rec.music.makers.synth:4315
Newsgroups: rec.music.marketplace,osu.for-sale,misc.forsale,misc.wanted,comp.music,sci.electronics,rec.music.makers.synth
Path: cantaloupe.srv.cs.cmu.edu!crabapple.srv.cs.cmu.edu!fs7.ece.cmu.edu!europa.eng.gtefsd.com!gatech!udel!wupost!usc!elroy.jpl.nasa.gov!ames!pioneer.arc.nasa.gov!glennd
From: glennd@pioneer.arc.nasa.gov (Glenn Deardorff)
Subject: Re: keyboard equipment wanted:
Message-ID: <1993Apr5.201502.12462@news.arc.nasa.gov>
Sender: glennd@pioneer.arc.nasa.gov (Glen Deardorff GDP)
Organization: NASA Ames Res. Ctr. Mtn Vw CA 94035
References: <9304041842.AA28793@photon.magnus.acs.ohio-state.edu>
Date: Mon, 5 Apr 1993 20:15:02 GMT
Lines: 10
> * Moog, Serge, Paia, or Buchla analogue synthesizer modules or components
> if you have any of the following items, or similar goods, please e-mail or call
Chris (Analog Modular Systems) in L.A. specializes in modular stuff, and I know as of
last week he has some Serge modules, and perhaps Moog as well.
Number> (213) 850-5216
I just got an Xpander from him - this guy knows how to pack 'em right.
I have benchmarked gensim LDA on this corpus, which can be viewed here: https://github.com/krispingal/topic_modeling/blob/master/20_newsgroup/lda_benchmark_20ng.ipynb .
I get the following top 20 words for 6 topics, as output while running **gensim LDA** on 20-newsgroups for 6 topics *with tf-idf*.
1. Topic id # 0 ['cunyvm', 'foxvog', 'vtt', 'huston', 'tko', 'dfo', 'waldrop', 'tesrt', 'tufts', 'announcing', 'fusi', 'nis', 'chuvashia', 'inguiry', 'eridan', 'daruwala', 'vrrend', 'ich', 'harvested', 'jade']
2. Topic id # 1 ['maine', 'sfu', 'callison', 'oehler', 'bcci', 'dta', 'mattias', 'bobc', 'rauser', 'camosun', 'krzysztof', 'captain', 'albany', 'maynard', 'cbda', 'apgea', 'oasys', 'cuesta', 'lockridge', 'mydisplay']
3. Topic id # 2 [\'_', 'would', 'card', 'people', 'x', 'one', 'government', 'c', 'get', 'like', 'know', 'please', 'article', 'thanks', 'use', 'think', 'anyone', 'drive', 'writes', 'also']
4. Topic id # 3 ['russotto', 'jpeg', 'gsh', 'slac', 'hennessy', 'jb', 'bigboote', 'victor', 'scodal', 'shearson', 'usl', 'wam', 'charlottesville', 'higgins', 'nswc', 'intercon', 'oo', 'srl', 'slacvm', 'ucf']
5. Topic id # 4 ['truelove', 'leftover', 'mpr', 'inescn', 'hess', 'porto', 'kwansik', 'turkey', 'tracy', 'pom', 'sandia', 'casserole', 'tlu', 'gic', 'ming', 'christmas', 'sylvain', 'chalmers', 'mgp', 'unh']
6. Topic id # 5 ['windows', 'graphics', 'scsi', 'ide', 'files', 'x', 'dos', 'controller', 'thanks', 'drive', 'batf', 'fbi', 'file', 'program', 'disk', 'images', 'bus', 'pc', 'format', 'ram']
and the following also from **gensim LDA**, but this time *without tf-idf* transformation.
1. Topic id # 0 ['people', 'would', 'one', 'government', 'writes', 'law', 'god', 'us', 'fbi', 'article', 'think', 'said', 'believe', 'right', 'even', 'many', 'may', 'children', 'say', 'also']
2. Topic id # 1 ['article', 'writes', 'graphics', 'apr', 'one', 'ca', 'news', 'would', 'c', 'cs', 'lines', 'modem', 'good', 'university', 'cd', 'think', 'like', 'new', 'know', 'washington']
3. Topic id # 2 [\'_', 'package', 'would', 'writes', 'article', 'apr', 'one', \'__', \'___', 'mode', 'digital', 'know', 'like', 'new', 'e', 'university', 'also', 'colors', 'could', 'get']
4. Topic id # 3 ['x', 'w', 'c', 'r', 'e', 'v', 'p', 'b', 'k', 'u', 'g', 'n', 'z', 'file', 'h', 'f', 'image', 'l', 'j', 'windows']
5. Topic id # 4 ['would', 'one', 'get', 'like', 'know', 'writes', 'use', 'article', 'think', 'time', 'want', 'good', 'well', 'also', 'much', 'dos', 'people', 'could', 'problem', 'two']
6. Topic id # 5 ['ax', 'q', 'f', 'max', 'g', 'p', 'u', 'mb', 'b', 'r', 'v', 'x', 'n', 'e', 'l', 'c', 'z', 'w', 'clipper', 'j']
I get the following top 20 words for 6 topics, as output while running **gensim LDA mallet wrapper** on 20-newsgroups for 6 topics *with tf-idf*.
1. Topic id # 0 ['good', 'r_z', 'uus', 'uuw', 'vrvrtv', 'alyzfo', 'ikh', 'ikai', 'ikl', 'mwbel', \'uu_', 'cvi', 'pdz', 'azzq', 'hhpl', 'sty', 'wkx', 'ystg', \'z_c_', 'uum']
2. Topic id # 1 ['tesrt', 'uuw', 'uum', 'xgyu', 'r_z', 'alyzfo', 'ikh', 'ikai', 'ikl', 'mwbel', \'uu_', 'cvi', 'pdz', 'azzq', 'hhpl', 'sty', 'wkx', 'ikj', \'z_c_', 'vrvrtv']
3. Topic id # 2 ['satan', 'test', 'bullshit', 'ikh', 'uuw', 'vrvrtv', 'alyzfo', 'ikai', 'ikl', 'mwbel', \'uu_', 'cvi', 'pdz', 'azzq', 'hhpl', 'sty', 'wkx', 'ikj', 'uus', \'z_c_']
4. Topic id # 3 ['test', 'exit', 'r_z', 'uus', 'uuw', 'vrvrtv', 'alyzfo', 'ikh', 'ikai', 'ikl', 'mwbel', \'uu_', 'cvi', 'pdz', 'azzq', 'hhpl', 'sty', 'wkx', \'z_c_', 'uum']
5. Topic id # 4 ['unsubscribe', 'kidding', 'test', 'ignore', 'xgyu', 'ikh', 'alyzfo', 'ikai', 'ikl', 'mwbel', \'uu_', 'cvi', 'pdz', 'azzq', 'hhpl', 'sty', 'wkx', 'ikj', 'vrvrtv', 'uum']
6. Topic id # 5 ['ken', 'ikh', 'uus', 'uuw', 'vrvrtv', 'r_z', 'alyzfo', 'ikai', 'ikl', 'mwbel', \'uu_', 'cvi', 'pdz', 'azzq', 'hhpl', 'sty', 'wkx', 'ikj', \'z_c_', 'uum']
I get the following top 20 words for 6 topics, as output while running **gensim LDA mallet wrapper** on 20-newsgroups for 6 topics *without tf-idf*.
1. Topic id # 0 ['god', 'people', 'writes', 'time', 'good', 'article', 'point', 'jesus', 'question', 'make', 'fact', 'true', 'life', 'things', 'read', 'man', 'wrong', 'find', 'christian', 'world']
2. Topic id # 1 ['_', 'car', 'drive', 'power', 'buy', 'price', \'__', 'good', \'___', 'apple', 'speed', 'uiuc', 'hp', 'cars', 'problem', 'sale', 'monitor', 'hard', 'bought', 'mb']
3. Topic id # 2 ['ax', 'writes', 'article', 'apr', 'max', 'cs', 'ca', 'lines', 'news', 'university', 'organization', 'netcom', 'org', 'posting', \'_', 'cc', 'uk', 'bike', 'dod', 'pl']
4. Topic id # 3 ['year', 'game', 'space', 'time', 'good', 'team', 'years', 'back', 'play', 'games', 'nasa', 'ca', 'long', 'high', 'win', 'hockey', 'research', 'hit', 'players', 'season']
5. Topic id # 4 ['people', 'government', 'state', 'law', 'gun', 'israel', 'time', 'rights', 'president', 'public', 'children', 'fbi', 'states', 'war', 'fire', 'today', 'jews', 'mr', 'make', 'years']
6. Topic id # 5 ['system', 'windows', 'file', 'bit', 'mail', 'program', 'data', 'software', 'information', 'key', 'dos', 'computer', 'version', 'image', 'card', 'files', 'work', 'run', 'problem', 'graphics']
Conclusion
----------
As you can notice there is significant difference between the one from gensim as well as the one from mallet.
Running both library's LDA on same dataset I noticed:
Gensim seems to perform better with corpuses that underwent tf-idf transformation.
Mallet seems to perform very well with regular corpuses but performs badly with tf-idf transformed corpus.
I am inclining more towards Mallet's LDA with no tf-idf transformation, as it seems to give out more words which I know of to belong in same topic.
One way to qualitatively measure accuracy between thse two models, would be to hold out some documents, and later test these documents on our model
and see which one correctly predicts the topics the most.
Finally I decided to try out HDP on this dataset.
I get the following top 20 words as output while running HDP, the non prameterised version of LDA, on 20-newsgroups for 6 topics.
1. Topic id # 0 ['would', 'one', 'people', 'x', 'like', 'know', 'get', 'c', 'think', 'god', 'article', 'writes', 'use', \'_', 'apr', 'time', 'also', 'could', 'anyone', 'new']
2. Topic id # 1 ['x', 'would', 'windows', 'one', 'know', 'thanks', 'drive', 'c', 'get', 'like', 'anyone', 'people', 'use', 'article', 'please', 'writes', 'apr', 'card', 'cs', \'_']
3. Topic id # 2 ['god', 'morality', 'cobb', 'would', 'uiuc', 'lis', 'know', 'thanks', 'one', 'anyone', 'get', 'could', 'think', 'ico', 'writes', 'objective', 'system', 'x', 'like', 'someone']
4. Topic id # 3 ['religion', 'x', 'rb', \'_', 'qur', 'cookson', 'thanks', 'mitre', 'god', 'switch', 'islam', 'engr', 'posting', 'timessqr', 'know', 'latech', 'get', 'bike', 'c', 'low']
5. Topic id # 4 ['mabe', 'lars_jorgensen', 'sex', 'new', 'bmug', 'way', 'black', 'monash', 'bike', 'please', 'war', 'gregg', 'would', 'uk', 'audibly', 'writes', 'jaeger', 'clutch', 'book', 'opinions']
6. Topic id # 5 ['objective', 'horizon', 'atheism', 'black', 'would', 'event', 'writes', 'values', 'moral', 'mathew', 'mantis', 'frank', 'reality', 'could', 'thanks', 'look', 'minar', 'milwaukeeans', 'send', 'itsmail']
| 82.882883 | 218 | 0.607065 |
d766539eb71168d24029f8e8001cde23536ecfe8 | 157 | rst | reStructuredText | docs/utils.rst | toumorokoshi/uranium | 2d99deb7762c7a788966637157afcee171fcf6a8 | [
"MIT"
] | 21 | 2016-01-14T04:06:08.000Z | 2021-03-23T01:43:48.000Z | docs/utils.rst | yunstanford/uranium | 9d2ae39ce92d3b169790d1b243a765e5d7d5da77 | [
"MIT"
] | 45 | 2015-02-09T06:02:01.000Z | 2018-07-22T19:16:01.000Z | docs/utils.rst | yunstanford/uranium | 9d2ae39ce92d3b169790d1b243a765e5d7d5da77 | [
"MIT"
] | 10 | 2015-02-07T20:56:22.000Z | 2018-07-20T03:18:07.000Z | =========
Utilities
=========
To help make common scenarios easier, Uranium provides a set of utility methods.
.. autofunction:: uranium.get_remote_script
| 19.625 | 80 | 0.707006 |
6007730932d8d07c58a8cfeeb11d7153e5fe6d39 | 2,189 | rst | reStructuredText | docs/source/tutorial/en/pretrain/pub.rst | nnnyt/EduNLP | a40e7de1d73cb177bc36f5d75d933904c18040ef | [
"Apache-2.0"
] | null | null | null | docs/source/tutorial/en/pretrain/pub.rst | nnnyt/EduNLP | a40e7de1d73cb177bc36f5d75d933904c18040ef | [
"Apache-2.0"
] | null | null | null | docs/source/tutorial/en/pretrain/pub.rst | nnnyt/EduNLP | a40e7de1d73cb177bc36f5d75d933904c18040ef | [
"Apache-2.0"
] | null | null | null | The overview of our public model
------------------------------------
Version Description
#########################
First level version:
* Public version 1 (luna_pub): college entrance examination
* Public version 2 (luna_pub_large): college entrance examination + regional examination
Second level version:
* Minor subjects(Chinese,Math,English,History,Geography,Politics,Biology,Physics,Chemistry)
* Major subjects(science, arts and all subject)
Third level version【to be finished】:
* Don't use third-party initializers
* Use third-party initializers
Description of train data in models
#######################################
* Currently, the data used in w2v and d2v models are the subjects of senior high school.
* test data:`[OpenLUNA.json] <http://base.ustc.edu.cn/data/OpenLUNA/OpenLUNA.json>`_
At present, the following models are provided. More models of different subjects and question types are being trained. Please look forward to it.
"d2v_all_256" (all subject), "d2v_sci_256" (Science), "d2v_eng_256" (English)，"d2v_lit_256" (Arts)
Examples of model training
----------------------------
Get the dataset
####################
.. toctree::
:maxdepth: 1
:titlesonly:
prepare_dataset <../../../build/blitz/pretrain/prepare_dataset.ipynb>
An example of d2v in gensim model
####################################
.. toctree::
:maxdepth: 1
:titlesonly:
d2v_bow_tfidf <../../../build/blitz/pretrain/gensim/d2v_bow_tfidf.ipynb>
d2v_general <../../../build/blitz/pretrain/gensim/d2v_general.ipynb>
d2v_stem_tf <../../../build/blitz/pretrain/gensim/d2v_stem_tf.ipynb>
An example of w2v in gensim model
####################################
.. toctree::
:maxdepth: 1
:titlesonly:
w2v_stem_text <../../../build/blitz/pretrain/gensim/w2v_stem_text.ipynb>
w2v_stem_tf <../../../build/blitz/pretrain/gensim/w2v_stem_tf.ipynb>
An example of seg_token
############################
.. toctree::
:maxdepth: 1
:titlesonly:
d2v.ipynb <../../../build/blitz/pretrain/seg_token/d2v.ipynb>
d2v_d1 <../../../build/blitz/pretrain/seg_token/d2v_d1.ipynb>
d2v_d2 <../../../build/blitz/pretrain/seg_token/d2v_d2.ipynb>
| 29.186667 | 145 | 0.645043 |
4e2bbfe7ca732a96e3d0aa32024813400acadb77 | 869 | rst | reStructuredText | HISTORY.rst | ClimateImpactLab/climate_toolbox | 9cd3e952213ef938c5cdd6b0805ace06134fcedc | [
"MIT"
] | 2 | 2017-07-19T19:12:41.000Z | 2020-05-03T20:41:36.000Z | HISTORY.rst | ClimateImpactLab/climate_toolbox | 9cd3e952213ef938c5cdd6b0805ace06134fcedc | [
"MIT"
] | 19 | 2017-07-25T01:09:19.000Z | 2021-11-15T17:47:36.000Z | HISTORY.rst | ClimateImpactLab/climate_toolbox | 9cd3e952213ef938c5cdd6b0805ace06134fcedc | [
"MIT"
] | 2 | 2019-05-23T17:13:39.000Z | 2019-06-11T22:07:39.000Z |
History
=======
0.1.4 (current version)
-----------------------
* Support vectorized indexing for xarray >= 0.10 in :py:func:`climate_toolbox.climate_toolbox._reindex_spatial_data_to_regions` (:issue:`10`)
* Support iteratively increasing bounding box in :py:func:`~climate_toolbox.climate_toolbox._fill_holes_xr` (:issue:`11`).
* Support multiple interpolation methods (linear and cubic) in :py:func:`~climate_toolbox.climate_toolbox._fill_holes_xr` (:issue:`12`).
* Fix bug causing tests to pass no matter what
0.1.3 (2017-08-04)
------------------
* Support passing a dataset (not just a filepath) into ``load_baseline`` and ``load_bcsd`` (:issue:`4`)
0.1.2 (2017-07-25)
------------------
* merge in bug fixes
0.1.1 (2017-07-25)
-----------------------
* Various bug fixes (see :issue:`2`)
0.1.0 (2017-07-24)
------------------
* First release on PyPI.
| 26.333333 | 141 | 0.637514 |
80c0c8abea3a7da452339db367decb2d39b138cb | 190 | rst | reStructuredText | install-guide/source/next-steps.rst | andymcc/ceilometer | fa3b047eb17152b30829eadd9220f12ca9949b4f | [
"Apache-2.0"
] | null | null | null | install-guide/source/next-steps.rst | andymcc/ceilometer | fa3b047eb17152b30829eadd9220f12ca9949b4f | [
"Apache-2.0"
] | null | null | null | install-guide/source/next-steps.rst | andymcc/ceilometer | fa3b047eb17152b30829eadd9220f12ca9949b4f | [
"Apache-2.0"
] | null | null | null | .. _next-steps:
Next steps
~~~~~~~~~~
Your OpenStack environment now includes the ceilometer service.
To add additional services, see
docs.openstack.org/draft/install-guides/index.html .
| 19 | 63 | 0.752632 |
00300f32eab48141d4667f445cab78a4b2d3df01 | 2,609 | rst | reStructuredText | docs/source/release.rst | Amourspirit/python-kwargshelper | 4851ad69cf26f0656bc4264c70f956226bf5017e | [
"MIT"
] | null | null | null | docs/source/release.rst | Amourspirit/python-kwargshelper | 4851ad69cf26f0656bc4264c70f956226bf5017e | [
"MIT"
] | 4 | 2021-10-16T20:11:42.000Z | 2021-12-11T09:54:06.000Z | docs/source/release.rst | Amourspirit/python-kwargshelper | 4851ad69cf26f0656bc4264c70f956226bf5017e | [
"MIT"
] | null | null | null | Release Notes
=============
Version 2.7.1
-------------
Update ``opt_logger`` accept ``Logger`` or a ``LoggerAdapter``.
See :doc:`/source/general/dec_feature/opt_logger`.
Version 2.7.0
-------------
Added option ``opt_logger`` to many decorators.
See :doc:`/source/general/dec_feature/opt_logger`.
Versoin 2.6.0
-------------
Added Rules:
* RulePath
* RulePathExist
* RulePathNotExist
* RuleStrPathExist
* RuleStrPathNotExist
Version 2.5.0
-------------
Added option ``opt_args_filter`` to ``AcceptedTypes``, ``RuleCheckAll``, ``RuleCheckAny``, ``SubClass``, ``TypeCheck``
See :doc:`/source/general/dec_feature/opt_args_filter`.
Upgraded underling engine to use OrderedDict to ensure order of keys for python <= 3.6
Version 2.4.0
-------------
Added SubClass, SubClassKw decorators.
Added ``opt_all_args`` feature to ``AcceptedTypes`` decorator. See :doc:`/source/general/dec_feature/opt_all_args`
Update AcceptedTypes decorator. Now passing enum types into constructor no longer
require enum type to be passed in as iterable object.
Updated many decorator error message. Now they are a little more human readable.
Version 2.3.0
-------------
Added decorator ``ArgsMinMax``
Added Rules:
* RuleIterable
* RuleNotIterable
Added ``opt_return`` feature to many decorators. See :doc:`/source/general/dec_feature/opt_return`
Version 2.2.1
-------------
``ArgsLen`` decorator now allows zero length args.
.. code-block:: python
@ArgsLen(0, 2)
def foo(*args, **kwargs): pass
Version 2.2.0
-------------
Added Decorator ArgsLen.
Added Rules:
* RuleByteSigned
* RuleByteUnsigned
Version 2.1.4
-------------
Bug fix for ``AcceptedTypes`` Decorator when function has leading named args before positional args.
The following will now work.
.. code-block:: python
@AcceptedTypes(float, str, int, [Color], int, bool)
def myfunc(arg1, arg2, *args, opt=True): pass
Version 2.1.3
-------------
Update fix for python DeprecationWarning:
Using or importing the ABCs from 'collections'
instead of from 'collections.abc' is deprecated
Added Install documentation.
Added Development documentation.
Version 2.1.2
-------------
Fix for Decorator ``AcceptedTypes`` not working correctly with optional arguments.
Version 2.1.1
-------------
Fix for version 2.1.0 setup not building correctly.
Version 2.1.0
-------------
**New Features**
Added Decorators that provided a large range of options for validating function, class input and return values.
Also added decorators that provide other functionality such as singleton pattern. | 22.110169 | 119 | 0.691453 |
1f98d74ba53457c9a8fbfec40629add8cdd80a78 | 254 | rst | reStructuredText | docs/source/model.rst | amipy/numerous | 46eb3806ad904c3c0b3dccad7f8f3ddb5582cbd9 | [
"BSD-3-Clause"
] | 20 | 2019-12-11T18:19:39.000Z | 2022-01-30T15:37:58.000Z | docs/source/model.rst | amipy/numerous | 46eb3806ad904c3c0b3dccad7f8f3ddb5582cbd9 | [
"BSD-3-Clause"
] | 38 | 2020-04-11T22:25:58.000Z | 2022-03-29T12:24:15.000Z | docs/source/model.rst | amipy/numerous | 46eb3806ad904c3c0b3dccad7f8f3ddb5582cbd9 | [
"BSD-3-Clause"
] | 7 | 2019-12-21T12:12:09.000Z | 2021-12-02T14:12:09.000Z | .. role:: hidden
:class: hidden-section
numerous.engine.model
===================================
.. automodule:: numerous.engine.model
.. currentmodule:: numerous.engine.model
:hidden:`Model`
~~~~~~~~~~~~~~~~
.. autoclass:: Model
:members:
| 15.875 | 40 | 0.551181 |
e487fb402510d380a37145178f3dbeba3c405fd4 | 458 | rst | reStructuredText | docs/source/simulator_configs/delayed_impact.rst | yoshavit/whynot | e33e56bae377b65fe87feac5c6246ae38f4586e8 | [
"MIT"
] | 376 | 2020-03-20T20:09:16.000Z | 2022-03-29T09:53:33.000Z | docs/source/simulator_configs/delayed_impact.rst | mrtzh/whynot | 0668f0a0c1e80defec6e4678f85ed60f45226477 | [
"MIT"
] | 5 | 2020-04-20T10:19:34.000Z | 2021-11-03T09:36:28.000Z | docs/source/simulator_configs/delayed_impact.rst | mrtzh/whynot | 0668f0a0c1e80defec6e4678f85ed60f45226477 | [
"MIT"
] | 41 | 2020-03-20T23:14:38.000Z | 2022-03-09T06:02:01.000Z | .. _delayed_impact:
Delayed Impact
==============
State
-----
.. autoclass:: whynot.simulators.delayed_impact.State()
:members:
Config
------
.. autoclass:: whynot.simulators.delayed_impact.Config()
:members:
Interventions
-------------
.. autoclass:: whynot.simulators.delayed_impact.Intervention
:members: __init__
Experiments
-----------
.. automodule:: whynot.simulators.delayed_impact.experiments
:members: CreditBureauExperiment
| 16.962963 | 60 | 0.681223 |
6b3dc24c6353017bbaeef4e9419fda391b1248ba | 9,877 | rst | reStructuredText | docs/index.rst | fxdgear/nemesis | 78b360b1fbfa0c0f852135b8108799272f946ba7 | [
"Apache-2.0"
] | null | null | null | docs/index.rst | fxdgear/nemesis | 78b360b1fbfa0c0f852135b8108799272f946ba7 | [
"Apache-2.0"
] | null | null | null | docs/index.rst | fxdgear/nemesis | 78b360b1fbfa0c0f852135b8108799272f946ba7 | [
"Apache-2.0"
] | null | null | null | ***********************************
Welcome to Nemesis's documentation!
***********************************
Nemesis is a python library to manage Elasticsearch resources as code. Nemesis operates
a lot more like Pulumi than terraform. Each resource that nemesis supports is an actual
python object which can be used like any other python object.
Elasticsearch resources can be crafted as Python objects.
Elasticsearch resources can be fetched from the Elasticsearch cluster and diffed against local versions.
Deployments can happen if a remote resource doesn't exist.
Deployments can happen if a local_resource is registered with force=True, to force updating of the
resource even if it hasn't changed.
Installation
============
Install ``nemesis`` package with `pip
<https://pypi.org/project/nemesis>`_:
.. code-block:: console
$ python -m pip install nemesis
Create your first nemesis project
=================================
First create the directory you want to put your nemesis project into:
.. code-block:: console
$ mkdir my_first_project
$ cd my_first_project
$ nemesis new
The __nemesis__.py file
=======================
After you run the `nemesis new` command a newly created __nemesis__.py file will exist. This file has some example code in it to help you get started.
#. Instantiate the `Nemesis` object as the variable `n`.
#. Using the `nemesis.resources.elasticsearch.*` modules create your ES resources
#. `register` those resources with the `Nemesis` client. `n.register(my_resource_name)`
Pre/Post deploy hooks
---------------------
nemesis supports pre and post deploy hooks. This is useful in various situations
#. You are creating an ingest pipeline and you want to run some tests to ensure your pipeline works before the pipeline is deployed. You can write a function to call `resource.simulate` on your pipeline resource.
#. You have a transform you want to "reset". You can define a "predeploy" function to "stop" the current transform, delete the current dest index, and then recreate the dest index. then define a "postdeploy" function which will start the transform
#. Watchers can be "simulated" using the "execute" api. This unfortunatly only works on watchers that exist already, but you can deploy the watcher and then write a post-deploy test that will ensure your watcher works as expected.
#. Your imagination is the limit on things you might want to do before and/or after something has been deployed
CLI
===
While nemesis was initially designed to be a CLI tool, that does not mean you can't include
nemesis in your own python projects as a library.
Help
----
Running the `--help` flag will give you help on any command or subcommand.
.. code-block:: console
> nemesis --help
Usage: nemesis [OPTIONS] COMMAND1 [ARGS]... [COMMAND2 [ARGS]...]...
Nemesis CLI
Options:
--help Show this message and exit.
Commands:
launch Deploy resources to Elasticsearch
new Create a new nemesis deployment
preview Preview the resources to deployed
Preview
-------
Run `nemesis preview` to see what will be deployed to Elasticsearch.
This will render a diff to tell you what's going to be created or changed.
Nemesis supports deep diffing of resources with a succinct mode and verbose mode.
Example of succinct diff.
.. code-block:: console
> nemesis preview
Preview resources to be deployed
┏━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━┓
┃ Resource ┃ Name ┃ Action ┃ Diff ┃
┡━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━┩
│ IndexTemplate │ index_template_billing_aggregate │ create │ + ['index_patterns'] │
│ │ │ │ + ['template'] │
│ │ │ │ + ['version'] │
├──────────────────┼──────────────────────────────────┼───────────┼──────────────────────┤
│ IngestPipeline │ total_cost │ create │ + ['id'] │
│ │ │ │ + ['processors'] │
│ │ │ │ + ['description'] │
│ │ │ │ + ['version'] │
├──────────────────┼──────────────────────────────────┼───────────┼──────────────────────┤
│ Transform │ total_cost_2021_12 │ create │ + ['source'] │
│ │ │ │ + ['dest'] │
│ │ │ │ + ['id'] │
│ │ │ │ + ['pivot'] │
│ │ │ │ + ['description'] │
│ │ │ │ + 'frequency'] │
├──────────────────┼──────────────────────────────────┼───────────┼──────────────────────┤
│ LogstashPipeline │ test_logstash_pipeline │ update │ ~ ['last_modified'] │
├──────────────────┼──────────────────────────────────┼───────────┼──────────────────────┤
│ Role │ test-role │ unchanged │ │
├──────────────────┼──────────────────────────────────┼───────────┼──────────────────────┤
│ RoleMapping │ test_role_mapping │ unchanged │ │
├──────────────────┼──────────────────────────────────┼───────────┼──────────────────────┤
│ Watch │ test-watch │ unchanged │ │
└──────────────────┴──────────────────────────────────┴───────────┴──────────────────────┘
Resources:
Creating: 3
Updating: 1
Unchanged: 3
Example of a verbose diff.
.. code-block:: console
> nemesis preview -v
────────────────────────────────────────────────────────────────────────────────────────────────────────
Preview IndexTemplate(index_template_billing_aggregate)
┏━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Field ┃ Value ┃
┡━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ ['index_patterns'] │ + [ │
│ │ "billing_aggregate_*" │
│ │ ] │
│ ['template'] │ + { │
│ │ "settings": { │
│ │ "index": { │
│ │ "number_of_shards": "1", │
│ │ "number_of_replicas": "1" │
│ │ } │
│ │ }, │
│ │ "mappings": { │
│ │ "_source": { │
│ │ "enabled": true │
│ │ }, │
│ │ "properties": { │
│ │ "@timestamp": { │
│ │ "type": "date" │
│ │ }, │
│ │ "@version": { │
│ │ "type": "text" │
│ │ }, │
│ │ "cloud_provider": { │
│ │ "type": "keyword" │
│ │ }, │
│ │ "sum_total": { │
│ │ "type": "float" │
│ │ }, │
│ │ "team_name": { │
│ │ "type": "keyword" │
│ │ } │
│ │ } │
│ │ } │
│ │ } │
│ ['version'] │ + 3 │
└─────────────────────┴─────────────────────────────────┘
Launch
------
Run `nemesis launch` to deploy your changes.
This will actually ship your resources to Elasticsearch
Compatibility
=============
Compatibility is not currently guareneed. But work will be done to tie versions of nemesis with
the release cycle of Elasticsearch.
Adding new resources
====================
Creating new resources is not trivial at this point in time.
It's difficult because, to create the resource you first need to define the dataclass and all the attributes on that class.
Next you would need to define the Schema for that resource, then you would need to define all the CRUD method for that resource.
There's no automated way to do this. But would be nice to create a code generator to scan the Elasticsearch repo and pull out the various resources and their types so they can be created in Nemesis.
Pull requests for new resources added to nemesis would be greatly appriciated!
Contents
========
.. toctree::
:maxdepth: 3
nemesis
resources
exceptions
License
=======
Copyright 2022, Licensed under the Apache License, Version 2.0.
Indices and tables
==================
* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`
| 43.320175 | 247 | 0.414093 |
1c05c5b25b127238c297ec11c93d778322873e45 | 11,047 | rst | reStructuredText | docsrc/source/functions/fitsignal.rst | luisfabib/deerlab | fe3ba1737a982e4bd9a661b799683fd576c1ddd2 | [
"MIT"
] | 3 | 2019-10-30T18:55:12.000Z | 2019-11-28T13:49:40.000Z | docsrc/source/functions/fitsignal.rst | luisfabib/deerlab | fe3ba1737a982e4bd9a661b799683fd576c1ddd2 | [
"MIT"
] | 54 | 2020-02-07T15:23:13.000Z | 2020-04-20T15:55:27.000Z | docsrc/source/functions/fitsignal.rst | luisfabib/DeerAnalysis2 | fe3ba1737a982e4bd9a661b799683fd576c1ddd2 | [
"MIT"
] | 2 | 2020-02-26T02:34:18.000Z | 2020-03-10T16:33:58.000Z | .. highlight:: matlab
.. _fitsignal:
***********************
:mod:`fitsignal`
***********************
Fit a full model to a dipolar time-domain trace
------------------------
Syntax
=========================================
.. code-block:: matlab
fitsignal(V,t,r,dd,bg,ex,par0)
[Vfit,Pfit,Bfit,parfit,modfitci,parci,stats] = fitsignal(V,t,r,dd,bg,ex,par0,lb,ub)
__ = fitsignal(V,t,r,dd,bg,ex,par0)
__ = fitsignal(V,t,r,dd,bg,ex)
__ = fitsignal(V,t,r,dd,bg)
__ = fitsignal(V,t,r,dd)
__ = fitsignal(V,t,r)
__ = fitsignal({V1,V2,__},{t1,t2,__},r,dd,{bg1,bg2,__},{ex1,ex2,__},par0,lb,ub)
__ = fitsignal({V1,V2,__},{t1,t2,__},r,dd,{bg1,bg2,__},{ex1,ex2,__},par0)
__ = fitsignal({V1,V2,__},{t1,t2,__},r,dd,{bg1,bg2,__},{ex1,ex2,__})
__ = fitsignal({V1,V2,__},{t1,t2,__},r,dd,{bg1,bg2,__},ex)
__ = fitsignal({V1,V2,__},{t1,t2,__},r,dd)
__ = fitsignal({V1,V2,__},{t1,t2,__},r)
__ = fitsignal(___,'Property',Values,___)
Parameters
* ``V`` -- Time-domain signal to fit (*N*-element array)
* ``t`` -- Time axis, in microseconds (*N*-element array)
* ``r`` -- Distance axis, in nanometers (*M*-element array)
* ``dd`` -- Distance distribution model, can be...
* ``@dd_model`` function handle for parametric distribution model
* ``'P'`` to indicate a non-parametric distribution
* ``'none'`` to indicate no distribution, i.e. only background
* ``bg`` -- Background model, can be...
-- ``@bg_model`` function handle for parametric background model
-- ``'none'`` to indicate no background decay
* ``ex`` - Experiment model, can be...
-- ``@ex_model`` function handle for parametric experiment model
-- ``'none'`` to indicate simple dipolar oscillation (mod.depth = 1)\
* ``par0`` -- Starting parameters ``{par0_dd,par0_bg,par0_ex}`` (3-element cell array)
* ``lb`` -- Lower bounds for parameters ``{lb_dd,lb_bg,lb_ex}`` (3-element cell array)
* ``ub`` -- Upper bounds for parameters ``{lb_dd,lb_bg,lb_ex}`` (3-element cell array)
Returns
* ``Vfit`` -- Fitted time-domain signal (*N*-element array)
* ``Pfit`` -- Fitted distance-domain signal (*M*-element array)
* ``Bfit`` -- Fitted background decay (*N*-element array)
* ``parfit`` - Structure with fitted parameters (struct)
* ``.dd`` -- Fitted parameters for distance distribution model
* ``.bg`` -- Fitted parameters for background model
* ``.ex`` -- Fitted parameters for experiment model
* ``modfituq`` -- Structure with uncertainty quantification of the fitted...
* ``.Pfit`` -- ... distance distribution
* ``.Bfit`` -- ... background(s)
* ``.Vfit`` -- ... signal(s)
* ``paruq`` -- Structure with uncertainty quantification of the fitted...
* ``.dd`` -- ...distance distribution model parameters
* ``.bg`` -- ...background(s) model parameters
* ``.ex`` -- ...experiment(s) model parameters
* ``stats`` -- Goodness of fit statistical estimators (struct)
------------------------
Description
=========================================
.. code-block:: matlab
__ = fitsignal(V,t,r,dd,bg,ex)
__ = fitsignal(V,t,r,dd,bg)
__ = fitsignal(V,t,r,dd)
__ = fitsignal(V,t,r)
Fits a full time-domain model of the dipolar signal constructed from the distance distribution model ``dd``, background model ``bg`` and experiment model ``ex`` to the experimental data ``V``, defined on a time-axis ``t``. The distance distribution is fitted on the specified distance axis ``r``. If some models are not specified, the defaults are used: ``'P'`` for the ``dd`` model, ``@bg_hom3d`` for the ``bg`` model, and ``@ex_4pdeer`` for the experiment model.
The fitted dipolar signal ``Vfit``, fitted distribution ``Pfit`` and fitted background ``Bfit`` are returned as the first outputs and their corresponding uncertainty quantification structures as ``modfituq``. The corresponding model parameters are returned in the ``parfit`` structure and their corresponding uncertainty quantification structures (see :ref:`cireference`) in the ``parci`` structure. ``stats`` contains information on the quality of the fit.
.. code-block:: matlab
fitsignal(V,t,r,dd,bg,ex)
If the function is called without outputs, the function plots the fit results, prints a summary of the fit results, and lists all parameters and their confidence intervals.
