Daily
Cost per Unit
$17.21
12.5%
Per Week
Market Revenue
$1875.54
18.71%
Per Month
Expenses
$784.62
57%
All Time
Daily Visits
1,15,187
17.8%
Recent Customers
Transaction period from 21 July to 25 Aug
| Customer | Phone | Location | Create Date | |
|---|---|---|---|---|
| Paul J. Friend |<PHONE_NUMBER> |<EMAIL_ADDRESS>| New York | 07/07/2018 |
| Bryan J. Luellen |<PHONE_NUMBER> |<EMAIL_ADDRESS>| New York | 09/12/2018 |
| Kathryn S. Collier |<PHONE_NUMBER> |<EMAIL_ADDRESS>| Canada | 06/30/2018 |
| Timothy Kauper | (216) 75 612 706 |<EMAIL_ADDRESS>| Denmark | 09/08/2018 |
| Zara Raws | (02) 75 150 655 |<EMAIL_ADDRESS>| Germany | 07/15/2018 |
Account Transactions
Transaction period from 21 July to 25 Aug
4257 **** **** 785211 April 2019 |
$79.49Amount |
Card |
Helen WarrenPay |
4265 **** **** 002528 Jan 2019 |
$1254.00Amount |
Card |
Kayla LambiePay |
5570 **** **** 854708 Dec 2018 |
$784.25Amount |
Card |
Hugo LavarackPay |
7845 **** **** 521403 Dec 2018 |
$485.24Amount |
Card |
Amber ScurryPay |
4257 **** **** 785212 Nov 2018 |
$8964.04Amount |
Card |
Caitlyn GibneyPay |


| 1 |
| e01a |
| CS24 W18 |
| Name: | |
|---|---|
| (as it would appear on official course roster) | |
| Umail address: | @umail.ucsb.edu |
EXAM: e01a: Practice Midterm Exam
| ready? | date | points |
|---|---|---|
| true | Thu 07/07 09:30AM |
You may not collaborate on this exam with anyone. If you need to use the restroom, you must leave your cell phone with the exam proctor before leaving the room.
- Write your name at the top of this page AND EVERY ODD NUMBERED PAGE.
- Double check that you turned in ALL pages; look for "End of Exam" on the last page.
- This exam is closed book, closed notes, closed mouth, cell phone off.
- You are permitted one sheet of paper (max size 8.5x11") on which to write notes.
- This sheet will be collected with the exam, and might not be returned.
- Please write your name on your notes sheet.
-
(50 pts) In the space below (and on the next page if needed) write the code forthe
IndexEntry
class according to the instructions on the separate handout provided.There is more room on the next page for your answer if you run out of room here.
Extra space for your answer to question 1
-
In CS16,24,32, for C/C++ programming, we used the
make
utility to streamline the process of compiling code.-
(2 pts) What is the name of the utility we are using in this course instead of make, because it is more suitable for Java?
-
(2 pts) With
make
we use a file calledMakefile
to control our build. What’s the corresponding file called with the utility we are using in this course? -
(8 pts) Within that utility, there are tasks and targets.
Describe an example of a target that would contain more than one task.
Your description should contain:
- the name of the target you are describing
- the names of the two tasks it contains
- a brief description of the purpose of the target
- a brief description of the purpose of each of the two tasks.
You do not need to give the full XML syntax for the target, and the two tasks. But if it will clarify your explanation, you may like to provide at least a general sense (perhaps with lots of bits left out) of how the target and task look in the XML code.
-
-
(10 pts) For each of the following indicate if the line of code involves auto-boxing, and/or auto-unboxing. If a line of code involves both, check both boxes. If it involves neither, check neither box. ASSUME THAT ALL THE LINES OF CODE ARE IN THE SAME
main
METHOD, CONSECUTIVELY.(Grading: -2 for each incorrect answer, but no more than -10 total.)
Code auto-boxing auto-unboxing ArrayList<Integer> mylist = new ArrayList<Integer>();
□ □ mylist.add(new Integer(7));
□ □ mylist.add(2);
□ □ mylist.add(mylist.get(0));
□ □ Integer x = mylist.get(0);
□ □ int y = mylist.get(1);
□ □ Integer z = mylist.get(mylist.get(1));
□ □ -
(10 pts) Briefly describe the two main categories of exceptions in Java.
Be sure that your answer includes not only the names of the two kinds of exceptions, but also the reason that there are two different categories, and how they have to be treated differently.
Describe as if you were asked during a job interview. You should include enough detail so that the interviewer knows that you are very familiar with exceptions in Java, but not so much that you are wasting the interviewer’s time.
-
In lecture, we discussed the way that that Java compiler (or any compiler, for that matter) deals with the problem of turning Java code into bytecodes that can be interpreted by the Java Virtual Machine.
