---
layout: post
title: Petit déjeuner
description: animatic storyboard for Lalux
date: '2019-10-29 10:10:12 +0100'
categories:
- Storyboards
- Animation
- Advertising
---
Lalux Petit Déjeuner, storyboard, directed by Nico Galoux, produced by HUGGGY.


All Classes
ApplicationInterface
ColdItem
ColdTruck
ConsoleView
CSVException
DeliveryException
Item
Main
Manifest
OrdinaryTruck
SalesSelection
Stock
StockException
StockType
Store
Truck
Utilities


A project specifically devoted to raising awareness and providing resources for and about the aromantic community.
Find Out MoreCheck out our page on aro history! It includes firsthand accounts, how terms came to be, history of the aromantic flag, and even a timeline on people who may have identified as aromantic before the term existed (the primary example of this is unmarried people, as this does apply to a lot of aros) and how those people were treated.
Check it out!We have a spotlight on different artists in our Arts and Lit section. Contact us if you would like your work featured!
We're always willing to answer questions and listen to concerns.
Want attention for your survey or project? Let us know!
This website is intended as a resource and source of positivity. If you see something wrong or have something to contribute, contact us today!
Have a question, concern, comment, or suggestion? Want to start a project or survey? Have something to add? I'd love to hear it!
@thearomanticinitiative


We're dedicated to making sure your family or business is as comfortable as possible
Like us on Facebook for our current offers and deals!
Whether you need to repair, replace, upgrade or even add a new system, out products are designed to make you more comfortable. We have the knowledge and expertise to help you choose the right heating and air conditioning system to meet your needs so that you benefit from increased efficiency, reliability, and control of your home or businesses' indoor environment.
Our goal is to keep you warm and comfortable through the winter months. We know which products and systems will work best for you. Our recommendations will always keep your requirements and budget in mind. We'll respond to your requests and act quickly when you call. Nothing is more important than your peace of mind when the weather is cold.
Central air conditioning helps keep you environment cool and reduces humidity levels. As the central air conditioning system draes air out of various rooms in your house or business through return air ducts, the air is pulled through an air filter, which removed airborne particles such as dust and lint. The filtered air is then routed to air supply ductwork that carries it back to the rooms.
Our goal is to keep you warm and comfortable through the winter months. We know which products and systems will work best for you. Our recommendations will always keep your requirements and budget in mid. We'll respond to your requests and act quickly when you call. Nothing is more important than your peace of mind when the weather is cold.


# -*- coding: utf-8 -*-
"""
Nearest Centroid Classification
"""
# Author: Robert Layton<EMAIL_ADDRESS># Olivier Grisel<EMAIL_ADDRESS>#
# License: BSD 3 clause
import warnings
import numpy as np
from scipy import sparse as sp
from ..base import BaseEstimator, ClassifierMixin
from ..metrics.pairwise import pairwise_distances
from ..preprocessing import LabelEncoder
from ..utils.validation import check_array, check_X_y, check_is_fitted
from ..utils.sparsefuncs import csc_median_axis_0
from ..utils.multiclass import check_classification_targets
class NearestCentroid(BaseEstimator, ClassifierMixin):
"""Nearest centroid classifier.
Each class is represented by its centroid, with test samples classified to
the class with the nearest centroid.
Read more in the :ref:`User Guide <nearest_centroid_classifier>`.
Parameters
----------
metric : string, or callable
The metric to use when calculating distance between instances in a
feature array. If metric is a string or callable, it must be one of
the options allowed by metrics.pairwise.pairwise_distances for its
metric parameter.
The centroids for the samples corresponding to each class is the point
from which the sum of the distances (according to the metric) of all
samples that belong to that particular class are minimized.
If the "manhattan" metric is provided, this centroid is the median and
for all other metrics, the centroid is now set to be the mean.
shrink_threshold : float, optional (default = None)
Threshold for shrinking centroids to remove features.
Attributes
----------
centroids_ : array-like, shape = [n_classes, n_features]
Centroid of each class
Examples
--------
>>> from sklearn.neighbors.nearest_centroid import NearestCentroid
>>> import numpy as np
>>> X = np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])
>>> y = np.array([1, 1, 1, 2, 2, 2])
>>> clf = NearestCentroid()
>>> clf.fit(X, y)
NearestCentroid(metric='euclidean', shrink_threshold=None)
>>> print(clf.predict([[-0.8, -1]]))
[1]
See also
--------
sklearn.neighbors.KNeighborsClassifier: nearest neighbors classifier
Notes
-----
When used for text classification with tf-idf vectors, this classifier is
also known as the Rocchio classifier.
References
----------
Tibshirani, R., Hastie, T., Narasimhan, B., & Chu, G. (2002). Diagnosis of
multiple cancer types by shrunken centroids of gene expression. Proceedings
of the National Academy of Sciences of the United States of America,
99(10), 6567-6572. The National Academy of Sciences.
"""
def __init__(self, metric='euclidean', shrink_threshold=None):
self.metric = metric
self.shrink_threshold = shrink_threshold
[docs] def fit(self, X, y):
"""
Fit the NearestCentroid model according to the given training data.
Parameters
----------
X : {array-like, sparse matrix}, shape = [n_samples, n_features]
Training vector, where n_samples in the number of samples and
n_features is the number of features.
Note that centroid shrinking cannot be used with sparse matrices.
y : array, shape = [n_samples]
Target values (integers)
"""
if self.metric == 'precomputed':
raise ValueError("Precomputed is not supported.")
# If X is sparse and the metric is "manhattan", store it in a csc
# format is easier to calculate the median.
if self.metric == 'manhattan':
X, y = check_X_y(X, y, ['csc'])
else:
X, y = check_X_y(X, y, ['csr', 'csc'])
is_X_sparse = sp.issparse(X)
if is_X_sparse and self.shrink_threshold:
raise ValueError("threshold shrinking not supported"
" for sparse input")
check_classification_targets(y)
n_samples, n_features = X.shape
le = LabelEncoder()
y_ind = le.fit_transform(y)
self.classes_ = classes = le.classes_
n_classes = classes.size
if n_classes < 2:
raise ValueError('y has less than 2 classes')
# Mask mapping each class to its members.
self.centroids_ = np.empty((n_classes, n_features), dtype=np.float64)
# Number of clusters in each class.
nk = np.zeros(n_classes)
for cur_class in range(n_classes):
center_mask = y_ind == cur_class
nk[cur_class] = np.sum(center_mask)
if is_X_sparse:
center_mask = np.where(center_mask)[0]
# XXX: Update other averaging methods according to the metrics.
if self.metric == "manhattan":
# NumPy does not calculate median of sparse matrices.
if not is_X_sparse:
self.centroids_[cur_class] = np.median(X[center_mask], axis=0)
else:
self.centroids_[cur_class] = csc_median_axis_0(X[center_mask])
else:
if self.metric != 'euclidean':
warnings.warn("Averaging for metrics other than "
"euclidean and manhattan not supported. "
"The average is set to be the mean."
)
self.centroids_[cur_class] = X[center_mask].mean(axis=0)
if self.shrink_threshold:
dataset_centroid_ = np.mean(X, axis=0)
# m parameter for determining deviation
m = np.sqrt((1. / nk) - (1. / n_samples))
# Calculate deviation using the standard deviation of centroids.
variance = (X - self.centroids_[y_ind]) ** 2
variance = variance.sum(axis=0)
s = np.sqrt(variance / (n_samples - n_classes))
s += np.median(s) # To deter outliers from affecting the results.
mm = m.reshape(len(m), 1) # Reshape to allow broadcasting.
ms = mm * s
deviation = ((self.centroids_ - dataset_centroid_) / ms)
# Soft thresholding: if the deviation crosses 0 during shrinking,
# it becomes zero.
signs = np.sign(deviation)
deviation = (np.abs(deviation) - self.shrink_threshold)
deviation[deviation < 0] = 0
deviation *= signs
# Now adjust the centroids using the deviation
msd = ms * deviation
self.centroids_ = dataset_centroid_[np.newaxis, :] + msd
return self
[docs] def predict(self, X):
"""Perform classification on an array of test vectors X.
The predicted class C for each sample in X is returned.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
Returns
-------
C : array, shape = [n_samples]
Notes
-----
If the metric constructor parameter is "precomputed", X is assumed to
be the distance matrix between the data to be predicted and
``self.centroids_``.
"""
check_is_fitted(self, 'centroids_')
X = check_array(X, accept_sparse='csr')
return self.classes_[pairwise_distances(
X, self.centroids_, metric=self.metric).argmin(axis=1)]


--- layout: post title: 'budget bites: magic peanut sauce' date: 2011-09-19 22:22:09.000000000 -04:00 type: post published: true status: publish categories: - budget bites - recipes - savory - vegan - vegetarian tags: - budget bites meta: _edit_last: '1' author: login: sophie email<EMAIL_ADDRESS>display_name: Pika first_name: '' last_name: '' ---
I swear, this sauce is like magic: put it anything from tofu to chicken to rice to noodles (cold peanut noodles, mmm!) to crudités for an instant pick-me-up! And so easy too.
Magic Peanut Sauce
(So this isn't really a recipe, I know...but you really don't need one, I swear! Just eyeball it and give it a taste...trust me :) The amounts are up to you! )
Pictured above is one of my favorite busy weeknight meals: steamed broccoli, tofu, and the aforementioned sauce!