Examples:
.. code-block:: matlab
fitsignal(V,t,r,@dd_gauss,@bg_hom3d,@ex_4pdeer) % Fit a 4pDEER signal with homogenous 3D background with Gaussian distribution
fitsignal(V,t,r,'P',@bg_hom3d,@ex_5pdeer) % Fit a 5pDEER signal with exponential background and Tikhonov regularization
fitsignal(V,t,r,'none',@bg_strexp,@ex_4pdeer) % Fit a 4pDEER stretched exponential background (no foreground)
fitsignal(V,t,r,@dd_rice,'none','none') % Fit a dipolar evolution function with Rician distribution
fitsignal(V,t,r,@dd_gauss2,'none',@ex_4pdeer) % Fit a 4pDEER form factor (no background) with bimodal Gaussian distribution
------------------------
__ = fitsignal(V,t,r,dd,bg,ex,par0)
The starting values of the parameter search can be specified via ``par0``. It must be 3-element cell arrays of the form ``{par0_dd,par0_bg,par0_ex}``, where the elements are arrays that give the initial values for the distance distribution parameters, background parameters, and experiment parameters, respectively. If not specified or passed empty, these values are automatically taken from the info structures of the parametric models.
------------------------
__ = fitsignal(V,t,r,dd,bg,ex,par0,lb,ub)
__ = fitsignal(V,t,r,dd,bg,ex,par0,[],ub)
__ = fitsignal(V,t,r,dd,bg,ex,par0,lb)
The lower/upper bounds for the parameter search range can be specified via ``lb`` and ``ub``. These inputs must be 3-element cell arrays of the form ``{ub_dd,ub_bg,ub_ex}`` and ``{lb_dd,lb_bg,lb_ex}``, where the elements are arrays that give the upper/lower bounds for the distance distribution parameters, background parameters, and experiment parameters, respectively. If not specified or passed empty, the boundaries are automatically taken from the info structures of the parametric models.
------------------------
.. code-block:: matlab
__ = fitsignal({V1,V2,__},{t1,t2,__},r,dd,{bg1,bg2,__},{ex1,ex2,__})
Multiple dipolar signals ``{V1,V2,__}`` can be globally fitted to a global distance distribution specified by the model ``dd``. For each signal passed, an experiment and background model can be specified for each signal. The corresponding time-axes ``{t1,t2,__}`` must be provided for all signals respectively.
.. code-block:: matlab
__ = fitsignal({V1,V2,__},{t1,t2,__},r,dd,{bg1,bg2,__},ex)
__ = fitsignal({V1,V2,__},{t1,t2,__},r,dd,bg,{ex1,ex2,__})
__ = fitsignal({V1,V2,__},{t1,t2,__},r,dd,bg,ex)
__ = fitsignal({V1,V2,__},{t1,t2,__},r)
If only one background model ``dd`` or experiment model ``ex`` are specified, that single model is applied for all input signals. If not models are specified, the default models mentioned above are used.
Examples:
.. code-block:: matlab
fitsignal({V1,V2},{t1,t2},r,@dd_gauss,@bg_hom3d,{@ex_4pdeer,@ex_4pdeer}) % Fit a Gaussian distribution to a 4pDEER and a 5pDEER signal globally
fitsignal({V1,V2},{t1,t2},r,'P',@bg_hom3d,@ex_5pdeer) % Fit a Tikhonov regularized distribution to two different 4pDEER signals
------------------------
Additional Settings
=========================================
Additional settings can be specified via name-value pairs. All property names are case insensitive and the name-value pairs can be passed in any order after the required input arguments have been passed.
.. code-block:: matlab
fitsignal(___,'Property1',Value1,'Property2',Value2,___)
- ``'RegType'`` - Regularization functional type
Specifies the type of regularization to be used to fit non-parametric distributions
* ``'tikh'`` -- Tikhonov regularization
* ``'tv'`` -- Total variation regularization
* ``'huber'`` -- Huber regularization
*Default:* ``tikh``
*Example:*
.. code-block:: matlab
fitsignal(___,'RegType','tv')
- ``'RegParam'`` - Regularization parameter selection
Specifies the method for the selection of the optimal regularization parameter (``'aic'``, ``'bic'``,...). See ``selregparam`` for more details. The regularization parameter can be manually fixed by passing its value.
*Default:* ``'aic'``
*Example:*
.. code-block:: matlab
fitsignal(___,'RegParam','bic')
fitsignal(___,'RegParam',0.2)
- ``'GlobalWeights'`` - Global analysis weights
Array of weighting coefficients for the individual signals in global fitting. If not specified, the global fit weights are automatically computed according to their contribution to ill-posedness. The same number of weights as number of input signals is required. Weight values do not need to be normalized.
*Default:* [*empty*]
*Example:*
.. code-block:: matlab
param = fitparamodel({S1,S2,S3},@dd_gauss,r,{K1,K2,K3},'GlobalWeights',[0.1 0.6 0.3]])
- ``'MultiStart'`` - Multi-start global optimization
Number of initial points to be generated for a global search. For each start point, a local minimum is searched, and the solution with the lowest objective function value is selected as the global optimum.
*Default:* ``1`` (No global optimization)
*Example:*
.. code-block:: matlab
param = fitsignal(___,'MultiStart',50)
- ``'Rescale'`` - Rescaling of fitted dipolar signal
This enables/disables the automatic optimization of the dipolar signal scale. If enabled (``true``) the experimental dipolar signal does not need to fulfill ``V(t=0) = 1``, if disabled (``false``) it needs to be fulfilled.
*Default:* ``true``
*Example:*
.. code-block:: matlab
V = correctscale(V,t);
fitsignal(___,'Rescale',false)
- ``'normP'`` - Renormalization of the distance distribution
This enables/disables the re-normalization of the fitted distance distribution such that ``sum(Pfit)*dr = 1``.
*Default:* ``true``
*Example:*
.. code-block:: matlab
fitsignal(___,'normP',false)
- ``'Display'`` - Plot and print results
This enables/disables plotting and printing of results.
*Default:* ``true`` if no outputs requested, otherwise ``false``
*Example:*
.. code-block:: matlab
fitsignal(___,'Display',true) | 43.152344 | 495 | 0.631484 |
468915a5b2072e7b50296999a4327d3452285e57 | 2,890 | rst | reStructuredText | docs/usecases/vppinaws.rst | amithbraj/vpp | edf1da94dc099c6e2ab1d455ce8652fada3cdb04 | [
"Apache-2.0"
] | 52 | 2016-09-20T15:08:46.000Z | 2020-12-22T23:03:25.000Z | docs/usecases/vppinaws.rst | amithbraj/vpp | edf1da94dc099c6e2ab1d455ce8652fada3cdb04 | [
"Apache-2.0"
] | 63 | 2018-06-11T09:48:35.000Z | 2021-01-05T09:11:03.000Z | docs/usecases/vppinaws.rst | amithbraj/vpp | edf1da94dc099c6e2ab1d455ce8652fada3cdb04 | [
"Apache-2.0"
] | 36 | 2016-07-21T11:20:33.000Z | 2022-01-16T15:55:45.000Z | .. _vppinaws:
.. toctree::
VPP in AWS
___________________
Warning: before starting this guide you should have a minimum knowledge on how `AWS works <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/concepts.html>`_!
First of all, you should log into your Virtual Machine inside AWS (we suggest to create an instance with Ubuntu 16.04 on a m5 type) and download some useful packages to make VPP installation as smooth as possible:
.. code-block:: console
$ sudo apt-get update
$ sudo apt-get upgrade
$ sudo apt-get install build-essential
$ sudo apt-get install python-pip
$ sudo apt-get install libnuma-dev
$ sudo apt-get install make
$ sudo apt install libelf-dev
Afterwards, types the following commands to install VPP:
.. code-block:: console
$ curl -s https://packagecloud.io/install/repositories/fdio/1807/script.deb.sh | sudo bash
In this case we downloaded VPP version 18.07 but actually you can use any VPP version available. Then, you can install VPP with all of its plugins:
.. code-block:: console
$ sudo apt-get update
$ sudo apt-get install vpp
$ sudo apt-get install vpp-plugins vpp-dbg vpp-dev vpp-api-java vpp-api-python vpp-api-lua
Now, you need to bind the NICs (Network Card Interface) to VPP. Firstly you have the retrieve the PCI addresses of the NICs you want to bind:
.. code-block:: console
$ sudo lshw -class network -businfo
The PCI addresses have a format similar to this: 0000:00:0X.0. Once you retrieve them, you should copy them inside the startup file of VPP:
.. code-block:: console
$ sudo nano /etc/vpp/startup.conf
Here, inside the dpdk block, copy the PCI addresses of the NIC you want to bind to VPP.
.. code-block:: console
dev 0000:00:0X.0
Now you should install DPDK package. This will allow to bind the NICs to VPP through a script available inside the DPDK package:
.. code-block:: console
$ wget https://fast.dpdk.org/rel/dpdk-18.08.tar.xz
$ tar -xvf dpdk-18.08.tar.xz
$ cd ~/dpdk-18.08/usertools/
and open the script:
.. code-block:: console
$ ./dpdk-setup.sh
When the script is running, you should be able to execute several options. For the moment, just install T=x86_64-native-linuxapp-gcc and then close the script. Now go inside:
.. code-block:: console
$ cd ~/dpdk-18.08/x86_64-native-linuxapp-gcc/
and type:
.. code-block:: console
$ sudo modprobe uio
$ sudo insmod kmod/igb_uio.ko
In this way, the PCIs addresses should appear inside the setup file of DPDK and therefore you can bind them:
.. code-block:: console
$ ./dpdk-setup.sh
Inside the script, bind the NICs using the option 24.
Finally restart VPP and the NICs should appear inside VPP CLI:
.. code-block:: console
$ sudo service vpp stop
$ sudo service vpp start
$ sudo vppctl show int
Notice that if you stop the VM, you need to bind again the NICs.
| 19.527027 | 214 | 0.72699 |
e71c10963b0291016866f078e62b189c8893b65e | 1,955 | rst | reStructuredText | content/articles/012-anonymous.rst | HSkogmo/qmcs.github.io | d9a845f833b305c776d61d2a72878bdad535745a | [
"CC-BY-4.0"
] | null | null | null | content/articles/012-anonymous.rst | HSkogmo/qmcs.github.io | d9a845f833b305c776d61d2a72878bdad535745a | [
"CC-BY-4.0"
] | null | null | null | content/articles/012-anonymous.rst | HSkogmo/qmcs.github.io | d9a845f833b305c776d61d2a72878bdad535745a | [
"CC-BY-4.0"
] | null | null | null | Anonymity
=========
:date: 2014-03-27 18:00
:tags: apps, anonymity
:category: Anonymity
:author: Anish Patel
As the world makes a shift online, from our daily habits increasing our reliance
on the internet here is an interesting topic that comes up, the aspect of online
anonymity. Anonymous apps such as Whisper and Secret have made us aware of the
issues we face in the modern world, reigniting the debate as to whether
anonynmity outweights the risk it comes with.
-- PELICAN_END_SUMMARY --
This is an important topic beyond tech, a question of how humans should treat one
another: Can we improve ourselves? Do we want to? Do we have a moral obligation
to do so? People in tech are outstanding at building, but at moderating? There
we don’t have much of a track record. Even the likes of Facebook have not been
able to control that and make favourable decisions most of the time.
People are people, and will exhibit bad behaviour almost anywhere so it's more
of an individual choice. We have soldiers in Afghanistan, who might not have
proper resources to get the emotional support they need during combat. This
platform act as a medium to express feelings. Anonymity facilitates the
feeling of "I'm not the only one out there...".
Like any other platform there are bound to be issues which we have no control
over, such systems will always get users. But to what end, and at what cost.
Sometimes it depends individually such that our personality defines who we
really are and what we end up doing.
We all have a story to share, and most of the times we learn from our mistakes
but I believe we can learn from other people's mistakes too.
The facts are laid out but I think it's all about making the right choice by
figuring out if the positive aspects of this ideas outweigh the negative.
For those who'd like to give it a try, you can visit `Secret <https://www.secret.ly>`_
or `Whisper <http://whisper.sh>`_ to get a better understanding.
| 45.465116 | 86 | 0.780563 |
0e2c4eb4536d9156afce603d72e5befb784389e9 | 155 | rst | reStructuredText | tests/data/metadata_extractors/f-rest-1-toml.rst | asmeurer/nikola | ea1c651bfed0fd6337f1d22cf8dd99899722912c | [
"MIT"
] | 1,901 | 2015-01-02T02:49:51.000Z | 2022-03-30T23:31:35.000Z | tests/data/metadata_extractors/f-rest-1-toml.rst | asmeurer/nikola | ea1c651bfed0fd6337f1d22cf8dd99899722912c | [
"MIT"
] | 1,755 | 2015-01-01T08:17:16.000Z | 2022-03-24T18:02:22.000Z | tests/data/metadata_extractors/f-rest-1-toml.rst | asmeurer/nikola | ea1c651bfed0fd6337f1d22cf8dd99899722912c | [
"MIT"
] | 421 | 2015-01-02T18:06:37.000Z | 2022-03-28T23:18:54.000Z | +++
title = "T: reST, 1, TOML"
slug = "s-rest-1-toml"
date = "2017-07-01 00:00:00 UTC"
tags = "meta,reST,onefile,TOML"
+++
Content line 1.
Content line 2.
| 17.222222 | 32 | 0.625806 |
481d46b88e81b002c6e698691655e19e169527e4 | 283 | rst | reStructuredText | posts/oculos-escuros-5-a-fundacao-de-uma-republica.rst | tczank/nikola-netlify-cms | 102886968af47c947b2b278cf3c00b72fce05374 | [
"MIT"
] | null | null | null | posts/oculos-escuros-5-a-fundacao-de-uma-republica.rst | tczank/nikola-netlify-cms | 102886968af47c947b2b278cf3c00b72fce05374 | [
"MIT"
] | null | null | null | posts/oculos-escuros-5-a-fundacao-de-uma-republica.rst | tczank/nikola-netlify-cms | 102886968af47c947b2b278cf3c00b72fce05374 | [
"MIT"
] | null | null | null | .. date: 2021-08-15 10:58:18 UTC
.. slug: oculos-escuros-5-a-fundacao-de-uma-republica
.. category: Óculos Escuros
.. title: Óculos Escuros 5: A Fundação de uma República
.. author: Óculos Escuros
.. youtube:: Nhpsrkorrvs
:width: 350
Quinto episódio do podcast Óculos Escuros.
| 25.727273 | 55 | 0.727915 |
bac3bdc7a209cb26bb8432a85b3072a9ce3515d7 | 1,522 | rst | reStructuredText | user_web/source/chapter9.rst | bobcraven/docs | 3bd008d16a2229787152a435692aed9192a4a890 | [
"MIT"
] | null | null | null | user_web/source/chapter9.rst | bobcraven/docs | 3bd008d16a2229787152a435692aed9192a4a890 | [
"MIT"
] | null | null | null | user_web/source/chapter9.rst | bobcraven/docs | 3bd008d16a2229787152a435692aed9192a4a890 | [
"MIT"
] | null | null | null | #####################################
Client Agent Software and Downloads
#####################################
The |prodname| Cloud access platform supports several different clients which allow users to leverage cloud storage in ways that make sense for
the client. Supported clients include:
* HTML 5 based Web Portal
- Chrome
- Firefox
- Internet Explorer
- Opera
- Safari
- older web browsers such as Internet Explorer 8
* Desktop Client for Windows and Mac
* Server Agent for Windows Servers
* Mobile Clients for iOS (iPad and iPhone)
* Mobile Clients for Android phones
* Mobile Clients for Windows Phone
.. warning::
Internet Explorer 8 is supported for Team User. However
for any administrative works (Cluster Admin, Tenant Admin,
Delegate Admin), Internet Explorer 8 is no longer supported
for any administrative works.
Download Client Agent Software
===============================
Most of the Mobile clients will need to be downloaded from the Apple Store, Google Play Store or Windows Phone Market Place.
The Windows and Mac client agent software can be downloaded directly from the |prodname| web portal itself. Click the small user icon (1) and then click the client download graphic (2) to get started.
.. figure:: _static/image_s9_1_1.png
:align: center
ACCESSING YOUR DOWNLOADS
.. figure:: _static/image_s9_1_2.png
:align: center
DOWNLOAD CLIENT AGENT SOFTWARE | 32.382979 | 201 | 0.667543 |
adf5a4b6d23339d58cd9514716e8fbb2c03d81ba | 3,555 | rst | reStructuredText | docs/specutils/fits_wcs.rst | bsipocz/specutils | 926920e1d70a0df1f7862363ca027eb723a61518 | [
"BSD-3-Clause"
] | null | null | null | docs/specutils/fits_wcs.rst | bsipocz/specutils | 926920e1d70a0df1f7862363ca027eb723a61518 | [
"BSD-3-Clause"
] | null | null | null | docs/specutils/fits_wcs.rst | bsipocz/specutils | 926920e1d70a0df1f7862363ca027eb723a61518 | [
"BSD-3-Clause"
] | null | null | null | Reading Spectra from a FITS file
=================================
.. currentmodule:: specutils.io.read_fits
FITS is one of the most common ways to store spectra. In most cases the flux values are stored as the pixel values
in a 1-, 2- or 3-D arrays. The mapping of axes indices to physically meaningful values (e.g. to wavelength) is encoded
in so FITS keywords (see :doc:`WCS <specwcs>`). This document describes how to extract this information and read it in to the various spectral
classes. A lot of information about the keyword header storage is taken from
`The IRAF/NOAO Spectral World Coordinate Systems <http://iraf.net/irafdocs/specwcs.php>`_. As the FITS keyword headers
have a complex way of storing information (often redundantly), we have created a FITS WCS parser (`~specutils.io.read_fits.FITSWCSSpectrum`)
that initializes with a FITS header and can extract/validate the information stored in the various keyword headers
making them available in a simple API. All of the FITS readers use this parser object.
.. note::
FITS keywords can encode two mappings from physical to logical to dispersion. A general approach to logical coordinate
systems is in development. Currently, the FITS readers ignore this information and might give wrong results.
Reading simple linear 1D WCS
----------------------------
One of the most common and simple ways that dispersion is encoded in FITS files is linear dispersion using four keywords::
CRVAL1 = 4402.538203477947
CRPIX1 = 1
CDELT1 = 1.3060348033905
CUNIT1 = 'Angstrom'
One can easily create a simple wcs file from this information::
>>> from specutils.wcs import specwcs
>>> from astropy.io import fits
>>> from astropy import units as u
>>> header = fits.getheader('myfile.fits')
>>> dispersion_start = dispersion_start - (header['CRPIX1'] - 1) * dispersion_delta
>>> linear_wcs = specwcs.Spectrum1DPolynomialWCS(degree=1, c0=dispersion_start,
c1=header['CDELT1'], unit=u.Unit(header['CUNIT1']))
>>> flux = fits.getdata('myfile.fits')
>>> myspec = Spectrum1D(flux=flux, wcs=linear_wcs)
As this is such a common format, there is a WCS reader available which generates a linear_wcs::
>>> from astropy.io import fits
>>> from specutils.io import read_fits
>>> fits_wcs_info = read_fits.FITSWCSSpectrum(fits.getheader('myfile.fits')) # parsing the FITS WCS information
>>> linear_wcs = read_fits_wcs_linear1d(fits_wcs_info)
Finally, there exists a reader that generates a Spectrum1D object from a fits file. The reader will iterate over the
available FITS 1D WCS readers until a matching one is found::
>>> from specutils.io import read_fits
>>> myspec = read_fits.read_fits_spectrum1d('myfile.fits'):
Currently only linear one-dimensional WCS is implemented, but the examples should give a guide to implement more complex
or WCS created from different keywords.
Reading FITS "multispec" format WCS
------------------------------------
Here is an example of reading a simple FITS multispec format. The output will not be a two-dimensional Spectrum, but
a list of `~specutils.Spectrum1D` objects::
>>> from specutils.io import read_fits
>>> read_fits.read_fits_multispec_to_list('mymultispec.fits')
Internally, the function again uses the `~FITSWCSSpectrum` parser object.
Reference/API
-------------
.. automodapi:: specutils.io.read_fits
:no-inheritance-diagram:
:skip: OrderedDict, Spectrum1D
| 45.576923 | 142 | 0.716456 |
bccddeae78a2245c40e131016c5bb36eba15a688 | 241 | rst | reStructuredText | docs/api-reference/storage/index.rst | ghsecuritylab/esp-idf-zh | 6d673f4fa2b9335dcb9df48179bbccf3fafdc290 | [
"Apache-2.0"
] | 104 | 2017-05-04T09:55:08.000Z | 2022-03-22T11:29:05.000Z | docs/api-reference/storage/index.rst | ghsecuritylab/esp-idf-zh | 6d673f4fa2b9335dcb9df48179bbccf3fafdc290 | [
"Apache-2.0"
] | 28 | 2017-08-01T09:19:23.000Z | 2017-12-26T13:41:14.000Z | docs/api-reference/storage/index.rst | ghsecuritylab/esp-idf-zh | 6d673f4fa2b9335dcb9df48179bbccf3fafdc290 | [
"Apache-2.0"
] | 44 | 2017-05-05T03:12:45.000Z | 2022-03-18T06:33:47.000Z | 存储器 API
***********
.. toctree::
:maxdepth: 1
SPI Flash 和分区 API <spi_flash>
SD/MMC <sdmmc>
非易失型存储器 <nvs_flash>
虚拟文件系统 <vfs>
FAT 文件系统 <fatfs>
损耗均衡 <wear-levelling>
关于本节 API 的示例代码请参考 ESP-IDF 示例中的 :example:`storage` 目录。
| 16.066667 | 53 | 0.622407 |
7fb8685221261f9cd283da807a24614195c124e4 | 3,448 | rst | reStructuredText | docs/admin-manual/java-support-installation.rst | sridish123/htcondor | 481d975fd8602242f6a052aab04e20b0b560db89 | [
"Apache-2.0"
] | 217 | 2015-01-08T04:49:42.000Z | 2022-03-27T10:11:58.000Z | docs/admin-manual/java-support-installation.rst | sridish123/htcondor | 481d975fd8602242f6a052aab04e20b0b560db89 | [
"Apache-2.0"
] | 185 | 2015-05-03T13:26:31.000Z | 2022-03-28T03:08:59.000Z | docs/admin-manual/java-support-installation.rst | sridish123/htcondor | 481d975fd8602242f6a052aab04e20b0b560db89 | [
"Apache-2.0"
] | 133 | 2015-02-11T09:17:45.000Z | 2022-03-31T07:28:54.000Z | Java Support Installation
=========================
:index:`Java<single: Java; installation>` :index:`Java`
Compiled Java programs may be executed (under HTCondor) on any execution
site with a :index:`Java Virtual Machine`\ :index:`JVM`
Java Virtual Machine (JVM). To do this, HTCondor must be informed of
some details of the JVM installation.
Begin by installing a Java distribution according to the vendor's
instructions. Your machine may have been delivered with a JVM already
installed - installed code is frequently found in ``/usr/bin/java``.
HTCondor's configuration includes the location of the installed JVM.
Edit the configuration file. Modify the ``JAVA`` :index:`JAVA`
entry to point to the JVM binary, typically ``/usr/bin/java``. Restart
the *condor_startd* daemon on that host. For example,
.. code-block:: console
$ condor_restart -startd bluejay
The *condor_startd* daemon takes a few moments to exercise the Java
capabilities of the *condor_starter*, query its properties, and then
advertise the machine to the pool as Java-capable. If the set up
succeeded, then *condor_status* will tell you the host is now
Java-capable by printing the Java vendor and the version number:
.. code-block:: console
$ condor_status -java bluejay
After a suitable amount of time, if this command does not give any
output, then the *condor_starter* is having difficulty executing the
JVM. The exact cause of the problem depends on the details of the JVM,
the local installation, and a variety of other factors. We can offer
only limited advice on these matters, but here is an approach to solving
the problem.
To reproduce the test that the *condor_starter* is attempting, try
running the Java *condor_starter* directly. To find where the
*condor_starter* is installed, run this command:
.. code-block:: console
$ condor_config_val STARTER
This command prints out the path to the *condor_starter*, perhaps
something like this:
.. code-block:: console
$ /usr/condor/sbin/condor_starter
Use this path to execute the *condor_starter* directly with the
*-classad* argument. This tells the starter to run its tests and display
its properties.
.. code-block:: console
$ /usr/condor/sbin/condor_starter -classad
This command will display a short list of cryptic properties, such as:
.. code-block:: condor-classad
IsDaemonCore = True
HasFileTransfer = True
HasMPI = True
CondorVersion = "$CondorVersion: 7.1.0 Mar 26 2008 BuildID: 80210 $"
If the Java configuration is correct, there will also be a short list of
Java properties, such as:
.. code-block:: condor-classad
JavaVendor = "Sun Microsystems Inc."
JavaVersion = "1.2.2"
HasJava = True
If the Java installation is incorrect, then any error messages from the
shell or Java will be printed on the error stream instead.
Many implementations of the JVM set a value of the Java maximum heap
size that is too small for particular applications. HTCondor uses this
value. The administrator can change this value through configuration by
setting a different value for ``JAVA_EXTRA_ARGUMENTS``
:index:`JAVA_EXTRA_ARGUMENTS`.
.. code-block:: condor-config
JAVA_EXTRA_ARGUMENTS = -Xmx1024m
Note that if a specific job sets the value in the submit description
file, using the submit command
**java_vm_args** :index:`java_vm_args<single: java_vm_args; submit commands>`, the
job's value takes precedence over a configured value.
| 34.138614 | 82 | 0.762761 |
0ec0dcab88ddbd70d5285be99bacbf7d07416d54 | 427 | rst | reStructuredText | docs/color.rst | Akuli/BananaGUI | d1bb2823770fb9d2e13da1d377d7a51e6a144679 | [
"MIT"
] | 4 | 2017-01-13T16:51:45.000Z | 2019-06-13T20:54:42.000Z | docs/color.rst | Akuli/BananaGUI | d1bb2823770fb9d2e13da1d377d7a51e6a144679 | [
"MIT"
] | 1 | 2019-06-13T21:04:42.000Z | 2019-06-20T13:27:56.000Z | docs/color.rst | Akuli/BananaGUI | d1bb2823770fb9d2e13da1d377d7a51e6a144679 | [
"MIT"
] | null | null | null | bananagui.color - color constants and handy functions
=====================================================
.. We can't rely on __all__ because it lists the constants.
.. automodule:: bananagui.color
.. autofunction:: bananagui.color.rgb2hex
.. autofunction:: bananagui.color.hex2rgb
.. autofunction:: bananagui.color.rgbstring2hex
.. autofunction:: bananagui.color.hex2rgbstring
.. autofunction:: bananagui.color.brightness
| 35.583333 | 59 | 0.688525 |
2afd82413873c1a915c3b555ac9caa63958004f2 | 343 | rst | reStructuredText | docs/source/index.rst | zhaocai/powerline | 8aae1145835b4b2a71f1ed71b81d490e2907bd39 | [
"MIT"
] | 19 | 2015-09-01T20:49:16.000Z | 2022-01-08T22:13:23.000Z | docs/source/index.rst | zhaocai/powerline | 8aae1145835b4b2a71f1ed71b81d490e2907bd39 | [
"MIT"
] | null | null | null | docs/source/index.rst | zhaocai/powerline | 8aae1145835b4b2a71f1ed71b81d490e2907bd39 | [
"MIT"
] | 6 | 2019-04-25T03:42:35.000Z | 2020-06-05T15:25:23.000Z | *********
Powerline
*********
.. toctree::
:maxdepth: 2
:glob:
introduction
overview
configuration
tipstricks
fontpatching
license-credits
Segments
========
.. toctree::
segments/common
segments/shell
segments/vim
Indices and tables
==================
* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`
| 11.433333 | 18 | 0.577259 |
f781cfdef5a6c363daef9a1632dce028a8c5d0e3 | 242 | rst | reStructuredText | news/add-xontrib-powerline2.rst | halloleo/xonsh | 3a34d9f2e347d5b4518d42a25a8b4080001ec748 | [
"BSD-2-Clause-FreeBSD"
] | 1 | 2021-01-21T21:36:42.000Z | 2021-01-21T21:36:42.000Z | news/add-xontrib-powerline2.rst | halloleo/xonsh | 3a34d9f2e347d5b4518d42a25a8b4080001ec748 | [
"BSD-2-Clause-FreeBSD"
] | null | null | null | news/add-xontrib-powerline2.rst | halloleo/xonsh | 3a34d9f2e347d5b4518d42a25a8b4080001ec748 | [
"BSD-2-Clause-FreeBSD"
] | null | null | null | **Added:**
* added `xontrib-powerline2 <https://github.com/vaaaaanquish/xontrib-powerline2>`_
**Changed:**
* <news item>
**Deprecated:**
* <news item>
**Removed:**
* <news item>
**Fixed:**
* <news item>
**Security:**
* <news item>
| 10.083333 | 82 | 0.61157 |
2b7fbdc784f17c4be41c3dc9ce5d3473fe8fb096 | 5,940 | rst | reStructuredText | doc/index.rst | ClericPy/trequests | 51dbf398da9383850bd0688fa3fb4edbe971597c | [
"MIT"
] | 27 | 2015-11-15T10:59:27.000Z | 2021-12-30T14:12:06.000Z | doc/index.rst | ClericPy/trequests | 51dbf398da9383850bd0688fa3fb4edbe971597c | [
"MIT"
] | 29 | 2015-11-15T12:47:22.000Z | 2020-03-23T09:28:56.000Z | doc/index.rst | ClericPy/trequests | 51dbf398da9383850bd0688fa3fb4edbe971597c | [
"MIT"
] | 5 | 2016-02-23T07:38:32.000Z | 2021-02-25T14:58:00.000Z | .. torequests documentation master file, created by
sphinx-quickstart on Sat Mar 17 02:18:11 2018.
You can adapt this file completely to your liking, but it should at least
contain the root `toctree` directive.
Welcome to torequests's documentation!
======================================
`https://github.com/ClericPy/torequests <https://github.com/ClericPy/torequests>`_
Indices and tables
==================
* :ref:`modindex`
* :ref:`genindex`
Quickstart
==================
To start:
----------
| ``pip install torequests -U``
**requirements:**
| requests
| futures # python2
| aiohttp >= 3.6.2 # python3
| uvloop # python3
**optional:**
| psutil
| pyperclip
Examples:
----------
**1. Async, threads - make functions asynchronous**
::
from torequests.main import Async, threads
import time
def use_submit(i):
time.sleep(i)
result = 'use_submit: %s' % i
print(result)
return result
@threads()
def use_decorator(i):
time.sleep(i)
result = 'use_decorator: %s' % i
print(result)
return result
new_use_submit = Async(use_submit)
tasks = [new_use_submit(i) for i in (2, 1, 0)
] + [use_decorator(i) for i in (2, 1, 0)]
print([type(i) for i in tasks])
results = [i.x for i in tasks]
print(results)
# use_submit: 0
# use_decorator: 0
# [<class 'torequests.main.NewFuture'>, <class 'torequests.main.NewFuture'>, <class 'torequests.main.NewFuture'>, <class 'torequests.main.NewFuture'>, <class 'torequests.main.NewFuture'>, <class 'torequests.main.NewFuture'>]
# use_submit: 1
# use_decorator: 1
# use_submit: 2
# use_decorator: 2
# ['use_submit: 2', 'use_submit: 1', 'use_submit: 0', 'use_decorator: 2', 'use_decorator: 1', 'use_decorator: 0']
**2. tPool - thread pool for async-requests**
::
from torequests.main import tPool
from torequests.logs import print_info
trequests = tPool()
test_url = 'http://p.3.cn'
ss = [
trequests.get(
test_url,
retry=2,
callback=lambda x: (len(x.content), print_info(len(x.content))))
for i in range(3)
]
# or [i.x for i in ss]
trequests.x
ss = [i.cx for i in ss]
print_info(ss)
# [2018-03-18 21:18:09]: 612
# [2018-03-18 21:18:09]: 612
# [2018-03-18 21:18:09]: 612
# [2018-03-18 21:18:09]: [(612, None), (612, None), (612, None)]
**3. Requests - aiohttp-wrapper**
::
# ====================== sync environment ======================
from torequests.dummy import Requests
from torequests.logs import print_info
req = Requests(frequencies={'p.3.cn': (2, 1)})
tasks = [
req.get(
'http://p.3.cn',
retry=1,
timeout=5,
callback=lambda x: (len(x.content), print_info(x.status_code)))
for i in range(4)
]
req.x
results = [i.cx for i in tasks]
print_info(results)
# [2020-02-11 15:30:54] temp_code.py(11): 200
# [2020-02-11 15:30:54] temp_code.py(11): 200
# [2020-02-11 15:30:55] temp_code.py(11): 200
# [2020-02-11 15:30:55] temp_code.py(11): 200
# [2020-02-11 15:30:55] temp_code.py(16): [(612, None), (612, None), (612, None), (612, None)]
# ====================== async with ======================
from torequests.dummy import Requests
from torequests.logs import print_info
import asyncio
async def main():
async with Requests(frequencies={'p.3.cn': (2, 1)}) as req:
tasks = [
req.get(
'http://p.3.cn',
retry=1,
timeout=5,
callback=lambda x: (len(x.content), print_info(x.status_code))
) for i in range(4)
]
await req.wait(tasks)
results = [task.cx for task in tasks]
print_info(results)
if __name__ == "__main__":
loop = asyncio.get_event_loop()
loop.run_until_complete(main())
loop.close()
# [2020-02-11 15:30:55] temp_code.py(36): 200
# [2020-02-11 15:30:55] temp_code.py(36): 200
# [2020-02-11 15:30:56] temp_code.py(36): 200
# [2020-02-11 15:30:56] temp_code.py(36): 200
# [2020-02-11 15:30:56] temp_code.py(41): [(612, None), (612, None), (612, None), (612, None)]
**4. utils: some useful crawler toolkits**
| **ClipboardWatcher**: watch your clipboard changing.
| **Counts**: counter while every time being called.
| **Null**: will return self when be called, and alway be False.
| **Regex**: Regex Mapper for string -> regex -> object.
| **Saver**: simple object persistent toolkit with pickle/json.
| **Timer**: timing tool.
| **UA**: some common User-Agents for crawler.
| **curlparse**: translate curl-string into dict of request.
| **md5**: str(obj) -> md5_string.
| **print_mem**: show the proc-mem-cost with psutil, use this only for lazinesssss.
| **ptime**: %Y-%m-%d %H:%M:%S -> timestamp.
| **ttime**: timestamp -> %Y-%m-%d %H:%M:%S
| **slice_by_size**: slice a sequence into chunks, return as a generation of chunks with size.
| **slice_into_pieces**: slice a sequence into n pieces, return a generation of n pieces.
| **timeago**: show the seconds as human-readable.
| **unique**: unique one sequence.
Read More
=================
* :ref:`modindex`
| 31.935484 | 232 | 0.525421 |
4d53aea5461dd1e3b7032ae5d94d5b0c99bfc436 | 173 | rst | reStructuredText | docs/_api/modules.rst | vhorvath/nglview | 7e31c40efe6cfc45e04d6374dc6a43fd62e68b90 | [
"MIT"
] | 161 | 2020-07-28T14:05:57.000Z | 2022-03-31T08:38:06.000Z | docs/_api/modules.rst | vhorvath/nglview | 7e31c40efe6cfc45e04d6374dc6a43fd62e68b90 | [
"MIT"
] | 123 | 2020-07-27T15:02:27.000Z | 2022-03-30T18:31:51.000Z | docs/_api/modules.rst | vhorvath/nglview | 7e31c40efe6cfc45e04d6374dc6a43fd62e68b90 | [
"MIT"
] | 42 | 2020-07-28T09:50:06.000Z | 2022-03-11T18:50:22.000Z | nglview
=======
.. toctree::
:maxdepth: 4
nglview
nglview.widget
nglview.adaptor
nglview.shape
nglview.widget_utils
nglview.player
nglview.scripts
| 12.357143 | 23 | 0.66474 |
ac9952b1096defbd6efc85e81cb382d28e2a7e0f | 1,963 | rst | reStructuredText | Client/Profile/EditProfile.rst | b4you/EmpAppDocs | 91a078e75bebfb0fe64ce255e613f8ecfdc3fe08 | [
"Apache-2.0"
] | null | null | null | Client/Profile/EditProfile.rst | b4you/EmpAppDocs | 91a078e75bebfb0fe64ce255e613f8ecfdc3fe08 | [
"Apache-2.0"
] | null | null | null | Client/Profile/EditProfile.rst | b4you/EmpAppDocs | 91a078e75bebfb0fe64ce255e613f8ecfdc3fe08 | [
"Apache-2.0"
] | 1 | 2018-01-31T08:48:19.000Z | 2018-01-31T08:48:19.000Z | .. _edit_profile:
====================
Edit Profile
====================
User can update their personal infomation and setting at this screen.