We discussed that the first phase is often to turn a sequence of characters into a sequence of tokens.
Here is some Java code. List what the first twelve tokens in this code would be by filling in the blanks.
for (int i=0; i<=p.getDegree(); i++) { System.out.println("coeff=" + p.get(i)); }
1: 2: 3: 4: 5: 6: 7: 8: 9: 10: 11: 12 Grader: -1 for each incorrect answer, minimum grade of 0.
-
(4 pts) Assume that the following line of code appears inside a java
main()
method.Dog [] pets = new Dog[7];
One, and only one of the following is a completely true statement? Which one? (Note that the others may be a mix of true and false statements.)
-
pets
is a local variable on the stack that refers to anArray
object. This is an array of sevenDog
objects,pets[0]
throughpets[6]
each of which is allocated on the heap. This statement is not legal if the Dog class does not contain a default constructor. -
pets
is a local variable on the stack that refers to anArray
object. That array object is on the heap. The array object contains sevenDog
referencespets[0]
throughpets[6]
, each of which is initiallynull
. NoDog
objects are created by this statement.
-
-
(4 pts) Write a line of Java code that declares a variable
p
that is NOT of a reference type. -
(2 pts) Write a line of Java code that declares a variable
q
that is NOT of a primitive type. -
(4 pts) Under what conditions does the compiler create a no-arg constructor for you?
-
(4 pts) Under what conditions does the compiler NOT create a no-arg constructor for you?


case classResearcher[ResultType, TrialType](config: ExecutionConfig)(implicit evidence$1: scala.reflect.api.JavaUniverse.TypeTag[ResultType]) extends Product with Serializable
An experiment consists of 0 or more warmup invocations, and 1 or more measured trials. Warmup invocations will be
excluded from measurement. Depending on which measurement ModeWord is set and the number of specified threads
and invocations, we might collect non-intrusive measurements for individual invocations on individual threads.
Note: The ResultType TypeTag represents the measured function's return value, while TrialType represents the type
parameter of the returned TrialResult. This second type parameter is necessary because ResultType might
be a TrialResult, in which case we want to return a TrialResult containing the same TrialType parameter.
If ResultType is some other type, then we will wrap it in a TrialResult and store the value as maybeResult.
Created by tomas.mccandless on 12/20/16.
Linear Supertypes
Serializable, Serializable, Product, Equals, AnyRef, Any
Conducts experiments using the provided ExecutionConfig.
An experiment consists of 0 or more warmup invocations, and 1 or more measured trials. Warmup invocations will be excluded from measurement. Depending on which measurement ModeWord is set and the number of specified threads and invocations, we might collect non-intrusive measurements for individual invocations on individual threads.
Note: The ResultType TypeTag represents the measured function's return value, while TrialType represents the type parameter of the returned TrialResult. This second type parameter is necessary because ResultType might be a TrialResult, in which case we want to return a TrialResult containing the same TrialType parameter. If ResultType is some other type, then we will wrap it in a TrialResult and store the value as
maybeResult
.Created by tomas.mccandless on 12/20/16.


| DOSE: |
1 repeated |
smoked |
Cannabis |
(plant material) |
I was 13 years old when I smoked my first joint, but I really didn't know how to do it.  She didn't want to, but I insisted. First time was a no go...I didn't know how to inhale so I barely got a buzz. Disappointing, but, it happens.
So, we decide to try again. This time we use the dad's pipe. We packed it tight and sparked it, and I smoked as much as I could, holding it in for as long as I could stand it. I was getting really anxious for results so I kept smoking more and more until I had a huge coughing fit and had to slow down. Suddenly, it hit me. The weed had finally sunk in.
First thing I felt was bliss. Happiness and belonging with nature. I felt so good, and I started loving the smell of the weed more and more. We decide to go outside, my friend hasn't even had any yet. I kinda hoarded it, and she was having second thoughts. So she packs another bowl, sparks it, and lets it burn for a little while without trying it. I get annoyed, and take it from her so I can get even more stoned. She's getting paranoid that her parents are gonna find out. I'm way beyond rationality at this point, so I just keep smoking and then give it to her. I jump on the trampoline and start doing tricks I've never been able to do before, back handsprings and shit, and I keep falling over.
I remember jumping up and down, up and down, rhythmically, like I was one with nature. I felt closer and closer to the sky, like I was touching the trees with each bounce of the trampoline. It was a wonderful, euphoric feeling. She's hanging under the porch stairs, still holding the pipe which hasn't quite been cashed but is almost out. I beg her to try it so we'll be on the same wavelength. She finally does and feels the effects almost immediatley. Soon we're both on the trampoline, jumping up and down and laughing hysterically. Can't. Stop. Laughing.