Poll boost helps Ardern with post-surgery recovery
by Ben McKayWellington: New polling results have given a boost to recovering New Zealand prime minister Jacinda Ardern as she recovers from surgery.
Ardern went under the knife and a general anaesthetic at the weekend to extract an impacted wisdom tooth.
The surgery caused Ardern to miss Monday's cabinet meeting but a spokesperson for the prime minister said she was "working from home for now but doing fine".
Her mood will have been brightened by her popularity in a survey by first-time New Zealand pollsters YouGov.
The British company, which has partnered with news outlet Stuff, registered Labour support at 41 per cent, ahead of the National opposition, which is the biggest party in the current parliament, on 38 per cent.
Significantly, both Ardern's coalition partners - the Greens and NZ First - are on eight per cent.
Extrapolated across New Zealand's complicated mixed-member proportional system, the most likely result in the 2020 election would see Labour able to form a majority government with just one of those partners.
"It's really encouraging to see all of the coalition parties up when we compare the numbers against the last election," Ardern told Stuff.
"We've taken on some big challenges but we're making good progress - I'd like to think this poll reflects that."
National rejected the results, which are markedly different from two polls taken in October by television news outlets Newshub and 1News.
All three polls show Ardern to be crushing opposition leader Simon Bridges on personal favourability - a gulf that Labour will look to exploit during the election year before a poll expected around September 2020.
Ardern is expected to return to full duties midweek before giving the keynote address at this weekend's Labour conference in Whanganui on Sunday.
The Stuff-YouGov poll (November) had Ardern's Labour at 41 per cent, Nationals 38, Greens 8, NZ First 8, and the right-wing ACT Party at 2.
The Newshub-Reid poll published in October had Labour at 42, National 44, Greens 6, NZ First 4, ACT 1. The 1News-Colmar Brunton poll, also published in October, put Labour on 40, National 47, Greens 7, NZ First 4, ACT 1.
AAP


Can You Spot the Mouse Hiding Among the Squirrels?
Gergely Dudás has mastered the art of the hidden image puzzle. The Hungarian artist, who goes by the name Dudolf on the web, is famous for his Where's Waldo?-style brainteasers that embed camouflaged objects into playful illustrations. His latest scene is one of his most challenging creations yet.
The picture below shows dozens of brown squirrels crowded into a tight frame. If you study the image closely enough, you'll notice that one of the squirrels is actually a mouse. Like all of the hidden images in Dudolf's puzzles, the mouse is designed to blend in with its surroundings, making it almost impossible to spot at first glance.
If you've been staring at the image for a minute or two with no luck, here's a tip: Check the ears to find the animal that doesn't belong. And if that clue doesn't prove helpful, scroll to the bottom of this webpage for the answer.
Dudolf has created visual brainteasers for every time of year. After completing the puzzle above, see if you can find the ghost among the rabbits, the sheep in the Santa Clauses, and the heart in the snails.


It is a shame that most people will never explore the limitations of their bodies. Triathletes are not exempt from this. You can climb the same old hill, year after year, or you can conquer the mountain of uncertainty that will require you to explore your mental and physical limits. Do you want to finish, or do you want to race? Do you want to finish, or do you want to win? Ironman is a costly event that requires many long hours of training and time away from family, friends, and social events. You owe it to yourself, family, and friends to go ALL IN on this grueling event. While treading water in Kailua Bay, waiting for the canon to set you free, remember: This effort is for the rest of your life!
Training scenarios: Train like you fight. You will not rise to the occasion.  If you don’t push the limits in training, then you will not start the race knowing what you are truly capable of.
“Race Pace” is a term that is used to describe your best effort on any given day. Suffer more in training, and bleed less in the fight. Racing is a reward for the training you have done. Digging deep in training will make race day seem like a break from continuously training in a state of fatigue. Learn to become comfortable in an uncomfortable environment. Carfrae: “Most people are unwilling to hurt to the next level.” Run 5:30/mile intervals on the track so that I can run 7:00/mile pace in the Ironman. Never miss an opportunity to push yourself to an uncomfortable state in training. Hold yourself accountable: If you are able to push the tempo in a bigger gear, then shift up. When things start to feel uncomfortable in the run, analyze what is happening with your form- “Head to Toe, Treat as You Go:” Are my shoulders tensing up? Am I running tall? Am I closing the angle in my elbows? Am I slouching in the hips? Am I leading with the knees? Am I bouncing? Is my cadence slowing? Am I leaning forward at the ankles? Fix it! There is no such thing as quitting: Quitting, or a bad day, results in loss of life in combat. Quitting in training will make it easy to quit in the race. If you make a nutritional mistake in training, and hit the wall, drag yourself home at a reduced tempo, but don’t quit.Live in the moment: You cannot control the past or the future, only what is happening right now.
Treat every interval as if it were the last one of the set. Focus ONLY on the interval that you are completing at that moment. Thinking about “how many more” intervals you have to do will not allow you to put the quality in each and every effort. Thinking about how badly you want to get off the bike and start the run will not help your ability to remain focused on the bike effort. Never miss an opportunity to get faster, stronger, better than you were yesterday. There should be no question on race morning whether you have done enough to be there. Every training session is another opportunity to perform better than you did last time. Down hill sections on your bike ride is an opportunity to hammer downhill in the aero bars, thus enhancing your bike handling skills rather than lying up. You will see the look of defeat on the faces of those who are left wondering on race morning if they have earned the right to be there. This will not be you.
 The body does not know what a mile is; however, it does react to time. Do not allow an electronic gadget determine your ability on race day. Data is fine in the lab, but labs do not mimic race day. The body is never fully recovered (at least it shouldn’t it be) during training; so don’t allow a gadget to dictate your ability when you are fully tapered for an Ironman. The body will tell you all you need to know in order to set the pace. You must explore limits in training- the worst that can happen if you blow up in a training event is that you’ll learn where to set the bar during your next session. Let the rabbits go- you will see them later on the course. Train your stomach: No matter how long the session, utilize the same calorie concentration for each bike and run event. During the swim portion, there are No calorie bottles during the race, so don’t use them at the pool. (Train like you fight) 70.3 races provide great opportunities to explore nutritional details. Utilize what is on the course. Keep it simple. Two bottle set-up: One with calories, one with water. No Calories w/out water, no water w/out calories. Salt tablets, regardless of conditions. Breakfast is the same every day of the year- same on race morning. No surprises on race morning.Ironman is an individual event, so the majority of your training should be done on your own. (Train like you fight) There is more than enough time to socialize at the coffee shop when the training is complete. Don’t look for answers: Once you find what works FOR YOU, stick to the formula. Consistency in your training plan will out-perform any new “whiz-bang” idea in Triathlete Magazine. Don’t be tempted by the “Good-Idea Fairy.” She is out there, and she knows that Triathletes will buy anything. There is no one-size-fits-all plan online that will get you to Kona.Every workout has a specific goal. Long bike and run are the only workouts that do not require specific instructions. Quality, Quality, Quality.
Got this gold from here!


Credits
Title Screen Music Background by Timothy
Chicken Sound Background by GAMEBANANA
Gameplay Music Background by Derek & Brandon Fiechter
Chicken Assets by Pjager


Id: 247
Name: Mrs. Poopybutthole
Status: Alive
Species: Poopybutthole
Type:
Gender: Female
OriginName: unknown
OriginUrl:
LocationName: unknown
LocationUrl:
Image: https://rickandmortyapi.com/api/character/avatar/247.jpeg
Episode: ['https://rickandmortyapi.com/api/episode/31']
Url: https://rickandmortyapi.com/api/character/247
Created: 2017-12-30T18:10:48.293Z


module Def:sig
..end
The definition is the only way for a block to perform some
side effects.
typet =
def term
val create : ?tid:tid -> var -> exp -> t
create ?tid x exp
creates definition x := exp
val lhs : t -> var
returns the right hand side of a definition
val rhs : t -> exp
val with_lhs : t -> var -> t
updates the right hand side of a definition
val with_rhs : t -> exp -> t
val map_exp : t -> f:(exp -> exp) -> t
map_exp def f
applies f
to a rhs
of def
and returns
an updated definition.val substitute : t -> exp -> exp -> t
substitute def x y
substitutes x
by y
in the right hand
side of a definition def
val free_vars : t -> Var.Set.t
free_vars def
returns a set of free variables, that occurs
on the right hand side of definition def
. See Exp.free_vars
for more information.include Bap.Std.Regular


Topicstarter
An option to filter servers by total ticket amount would be awesome if possible
BrainFooLong
Administrator
Isn't possible yet (without many extra requests fired to battlelog servers).
Maybe DICE would implement something like this.
Greetz


Health Students Helping In Pandemics
Hi! We are HealthSHIP, a student-led social movement rooted in compassion for the health of our communities.
We aim to support health and social care staff with everyday tasks from caring responsibilities to grocery shopping. We believe the impact of COVID-19 will span the entirety of our social fabrics and that each have a role to play in the hindrance of this pandemic.
Students may not be able to work on the front line yet, but we can support those that do.
Organiser extraordinaire. Second year medical student. Otherwise known as @_banandra.
Tech and stuff. First year medical student. Often found talking to himself as @quackophage.
A very special thanks to John Day for our AWS hosting and to RS for all their guidance and support.
Many thanks to Google Cloud for donating access to their hosting services.
We have built this from the ground up and have not outsourced any of the development of this site. Therefore users can be reassured that their information will never be used for commercial purposes.


I’m A Celeb's Roman Kemp branded 'racist' in deleted Twitter row over Korean pop group BTS
The radio presenter became embroiled in a social media showdown after calling the music of Korean pop group BTS music 'noise'
by Louise Randell, https://www.mirror.co.uk/authors/louise-randell/I'm A Celebrity 2019 star Roman Kemp was branded "racist" in an explosive Twitter row last year over comments he made about South Korean pop group BTS.
Back in 2018, Roman, 26, became embroiled in a social media showdown after calling BTS' music "noise" during his Capital breakfast show.
Around 60 complaints were made to media watchdog Ofcom, and Roman was embroiled in a storm on Twitter as he was branded "racist" and "xenophobic" by furious listeners.
At the time, Roman hit back at the haters who criticised him online but he has since deleted his responses.
In an exchange with the star, one Twitter user wrote: "You mean to say, it’s alright to be racist towards other languages? I don’t think it’s 'normal'."
Roman's responses to the user have now been wiped.
Another BTS fan wrote: "This fandom has been professional! We are open for criticism of their music.
"We understand that not all people will like BTS, but being xenophobic and racist is not acceptable in this society."