.. figure:: ../Resources/Images/EditProfile.jpg
:alt: Profile Screen
:scale: 50 %
#. Overview
#. Contact infomation
#. User setting
1. Overview
-----------------------------
.. figure:: ../Resources/Images/EditProfile_Explain.jpg
:alt: Profile Screen
:scale: 50 %
(1) Profile picture: user can change their profile picture by clicking on image.
The pop up appears then user can choose existing picture or take new one.
.. figure:: ./Resource/Images/EditProfile_SelectImage.jpg
:alt: Profile Screen
:scale: 25 %
(2) Firstname
(3) Lastname
(4) Position description
(5) Sharing status
(6) Phone infomation
(7) Email infomation
(8) User setting
2. Contact infomation
-----------------------------
User can add/remove and allow other can reach them via contact information they added.
.. figure:: ../Resources/Images/EditProfile_ContactInfo.jpg
:alt: Profile Screen
:scale: 50 %
(1) Toogle button: show/hide phone infomation in their profile page.
When user hides those information, call or email button will be disable in thier profile page.
.. figure:: ../Resources/Images/Profile_Other.jpg
:alt: Profile Screen
:scale: 50 %
(2) Phone list: user can remove phone by click on (x) button.
(3) Add new phone: when click on this button, input field will be showns allow user to add new phone.
(4) New phone input: allow user input new phone. They can confirm adding new phone by OK button, or discard it by (x) button.
3. User setting
-----------------------------
- Notification setting: user can switch on/off notification. When it's off, user won't receive any notification related to post.
But they still receive update notification or important notification.
- Languages: user can choose display language for app. English and German are supported for now.
| 29.742424 | 130 | 0.690779 |
255f36646b2322e75bbe450d7ddf60eabc77e0e2 | 1,022 | rst | reStructuredText | CHANGELOG.rst | fx-bricks/pfx-brick-py | dacd3c04fcbbecef7a6a5d9603ed8cf9a2eb3469 | [
"MIT"
] | 11 | 2018-04-26T22:53:44.000Z | 2022-02-14T13:44:27.000Z | CHANGELOG.rst | fx-bricks/pfx-brick-py | dacd3c04fcbbecef7a6a5d9603ed8cf9a2eb3469 | [
"MIT"
] | 3 | 2021-01-14T18:48:48.000Z | 2022-02-16T04:06:06.000Z | CHANGELOG.rst | fx-bricks/pfx-brick-py | dacd3c04fcbbecef7a6a5d9603ed8cf9a2eb3469 | [
"MIT"
] | 2 | 2018-05-20T11:30:53.000Z | 2022-02-15T06:42:37.000Z |
Change Log
==========
v.0.8.1
-------
* bug fixes
v.0.8.0
-------
* all new support added for v.3.38 of ICD
* support for v.1.50+ firmware which conforms to v.3.38 ICD
* added command line utility scripts which are installed into the python path
* revised documentation
v.0.7.1
-------
* revised documentation
* improved BLE notifcation callbacks
v.0.7.0
-------
* added Bluetooth LE connection access with same functionality as USB
* added convenience methods to PFxBrick class to execute actions directly
* added support for running scripts on PFx Brick
v.0.6.2
-------
* fixed error reporting for file system access methods
* fixed file directory refresh to ignore empty directory entries
v.0.6.1
-------
* changed the USB write function to ensure consistent cross-platform compatibility
v.0.6.0
-------
* finished implementing missing functionality
* finished documentation
* first public announced release
v.0.5.1
-------
* Added CHANGELOG.rst to project manifest
v.0.5.0
-------
* Initial release
| 17.62069 | 82 | 0.710372 |
c2cf061f6b78ce971050a9652e07d2bc030dcba3 | 2,038 | rst | reStructuredText | host_xrt/iops_test_xrt/README.rst | Ddnirvana/Vitis_Accel_Examples | b41830f3dfc2ad85020c0cf3bdb7d27d774b90fc | [
"Apache-2.0"
] | 270 | 2019-10-22T02:53:56.000Z | 2022-03-31T11:15:13.000Z | host_xrt/iops_test_xrt/README.rst | ioannis-krmp/Vitis_Accel_Examples | 0903aedd14326224d760f4461bd56e85987d3581 | [
"Apache-2.0"
] | 57 | 2020-01-03T04:52:12.000Z | 2022-03-17T13:34:01.000Z | host_xrt/iops_test_xrt/README.rst | ioannis-krmp/Vitis_Accel_Examples | 0903aedd14326224d760f4461bd56e85987d3581 | [
"Apache-2.0"
] | 142 | 2019-10-18T18:57:38.000Z | 2022-03-16T14:10:29.000Z | IOPS Test XRT (XRT Native API's)
================================
This is simple test design to measure Input/Output Operations per second. In this design, a simple kernel is enqueued many times and measuring overall IOPS using XRT native api's.
**KEY CONCEPTS:** Input/Output Operations per second
EXCLUDED PLATFORMS
------------------
Platforms containing following strings in their names are not supported for this example :
::
nodma
DESIGN FILES
------------
Application code is located in the src directory. Accelerator binary files will be compiled to the xclbin directory. The xclbin directory is required by the Makefile and its contents will be filled during compilation. A listing of all the files in this example is shown below
::
src/hello.cpp
src/host.cpp
COMMAND LINE ARGUMENTS
----------------------
Once the environment has been configured, the application can be executed by
::
./iops_test_xrt -x <hello XCLBIN>
DETAILS
-------
This is simple test design to measure Input/Output Operations per second using xrt native api's.
For measuring the IOPS we run kernel 1 Million times and capture the time it takes to complete -
Following is the real log reported while running the design on U250
platform:
::
Open the device0
Load the xclbin ./build_dir.hw.xilinx_u250_gen3x16_xdma_3_1_202020_1/hello.xclbin
Allocated commands, expect 10000, created 10000
Commands: 10 iops: 84033.6
Commands: 50 iops: 127226
Commands: 100 iops: 270270
Commands: 200 iops: 282486
Commands: 500 iops: 295159
Commands: 1000 iops: 299940
Commands: 1500 iops: 297442
Commands: 2000 iops: 304599
Commands: 3000 iops: 310013
Commands: 5000 iops: 314505
Commands: 10000 iops: 316937
Commands: 50000 iops: 335004
Commands: 100000 iops: 340296
Commands: 500000 iops: 357458
Commands: 1000000 iops: 359184
TEST PASSED
For more comprehensive documentation, `click here <http://xilinx.github.io/Vitis_Accel_Examples>`__. | 29.970588 | 275 | 0.713445 |
c6e8fe02fe2ac961099898b41c9e252cff15712a | 94 | rst | reStructuredText | docs/moduledocs.rst | shawnmullaney/graphitesend | 3759d1a6be25e84674e7f9e18920050f5a1586c1 | [
"Apache-2.0"
] | 122 | 2015-01-13T11:50:19.000Z | 2021-11-08T09:39:25.000Z | docs/moduledocs.rst | shawnmullaney/graphitesend | 3759d1a6be25e84674e7f9e18920050f5a1586c1 | [
"Apache-2.0"
] | 57 | 2015-02-08T21:15:21.000Z | 2019-08-09T21:50:57.000Z | docs/moduledocs.rst | shawnmullaney/graphitesend | 3759d1a6be25e84674e7f9e18920050f5a1586c1 | [
"Apache-2.0"
] | 42 | 2015-01-25T16:39:13.000Z | 2019-10-10T07:49:51.000Z |
================
GraphiteSend API
================
.. automodule:: graphitesend
:members:
| 11.75 | 28 | 0.468085 |
a7317a6015913577258b1591ba96b64e277c7e60 | 90 | rst | reStructuredText | doc/source/reference/generated/numpy.ma.argsort.rst | qpython-android/QPypi-numpy | 4e5fa5c2e01bb6250537fe44f426f878a240bcc7 | [
"BSD-3-Clause"
] | 7 | 2016-11-29T18:01:53.000Z | 2018-08-21T09:45:15.000Z | doc/source/reference/generated/numpy.ma.argsort.rst | qpython-lab/QPypi-numpy | 4e5fa5c2e01bb6250537fe44f426f878a240bcc7 | [
"BSD-3-Clause"
] | 1 | 2016-06-28T14:03:59.000Z | 2016-06-28T14:03:59.000Z | doc/source/reference/generated/numpy.ma.argsort.rst | qpython-libs/QPypi-numpy | 4e5fa5c2e01bb6250537fe44f426f878a240bcc7 | [
"BSD-3-Clause"
] | 3 | 2016-10-19T00:41:31.000Z | 2020-03-01T04:57:36.000Z | numpy.ma.argsort
================
.. currentmodule:: numpy.ma
.. autofunction:: argsort
| 12.857143 | 27 | 0.588889 |
6240a68c1150a5abc1a60f5501af1f04e9b0254a | 1,196 | rst | reStructuredText | EEPROM/README.rst | nonNoise/Kitagami-KnowledgeBase | 22f094e4979b97702876d2128b49e3006f0ec98b | [
"MIT"
] | null | null | null | EEPROM/README.rst | nonNoise/Kitagami-KnowledgeBase | 22f094e4979b97702876d2128b49e3006f0ec98b | [
"MIT"
] | null | null | null | EEPROM/README.rst | nonNoise/Kitagami-KnowledgeBase | 22f094e4979b97702876d2128b49e3006f0ec98b | [
"MIT"
] | null | null | null | ====================================================================================
出荷時にデータが書き込まれたEEPROM
====================================================================================
■ はじめに
------------------------------------------------------------------------------------
EEPROMを実装する際に、すでにデータが書き込まれたものがある為、それをまとめて置く。
48bit MACアドレスが書き込まれたEEPROM
------------------------------------------------------------------------------------
- 24AA02E48
2Kb I2C Serial EEPROM with Pre-Programmed EUI-48™ MAC ID
https://www.microchip.com/wwwproducts/en/24AA02E48
64bit MACアドレス(IPv6用)が書き込まれたEEPROM
------------------------------------------------------------------------------------
- 24AA02E64
2Kb I2C Serial EEPROM with Pre-Programmed EUI-64™ MAC ID
https://www.microchip.com/wwwproducts/en/24AA02E64
32ビットUID(シリアル番号)が書き込まれたEEPROM
------------------------------------------------------------------------------------
- 24AA02UID
2Kb I2C Serial EEPROM with Pre-Programmed Serial Number
https://www.microchip.com/wwwproducts/en/24AA02UID
|
|
|
|
::
MIT License
Copyright (c) 2018 Yuta KItagami
固有の企業や団体と一切関わりが無い個人のプロジェクトです。
| 23.45098 | 84 | 0.418896 |
cd5063c0ad470d98bfafa5157fba3858d645359f | 1,864 | rst | reStructuredText | README.rst | dellielo/KataTest | 83f4499a0e3f9d950ebc6c8bd02604181836d23a | [
"MIT"
] | null | null | null | README.rst | dellielo/KataTest | 83f4499a0e3f9d950ebc6c8bd02604181836d23a | [
"MIT"
] | null | null | null | README.rst | dellielo/KataTest | 83f4499a0e3f9d950ebc6c8bd02604181836d23a | [
"MIT"
] | null | null | null | ========
Overview
========
.. start-badges
.. list-table::
:stub-columns: 1
* - docs
- |docs|
* - tests
- | |travis| |appveyor|
| |codecov|
* - package
- | |version|
| |commits-since|
.. |docs| image:: https://readthedocs.org/projects/katatest/badge/?style=flat
:target: https://readthedocs.org/projects/katatest
:alt: Documentation Status
.. |travis| image:: https://api.travis-ci.org/dellielo/katatest.svg?branch=master
:alt: Travis-CI Build Status
:target: https://travis-ci.org/dellielo/katatest
.. |appveyor| image:: https://ci.appveyor.com/api/projects/status/github/dellielo/katatest?branch=master&svg=true
:alt: AppVeyor Build Status
:target: https://ci.appveyor.com/project/dellielo/katatest
.. |codecov| image:: https://codecov.io/github/dellielo/katatest/coverage.svg?branch=master
:alt: Coverage Status
:target: https://codecov.io/github/dellielo/katatest
.. |commits-since| image:: https://img.shields.io/github/commits-since/dellielo/katatest/v0.0.0.svg
:alt: Commits since latest release
:target: https://github.com/dellielo/katatest/compare/v0.0.0...master
.. end-badges
Mise pratique de tests sur un projet Kata
* Free software: MIT license
Installation
============
::
pip install katatest
You can also install the in-development version with::
pip install https://github.com/dellielo/katatest/archive/master.zip
Documentation
=============
https://katatest.readthedocs.io/
Development
===========
To run the all tests run::
tox
Note, to combine the coverage data from all the tox environments run:
.. list-table::
:widths: 10 90
:stub-columns: 1
- - Windows
- ::
set PYTEST_ADDOPTS=--cov-append
tox
- - Other
- ::
PYTEST_ADDOPTS=--cov-append tox
| 20.94382 | 113 | 0.647532 |
f4cf11a07fd14965fe4a84c065ea99107537e4a3 | 1,004 | rst | reStructuredText | migration/Foxy.rst | ccmarquez/copyofnavigation.ros.org | 34bedc5f54335ebece2a2d0e14a351cddbc73cf3 | [
"Apache-2.0"
] | null | null | null | migration/Foxy.rst | ccmarquez/copyofnavigation.ros.org | 34bedc5f54335ebece2a2d0e14a351cddbc73cf3 | [
"Apache-2.0"
] | null | null | null | migration/Foxy.rst | ccmarquez/copyofnavigation.ros.org | 34bedc5f54335ebece2a2d0e14a351cddbc73cf3 | [
"Apache-2.0"
] | null | null | null | .. _foxy_migration:
Foxy to Galactic
################
Moving from ROS 2 Foxy to Galactic, a number of stability improvements were added that we will not specifically address here.
NavigateToPose BT-node Interface Changes
****************************************
The NavigateToPose input port has been changed to PoseStamped instead of Point and Quaternion.
See :ref:`bt_navigate_to_pose_action` for more information.
BackUp BT-node Interface Changes
********************************
The ``backup_dist`` and ``backup_speed`` input ports should both be positive values indicating the distance to go backward respectively the speed with which the robot drives backward.
BackUp Recovery Interface Changes
*********************************
``speed`` in a backup recovery goal should be positive indicating the speed with which to drive backward.
``target.x`` in a backup recovery goal should be positive indicating the distance to drive backward.
In both cases negative values are silently inverted.
| 38.615385 | 183 | 0.710159 |
1619e9d10ba44489b81e22cb318cda4ebc1b8325 | 1,836 | rst | reStructuredText | Rdatasets/doc/robustbase/rst/toxicity.rst | LuisFRoch/data | fef796bc2733120f20236f1de817a9f20acc9c94 | [
"MIT"
] | 467 | 2015-04-02T13:29:22.000Z | 2022-03-04T13:52:03.000Z | Rdatasets/doc/robustbase/rst/toxicity.rst | LuisFRoch/data | fef796bc2733120f20236f1de817a9f20acc9c94 | [
"MIT"
] | 10 | 2015-08-03T23:46:07.000Z | 2016-07-16T15:57:09.000Z | Rdatasets/doc/robustbase/rst/toxicity.rst | LuisFRoch/data | fef796bc2733120f20236f1de817a9f20acc9c94 | [
"MIT"
] | 188 | 2015-03-08T18:10:50.000Z | 2022-02-17T08:50:08.000Z | +------------+-------------------+
| toxicity | R Documentation |
+------------+-------------------+
Toxicity of Carboxylic Acids Data
---------------------------------
Description
~~~~~~~~~~~
The aim of the experiment was to predict the toxicity of carboxylic
acids on the basis of several molecular descriptors.
Usage
~~~~~
::
data(toxicity)
Format
~~~~~~
A data frame with 38 observations on the following 10 variables which
are attributes for carboxylic acids:
``toxicity``
aquatic toxicity, defined as *log(IGC50^(-1))*; typically the
“response”.
``logKow``
*log Kow*
, the partition coefficient
``pKa``
pKa: the dissociation constant
``ELUMO``
**E**\ nergy of the **l**\ owest **u**\ noccupied **m**\ olecular
**o**\ rbital
``Ecarb``
Electrotopological state of the **carb**\ oxylic group
``Emet``
Electrotopological state of the **met**\ hyl group
``RM``
Molar refractivity
``IR``
Refraction index
``Ts``
Surface tension
``P``
Polarizability
Source
~~~~~~
The website accompanying the MMY-book:
`http://www.wiley.com/legacy/wileychi/robust\_statistics <http://www.wiley.com/legacy/wileychi/robust_statistics>`__
References
~~~~~~~~~~
Maguna, F.P., Núñez, M.B., Okulik, N.B. and Castro, E.A. (2003) Improved
QSAR analysis of the toxicity of aliphatic carboxylic acids; *Russian
Journal of General Chemistry* **73**, 1792–1798.
Examples
~~~~~~~~
::
data(toxicity)
summary(toxicity)
plot(toxicity)
plot(toxicity ~ pKa, data = toxicity)
## robustly scale the data (to scale 1) using Qn
(scQ.tox <- sapply(toxicity, Qn))
scTox <- scale(toxicity, center = FALSE, scale = scQ.tox)
csT <- covOGK(scTox, n.iter = 2,
sigmamu = s_Qn, weight.fn = hard.rejection)
as.dist(round(cov2cor(csT$cov), 2))
| 20.175824 | 116 | 0.617647 |
385beab29e56c166eac580c312634bbe9002bd0a | 2,504 | rst | reStructuredText | docs/reference/index.rst | m-novikov/websockets | 668f320e0547d80afe6529528e1ecc6088955cdc | [
"BSD-3-Clause"
] | 3,909 | 2015-01-02T02:35:09.000Z | 2022-03-31T14:03:01.000Z | docs/reference/index.rst | m-novikov/websockets | 668f320e0547d80afe6529528e1ecc6088955cdc | [
"BSD-3-Clause"
] | 1,066 | 2015-01-19T07:32:35.000Z | 2022-03-26T15:00:11.000Z | docs/reference/index.rst | m-novikov/websockets | 668f320e0547d80afe6529528e1ecc6088955cdc | [
"BSD-3-Clause"
] | 549 | 2015-01-10T10:23:42.000Z | 2022-03-25T16:38:32.000Z | API reference
=============
.. currentmodule:: websockets
websockets provides client and server implementations, as shown in
the :doc:`getting started guide <../intro/index>`.
The process for opening and closing a WebSocket connection depends on which
side you're implementing.
* On the client side, connecting to a server with :func:`~client.connect`
yields a connection object that provides methods for interacting with the
connection. Your code can open a connection, then send or receive messages.
If you use :func:`~client.connect` as an asynchronous context manager,
then websockets closes the connection on exit. If not, then your code is
responsible for closing the connection.
* On the server side, :func:`~server.serve` starts listening for client
connections and yields an server object that you can use to shut down
the server.
Then, when a client connects, the server initializes a connection object and
passes it to a handler coroutine, which is where your code can send or
receive messages. This pattern is called `inversion of control`_. It's
common in frameworks implementing servers.
When the handler coroutine terminates, websockets closes the connection. You
may also close it in the handler coroutine if you'd like.
.. _inversion of control: https://en.wikipedia.org/wiki/Inversion_of_control
Once the connection is open, the WebSocket protocol is symmetrical, except for
low-level details that websockets manages under the hood. The same methods
are available on client connections created with :func:`~client.connect` and
on server connections received in argument by the connection handler
of :func:`~server.serve`.
Since websockets provides the same API — and uses the same code — for client
and server connections, common methods are documented in a "Both sides" page.
.. toctree::
:titlesonly:
client
server
common
utilities
exceptions
types
extensions
limitations
Public API documented in the API reference are subject to the
:ref:`backwards-compatibility policy <backwards-compatibility policy>`.
Anything that isn't listed in the API reference is a private API. There's no
guarantees of behavior or backwards-compatibility for private APIs.
For convenience, many public APIs can be imported from the ``websockets``
package. This feature is incompatible with static code analysis tools such as
mypy_, though. If you're using such tools, use the full import path.
.. _mypy: https://github.com/python/mypy
| 37.373134 | 78 | 0.77516 |
5c0c010ff6c23607b8531e169889e45a092ec856 | 219 | rst | reStructuredText | docs/instrumentation/instrumentor.rst | TimPansino/opentelemetry-python | 51ed4576c611316bd3f74d213501f5ffa3e2a5ca | [
"Apache-2.0"
] | 208 | 2020-04-07T21:18:03.000Z | 2022-03-31T21:45:30.000Z | docs/instrumentation/instrumentor.rst | TimPansino/opentelemetry-python | 51ed4576c611316bd3f74d213501f5ffa3e2a5ca | [
"Apache-2.0"
] | 636 | 2020-04-08T17:39:48.000Z | 2022-03-31T18:48:40.000Z | docs/instrumentation/instrumentor.rst | TimPansino/opentelemetry-python | 51ed4576c611316bd3f74d213501f5ffa3e2a5ca | [
"Apache-2.0"
] | 172 | 2020-06-05T22:33:37.000Z | 2022-03-30T13:57:27.000Z | opentelemetry.instrumentation.instrumentor package
==================================================
.. automodule:: opentelemetry.instrumentation.instrumentor
:members:
:undoc-members:
:show-inheritance:
| 27.375 | 58 | 0.598174 |
a539f4127855e220812adcbccd0a258ac3086569 | 389 | rst | reStructuredText | docs/source/getting_started.rst | JuliaPackageMirrors/MarketTechnicals.jl | 4c80ac26b9a24fb3c4992f6ff1795abdd689dad3 | [
"MIT"
] | 2 | 2017-07-25T07:56:03.000Z | 2017-07-25T08:34:12.000Z | docs/source/getting_started.rst | JuliaPackageMirrors/MarketTechnicals.jl | 4c80ac26b9a24fb3c4992f6ff1795abdd689dad3 | [
"MIT"
] | null | null | null | docs/source/getting_started.rst | JuliaPackageMirrors/MarketTechnicals.jl | 4c80ac26b9a24fb3c4992f6ff1795abdd689dad3 | [
"MIT"
] | null | null | null | Getting Started
==============
MarketTechnicals is a registered package. To add it to your Julia packages, simply do the following in
REPL::
Pkg.add("MarketTechnicals")
We will use data from the ``MarketData`` package to demonstrate how this package produces results from various technical analysis indicators. That
package can also be added from REPL::
Pkg.add("MarketData")
| 29.923077 | 146 | 0.745501 |
2bd5a664db5fd881b6934ad6280b1a390259257e | 336 | rst | reStructuredText | docs/user_guide/index.rst | kpritch/simp-doc | 3b65613136da82304e0d1ce6cd065619f465e85c | [
"Apache-2.0"
] | null | null | null | docs/user_guide/index.rst | kpritch/simp-doc | 3b65613136da82304e0d1ce6cd065619f465e85c | [
"Apache-2.0"
] | null | null | null | docs/user_guide/index.rst | kpritch/simp-doc | 3b65613136da82304e0d1ce6cd065619f465e85c | [
"Apache-2.0"
] | null | null | null | .. _simp-user-guide:
SIMP User Guide
===============
Contents:
.. toctree::
:maxdepth: 2
Introduction
Initial_Server_Configuration
Client_Management
SIMP_Administration
User_Management
Upgrade_SIMP
Troubleshooting
HOWTO
SIMP_Package_Data
Indices and tables
------------------
* :ref:`genindex`
* :ref:`search`
| 12.923077 | 30 | 0.675595 |
b184185bcf22998cbda4fd56729d0e01af2ca9c8 | 16,474 | rst | reStructuredText | design/index.rst | RicardoM17/ros2_planning_system.github.io | 299de93f7e64c64255f9c6d9194256f8f55fe5b6 | [
"Apache-2.0"
] | 5 | 2020-12-23T12:15:07.000Z | 2021-11-19T10:06:47.000Z | design/index.rst | RicardoM17/ros2_planning_system.github.io | 299de93f7e64c64255f9c6d9194256f8f55fe5b6 | [
"Apache-2.0"
] | 7 | 2021-04-28T20:56:07.000Z | 2022-03-07T08:53:52.000Z | design/index.rst | RicardoM17/ros2_planning_system.github.io | 299de93f7e64c64255f9c6d9194256f8f55fe5b6 | [
"Apache-2.0"
] | 3 | 2021-06-04T01:31:24.000Z | 2021-11-25T15:04:06.000Z | .. _design:
PlanSys2 design
###############
.. image:: images/plansys2_arch.png
:width: 800px
:align: center
PlanSys2 has a modular design. It is basically composed of 4 nodes:
* **Domain Expert**: Contains the PDDL model information (types, predicates, functions, and actions).
* **Problem Expert**: Contains the current instances, predicates, functions, and goals that compose the model.
* **Planner**: Generates plans (sequence of actions) using the information contained in the Domain and Problem Experts.
* **Executor**: Takes a plan and executes it by activating the *action performers* (the ROS2 nodes that implement each action).
Each of these nodes exposes its functionality using ROS2 services. Even so, in PlanSys2 we have created a client library that can be used in
any application and hides the complexity of using ROS2 services.
.. image:: images/plansys2_clients.png
:width: 500px
:align: center
1. Domain Expert
****************
The objective of the Domain Expert is to read PDDL domains from files and make them available to the rest of the components. It's static (by now).
Parameters
----------
* ``model_file`` [string]: PDDL model files to load, separates by ":". These models will be merged. This allows for a modular application in which each component/package contributes with part of the PDDL and the action implementation. See `plansys2_multidomain_example <https://github.com/IntelligentRoboticsLabs/ros2_planning_system_examples/tree/master/plansys2_multidomain_example>`_ for more details.
Client API
----------
.. code-block:: c++
std::vector<std::string> getTypes()
std::vector<plansys2::Predicate> getPredicates()
std::optional<plansys2::Predicate> getPredicate(const std::string & predicate)
std::vector<plansys2::Function> getFunctions()
std::optional<plansys2::Function> getFunction(const std::string & function)
std::vector<std::string> getActions()
plansys2_msgs::msg::Action::SharedPtr getAction(const std::string & action)
std::vector<std::string> getDurativeActions()
plansys2_msgs::msg::DurativeAction::SharedPtr getDurativeAction(const std::string & action)
std::string getDomain()
Services
--------
* ``domain_expert/get_domain`` [plansys2_msgs::srv::GetDomain]: Get the domain.
* ``domain_expert/get_domain_types`` [plansys2_msgs::srv::GetDomainTypes]: Get the valid types.
* ``domain_expert/get_domain_actions`` [plansys2_msgs::srv::GetDomainActions]: Get the available actions.
* ``domain_expert/get_domain_action_details`` [plansys2_msgs::srv::GetDomainActionDetails]: Get the details of a specific action.
* ``domain_expert/get_domain_durative_actions`` [plansys2_msgs::srv::GetDomainDurativeActions]: Get the available durative actions.
* ``domain_expert/get_domain_durative_action_details`` [plansys2_msgs::srv::GetDomainDurativeActionDetails]: Get the details of a specific durative action.
* ``domain_expert/get_domain_predicates`` [plansys2_msgs::srv::GetDomainPredicates]: Get the valid predicates.
* ``domain_expert/get_domain_predicate_details`` [plansys2_msgs::srv::GetDomainPredicateDetails]: Get the details of a specific predicate.
* ``domain_expert/get_domain_functions`` [plansys2_msgs::srv::GetDomainFunctions]: Get the valid functions.
* ``domain_expert/get_domain_function_details`` [plansys2_msgs::srv::GetDomainFunctionDetails]: Get the details of a specific function.
* ``domain_expert/get_domain`` [plansys2_msgs::srv::GetDomain]: Set the domain as a string.
Publishers / Subscriber
-----------------------
None
2. Problem Expert
*****************
Contains the knowledge of the system: instances, grounded predicates and functions, and goals.
Parameters
----------
* ``model_file`` [string]: PDDL model files to load, separates by ":". These models will be merged. This allows for a modular application in which each component/package contributes with part of the PDDL and the action implementation. See `plansys2_multidomain_example <https://github.com/IntelligentRoboticsLabs/ros2_planning_system_examples/tree/master/plansys2_multidomain_example>`_ for more details.
Client API
----------
.. code-block:: c++
std::vector<plansys2::Instance> getInstances();
bool addInstance(const plansys2::Instance & instance);
bool removeInstance(const plansys2::Instance & instance);
std::optional<plansys2::Instance> getInstance(const std::string & name);
std::vector<plansys2::Predicate> getPredicates();
bool addPredicate(const plansys2::Predicate & predicate);
bool removePredicate(const plansys2::Predicate & predicate);
bool existPredicate(const plansys2::Predicate & predicate);
std::optional<plansys2::Predicate> getPredicate(const std::string & predicate);
std::vector<plansys2::Function> getFunctions();
bool addFunction(const plansys2::Function & function);
bool removeFunction(const plansys2::Function & function);
bool existFunction(const plansys2::Function & function);
bool updateFunction(const plansys2::Function & function);
std::optional<plansys2::Function> getFunction(const std::string & function);
plansys2::Goal getGoal();
bool setGoal(const plansys2::Goal & goal);
bool isGoalSatisfied(const plansys2::Goal & goal);
bool clearGoal();
bool clearKnowledge();
std::string getProblem();
Services
--------
* ``problem_expert/add_problem_goal`` [plansys2_msgs::srv::AddProblemGoal]: Replace the goal.
* ``problem_expert/add_problem_instance`` [plansys2_msgs::srv::AffectParam]: Add an instance.
* ``problem_expert/add_problem_predicate`` [plansys2_msgs::srv::AffectNode]: Add a predicate.
* ``problem_expert/add_problem_function`` [plansys2_msgs::srv::AffectNode]: Add a function.
* ``problem_expert/get_problem_goal`` [plansys2_msgs::srv::GetProblemGoal]: Get the current goal.
* ``problem_expert/get_problem_instance`` [plansys2_msgs::srv::GetProblemInstanceDetails]: Get the details of an instance.
* ``problem_expert/get_problem_instances`` [plansys2_msgs::srv::GetProblemInstances]: Get all the instances.
* ``problem_expert/get_problem_predicate =`` [plansys2_msgs::srv::GetNodeDetails]: Get the details of a predicate.
* ``problem_expert/get_problem_predicates`` [plansys2_msgs::srv::GetStates]: Get all the predicates.
* ``problem_expert/get_problem_function =`` [plansys2_msgs::srv::GetNodeDetails]: Get the details of a function.
* ``problem_expert/get_problem_functions`` [plansys2_msgs::srv::GetStates]: Get all the functions.
* ``problem_expert/get_problem`` [plansys2_msgs::srv::GetProblem]: Get the PDDL problem as a string.
* ``problem_expert/remove_problem_goal`` [plansys2_msgs::srv::RemoveProblemGoal]: Remove the current goal.
* ``problem_expert/remove_problem_instance`` [plansys2_msgs::srv::AffectParam]: Remove an instance.
* ``problem_expert/remove_problem_predicate`` [plansys2_msgs::srv::AffectNode]: Remove a predicate.
* ``problem_expert/remove_problem_function`` [plansys2_msgs::srv::AffectNode]: Remove a function.
* ``problem_expert/clear_problem_predicate`` [plansys2_msgs::srv::ClearProblemKnowledge]: Clears the instances, predicates, and functions.
* ``problem_expert/exist_problem_predicate`` [plansys2_msgs::srv::ExistNode]: Check if a predicate exists.
* ``problem_expert/exist_problem_function`` [plansys2_msgs::srv::ExistNode]: Check if a function exists.
* ``problem_expert/update_problem_function`` [plansys2_msgs::srv::AffectNode]: Update a function value.
* ``problem_expert/is_problem_goal_satisfied`` [plansys2_msgs::srv::IsProblemGoalSatisfied]: Check if a goal is satisfied.
Publishers / Subscriber
-----------------------
* ``problem_expert/update_notify`` [std_msgs::msg::Empty] {Publisher: rclcpp::QoS(100)}: A message is published on this topic when any element of the problem changes.
* ``problem_expert/knowledge`` [plansys2_msgs::msg::Knowledge] {Publisher: rclcpp::QoS(100)}: A message is published on this topic when any element of the problem changes.
3. Planner
**********
This component calculates the plan to obtain a goal.
1. A plan may be requested by providing a domain acquired from the Domain Expert and a problem acquired from the Problem expert.
2. The domain is stored in ``/tmp/<node namespace>/domain.pddl``. This allows for several PlanSys2 instances in the same machine, which is useful for simulating multiple robots in the same machine.
3. The problem is stored in ``/tmp/<node namespace>/problem.pddl``.
4. Run the PDDL Solver, storing the output in ``tmp/<node namespace>/plan.pddl``.
5. Parse ``tmp/<node namespace>/plan.pddl`` to get the sequence of actions as a vector of string.
6. Return the result.
Each PDDL solver in PlanSys2 is a plugin. By default PlanSys2 uses `POPF <https://github.com/IntelligentRoboticsLabs/ros2_planning_system/tree/master/plansys2_popf_plan_solver>`_, although other PDDL solvers can be used easily. Currently, the
`Temporal Fast Downward <https://github.com/IntelligentRoboticsLabs/plansys2_tfd_plan_solver>`_ is also available.
.. image:: images/plansys2_planner.png
:width: 300px
:align: center
Parameters
----------
* ``plan_solver_plugins`` [vector<string>]: List of PDDL solver plugins. Currently, only the first plugin specified will be used. If not set, POPF will be used by default. Check `this config <https://github.com/IntelligentRoboticsLabs/ros2_planning_system/blob/master/plansys2_bringup/params/plansys2_params.yaml>`_ as an example on how to use it.
Client API
----------
.. code-block:: c++
boost::optional<plansys2_msgs::msg::Plan> getPlan(const std::string & domain, const std::string & problem)
Services
--------
* ``planner/get_plan`` [plansys2_msgs::srv::GetPlan]: Get a plan that will satisfy the provided domain and problem.
Publishers / Subscriber
-----------------------
None
4. Executor
***********
This component is responsible for executing a provided plan. It is, by far, the most complex component since the execution involves activating the action performers. This task is carried out with the following characteristics:
* It optimizes its execution, parallelizing the actions when possible.
* It checks if the requirements are met at runtime.
* It allows more than one action performer for each action, supporting multirobot execution.
.. image:: images/plansys2_arch2.png
:width: 600px
:align: center
Parameters
----------
* ``action_timeouts.actions`` [vector<string>]: List of actions with enabled duration timeout capability. When the duration timeout capability is enabled for a given action, the action will halt after exceeding the action duration by more than a specified percentage. Duration timeouts are not enabled by default. To enable duration timeouts, the user must provide a custom action execution XML behavior tree template that includes the CheckTimeout BT node. Additionally, this parameter must specify the actions for which duration timeouts are enabled. Finally, the duration overrun percentage must be specified for each action.
* ``action_timeouts.<action_name>.duration_overrun_percentage`` [double]: When action duration timeouts are enabled (see explanation above), the duration overrun percentage specifies the amount of time an action is allowed to overrun its duration before halting. The overrun time is defined as a percentage of the action duration specified by the domain.
* ``default_action_bt_xml_filename`` [string]: Filepath to a user provided custom action execution XML behavior tree template. The user can use this template to specify a different XML behavior tree template than the one provided in the plansy2_executor package. Currently the only available BT node not used by the default behavior tree template is the CheckTimeout node.
* ``enable_dotgraph_legend`` [bool]: Enable legend with planning graph in DOT graph plan viewer.
* ``print_graph`` [bool]: Print planning graph to terminal.
* ``enable_groot_monitoring`` [bool]: Enable visualizing the plan's behavior tree inside `Groot <https://github.com/BehaviorTree/Groot>`_.
* ``publisher_port`` [unsigned int]: ZeroMQ publisher port for `Groot <https://github.com/BehaviorTree/Groot>`_.
* ``server_port`` [unsigned int]: ZeroMQ server port for `Groot <https://github.com/BehaviorTree/Groot>`_.
* ``max_msgs_per_second`` [unsigned int]: Maximum number of ZeroMQ messages sent per second to `Groot <https://github.com/BehaviorTree/Groot>`_.