Right about the time when she was peaking I got horrible munchies.  I run inside, make like 3 bags of popcorn, and eat like 5 pounds of salted peanuts...at least that's what it felt like.  My friend is still outside, jumping and laughing like a lunatic. Phone rings. My mother. Shit, gotta act sober. The phone started looking funny. I was holding it weird. My mom's picking me up in 5 minutes. Fuck. Fuck. Fuck.
Febreeze and lots of perfume, and I'm ready to go. I get in the car, crack the window, and inch away from Mom.
'Yeah.' I'm having one of the best experiences of my life. Funny thing is, she warned me about drug use constantly and told me that once I'd tried it she'd know immediatley. I was 13 years old, smelling like febreeze and herb, and I had called her Dad like 3 times. Yeah. She knew, all right. Not.
Since then I've done weed pretty regularly, but my first time was definitley the best.
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.


Please list any states in which you hold a license to practice medicine. Please provide a license number. If an application is pending in a state, please write “pending.”
Yes
No
Yes
No
Have you ever been reprimanded, or had your license suspended or revoked in any of these states?
Yes (If so, please explain in an attached sheet.)
No
File Successfully Uploaded
Have you ever been named in (and/or had a judgment against you) in a medical malpractice legal suit?
Yes (If so, please explain in an attached sheet.)
No


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Table Of Contents
In this series, we’re instrumenting a Phoenix app and sending metrics to StatsD with the help of Elixir and Erlang’s Telemetry offerings.
- Part I: Telemetry Under The Hood
- Part II: Handling Telemetry Events with
TelemetryMetrics
+TelemetryMetricsStatsd
- Part III: Observing Phoenix + Ecto Telemetry Events
- Part IV: Erlang VM Measurements with
telemetry_poller
,TelemetryMetrics
+TelemetryMetricsStatsd
Intro
In the previous post, we saw how the Telemetry.Metrics
and TelemetryMetricsStatsd
libraries abstracted away the need to define custom handlers, attach those handlers to events, and implement our own metric reporting logic. But our Telemetry pipeline still needs a little work–we’re still on the hook for emitting all of our own Telemetry events!
In order to really be able to observe the state of our production Phoenix app, we need to be reporting on much more than just one endpoint’s request duration and count. We need to report information-rich metrics describing web requests across the app, database queries, the behavior and state of the Erlang VM, the behavior and state of any workers in our app, and more.
Instrumenting all of that by hand, by executing custom Telemetry events wherever we need them, will be tedious and time-consuming. On top of that, it will be a challenge to standardize event naming conventions, measurements, and metadata across the app.
In this post, we’ll examine Phoenix and Ecto’s out-of-the-box Telemetry events and use Telemetry.Metrics
to observe a wide-range of such events.
Achieving Observability with Phoenix and Ecto Telemetry Events
To achieve observability, we know we nee to track things like:
- Count and duration of all requests to all endpoints, with the ability to view this information broken down by things like:
- Route
- Response status
- Count and duration of all Ecto queries, with the ability to view this information broken down by things like:
- Query command (e.g.
SELECT
,UPDATE
) - Table (e.g.
Users
)
- Query command (e.g.
Luckily for us, pretty much all of these events are already being emitted by Phoenix and Ecto directly!
In the following tutorial, we will teach Telemetry.Metrics
to observe these out-of-the-box events and format the appropriate set of metrics, with information-rich tags, for each event.
A Note On Formatting Metrics
In our previous post, we used the TelemetryMetricsStatsd
reporting library to format metrics and send them to StatsD over UDP. We can configure this reporter with either the standard formatter or the DogStatsD formatter. The standard formatter constructs and emits metrics that are compatible with the Etsy implementation of StatsD. This implementation does not support tagging, so TelemetryMetricsStatsd
accommodates the tags we assign to metrics by including the tag values in the metric name.
For example, if we specify the following counter metric:
counter(
"phoenix.request",
tags: [:request_path]
)
And execute a Telemetry event where the conn
we pass in for the metadata argument contains %{request_path: "/register/new"}
, then TelemetryMetricsStatsd
will construct a metric:
"phoenix.request.-register-new"
What if we ultimately want to send StatsD metrics to Datadog, which does support metric tagging? In that case, we can configure the TelemetryMetricsStatsd
reporter to use the DogStatsD formatter, which would emit the following counter metric for the above event, including tags:
"phoenix.request:1|c|#request_path:/register/new"
For the purposes of this tutorial, we’ll use the DogStatsD formatter to make it easy to read and understand the metrics and tags that we are constructing and sending to StatsD.
defmodule Quantum.Telemetry do
use Supervisor
import Telemetry.Metrics
def start_link(arg) do
Supervisor.start_link(__MODULE__, arg, name: __MODULE__)
end
def init(_arg) do
children = [
{TelemetryMetricsStatsd, metrics: metrics(), formatter: :datadog} # Add the formatter here!