"I hope you've since taught him better because honestly it was embarrassing to hear that from a grown adult in 2018. Thanks xx
The revelation comes as the radio presenter issued a public apology for "offensive" posts that had previously appeared on his social media.
It is not known if the posts he is referring too were shared as part of the race row or if they were related to another subject.
Despite not sharing details of his tweets, Roman insisted he was "shocked and appalled" by some of the "offensive" messages he'd posted in the past.
He insisted he'd cleaned up his account and deleted the offending tweets, telling followers he was "ashamed" and "truly, deeply and utterly sorry".
Roman's race row kicked off in September 2018 when he was talking about BTS' single IDOL - a collaboration with Nicki Minaj .
He said: "That was BTS and Nicki Minaj, that noise you were just hearing there...
His co-host Sonny Jay then chipped in: "I thought there [were] construction workers outside.”
It unfiriated fans of the band as well as many Capital listeners, and Roman had to issue an apology on Twitter.
The statement, which has since been deleted, read: "The comments I have made have been widely twisted and labelled as something that they are not
"I will accept 100% responsibility if some of the views I put across have been deemed offensive and to those I can only apologise. No offence was ever meant.
“It’s never my intention to garner negative energy for anyone let alone within the world of music that I love so dearly.
"However comments have started to now be aimed toward not only myself but my family and loved ones, I would please ask for this to stop.
"I am sorry to anyone who may have been offended by any comment I have made toward BTS.
"I ask all BTS fans to know in their hearts that I have never thought anything negative of the band nor would I wont to stop the joy of spreading music."
Bosses at Ofcom assessed the comp[laints about Roman's comments, but declined to take any further action.
A spokesperson for the organisation said at the time: "We considered complaints about the presenter’s description of a song by the Korean group BTS.
“In our view, the presenter was expressing a personal opinion about the music, which was not racially motivated.”
Roman is believed to be flying to Australia this weekend ahead of the I'm A Celebrity launch.
He's not been officially confirmed by ITV, but was featured in a leaked line-up yesterday and his appearance on the show has been rumoured for weeks.
The headline-grabbing apology Roman made today comes two years after another I'm A Celebrity star, Jack Maynard, was kicked off the show over his dark Twitter history.

ITV bosses booted him off the show with immediate effect.
Do you have a story to sell? Get in touch with us at<EMAIL_ADDRESS>or call us direct 0207 29 33033


So I was really bored up at college this past summer. I had tried duster before when I was high, and I loved it. I did it quite a bit when I was blazed, but that was ok, just a little bit once and a while.
 It was fun and I enjoyed, but just wait. I'm getting ready for bed the next night. I start walking to my bedroom in my apartment, then it came back to haunt me. I started getting really fuzzy vision, like when I was taking hits off the can of duster. I started stumbling very badly, I couldn't breathe, and I finally fell over flat on my face. I had blacked out, some time went by, I don't remember how much, I lifted my head, and stood up to go to bed. This time I tried moving slower, I was going to get a glass of water, I could not, the same feeling came back over me. I just went to my bed and finally gained my composure back and went to sleep.
Worst experience ever!!! I honestly felt like like I was dying, and I probably could have that night. I have tried it couple of times since, but I get scared every time I do it, cause I remember those horrible after effects.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


host_reboot
Function - Reboot this host.
SYNOPSIS
kern_return_t host_reboot (host_priv_t host_priv, int options);
PARAMETERS
- host_priv
-
[in host-control send right]
The control port the host to be re-booted.
- options
-
[in scalar]
Reboot options. See \*L
\*O for details.
DESCRIPTION
The host_reboot function reboots the specified host.
NOTES
If successful, this call will not return.
RETURN VALUES
Only generic errors apply.
RELATED INFORMATION
None.


Car Inventory
Identities
Car Inventory
Blockchain
Cars
Add Manufacture
Car Model
Available Count
×
Car Model
Count
Add


Hearthstone Data
by the community,
for the community
The Data Drinker Project
Hearthstone Data Discussion
Download & Use Replay Data


mdslides - Generate HTML5-Presentations from Markdown Files
Generate from External Url
Example
Rules
- Use # for the prensentation title and ## for the section titles
- The first image will be used as background image
- If no text is given after the section headline, it will be used as shout
Credits
Created by DracoBlue (@DracoBlue) in December 2012. Uses showdown.js (for markdown to html conversion), jquery (for dom manipulation) and shower (for the awesome template and html5 slides logic).


Core Modules
Core modules are optional and can be replaced by any module as long as it provides the same interface.
Some are optional, like the REPL module. If you don't need or don't want a REPL you can remove it from the list of coremodules
using the configuration object that you pass to the application instance during the initialization of your program, in the entry point file.
The most likely scenario is that you might want to enable it during development but not on production.
This is the list of core modules bundled with core.io:
- Logger
- Errors
- Monitoring
- Dispatcher
- REPL
Core modules are loaded first and made available for all user modules. You can override this list using a coremodules
key in the configuration object you initialize your instance with:
const config = Application.loadConfig({
coremodules: ['./logger', './errors', './dispatcher']
}, true);
const app = new Application({config});
Here we removed the monitoring and the REPL.
Dispatcher
REPL
Applications start a repl instance which exposes the context in the app
variable.
════════════════════════════════════════════════════════════════════╗
║ ║
║ poke-repl remote console √ ║
║ ║
║ All connections are monitored and recorded ║
║ Disconnect IMMEDIATELY if you are not an authorized user ║
╚════════════════════════════════════════════════════════════════════╝
REPL Session Information
Name : application-core
Version : 0.0.0
Environment : development
App Kernel > app.getUid()
'jxo6adbd-ts7wnaivr0e'
Logger
core.io provides a logger to the application context as context.logger
and is the module with the highest priority, meaning it will be available on first run. Under the hood the logger wraps [winston][winston] and extends it with some extra features:
- child loggers
- filters
- the ability to mute all output
- the ability to have focus on child logger
- it can optionally wrap the console so that it has the same format
- it can disable
console
output
When a module is loaded a child logger is created and assigned to the module. You access child loggers via the context.logger.getLogger(loggerId)
method, where loggerId
is the name of the logger.
Each call to getLogger
will return the same instance, and it's output is identified by the logger's name:
INFO [23:28:48] ├── core : Created logger "core"...
INFO [23:28:48] ├── app : Created logger "app"...
INFO [23:28:48] ├── console : Created logger "console"...
WARN [23:28:48] ├── core : Register: we are going to override plugin logger
INFO [23:28:48] ├── core : Mount Handler: module "errors" mounted...
INFO [23:28:48] ├── core : Mount Handler: module "dispatcher" mounted...
INFO [23:28:48] ├── dispatcher : Created logger "dispatcher"...
DEBUG [23:28:48] ├── dispatcher : Module "dispatcher" ready...
Each application has at least two loggers; core and app. Using the built in logger is optional, however if you decide to log from within your modules it's a good idea to use the same provided logger.
TIP: When you are initializing your modules, in the init
function, you can access the logger using the context.getLogger
You can wrap the console
so it has the same output as the regular logger output and also you can apply filters.
You can have an active logger, so that only the log output of a given logger is shown.
You can mute all output.
Options:
- muteConsole: Uses [noop-console][noop-console] module.
- wrapConsole
- handlingExceptions
You can set these values by default using the ./config/logger.js
configuration file or you can interact with the logger through the REPL.
Configuration
The default configuration for the logger includes three different transports:
- Console: log level silly.
- File Exceptions: catch and log uncaughtException events
- File Debug: Log level debug. Disabled by default in production.
To override the default configuration you can create a ./config/logger.js
configuration file.


I am born and raised in the Philippines!
If you answer No, to the question if I like cats, that's pretty amazing!
I do have a princess, her name is Anika and she is growing up way too fast!
I love colors Teal and Mustard Yellow!
I love sharing my beautiful smile too!


For some reason, when Cowinde came to wake her in the gray before dawn, Egwene felt refreshed despite her dreams. Refreshed and ready to see what she could learn in the city. One long yawn and stretch, and she was on her feet, humming as she washed and dressed hurriedly, hardly taking the time to brush her hair properly. She would have hurried away from the tents without wasting time on breakfast, but Sorilea saw her, and that put an abrupt end to that notion. Which turned out to be just as well.
“You should not have left the sweat tent so soon,” Amys told her, taking a bowl of porridge and dried fruit from Rodera. Close to two dozen Wise Ones had crowded into Amys’s tent, and Rodera, Cowinde and a white-robed man named Doilan, another Shaido, were scurrying to serve them all. “Rhuarc had much to say about your sisters. Perhaps you can add more.”
After months of pretense, Egwene did not need to think to know she meant the Tower embassy. “I will tell you what I can. What did he say?”
For one thing, that there were six Aes Sedai, and two of them Red, not one—Egwene could not believe the arrogance, or perhaps stupidity, of Elaida to have sent any at all—but at least a Gray was in charge. The Wise Ones, most lying in a large circle like the spokes of a wheel, some standing or kneeling in the spaces between, turned their eyes to Egwene as soon as the list of names was done.
“I’m afraid I only know two of them,” she said carefully. “There are a good many Aes Sedai, after all, and I haven’t been a full sister long enough to know many.” Heads nodded; they accepted that. “Nesune Bihara is fair-minded—she listens to all sides before reaching a conclusion—but she can find even the smallest flaw in what you