Client API
----------
.. code-block:: c++
bool start_plan_execution(const plansys2_msgs::msg::Plan & plan);
bool execute_and_check_plan();
void cancel_plan_execution();
std::vector<plansys2_msgs::msg::Tree> getOrderedSubGoals();
std::optional<plansys2_msgs::msg::Plan> getPlan();
ExecutePlan::Feedback getFeedBack() {return feedback_;}
std::optional<ExecutePlan::Result> getResult();
Actions
--------
* ``execute_plan`` [plansys2_msgs::action::ExecutePlan]: Execute the provided plan.
Publishers / Subscriber
-----------------------
* ``dot_graph`` [std_msgs::msg::String] {Publisher: rclcpp::QoS(1)}: Publishes the planning DOT graph.
* ``/action_execution_info`` [plansys2_msgs::msg::ActionExecutionInfo] {Publisher: rclcpp::QoS(100)}: Publishes the action execution information. Note that the action execution information is also provided to the ExecutePlan action client via the feedback and result channels.
Behavior Tree builder
*********************
Once a plan is obtained, the Executor converts it to a Behavior Tree to execute it. Each action becomes the following subtree:
.. image:: images/action_bt.png
:width: 400px
:align: center
The first step is building a planning graph that encodes the action dependencies that define the execution order. This is made
by pairing the effects of an action with a requirement of a posterior action. We take as reference the time of the calculated plan:
.. image:: images/action_deps.png
:width: 250px
:align: center
.. image:: images/plan_graph.png
:width: 200px
:align: center
Once created the graph, we identify the execution flows:
.. image:: images/graph_flows.png
:width: 800px
:align: center
From the red flow, for example, we get:
.. image:: images/red_flow.png
:width: 400px
:align: center
Each flow is executed in parallel. There is no problem if flows overlap because the BT that executes an action is implemented following a Singleton-like approach.
Action delivery protocol
************************
In the first implementations of PlanSys2, the delivery of actions was done using ROS2 actions. This approach has currently been discarded as it is not flexible enough.
Instead, a bidding-based delivery protocol has been developed in the ``ActionExecutor`` and ``ActionExecutorClient`` classes that uses the ``plansys2_msgs::msg::ActionExecution`` message.
When the Executor must execute an action, it requests which action performer can execute it. Those who can
reply to this request. The Executor confirms one of them (the first to answer), rejecting the rest. If none are found, repeat the request every second until you give up, aborting the
execution of the plan. This protocol uses the topic ``/action_hub``, where you can monitor the execution of the system.
.. image:: images/protocol.png
:width: 500px
:align: center
All the action performers inherit from ``ActionExecutorClient``, that is a ROS2 Node with the next information:
Parameters
----------
* ``~/action`` [string]: The action managed. This action performer discard any request non equal to this parameter.
* ``~/specialized_arguments`` [vector<string>]: If this parameter is not void, it only replies to action request that contains in any of the arguments any of these values.
.. note:: In a multirobot application, for example, we add to the actions a parameter with the robot that should do the action. In each robot we can execute the same action performer, and using ``~/specialized_arguments`` we can select which will be executed.
Publishers / Subscriber
-----------------------
* ``/actions_hub`` [plansys2_msgs::msg::ActionExecution] {Publisher: rclcpp::QoS(100).reliable()}: Receive messages from the Action Hub.
* ``/actions_hub`` [plansys2_msgs::msg::ActionExecution] {Subscriber: rclcpp::QoS(100).reliable()}: Publish messages to the Action Hub.
| 54.190789 | 628 | 0.748391 |
1056a52709ec661ee803b83be90243bff5547675 | 546 | rst | reStructuredText | README.rst | icsa-caps/c3d-protocol | 3cd3a1507a6e9862d229bfca22a481153187d899 | [
"BSD-3-Clause"
] | 1 | 2017-07-05T03:15:40.000Z | 2017-07-05T03:15:40.000Z | README.rst | icsa-caps/c3d-protocol | 3cd3a1507a6e9862d229bfca22a481153187d899 | [
"BSD-3-Clause"
] | null | null | null | README.rst | icsa-caps/c3d-protocol | 3cd3a1507a6e9862d229bfca22a481153187d899 | [
"BSD-3-Clause"
] | null | null | null | ============
C3D Protocol
============
This repository provides a Murphi `model <C3D.m>`_ and detailed protocol
`specification <as-table/c3d-protocol.pdf>`_ in table format of the C3D
protocol [1]_.
References
==========
.. [1] Cheng-Chieh Huang, Rakesh Kumar, Marco Elver, Boris Grot, and Vijay Nagarajan.
`C3D: Mitigating the NUMA Bottleneck via Coherent DRAM Caches
<http://homepages.inf.ed.ac.uk/bgrot/pubs/C3D_MICRO16.pdf>`_.
In IEEE/ACM International Symposium on Microarchitecture (MICRO). Taipei,
Taiwan, October 2016.
| 32.117647 | 85 | 0.701465 |
552a894c439f0692ee92c859e0e7aec910c346e5 | 1,199 | rst | reStructuredText | chef_master/source/resource_chef_mirror.rst | jblaine/chef-docs | dc540f7bbc2d3eedb05a74f34b1caf25f1a5d7d3 | [
"CC-BY-3.0"
] | null | null | null | chef_master/source/resource_chef_mirror.rst | jblaine/chef-docs | dc540f7bbc2d3eedb05a74f34b1caf25f1a5d7d3 | [
"CC-BY-3.0"
] | 1 | 2021-06-27T17:03:16.000Z | 2021-06-27T17:03:16.000Z | chef_master/source/resource_chef_mirror.rst | jblaine/chef-docs | dc540f7bbc2d3eedb05a74f34b1caf25f1a5d7d3 | [
"CC-BY-3.0"
] | null | null | null | =====================================================
chef_mirror
=====================================================
.. warning:: .. include:: ../../includes_notes/includes_notes_provisioning.rst
.. include:: ../../includes_chef_client/includes_chef_client.rst
.. include:: ../../includes_resources/includes_resource_chef_mirror.rst
Syntax
=====================================================
.. include:: ../../includes_resources/includes_resource_chef_mirror_syntax.rst
Actions
=====================================================
.. include:: ../../includes_resources/includes_resource_chef_mirror_actions.rst
Properties
=====================================================
.. include:: ../../includes_resources/includes_resource_chef_mirror_attributes.rst
..
.. Providers
.. =====================================================
.. .. include:: ../../includes_resources_common/includes_resources_common_provider.rst
..
.. .. include:: ../../includes_resources_common/includes_resources_common_provider_attributes.rst
..
.. .. include:: ../../includes_resources/includes_resource_chef_mirror_providers.rst
..
Examples
=====================================================
None.
| 33.305556 | 97 | 0.52794 |
c0636f4b9e175e9428cf92b1657fa99fa0a1d7c2 | 439 | rst | reStructuredText | docs/vim/fault/VspanPromiscuousPortNotSupported.rst | nandonov/pyvmomi | ad9575859087177623f08b92c24132ac019fb6d9 | [
"Apache-2.0"
] | 12 | 2016-09-14T21:59:46.000Z | 2019-12-18T18:02:55.000Z | docs/vim/fault/VspanPromiscuousPortNotSupported.rst | nandonov/pyvmomi | ad9575859087177623f08b92c24132ac019fb6d9 | [
"Apache-2.0"
] | 2 | 2019-01-07T12:02:47.000Z | 2019-01-07T12:05:34.000Z | docs/vim/fault/VspanPromiscuousPortNotSupported.rst | nandonov/pyvmomi | ad9575859087177623f08b92c24132ac019fb6d9 | [
"Apache-2.0"
] | 8 | 2020-05-21T03:26:03.000Z | 2022-01-26T11:29:21.000Z | .. _str: https://docs.python.org/2/library/stdtypes.html
.. _vim.fault.DvsFault: ../../vim/fault/DvsFault.rst
vim.fault.VspanPromiscuousPortNotSupported
==========================================
:extends:
`vim.fault.DvsFault`_
Thrown if a promiscuous port appears in transmitted source or destination ports of any Distributed Port Mirroring session.
Attributes:
vspanSessionKey (`str`_)
portKey (`str`_)
| 19.086957 | 124 | 0.651481 |
36ccc1996bf5cd72601302a26abda6b21677f8ac | 284 | rst | reStructuredText | news/py-rc-files.rst | meramsey/xonsh | 5685ffc8b8aa921012b31dc8af02e14388b730e9 | [
"BSD-2-Clause-FreeBSD"
] | 4,716 | 2016-06-07T05:48:42.000Z | 2022-03-31T22:30:15.000Z | news/py-rc-files.rst | meramsey/xonsh | 5685ffc8b8aa921012b31dc8af02e14388b730e9 | [
"BSD-2-Clause-FreeBSD"
] | 3,644 | 2016-06-07T05:55:42.000Z | 2022-03-31T13:25:57.000Z | news/py-rc-files.rst | agoose77/xonsh | 7331d8aee50e8939f8fe4d5b7133ed3907f204f4 | [
"BSD-2-Clause-FreeBSD"
] | 576 | 2016-06-07T06:28:32.000Z | 2022-03-31T02:46:15.000Z | **Added:**
* Pure Python control files are now supported when named ``*.py``.
Using python files may lower the startup time by a bit.
**Changed:**
* <news item>
**Deprecated:**
* <news item>
**Removed:**
* <news item>
**Fixed:**
* <news item>
**Security:**
* <news item>
| 11.36 | 66 | 0.612676 |
a17847ecd6d96cb610c35ecbec43fccd2c2fcdcd | 3,093 | rst | reStructuredText | docs/examples/rst/cl_crops_cropstr.rst | jjavier-bm/crops | 658a98f9c168cc27b3f967e7a60a0df896ef5ac6 | [
"BSD-3-Clause"
] | null | null | null | docs/examples/rst/cl_crops_cropstr.rst | jjavier-bm/crops | 658a98f9c168cc27b3f967e7a60a0df896ef5ac6 | [
"BSD-3-Clause"
] | 5 | 2020-07-17T08:45:22.000Z | 2022-03-11T13:39:26.000Z | docs/examples/rst/cl_crops_cropstr.rst | jjavier-bm/crops | 658a98f9c168cc27b3f967e7a60a0df896ef5ac6 | [
"BSD-3-Clause"
] | 1 | 2020-07-07T15:42:07.000Z | 2020-07-07T15:42:07.000Z | .. _cl_crops_cropstr:
Structure file cropping
------------------------
For the removal of residues out of a structure file, this CROPS command will do it for you:
.. code-block:: shell-session
crops-cropstr 3org.fasta 3org.pdb dbs/pdb_chain_uniprot.csv --output mydir/
The result of the above call is the output file ``3org/3org.crops.to_uniprot.pdb`` containing a minimal output of the original ``3org.pdb`` with the residues of all models and chains cropped and renumbered according to residue position in the new sequences produced in ``3org.crops.to_uniprot.fasta``. Ligands are renumbered with consecutive indices right after the chain ends. Addional outputs are a renumbered minimal version of the original pdb ``3org/3org.crops.seqs.pdb`` (same as returned by ``crops-renumber``), and a cropped version with the residue numbers being the position in the **old** sequence ``3org/3org.crops.to_uniprot.oldids.pdb``. The interval database ``dbs/pdb_chain_uniprot.csv`` in this case is the SIFTS database mapping each residue to a Uniprot reference or none at all (and hence the *to_uniprot* filetag). When a custom interval database is provided (the custom ``.csv`` database format must be *pdb_ID*, *monomer_ID*, *integer*, *integer*), the filetag name will be *custom* instead.
The output directory argument is optional. If not provided, the results will be saved in the sequence file's directory by default.
.. note::
The residue content and positioning in the sequence and structure files **must** be compatible with each other (i.e. both files should come from the same source). If that is not the case, an ERROR message will appear.
--------------------------------------------------------------
Additionally, one of these mutually exclusive conditions can also be imposed:
1. To produce sequences that only discard the *non-Uniprot* (or custom criteria) segments at each of the chains' ends, the option ``--terminals`` or ``-t`` can be added to the command line instruction so only the unwanted parts at the ends are removed:
.. code-block:: shell-session
crops-cropstr 3org.fasta 3org.pdb dbs/pdb_chain_uniprot.csv --terminals --output mydir/
For instance, in a case in which the intervals imported for one particular chain are ``[5,20]`` and ``[90,125]``, this option will tell CROPS to act as if one single interval ``[5,125]`` is provided, therefore preserving the middle part of the sequence and structure that otherwise would be removed.
2. Sometimes, small contributions from Uniprot sequences other than the main one may not be desired in the cropped version. The option ``--uniprot`` or ``-u`` allows to keep Uniprot residues **only** from those Uniprot references that contribute with a percentage of residues above the given threshold:
.. code-block:: shell-session
crops-cropstr 3org.fasta 3org.pdb dbs/pdb_chain_uniprot.csv --uniprot 70 uniclust##_yyyy_mm_consensus --terminals --output mydir/
In the above case, only those Uniprot references that contribute with more than 70% of their original residues are considered.
| 79.307692 | 1,014 | 0.746848 |
ccf2c8caa1215b258c6e62278a8b383e805a38b9 | 751 | rst | reStructuredText | docs/installation.rst | sphinxnh/pybliometrics | 48311d701f581e049e835e5c8e06b782099cdab4 | [
"MIT"
] | 1 | 2019-10-19T17:03:45.000Z | 2019-10-19T17:03:45.000Z | docs/installation.rst | sphinxnh/pybliometrics | 48311d701f581e049e835e5c8e06b782099cdab4 | [
"MIT"
] | null | null | null | docs/installation.rst | sphinxnh/pybliometrics | 48311d701f581e049e835e5c8e06b782099cdab4 | [
"MIT"
] | null | null | null | ============
Installation
============
.. include:: ../README.rst
:start-after: installation-begin
:end-before: installation-end
To access the Scopus database using `pybliometrics`, get an API key from http://dev.elsevier.com/myapikey.html. On first usage, `pybliometrics` prompts you for authentication details and stores them in `~/.scopus/config.ini`, where you can change it manually (see :doc:`Configuration </configuration>`). If your institution subscribes to Scopus, you may need to be in your institution's network or you need to have an InstToken, which can also be saved in the configuration. Non-subscribers only get limited access to two APIs.
See extended description and examples in the :doc:`Examples </examples>` section.
| 62.583333 | 530 | 0.744341 |
72e8155d9dd5793571f65b888bb2e8c139b2497c | 1,644 | rst | reStructuredText | typo3conf/ext/pagenotfoundhandling/Documentation/Administration/Index.rst | michelsacher/giennale | 47ab33d1611389d37ef8263a3adc79dd8c841781 | [
"CC-BY-3.0"
] | null | null | null | typo3conf/ext/pagenotfoundhandling/Documentation/Administration/Index.rst | michelsacher/giennale | 47ab33d1611389d37ef8263a3adc79dd8c841781 | [
"CC-BY-3.0"
] | null | null | null | typo3conf/ext/pagenotfoundhandling/Documentation/Administration/Index.rst | michelsacher/giennale | 47ab33d1611389d37ef8263a3adc79dd8c841781 | [
"CC-BY-3.0"
] | null | null | null | .. include:: ../Includes.txt
.. _section-administration:
==============================
Administration
==============================
.. _section-installation:
Installation
==============================
Install the extension via extension manager.
Once installed the extension is already active. By default the 404 Page is a
simple pure HTML template, that includes a title and a message with almost
no styles.
**Important:** If your default website language is not english, configure
your default language code in the extension manager.
Suggestions
^^^^^^^^^^^
* Optional you can make use of the third-party extension
`static_info_tables <http://typo3.org/extensions/repository/view/static_info_tables/current/>`_.
.. _section-available-markers:
Available markers
==============================
In template files or in fetched pages, several markers will be replaced before
outputting:
.. container:: table-row
Marker
###TITLE###
Description
``page_title`` from locallang_404.xml
.. container:: table-row
Marker
###MESSAGE###
Description
``page_message`` from locallang_404.xml
.. container:: table-row
Marker
###REASON_TITLE###
Description
``reason_title`` from locallang_404.xml
.. container:: table-row
Marker
###REASON###
Description
From TYPO3 (autofilled)
.. container:: table-row
Marker
###CURRENT_URL_TITLE###
Description
``current_url_title`` from locallang_404.xml
.. container:: table-row
Marker
###CURRENT_URL###
Description
From TYPO3 (autofilled)
| 18.47191 | 98 | 0.631995 |
396dbde56e83bf0642e1e1644305467e9a4621cd | 208 | rst | reStructuredText | HISTORY.rst | skada/django-money-rates | aeb2edf240471fac64f9cdf71e34f91d632f1b86 | [
"BSD-3-Clause"
] | 75 | 2015-01-02T11:10:35.000Z | 2022-01-29T06:05:38.000Z | HISTORY.rst | skada/django-money-rates | aeb2edf240471fac64f9cdf71e34f91d632f1b86 | [
"BSD-3-Clause"
] | 24 | 2015-02-05T21:04:05.000Z | 2019-03-29T08:19:41.000Z | HISTORY.rst | skada/django-money-rates | aeb2edf240471fac64f9cdf71e34f91d632f1b86 | [
"BSD-3-Clause"
] | 59 | 2015-04-06T19:15:54.000Z | 2019-12-18T19:45:06.000Z | .. :changelog:
History
-------
0.3.0 (2013-12-30)
++++++++++++++++++
* `convert_money` utility function now returns moneyed.Money instances
0.1.0 (2013-10-16)
++++++++++++++++++
* First release on PyPI.
| 13.866667 | 70 | 0.552885 |
5a6ca6ef395df6603d8ba4ceb3b55ee3e15ff06c | 2,690 | rst | reStructuredText | Doc/build_docs/annotations.rst | federicomarini/profDGE48 | bf60ee1fbef85de25aca80288110af75bcd3688f | [
"MIT"
] | 12 | 2016-03-30T14:14:08.000Z | 2021-01-06T01:37:09.000Z | Doc/build_docs/annotations.rst | federicomarini/profDGE48 | bf60ee1fbef85de25aca80288110af75bcd3688f | [
"MIT"
] | 4 | 2016-06-15T21:19:43.000Z | 2017-09-21T15:45:00.000Z | Doc/build_docs/_build/html/_sources/annotations.txt | bartongroup/profDGE48 | d12c8407ead17d27151fb4d00d843c4a29f06541 | [
"MIT"
] | 7 | 2016-03-31T11:30:01.000Z | 2021-12-13T18:43:04.000Z | .. annotations:
.. _annotations:
***********
Annotations
***********
The annotations used to interpret the RNA-seq data for the project. Includes
the ensembl release 68 annotations for Saccharomyces
cerevisiae and details of the ERCC artificial spike-in Mix kit from
`ThermoFisher <https://www.thermofisher.com/order/catalog/product/4456740>`_.
.. ERCC_Controls_Analysis_tsvdoc:
.. _ERCC_Controls_Analysis_tsvdoc:
==========================
ERCC_Controls_Analysis.txt
==========================
Details of the 92 ERCC spike-in analysis values, including the concentrations
of each spike-in in each mix.
.. ERCC_Controls_Annotation_tsvdoc:
.. _ERCC_Controls_Annotation_tsvdoc:
============================
ERCC_Controls_Annotation.txt
============================
Details of the 92 ERCC spike-ins, including ID, Genbank accessions and their
sequence.
.. ERCC92_tsvdoc:
.. _ERCC92_tsvdoc:
==========
ERCC92.gtf
==========
Annotation information for the 92 ERCC spike-ins. (`gtf format
<http://www.ensembl.org/info/website/upload/gff.html>`_)
.. get_gene_info_perldoc:
.. _get_gene_info_perldoc:
================
get_gene_info.pl
================
Get gene descriptions from Ensembl and store them in a tab-separated output file with three columns: gene id, gene name and description. The default name of the output file is C<gene_descriptions.tsv> in the current directory.::
get_gene_info -genlist=WT_raw.tsv
:param: `-genlist` - Gene list, where first column contains gene names. Other columns are ignored. (default: `WT_raw.tsv`)
.. RNA_sample_details_tsvdoc:
.. _RNA_sample_details_tsvdoc:
======================
RNA_sample_details.tsv
======================
Details of the RNA samples used for the experiment. Includes Sample IDs,
Saccharomyces cerevisiae strain, concentrations and RNA QC measurements
.. Saccharomyces_cerevisiae_with_spike_ins_tsvdoc:
.. _Saccharomyces_cerevisiae_with_spike_ins_tsvdoc:
==================================================
Saccharomyces_cerevisiae_with_spike_ins.EF4.68.gtf
==================================================
`Ensembl <http://www.ensembl.org/index.html>`_ release 68 Saccharomyces
cerevisiae annotations with the 92 ERCC artificial spike-ins included
(`gtf format <http://www.ensembl.org/info/website/upload/gff.html>`_)
.. Saccharomyces_cerevisiae_tsvdoc:
.. _Saccharomyces_cerevisiae_tsvdoc:
===================================
Saccharomyces_cerevisiae.EF4.68.gtf
===================================
`Ensembl <http://www.ensembl.org/index.html>`_ release 68 Saccharomyces
cerevisiae annotations (`gtf format <http://www.ensembl.org/info/website/upload/gff.html>`_)
.. toctree::
:maxdepth: 1
| 27.731959 | 228 | 0.677323 |
1e4c991e2f5dd6f2cea4b5aa0c9d9c165aeccfd5 | 508 | rst | reStructuredText | source/java/ThrowingExceptionFailure.rst | Andilyn/learntosolveit | fd15345c74ef543e4e26f4691bf91cb6dac568a4 | [
"BSD-3-Clause"
] | 1 | 2021-04-09T04:15:24.000Z | 2021-04-09T04:15:24.000Z | source/java/ThrowingExceptionFailure.rst | Andilyn/learntosolveit | fd15345c74ef543e4e26f4691bf91cb6dac568a4 | [
"BSD-3-Clause"
] | null | null | null | source/java/ThrowingExceptionFailure.rst | Andilyn/learntosolveit | fd15345c74ef543e4e26f4691bf91cb6dac568a4 | [
"BSD-3-Clause"
] | 1 | 2021-07-31T02:45:29.000Z | 2021-07-31T02:45:29.000Z | ==========================
Throwing Exception Failure
==========================
Question
========
ADDQUESTION
Solution
========
.. literalinclude:: ../../languages/java/ThrowingExceptionFailure.java
:language: java
:tab-width: 4
.. runcode:: ../../languages/java/ThrowingExceptionFailure.java
:language: java
:codesite: ideone
Explanation
===========
.. seealso::
* :java-suggest-improve:`ThrowingExceptionFailure.java`
* :java-better-explain:`ThrowingExceptionFailure.rst`
| 14.514286 | 70 | 0.608268 |
723871463054091a0385712d106cab59ae251b81 | 313 | rst | reStructuredText | docs/vim/event/VmFailedRelayoutOnVmfs2DatastoreEvent.rst | nandonov/pyvmomi | ad9575859087177623f08b92c24132ac019fb6d9 | [
"Apache-2.0"
] | 12 | 2016-09-14T21:59:46.000Z | 2019-12-18T18:02:55.000Z | docs/vim/event/VmFailedRelayoutOnVmfs2DatastoreEvent.rst | nandonov/pyvmomi | ad9575859087177623f08b92c24132ac019fb6d9 | [
"Apache-2.0"
] | 2 | 2019-01-07T12:02:47.000Z | 2019-01-07T12:05:34.000Z | docs/vim/event/VmFailedRelayoutOnVmfs2DatastoreEvent.rst | nandonov/pyvmomi | ad9575859087177623f08b92c24132ac019fb6d9 | [
"Apache-2.0"
] | 8 | 2020-05-21T03:26:03.000Z | 2022-01-26T11:29:21.000Z | .. _vim.event.VmEvent: ../../vim/event/VmEvent.rst
vim.event.VmFailedRelayoutOnVmfs2DatastoreEvent
===============================================
This event records a failure to relay out a virtual machine when the virtual machine still has disks on a VMFS2 volume.
:extends: vim.event.VmEvent_
Attributes:
| 31.3 | 121 | 0.667732 |
326ec3391c4f6327046eb22a94c263d6e43d2787 | 177 | rst | reStructuredText | docs/source/board_app.rst | rainflame/pith-api | f3eb48d2d43aad8583d2732e71c1847e109d3708 | [
"Apache-2.0"
] | 4 | 2020-11-13T11:01:29.000Z | 2021-07-28T17:15:15.000Z | docs/source/board_app.rst | rainflame/pith-api | f3eb48d2d43aad8583d2732e71c1847e109d3708 | [
"Apache-2.0"
] | 67 | 2020-12-03T22:01:07.000Z | 2021-05-05T23:21:08.000Z | docs/source/board_app.rst | rainflame/pith-api | f3eb48d2d43aad8583d2732e71c1847e109d3708 | [
"Apache-2.0"
] | 1 | 2021-01-02T23:05:15.000Z | 2021-01-02T23:05:15.000Z | #####################################
Board Namespace
#####################################
.. automodule:: app
:members: create
:undoc-members:
:show-inheritance:
| 19.666667 | 37 | 0.378531 |
19703d3a376afc51e0e6f9c1ab3047bed91b1398 | 219 | rst | reStructuredText | docs/topics/contrib/index.rst | catalpainternational/rapidsms | eb7234d04ceb31e4d57187f2d6ba2806d0c54e15 | [
"BSD-3-Clause"
] | 330 | 2015-01-11T03:00:14.000Z | 2022-03-21T11:34:23.000Z | docs/topics/contrib/index.rst | catalpainternational/rapidsms | eb7234d04ceb31e4d57187f2d6ba2806d0c54e15 | [
"BSD-3-Clause"
] | 45 | 2015-01-06T16:14:19.000Z | 2022-03-16T13:12:53.000Z | docs/topics/contrib/index.rst | catalpainternational/rapidsms | eb7234d04ceb31e4d57187f2d6ba2806d0c54e15 | [
"BSD-3-Clause"
] | 166 | 2015-01-30T19:53:38.000Z | 2021-11-09T18:44:44.000Z | Contributed Applications
========================
RapidSMS comes with a number of contributed applications.
.. toctree::
default
echo
handlers
httptester
messagelog
messaging
registration
| 14.6 | 57 | 0.634703 |
39ed285078382492e92a7cab53437a5e8f565476 | 15,050 | rst | reStructuredText | docs/rasp_tutorial.rst | kellielu/ReAgent | c538992672220453cdc95044def25c4e0691a8b0 | [
"BSD-3-Clause"
] | 1,156 | 2019-10-02T12:15:31.000Z | 2022-03-31T16:01:27.000Z | docs/rasp_tutorial.rst | kellielu/ReAgent | c538992672220453cdc95044def25c4e0691a8b0 | [
"BSD-3-Clause"
] | 448 | 2019-10-03T13:40:52.000Z | 2022-03-28T07:49:15.000Z | docs/rasp_tutorial.rst | kellielu/ReAgent | c538992672220453cdc95044def25c4e0691a8b0 | [
"BSD-3-Clause"
] | 214 | 2019-10-13T13:28:33.000Z | 2022-03-24T04:11:52.000Z | .. _rasp_tutorial:
ReAgent Serving Platform (RASP)
===============================
Welcome to the ReAgent Serving Platform! This tutorial gets readers
familiar with reasoning at scale by building an artificial e-commerce
site.
What is RASP?
-------------
RASP is a set of scoring and ranking functions and a systematic way to
collect data and deploy models. A set of potential actions are input to
RASP and a ranked list of scores is output. The method for scoring and
ranking actions is called a decision plan. In this tutorial, we will
create several different decision plans and simulate user traffic to see
the results.
Installing ReAgent
------------------
Before beginning this tutorial, please install ReAgent by following
these instructions:
https://github.com/facebookresearch/ReAgent/blob/master/docs/installation.rst
Store set-up
------------
For this tutorial, we will be in charge of recommendations for
Pig-E-Barbeque, a pork e-store. Pig-E-Barbeque sells two products: Ribs
and Bacon. Our product manager has told us to optimize for clicks. Since
we are just starting out, we don’t know anything about our visitors, but
we know that bacon is delicious. We give bacon a score of 1.1 and ribs a
score of 1.0. (If we were optimizing for revenue, we could set the score
to the price, or we could have a custom scoring function.)
We also need to provide a ranking function that takes our scores and
decides which items to recommend. In Pig-E-Barbeque, we only have one
spot for recommendations, so the first item will be shown to visitors
and the second choice is discarded. If we use a greedy ranking function,
we will always show bacon (with it’s score of 1.1) and never show ribs
(with a score of 0.9). This means we will never know the true
performance of recommending ribs and can’t improve our system in the
future. This is known as the cold-start or explore-exploit problem
( https://arxiv.org/abs/1812.00116 ).
To avoid that problem, we will use the SoftmaxRanker, which will show
bacon 52% of the time and ribs 48% of the time. The SoftmaxRanker
operator is based on the softmax function:
::
>>> import numpy as np
>>>
>>> def softmax(x):
... e_x = np.exp(x - np.max(x))
... return e_x / e_x.sum()
...
>>> print(softmax([1.1, 1.0]))
[0.52497919 0.47502081]
Here is the decision plan generator:
::
def softmaxranker_decision_plan():
op = SoftmaxRanker(temperature=1.0, values={"Bacon": 1.1, "Ribs": 1.0})
return DecisionPlanBuilder().set_root(op).build()
And here is the generated decision plan:
::
{
"operators": [
{
"name": "SoftmaxRanker_1",
"op_name": "SoftmaxRanker",
"input_dep_map": {
"temperature": "constant_2",
"values": "constant_3"
}
}
],
"constants": [
{
"name": "constant_2",
"value": {
"double_value": 1.0
}
},
{
"name": "constant_3",
"value": {
"map_double_value": {
"Bacon": 1.1,
"Ribs": 1.0
}
}
}
],
"num_actions_to_choose": 1,
"reward_function": "reward",
"reward_aggregator": "sum"
}
User simulator
--------------
Because this isn’t a real store, we need a way to simulate users. Our
simulator has a few rules:
1. Visitors click on bacon recommendations 50% of the time
2. 10% of visits are by rib lovers and the rest are regular visitors
1. Rib lovers click on rib recommendations 90% of the time
2. Regular visitors click on rib recommendations 10%
We will be using the built-in web service directly for this tutorial.
The simulator code can be found at:
serving/examples/ecommerce/customer_simulator.py
Makin’ bacon
------------
In one terminal window, start the RP server:
::
➜ ./serving/build/RaspCli --logtostderr
I1014 17:23:19.736086 457250240 DiskConfigProvider.cpp:10] READING CONFIGS FROM serving/examples/ecommerce/plans
I1014 17:23:19.738142 457250240 DiskConfigProvider.cpp:42] GOT CONFIG multi_armed_bandit.json AT serving/examples/ecommerce/plans/multi_armed_bandit.json
I1014 17:23:19.738286 457250240 DiskConfigProvider.cpp:46] Registered decision config: multi_armed_bandit.json
I1014 17:23:19.738932 457250240 DiskConfigProvider.cpp:42] GOT CONFIG contextual_bandit.json AT serving/examples/ecommerce/plans/contextual_bandit.json
I1014 17:23:19.739020 457250240 DiskConfigProvider.cpp:46] Registered decision config: contextual_bandit.json
I1014 17:23:19.739610 457250240 DiskConfigProvider.cpp:42] GOT CONFIG heuristic.json AT serving/examples/ecommerce/plans/heuristic.json
I1014 17:23:19.739682 457250240 DiskConfigProvider.cpp:46] Registered decision config: heuristic.json
I1014 17:23:19.739843 131715072 Server.cpp:58] STARTING SERVER
Then in another, run our simulator. The simulator will spawn many
threads and call RASP 1,000 times:
::
➜ python serving/examples/ecommerce/customer_simulator.py heuristic.json
0
200
100
400
300
500
600
700
800
900
Average reward: 0.363
Action Distribution: {'Ribs': 471, 'Bacon': 529}
As expected, we recommend Bacon 52% of the time and Ribs 48% of the
time. We get an average reward (in this case, average # of clicks) of about 0.36.
This is our baseline performance, but can we do better? From the log, we
can see that more bacon recommendations were clicked on:
::
➜ cat /tmp/rasp_logging/log.txt | grep '"name":"Ribs"}]' | grep '"reward":0.0' | wc -l
390 # Ribs not clicked
➜ cat /tmp/rasp_logging/log.txt | grep '"name":"Ribs"}]' | grep '"reward":1.0' | wc -l
88 # Ribs clicked
➜ cat /tmp/rasp_logging/log.txt | grep '"name":"Bacon"}]' | grep '"reward":1.0' | wc -l
266 # Bacon clicked
➜ cat /tmp/rasp_logging/log.txt | grep '"name":"Bacon"}]' | grep '"reward":0.0' | wc -l
253 # Bacon not clicked
This makes sense since, from our simulator definition, most people
aren’t rib-lovers and only click on ribs 10% of the time. We can change
the decision plan to use a multi-armed bandit that will learn to show
bacon much more often. For this tutorial, we will use the UCB1 bandit
ranker. Passing this to the plan generator:
::
def ucb_decision_plan():
op = UCB(method="UCB1", batch_size=16)
return DecisionPlanBuilder().set_root(op).build()
Generates this plan:
::
➜ cat serving/examples/ecommerce/plans/multi_armed_bandit.json
{
"operators": [
{
"name": "UCB_1",
"op_name": "Ucb",
"input_dep_map": {
"method": "constant_2",
"batch_size": "constant_3"
}
}
],
"constants": [
{
"name": "constant_2",
"value": {
"string_value": "UCB1"
}
},
{
"name": "constant_3",
"value": {
"int_value": 16
}
}
],
"num_actions_to_choose": 1,
"reward_function": "reward",
"reward_aggregator": "sum"
}
Running with this new plan gives:
::
➜ python serving/examples/ecommerce/customer_simulator.py multi_armed_bandit.json
0
200
100
400
300
500
600
700
800
900
Average reward: 0.447
Action Distribution: {'Ribs': 184, 'Bacon': 816}
This is already better than our previous score of 0.363. While we were
running, the bandit was learning and adapting the scores. Let’s run
again:
::
➜ python serving/examples/ecommerce/customer_simulator.py multi_armed_bandit.json
0
200
100
400
300
500
600
700
800
900
Average reward: 0.497
Action Distribution: {'Bacon': 926, 'Ribs': 74}
So the new ranker chooses bacon more often and gets more reward on
average than our first plan. If we keep running, eventually the model
will stop exploring the Ribs action and the average reward will approach
50% (which is the chance of a reward that we set in our simulator).
Straight Outta Context
----------------------
While running the store, our data scientist has discovered a way to
figure out who is a rib-lover. Now we can pass a context feature which
is 1 when the visitor is a rib lover and 0 otherwise. In this section we
will train a contextual bandit that learns to show ribs to rib lovers
and bacon to everyone else.
As we specified in our config, RP has been writing a log of visits and
feedback to a file. We can input this file with a training config to
ReAgent to train a contextual bandit model. First, let’s clear our
training data and start over by sending a SIGINT (control-c) to our
instance of RaspCli:
::
…
I1014 17:45:36.613893 6602752 Server.cpp:58] STARTING SERVER
^C
➜ rm /tmp/rasp_logging/log.txt
➜ ./serving/build/RaspCli --logtostderr
I1014 17:48:49.674149 144418240 DiskConfigProvider.cpp:10] READING CONFIGS FROM serving/examples/ecommerce/plans
I1014 17:48:49.678155 144418240 DiskConfigProvider.cpp:42] GOT CONFIG multi_armed_bandit.json AT serving/examples/ecommerce/plans/multi_armed_bandit.json
I1014 17:48:49.679606 144418240 DiskConfigProvider.cpp:46] Registered decision config: multi_armed_bandit.json
I1014 17:48:49.680496 144418240 DiskConfigProvider.cpp:42] GOT CONFIG contextual_bandit.json AT serving/examples/ecommerce/plans/contextual_bandit.json
I1014 17:48:49.680778 144418240 DiskConfigProvider.cpp:46] Registered decision config: contextual_bandit.json
I1014 17:48:49.682201 144418240 DiskConfigProvider.cpp:42] GOT CONFIG heuristic.json AT serving/examples/ecommerce/plans/heuristic.json
I1014 17:48:49.682344 144418240 DiskConfigProvider.cpp:46] Registered decision config: heuristic.json
I1014 17:48:49.682667 65638400 Server.cpp:58] STARTING SERVER
Now let’s run the heuristic model a few times to generate enough data
(this may take a few minutes). At the end there should be 10000 samples
(we can verify this with the wc command):
::
➜ for run in {1..10}; do python serving/examples/ecommerce/customer_simulator.py heuristic.json; done
0
200
...
