nmeans

t.prefs_.set('color-palette-overrides',["#002831", "#d11c24", "#738a05", "#a57706", "#2176c7", "#c61c6f", "#259286", "#eae3cb", "#001e27", "#bd3613", "#475b62", "#536870", "#708284", "#5956ba", "#819090", "#fcf4dc"]);
t.prefs_.set('cursor-color', 'rgba(112,130,132,0.5)');

nmeans

Talks

• Leadership. By the numbers., Michael Lopp, The Lead Developer UK 2016
• How do you get an engineering team to eat their vegetables, Duretti Hirpa, The Lead Developer UK 2016
• Rebooting Culture, Camille Fournier, The Lead Developer UK 2016 (Wait for 2017 Lead Developer NYC version of this talk – it's quite a bit better)

Books

• How To Win Friends and Influence People, Dale Carnegie
• Leading Snowflakes, Oren Ellenbogen
• The Effective Executive, Peter Drucker
• Extreme Programming Explained, Kent Beck and Cynthia Andres

nmeans

Hi Garmin,

I'm seeing incorrect calorie publishing from Garmin Connect into Apple HealthKit. For example, I did a run at lunch today. Garmin Connect recorded 453 calories. When I look at the workout in the Activity app, I see 0 calories. When I look at the workout data in the Apple Health app, I see the calorie total reported as 0.45 kcal. I think this is a calorie/kilocalorie reporting issue.

I'm guessing your developers used HKUnit.calorie() to publish the workout to HealthKit when they should've used HKUnit.kilocalorie() when reporting these totals (https://developer.apple.com/reference/healthkit/hkunit/1615359-calorie vs. https://developer.apple.com/reference/healthkit/hkunit/1615576-kilocalorie). Your developers will know what I'm talking about.

I can't be the only person to have run across this problem. Is it a known issue? Any idea when you might have a fix?

Cheers, Nick

nmeans

def parse_roles(user_hash)
  custom_schemas = user_hash.fetch("customSchemas") { return [] }
  roles = custom_schemas.fetch("Roles") { return [] }
  roles
end

user1 = {
  "email": "andrew@muvehealthlabs.com",
  "customSchemas": {
    "Roles": ["accountant", "admin"]

nmeans

% time wget -O - "https://api.geocod.io/v1/geocode?q=5119+Burnet+Rd+Austin+TX+78756&api_key=[REDACTED]"
--2014-08-26 11:39:21--  https://api.geocod.io/v1/geocode?q=5119+Burnet+Rd+Austin+TX+78756&api_key=[REDACTED]
Resolving api.geocod.io... 107.170.69.34
Connecting to api.geocod.io|107.170.69.34|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: unspecified [application/json]
Saving to: ‘STDOUT’

    [<=>                                                                                                                                                                                                                                                                                  ] 0           --.-K/s              {"input":{"address_components":{"number":"5119","street":"Burnet","suffix":"Rd","city":"Austin","state":"TX","zip":"78756"},"formatted_address":"5119 Burnet Rd, Austin, TX 78756"},"results":[{"address_components":{"number":"5119","street":"Burnet","suffix":"Rd","city":"Austin","count

nmeans

Keybase proof

I hereby claim:

• I am nmeans on github.
• I am nmeans (https://keybase.io/nmeans) on keybase.
• I have a public key whose fingerprint is F066 E600 744C BD12 34BE 2DF2 287A 53B5 165F BA0C

To claim this, I am signing this object:

nmeans

# Add a no-op version of the console object so accidental
# calls to console that leak to prod won't raise errors 
# in IE < 10.
if typeof(console) == "undefined"
  window.console = 
    log: () ->
    debug: () ->
    info: () ->
    warn: () ->
    error: () ->

nmeans

require 'rubygems'
require 'sinatra'

get '/' do
  haml :form
end

post '/DO_NOT_SHOW_IN_HISTORY' do
  redirect to('/show_in_history'), 302
end

nmeans

set -g default-terminal "screen-256color"

set -sg escape-time 0

# scrollback buffer size increase
set -g history-limit 500000

# Use up and down arrows for temporary "maximize"
unbind Up; bind Up resize-pane -Z; unbind Down; bind Down resize-pane -Z

nmeans

input = (-1000...1000).collect{|i| [i]}
output = input.map{|i| i > 0 ? [1,0] : [0,1]}
train = RubyFann::TrainData.new(:inputs => input, :desired_outputs => output)
fann = RubyFann::Standard.new(:num_inputs=>2, :hidden_neurons=>[3,3,3], :num_outputs=>2)
fann.train_on_data(train, 1001, 10, 0.001)
fann.run([-500]) # [0.03544681023290716, 1.0]
fann.run([500]) # [1.0, 0.0]