[%settitle Resource Index%]
[%file newheader%] [%file newnavbar%]This document provides links to the various supporting profiles within the context of the DAF FHIR IG. The supporting profiles are defined as those which are used within other DAF profiles. DAF use cases will not be querying the resources represented by the supporting profiles directly. For e.g DAF Organization profile and DAF Practitioner profiles are used in other DAF profiles of resources such as Patient, Medication Administration, Condition etc.
| DAF Supporting profile | Purpose | Base FHIR Resource |
|---|---|---|
| DAFPractitioner | This profile is used to represent a medical practitioner who delivers various clinical services. | Practitioner |
| DAFOrganization | This profile is used to represent an organization where clinical services or delivered or is somehow related to the treatment of the patient. | Organization |
| DAFLocation | This profile is used to represent a location associated with the delivery of clinical services to a patient. | Location |
| DAFSubstance | This profile is used to represent either a substance which is part of a drug or is a substance which is known to cause allergies to a patient. | Substance |
| DAFSpecimen | This profile is used to represent a specimen that is used to perform lab tests or other clincal observations against. | Specimen |
| DAFRelatedPerson | This profile is used to represent a person who is related to a patient. | RelatedPerson |


The Transportation Safety Center (TSC) provides a foundation and mechanism to facilitate the development of sustainable systems to improve highway safety and achieve the goal of zero deaths on Florida’s roads.
The TSC was establish to promote the highway safety initiatives through applied and theoretical safety-related research projects; workforce development and training of current transportation professionals; academic program enhancements for college-attending students in transportation and safety-related disciplines; technical assistance about practical application of effective infrastructure and non-infrastructure safety countermeasures; collaboration with state and local highway safety professionals to address prioritized safety areas through coalitions; outreach to local government municipalities to promote funding programs that utilizes federal-aid funds for safety improvements on locally owned and maintained roads; and knowledge transfer support through technology to build a comprehensive program serving more stakeholders and customers.


import { Logger } from "./Logger" import { APISocket } from './APISocket'; import axios from 'axios'; /** * @class * @hideconstructor * @classdesc * Guests are temporary users that are granted access to one group {@link Chat} using the chat's {@link Chat#guest_url guest URL}. */ export class Guest { constructor(options) { /** * @readonly * @prop id * @type {String} * @summary * The ID of the user, assigned by the API * */ this.id = "" /** * @prop first_name * @type {String} * @summary * The first name of the guest. */ this.first_name = "" /** * @prop last_name * @type {String} * @summary * The last name of the guest. */ this.last_name = "" /** * @prop avatar * @type {String} * @summary * The URL of the guest's avatar. */ this.avatar = "" /** * @prop email * @type {String} * @summary * The email address of the guest. */ this.email = "" /** * @prop chat_id * @type {String} * @summary * The {@link Chat#id Chat ID} this guest is valid for. */ this.chat_id = "" /* * @prop extensionSecret * @type {String} * @summray * The user's password for SIP phone registration. */ this.extension_secret = ""; /** * @prop role * @type {String} * @summary * The user's role on the team, possibilities are `admin` or `member` */ this.role = "" /** * @readonly * @prop teams * @type {Team[]} * @summary * A list of teams this user is on */ this.teams = [] /** * @prop caller_id_name * @type {String} * @summary * When making outbound calls, this will be the name field of the Caller ID, visible to the other caller. If this is blank * (default), the name will default to {@linkcode Team#caller_id_name Team.caller_id_name}. */ this.caller_id_name = "" /** * @prop caller_id_number * @type {String} * @summary * When making outbound calls, this will be the number field of the Caller ID, visible to the other caller. If this is blank (default), the name will default to {@linkcode Team#caller_id_number Team.caller_id_number}. */ this.caller_id_number = "" // Assign in passed values for(let [key, value] of Object.entries(options)) { if (this.hasOwnProperty(key)) { this[key] = value; } else { // Logger.info("Key not found in Guest", key, value); } } } /** * @summary * Check if a guest exists on a given team. * * @description * Guests are unique to each team, so a Team or TeamID must also be supplied, and can only * be called after logging-in. This is called automatically by {@link Chat#inviteGuest `Chat.inviteGuest()`}. * * @param {Object} opts Options for this request * @param {String} opts.email Email of the guest to look for * @param {Team|String} opts.team The team to look for this guest in. Either a Team object or a Team ID * * @returns {Promise} Promise that will resolve with a boolean representing if a team with that name exists or not, or rejected with the error as the first argument * * @example * Guest.exists({ email<EMAIL_ADDRESS>team: myTeam }) * .then((guestExists) => console.log(guestExists ? 'guest exists!' : 'no guest with that email')) * .catch((err) => console.error(err)) */ static async exists(opts) { let options = Object.assign({}, { email: '', team: '', }, opts); let exists_res; let response_code; if (!options.email) throw Error('Guest.exists requires an email (opts.email)'); if (!options.team) throw Error('Guest.exists requires a Team object or a team ID (opts.team)'); if (typeof options.email != "string") throw TypeError("Guest.exists email must be a string, received", typeof options.email) if (typeof options.team != "string" && options.team.constructor.name != "Team") { throw TypeError("Guest.exists team must be either a team ID or a Team object, received", typeof options.team); } // If user passed a Team object, pull the ID from that if (options.team.constructor.name == "Team") options.team = options.team.id try { exists_res = await APISocket.post(`team/${options.team}/guest/exists`, { emails: [options.email] }); } catch(err) { return new Error(err); } if ( typeof exists_res == "object" && Object.prototype.hasOwnProperty.call(exists_res, 'existing') ) { return !!exists_res.existing.length; } } }


Conway's Game of Life provided the opportunity to finally get up and write some Matrix classes I had been meaning to draft for various JS purposes. Unfortunately it also introduced me to the reason why Knuth said "Premature optimization is the root of all evil." The algorithm is implemented by a so-called "Sparse Matrix", anticipating most of the values being undefined or some other default value, like 0, and only saving the ones that are necessary. This is a favored technique for a lot of matrix operations, but in this case, it is strictly overkill, as it allows the animations to render insanely fast... too fast to easily enjoy and watch.
Drawing the "life" with the Canvas API also provided a lot of challenges, because it is new to me! Not only is throttling it a bit difficult, so it prefers to render at V8's default speed of "blazing fast" even when a slower render would be desireable, but while seemingly simple, it has very particular rules about how things are drawn on it and how the canvas can be cleared to set up the next draw. In addition, it turns out that implementing relatively simple concepts like "detect a click on this location" is not necessarily native to it, unlike with most HTML elements.
Conway's Game of Life provided the opportunity to finally get up and write some Matrix classes I had been meaning to draft for various JS purposes. Unfortunately it also introduced me to the reason why Knuth said "Premature optimization is the root of all evil." The algorithm is implemented by a so-called "Sparse Matrix", anticipating most of the values being undefined or some other default value, like 0, and only saving the ones that are necessary. This is a favored technique for a lot of matrix operations, but in this case, it is strictly overkill, as it allows the animations to render insanely fast... too fast to easily enjoy and watch.
Drawing the "life" with the Canvas API also provided a lot of challenges, because it is new to me! Not only is throttling it a bit difficult, so it prefers to render at V8's default speed of "blazing fast" even when a slower render would be desireable, but while seemingly simple, it has very particular rules about how things are drawn on it and how the canvas can be cleared to set up the next draw. In addition, it turns out that implementing relatively simple concepts like "detect a click on this location" is not necessarily native to it, unlike with most HTML elements.


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java.lang.Object State StateGame
public class StateGame
StateGame is a mode of the program where the user can play the game of Pacman various maps StateGame is a subclass of State
| Field Summary | |
|---|---|
private AIManager |
ai
|
private int |
currentLevel
|
private boolean |
gamePaused
|
private int |
livesRemaining
|
private Map |
map
|
private int |
mapHeight
|
private java.lang.String |
mapName
|
private int |
mapWidth
|
private long |
pauseTime
|
private Player |
player
|
private int |
sessionScore
|
| Fields inherited from class State |
|---|
game, STATE_DEAD, STATE_EDITOR, STATE_EXITING, STATE_GAME, STATE_MENU, STATE_SCOREBOARD |
| Constructor Summary | |
|---|---|
StateGame(Game g)
StateGame Constructor |
| Method Summary | |
|---|---|
void |
end()
Player has died or the Supervisor has decided to change the state abruptly |
int |
getSessionScore()
Get the current session score. |
void |
keyPressed(java.awt.event.KeyEvent e)
Start automove in certain direction |
void |
logic()
Main game logic for rendering and processing. |
void |
lose()
Player has died, reset() if lives remain. |
void |
reset()
Reset the state of the game entirely (level 1) |
void |
respawn(boolean nextLevel)
Respawns the player after a death or win. |
void |
win()
Player has won, move to the next level Called by logic() |
| Methods inherited from class State |
|---|
getGame, keyReleased, keyTyped |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Field Detail |
|---|
private Player player
private Map map
private AIManager ai
private java.lang.String mapName
private int currentLevel
private int sessionScore
private int livesRemaining
private boolean gamePaused
private long pauseTime
private int mapWidth
private int mapHeight
| Constructor Detail |
|---|
public StateGame(Game g)
g
- Reference to the game supervisor| Method Detail |
|---|
public int getSessionScore()
win()
,
lose()
public void reset()
reset
in class State
State.reset()
public void respawn(boolean nextLevel)
nextLevel
- Moves to the next level and corresponding mappublic void logic()
logic
in class State
Game.mainThreadLoop()
,
State.logic()
public void end()
end
in class State
State.end()
public void win()
logic()
public void lose()
logic()
public void keyPressed(java.awt.event.KeyEvent e)
KeyListener.keyPressed(java.awt.event.KeyEvent)
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IOPERM
Section: Linux Programmer's Manual (2)Updated: 2007-06-15
Index Return to Main Contents
NAME
ioperm - set port input/output permissionsSYNOPSIS
#include <unistd.h> /* for libc5 */#include <sys/io.h> /* for glibc */
int ioperm(unsigned long from, unsigned long num, int turn_on);
DESCRIPTION
ioperm() sets the port access permission bits for the calling process for num bytes starting from port address from to the value turn_on. If turn_on is non-zero, the calling process must be privileged (CAP_SYS_RAWIO).Only the first 0x3ff I/O ports can be specified in this manner. For more ports, the iopl(2) system call must be used.
Permissions are not inherited by the child created by fork(2). Permissions are preserved across execve(2); this is useful for giving port access permissions to non-privileged programs.
This call is mostly for the i386 architecture. On many other architectures it does not exist or will always return an error.
RETURN VALUE
On success, zero is returned. On error, -1 is returned, and errno is set appropriately.ERRORS
- EINVAL
- Invalid values for from or num.
- EIO
- (on PowerPC) This call is not supported.
- ENOMEM
- Out of memory.
- EPERM
- The calling process has insufficient privilege.
CONFORMING TO
ioperm() is Linux-specific and should not be used in programs intended to be portable.NOTES
Libc5 treats it as a system call and has a prototype in <unistd.h>. Glibc1 does not have a prototype. Glibc2 has a prototype both in <sys/io.h> and in <sys/perm.h>. Avoid the latter, it is available on i386 only.SEE ALSO
iopl(2), capabilities(7)COLOPHON
This page is part of release 3.22 of the Linux man-pages project. A description of the project, and information about reporting bugs, can be found at http://www.kernel.org/doc/man-pages/.
Index
This document was created by man2html, using the manual pages.
Time: 05:33:04 GMT, December 24, 2015