900
Average reward: 0.36
Action Distribution: {'Bacon': 516, 'Ribs': 484}
➜ wc -l /tmp/rasp_logging/log.txt
10000 /tmp/rasp_logging/log.txt
RASP’s logging format and the ReAgent models’ input format is slightly
different. Fortunately, there’s a tool to convert from one to the other:
::
➜ python serving/scripts/rasp_to_model.py /tmp/rasp_logging/log.txt /tmp/input_df.pkl
...
INFO:__main__: ds mdp_id sequence_number state_features action reward action_probability possible_actions metrics
0 2019-01-01 1287515757457242569 0 {0: 0.0, 1: 1.0} Ribs 0.0 0.475021 [Bacon, Ribs] {'reward': 0.0}
1 2019-01-01 -1441171268272508658 0 {0: 0.0, 1: 1.0} Ribs 0.0 0.475021 [Bacon, Ribs] {'reward': 0.0}
2 2019-01-01 -267723109738500267 0 {0: 0.0, 1: 1.0} Bacon 1.0 0.524979 [Bacon, Ribs] {'reward': 1.0}
3 2019-01-01 7619952535038766490 0 {0: 0.0, 1: 1.0} Ribs 0.0 0.475021 [Bacon, Ribs] {'reward': 0.0}
4 2019-01-01 -2393212434904546228 0 {0: 0.0, 1: 1.0} Bacon 0.0 0.524979 [Bacon, Ribs] {'reward': 0.0}
Since we are using the contextual bandit or RL model, we need to build a
timeline:
::
# Set the config
➜ export CONFIG=serving/examples/ecommerce/training/contextual_bandit.yaml
# First clean up derby database from last run
➜ rm -Rf spark-warehouse derby.log metastore_db preprocessing/spark-warehouse preprocessing/metastore_db preprocessing/derby.log
# Run timeline operator
➜ ./reagent/workflow/cli.py run reagent.workflow.gym_batch_rl.timeline_operator "$CONFIG"
The `Click <https://click.palletsprojects.com/en/7.x/>`_ command submits a Spark job that uploads the timeline table to Hive.
Now we can train the contextual bandit.
::
➜ ./reagent/workflow/cli.py run reagent.workflow.training.identify_and_train_network "$CONFIG"
...
I0524 112136.208 model_manager.py:213] Saved torchscript model to model_1590344496.torchscript
At this point, we have a model saved at ``model_*.torchscript``. We
are going to combine this scoring model with an Softmax ranker. The
ranker chooses the best actions most of the time, but rarely
chooses other actions to explore:
::
{
"operators": [
{
"name": "ActionValueScoringOp",
"op_name": "ActionValueScoring",
"input_dep_map": {
"model_id": "model_id",
"snapshot_id": "snapshot_id"
}
},
{
"name": "SoftmaxRankerOp",
"op_name": "SoftmaxRanker",
"input_dep_map": {
"temperature": "constant_2",
"values": "ActionValueScoringOp"
}
}
],
"constants": [
{
"name": "model_id",
"value": {
"int_value": 0
}
},
{
"name": "snapshot_id",
"value": {
"int_value": 0
}
},
{
"name": "constant_2",
"value": {
"double_value": 0.001
}
}
],
"num_actions_to_choose": 1,
"reward_function": "reward",
"reward_aggregator": "sum"
}
The “model_id” and “snapshot_id” tell us where to find the model. Let’s
put the model there so we can find it:
::
➜ mkdir -p /tmp/0
➜ cp model_*.torchscript /tmp/0/0
Let’s run with our model:
::
➜ python serving/examples/ecommerce/customer_simulator.py contextual_bandit.json
0
200
100
400
300
500
600
700
800
900
Average reward: 0.52
Action Distribution: {'Bacon': 883, 'Ribs': 117}
Nice! We have a reward higher than 50%, which is the click-through-rate
for bacon. This means that we must be getting most of the rib lovers. In
case you were curious, the best possible score is (0.9*0.5 + 0.1*\ 0.9)
== 0.54. We still have some exploration in our new plan so we won’t get
exactly 0.54 even with many iterations, but we need that exploration to
generate an even better model next time when we learn more about our
customers.
All of the decisions made so far have been pointwise: we don’t consider
repeat visitors. ReAgent can also optimize for long-term value in
sequential decisions using reinforcement learning, but that is out of
the scope of this starting tutorial.
| 34.126984 | 156 | 0.650365 |
75478478802d9822c67d5cad59288389fd15e250 | 5,840 | rst | reStructuredText | docs/launch-with/launch.rst | dockstore/dockstore-documentation | baf08b1920a696289aedb3b0aa93082cbd500f17 | [
"Apache-2.0"
] | 2 | 2020-11-11T00:28:12.000Z | 2021-01-05T18:16:21.000Z | docs/launch-with/launch.rst | dockstore/dockstore-documentation | baf08b1920a696289aedb3b0aa93082cbd500f17 | [
"Apache-2.0"
] | 92 | 2019-08-09T18:25:05.000Z | 2022-03-31T18:25:20.000Z | docs/launch-with/launch.rst | dockstore/dockstore-documentation | baf08b1920a696289aedb3b0aa93082cbd500f17 | [
"Apache-2.0"
] | 7 | 2019-09-17T13:21:21.000Z | 2021-02-12T18:08:54.000Z | Launching Tools and Workflows
=============================
Tutorial Goals
--------------
- Launch a tool and a workflow using the Dockstore CLI
.. _launch-dockstore-cli:
Dockstore CLI
-------------
The dockstore command-line includes basic tool and workflow launching
capability built on top of
`cwltool <https://github.com/common-workflow-language/cwltool>`__. The
Dockstore command-line also includes support for file provisioning via
`plugins <https://github.com/dockstore/dockstore-cli/tree/master/dockstore-file-plugin-parent>`__
which allow for the reading of input files and the upload of output
files from remote file systems. Support for HTTP and HTTPS is built-in.
Support for AWS S3 and `ICGC Score
client <https://github.com/dockstore/icgc-storage-client-plugin>`__ is
provided via plugins installed by default.
Launch Tools
~~~~~~~~~~~~
If you have followed the tutorial, you will have a tool registered on
Dockstore. You may want to test it out for your own work. For now you
can use the Dockstore command-line interface (CLI) to run several useful
commands:
1. create an empty "stub" JSON config file for entries in the Dockstore
``dockstore tool convert``
2. launch a tool locally ``dockstore tool launch``
3. automatically copy inputs from remote URLs if HTTP, FTP, S3 or other
remote URLs are specified
4. call the ``cwltool`` command line to execute your tool using the CWL
from the Dockstore and the JSON for inputs/outputs
5. if outputs are specified as remote URLs, copy the results to these
locations
6. download tool descriptor files ``dockstore tool cwl`` and
``dockstore tool wdl``
Note that launching a CWL tool locally requires the cwltool to be
installed. Check `onboarding <https://dockstore.org/onboarding>`__ if
you have not already to ensure that your dependencies are correct.
An example of launching a tool, in this case a bamstats sample tool
follows:
::
# make a runtime JSON template and fill in desired inputs, outputs, and other parameters
$ dockstore tool convert entry2json --entry quay.io/collaboratory/dockstore-tool-bamstats:1.25-6_1.0 > Dockstore.json
$ vim Dockstore.json
# note that the empty JSON config file has been filled with an input file retrieved via http
$ cat Dockstore.json
{
"mem_gb": 4,
"bam_input": {
"path": "https://github.com/CancerCollaboratory/dockstore-tool-bamstats/raw/develop/rna.SRR948778.bam",
"format": "http://edamontology.org/format_2572",
"class": "File"
},
"bamstats_report": {
"path": "/tmp/bamstats_report.zip",
"class": "File"
}
}
# run it locally with the Dockstore CLI
$ dockstore tool launch --entry quay.io/collaboratory/dockstore-tool-bamstats:1.25-6_1.0 --json Dockstore.json
This information is also provided in the "Launch With" section of every
tool.
Launch Workflows
~~~~~~~~~~~~~~~~
Launching CWL and WDL Workflows
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
A parallel set of commands is available for workflows. ``convert``,
``wdl``, ``cwl``, and ``launch`` are all available under the
``dockstore workflow`` mode.
While launching tools and workflows locally is useful for testing, this
approach is not useful for processing a large amount of data in a
production environment. The next step is to take our Docker images,
described by CWL/WDL and run them in an environment that supports those
descriptors. For now, we can suggest taking a look at the environments
that currently support and are validated with CWL at
https://www.commonwl.org/#Implementations and for WDL,
`Cromwell <https://github.com/broadinstitute/cromwell>`__.
For developers, you may also wish to look at our brief summary at :doc:`batch
services </advanced-topics/batch-services>` and commercial solutions such as `DataBiosphere
dsub <https://github.com/DataBiosphere/dsub>`__ and
`AWS Batch <https://aws.amazon.com/batch/>`__.
Launching Nextflow Workflows
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Currently the Dockstore CLI does not support integration with the
Nextflow CLI. However, the Nextflow CLI offers many of the same benefits
as the Dockstore CLI.
All non-hosted workflows in Dockstore are associated with a Git
repository from GitHub, BitBucket, or GitLab. With the Nextflow CLI we
can launch a Dockstore workflow by using this Git repository information
through `pipeline
sharing <https://www.nextflow.io/docs/latest/sharing.html#pipeline-sharing>`__.
Say we have the workflow ``organization/my-workflow``. To launch, we
would run the following commands based on the code repository that the
workflow is stored on. See the link above for more advanced usage.
::
# Run workflow from GitHub (--hub github is optional)
nextflow run organization/my-workflow --hub github
# Run workflow from BitBucket
nextflow run organization/my-workflow --hub bitbucket
# Run workflow from GitLab
nextflow run organization/my-workflow --hub gitlab
Next Steps
----------
We also recommend looking at the best practices guide before creating
your first real tool/workflow. There are three descriptor languages
available on Dockstore. Follow the links for the language that you are
interested in.
- :doc:`Best practices for CWL <../advanced-topics/best-practices/cwl-best-practices>`
- :doc:`Best practices for WDL <../advanced-topics/best-practices/wdl-best-practices/>`
- :doc:`Best practices for Nextflow <../advanced-topics/best-practices/nfl-best-practices/>`
See Also
--------
- :doc:`AWS Batch <../advanced-topics/aws-batch/>`
- :doc:`Azure Batch <../advanced-topics/azure-batch/>`
- :doc:`CGC Launch With <../launch-with/cgc-launch-with/>`
- :doc:`DNAstack Launch With <../launch-with/dnastack-launch-with/>`
- :doc:`Terra Launch With <../launch-with/terra-launch-with/>`
.. discourse::
:topic_identifier: 1275
| 38.421053 | 121 | 0.734589 |
d2090e52a04c0dd572b2c132ce8de653031ce167 | 1,422 | rst | reStructuredText | source/c13/p14_putting_limits_on_memory_and_cpu_usage.rst | Xiao-jiuguan/python3-cookbook | 95d5a1d5cb59b5d88e816f6f10eb1e5befc25b05 | [
"Apache-2.0"
] | 3 | 2018-05-10T01:13:08.000Z | 2018-06-17T12:34:07.000Z | source/c13/p14_putting_limits_on_memory_and_cpu_usage.rst | Xiao-jiuguan/python3-cookbook | 95d5a1d5cb59b5d88e816f6f10eb1e5befc25b05 | [
"Apache-2.0"
] | 2 | 2020-09-19T17:10:23.000Z | 2020-10-17T16:43:52.000Z | source/c13/p14_putting_limits_on_memory_and_cpu_usage.rst | Xiao-jiuguan/python3-cookbook | 95d5a1d5cb59b5d88e816f6f10eb1e5befc25b05 | [
"Apache-2.0"
] | 1 | 2020-07-20T22:10:31.000Z | 2020-07-20T22:10:31.000Z | ==============================
13.14 限制内存和CPU的使用量
==============================
----------
问题
----------
你想对在Unix系统上面运行的程序设置内存或CPU的使用限制。
----------
解决方案
----------
``resource`` 模块能同时执行这两个任务。例如，要限制CPU时间，可以像下面这样做：
.. code-block:: python
import signal
import resource
import os
def time_exceeded(signo, frame):
print("Time's up!")
raise SystemExit(1)
def set_max_runtime(seconds):
# Install the signal handler and set a resource limit
soft, hard = resource.getrlimit(resource.RLIMIT_CPU)
resource.setrlimit(resource.RLIMIT_CPU, (seconds, hard))
signal.signal(signal.SIGXCPU, time_exceeded)
if __name__ == '__main__':
set_max_runtime(15)
while True:
pass
程序运行时，``SIGXCPU`` 信号在时间过期时被生成，然后执行清理并退出。
要限制内存使用，设置可使用的总内存值即可，如下：
.. code-block:: python
import resource
def limit_memory(maxsize):
soft, hard = resource.getrlimit(resource.RLIMIT_AS)
resource.setrlimit(resource.RLIMIT_AS, (maxsize, hard))
像这样设置了内存限制后，程序运行到没有多余内存时会抛出 ``MemoryError`` 异常。
----------
讨论
----------
在本节例子中，``setrlimit()`` 函数被用来设置特定资源上面的软限制和硬限制。
软限制是一个值，当超过这个值的时候操作系统通常会发送一个信号来限制或通知该进程。
硬限制是用来指定软限制能设定的最大值。通常来讲，这个由系统管理员通过设置系统级参数来决定。
尽管硬限制可以改小一点，但是最好不要使用用户进程去修改。
``setrlimit()`` 函数还能被用来设置子进程数量、打开文件数以及类似系统资源的限制。
更多详情请参考 ``resource`` 模块的文档。
需要注意的是本节内容只能适用于Unix系统，并且不保证所有系统都能如期工作。
比如我们在测试的时候，它能在Linux上面正常运行，但是在OS X上却不能。
| 22.571429 | 64 | 0.660338 |
a374c255b0913df8a4c2dc70bf7d865eac83a4cb | 481 | rst | reStructuredText | doc/Changelog/9.2/Feature-83942-ProvideViewHelperToRenderIconForResources.rst | DanielSiepmann/typo3scan | 630efc8ea9c7bd86c4b9192c91b795fff5d3b8dc | [
"MIT"
] | 1 | 2019-10-04T23:58:04.000Z | 2019-10-04T23:58:04.000Z | doc/Changelog/9.2/Feature-83942-ProvideViewHelperToRenderIconForResources.rst | DanielSiepmann/typo3scan | 630efc8ea9c7bd86c4b9192c91b795fff5d3b8dc | [
"MIT"
] | 1 | 2021-12-17T10:58:59.000Z | 2021-12-17T10:58:59.000Z | doc/Changelog/9.2/Feature-83942-ProvideViewHelperToRenderIconForResources.rst | DanielSiepmann/typo3scan | 630efc8ea9c7bd86c4b9192c91b795fff5d3b8dc | [
"MIT"
] | 4 | 2020-10-06T08:18:55.000Z | 2022-03-17T11:14:09.000Z | .. include:: ../../Includes.txt
=================================================================
Feature: #83942 - Provide ViewHelper to render icon for resources
=================================================================
See :issue:`83942`
Description
===========
A new ViewHelper to render the icon markup based on a FAL resource has been introduced.
Example:
.. code-block:: html
<core:iconForResource resource="{file}" />
.. index:: Backend, Fluid, ext:core
| 22.904762 | 87 | 0.50104 |
60fec389ec60033983ed4eeb47881c276185ed3e | 5,423 | rst | reStructuredText | docs/index.rst | rdevaul/yapCAD | 2250a3b1332283384f51f4fb9398feb5dd4dd544 | [
"MIT"
] | 18 | 2020-12-14T17:17:59.000Z | 2021-09-26T22:01:13.000Z | docs/index.rst | rdevaul/yapCAD | 2250a3b1332283384f51f4fb9398feb5dd4dd544 | [
"MIT"
] | null | null | null | docs/index.rst | rdevaul/yapCAD | 2250a3b1332283384f51f4fb9398feb5dd4dd544 | [
"MIT"
] | 1 | 2020-12-14T21:47:11.000Z | 2020-12-14T21:47:11.000Z | ======
yapCAD
======
Welcome to **yapCAD**, yet another procedural CAD and computational
geometry system, written in Python_. This project is still in a
pretty early state, though we hope you will find it useful.
.. note::
**yapCAD** was created to solve some fairly specific problems in
procedural CAD and `parametric design`_ , and at present is most
developed for generating 2D drawings in the `AutoCad DXF`_ format.
If you don't know what procedural CAD or paramaterized design
might be useful for, this may not be the tool for you.
On the other hand, if you are tired of manually editing your CAD
files whenever you change the thickness of a material, the size of
a pipe fitting, or the diameter and spacing of bolts, *etc.*, this
might just be the tool you are looking for.
For an example and discussion of what parametric design is and why
it might be useful see `What is Parametric Design?`_ below.
Much of the documentation for **yapCAD** can be found in the
**README** files, as well as in the ``yapcad.geom`` module
documentation linked below.
Contents
========
.. toctree::
:maxdepth: 4
License <license>
Authors <authors>
Changelog <changelog>
Module Reference <api/modules>
README <README>
Indices and tables
==================
* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`
What is Parametric Design?
==========================
`Parametric design`_ is a generalizable approach to solving design
problems by means of parameters and algorithms, as opposed to the
creation of static drawings or models. Put another way, a
conventional design is like a drawing, and a parametric design is like
a piece of software that you configure to create the specific drawing
that you want.
the acrylic box: a parametric design example
--------------------------------------------
For example, imagine that you wanted to design a decorative acrylic
box to be assembled from pieces cut from a sheet of material of
uniform thickness. This box will be a squeeze-fit design, so that it
assembles like a 3D jigsaw puzzle, without the need for additional
glue or fasteners.
.. image:: images/laserbox.jpg
:alt: picture of a laser-cut acrylic box, squeeze-fit design
:width: 221px
You might decide on the dimensions of your box, and a scheme by which
you cut the edges to create tabs and slots so that when cut, the box
will fit together just so. However, the depth of your tabs and slots
will necessarily depend on the thickness of the material, which might
vary slightly from sheet to sheet, or vendor to vendor. Furthermore,
your cutting tool (perhaps a laser cutter) will create a kerf, or
width of cut, that vary from machine to machine and with depth of
focus.
Finally, your box might be sized to hold a variety of contents, which
themselves might vary in size and shape.
One approach is to create a conventional design. You could draw your
design for one size of box, material, and thickness of cut, and then
hope you have your tolerances correct. If there is a problem, or you
want to change box dimensions, you will need to go back and revise
your design. Each time you revise, you are essentially redoing the
entire drawing from scratch.
Alternately, you could create a parametric design, in which the
desired length, width, and height of the box are input parameters,
along with the thickness of the material and an estimate of the kerf.
Creating a parametric design system might be a bit more difficult than
creating a conventional drawing, but once you are done you will be
able to generate the design for any desired box, from any desired
material thickness, with any kerf, simply by changing a few numbers --
automatically, and without having to revise any code or drawing.
.. note::
For a **yapCAD** solution to this particular problem, see the
``boxcut`` example in the ``examples`` directory
This ability to solve for an entire family of related design problems
with a single parametric design system is what gives this approach
it's power and flexibility. For anyone who has spent hours
re-drafting a drawing to accommodate minor variations in requirements,
this can be an impressive force multiplier on productivity.
.. _AutoCad DXF: https://en.wikipedia.org/wiki/AutoCAD_DXF
.. _parametric design: https://en.wikipedia.org/wiki/Parametric_design
.. _module reference: ./api/modules
.. _toctree: http://www.sphinx-doc.org/en/master/usage/restructuredtext/directives.html
.. _reStructuredText: http://www.sphinx-doc.org/en/master/usage/restructuredtext/basics.html
.. _references: http://www.sphinx-doc.org/en/stable/markup/inline.html
.. _Python domain syntax: http://sphinx-doc.org/domains.html#the-python-domain
.. _Sphinx: http://www.sphinx-doc.org/
.. _Python: http://docs.python.org/
.. _Numpy: http://docs.scipy.org/doc/numpy
.. _SciPy: http://docs.scipy.org/doc/scipy/reference/
.. _matplotlib: https://matplotlib.org/contents.html#
.. _Pandas: http://pandas.pydata.org/pandas-docs/stable
.. _Scikit-Learn: http://scikit-learn.org/stable
.. _autodoc: http://www.sphinx-doc.org/en/stable/ext/autodoc.html
.. _Google style: https://github.com/google/styleguide/blob/gh-pages/pyguide.md#38-comments-and-docstrings
.. _NumPy style: https://numpydoc.readthedocs.io/en/latest/format.html
.. _classical style: http://www.sphinx-doc.org/en/stable/domains.html#info-field-lists
| 41.715385 | 106 | 0.747557 |
83333adecdbe48710dcdfe9da6b05d4ef72afde6 | 1,883 | rst | reStructuredText | exotica/doc/own_robot.rst | maxspahn/exotica | f748a5860939b870ab522a1bd553d2fa0da56f8e | [
"BSD-3-Clause"
] | 130 | 2018-03-12T11:00:55.000Z | 2022-02-21T02:41:28.000Z | exotica/doc/own_robot.rst | maxspahn/exotica | f748a5860939b870ab522a1bd553d2fa0da56f8e | [
"BSD-3-Clause"
] | 349 | 2017-09-14T00:42:33.000Z | 2022-03-29T13:51:04.000Z | exotica/doc/own_robot.rst | maxspahn/exotica | f748a5860939b870ab522a1bd553d2fa0da56f8e | [
"BSD-3-Clause"
] | 48 | 2017-10-04T15:50:42.000Z | 2022-02-10T05:03:39.000Z | *********************************************
Creating a planner package for your own robot
*********************************************
To start using EXOTica with a new robot we require the configuration files
for your robot and some changes to the ROS package that you will be using.
URDF File
=========
EXOTica extracts the dimensions and details of the robot from the robot's
URDF configuration file. To start generating motion plans for your own robot,
a URDF file is required.
The URDF file for the `lwr\_simplified <https://github.com/ipab-slmc/exotica/blob/master/exotica_examples/resources/robots/lwr_simplified.urdf>`_
KUKA arm included in the EXOTica examples file will be used throughout these tutorials.
SRDF File
=========
In addition to the URDF file, an SRDF file is also required. This
contains semantic information about the robot extracted from the URDF.
EXOTica extracts joint dimensions, limits, DH parameters and self
collision matrices from the SRDF file. Follow the `MoveIt! setup
assistant <http://docs.ros.org/hydro/api/moveit_setup_assistant/html/doc/tutorial.html>`__ tutorial to generate an SRDF file. The SRDF file for the
`lwr\_simplified <https://github.com/ipab-slmc/exotica/blob/master/exotica_examples/resources/robots/lwr_simplified.srdf>`__
KUKA arm included in the source files will be used throughout these
tutorials.
CMakeLists.txt & package.xml
============================
Add the following lines to the CMakeLists.txt file of any package that uses EXOTica.
In the ``find_package(catkin REQUIRED COMPONENTS)`` section,
add
.. code-block:: cmake
find_package(catkin REQUIRED COMPONENTS exotica_core)
Also, add the following to ``package.xml`` for a c++ package:
.. code-block:: xml
<depend>exotica_core</depend>
or the following for a python package:
.. code-block:: xml
<depend>exotica_python</depend>
| 35.528302 | 147 | 0.728093 |
4d94956e8e2cda03ff5581e60659ed568665cf60 | 1,507 | rst | reStructuredText | docs/source/usage/modules.rst | morgenst/PyAnalysisTools | f3b1f89870e7bbae1549c228a56d2c36bbba7af3 | [
"MIT"
] | null | null | null | docs/source/usage/modules.rst | morgenst/PyAnalysisTools | f3b1f89870e7bbae1549c228a56d2c36bbba7af3 | [
"MIT"
] | null | null | null | docs/source/usage/modules.rst | morgenst/PyAnalysisTools | f3b1f89870e7bbae1549c228a56d2c36bbba7af3 | [
"MIT"
] | null | null | null | Modules
=======
Several modules are provided
Core modules
------------
The base module contains the core functionality used as underlying structure for all analysis tools. It provides basic
interfaces for reading and writing data in different formats (root files, yaml, json), logging, batch job handling and
others.
Plotting tools
--------------
Anything which is related to plotting starting from making histograms towards style tuning are provided in the plotting
"PlottingTools" module. The core is implemented in BasePlotter.py which provides the basic interface.
In the context of plotting each object which can be plotted, e.g. histograms (TH1, TH2), graphs (TGraph), profiles, etc.
is typically referred to as *plotable object* (a dedicated generic implementation is currently worked on).
The actual plotting is done via the Plotter class in Plotter.py. There are several dedicated plotting algorithms provided:
* ComparisonPlotter.py: Compare distributions from different sources
* EventComparisionPlotter.py: Plot event-by-event comparisons
* RatioPlotter.py: Plots ratios and adds them to canvases
* CorrelationPlotter.py: Plots correlations
Basic wrappers to manipulate
AnalysisTools
--------------
The AnalysisTools modules contains a variety of tools used in typical HEP data analysis projects. This included background
estimation tools, selection tools, fitting procedures and ML tools. A brief overview is given below and dedicated examples
are given in **this has to be done** | 38.641026 | 122 | 0.78633 |
98c242b3bb2a8d8c351713250beefa7cab7731cc | 646 | rst | reStructuredText | doc/demo/index.rst | wanchangyan/tqsdk-python | ff935ee89c35cfe1f69da1bc981e21a6e1a7e21c | [
"Apache-2.0"
] | 1 | 2019-06-21T02:57:45.000Z | 2019-06-21T02:57:45.000Z | doc/demo/index.rst | wanchangyan/tqsdk-python | ff935ee89c35cfe1f69da1bc981e21a6e1a7e21c | [
"Apache-2.0"
] | null | null | null | doc/demo/index.rst | wanchangyan/tqsdk-python | ff935ee89c35cfe1f69da1bc981e21a6e1a7e21c | [
"Apache-2.0"
] | 1 | 2019-05-28T02:13:52.000Z | 2019-05-28T02:13:52.000Z | .. _demo:
示例程序
====================================================
基本使用
--------------------------------------------------------------------------------------------------------
.. toctree::
:maxdepth: 1
tutorial/t10.rst
tutorial/t20.rst
tutorial/t30.rst
tutorial/t40.rst
tutorial/t60.rst
tutorial/t70.rst
tutorial/t71.rst
tutorial/t80.rst
交易策略
--------------------------------------------------------------------------------------------------------
.. toctree::
:maxdepth: 1
example/gridtrading.rst
example/turtle.rst
example/dualthrust.rst
example/rbreaker.rst
example/vwap.rst
| 20.83871 | 104 | 0.386997 |
c2f721f6726e7ade80fe02660bee24b5fc81aa30 | 8,445 | rst | reStructuredText | docs/source/Documentation/5_LLVMTransformations/Opt/3_ListOfOptimizations.rst | DecomPy/DecomPy | 2e11956e07143ed4b9b4c6335e61a6da75fcdddd | [
"BSD-3-Clause"
] | 7 | 2018-10-18T00:42:35.000Z | 2021-03-10T21:50:15.000Z | docs/source/Documentation/5_LLVMTransformations/Opt/3_ListOfOptimizations.rst | DecomPy/DecomPy | 2e11956e07143ed4b9b4c6335e61a6da75fcdddd | [
"BSD-3-Clause"
] | 22 | 2018-10-23T00:47:49.000Z | 2019-08-24T04:25:07.000Z | docs/source/Documentation/5_LLVMTransformations/Opt/3_ListOfOptimizations.rst | DecomPy/DecomPy | 2e11956e07143ed4b9b4c6335e61a6da75fcdddd | [
"BSD-3-Clause"
] | null | null | null | List of Optimizations
*********************
Transform Passes
----------------
LLVM Transformation Passes actually change the code. It is possible, even though these passes are meant to
optimize code, that these passes may make the code more readable and facilitate swaps that will deoptimize the code.
Because of this, we will be filtering out any of LLVM's passes which only make the code worse. The decompiler will
learn which optimizations lead to improvement.
All of the LLVM passes are intended to optimize the code, which usually makes it less readable. However, the RL Agent
may be able to combine these passes, and the snippet swaps, in unforeseen ways, leading to more readable code.
Because of this, the passes that we won't be using are only those that we know will make things much more complex.
Detailed descriptions of the following passes can be found at: https://llvm.org/docs/Passes.html#transform-passes
In the following documentation, we will outline which passes we will be using and why, and which passes we won't be
using and why. We will also describe the order that passes must be run in. Some passes might require being run in a
particular order. While it is possible that the RL agent may learn this ordering on its own, it would be helpful to
figure out the required passes ourselves.
Passes We Will Use:
-------------------
This section has been split into four parts: Opt passes that are **independent** (they do not require other passes
to run before them), passes that are **dependent**, passes that are **likely independent**, and passes that are
**unknown** (still being researched.) It is important to note that some passes may *seem* like they do nothing when
run on the wrong type of program. We may test if opt passes are independent, but we might falsely label opt passes as
*dependent* simply because we did not use code with the proper features (ie, code without constants will not change
with const merge). Since the decompiler will be able to learn what passes go in which order, it is best to default
all passes to "independent." This prevents mistakes *we* might make without enough data; the RL Agent will learn the
correct ordering better than us.
Independent Passes:
**-break-crit-edges: Break critical edges in CFG**
This may be required for other passes that cannot handle critical edges. (The other passes are unknown at this time.)
**-gvn: Global Value Numbering**
**-instcombine: Combine redundant instructions**
**-jump-threading: Jump Threading**
If a condition is always true, or always false, this will get rid of it.
**-licm: Loop Invariant Code Motion**
**-loop-extract: Extract loops into new functions**
**-loop-extract-single: Extract at most one loop into a new function**
**-loop-rotate: Rotate Loops**
**-mem2reg: Promote Memory to Register**
The RL Agemt may find that some snippet swaps work better when done with registers.
**-prune-eh: Remove unused exception handling info**
**-reg2mem: Demote all values to stack slots**
The RL Agemt may find that some snippet swaps work better when done with memory.
**-simplifycfg: Simplify the CFG**
This simplifies the control flow graph, which might make the end result more readable.
Likely Independent Passes:
**-adce: Aggressive Dead Code Elimination**
All passes which involve removing dead code may be useful to our RL Agent. Our agent will perform swaps and passes
which may generate code that no longer matters. Dead code elimination will remove this code, thus simplifying the
result.
**-constmerge: Merge Duplicate Global Constants**
**-constprop: Simple constant propagation**
**-dce: Dead Code Elimination**
All passes which involve removing dead code may be useful. See Aggressive Dead Code Elimination for more information.
**-deadargelim: Dead Argument Elimination**
All passes which involve removing dead code may be useful. See Aggressive Dead Code Elimination for more information.
**-die: Dead Instruction Elimination**
All passes which involve removing dead code may be useful. See Aggressive Dead Code Elimination for more information.
**-dse: Dead Store Elimination**
All passes which involve removing dead code may be useful. See Aggressive Dead Code Elimination for more information.
**-functionattrs: Deduce function attributes**
**-globaldce: Dead Global Elimination**
All passes which involve removing dead code may be useful. See Aggressive Dead Code Elimination for more information.
**-globalopt: Global Variable Optimizer**
**-inline: Function Integration/Inlining**
Inlined functions are functions to be called faster than normal
**-loop-deletion: Delete dead loops**
All passes which involve removing dead code may be useful. See Aggressive Dead Code Elimination for more information.
**-lowerinvoke: Lower invokes to calls, for unwindless code generators**
**-lowerswitch: Lower SwitchInsts to branches**
Branches may be easier to deal with than switches.
**-mergefunc: Merge Functions**
**-partial-inliner: Partial Inliner**
**-strip-dead-prototypes: Strip Unused Function Prototypes**
All passes which involve removing dead code may be useful. See Aggressive Dead Code Elimination for more information.
Unknown Passes:
**-indvars: Canonicalize Induction Variables**
This may be required by other passes.
**-lcssa: Loop-Closed SSA Form Pass**
This may be required by other passes.
**-loop-simplify: Canonicalize natural loops**
This may be required for other passes.
**-reassociate: Reassociate expressions**
This makes other passes more efffective
**-sccp: Sparse Conditional Constant Propagation**
**-sink: Code sinking**
Dependent Passses:
**-loop-unswitch: Unswitch loops**
Depends on -lcim
Passes We Will Not Use:
-----------------------
A description of why we are not using these passes is coming soon.
**-always-inline: Inliner for always_inline functions**
This only inlines function that are marked with a keyword. The other inlining functions work fine for our purposes.
**-argpromotion: Promote ‘by reference’ arguments to scalars**
Will convert array objects to scalars, which complicates the code unnecessarily.
**-aggressive-instcombine: Combine expression patterns**
the regular instcombine optimization should suffice. This one is less efficient.
**-block-placement: Profile Guided Basic Block Placement**
Doesn't actually work
**-deadtypeelim: Dead Type Elimination**
Doesn't actually work
**-internalize: Internalize Global Symbols**
Our code, for our demo, will not have main functions.
**-ipconstprop: Interprocedural constant propagation**
**-ipsccp: Interprocedural Sparse Conditional Constant Propagation**
**-loop-reduce: Loop Strength Reduction**
**-loop-unroll: Unroll loops**
Loop unroll is complex and is an optimization we want to undo.
**-loop-unroll-and-jam: Unroll and Jam loops**
Loop unroll is complex and is an optimization we want to undo.
**-sroa: Scalar Replacement of Aggregates**
This replaces aggregates (such as arrays) with individual scalars, thus making the code less clear.
**-strip: Strip all symbols from a module**
All of the strip optimizations make the code less readable, according to LLVM's documentation: https://llvm.org/docs/Passes.html#strip-strip-all-symbols-from-a-module
**-strip-debug-declare: Strip all llvm.dbg.declare intrinsics**
See "Strip all symbols from a module."
**-strip-nondebug: Strip all symbols, except dbg symbols, from a module**
See "Strip all symbols from a module."
**-strip-dead-debug-info: Strip debug info for unused symbols**
See "Strip all symbols from a module."
**-tailcallelim: Tail Call Elimination**
This removes recursive calls and turns them into loops. We believe that this will generally complicate the code more.
Unknown Passes:
---------------
These passes are under consideration.
**-codegenprepare: Optimize for code generation**
This pass "munges" the code, which should make it worse. It is unknown if other passes we need require it though.
**Does not depend on other passes**
**-loweratomic: Lower atomic intrinsics to non-atomic form**
This may not make the code worse, but it is unknown if it will make it better.
**-memcpyopt: MemCpy Optimization**
**-mergereturn: Unify function exit nodes** | 41.806931 | 166 | 0.749438 |
195a9b791fd814b4def9aa963f99cf4bbe40e475 | 5,272 | rst | reStructuredText | docs/developer/corearchitecture/multi_thread.rst | xerothermic/vpp | 25a52a2c9c3e77acaf06a68a98be46fae254083d | [
"Apache-2.0"
] | 751 | 2017-07-13T06:16:46.000Z | 2022-03-30T09:14:35.000Z | docs/developer/corearchitecture/multi_thread.rst | xerothermic/vpp | 25a52a2c9c3e77acaf06a68a98be46fae254083d | [
"Apache-2.0"
] | 15 | 2018-03-19T15:20:07.000Z | 2022-03-18T19:48:21.000Z | docs/developer/corearchitecture/multi_thread.rst | xerothermic/vpp | 25a52a2c9c3e77acaf06a68a98be46fae254083d | [
"Apache-2.0"
] | 479 | 2017-07-13T06:17:26.000Z | 2022-03-31T18:20:43.000Z | .. _vpp_multi_thread:
Multi-threading in VPP
======================
Modes
-----
VPP can work in 2 different modes:
- single-thread
- multi-thread with worker threads
Single-thread
~~~~~~~~~~~~~
In a single-thread mode there is one main thread which handles both
packet processing and other management functions (Command-Line Interface
(CLI), API, stats). This is the default setup. There is no special
startup config needed.
Multi-thread with Worker Threads
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In this mode, the main threads handles management functions(debug CLI,
API, stats collection) and one or more worker threads handle packet
processing from input to output of the packet.
Each worker thread polls input queues on subset of interfaces.
With RSS (Receive Side Scaling) enabled multiple threads can service one
physical interface (RSS function on NIC distributes traffic between
different queues which are serviced by different worker threads).
Thread placement
----------------
Thread placement is defined in the startup config under the cpu { … }
section.
The VPP platform can place threads automatically or manually. Automatic
placement works in the following way:
- if “skip-cores X” is defined first X cores will not be used
- if “main-core X” is defined, VPP main thread will be placed on core
X, otherwise 1st available one will be used
- if “workers N” is defined vpp will allocate first N available cores
and it will run threads on them
- if “corelist-workers A,B1-Bn,C1-Cn” is defined vpp will automatically
assign those CPU cores to worker threads
User can see active placement of cores by using the VPP debug CLI
command show threads:
.. code-block:: console
vpd# show threads
ID Name Type LWP lcore Core Socket State
0 vpe_main 59723 2 2 0 wait
1 vpe_wk_0 workers 59755 4 4 0 running
2 vpe_wk_1 workers 59756 5 5 0 running
3 vpe_wk_2 workers 59757 6 0 1 running
4 vpe_wk_3 workers 59758 7 1 1 running
5 stats 59775
vpd#
The sample output above shows the main thread running on core 2 (2nd
core on the CPU socket 0), worker threads running on cores 4-7.
Sample Configurations
---------------------
By default, at start-up VPP uses
configuration values from: ``/etc/vpp/startup.conf``
The following sections describe some of the additional changes that can be made to this file.
This file is initially populated from the files located in the following directory ``/vpp/vpp/conf/``
Manual Placement
~~~~~~~~~~~~~~~~
Manual placement places the main thread on core 1, workers on cores
4,5,20,21.
.. code-block:: console
cpu {
main-core 1
corelist-workers 4-5,20-21
}
Auto placement
--------------
Auto placement is likely to place the main thread on core 1 and workers
on cores 2,3,4.
.. code-block:: console
cpu {
skip-cores 1
workers 3
}
Buffer Memory Allocation
~~~~~~~~~~~~~~~~~~~~~~~~
The VPP platform is NUMA aware. It can allocate memory for buffers on
different CPU sockets (NUMA nodes). The amount of memory allocated can
be defined in the startup config for each CPU socket by using the
socket-mem A[[,B],C] statement inside the dpdk { … } section.
For example:
.. code-block:: console
dpdk {
socket-mem 1024,1024
}
The above configuration allocates 1GB of memory on NUMA#0 and 1GB on
NUMA#1. Each worker thread uses buffers which are local to itself.
Buffer memory is allocated from hugepages. VPP prefers 1G pages if they
are available. If not 2MB pages will be used.
VPP takes care of mounting/unmounting hugepages file-system
automatically so there is no need to do that manually.
’‘’NOTE’’’: If you are running latest VPP release, there is no need for
specifying socket-mem manually. VPP will discover all NUMA nodes and it
will allocate 512M on each by default. socket-mem is only needed if
bigger number of mbufs is required (default is 16384 per socket and can
be changed with num-mbufs startup config command).
Interface Placement in Multi-thread Setup
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
On startup, the VPP platform assigns interfaces (or interface, queue
pairs if RSS is used) to different worker threads in round robin
fashion.
The following example shows debug CLI commands to show and change
interface placement:
.. code-block:: console
vpd# sh dpdk interface placement
Thread 1 (vpp_wk_0 at lcore 5):
TenGigabitEthernet2/0/0 queue 0
TenGigabitEthernet2/0/1 queue 0
Thread 2 (vpp_wk_1 at lcore 6):
TenGigabitEthernet2/0/0 queue 1
TenGigabitEthernet2/0/1 queue 1
The following shows an example of moving TenGigabitEthernet2/0/1 queue 1
processing to 1st worker thread:
.. code-block:: console
vpd# set interface placement TenGigabitEthernet2/0/1 queue 1 thread 1
vpp# sh dpdk interface placement
Thread 1 (vpp_wk_0 at lcore 5):
TenGigabitEthernet2/0/0 queue 0
TenGigabitEthernet2/0/1 queue 0
TenGigabitEthernet2/0/1 queue 1
Thread 2 (vpp_wk_1 at lcore 6):
TenGigabitEthernet2/0/0 queue 1
| 31.011765 | 101 | 0.693665 |
dbca9433b26488a56129768d83e57ce3bb2966df | 317,141 | rst | reStructuredText | notebook/dimention/4_prod/run_-165_45.rst | yutakasi634/MDToolbox.jl | 4a61ec671910d3fe25d86818a85e7929209d065d | [
"BSD-3-Clause"
] | null | null | null | notebook/dimention/4_prod/run_-165_45.rst | yutakasi634/MDToolbox.jl | 4a61ec671910d3fe25d86818a85e7929209d065d | [
"BSD-3-Clause"
] | null | null | null | notebook/dimention/4_prod/run_-165_45.rst | yutakasi634/MDToolbox.jl | 4a61ec671910d3fe25d86818a85e7929209d065d | [
"BSD-3-Clause"
] | null | null | null | ACE
4342 0.1200000E+04
7.9385612 23.7164804 24.6077603 8.2650225 23.7578375 23.5686205
7.6710002 23.1555958 22.8812033 9.1853150 23.1783832 23.4951736
8.4318075 25.2639019 23.1075092 7.8374722 26.0939744 23.7027895
9.1912775 25.4939228 21.9817432 9.5987124 24.6899668 21.5259454
9.4517386 26.7647841 21.4959636 8.5072263 27.3054487 21.4353084
10.4493571 27.4957531 22.4389188 10.7577055 28.4444446 21.9995947
10.0575353 27.6546922 23.4435650 11.4184728 27.0016587 22.5080961
9.9760276 26.7611320 20.0679286 10.9433772 27.4151381 19.6333125
9.4085805 25.8588746 19.2595581 8.5032368 25.4733953 19.4872825
9.9152606 25.4248045 17.9305269 9.3346137 24.5643724 17.5979523
9.7609141 26.2465575 17.2312423 10.8908631 24.9466714 18.0182134
19.9538214 13.3366250 1.1189721 19.6017516 13.0286738 0.2838405
20.5585380 12.6470286 1.3928453 1.9374879 0.8180399 11.3933650
2.7448404 0.4016974 11.6951473 1.9708249 0.7421286 10.4397623
4.4190499 28.9381618 24.2431145 5.0736642 29.6209995 24.0966748
3.8791659 28.9504942 23.4527950 26.7650275 16.5759824 11.9642798
26.2282846 16.1174822 12.6107444 26.2739571 16.4976826 11.1463857
32.5537112 4.0625428 2.1142821 32.6738766 3.2006689 1.7155773
31.7125455 4.0018226 2.5670350 9.0518874 13.4281064 23.3403862
9.7798954 13.4548488 23.9612896 8.2733002 13.3290325 23.8883080
24.9229259 5.2719385 3.5371734 24.3637710 4.4978659 3.4709216
24.4074415 5.9743952 3.1408626 26.4549749 6.2451415 0.2702871
26.8043606 7.1097182 0.4863165 25.6486455 6.4264761 -0.2126026
31.2476620 4.6137479 7.6059428 31.8234900 3.8923555 7.8594124
30.5870550 4.2071863 7.0451060 27.6872345 16.2053009 20.1585722
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10.2706366 31.3380921 12.3992316 11.2059678 31.1447633 12.4625670
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4.3366599 18.4494150 16.0279065 5.0695364 18.9001739 16.4473589
3.5576746 18.8824508 16.3770394 24.9801177 7.9279896 29.1490826
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24.2641982 10.2124838 19.5624653 19.5732925 2.7538929 27.8842172
19.3564498 3.6182133 27.5347015 19.5498250 2.1747229 27.1224802
12.0032007 7.2590298 23.2159937 12.6082151 6.6139547 22.8498413
12.5395025 7.7764308 23.8167502 3.3915160 11.2784805 21.6707273
4.3451441 11.3368554 21.7291875 3.2303394 10.4681231 21.1874314
34.0535540 6.1633363 3.0343443 33.7419157 5.3261932 2.6903895
34.9796400 6.0141308 3.2249598 4.9524423 10.9623304 18.1972204
4.1101068 11.2614221 18.5396339 5.6017526 11.3617510 18.7760910
12.0041968 9.4470065 29.2943251 12.1328077 8.5642797 28.9472165
12.8867979 9.8131678 29.3506544 0.5985574 12.6127137 8.1524076
1.4535384 12.1867642 8.2141044 0.8013241 13.5381121 8.0154581
3.0412861 24.6122582 31.3655993 3.3125709 23.9029419 31.9482713
2.0846609 24.5844357 31.3836579 23.0570134 13.6868875 15.3800593
23.9960007 13.5155812 15.4520932 22.6450214 12.8410702 15.5563759
23.0692864 27.7782192 22.5796761 23.2923695 27.6861013 21.6534040
23.6629883 27.1773664 23.0299270 1.3384473 31.3779072 20.6169206
1.9977938 32.0333176 20.3890365 0.5018561 31.8089777 20.4422056
14.4498838 11.8350534 9.4577774 15.2955069 11.6615094 9.8713424
13.8233699 11.8277904 10.1814205 11.8246321 23.6346811 23.7809862
12.3289179 23.9084493 23.0148409 11.5907604 22.7241257 23.6009177
15.1248298 7.0019368 7.4407240 15.6258231 6.2380057 7.7264629
14.4270636 7.0874348 8.0903734 27.6369957 19.3814991 12.1508423
27.2154708 18.5258934 12.0702980 27.4388585 19.8247227 11.3259020
34.2773431 1.8368865 4.6547876 35.1421225 1.5486296 4.9468430
34.2418594 2.7640629 4.8899826 35.0214202 30.5530452 10.8595084
35.6735721 29.9701423 10.4707232 34.8891772 31.2365582 10.2025810
9.0875806 7.3821917 3.4512621 9.6043166 8.1878144 3.4375572
9.3455991 6.9459331 4.2632576 12.9839292 23.1111612 18.7039927
13.6849085 23.7461473 18.5568446 13.3380753 22.2836817 18.3782781
16.0631850 26.0913995 5.7457632 15.7609372 26.7089378 6.4117396
16.3634879 26.6447188 5.0247307 13.8529435 1.9338002 12.4693319
13.6197148 2.6103042 13.1050823 14.0739138 2.4184757 11.6740372
5.5566318 30.9354554 10.9211275 5.2253159 31.7055355 11.3831213
6.0781867 31.2931858 10.2026281 24.9594611 16.9810287 19.7334047
24.6217536 17.5401670 20.4330831 24.8380454 17.4959170 18.9356704
14.7169206 17.9239269 27.2841826 14.1348209 18.4304759 26.7177906
14.7832173 18.4434087 28.0854162 1.4921609 34.2392051 22.5761009
0.7661398 34.6861181 23.0112951 1.8823477 33.6944605 23.2596500
6.7858347 12.4805163 28.6437230 7.2604493 13.2894368 28.8350878
6.9067273 11.9412774 29.4252844 21.3086597 10.3422923 26.7896453
20.5516778 10.7530385 26.3719159 21.4667794 10.8709704 27.5717767
9.5975846 22.7122229 27.7540114 10.0869343 23.3467585 27.2304341
9.1399454 23.2422911 28.4065649 24.1800348 24.5167447 23.9589822
24.1355662 23.9364963 24.7189599 24.8496510 25.1610936 24.1884608
6.4715087 4.5306928 23.8908120 6.9409692 4.8021676 24.6795706
6.3330547 3.5906041 24.0061178 9.5320737 6.9202798 29.1887237
8.7046106 7.3970312 29.2538747 9.9464479 7.2665987 28.3984142
31.3592435 33.7317182 31.8547262 30.5178672 34.1867680 31.8194070
31.7435438 34.0031655 32.6883097 22.1647578 34.4533009 26.5430409
22.1391741 33.5406051 26.8303800 21.4248251 34.8655864 26.9888571
31.4760138 19.4821495 6.5245089 32.2243792 18.9530010 6.2484962
31.6220097 19.6349194 7.4580925 2.6750201 7.1982542 8.2367871
2.6950781 7.0024996 9.1735419 3.5478756 6.9608492 7.9237473
9.9341530 12.1181726 8.1084822 9.2763862 12.8109108 8.0477495
9.8092554 11.5989859 7.3140783 19.5380487 1.6268818 25.3006402
20.1639156 1.6532928 24.5768826 19.4380435 0.6953777 25.4969333
32.4197046 33.8441025 16.9025451 33.3460044 33.9161900 17.1327709
32.4142406 33.3476543 16.0841680 17.4549123 2.0584284 9.6995018
18.3462892 2.1263154 9.3573461 17.1206438 1.2384394 9.3360263
24.5349894 9.6732217 6.3275922 24.1307163 8.8245434 6.1472027
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| 72.973079 | 80 | 0.686896 |
e2620ce261bca678b4b88733fd184e48ed82e0f2 | 3,378 | rst | reStructuredText | docs/source/dev/debugging.rst | CarloSucameli/Openfast-noise | b695c53ff790ac390f9fcf7ec1bf67e24688deb0 | [
"Apache-2.0"
] | null | null | null | docs/source/dev/debugging.rst | CarloSucameli/Openfast-noise | b695c53ff790ac390f9fcf7ec1bf67e24688deb0 | [
"Apache-2.0"
] | null | null | null | docs/source/dev/debugging.rst | CarloSucameli/Openfast-noise | b695c53ff790ac390f9fcf7ec1bf67e24688deb0 | [
"Apache-2.0"
] | 1 | 2021-02-05T17:50:01.000Z | 2021-02-05T17:50:01.000Z | .. _debugging:
Debugging OpenFAST
==================
Being a Fortran project, OpenFAST can be challenging to debug and the process
is unique for each system and environment. However, a common requirement for
all systems is to compile OpenFAST in debug mode.
Keep in mind that some OpenFAST cases can be quite large in their memory
footprint and may take a long time to reach the point you're targetting in
the code. Choosing a minimal test case could save significant time.
It may by helpful to write a small fortran program to verify that your
debugging tools are set up properly before diving in to OpenFAST. Be sure to
simulate a bug by doing something like accessing an array element that is not
allocated and verify that you can catch the bug with your tools.
Debugging on Windows
--------------------
Windows developers using Intel tools can use Visual Studio for debugging. This
is a straightforward process with lots of support from Intel.
Otherwise, Windows developers compiling with CygWin or MinGW should proceed to
the section for debugging with linux.
Debugging on Linux and macOS
----------------------------
First, compile OpenFAST in debug mode by setting CMAKE_BUILD_TYPE to Debug.
You can do this on the command line with
.. code-block:: bash
cmake .. -D CMAKE_BUILD_TYPE=Debug
or by using ccmake to open the command line cmake gui to change it.
The GNU debugger, GDB, works well for debugging compiled code. It has a
comprehensive command line interface which enables developers to add
breakpoints and inspect variables.
Driving the debugger through an IDE can make inspecting the code much more
efficient. One IDE known to work well is Visual Studio Code with the Native
Debug extension. You can set up a launch configuration in VS Code so that
you can debug a particular OpenFAST case through the IDE. To do this, open
the launch configuration and add a block similar to this:
.. code-block:: json
{
"name": "AOC_WSt",
"type": "gdb",
"request": "launch",
"printCalls": false,
"showDevDebugOutput": false,
"valuesFormatting": "prettyPrinters",
"gdbpath": "gdb",
"target": "${workspaceRoot}/build/glue-codes/openfast/openfast",
"cwd": "${workspaceRoot}/build/reg_tests/glue-codes/openfast/AOC_WSt/",
"arguments": "${workspaceRoot}/build/reg_tests/glue-codes/openfast/AOC_WSt/AOC_WSt.fst",
},
macOS configuration
~~~~~~~~~~~~~~~~~~~
GDB on macOS needs some configuration before the system allows it to take
over a process. It is recommended that gdb be installed with homebrew
.. code-block:: bash
brew info gdb
brew install gdb
After that completes, be sure to follow the caveats to finish the installation.
For gdb 8.2.1, it looks like this:
.. code-block:: bash
==> Caveats
gdb requires special privileges to access Mach ports.
You will need to codesign the binary. For instructions, see:
https://sourceware.org/gdb/wiki/BuildingOnDarwin
On 10.12 (Sierra) or later with SIP, you need to run this:
echo "set startup-with-shell off" >> ~/.gdbinit
For Native Debug on macOS, you have to sort of hack the extension to allow
breakpoints in fortran files by adding this line to your settings.json:
.. code-block:: json
"debug.allowBreakpointsEverywhere": true,
| 35.93617 | 100 | 0.720841 |
85038629413ce93bc836be3667934b3b9b0d9c12 | 3,129 | rst | reStructuredText | README.rst | jkanche/epivizFileParser | 29caf7a0ee2dee6396cbd77ac2d50bb849607b17 | [
"MIT"
] | null | null | null | README.rst | jkanche/epivizFileParser | 29caf7a0ee2dee6396cbd77ac2d50bb849607b17 | [
"MIT"
] | null | null | null | README.rst | jkanche/epivizFileParser | 29caf7a0ee2dee6396cbd77ac2d50bb849607b17 | [
"MIT"
] | null | null | null | ==================
Epiviz File Server
==================
.. image:: https://readthedocs.org/projects/epivizfileserver/badge/?version=latest
:target: https://epivizfileserver.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status
.. image:: https://travis-ci.org/epiviz/epivizFileServer.svg?branch=master
:target: https://travis-ci.org/epiviz/epivizFileServer
Compute and Query Parser for Genomic Files
Description
===========
Epiviz file Server is a Python library, to query genomic files,
not only for visualization but also for transformation.
The library provides various modules to perform various tasks -
- Parser to read various genomic file formats,
- Query to access only necessary bytes of file,
- Compute to apply transformations on data,
- Server to instantly convert the datasets into an API and
- Visualization.
A quick overview of the library and its features, are described in an IPython notebook
available at - https://epiviz.github.io/post/2019-02-04-epiviz-fileserver/
Note
====
1. The library requires the server hosting the data files to support HTTP range requests so that the file server's parser module can only request the necessary byte-ranges needed to process the query
2. The library currently supports indexed genomic file formats like BigWig, BigBed, Bam (with bai), Sam (with sai) or any genomic data file that can be indexed using tabix.
Developer Notes
===============
This project has been set up using PyScaffold 3.1. For details and usage
information on PyScaffold see https://pyscaffold.org/.
use a virtualenv for testing & development.
To setup run the following commands from the project directory
.. code-block:: python
virtualenv env --python=python3
source env/bin/activate # (activate.fish if using the fish-shell)
pip install -r requirements.txt
# to deactivate virtualenv
deactivate
1. Test - ```python setup.py test```
2. Docs - ```python setup.py docs```
3. Build
- source distribution ```python setup.py sdist```
- binary distribution ```python setup.py bdist```
- wheel distribution ```python setup.py bdist_wheel```
Download and/or Build Genome or Transcript files for use with Epiviz File Server
================================================================================
Either --ucsc or --gtf must be provided.
- To generate a genome file, ```efs build_genome --ucsc=mm10 --output=mm10```
- To generate a transcripts file, ```efs build_transcript --ucsc=mm10 --output=mm10``` (transcript files are prepended with `transcripts.`)
- To generate both files, ```efs build_both --ucsc=mm10 --output=mm10```
Usage:
```efs.py (build_genome | build_transcript | build_both) (--ucsc=<genome> | --gtf=<file>) [--compressed] [--output=<output>]```
Options:
- ```--ucsc=<genome>``` genome build to download and parse from ucsc, eg: mm10
- ```--gtf=<file>``` local gtf file
- ```-c --compressed``` File is gzip compressed
- ```--output=<output>``` the directory where file is saved, defaults to current working directory
- ```-h --help``` Show this screen.
| 38.158537 | 199 | 0.69511 |
459e56c1443e14bfca2c6dc278d33939bc9a66da | 3,383 | rst | reStructuredText | docs/index.rst | Ajay2810-hub/console-messenger | c5052b90c6dde603336014d2918577dc7caa54b1 | [
"MIT"
] | null | null | null | docs/index.rst | Ajay2810-hub/console-messenger | c5052b90c6dde603336014d2918577dc7caa54b1 | [
"MIT"
] | null | null | null | docs/index.rst | Ajay2810-hub/console-messenger | c5052b90c6dde603336014d2918577dc7caa54b1 | [
"MIT"
] | null | null | null | console-messenger
=================
| |Downloads|
| |Downloads/Week|
| |Downloads/Month|
| |MIT License|
| |Latest PyPI version|
| |Supported Python versions|
About
-----
This package displays success, warning and info messages and errors on
console with different colours using
`rich <https://pypi.org/project/rich/>`__ module. It also prints any
error type without passing it as a parameter.
Requirements
------------
.. code:: shell
python>=3.0
Dependencies
------------
.. code:: shell
rich>=9.0.0
Installation
------------
.. code:: shell
pip install console-messenger
Usage
-----
.. code:: python
>>> from ConsoleMessenger import ConsoleMessage
>>> console = ConsoleMessage()
**Print an error**
.. code:: python
try:
a = 5/0
except Exception as e:
console.danger(e)
Output :-
|Broken Image|
**Display a custom error**
.. code:: python
console.danger("this is a custom error", err_type="My Error")
Output :-
|Broken Image|
**Print a success message**
.. code:: python
console.success("Success", "success method worked!")
Output :-
|Broken Image|
**Display a warning**
.. code:: python
console.warning("Warning", "You are using pip version 20.2.4; however, version 20.3 is available.")
Output :-
|Broken Image|
**Display a info message**
.. code:: python
console.info("INFO", "Hello User!")
Output :-
|Broken Image|
**Display a dark message**
.. code:: python
console.dark("Dark", "This is a dark message!")
Output :-
|Broken Image|
.. |Downloads| image:: https://static.pepy.tech/personalized-badge/console-messenger?period=total&units=international_system&left_color=grey&right_color=orange&left_text=Downloads
:target: https://pepy.tech/project/console-messenger
.. |Downloads/Week| image:: https://static.pepy.tech/personalized-badge/console-messenger?period=week&units=international_system&left_color=grey&right_color=blue&left_text=Downloads/Week
:target: https://pepy.tech/project/console-messenger
.. |Downloads/Month| image:: https://static.pepy.tech/personalized-badge/console-messenger?period=week&units=international_system&left_color=grey&right_color=brightgreen&left_text=Downloads/Month
:target: https://pepy.tech/project/console-messenger
.. |MIT License| image:: https://img.shields.io/badge/License-MIT-yellow.svg
:target: https://opensource.org/licenses/MIT
.. |Latest PyPI version| image:: https://img.shields.io/pypi/v/console-messenger.svg
:target: https://pypi.org/project/console-messenger
.. |Supported Python versions| image:: https://img.shields.io/pypi/pyversions/console-messenger.svg
:target: https://pypi.org/project/console-messenger
.. |Broken Image| image:: https://raw.githubusercontent.com/Ajay2810-hub/console-messenger/main/images/img.png
.. |Broken Image| image:: https://raw.githubusercontent.com/Ajay2810-hub/console-messenger/main/images/img1.png
.. |Broken Image| image:: https://raw.githubusercontent.com/Ajay2810-hub/console-messenger/main/images/img2.png
.. |Broken Image| image:: https://raw.githubusercontent.com/Ajay2810-hub/console-messenger/main/images/img3.png
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.. |Broken Image| image:: https://raw.githubusercontent.com/Ajay2810-hub/console-messenger/main/images/img5.png
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509e5a594f71a5de8cb7d039f264d624a8901565 | 387 | rst | reStructuredText | docs/api/snl_d3d_cec_verify.rst | Data-Only-Greater/SNL-Delft3D-CEC-Verify | 3aaab93b8fab6e3b6710b68d181b9946ae3ab74a | [
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] | 34 | 2021-12-20T14:51:36.000Z | 2022-03-16T11:44:30.000Z | docs/api/snl_d3d_cec_verify.rst | H0R5E/SNL-Delft3D-CEC-Verify | 234c0acead13c74bad2979b300671733c7b184f7 | [
"MIT"
] | 1 | 2021-12-20T14:17:30.000Z | 2021-12-20T14:17:30.000Z | API
===
Subpackages
-----------
.. toctree::
:maxdepth: 4
snl_d3d_cec_verify.copier
snl_d3d_cec_verify.grid
snl_d3d_cec_verify.report
snl_d3d_cec_verify.result
snl_d3d_cec_verify.runner
snl_d3d_cec_verify.text
snl\_d3d\_cec\_verify package
-----------------------------
.. automodule:: snl_d3d_cec_verify
:members:
:undoc-members:
:inherited-members:
| 15.48 | 34 | 0.666667 |
36764cce1ef76ab905569544abdd6f4fc1ffc5a2 | 26,900 | rst | reStructuredText | index.rst | lsst-dm/dmtn-035 | 90805e39eadc6cfe75020618d6db4c1d59ab62cb | [
"CC-BY-4.0"
] | null | null | null | index.rst | lsst-dm/dmtn-035 | 90805e39eadc6cfe75020618d6db4c1d59ab62cb | [
"CC-BY-4.0"
] | null | null | null | index.rst | lsst-dm/dmtn-035 | 90805e39eadc6cfe75020618d6db4c1d59ab62cb | [
"CC-BY-4.0"
] | null | null | null | ..
Technote content.
See https://developer.lsst.io/docs/rst_styleguide.html
for a guide to reStructuredText writing.
Do not put the title, authors or other metadata in this document;
those are automatically added.
Use the following syntax for sections:
Sections
========
and
Subsections
-----------
and
Subsubsections
^^^^^^^^^^^^^^
To add images, add the image file (png, svg or jpeg preferred) to the
_static/ directory. The reST syntax for adding the image is
.. figure:: /_static/filename.ext
:name: fig-label
:target: http://target.link/url
Caption text.
Run: ``make html`` and ``open _build/html/index.html`` to preview your work.
See the README at https://github.com/lsst-sqre/lsst-technote-bootstrap or
this repo's README for more info.
Feel free to delete this instructional comment.
:tocdepth: 1
.. sectnum::
.. Add content below. Do not include the document title.
Previous Data Release from `Summer 2012`_ :cite:`DMTN-034`
.. _Summer 2012: https://dmtn-034.lsst.io
Image Differencing
------------------
A report is available `here <https://ls.st/LDM-227>`_ :cite:`LDM-227`
SDSS Stripe 82 Reprocessing (co-adds and forced photometry)
-----------------------------------------------------------
LSST Data Management have recently finished building r-band SDSS Stripe 82 co-adds and performing forced photometry on individual epochs of ``g``, ``r``, and ``i``-band Stripe 82 data.
The primary goal of this effort was to add the capability to make background matched co-adds to the DM stack, and test it at large scale by reprocessing real survey data. The full description of the challenge is available in the `Winter 2013 Data Challenge Handbook`_.
.. _Winter 2013 Data Challenge Handbook: https://docushare.lsstcorp.org/docushare/dsweb/Get/Document-15299
Background matched co-adds preserve the diffuse astrophysical backgrounds in the stacked image. This increases its scientific usefulness.
Furthermore, the thus constructed background in the co-add has higher S/N, making it easier to subtract it when needed. We plan to use this method to generate the co-adds in LSST production, and it was therefore important to have it built into the stack early.
This will make upcoming tests of stackfit/multifit algorithms more realistic.
Our preliminary analysis indicates the quality of this dataset is comparable to the quality of Stripe 82 reprocessing we performed for `Summer 2012`_, but with significantly more area.
**Nevertheless, we caution you that these data were processed "on a budget", with prototype code, and minimal quality assessment.
They are a byproduct of an ongoing software development effort, and not a result of a concerted scientific investigation. The code is still incomplete both in terms of features and quality, and the same will be true of the reprocessed data.
In particular, if you plan to use this data set for science, expect to have to devote time to perform additional QA, and to have to communicate with DM developers to understand the details of the dataset.**
If you do notice issues, or have questions, please don't hesitate to contact us at ``<dm-help --at-- lsst.org>``.
A `report is available as LDM-226 <https://ls.st/LDM-226>`_. :cite:`LDM-226`
.. _data-access-rules:
Data Access Rules
-----------------
The data products provided by LSST DM are intended only for members of the LSST Science Collaborations unless noted otherwise.
If their use results in a publication, their users will have to to abide by the `LSST Publication Policy`_. :cite:`LPM-162`
.. _LSST Publication Policy: http://ls.st/LPM-162
The products are protected by a "well known" username and password: ``lsst`` / ``3gigapix!`` .
Using this combination to access the data implies you understand and accept the restrictions on their redistribution and usage.
.. _data-locations:
Data Locations
--------------
Note #1: Some of these websites require the standard DM user name and password; see the :ref:`data-access-rules` section for more information.
Note #2: The catalog and image access tools in use here are temporary solutions for data distribution built with off-the-shelf open source components: in particular, they are *NOT* representative of the Science User Interface the LSST will ultimately have.
Where to get data/information:
* Contact by email: ``<dm-help --at-- lsst.org>``
* `Winter 2013 Data Challenge Handbook`_.
* Catalogs access (phpMyAdmin): https://lsst-web.ncsa.illinois.edu/mydb/
- Note #1: if you don't have a DM mysql database account, use `this link <http://lsst-web.ncsa.illinois.edu/dbaccount>`_ to sign up.
- Note #2: You will need the "well known" username/password to access the signup form and the database entry page (see the :ref:`data-access-rules` section above).
- Note #3: If you're accessing using the native mysql client, the database name is ``DC_W13_Stripe82``.
* FITS image access (coadds): See :ref:`accessing-coadds`.
* Co-add visualization tool: http://moe.astro.washington.edu/sdss/
* `Data Management Software v6_1 Release <https://dev.lsstcorp.org/trac/wiki/Installing/Winter2013>`_ (an intermediate Winter 2013 release).
If you decide to make use of this data, feel free to inquire about the details at ``<dm-help --at-- lsst.org>``.
.. _accessing-coadds:
Accessing Winter 2013 Coadd FITS Files
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
The server ``lsst-web.ncsa.illinois.edu`` provides access to the data.
The entire namespace can be explored by pointing your browser to: http://lsst-web.ncsa.illinois.edu/lsstdata
The individual FITS files are stored in a directory hierarchy using the following scheme:
.. code-block:: bash
http://lsst-web.ncsa.illinois.edu/lsstdata/dr-w2013/deepCoadd/[ugriz]/<tract>/<patch>/coadd-[ugriz]-<tract>-<patch>.fits
where
* ``[ugriz]`` is a single filter id from the indicated list (currently only ``r``)
* ``<tract>`` is the LSST skymap tract id (currently 0 or 3)
* ``<patch>`` is the LSST skymap patch id (of the form ``xxx,yyy``)
For example:
.. code-block:: bash
wget http://lsst-web.ncsa.illinois.edu/lsstdata/dr-w2013/deepCoadd/r/3/7,2/coadd-r-3-7,2.fits
Individual coadd files are 40MB (uncompressed).
Description of Data Products
----------------------------
We used 298 runs imaged as a part of SDSS Stripe 82 (2 million fields) to create a deep co-add approximately covering -40 deg < R.A. < 55 deg, -1.25 < Dec < 1.25 (237 deg^2^).
No PSF matching was performed on the co-adds, making them deeper but less suitable for photometry.
The co-adds were used to detect 14.7 million sources, most of which would otherwise fall below the faint limit of individual exposures.
Photometry was performed in individual epochs, at the location of each source detected in the co-adds, resulting in 3.9 billion ``g``, ``r`` and ``i`` band measurements ("forced photometry").
``u`` and ``z`` bands were not processed. We also produced catalogs of averaged forced photometry, both across the duration of the whole survey (~10 years), and on a yearly basis.
The co-adds are available as a series of 5126 FITS images, each spanning 2060 x 1937 pixels (see [wiki:W2013WebDataAccess] for how to access them). The catalogs are kept in a MySQL database and available through phpMyAdmin web interface, or (for power users), through the command-line mysql client.
See the :ref:`data-locations` for instructions on how to access the database, and how to open an account if you don't already have one.
The database contains 20 tables and views; however, only a few are of general interest (listed below).
We do not have at this time a detailed description of the schema of each of these tables; however, the `Summer2012 schema <http://lsst1.ncsa.uiuc.edu/schema/index.php?sVer=S12_sdss>`_ should provide sufficient information to understand the meaning of most of these columns even though the exact names may have changed.
Most frequently used tables:
.. _table-AvgForcedPhot:
.. table:: AvgForcedPhot table.
+---------------------+---------------------------------------------------------------------+
| Column | Description |
+=====================+=====================================================================+
| deepSourceId | object identifier |
+---------------------+---------------------------------------------------------------------+
| ra | Right Ascension (degrees) |
+---------------------+---------------------------------------------------------------------+
| decl | Declination (degrees) |
+---------------------+---------------------------------------------------------------------+
| nMag_[gri] | number of measurements for the band |
+---------------------+---------------------------------------------------------------------+
| magFaint_[gri] | magnitude of the faintest measurement in the band |
+---------------------+---------------------------------------------------------------------+
| medMag_[gri] | magnitude of the median measurement in the band |
+---------------------+---------------------------------------------------------------------+
| magBright_[gri] | magnitude of the brightest measurement in the band |
+---------------------+---------------------------------------------------------------------+
| q1Mag_[gri] | magnitude of the first (faintest) quartile measurement in the band |
+---------------------+---------------------------------------------------------------------+
| q3Mag_[gri] | magnitude of the third (brightest) quartile measurement in the band |
+---------------------+---------------------------------------------------------------------+
| faint5perMag_[gri] | 5th percentile magnitude in the band |
+---------------------+---------------------------------------------------------------------+
| bright5perMag_[gri] | 95th percentile magnitude in the band |
+---------------------+---------------------------------------------------------------------+
AvgForcedPhot
A table with percentiles of photometry in each band (5th, 25th, 50th (median), 75th, 95th). Columns are specified in :ref:`the table above <table-AvgForcedPhot>`.
All percentiles were calculated on the fluxes and converted back to magnitude for convenience.
AvgForcedPhotYearly
Same as the AvgForcedPhot table, except the percentiles are computed for each year of the survey.
Therefore there are typically ~10 rows per object.
Compared to AvgForcedPhot, this table has one extra column (''year'', running from 1 to 10), and no 5th and 95th percentile columns.
DeepForcedSource
Table with forced photometry measurements in individual epochs.
Use this table if you're interested in querying for complete light curves.
DeepSource
A table of sources detected on co-adds. This is in effect the master "object catalog".
Note however that because the co-adds were not PSF-matched, the photometry in this table will be relatively poor; use AvgForcedPhot table instead.
RefObject
A containing SDSS DR7 Stripe82 co-add :cite:`2014ApJ...794..120A` catalog. It's been matched to DeepSource via RefDeepSrcMatch table.
Science_Ccd_Exposure
A table with metadata for all SDSS Stripe82 `fields <http://skyserver.sdss.org/dr7/en/sdss/data/data.asp>`_.
Science_Ccd_Exposure_coadd_r
A table with metadata for all co-add "patches" (when producing the co-add, we divided the sky into large "tracts", and each tract has been subdivided into "patches").
The patches are stored as FITS files on the image server (see :ref:`accessing-coadds`).
Example Queries
---------------
**Retrieve median g, r, i magnitudes for all objects in a (ra, dec) box:**
.. code-block:: sql
SELECT
ra, decl,
medMag_g, medMag_r, medMag_i
FROM
`AvgForcedPhot`
WHERE
ra BETWEEN 0.01 and 0.02
AND decl BETWEEN 0.03 and 0.04
Alternatively, you can use `scisql <https://lsst-web.ncsa.illinois.edu/schema/sciSQL/>`_ geometry functions; this should speed up queries over large area:
.. code-block:: sql
SET @poly = scisql_s2CPolyToBin(0.01, 0.03, 0.02, 0.03, 0.03, 0.04, 0.01, 0.04);
CALL scisql.scisql_s2CPolyRegion(@poly, 20);
SELECT
ra, decl,
medMag_g, medMag_r, medMag_i
FROM
`AvgForcedPhot`
WHERE
scisql_s2PtInCPoly(ra, decl, @poly) = 1
**Retrieve a g-band light curve for object 1398579058966639:**
.. code-block:: sql
SELECT
deepSourceId,
deepForcedSourceId,
exp.run,
fsrc.timeMid,
scisql_dnToAbMag(fsrc.psfFlux, exp.fluxMag0) as g,
scisql_dnToAbMagSigma(fsrc.psfFlux, fsrc.psfFluxSigma, exp.fluxMag0, exp.fluxMag0Sigma) as gErr
FROM
DeepForcedSource AS fsrc,
Science_Ccd_Exposure AS exp
WHERE
exp.scienceCcdExposureId = fsrc.scienceCcdExposureId
AND fsrc.filterId = 1
AND NOT (fsrc.flagPixEdge | fsrc.flagPixSaturAny |
fsrc.flagPixSaturCen | fsrc.flagBadApFlux |
fsrc.flagBadPsfFlux)
AND deepSourceId = 1398579058966639
ORDER BY
fsrc.timeMid
Notes:
* The times (timeMid column) denote the mid-points of exposure each SDSS frame.