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java.lang.Object java.io.InputStream org.apache.poi.poifs.filesystem.DocumentInputStream
public class DocumentInputStream
This class provides methods to read a DocumentEntry managed by a Filesystem instance.
| Constructor Summary | |
|---|---|
DocumentInputStream(DocumentEntry document)
Create an InputStream from the specified DocumentEntry |
|
DocumentInputStream(POIFSDocument document)
Create an InputStream from the specified Document |
| Method Summary | |
|---|---|
int |
available()
Returns the number of bytes that can be read (or skipped over) from this input stream without blocking by the next caller of a method for this input stream. |
void |
close()
Closes this input stream and releases any system resources associated with the stream. |
void |
mark(int ignoredReadlimit)
Marks the current position in this input stream. |
boolean |
markSupported()
Tests if this input stream supports the mark and reset methods. |
int |
read()
Reads the next byte of data from the input stream. |
int |
read(byte[] b)
Reads some number of bytes from the input stream and stores them into the buffer array b. |
int |
read(byte[] b,
int off,
int len)
Reads up to len bytes of data from the input stream into an array of bytes. |
void |
reset()
Repositions this stream to the position at the time the mark method was last called on this input stream. |
long |
skip(long n)
Skips over and discards n bytes of data from this input stream. |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
|---|
public DocumentInputStream(DocumentEntry document) throws java.io.IOException
document
- the DocumentEntry to be read
java.io.IOException
- if the DocumentEntry cannot be opened
(like, maybe it has been deleted?)public DocumentInputStream(POIFSDocument document) throws java.io.IOException
document
- the Document to be read
java.io.IOException
- if the DocumentEntry cannot be opened
(like, maybe it has been deleted?)| Method Detail |
|---|
public int available() throws java.io.IOException
available
in class java.io.InputStream
java.io.IOException
- on error (such as the stream has been
closed)public void close() throws java.io.IOException
close
in interface java.io.Closeable
close
in class java.io.InputStream
java.io.IOException
public void mark(int ignoredReadlimit)
The readlimit arguments tells this input stream to allow that many bytes to be read before the mark position gets invalidated. This implementation, however, does not care.
The general contract of mark is that, if the method markSupported returns true, the stream somehow remembers all the bytes read after the call to mark and stands ready to supply those same bytes again if and whenever the method reset is called. However, the stream is not required to remember any data at all if more than readlimit bytes are read from the stream before reset is called. But this stream will.
mark
in class java.io.InputStream
ignoredReadlimit
- the maximum limit of bytes that can be
read before the mark position becomes
invalid. Ignored by this
implementation.public boolean markSupported()
markSupported
in class java.io.InputStream
public int read() throws java.io.IOException
read
in class java.io.InputStream
java.io.IOException
public int read(byte[] b) throws java.io.IOException, java.lang.NullPointerException
If b is null, a NullPointerException is thrown. If the length of b is zero, then no bytes are read and 0 is returned; otherwise, there is an attempt to read at least one byte. If no byte is available because the stream is at end of file, the value -1 is returned; otherwise, at least one byte is read and stored into b.
The first byte read is stored into element b[0], the next one into b[1], and so on. The number of bytes read is, at most, equal to the length of b. Let k be the number of bytes actually read; these bytes will be stored in elements b[0] through b[k-1], leaving elements b[k] through b[b.length-1] unaffected.
If the first byte cannot be read for any reason other than end of file, then an IOException is thrown. In particular, an IOException is thrown if the input stream has been closed.
The read(b) method for class InputStream has the same effect as:
read(b, 0, b.length)
read
in class java.io.InputStream
b
- the buffer into which the data is read.
java.io.IOException
java.lang.NullPointerException
public int read(byte[] b, int off, int len) throws java.io.IOException, java.lang.NullPointerException, java.lang.IndexOutOfBoundsException
The definition of this method in java.io.InputStream allows it to block, but it won't.
If b is null, a NullPointerException is thrown.
If off is negative, or len is negative, or off+len is greater than the length of the array b, then an IndexOutOfBoundsException is thrown.
If len is zero, then no bytes are read and 0 is returned; otherwise, there is an attempt to read at least one byte. If no byte is available because the stream is at end of file, the value -1 is returned; otherwise, at least one byte is read and stored into b.
The first byte read is stored into element b[off], the next one into b[off+1], and so on. The number of bytes read is, at most, equal to len. Let k be the number of bytes actually read; these bytes will be stored in elements b[off] through b[off+k-1], leaving elements b[off+k] through b[off+len-1] unaffected.
In every case, elements b[0] through b[off] and elements b[off+len] through b[b.length-1] are unaffected.
If the first byte cannot be read for any reason other than end of file, then an IOException is thrown. In particular, an IOException is thrown if the input stream has been closed.
read
in class java.io.InputStream
b
- the buffer into which the data is read.off
- the start offset in array b at which the data is
written.len
- the maximum number of bytes to read.
java.io.IOException
java.lang.NullPointerException
java.lang.IndexOutOfBoundsException
public void reset()
The general contract of reset is:
All well and good ... this class's markSupported method returns true and this method does not care whether you've called mark at all, or whether you've exceeded the number of bytes specified in the last call to mark. We're basically walking a byte array ... mark and reset to your heart's content.
reset
in class java.io.InputStream
public long skip(long n) throws java.io.IOException
skip
in class java.io.InputStream
n
- the number of bytes to be skipped.
java.io.IOException
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II BUSINESS PERSPECTIVES IN THE HISTORY OF COMMUNICATIONS
III MEASUREMENT OF THE SPEED OF COMMUNICATIONS – METHODS AND SOURCES
IV OVERSEAS MAIL AND SPEED OF COMMUNICATIONS BEFORE 1815
The Great Innovation of Sailing on Schedule
Wind vs. Steam – a Decade of Struggle
Business Information and the Telegraph
VI THE WEST INDIES AND SOUTH AMERICA
Overnight Change from Sail to Steam
International Competition and the Influence of the Telegraph


I wrote this at the request of a teacher. One of her students was having trouble grasping patterns of words quickly, and she wanted something that might help him move past sounding out each individual syllable.
The entire concept for this application is hers. We had a few conversations, discussed what she wanted it to do, and it was up to me to make it a reality. I thought of using something like React for this project, and I’m sure that would have worked. But, in the end, I decided it was overkill for the scope of something like this.
I ended up implementing my own little component system. Everything runs in a single page and the individual "screens" are generated in JavaScript files and added to the DOM via jQuery. I also used Bootstrap for the UI.


--- title: Philosophy of integral psychotherapy | Therapy Minneapolis - Integral Psychotherapy menu: Philosophy breadcrumb: true ---
It is easy to lose one's sense of balance and serenity in the turbulence of 21st century American culture. But, "growth comes through struggle," as Martin Luther King once said. If we can gather the courage to face our difficulties, we can learn from them, come to understand ourselves better, and grow stronger, wiser, and more balanced. Having a patient, understanding, non-judgmental guide through this terrain can often help immeasurably.
Who looks outside dreams; who looks inside awakens.
-Carl Gustav Jung
Our work with clients is based upon the integration of a number of schools of psychology and other wisdom traditions.
These include:
However, despite this broad bed of psychological wisdom, recognition of the uniqueness of each individual is paramount. Because of this, we enter into work with each client with an open mind, a sense of humility, and a recognition that everyone holds their own keys to healing. We believe that with patient, caring collaboration, together we will find the right path.
...[M]edicine is and has always been an art... True art is creation, and creation is beyond all theories. That is why I say to any beginner: Learn your theories as well as you can, but put them aside when you touch the miracle of the living soul.