Since SDSS took data in TDI mode, these have to be corrected to the effective time of observation of each object.
* No effort has been made to remove objects doubly-detected in overlap regions of SDSS frames.
You may therefore get more than one measurement per run.
**Retrieve a g-band light curves for all objects with 0.0 < ra < 0.01deg and 0.0 < dec < 0.01deg:**
.. code-block:: sql
SELECT
deepSourceId,
deepForcedSourceId,
exp.run,
fsrc.ra,
fsrc.decl,
fsrc.timeMid,
scisql_dnToAbMag(fsrc.psfFlux, exp.fluxMag0) as g,
scisql_dnToAbMagSigma(fsrc.psfFlux, fsrc.psfFluxSigma, exp.fluxMag0, exp.fluxMag0Sigma) as gErr
FROM
DeepForcedSource AS fsrc,
Science_Ccd_Exposure AS exp
WHERE
exp.scienceCcdExposureId = fsrc.scienceCcdExposureId
AND fsrc.filterId = 1
AND NOT (fsrc.flagPixEdge | fsrc.flagPixSaturAny |
fsrc.flagPixSaturCen | fsrc.flagBadApFlux |
fsrc.flagBadPsfFlux)
AND fsrc.ra BETWEEN 0.0 AND 0.01
AND fsrc.decl BETWEEN 0.0 AND 0.01
ORDER BY
fsrc.deepSourceId, fsrc.timeMid
Notes:
* Expect this query to take 1-2 minutes to complete.
It will return 2,014 rows.
Covered footprint
-----------------
A quick visualization of the footprint available in Winter 2013 Stripe 82 data, created by plotting all 15.9 million detected objects:
.. image:: /_static/Winter2013-Stripe82-Footprint.png
:alt: Winter2013 Footprint
:target: _static/Winter2013-Stripe82-Footprint.png
.. image:: /_static/Winter2013-Stripe82-Footprint-Zoomed.png
:alt: Winter2013 Footprint Zoomed
:target: _static/Winter2013-Stripe82-Footprint-Zoomed.png
RGB Color composites
--------------------
RGB color composite of an area in the vicinity of M2:
.. image:: /_static/M2Composite.png
:alt: Color composite of M2
:target: _static/M2Composite.png
The full-sized image can be viewed/panned/zoomed at http://moe.astro.washington.edu/sdss/.
Quality assessment
------------------
Comparison to S2012 and Completeness
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
We took a small subset of data from both the Summer 2012 DC and the Winter 2013 early production DC.
Using the DEEP2 catalogs :cite:`2004ApJ...617..765C` as reference, we compare the completeness as a function of magnitude between the two reductions.
.. image:: /_static/S12_W13_comp.png
:alt: Comparison histogram
:target: _static/S12_W13_comp.png
:width: 400 px
:align: center
The Winter 2013 (blue) completeness tracks very well with the Summer 2012 (red).
This shows that we have not changed anything substantial between the two reduction runs.
We next look at a much large section of the survey covering the Deep2 Field 4 photometric catalogs.
We construct completeness and contamination profiles for the Winter 2013 DC.
.. image:: /_static/completeness.png
:target: _static/completeness.png
:width: 400 px
:align: center
In addition to comparing to the DEEP2 catalogs, we compare the completeness of the Annis (2014) :cite:`2014ApJ...794..120A` catalogs to the Winter 2013 results.
The Winter 2013 catalog is significantly less complete at bright magnitudes.
We are looking more into this, but early evidence suggests this is due primarily to background subtraction around bright stars and to the fact that multiple peaks within a single detection footprint are not de-blended into individual sources for the Winter 2013 runs.
We have placed a 5-sigma S/N threshold on the Annis catalog and the Winter 2013 catalog does not go significantly below 5-sigma.
With these cuts the Winter 2013 catalog goes ~0.2 mag deeper than the Annis catalog.
The completeness plot is not the whole story.
We also look at the trends in S/N between the Annis (2014) :cite:`2014ApJ...794..120A` catalog and the Winter 2013 catalog.
.. image:: /_static/snr.png
:target: _static/snr.png
:width: 400 px
:align: center
This shows that for constant S/N the Winter 2013 catalog goes about 0.75 mag deeper than the Annis (2014) :cite:`2014ApJ...794..120A` catalog.
We also see that the Winter 2013 catalog is 10-sigma at our 50% limiting magnitude of 24.2.
This suggests that a 5-sigma threshold on the coadd to seed forced photometry is too conservative and that we should have pushed to 3-sigma (or fainter) in the coadd to reach completeness in the coadded catalog at 5-sigma.
We also looked for contamination in the Winter 2013 catalog.
We define contamination simply as any object in the Winter 2013 catalog that is not in the DEEP2 catalog.
The following figure shows that there is less than 5% relative contamination to our limiting magnitude.
.. image:: /_static/contamination.png
:target: _static/contamination.png
:width: 400 px
:align: center
The production pipelines perform photometric calibration using the catalog of Ivezic (2007) :cite:`2007AJ....134..973I`.
In this analysis we look at the distribution of forced photometry principal colors of stellar sources, described in Ivezic (2004) :cite:`2004AN....325..583I`.
We use the star-galaxy separation provided by the Annis (2014) :cite:`2014ApJ...794..120A` Stripe82 catalog to select point sources for the analysis; we do not do any native star-galaxy separation.
The figure below illustrates the process of defining a principal color (adopted from Ivezic (2004) :cite:`2004AN....325..583I`):
.. image:: /_static/zeljko_w.png
:target: _static/zeljko_w.png
:width: 240 px
:align: center
The width of the stellar locus perpendicular to principal color P1 (top) is a function of underlying stellar astrophysics, and errors on the photometry.
As the bottom panel demonstrates, this width increases as a function of magnitude, as photometric uncertainties start to dominate.
In our analysis, we look at the principal colors ``w``, shown in the figure above, and ``x``, which is the width perpendicular to the vertical distribution in the ``(r-i)`` vs. ``(g-r)`` diagram above.
We examine below the width of the principal loci as a function of the number of epochs for forced photometry: using 1 epoch (i.e. all the data), the median (in flux) of two epochs (where the flux medians to a value > 0.0), and the median of 10 and then 40 epochs.
We first show the results for Summer2012 processing below:
.. image:: /_static/S12_2.png
:target: _static/S12_2.png
:width: 49%
.. image:: /_static/S12.png
:target: _static/S12.png
:width: 49%
The *left* image provides the distribution of points around the principal colors ``w`` and ``x`` (i.e. the principal locus is at x=0 in all plots).
Each panel shows the all-data distribution, and then the median across epochs for all objects with N>9 epochs. When medianing across many measurements, the locus becomes tighter, and is less dominated by the photometric uncertainties to fainter magnitudes.
The *right* panel shows how the width of this locus improves as a function of the number of epochs, for N=1,2,10,40 epochs, along with a histogram of the number of objects vs. r-band magnitude.
We examine below the results of the Winter2013 processing for one of the 6 SDSS camcols.
This includes data from camcol=1 of both the N and S strips of the stripe.
We subdivide the data into areas 10 degrees wide in RA, and provide measurements of the median and standard deviation of the distributions (computed as 0.741 times the interquartile range) in tabular form for the first RA range.
-40 < RA < -30
""""""""""""""
.. image:: /_static/ra_dec_full0.dat_1.png
:target: _static/ra_dec_full0.dat_1.png
:width: 49%
.. image:: /_static/ra_dec_full0.dat_2.png
:target: _static/ra_dec_full0.dat_2.png
:width: 49%
.. code-block:: sh
Mag w;N=1 w;N=2 w;N=10 w;N=40 x;N=1 x;N=2 x;N=10 x;N=40
15.25 -0.004,0.015 -0.006,0.015 -0.002,0.010 -0.002,0.010 -0.027,0.016 ... ... ...
15.75 -0.004,0.016 -0.003,0.015 -0.003,0.011 -0.003,0.010 -0.009,0.032 -0.008,0.030 -0.010,0.022 -0.006,0.022
16.25 -0.003,0.016 -0.002,0.014 -0.002,0.010 -0.002,0.010 -0.015,0.037 -0.006,0.021 -0.013,0.027 -0.009,0.022
16.75 -0.003,0.016 -0.004,0.014 -0.003,0.010 -0.002,0.009 -0.016,0.037 -0.015,0.036 -0.019,0.026 -0.018,0.028
17.25 -0.003,0.016 -0.003,0.014 -0.002,0.010 -0.002,0.008 -0.007,0.037 -0.007,0.040 -0.005,0.034 -0.004,0.029
17.75 -0.002,0.017 -0.001,0.015 -0.002,0.010 -0.002,0.008 0.001,0.041 -0.008,0.044 0.002,0.034 0.004,0.035
18.25 -0.002,0.019 -0.002,0.016 -0.002,0.011 -0.002,0.009 -0.003,0.044 -0.007,0.042 0.001,0.032 0.000,0.031
18.75 -0.002,0.021 -0.003,0.018 -0.001,0.012 -0.001,0.009 0.000,0.050 0.001,0.047 0.002,0.036 0.002,0.035
19.25 -0.002,0.026 -0.002,0.021 -0.002,0.013 -0.002,0.010 0.004,0.063 0.005,0.059 0.004,0.042 0.006,0.038
19.75 -0.002,0.035 -0.003,0.029 -0.001,0.015 -0.002,0.010 -0.000,0.082 -0.000,0.076 0.001,0.050 -0.000,0.043
20.25 -0.002,0.050 -0.003,0.040 -0.002,0.021 -0.002,0.012 0.003,0.112 0.011,0.094 0.005,0.060 0.003,0.050
20.75 -0.002,0.074 -0.003,0.060 -0.003,0.029 -0.003,0.017 0.003,0.161 0.001,0.140 0.006,0.076 0.003,0.059
21.25 -0.001,0.113 -0.008,0.083 -0.005,0.042 -0.006,0.024 0.005,0.234 0.003,0.197 0.009,0.101 0.007,0.070
21.75 0.017,0.173 0.007,0.141 -0.008,0.066 -0.007,0.037 -0.008,0.337 0.004,0.291 0.015,0.159 0.017,0.093
22.25 0.056,0.274 0.043,0.225 -0.008,0.104 -0.012,0.060 -0.044,0.466 -0.034,0.388 0.033,0.225 0.034,0.136
22.75 0.128,0.390 0.081,0.350 -0.000,0.174 -0.011,0.097 -0.176,0.591 -0.096,0.525 0.064,0.364 0.064,0.215
23.25 0.249,0.467 0.178,0.422 0.035,0.254 0.005,0.155 -0.403,0.672 -0.309,0.631 -0.019,0.490 0.095,0.352
23.75 0.470,0.495 0.361,0.478 0.138,0.338 0.043,0.240 -0.722,0.681 -0.625,0.674 -0.275,0.610 0.026,0.499
24.25 0.780,0.493 0.632,0.549 0.372,0.372 0.145,0.257 -1.058,0.654 -0.985,0.668 -0.641,0.621 -0.179,0.618
24.75 1.112,0.514 0.934,0.480 0.673,0.362 0.437,0.293 -1.400,0.637 -1.169,0.675 -1.064,0.514 -0.597,0.743
25.25 1.448,0.525 1.299,0.411 0.963,0.503 ... -1.742,0.659 -1.615,0.879 -1.434,0.437 -1.155,0.668
-30 < RA < -20
""""""""""""""
.. image:: /_static/ra_dec_full1.dat_1.png
:target: _static/ra_dec_full1.dat_1.png
:width: 49%
.. image:: /_static/ra_dec_full1.dat_2.png
:target: _static/ra_dec_full1.dat_2.png
:width: 49%
-20 < RA < -10
""""""""""""""
.. image:: /_static/ra_dec_full2.dat_1.png
:target: _static/ra_dec_full2.dat_1.png
:width: 49%
.. image:: /_static/ra_dec_full2.dat_2.png
:target: _static/ra_dec_full2.dat_2.png
:width: 49%
-10 < RA < 0
""""""""""""
.. image:: /_static/ra_dec_full3.dat_1.png
:target: _static/ra_dec_full3.dat_1.png
:width: 49%
.. image:: /_static/ra_dec_full3.dat_2.png
:target: _static/ra_dec_full3.dat_2.png
:width: 49%
0 < RA < 10
"""""""""""
.. image:: /_static/ra_dec_full4.dat_1.png
:target: _static/ra_dec_full4.dat_1.png
:width: 49%
.. image:: /_static/ra_dec_full4.dat_2.png
:target: _static/ra_dec_full4.dat_2.png
:width: 49%
10 < RA < 20
""""""""""""
.. image:: /_static/ra_dec_full5.dat_1.png
:target: _static/ra_dec_full5.dat_1.png
:width: 49%
.. image:: /_static/ra_dec_full5.dat_2.png
:target: _static/ra_dec_full5.dat_2.png
:width: 49%
20 < RA < 30
""""""""""""
.. image:: /_static/ra_dec_full6.dat_1.png
:target: _static/ra_dec_full6.dat_1.png
:width: 49%
.. image:: /_static/ra_dec_full6.dat_2.png
:target: _static/ra_dec_full6.dat_2.png
:width: 49%
30 < RA < 40
""""""""""""
.. image:: /_static/ra_dec_full7.dat_1.png
:target: _static/ra_dec_full7.dat_1.png
:width: 49%
.. image:: /_static/ra_dec_full7.dat_2.png
:target: _static/ra_dec_full7.dat_2.png
:width: 49%
40 < RA < 50
""""""""""""
.. image:: /_static/ra_dec_full8.dat_1.png
:target: _static/ra_dec_full8.dat_1.png
:width: 49%
.. image:: /_static/ra_dec_full8.dat_2.png
:target: _static/ra_dec_full8.dat_2.png
:width: 49%
50 < RA < 55
""""""""""""
.. image:: /_static/ra_dec_full9.dat_1.png
:target: _static/ra_dec_full9.dat_1.png
:width: 49%
.. image:: /_static/ra_dec_full9.dat_2.png
:target: _static/ra_dec_full9.dat_2.png
:width: 49%
References
----------
.. bibliography:: bibliography.bib
:encoding: latex+latin
:style: plain
.. note::
This document was originally published as an LSST TRAC page at https://dev.lsstcorp.org/trac/wiki/DC/Winter2013
| 47.526502 | 318 | 0.646766 |
6db08d1ba7216fbb1881b3d9c5d6234349a73db0 | 1,708 | rst | reStructuredText | sphinx-docs/source/about.rst | icornelius/zettelgeist | a7f4781270647da25a3a63ed346488943aacc509 | [
"Apache-2.0"
] | 19 | 2017-06-05T13:41:52.000Z | 2022-02-20T20:35:05.000Z | sphinx-docs/source/about.rst | gkthiruvathukal/zdemo | 9ae81b84ed0d87ed288e454aa34e54fb610f1f99 | [
"Apache-2.0"
] | 26 | 2017-05-17T20:01:43.000Z | 2022-02-28T00:14:21.000Z | sphinx-docs/source/about.rst | gkthiruvathukal/zdemo | 9ae81b84ed0d87ed288e454aa34e54fb610f1f99 | [
"Apache-2.0"
] | 5 | 2019-01-23T21:15:59.000Z | 2021-07-06T15:04:27.000Z | About
======
ZettelGeist is a plaintext note-taking system, inspired by the
`ZettelKasten
Method <http://zettelkasten.de/posts/zettelkasten-improves-thinking-writing/>`__.
The project founders have both been interested in taking notes long
before discovering ZettelKasten. We really like the thought process
behind ZettelKasten, however, and think it is ahead of its time by being
“less is more” in its focus.
A key, salient feature of our approach to implementing a ZettelKasten
system is *not* to get distracted by GUI tools at an early stage of
development. The default assumption of our system is that we work from
plaintext files. We are particularly inspired by systems like Jekyll (a
static-site generator for building web sites) that uses YAML to organize
its front matter and Markdown as the body. We’re even starting more
simply by just using YAML without Markdown, although we might introduce
it at release time. The idea is to focus on true notetaking by not
encouraging the writing of large, complex documents (which aren’t really
notes, right??)
So ZettelGeist is aimed at supporting the *spirit* of ZettelKasten,
while ensuring that it will be useful in other domains. Our primary
audience is the scholar who wants to write notes using a simple text
editor and storing these notes in the cloud, e.g. in Dropbox, GitHub,
etc. While we’d love to build something like the successor to Evernote
or OneNote–even as a graphical client–our view is that no such tool
should be developed without having the right core abstractions in place.
Ultimately, the *note* is the central abstraction. Having support for
metadata is crucial, especially for scholarly–or other serious–projects.
Stay tuned!!
| 48.8 | 81 | 0.800937 |
0a347c46173a257e9a43f49248c290c740694172 | 15,268 | rst | reStructuredText | docs_rst/guide_to_writing_firetasks.rst | water-e/fireworks | 5db359430adc138a313326de3049e6f89dec4cbc | [
"BSD-3-Clause-LBNL"
] | 2 | 2017-06-27T07:12:27.000Z | 2017-09-22T12:06:18.000Z | docs_rst/guide_to_writing_firetasks.rst | water-e/fireworks | 5db359430adc138a313326de3049e6f89dec4cbc | [
"BSD-3-Clause-LBNL"
] | null | null | null | docs_rst/guide_to_writing_firetasks.rst | water-e/fireworks | 5db359430adc138a313326de3049e6f89dec4cbc | [
"BSD-3-Clause-LBNL"
] | null | null | null | ========================================================
The Comprehensive Guide to Writing Firetasks with Python
========================================================
This guide covers in more detail how one can write their own Firetasks (and return dynamic actions), and assemble those Firetasks into FireWorks and Workflows. This guide will also cover the FWAction object, passing data, and dynamic workflow actions.
A "Hello World Example"
=======================
If you'd like to see a "Hello World" Example of a custom Firetask, you can go `here <https://github.com/materialsproject/fireworks/tree/master/fireworks/examples/custom_firetasks/hello_world>`_.
If you are able to run that example and want more details of how to modify and extend it, read on...
Writing a Basic Firetask
========================
Step 1: Choose existing Firetask(s) or write your own?
------------------------------------------------------
The first thing you should decide is whether to use an existing Firetask or write your own. FireWorks comes pre-packaged with many "default" Firetasks - in particular, the :doc:`PyTask <pytask>` allows you to call any Python function. There are also existing Firetasks for running scripts, remotely transferring files, etc. The quickest route to getting something running is to use an existing Firetask, i.e. use the :doc:`PyTask <pytask>` if you want to run a quick script.
Links to documentation on default Firetasks can be found in the :doc:`main page <index>` under the heading "built-in Firetasks".
A few reasons to *not* use the default Firetasks are:
* You want to give your Firetasks custom names
* You prefer a class-based method to defining tasks rather than the function-based method of :doc:`PyTask <pytask>`
* You want control over how the Firetask is constructed, e.g., define required parameters.
Step 2: Start with a Firetask template and modify it
----------------------------------------------------
The easiest way to understand a Firetask is to examine an example; for example, here's one implementation of a task to archive files::
class ArchiveDirTask(FiretaskBase):
"""
Wrapper around shutil.make_archive to make tar archives.
Args:
base_name (str): Name of the file to create.
format (str): Optional. one of "zip", "tar", "bztar" or "gztar".
"""
_fw_name = 'ArchiveDirTask'
required_params = ["base_name"]
optional_params = ["format"]
def run_task(self, fw_spec):
shutil.make_archive(self["base_name"], format=self.get("format", "gztar"), root_dir=".")
You can copy this code to a new place and make the following modifications in order to write your Firetask:
* In the first line, the name of the class (*ArchiveDirTask*) can be anything - it does not affect the operation of the code if you follow the structure above.
* *Change the class name to anything you desire.*
* The class extends the *FiretaskBase* abstract class. This abstract class does some work under the covers and also requires that you define a ``run_task(self, fw_spec)`` method.
* *Keep this intact.*
* The ``_fw_name`` is how this Firetask is identified. It must be a unique name that is always retained. See the Appendix section for working around this and an alternate formulations for identifying the Firetask.
* *Change the ``fw_name`` value to a desired identifier for your Firetask, e.g. MyFavoriteTask.*
* The ``required_params`` and ``optional_params`` relate to how the Firetask is constructed. In the example above, an *ArchiveTask* could be instantiated using something like ``my_task = ArchiveTask(base_name="my_filename", format="bztar")``. Because ``base_name`` is in ``required_params``, it **must** be specified (``optional_params`` does not actually *do* anything).
* *Add your required and optional parameters as desired.*
* The meat of the Firetask is the ``run_task(self, fw_spec)`` method. It has two sources of information: the keys in ``fw_spec`` and a dictionary of ``self`` (which includes parameters like ``base_name`` used to construct the object). In this case, it's tarring and gzipping some files according to the parameters the dictionary of itself, and ignoring anything in the ``fw_spec``.
*Keep the run_task method header intact, but change the definition to your custom operation. Remember you can access dict keys of "fw_spec" as well as dict keys of "self"*
Step 3: Register your Firetask
------------------------------
When FireWorks bootstraps your Firetask from a database definition, it needs to know where to look for Firetasks.
**First**, you need to make sure your Firetask is defined in a file location that can be found by Python, i.e. is within Python's search path and that you can import your Firetask in a Python shell. If Python cannot import your code (e.g., from the shell), neither can FireWorks. This step usually means either installing the code into your ``site-packages`` directory (where many Python tools install code) or modifying your ``PYTHONPATH`` environment variable to include the location of the Firetask. You can see the locations where Python looks for code by typing ``import sys`` followed by ``print(sys.path)``. If you are unfamiliar with this topic, some more details about this process can be found `here <http://www.linuxtopia.org/online_books/programming_books/python_programming/python_ch28s04.html>`_, or try Googling "how does Python find modules?"
**Second**, you must register your Firetask so that it can be found by the FireWorks software. There are a couple of options for registering your Firetask (you only need to do *one* of the below):
1. Use the **@explicit_serialize** decorator to define your FW name (see the Appendix). No further registration is needed if you use this option.
#. (or) if you have access to the FireWorks source directory, put your Firetask definition anywhere in ``fireworks.user_objects`` or it subdirectories - it will be automatically be found there.
#. (or) put the Firetask wherever you'd like. However, you need to modify the ``USER_PACKAGES`` variable of the :doc:`FW config <config_tutorial>` to include the package for where to find the Firetask, e.g. "mypackage.my_subpackage". Note that FireWorks will search within subpackages automatically, so you can just put a root package (but loading will be slightly slower).
You are now ready to use your Firetask!
Dynamic and message-passing Workflows
=====================================
In the previous example, the ``run_task`` method did not return anything, nor does it pass data to downstream Firetasks or FireWorks. Remember that the setting the ``_pass_job_info`` key in the Firework spec to True will automatically pass information about the current job to the child job - see :doc:`reference <reference>` for more details.
However, one can also return a ``FWAction`` object that performs many powerful actions including dynamic workflows.
Here's an example of a Firetask implementation that includes dynamic actions via the *FWAction* object::
class FibonacciAdderTask(FiretaskBase):
_fw_name = "Fibonacci Adder Task"
def run_task(self, fw_spec):
smaller = fw_spec['smaller']
larger = fw_spec['larger']
stop_point = fw_spec['stop_point']
m_sum = smaller + larger
if m_sum < stop_point:
print('The next Fibonacci number is: {}'.format(m_sum))
# create a new Fibonacci Adder to add to the workflow
new_fw = Firework(FibonacciAdderTask(), {'smaller': larger, 'larger': m_sum, 'stop_point': stop_point})
return FWAction(stored_data={'next_fibnum': m_sum}, additions=new_fw)
else:
print('We have now exceeded our limit; (the next Fibonacci number would have been: {})'.format(m_sum))
return FWAction()
We discussed running this example in the :doc:`Dynamic Workflow tutorial <dynamic_wf_tutorial>` - if you have not gone through that tutorial, we strongly suggest you do so now (it also includes an example of message passing).
Note that this example is slightly different than the previous one:
* We did not define any required or optional parameters. The parameters are taken from the ``fw_spec`` rather than ``self``.
* We are explicitly returning *FWAction* objects. In one case, the object looks to be storing data and adding FireWorks.
Other than those differences, the code is the same format as earlier. The dynamicism comes only from the *FWAction* object; next, we will this object in more detail.
File-passing Workflows
======================
In many common types of workflows, you want to pass files from one Firework to the next. For example, the output files generated by one Firework may be used by the next Firework as an input.
FireWorks support two keys - ``_files_in`` and ``files_out`` - as a means to specifying the expected input and output
files for a Firework. See :doc:`reference <reference>` for more details.
An example of such a workflow is given below::
fw1 = Firework(
[ScriptTask.from_str('echo "This is the first FireWork" > test1')],
spec={"_files_out": {"fwtest1": "test1"}}, fw_id=1)
fw2 = Firework([ScriptTask.from_str('gzip hello')], fw_id=2,
parents=[fw1],
spec={"_files_in": {"fwtest1": "hello"},
"_files_out": {"fw2": "hello.gz"}})
fw3 = Firework([ScriptTask.from_str('cat fwtest.2')], fw_id=3,
parents=[fw2],
spec={"_files_in": {"fw2": "fwtest.2"}})
wf = Workflow([fw1, fw2, fw3],
{fw1: [fw2], fw2: [fw3]})
Both ``_files_in`` and ``_files_out`` are dicts of {mapped_name: actual_file_name}. If the child Firework has ``_files_in``
that intersects with ``files_out`` of the parent, these files are automatically copied over and renamed, with gzip,
bzip2 compression being handled transparently. In the above example, ``fw1`` generates a file called ``test1``, which
is available in _files_out under the name ``fwtest1``. The ``files_in`` of fw2 contains ``fwtest1``, which means that
the file ``test1`` is being copied to the launch directory of fw2 and renamed as ``hello``. The same concept applies
to fw2 and fw3, though in this case, the gzipped file of fw2 is moved to the launch directory of fw3, ungzipped and
made available as ``fwtest.2``. Note that the mapped names must conform to MongoDB rules, i.e., no "." and "$" cannot be
the first character. There are no restrictions on the actual file name.
This framework completely decouples the input and output file names between linked Fireworks for flexibility, and also
makes it easier for most Fireworks to make use of compression where necessary to reduce storage requirements without
requiring child fireworks to implement complex logic for handling compressed files. The FW spec also becomes a
complete definition of expected input and output files, a very common use case in many sophisticated workflows.
The FWAction object
===================
A Firetask (or a function called by :doc:`PyTask <pytask>`) can return a *FWAction* object that can perform many powerful actions. Note that the *FWAction* is stored in the FW database after execution, so you can always go back and see what actions were returned by different Firetasks. A diagram of the different FWActions is below:
.. image:: _static/fwactions.png
:alt: FW actions
:align: center
The parameters of FWAction are as follows:
* **stored_data**: *(dict)* data to store from the run. The data is put in the Launch database along with the rest of the FWAction. Does not affect the operation of FireWorks.
* **exit**: *(bool)* if set to True, any remaining Firetasks within the same Firework are skipped (like a ``break`` statement for a Firework).
* **update_spec**: *(dict)* A data dict that will update the spec for any remaining Firetasks *and* the following Firework. Thus, this parameter can be used to pass data between Firetasks or between FireWorks. Note that if the original fw_spec and the update_spec contain the same key, the original will be overwritten.
* **mod_spec**: ([dict]) This has the same purpose as update_spec - to pass data between Firetasks/FireWorks. However, the update_spec option is limited in that it can't increment variables or append to lists. This parameter allows one to update the child FW's spec using the DictMod language, a Mongo-like syntax that allows more fine-grained changes to the fw_spec.
* **additions**: ([Workflow]) a list of WFs/FWs to add as children to this Firework.
* **detours**: ([Workflow]) a list of WFs/FWs to add as children (they will inherit the current FW's children)
* **defuse_children**: (bool) defuse all the original children of this Firework
* **defuse_workflow**: (bool) defuse all incomplete FWs in this Workflow
The FWAction thereby allows you to *command* the workflow programmatically, allowing for the design of intelligent workflows that react dynamically to results.
Appendix 1: accessing the LaunchPad within the Firetask
=======================================================
It is generally not good practice to use the LaunchPad within the Firetask because this makes the task specification less explicit. For example, this could make duplicate checking more problematic. However, if you really need to access the LaunchPad within a Firetask, you can set the ``_add_launchpad_and_fw_id`` key of the Firework spec to be True. Then, your tasks will be able to access two new variables, ``launchpad`` (a LaunchPad object) and ``fw_id`` (an int), as members of your Firetask. One example is shown in the unit test ``test_add_lp_and_fw_id()``.
Appendix 2: alternate ways to identify the Firetask and changing the identification
===================================================================================
Other than explicitly defining a ``_fw_name`` parameter, there are two alternate ways to identify the Firetask:
* You can omit the ``_fw_name`` parameter altogether, and the code will then use the Class name as the identifier. However, note that this is dangerous as changing your Class name later on can break your code. In addition, if you have two Firetasks with the same name the code will throw an error.
* (or) You can omit the ``_fw_name`` **and** add an ``@explicit_serialize`` decorator to your Class. This will identify your class by the module name AND class name. This prevents namespace collisions, AND it allows you to skip registering your Firetask! However, the serialization is even more sensitive to refactoring: moving your Class to a different module will break the code, as will renaming it. Here's an example of how to use the decorator::
from fireworks.utilities.fw_utilities import explicit_serialize
@explicit_serialize
class PrintFW(FiretaskBase):
def run_task(self, fw_spec):
print str(fw_spec['print'])
In both cases of removing ``_fw_name``, there is still a workaround if you refactor your code. The :doc:`FW config <config_tutorial>` has a parameter called ``FW_NAME_UPDATES`` that allows one to map old names to new ones via a dictionary of {<old name>:<new name>}. This method also works if you need to change your ``_fw_name`` for any reason.
| 77.111111 | 858 | 0.725766 |
d7051c642ceb9f3f19640e78d9c457e2be3121cc | 5,837 | rst | reStructuredText | docs/faq/building-open-mpi.rst | zhaog6/ompi | cc9647e6c1402f6432882ae9f426307ecb7ac721 | [
"BSD-3-Clause-Open-MPI"
] | null | null | null | docs/faq/building-open-mpi.rst | zhaog6/ompi | cc9647e6c1402f6432882ae9f426307ecb7ac721 | [
"BSD-3-Clause-Open-MPI"
] | null | null | null | docs/faq/building-open-mpi.rst | zhaog6/ompi | cc9647e6c1402f6432882ae9f426307ecb7ac721 | [
"BSD-3-Clause-Open-MPI"
] | 1 | 2022-02-04T06:10:07.000Z | 2022-02-04T06:10:07.000Z | Building Open MPI
=================
.. TODO How can I create a TOC just for this page here at the top?
/////////////////////////////////////////////////////////////////////////
How do I statically link to the libraries of Intel compiler suite?
------------------------------------------------------------------
The Intel compiler suite, by default, dynamically links its runtime libraries
against the Open MPI binaries and libraries. This can cause problems if the Intel
compiler libraries are installed in non-standard locations. For example, you might
get errors like:
.. code-block::
error while loading shared libraries: libimf.so: cannot open shared object file:
No such file or directory
To avoid such problems, you can pass flags to Open MPI's configure
script that instruct the Intel compiler suite to statically link its
runtime libraries with Open MPI:
.. code-block::
shell$ ./configure CC=icc CXX=icpc FC=ifort LDFLAGS=-Wc,-static-intel ...
/////////////////////////////////////////////////////////////////////////
Why do I get errors about hwloc or libevent not found?
------------------------------------------------------
Sometimes you may see errors similar to the following when attempting
to build Open MPI:
.. code-block::
...
PPFC profile/pwin_unlock_f08.lo
PPFC profile/pwin_unlock_all_f08.lo
PPFC profile/pwin_wait_f08.lo
FCLD libmpi_usempif08.la
ld: library not found for -lhwloc
collect2: error: ld returned 1 exit status
make``2``: *** ``libmpi_usempif08.la`` Error 1
This error can happen when a number of factors occur together:
#. If Open MPI's ``configure`` script chooses to use an "external"
installation of `hwloc <https://www.open-mpi.org/projects/hwloc/>`_
and/or `Libevent <https://libevent.org/>`_ (i.e., outside of Open
MPI's source tree).
#. If Open MPI's ``configure`` script chooses C and Fortran compilers
from different suites/installations.
Put simply: if the default search library search paths differ between
the C and Fortran compiler suites, the C linker may find a
system-installed ``libhwloc`` and/or ``libevent``, but the Fortran linker
may not.
This may tend to happen more frequently starting with Open MPI v4.0.0
on Mac OS because:
#. In v4.0.0, Open MPI's ``configure`` script was changed to "prefer"
system-installed versions of hwloc and Libevent (vs. preferring the
hwloc and Libevent that are bundled in the Open MPI distribution
tarballs).
#. In MacOS, it is common for `Homebrew <https://brew.sh/>`_ or
`MacPorts <https://www.macports.org/>`_ to install:
* hwloc and/or Libevent
* gcc and gfortran
For example, as of July 2019, Homebrew:
* Installs hwloc v2.0.4 under ``/usr/local``
* Installs the Gnu C and Fortran compiler suites v9.1.0 under
``/usr/local``. *However*, the C compiler executable is named ``gcc-9``
(not ``gcc``!), whereas the Fortran compiler executable is
named ``gfortran``.
These factors, taken together, result in Open MPI's ``configure``
script deciding the following:
* The C compiler is ``gcc`` (which is the MacOS-installed C
compiler).
* The Fortran compiler is ``gfortran`` (which is the
Homebrew-installed Fortran compiler).
* There is a suitable system-installed hwloc in ``/usr/local``, which
can be found -- by the C compiler/linker -- without specifying any
additional linker search paths.
The careful reader will realize that the C and Fortran compilers are
from two entirely different installations. Indeed, their default
library search paths are different:
* The MacOS-installed ``gcc`` will search ``/usr/local/lib`` by
default.
* The Homebrew-installed ``gfortran`` will *not* search
``/usr/local/lib`` by default.
Hence, since the majority of Open MPI's source code base is in C, it
compiles/links against hwloc successfully. But when Open MPI's
Fortran code for the ``mpi_f08`` module is compiled and linked, the
Homebrew-installed ``gfortran`` -- which does not search
``/usr/local/lib`` by default -- cannot find ``libhwloc``, and the link
fails.
There are a few different possible solutions to this issue:
#. The best solution is to always ensure that Open MPI uses a C and
Fortran compiler from the same suite/installation. This will
ensure that both compilers/linkers will use the same default
library search paths, and all behavior should be consistent. For
example, the following instructs Open MPI's ``configure`` script to
use ``gcc-9`` for the C compiler, which (as of July 2019) is the
Homebrew executable name for its installed C compiler:
.. code-block:: sh
shell$ ./configure CC=gcc-9 ...
# You can be precise and specify an absolute path for the C
# compiler, and/or also specify the Fortran compiler:
shell$ ./configure CC=/usr/local/bin/gcc-9 FC=/usr/local/bin/gfortran ...
Note that this will likely cause ``configure`` to *not* find the
Homebrew-installed hwloc, and instead fall back to using the
bundled hwloc in the Open MPI source tree.
#. Alternatively, you can simply force ``configure`` to select the
bundled versions of hwloc and libevent, which avoids the issue
altogether:
.. code-block:: sh
shell$ ./configure --with-hwloc=internal --with-libevent=internal ...
#. Finally, you can tell ``configure`` exactly where to find the
external hwloc library. This can have some unintended
consequences, however, because it will prefix both the C and
Fortran linker's default search paths with ``/usr/local/lib``:
.. code-block:: sh
shell$ ./configure --with-hwloc-libdir=/usr/local/lib ...
Be sure to :ref:`see this section of the Installation guide
<label-install-required-support-libraries>` for more
information about the bundled hwloc and/or Libevent
vs. system-installed versions.
| 38.401316 | 83 | 0.696591 |
cea7c660f05d8db0519d320cb88ea7499bfdade8 | 363 | rst | reStructuredText | docs/sources/index.rst | DCPUTeam/DCPUToolchain | 1882aadbcbd4226064e4d8be9e7178ba771491d8 | [
"MIT"
] | 7 | 2015-10-31T19:11:46.000Z | 2022-02-20T23:55:03.000Z | docs/sources/index.rst | DCPUTeam/DCPUToolchain | 1882aadbcbd4226064e4d8be9e7178ba771491d8 | [
"MIT"
] | 2 | 2016-10-07T06:33:34.000Z | 2017-12-13T16:00:11.000Z | docs/sources/index.rst | DCPUTeam/DCPUToolchain | 1882aadbcbd4226064e4d8be9e7178ba771491d8 | [
"MIT"
] | 4 | 2015-10-08T02:24:35.000Z | 2022-02-20T21:39:29.000Z | Welcome!