Gateway
BOT
19-Mar-19 10:43 PM
[dscrdvrsc] <Vycid> so actually no, they're not cards
[dscrdvrsc] <Vycid> they're socketed CPUs, although yes the cards do exist and I have a couple dozen gathering dust
[dscrdvrsc] <0x03> 'standard' amd64 type cpus?
[dscrdvrsc] <Vycid> About 80% of my hardware is actually ATX boards with radiators/water cooling. The other 20% is server blades
[dscrdvrsc] <0x03> or with bells and whistles?
[dscrdvrsc] <Vycid> Yep. I run rancherOS on them
[dscrdvrsc] <0x03> i guess the 'yep' matches the first of my 2 questions
(edited)
[dscrdvrsc] <Vycid> yeah, amd64
[dscrdvrsc] <0x03> how much is one of these?
[dscrdvrsc] <Vycid> but one major whistle: 16 gig of HBM2 on package
[dscrdvrsc] <0x03> and much more important, how much hashrate can you rip out of them
[dscrdvrsc] <Vycid> like literally under the CPU IHS
[dscrdvrsc] <0x03> faster than the "modern" architectures without north/southbridge?
[dscrdvrsc] <Vycid> heh, price depends on who you know and how much you buy
[dscrdvrsc] <0x03> because these usually have their mem channeled right into the cpu as well
[dscrdvrsc] <0x03> oh wow
[dscrdvrsc] <0x03> ridiculously faster
[dscrdvrsc] <Vycid> yeah around 500 GB/sec bandwidth
[dscrdvrsc] <Vycid> basically a GPU with CPU architecture
[dscrdvrsc] <0x03> aha, more speed by wider bus, so google tells me
(edited)
[dscrdvrsc] <Vycid> hashrate depends a ton on what algorithm and how well the miner is optimized for phi
[dscrdvrsc] <Vycid> It's pretty neat, I run the DDR4 slots totally empty
[dscrdvrsc] <0x03> heh. does the phi mem show up in the POST/uefi/whatnot?
[dscrdvrsc] <0x03> or does it boot with 0gb?
[dscrdvrsc] <0x03> because that probably looks ridiculous
[dscrdvrsc] <Vycid> huh that's a good question I don't remember
[dscrdvrsc] <Vycid> I think it does
[dscrdvrsc] <Vycid> The BIOS has several memory modes and I generally run it in the mode where it doesn't differentiate HBM2 from DDR4
[dscrdvrsc] <0x03> def. sounds like a toy for me
[dscrdvrsc] <Oink> Like running on only cache
[dscrdvrsc] <0x03> it's like having libvirt style powers
[dscrdvrsc] <0x03> but with real hw
[dscrdvrsc] <0x03> 'here, let me reboot quickly and shove in another cpu core'
[dscrdvrsc] <0x03> and that sounds like hell of a thing
[dscrdvrsc] <Oink> Nice to toy with....
[dscrdvrsc] <0x03> @Vycid did you try kvm/libvirt/something alike (besides docker) on these?
[dscrdvrsc] <0x03> .... can they have direct storage? per card?


|
EF_CoreDapperTuto
|
Sets the template for the read operations on the DB (Should be at Persistance layer) More...
Public Member Functions | |
| Task< IReadOnlyList< T > > | QueryAsync< T > (string sql, object param=null, IDbTransaction transaction=null, CancellationToken cancellationToken=default) |
| Asynchronously sends a plain string sql query through Dapper More... | |
| Task< T > | QueryFirstOrDefaultAsync< T > (string sql, object param=null, IDbTransaction transaction=null, CancellationToken cancellationToken=default) |
| Asynchronously sends a plain string sql query through Dapper, idealized to return a single record More... | |
| Task< T > | QuerySingleAsync< T > (string sql, object param=null, IDbTransaction transaction=null, CancellationToken cancellationToken=default) |
| Asynchronously sends a plain string sql query through Dapper, idealized to return a single record More... | |
Sets the template for the read operations on the DB (Should be at Persistance layer)
Definition at line 11 of file IApplicationReadDbConnection.cs.
| Task<IReadOnlyList<T> > EF_CoreDapperTuto.Domain.Interfaces.IApplicationReadDbConnection.QueryAsync< T > | ( | string | sql, |
| object | param = null , |
||
| IDbTransaction | transaction = null , |
||
| CancellationToken | cancellationToken = default |
||
| ) |
Asynchronously sends a plain string sql query through Dapper
| sql | A plain string sql query |
| param | An object containing a parametrized query procedure |
| transaction | Represents a transaction to be performed at a data source, and is implemented by .NET data providers that access relational databases. |
| cancellationToken | Propagates notification that operations should be canceled. |
| T | A generic type |
Implemented in EF_CoreDapperTuto.Persistence.Connections.ApplicationWriteDbConnection, and EF_CoreDapperTuto.Persistence.Connections.ApplicationReadDbConnection.
References EF_CoreDapperTuto.Domain.Interfaces.IApplicationReadDbConnection.QueryFirstOrDefaultAsync< T >(), and EF_CoreDapperTuto.Domain.Interfaces.IApplicationReadDbConnection.QuerySingleAsync< T >().
| Task<T> EF_CoreDapperTuto.Domain.Interfaces.IApplicationReadDbConnection.QueryFirstOrDefaultAsync< T > | ( | string | sql, |
| object | param = null , |
||
| IDbTransaction | transaction = null , |
||
| CancellationToken | cancellationToken = default |
||
| ) |
Asynchronously sends a plain string sql query through Dapper, idealized to return a single record
| sql | A plain string sql query |
| param | An object containing a parametrized query procedure |
| transaction | Represents a transaction to be performed at a data source, and is implemented by .NET data providers that access relational databases. |
| cancellationToken | Propagates notification that operations should be canceled. |
| T | A generic type |
Implemented in EF_CoreDapperTuto.Persistence.Connections.ApplicationWriteDbConnection, and EF_CoreDapperTuto.Persistence.Connections.ApplicationReadDbConnection.
Referenced by EF_CoreDapperTuto.Domain.Interfaces.IApplicationReadDbConnection.QueryAsync< T >().
| Task<T> EF_CoreDapperTuto.Domain.Interfaces.IApplicationReadDbConnection.QuerySingleAsync< T > | ( | string | sql, |
| object | param = null , |
||
| IDbTransaction | transaction = null , |
||
| CancellationToken | cancellationToken = default |
||
| ) |
Asynchronously sends a plain string sql query through Dapper, idealized to return a single record
| sql | A plain string sql query |
| param | An object containing a parametrized query procedure |
| transaction | Represents a transaction to be performed at a data source, and is implemented by .NET data providers that access relational databases. |
| cancellationToken | Propagates notification that operations should be canceled. |
| T | A generic type |
Implemented in EF_CoreDapperTuto.Persistence.Connections.ApplicationWriteDbConnection, and EF_CoreDapperTuto.Persistence.Connections.ApplicationReadDbConnection.
Referenced by EF_CoreDapperTuto.Domain.Interfaces.IApplicationReadDbConnection.QueryAsync< T >().


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Basic People Reading Skills
Openness / Yes- open hands
- uncrossed arms/legs
- unbuttoning jacket, removing clothing
- rubbing hands palm down on chest (honesty and sincerity)
- hands rubbing together (eagerness)
- tilted head, hand to cheek (attentiveness/interest)
- stroking chin (formulating decision)
- leaning forward/back (varied amounts of interest)
- direct eye contact (confidence)
- steepling fingers or hands together (higher the steeple = higher confidence)
- hands behind head (confidence)
- eyes dilated
- relaxed facial muscles
- Observe Their Basic Demeanor
- Everyone tends to wear their emotions on their face all the time, whether they know it or not.  If there's a smile on their face, we can usually tell if it's forced or genuine. Is their posture relaxed, or tense? Are they facing you straight on, or more diagonally? Imagine yourself facing someone directly, then do the same but be standing at an angle from them. It's easier to trust someone who is facing you.
- Ask Some Simple Questions that will have the Subject Saying Yes
- We tend to trust another person the more we agree, or say yes, to what they ask us. By simple, I don't mean 'is it daytime' when the sun is out. It's important to make the questions slightly personal, to engender trust from the subject. Perhaps something along the lines of (with a genuine smile on their face) 'I see you're quite happy or excited about the idea of something, yes?' (makes the subject focus even more on their happy mental topic) then, 'Do you usually feel even more excited when you are so focused on an idea that makes you happy?'.
- Mental Observations to Lead You into What to Say Next...
- You have taken note of their activities that say 'openness'. You have a general idea of their demeanor. You have asked at least 4 questions regarding that facial expression that has them in a good mood towards you specifically, and that they have answered 'yes' to, every time.
- You have probably noticed that they have also performed a few more of the Openness / Yes possibilities as soon as their trust level unconsciously increased. You are doing well so far in this easy and relaxed conversation.
- Here is a simple checklist that is easy to memorize.
- Look. Listen. Pay attention.


--- layout: post title: Brighton & Hove Issues date: 2005-02-17 00:00:00 categories: personal social ---
OK, here's the official invite to the Brighton & Hove Issues Forum. I'm ashamed to say that my involvement in this has been close-to-zero - i.e. turning up to an initial meeting and leaving early. But it's great to see this sort of thing actually happening: getting individuals engaging with government at the messy local level where Things Actually Happen.
"I am part of a team which is launching a new web site for everyone in
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The forum is an independent project, run by volunteers whose only interest
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your voice might be heard by people with the power to make a difference.
We'd like you to be one of the first group of Brighton and Hove people that
joins our new forum. It is easy to join. Sign-up on the web site now at:
http://e-democracy.org/brighton-hove
You can choose to participate via email or over the web. To take part, all
you need is an email address and access to the web - available free at your
local library. Please tell your friends about this new public forum."


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api.sensors package¶
Submodules¶
api.sensors.camera module¶
-
class
api.sensors.camera.
Camera
(name, platform)¶ Bases:
pioneer.das.api.sensors.sensor.Sensor
Camera sensor, expects ‘img’ datasource, intrinsics matrix and distortion coefficients
-
__init__
(name, platform)¶ Constructor.
- Parameters
name – the sensor’s name and position id, e.g. ‘eagle_tfc’
platform – the platform this sensor belongs to
factories – a dict containing one entry per datasource type, each entry’s value is a tuple containing (Sample-derived, optional_interpolator_function). For example, a factoryies dict could be {“ech”:(Echo, None), “sta”:(Sample, interpolators.linear_dict_of_float_interpolator)}
call_start – a callback to be called by Sensor.start() (e.g. to start an actual live sensor)
call_stop – similar to call_start
-
property
camera_matrix
¶ the 3x3 intrinsics matrix
See also: https://docs.opencv.org/4.0.0/d9/d0c/group__calib3d.html#ga3207604e4b1a1758aa66acb6ed5aa65d
- Type
np.ndarray
-
property
distortion_coeffs
¶ Nx1 distortion coefficient, refer to opencv documentation
See also: https://docs.opencv.org/4.0.0/d9/d0c/group__calib3d.html#ga3207604e4b1a1758aa66acb6ed5aa65d
- Type
np.ndarray
-
load_intrinsics
(intrinsics_config)¶ Looks for a pickle file containing intrinsics information for this sensor, e.g. ‘eagle_tfc.pkl’
- Parameters
intrinsics_config – path to folder containing this sensor’s intrinsics pickle file,
or relative to dataset path), e.g. '/nas/cam_intrinsics' or 'cam_intrinsics' ((absolute) –
-
api.sensors.carla_gps module¶
-
class
api.sensors.carla_gps.
CarlaGPS
(name, platform)¶ Bases:
pioneer.das.api.sensors.sensor.Sensor
-
__init__
(name, platform)¶ Constructor.
- Parameters
name – the sensor’s name and position id, e.g. ‘eagle_tfc’
platform – the platform this sensor belongs to
factories – a dict containing one entry per datasource type, each entry’s value is a tuple containing (Sample-derived, optional_interpolator_function). For example, a factoryies dict could be {“ech”:(Echo, None), “sta”:(Sample, interpolators.linear_dict_of_float_interpolator)}
call_start – a callback to be called by Sensor.start() (e.g. to start an actual live sensor)
call_stop – similar to call_start
-
api.sensors.carla_imu module¶
-
class
api.sensors.carla_imu.
CarlaEgomotionProvider
(referential_name: str, sensor, ds_type)¶ Bases:
pioneer.das.api.sensors.egomotion_provider.EgomotionProvider
-
__init__
(referential_name: str, sensor, ds_type)¶ Initialize self. See help(type(self)) for accurate signature.
-
get_Global_from_Ego_at
(ts: int, dtype=<class 'numpy.float64'>) → numpy.ndarray¶ Transform to map a point from world coords to EgomotionProdiver’s coords
-
-
class
api.sensors.carla_imu.
CarlaIMU
(name, platform)¶ Bases:
pioneer.das.api.sensors.sensor.Sensor
-
__init__
(name, platform)¶ Constructor.
- Parameters
name – the sensor’s name and position id, e.g. ‘eagle_tfc’
platform – the platform this sensor belongs to
factories – a dict containing one entry per datasource type, each entry’s value is a tuple containing (Sample-derived, optional_interpolator_function). For example, a factoryies dict could be {“ech”:(Echo, None), “sta”:(Sample, interpolators.linear_dict_of_float_interpolator)}
call_start – a callback to be called by Sensor.start() (e.g. to start an actual live sensor)
call_stop – similar to call_start
-
create_egomotion_provider
()¶
-
api.sensors.egomotion_provider module¶
-
class
api.sensors.egomotion_provider.
EgomotionProvider
(referential_name: str, subsampling: int = 100)¶ Bases:
object
-
__init__
(referential_name: str, subsampling: int = 100)¶ Initialize self. See help(type(self)) for accurate signature.
-
apply_trajectory
(trajectory: numpy.ndarray, points: numpy.ndarray) → numpy.ndarray¶
-
compute_tf_EgoZero_from_Sensor
(tf_Ego_from_Sensor: numpy.ndarray, reference_ts: int) → numpy.ndarray¶
-
compute_trajectory
(sorted_ts: numpy.ndarray, tf_Global_from_EgoZero: numpy.ndarray, dtype=<class 'numpy.float64'>) → numpy.ndarray¶ Trajectory of tf_EgoZero_from_Ego transforms
-
get_Global_from_Ego_at
(ts: int, dtype=<class 'numpy.float64'>) → numpy.ndarray¶ Transform to map a point from world coords to EgomotionProdiver’s coords
-
property
referential_name
¶
-
property
tf_Global_from_EgoZero
¶
-
api.sensors.encoder module¶
-
class
api.sensors.encoder.
Encoder
(name, platform)¶ Bases:
pioneer.das.api.sensors.sensor.Sensor
-
__init__
(name, platform)¶ Constructor.
- Parameters
name – the sensor’s name and position id, e.g. ‘eagle_tfc’
platform – the platform this sensor belongs to
factories – a dict containing one entry per datasource type, each entry’s value is a tuple containing (Sample-derived, optional_interpolator_function). For example, a factoryies dict could be {“ech”:(Echo, None), “sta”:(Sample, interpolators.linear_dict_of_float_interpolator)}
call_start – a callback to be called by Sensor.start() (e.g. to start an actual live sensor)
call_stop – similar to call_start
-
create_egomotion_provider
()¶
-
-
class
api.sensors.encoder.
WheelEgomotionProvider
(referential_name: str, sensor, ds_type)¶ Bases:
pioneer.das.api.sensors.egomotion_provider.EgomotionProvider
-
__init__
(referential_name: str, sensor, ds_type)¶ Initialize self. See help(type(self)) for accurate signature.
-
get_Global_from_Ego_at
(ts: int, dtype=<class 'numpy.float64'>) → numpy.ndarray¶ Transform to map a point from world coords to EgomotionProdiver’s coords
-
api.sensors.imu_egomotion_provider module¶
-
class
api.sensors.imu_egomotion_provider.
IMUEgomotionProvider
(referential_name: str, navposvel: pioneer.das.api.datasources.abstract_datasource.AbstractDatasource, ekfeuler: pioneer.das.api.datasources.abstract_datasource.AbstractDatasource, subsampling: int = 100)¶ Bases:
pioneer.das.api.sensors.egomotion_provider.EgomotionProvider
-
__init__
(referential_name: str, navposvel: pioneer.das.api.datasources.abstract_datasource.AbstractDatasource, ekfeuler: pioneer.das.api.datasources.abstract_datasource.AbstractDatasource, subsampling: int = 100)¶ Initialize self. See help(type(self)) for accurate signature.
-
get_Global_from_Ego_at
(ts: int, dtype=<class 'numpy.float64'>) → numpy.ndarray¶ override
-
api.sensors.imu_sbg_ekinox module¶
-
class
api.sensors.imu_sbg_ekinox.
ImuSbgEkinox
(name, platform)¶ Bases:
pioneer.das.api.sensors.sensor.Sensor
-
__init__
(name, platform)¶ Constructor.
- Parameters
name – the sensor’s name and position id, e.g. ‘eagle_tfc’
platform – the platform this sensor belongs to
factories – a dict containing one entry per datasource type, each entry’s value is a tuple containing (Sample-derived, optional_interpolator_function). For example, a factoryies dict could be {“ech”:(Echo, None), “sta”:(Sample, interpolators.linear_dict_of_float_interpolator)}
call_start – a callback to be called by Sensor.start() (e.g. to start an actual live sensor)
call_stop – similar to call_start
-
create_egomotion_provider
()¶
-
api.sensors.lca3 module¶
-
class
api.sensors.lca3.
LCA3
(name, platform)¶ Bases:
pioneer.das.api.sensors.lcax.LCAx
-
__init__
(name, platform)¶ Constructor.
- Parameters
name – the sensor’s name and position id, e.g. ‘eagle_tfc’
platform – the platform this sensor belongs to
factories – a dict containing one entry per datasource type, each entry’s value is a tuple containing (Sample-derived, optional_interpolator_function). For example, a factoryies dict could be {“ech”:(Echo, None), “sta”:(Sample, interpolators.linear_dict_of_float_interpolator)}
call_start – a callback to be called by Sensor.start() (e.g. to start an actual live sensor)
call_stop – similar to call_start
-
get_trace_smoothing_kernel
()¶ Get the convolution kernel for trace processing for Eagle
-
api.sensors.lcax module¶
-
class
api.sensors.lcax.
LCAx
(name, platform)¶ Bases:
pioneer.das.api.sensors.sensor.Sensor
LeddarTech LCAx family of sensors, expects ‘ech’, ‘sta’ and ‘cfg’ datasources
-
__init__
(name, platform)¶ Constructor.
- Parameters
name – the sensor’s name and position id, e.g. ‘eagle_tfc’
platform – the platform this sensor belongs to
factories – a dict containing one entry per datasource type, each entry’s value is a tuple containing (Sample-derived, optional_interpolator_function). For example, a factoryies dict could be {“ech”:(Echo, None), “sta”:(Sample, interpolators.linear_dict_of_float_interpolator)}
call_start – a callback to be called by Sensor.start() (e.g. to start an actual live sensor)
call_stop – similar to call_start
-
apply_distance_corrections
(timestamp, indices, distances)¶ Applies calibration and temperature-related distances corrections
-
apply_temperature_correction
(timestamp, indices, distances)¶ Applies temperature-related distance corrections
-
property
base_point_count
¶
-
property
binning
¶
-
cache
(specs: Dict[str, Union[int, float]]) → Dict[str, numpy.ndarray]¶ caches computation that are shared for all ‘ech’ samples.
- Parameters
specs – a dict with keys, ‘v’: number of scan channels, ‘h’: the number of imaging channels, ‘v_fov’: scan field of view, in degrees, ‘h_fov’: imaging field of view, in degrees
- Returns
A dict with keys ‘angles’ (the projection angles), ‘directions’ (the projection directions) and ‘quad_directions’ (the projection surface cloud directions)
Note
If ‘angle_chart’ is defined in this sensor’s intrinsics, the angle chart’s angles is used to compute ‘directions’, but not ‘quad_directions’. If ‘mirror_temp_compensation’ is defined in this sensor’s intrisincs, ‘angles_temp_lut’ and ‘directions_temp_lut’ will appear in cache and be used by apply_direction_corrections()
-
property
distance_scaling
¶ Get the distance in meters between two subsequent points in a trace
-
get_corrected_cloud