=============================================
Welcome to the documentation for the DCPU-16 Toolchain.
Contents:
.. toctree::
:maxdepth: 2
whatsnew/index
whatsnew/deployable
tutorial/index
tools/index
lang/index
modules/index
kernels/index
Indices and tables
==================
* :ref:`genindex`
* :ref:`search`
| 13.961538 | 55 | 0.550964 |
df8ddcee8bdebf1620c1024ede28c99437427bd3 | 3,011 | rst | reStructuredText | 2022/Round A/Speed Typing/PROBLEM.rst | Harmon758/Google-Code-Jam-Kickstart | 7199300a6c3ae0c846c401e2b3ac22397678028d | [
"MIT"
] | 2 | 2018-05-21T22:47:17.000Z | 2018-12-14T13:37:22.000Z | 2022/Round A/Speed Typing/PROBLEM.rst | Harmon758/Google-Code-Jam-Kickstart | 7199300a6c3ae0c846c401e2b3ac22397678028d | [
"MIT"
] | null | null | null | 2022/Round A/Speed Typing/PROBLEM.rst | Harmon758/Google-Code-Jam-Kickstart | 7199300a6c3ae0c846c401e2b3ac22397678028d | [
"MIT"
] | null | null | null | Problem
-------
Barbara is a speed typer. In order to check her typing speed, she performs a
speed test. She is given a string **I** that she is supposed to type.
While Barbara is typing, she may make some mistakes, such as pressing the wrong
key. As her typing speed is important to her, she does not want to spend
additional time correcting the mistakes, so she continues to type with the
errors until she finishes the speed test. After she finishes the speed test,
she produces a **P**.
Now she wonders how many extra letters she needs to delete in order to get
**I** from **P**. It is possible that Barbara made a mistake and **P** cannot
be converted back to **I** just by deleting some letters. In particular, it is
possible that Barbara missed some letters.
Help Barbara find out how many extra letters she needs to remove in order to
obtain **I** or if **I** cannot be obtained from **P** by removing letters then
output ``IMPOSSIBLE``.
Input
-----
The first line of the input gives the number of test cases, **T**. **T** test
cases follow.
Each test case has 2 lines. The first line of each test case is an input string
**I** (that denotes the string that the typing test has provided). The next
line is the produced string **P** (that Barbara has entered).
Output
------
For each test case, output one line containing |Case #x: y|, where *x* is the
test case number (starting from 1) and *y* is the number of extra letters that
need to be removed in order to obtain **I**. If it is not possible to obtain
**I** then output ``IMPOSSIBLE`` as *y*.
.. |Case #x: y| raw:: html
<code>Case #<i>x</i>: <i>y</i></code>
Limits
------
| Memory limit: 1 GB.
| 1 ≤ **T** ≤ 100.
| Both the strings contain letters from ``a``-``z`` and ``A``-``Z``.
| Length of the given strings will be 1 ≤ \|\ **I**\|, \|\ **P**\| ≤ 10\ :sup:`5`.
Test Set 1
^^^^^^^^^^
| Time limit: 20 seconds.
| All letters in **I** are the same.
Test Set 2
^^^^^^^^^^
Time limit: 40 seconds.
Sample
------
*Note: there are additional samples that are not run on submissions down
below.*
`Sample Input <speed_typing_sample_ts1_input.txt>`_
`Sample Output <speed_typing_sample_ts1_output.txt>`_
| In the first test case, **P** contains one extra ``a``, so she needs to
remove 1 extra letter in order to obtain **I**.
| In the second test case, Barbara typed only 4 letters ``b``, while **I**
consists of 5 letters ``b`` so the answer is ``IMPOSSIBLE``.
Additional Sample - Test Set 2
------------------------------
*The following additional sample fits the limits of Test Set 2. It will not be
run against your submitted solutions.*
`Sample Input <speed_typing_sample_ts2_input.txt>`_
`Sample Output <speed_typing_sample_ts2_output.txt>`_
| In the first test case, **P** has 2 extra letters, ``I`` and ``l``. The other
letters are in the order given in **I**. So she needs to remove 2 letters in
order to obtain **I**.
| In the second test case, there is no letter ``K`` in **P** so the answer is
``IMPOSSIBLE``.
| 35.423529 | 82 | 0.688808 |
9810acfa44160e93445cdb1ec94a580a2eebaacb | 1,675 | rst | reStructuredText | docs/usage.rst | shrinivdeshmukh/bearsql | 9c9742419728daf8f349695d8cd38c08a9421d19 | [
"MIT"
] | 12 | 2021-06-30T12:29:13.000Z | 2022-01-10T13:50:51.000Z | docs/usage.rst | shrinivdeshmukh/bearsql | 9c9742419728daf8f349695d8cd38c08a9421d19 | [
"MIT"
] | 35 | 2021-07-09T01:55:43.000Z | 2022-03-28T01:29:10.000Z | docs/usage.rst | shrinivdeshmukh/bearsql | 9c9742419728daf8f349695d8cd38c08a9421d19 | [
"MIT"
] | 2 | 2021-06-30T14:32:42.000Z | 2021-08-13T14:04:11.000Z | =====
Usage
=====
To use bearsql in a project::
from bearsql import SqlContext
import pandas as pd
sc = SqlContext()
# The above statement will create duckdb instance in memory. Once the session ends, the database will be erased and not be persisted
# To persist the database, you can instantiate sqlcontext like:
# sc = SqlContext(database='<YOUR_DATABASE_NAME>.db'
df = pd.DataFrame([{'name': 'John Doe', 'city': 'New York', 'age': 24}, {'name': 'Jane Doe', 'city': 'Chicago', 'age': 27}])
# Create table from pandas dataframe
sc.register_table(df, 'testable') # <YOUR_TABLENAME> instead of 'testable'
# Query table and output to pandas dataframe
results = sc.sql('select * from testable', output='df')
output_df = next(results)
print(output_df)
# Query table and output to pyarrow table
results = sc.sql('select * from testable', output='arrow')
output_arrow_table = next(results)
print(output_arrow_table)
# Query table and output raw tuples
results = sc.sql('select * from testable', output='any')
output_rows = next(results)
print(output_rows)
Create a relational table from dataframe and apply some operations::
rel = sc.relation(df, 'new_relation') # <YOUR_RELATION_NAME> instead of new_relation
print(rel.filter('age > 24'))
# OR convert to df:
rel.filter('age > 24').df()
Export the data to filesystem::
result = sc.sql('EXPORT DATABASE \'<OUTPUT_FOLDER>\' (FORMAT PARQUET);') # format can either be PARQUET or CSV
list(result)
For more examples, please visit https://github.com/duckdb/duckdb/blob/master/examples/python/duckdb-python.py
| 31.603774 | 136 | 0.68597 |
942b6d2698bb007cc1a33170f996eafe9b00f866 | 1,338 | rst | reStructuredText | docs/quickstart/index.rst | herringfromblr/f5-sdk-ternovskiy | adc8434be0c79176db6480bd6842d7a214ba9284 | [
"Apache-2.0"
] | null | null | null | docs/quickstart/index.rst | herringfromblr/f5-sdk-ternovskiy | adc8434be0c79176db6480bd6842d7a214ba9284 | [
"Apache-2.0"
] | null | null | null | docs/quickstart/index.rst | herringfromblr/f5-sdk-ternovskiy | adc8434be0c79176db6480bd6842d7a214ba9284 | [
"Apache-2.0"
] | null | null | null | Quick Start
===========
Prerequisites
-------------
- Python 3.x, for installation see `python download docs <https://www.python.org/downloads/>`_.
- Python virtual environment, for details see `python venv docs <https://docs.python.org/3/tutorial/venv.html>`_.
- Optional: Specify the log level verbosity to see additional log messages during SDK usage. See the :ref:`troubleshooting` section for more details.
- Optional: Ignore untrusted TLS certificate warnings during HTTPS requests to BIG-IP. See the :ref:`troubleshooting` section for more details.
Installation
------------
::
pip install f5-sdk-python
.. note::
Typically, all that is required to use the SDK is a basic installation. For certain platforms or system configurations it may be simpler to get started in a container.
::
docker run --rm -it -v $(pwd):/f5sdk python:3.7 /bin/bash
Usage
-----
This script uses the SDK to update BIG-IP L4-L7 configuration using AS3, provided via a local file.
For an example AS3 declaration, see the documentation `here <https://clouddocs.f5.com/products/extensions/f5-appsvcs-extension/latest/userguide/examples.html#example-1-simple-http-application>`_.
::
python example.py
.. literalinclude:: ../../examples/extension_as3.py
:language: python
|
.. include:: /_static/reuse/feedback.rst | 30.409091 | 195 | 0.723468 |
36e266e4d84ad575242a90aeb97fb31321bcbc18 | 2,626 | rst | reStructuredText | before.rst | CyVerse-learning-materials/DOI_request_quickstart | c4d5931958c7f4db348e4c352aad8afeeef986b8 | [
"CC-BY-4.0"
] | null | null | null | before.rst | CyVerse-learning-materials/DOI_request_quickstart | c4d5931958c7f4db348e4c352aad8afeeef986b8 | [
"CC-BY-4.0"
] | null | null | null | before.rst | CyVerse-learning-materials/DOI_request_quickstart | c4d5931958c7f4db348e4c352aad8afeeef986b8 | [
"CC-BY-4.0"
] | null | null | null | .. include:: cyverse_rst_defined_substitutions.txt
|CyVerse_logo|_
|Home_Icon|_
`Learning Center Home <http://learning.cyverse.org/>`_
1. Before you start
---------------------
Background
========================
CyVerse Curated Data in the Data Commons contains files that have been assigned a permanent identifier ( |DOI| ). These files are secure, stable, and unchangeable, thus making them the ideal platform for ease of data reuse and data citation. Datasets in the CyVerse Curated Data site can store very large datasets that are difficult to transfer, upload, and download across different computers and platforms. CyVerse Curated data is accessible to CyVerse's suite of large-scale computational analysis resources, allowing users to seamlessly analyze, manage, and publish new results.
Before you start
========================
Before you begin, review these related pages:
- |Is Data Commons Curated Data right for my data?|
- |Permanent Identifier FAQs|
Next Steps:
========================
2. `Organize data <organize.html>`_
3. `Add metadata <metadata.html>`_
4. `Submit request <submit.html>`_
5. `After publication <after.html>`_
Additional information, help
=============================
----
|Home_Icon|_
`Learning Center Home <http://learning.cyverse.org/>`_
.. Comment: Place Images Below This Line
use :width: to give a desired width for your image
use :height: to give a desired height for your image
replace the image name/location and URL if hyperlinked
.. |Clickable hyperlinked image| image:: ./img/IMAGENAME.png
:width: 500
:height: 100
.. _CyVerse logo: http://learning.cyverse.org/
.. |Static image| image:: ./img/IMAGENAME.png
:width: 25
:height: 25
.. Comment: Place URLS Below This Line
# Use this example to ensure that links open in new tabs, avoiding
# forcing users to leave the document, and making it easy to update links
# In a single place in this document
.. |DOI| raw:: html
<a href="https://www.doi.org/" target="blank">DOI</a>
.. |Is Data Commons Curated Data right for my data?| raw:: html
<a href="https://github.com/ramonawalls/DOI_request_quickstart" target="blank">Is Data Commons Curated Data right for my data?</a>
.. |Permanent Identifier FAQs| raw:: html
<a href="https://github.com/ramonawalls/DOI_request_quickstart" target="blank">Permanent Identifier FAQs</a>
.. |Requesting a permanent identifier| raw:: html
<a href="https://wiki.cyverse.org/wiki/display/DC/Requesting+a+Permanent+Identifier+in+the+Data+Commons" target="blank">Requesting a permanent identifier</a>
| 31.261905 | 582 | 0.702589 |
65f5d7c0aeaf689cac783c1e7de4f40ece2c34f6 | 9,611 | rst | reStructuredText | specs/pike/implemented/placement-project-user.rst | uggla/nova-specs | 793dd029b6afe9956432f3cc42ea89f4d5e458eb | [
"CC-BY-3.0"
] | 44 | 2015-01-29T20:10:45.000Z | 2020-12-21T15:17:53.000Z | specs/pike/implemented/placement-project-user.rst | uggla/nova-specs | 793dd029b6afe9956432f3cc42ea89f4d5e458eb | [
"CC-BY-3.0"
] | 1 | 2018-10-11T19:03:42.000Z | 2018-10-11T19:03:42.000Z | specs/pike/implemented/placement-project-user.rst | uggla/nova-specs | 793dd029b6afe9956432f3cc42ea89f4d5e458eb | [
"CC-BY-3.0"
] | 35 | 2015-05-05T05:33:09.000Z | 2022-01-25T17:30:51.000Z | ..
This work is licensed under a Creative Commons Attribution 3.0 Unported
License.
http://creativecommons.org/licenses/by/3.0/legalcode
=========================================
Add project/user association to placement
=========================================
https://blueprints.launchpad.net/nova/+spec/placement-project-user
This cycle we are changing the quota system to count resources to check
quota instead of tracking usage and reservations separately. As things
currently stand, we must query cell tables to count things like cores
and ram to check against quota limits. There are a couple of problems
with the current approach:
1. Querying all cells for instances owned by a project and summing their
cores and ram counts is not efficient.
2. Quota usage becomes effectively "freed" if contact with one or more
cells is lost for any reason, until the cells return.
To address these problems, we propose adding project and user associations
to placement for consumers.
Problem description
===================
With the current resource counting approach, placement allocated resources
such as cores and ram must be counted by querying for instances owned by
a project in all cells and summing their cores and ram. The counts could
be more efficiently obtained if placement stored project/user associations
for resource consumers and we could query placement for allocations based
on project/user and resource classes.
There is also the problem of relying on cell databases for allocated
resource counts. If the API cell loses contact with a cell for some reason
(network issue, cell maintenance, transient cell database issue, etc), the
resources for that cell cannot be counted. The down cell's resources then
become omitted from the counted usage for the project/user, allowing them
to allocate additional resources in other cells in the meantime. If and when
the down cell returns, the project/user could then have allocated more
resources than their allowed quota limit.
Use Cases
---------
As an administrator of an OpenStack multiple cell environment, it's important
that my users not be able to exceed their allocated quota limits when cells are
down.
Proposed change
===============
Add a ``consumers`` table for placement that stores project/user associations
for consumers with fields: consumer_id, project_id, user_id::
CREATE TABLE consumers (
id INT UNSIGNED NOT NULL AUTOINCREMENT PRIMARY KEY,
consumer_id VARCHAR(36) NOT NULL,
project_id VARCHAR(255) NOT NULL,
user_id VARCHAR(255) NOT NULL,
INDEX (project_id, consumer_id),
INDEX (project_id, user_id, consumer_id)
);
The records should have the same lifetime as ``allocations`` records.
The queries for usages for a project/user will look like::
GET /usages?project_id=<uuid>
GET /usages?project_id=<uuid>&user_id=<uuid>
In placement, when a query is received it will look up the consumer_ids and
matching allocations by querying the ``consumers`` table joined with the
``allocations`` table on consumer_id and return the summarized usages.
After the usages are returned from placement, the quota counting code can use
them to check against quota limits.
Alternatives
------------
Another way to associate project/user with allocations would be to add
project_id and user_id columns to the ``allocations`` table. It would be more
direct than creating a ``consumers`` table with the associations but it
wouldn't be as generic. A ``consumers`` table could potentially be used for
queries other than just allocations.
Data model impact
-----------------
The following data model changes will be needed:
* New models for: ``Consumer``
* New database table for ``Consumer``
* Database migration will be needed to add the ``consumers`` table to the
schema.
REST API impact
---------------
A new REST resource: ``/usages`` will be added and the GET method will accept
query strings in the URI called 'project_id' and 'user_id' that will return
usages matching the project_id and user_id. A usage is a sum of allocations
that match the project_id and user_id, per resource class. The addition of the
REST resource will require a new placement API microversion.
Example::
GET /usages?project_id=<uuid>
The response would be::
200 OK
Content-Type: application/json
{
"usages": {
"VCPU": 2,
"MEMORY_MB": 1024,
"DISK_GB": 50,
...
}
}
The PUT method of ``/allocations/{consumer_uuid}`` will be changed to accept
'project_id' and 'user_id' as required properties on payload as part of the
same new placement API microversion described earlier. They are considered to
be required because allocations are going to be written by either a human/user
or on behalf of a human/user, as a privileged API action. In the case of the
resource tracker, the project_id and user_id are easily obtained from the
Instance object.
Example::
ALLOCATION_SCHEMA = {
"type": "object",
"properties": {
"allocations": {
"type": "array",
"items": {
"type": "object",
"properties": {
"resource_provider": {
"type": "object",
"properties": {
"uuid": {
"type": "string",
"format": "uuid"
}
},
"additionalProperties": False,
"required": ["uuid"]
},
"resources": {
"type": "object",
"patternProperties": {
"^[0-9A-Z_]+$": {
"type": "integer",
"minimum": 1,
}
},
"additionalProperties": False
}
},
"required": [
"resource_provider",
"resources"
],
"additionalProperties": False
}
},
"project_id": {
"type": "string",
"minLength": 1,
"maxLength": 255
},
"user_id": {
"type": "string",
"minLength": 1,
"maxLength": 255
}
},
"required": [
"allocations",
"project_id",
"user_id"
],
"additionalProperties": False
}
Security impact
---------------
None.
Notifications impact
--------------------
None.
Other end user impact
---------------------
None.
Performance Impact
------------------
Performance of quota resource counting should be more efficient with the new
API over querying all cells for instances owned by a project and iterating
over them, summing the cores and ram values. Instead of N database queries
for N cells, there will be one database query by placement of consumers
associated with a project/user joined on allocations to get the matching
allocations, which will be summed to represent usages. Performance will also be
improved in that cells being temporarily down will no longer have the potential
for end users to exceed allowed quota limits.
Other deployer impact
---------------------
None.
Developer impact
----------------
None.
Implementation
==============
Assignee(s)
-----------
Primary assignee:
melwitt
Other contributors:
None
Work Items
----------
* Fix bug 1679750 where allocations are not cleaned up upon local delete
https://bugs.launchpad.net/nova/+bug/1679750
* Create database migration that creates the ``consumers`` table
* Update AllocationList object to read/write the ``consumers`` table
* Add a new REST resource: ``/usages`` for the placement REST API to query
usages by project_id and user_id as part of a new placement API microversion
* Add 'project_id' and 'user_id' as required properties on the allocations PUT
request schema as part of the same new placement API microversion
* Update the resource tracker to send project_id and user_id when setting
allocations in placement
* Bump the service version and add a conditional for whether to call placement
for counting cores and ram usage, based on the service version. During an
upgrade, old computes will be writing allocations without project_id and
user_id, so we can't rely on placement for usage until all computes have been
upgraded. Existing allocation records will self-heal when upgraded computes
update them as part of the nova-compute periodic task:
update_available_resource.
Dependencies
============
The quota counting spec is a foundation for this work, since the need for the
project/user association and updates to the allocations REST API is based on
counting resources for checking quota.
* http://specs.openstack.org/openstack/nova-specs/specs/pike/approved/cells-count-resources-to-check-quota-in-api.html
Testing
=======
New unit tests for the migration and changes to the AllocationList object will
be added. Gabbi functional tests will be added to test the new request
parameters in the allocations REST API and the new ``/usages`` REST resource.
Documentation Impact
====================
The placement-api-ref will be updated to document the new ``/usages`` REST
resource and the new required request parameters for the PUT method of the
``/allocations/{consumer_uuid}`` REST API.
References
==========
* http://specs.openstack.org/openstack/nova-specs/specs/pike/approved/cells-count-resources-to-check-quota-in-api.html
History
=======
.. list-table:: Revisions
:header-rows: 1
* - Release Name
- Description
* - Pike
- Introduced
| 31.10356 | 118 | 0.679638 |
837646b3f7224f6ecdb449a4e95d2a28af71f4be | 4,586 | rst | reStructuredText | docs/installation/prerequirements.rst | rhertzog/mirrorbrain | 76f2909e33004a7f5e0dd52b816881eb9fbd4246 | [
"Apache-2.0"
] | 71 | 2015-06-05T07:52:13.000Z | 2022-03-12T07:40:19.000Z | docs/installation/prerequirements.rst | rhertzog/mirrorbrain | 76f2909e33004a7f5e0dd52b816881eb9fbd4246 | [
"Apache-2.0"
] | 181 | 2015-06-05T00:42:22.000Z | 2022-02-23T10:36:46.000Z | docs/installation/prerequirements.rst | rhertzog/mirrorbrain | 76f2909e33004a7f5e0dd52b816881eb9fbd4246 | [
"Apache-2.0"
] | 25 | 2015-06-11T19:16:41.000Z | 2022-03-12T07:40:19.000Z | .. _prerequirements:
Prerequirements
===============
General
-------
The file tree to be served needs to be accessible locally by the Apache that
runs mod_mirrorbrain. (See the `FAQ`_ as well as
:ref:`initial_configuration_file_tree`.)
The hardware needs are mediocre; MirrorBrain needs few resources.
.. _`FAQ`: http://mirrorbrain.org/faq/#does-a-copy-of-the-mirrored-content-have-to-be-kept-locally
Apache
------
A recent enough version of the Apache HTTP server is required. **2.2.6** or
later should be used. In addition, the apr-util library should be **1.3.0**
or newer, or at least a not-too-old **1.2.x** release. This is because the `DBD
database pool functionality`_ was developed mainly around 2006 and 2007, and
reached production quality at the time. This will mean that you have to upgrade
Apache when installing on an oldish enterprise platform.
.. _`DBD database pool functionality`: http://apache.webthing.com/database/
Status of Apache version on individual platforms
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
openSUSE/SLE
Sufficiently new, since openSUSE 11.0 and SLE11. SLE11 does not ship
the required PostgreSQL database adapter. The one from openSUSE 11.1 would work.
Current and stable Apache for openSUSE/SLE can always be found here:
http://download.opensuse.org/repositories/Apache/
CentOS 5/RHEL
Ancient Apache. It *might* work or not -- you might need to get a
newer one. Feedback would be appreciated!
Debian
The Apache in *Lenny* (or newer) is fine. The version in *Etch* was too old.
Ubuntu
Apache is new enough and known to work at least since *9.04*.
Arch Linux
Has a new enough Apache.
Gentoo
Has a new enough Apache.
Frontend (mod_mirrorbrain, the redirector)
------------------------------------------
* if geographical mirror selection is going to be used, `mod_geoip`_ and `libGeoIP`_
are required.
* If `mod_geoip`_ is used, it needs to be version 1.2.0 or newer. See
http://mirrorbrain.org/issues/issue16
* `mod_form`_, plus a `patch preserving the arguments that it parses`_ for
other modules, like mod_autoindex.
* if you want to compile with the optional memcache support (there
should not be reason for it, though), you would need
libapr_memcache, `mod_memcache`_, `memcache`_ daemon
.. _`mod_form`: http://apache.webthing.com/mod_form/
.. _`mod_geoip`: http://www.maxmind.com/app/mod_geoip
.. _`libGeoIP`: http://www.maxmind.com/app/c
.. _`mod_memcache`: http://code.google.com/p/modmemcache/
.. _`memcache`: http://www.danga.com/memcached/
.. _`patch preserving the arguments that it parses`: https://build.opensuse.org/source/Apache:Modules/apache2-mod_form/mod_form.c.preserve_args.patch?rev=40cbd37223a3593d7d66aacc389d716e
Database
--------
* `PostgreSQL`_
* mod_mirrorbrain, the core of MirrorBrain, is not really bound to a particular
database; you could use MySQL just as well, SQLite, or Oracle - everything that the
Apache DBD API has a driver for. The admin framework and tool set
however is currently provided for PostgreSQL only. Therefore, it doesn't make sense
to use a different database, unless you are prepared to extend MirrorBrain, or have
a special setup in mind (like, integrating MirrorBrain with some existing database).
* `mod_asn`_ is optional, and needed only for refined mirror selection and full
exploitation of network locality. It works only with PostgreSQL as database.
It needs a data type for PostgreSQL called "ip4r" that needs to be installed
additionally.
The question whether you should (or should not) extend MirrorBrain with mod_asn
is discussed in the section :ref:`installing_mod_asn`.
If you intend to install it, confer to `its documentation`_ and `its prerequirements`_).
.. _`PostgreSQL`: http://www.postgresql.org/
.. _`mod_asn`: http://mirrorbrain.org/mod_asn/
.. _`its documentation`: http://mirrorbrain.org/mod_asn/docs/
.. _`its prerequirements`: http://mirrorbrain.org/mod_asn/docs/installation/#prerequirements
Python and Perl modules
-----------------------
The toolset for database maintenance needs Python (an old 2.4.x is sufficient) and the following Python modules:
* :mod:`cmdln`
* :mod:`sqlobject`
* :mod:`psycopg2`
The following Perl modules are required:
* :mod:`Config::IniFiles`
* :mod:`libwww::perl`
* :mod:`DBD::Pg`
* :mod:`Digest::MD4`
* :mod:`Date::Parse`
(If you install MirrorBrain in pre-packaged form, all these requirements should
automatically be met.)
The following sections will guide you through installing the various components.
| 34.742424 | 186 | 0.730266 |
45ed05123546172b6d021122c85c110c279474db | 376 | rst | reStructuredText | doc/showcase/further<br>nested"document.rst | mgeier/insipid-sphinx-theme | 6731e346936ca17e84958c484d7603873ece9822 | [
"BSD-2-Clause"
] | 25 | 2020-08-10T06:28:13.000Z | 2022-03-24T13:22:46.000Z | doc/showcase/further<br>nested"document.rst | mgeier/insipid-sphinx-theme | 6731e346936ca17e84958c484d7603873ece9822 | [
"BSD-2-Clause"
] | 23 | 2020-08-05T18:16:55.000Z | 2022-03-21T20:05:53.000Z | doc/showcase/further<br>nested"document.rst | mgeier/insipid-sphinx-theme | 6731e346936ca17e84958c484d7603873ece9822 | [
"BSD-2-Clause"
] | 6 | 2020-11-23T09:40:51.000Z | 2021-09-15T20:21:50.000Z | Some text before section title.
Further<br>Nested"Document
==========================
This is a nested document within a :doc:`nested document <nested document>`.
To check whether HTML escaping works, both the file name and the title contain
strange characters.
The double quotes character in the title is only problematic when
:confval:`smartquotes` is set to ``False``.
| 28.923077 | 78 | 0.728723 |
dcf953d44242a534adb32e4fbabc9098de06aaf1 | 63 | rst | reStructuredText | doc/doc_src/lib/ids.rst | adian98/https-ids | a35d52091a332156383d4f6be11e05de866cbd33 | [
"BSD-3-Clause"
] | 1 | 2020-04-09T07:20:09.000Z | 2020-04-09T07:20:09.000Z | doc/doc_src/lib/ids.rst | adian98/https-ids | a35d52091a332156383d4f6be11e05de866cbd33 | [
"BSD-3-Clause"
] | null | null | null | doc/doc_src/lib/ids.rst | adian98/https-ids | a35d52091a332156383d4f6be11e05de866cbd33 | [
"BSD-3-Clause"
] | 2 | 2015-07-30T08:50:21.000Z | 2020-04-09T07:20:06.000Z | =======
lib/ids
=======
.. automodule :: lib.ids
:members: | 10.5 | 24 | 0.460317 |
e22c08f377addf4f0cf8780d5d83f56fb72b4e01 | 1,265 | rst | reStructuredText | vehicle/OVMS.V3/components/vehicle_track/docs/index.rst | Daisy000888/Open-Vehicle-Monitoring-System-3 | f6121dddb9171bed44de4053c4a99512ce8e32ed | [
"MIT"
] | 322 | 2017-06-12T16:56:49.000Z | 2022-03-27T15:46:38.000Z | vehicle/OVMS.V3/components/vehicle_track/docs/index.rst | Daisy000888/Open-Vehicle-Monitoring-System-3 | f6121dddb9171bed44de4053c4a99512ce8e32ed | [
"MIT"
] | 426 | 2017-08-30T04:47:34.000Z | 2022-03-25T21:01:11.000Z | vehicle/OVMS.V3/components/vehicle_track/docs/index.rst | Daisy000888/Open-Vehicle-Monitoring-System-3 | f6121dddb9171bed44de4053c4a99512ce8e32ed | [
"MIT"
] | 194 | 2017-07-03T23:34:08.000Z | 2022-03-16T09:09:22.000Z | =================
Tracking Vehicles
=================
Vehicle Type: **XX**
The track vehicle will be documented here.
----------------
Support Overview
----------------
=========================== ==============
Function Support Status
=========================== ==============
Hardware Any OVMS v3 (or later) module. Vehicle support: Not widely tested, but should be all.
Vehicle Cable OBD-II to DB9 Data Cable for OVMS (1441200 right, or 1139300 left), or any cable proving power
GSM Antenna 1000500 Open Vehicles OVMS GSM Antenna (or any compatible antenna)
GPS Antenna 1020200 Universal GPS Antenna (SMA Connector) (or any compatible antenna)
SOC Display No
Range Display No
GPS Location Yes (from modem module GPS)
Speed Display Yes (from modem module GPS)
Temperature Display No
BMS v+t Display No
TPMS Display No
Charge Status Display No
Charge Interruption Alerts No
Charge Control No
Cabin Pre-heat/cool Control No
Lock/Unlock Vehicle No
Valet Mode Control No
Others None
=========================== ==============
| 36.142857 | 122 | 0.525692 |
00417c05acf5af8d7e934b548d74e6b4cc0a7e78 | 282 | rst | reStructuredText | docs/source/api/timer.rst | onkwon/libabov | 54e54f42666dc3549c10dad905a14867283de294 | [
"MIT"
] | 2 | 2021-04-14T09:22:51.000Z | 2021-04-15T17:27:58.000Z | docs/source/api/timer.rst | onkwon/libabov | 54e54f42666dc3549c10dad905a14867283de294 | [
"MIT"
] | 62 | 2021-03-30T11:38:05.000Z | 2021-06-02T02:20:24.000Z | docs/source/api/timer.rst | onkwon/halmcu | 54e54f42666dc3549c10dad905a14867283de294 | [
"MIT"
] | 1 | 2021-04-10T19:09:04.000Z | 2021-04-10T19:09:04.000Z | Timer
=====
.. image:: ../assets/images/timer.svg
Examples
--------
.. literalinclude:: ../../../examples/peripheral/timer_capture.c
:language: C
HAL
---
.. doxygenfile:: halmcu/hal/timer.h
:project: halmcu
LL
--
.. doxygenfile:: halmcu/periph/timer.h
:project: halmcu
| 14.1 | 64 | 0.634752 |
0d857fc83be347272b016294f08a5a960f9665da | 327 | rst | reStructuredText | docs/src/en/profiles/vendor-Protei.rst | xUndero/noc | 9fb34627721149fcf7064860bd63887e38849131 | [
"BSD-3-Clause"
] | 1 | 2019-09-20T09:36:48.000Z | 2019-09-20T09:36:48.000Z | docs/src/en/profiles/vendor-Protei.rst | ewwwcha/noc | aba08dc328296bb0e8e181c2ac9a766e1ec2a0bb | [
"BSD-3-Clause"
] | null | null | null | docs/src/en/profiles/vendor-Protei.rst | ewwwcha/noc | aba08dc328296bb0e8e181c2ac9a766e1ec2a0bb | [
"BSD-3-Clause"
] | null | null | null | .. _profiles-vendor-Protei:
======
Protei
======
.. toctree::
:titlesonly:
:glob:
/profiles/Protei.*
`Protei.*` family of profiles support various
`Protei <https://www.protei.ru/>`_
network equipment.
Supported Platforms
-------------------
.. include:: ../include/auto/supported-vendor-platforms-PROTEI.rst
| 15.571429 | 66 | 0.629969 |
6b70aaf5996dc48ed0707fd744c6b71dc52001ab | 2,209 | rst | reStructuredText | docs/models.rst | fizista/django-revisions | 1a18ea3bb620c9cc79d75148d90b90b318cf7562 | [
"BSD-2-Clause-FreeBSD"
] | 6 | 2015-11-05T11:48:46.000Z | 2021-04-14T07:10:16.000Z | docs/models.rst | fizista/django-revisions | 1a18ea3bb620c9cc79d75148d90b90b318cf7562 | [
"BSD-2-Clause-FreeBSD"
] | null | null | null | docs/models.rst | fizista/django-revisions | 1a18ea3bb620c9cc79d75148d90b90b318cf7562 | [
"BSD-2-Clause-FreeBSD"
] | 1 | 2019-02-13T21:01:48.000Z | 2019-02-13T21:01:48.000Z | Caveats when working with ``VersionedModel``
============================================
References to bundles or specific versions
------------------------------------------
A foreign key to a versioned object will always point to a specific
version and not the bundle as a whole. Sometimes, however, it's useful to be able
to have a reference to the *bundle* and not a specific version — every revision of "client"
that's tied to a "project", say.
Provided you're accessing a piece of versioned content through a reference from another
model, you can get the latest revision of that reference with the ``get_latest_revision`` method.
The other way around is easy too. Say you have an Author model that refers to a versioned Story
model. On instances, you can simply use ``story.related_author_set`` (instead of ``story.author_set``)
to access all authors across versions and regardless of which specific version or versions an
author is linked to.
A side note: why you shouldn't use Django's to_field to reference content bundles
---------------------------------------------------------------------------------
In Django 1.0 you used to be able to abuse foreign keys to allow for
pseudo-foreign key references to a *bundle* instead of a specific version.
class Instructions(models.Model):
# dit om een model te testen gerelateerd aan de bundel
story = models.ForeignKey(Story, to_field='id')
Because ``VersionedModel.latest`` is the default manager for versioned content,
such a foreign key attribute would then return the latest revision of the bundle
even though the bundle id field is shared among revisions.
However, in Django 1.2, this no longer works, because foreign keys should by their
very nature only reference unique fields. See
http://groups.google.com/group/django-users/browse_thread/thread/fcd3915a19ae333e
and
http://code.djangoproject.com/ticket/11702
for more information.
Adding your own managers
------------------------
If you add your own managers to an object, make sure to add revisions.managers.LatestManager()
back in, preferably as the first and thus default manager. You'll probably also want to
add django.db.managers.Manager() back in, as `objects`. | 48.021739 | 102 | 0.718425 |
56e9e115c14c7b2ad2b96e34f86b08d243ab2d91 | 886 | rst | reStructuredText | docs/generated/aries_cloudagent.protocols.basicmessage.rst | euroledger/aries-cloudagent-python | caf457276b19df374c16c2890e1c7e4914f46254 | [
"Apache-2.0"
] | 2 | 2019-10-10T16:33:01.000Z | 2019-10-10T19:22:17.000Z | docs/generated/aries_cloudagent.protocols.basicmessage.rst | euroledger/aries-cloudagent-python | caf457276b19df374c16c2890e1c7e4914f46254 | [
"Apache-2.0"
] | 5 | 2019-10-13T01:28:48.000Z | 2019-10-21T20:10:47.000Z | docs/generated/aries_cloudagent.protocols.basicmessage.rst | euroledger/aries-cloudagent-python | caf457276b19df374c16c2890e1c7e4914f46254 | [
"Apache-2.0"
] | 4 | 2019-07-09T20:41:03.000Z | 2021-06-06T10:45:23.000Z | aries\_cloudagent\.protocols\.basicmessage package
==================================================
.. automodule:: aries_cloudagent.protocols.basicmessage
:members:
:undoc-members:
:show-inheritance:
Subpackages
-----------
.. toctree::
aries_cloudagent.protocols.basicmessage.handlers
aries_cloudagent.protocols.basicmessage.messages
Submodules
----------
aries\_cloudagent\.protocols\.basicmessage\.message\_types module
-----------------------------------------------------------------
.. automodule:: aries_cloudagent.protocols.basicmessage.message_types
:members:
:undoc-members:
:show-inheritance:
aries\_cloudagent\.protocols\.basicmessage\.routes module
---------------------------------------------------------
.. automodule:: aries_cloudagent.protocols.basicmessage.routes
:members:
:undoc-members:
:show-inheritance:
| 23.945946 | 69 | 0.597065 |
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