(timestamp, cache, type, indices, distances, amplitudes=None, dtype=<class 'numpy.float64'>)¶ Returns the point-cloud (or quad-cloud) using the get_corrected_projection_data() method.
- Parameters
type – ‘point_cloud’ or ‘quad_cloud’
-
get_corrected_projection_data
(timestamp: Union[int, float], cache: dict, type: str = 'directions')¶ Returns temperature compensated projections directions or angles
- Parameters
timestamp – the timestamp at which the sample is needed (use to obtain the right temperature)
cache – the cache to search in (obtained by calling LCAx.cache(…))
type – the type of directions (e.g) ‘directions’ or ‘quad_directions’. Must be present in the cache
- Returns
the compensated directions if any, or the uncompensated direction otherwise
-
get_temperature_at
(timestamp)¶
-
get_trace_smoothing_kernel
()¶ Get the convolution kernel for trace processing for LCA2
-
load_intrinsics
(intrinsics_config: Union[str, dict])¶ Load the LCAx intrinsics from a dictionnary like {‘v’: 8, ‘h’, 32, ‘v_fov’: 20, ‘h_fov’: 30}
- Parameters
intrinsics_config – The intrinsics configuration
-
load_specs_from_cfg
()¶
-
load_static_noise_from_cfg
()¶
-
load_time_base_delays_from_cfg
()¶
-
property
oversampling
¶
-
api.sensors.motor_lidar module¶
-
class
api.sensors.motor_lidar.
MotorLidar
(name, platform)¶ Bases:
pioneer.das.api.sensors.sensor.Sensor
-
__init__
(name, platform)¶ Constructor.
- Parameters
name – the sensor’s name and position id, e.g. ‘eagle_tfc’
platform – the platform this sensor belongs to
factories – a dict containing one entry per datasource type, each entry’s value is a tuple containing (Sample-derived, optional_interpolator_function). For example, a factoryies dict could be {“ech”:(Echo, None), “sta”:(Sample, interpolators.linear_dict_of_float_interpolator)}
call_start – a callback to be called by Sensor.start() (e.g. to start an actual live sensor)
call_stop – similar to call_start
-
apply_temperature_correction
(timestamp, distances)¶ Applies temperature-related distance corrections
-
get_corrected_cloud
(timestamp, pts, dtype)¶ It corrects the pts-cloud according to a temperature compensation (if any).
-
load_intrinsics
(intrinsics_config: Union[str, dict])¶ load data from yml platform
-
api.sensors.mti module¶
-
class
api.sensors.mti.
MTi
(name, platform)¶ Bases:
pioneer.das.api.sensors.sensor.Sensor
-
__init__
(name, platform)¶ Constructor.
- Parameters
name – the sensor’s name and position id, e.g. ‘eagle_tfc’
platform – the platform this sensor belongs to
factories – a dict containing one entry per datasource type, each entry’s value is a tuple containing (Sample-derived, optional_interpolator_function). For example, a factoryies dict could be {“ech”:(Echo, None), “sta”:(Sample, interpolators.linear_dict_of_float_interpolator)}
call_start – a callback to be called by Sensor.start() (e.g. to start an actual live sensor)
call_stop – similar to call_start
-
api.sensors.pixell module¶
-
class
api.sensors.pixell.
Pixell
(name, platform)¶ Bases:
pioneer.das.api.sensors.lcax.LCAx
-
__init__
(name, platform)¶ Constructor.
- Parameters
name – the sensor’s name and position id, e.g. ‘eagle_tfc’
platform – the platform this sensor belongs to
factories – a dict containing one entry per datasource type, each entry’s value is a tuple containing (Sample-derived, optional_interpolator_function). For example, a factoryies dict could be {“ech”:(Echo, None), “sta”:(Sample, interpolators.linear_dict_of_float_interpolator)}
call_start – a callback to be called by Sensor.start() (e.g. to start an actual live sensor)
call_stop – similar to call_start
-
static
angles_from_heads
(distances, angles, head_positions)¶
-
cache
(specs)¶ caches computation that are shared for all ‘ech’ samples.
- Parameters
specs – a dict with keys, ‘v’: number of scan channels, ‘h’: the number of imaging channels, ‘v_fov’: scan field of view, in degrees, ‘h_fov’: imaging field of view, in degrees
- Returns
A dict with keys ‘angles’ (the projection angles), ‘directions’ (the projection directions) and ‘quad_directions’ (the projection surface cloud directions)
Note
If ‘angle_chart’ is defined in this sensor’s intrinsics, the angle chart’s angles is used to compute ‘directions’, but not ‘quad_directions’. If ‘mirror_temp_compensation’ is defined in this sensor’s intrisincs, ‘angles_temp_lut’ and ‘directions_temp_lut’ will appear in cache and be used by apply_direction_corrections()
-
get_cloud
(cache, type, indices, distances, amplitudes=None, dtype=<class 'numpy.float64'>)¶ Get cloud data (type_pts, type_amplitudes, type_indices) from a sensor.
-
get_corrected_cloud
(timestamp, cache, type, indices, distances, amplitudes=None, dtype=<class 'numpy.float64'>)¶ Returns the point-cloud (or quad-cloud) using the get_corrected_projection_data() method.
- Parameters
type – ‘point_cloud’ or ‘quad_cloud’
-
get_head_position_per_channel
()¶
-
get_trace_smoothing_kernel
()¶ Get the convolution kernel for trace processing for LCA2
-
load_intrinsics
(intrinsics_config: Union[str, dict])¶ Basic intrinsics are brougth back under Sensor.
-
api.sensors.radar_ti module¶
-
class
api.sensors.radar_ti.
RadarTI
(name, platform)¶ Bases:
pioneer.das.api.sensors.sensor.Sensor
-
__init__
(name, platform)¶ Constructor.
- Parameters
name – the sensor’s name and position id, e.g. ‘eagle_tfc’
platform – the platform this sensor belongs to
factories – a dict containing one entry per datasource type, each entry’s value is a tuple containing (Sample-derived, optional_interpolator_function). For example, a factoryies dict could be {“ech”:(Echo, None), “sta”:(Sample, interpolators.linear_dict_of_float_interpolator)}
call_start – a callback to be called by Sensor.start() (e.g. to start an actual live sensor)
call_stop – similar to call_start
-
get_corrected_cloud
(timestamp, pts, dtype)¶
-
api.sensors.sensor module¶
-
class
api.sensors.sensor.
Sensor
(name: str, pf, factories: Dict[str, Tuple[Any, Any]] = {}, call_start: Optional[Callable] = None, call_stop: Optional[Callable] = None)¶ Bases:
object
A sensor encapsulate a sensor and its datasources. Important when you add a new derivation of class Sensor, don’t forget to add it to platform.SENSOR_FACTORY.
-
exception
NoPathToReferential
¶ Bases:
Exception
-
__getitem__
(key: str)¶ Returns the datasource
- Parameters
key – the datasource type, e.g. ‘ech’
-
__init__
(name: str, pf, factories: Dict[str, Tuple[Any, Any]] = {}, call_start: Optional[Callable] = None, call_stop: Optional[Callable] = None)¶ Constructor.
- Parameters
name – the sensor’s name and position id, e.g. ‘eagle_tfc’
platform – the platform this sensor belongs to
factories – a dict containing one entry per datasource type, each entry’s value is a tuple containing (Sample-derived, optional_interpolator_function). For example, a factoryies dict could be {“ech”:(Echo, None), “sta”:(Sample, interpolators.linear_dict_of_float_interpolator)}
call_start – a callback to be called by Sensor.start() (e.g. to start an actual live sensor)
call_stop – similar to call_start
-
add_datasource
(ds, ds_type: str, cache_size: int = 100)¶ Adds a datasouce to this sensor
- Parameters
ds – a Filesource-derived instance or VirtualDatasource
ds_type – the datasource type, e.g. ‘ech’
-
create_egomotion_provider
() → Optional[EgomotionProvider]¶
-
datasource_names
() → List[str]¶ Returns this sensor’s datasource types
-
property
extrinsics_dirty
¶ The extrinsics dirty signal
-
invalidate_datasources_caches
()¶ Invalidate sensor’s datasources caches
-
items
()¶ Returns the datasource key,value iterable, implement dict API
-
keys
()¶ Returns the datasource types, implement dict API
-
load_extrinsics
(extrinsics_folder: str)¶ Looks for a pickle file containing extrinsics information for this sensor, named ‘From-To’ e.g. ‘flir_tfl-eagle_tfc.pkl’
- Parameters
intrinsics_config – path to folder containing this sensor’s extrinsics pickle file
or relative to dataset path), e.g. '/nas/extrinsics' or 'extrinsics' ((absolute) –
-
load_intrinsics
(intrinsics_config: str)¶ Looks for a pickle file containing intrinsics information for this sensor, e.g. ‘eagle_tfc.pkl’
- Parameters
intrinsics_config – path to folder containing this sensor’s intrinsics pickle file,
or relative to dataset path), e.g. '/nas/cam_intrinsics' or 'cam_intrinsics' ((absolute) –
-
map_to
(target: str) → numpy.ndarray¶ Returns a 4x4 tranform matrix mapping a point from this sensor’s referential to ‘target’ sensor’s referential
- Parameters
target – the name of the target sensor in which referential we want to map to
- Raises
Sensor.NoPathToReferential – if no mapping could be found
-
property
platform
¶
-
start
()¶ Starts the live sensor wrapped by this Sensor instance
-
stop
()¶ Stops the live sensor wrapped by this Sensor instance
-
exception


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"Live each day as if it is your first"
One of my favourite bits of the article is the idea that you should live each day as if it is your first. When I read this I first thought about the Buddhist idea of having a beginner's mind. The theory is that having a clear mind allows you to look at a situation with out any pre-conceptions and therefore produce an action that is truly your own. When you think about it this is pretty powerful.
Being a web designer it's easy to get bogged bown into the 'standard' layouts of a website and this can really put a downer on your creativity. If you asked someone to design a web page that had never seen one before I bet that it would look nothing like the sorts of web pages out there today. Having a mind free of any knowledge or pre-conceptions about a subject can help you to be really innovative, without even knowing it.
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