]
Supervisor.init(children, strategy: :one_for_one)
end
defp metrics do
[
# coming soon!
]
end
end
Getting Started
You can follow along with this tutorial by cloning down the repo [here] (https://github.com/elixirschool/telemetry-code-along/tree/part-3-start).
- Checking out the starting state of our code on the branch part-3-start
- Find the solution code on the branch part-3-solution
Phoenix Telemetry Events
The [:phoenix, :router_dispatch, :stop]
Event
First up, we’ll leverage one of the out-of-the-box Phoenix events to help us track and report metrics for web request counts and durations–the [:phoenix, :router_dispatch, :stop]
event.
The Phoenix.Router
module executes this event after the request is processed by the Plug pipeline and the controller, but before a response is rendered. Looking in Phoenix source code we can see the event being emitted here:
# phoenix/lib/phoenix/router.ex
duration = System.monotonic_time() - start
metadata = %{metadata | conn: conn}
:telemetry.execute([:phoenix, :router_dispatch, :stop], %{duration: duration}, metadata)
Here, Phoenix is calculating the duration by subtracting the start time, set at the beginning of the request processing pipeline, from the current time. Then it’s updating the metadata map to include the conn
. Lastly, it’s executing the Telemetry metric with this information.
Now that we know which Telemetry event we care about, let’s make our Telemetry.Metrics
, Quantum.Telemetry
module aware of it.
# lib/quantum/telemetry.ex
def metrics do
[
summary(
"phoenix.router_dispatch.stop.duration",
unit: {:native, :millisecond},
tags: [:plug, :plug_opts]
),
counter(
"phoenix.router_dispatch.stop.count",
tags: [:plug, :plug_opts]
)
]
end
Now, whenever the Phoenix.Router
executes the [:phoenix, :router_dispatch, :stop]
Telemetry event for a given web request, we will see counter and timer metrics emitted to StatsD tagged with the :plug
and :plug_opts
values from the event metadata.
By running the app and visiting the landing page, we see the following reported to StatsD:
# timing
"phoenix.router_dispatch.stop.duration:5.411|ms|#plug:Elixir.QuantumWeb.PageController,plug_opts:index"
# counter
"phoenix.router_dispatch.stop.count:1|c|#plug:Elixir.QuantumWeb.PageController,plug_opts:index"
This represents a BIG win for us, as compared to our previous approach of manually executing a Telemetry event from every controller action in our app. By defining metrics for this event in our Quantum.Telemetry
module and providing those metrics to the TelemetryMetricsStatsd
reporter, we are able to report metrics for every web request our app receives, across all endpoints.
Getting More Out Of Tags
We can also see how helpful the :tags
option of the metrics functions can be. These tags are ensuring that the metrics we report to StatsD are information-rich–they contain data from the context of the web request. Recall from the previous post that the TelemetryMetricsStatsd
reporter will apply tags for a given metric where those tags are present as keys in the event metadata. So, when Phoenix.Router
executes the following Telemetry event:
# phoenix/lib/phoenix/router.ex
duration = System.monotonic_time() - start
metadata = %{metadata | conn: conn}
:telemetry.execute([:phoenix, :router_dispatch, :stop], %{duration: duration}, metadata)
It provides the :telemetry.execute/3
call with metadata
that includes top-level keys of :plug
and :plug_opts
.
It also includes the request conn
in that metadata map, under a key of :conn
. What if we want to grab some data out of the conn
to include in our metric tags?
It would be great if we could tag these web request counter metrics with the response status–that way we can aggregate counts of successful and failed web requests.
The response status is present in the conn
, under a key of :status
. But the Telemetry.Metrics.counter/2
function only knows how to deal with tags that are top-level in the provided metadata
. If only there was some way to tell the counter metric how to apply tags from data that is nested inside the provided metadata.
This is where the metrics functions’ :tag_values
option comes in! We can use the :tag_values
option to store a function that will be called later on during the Telemetry event handling process to construct additional tags from nested metadata info.
All we have to do is implement a function that expects to receive the event metadata and returns a map that includes all of the tags we want to apply to our metric:
# lib/quantum/telemetry.ex
def endpoint_metadata(%{conn: %{status: status}, plug: plug, plug_opts: plug_opts}) do
%{status: status, plug: plug, plug_opts: plug_opts}
end
Then, when we call a given metrics function, for example counter/2
, we set the :tag_values
option to this function and :tags
to our complete list of tags:
# lib/quantum/telemetry.ex
def metrics do
[
counter(
"phoenix.router_dispatch.stop.count",
tag_values: &__MODULE__.endpoint_metadata/1,
tags: [:plug, :plug_opts, :status]
)
]
end
Now, when we run our Phoenix server and visit the landing page, we see the following counter metric emitted to StatsD:
"phoenix.router_dispatch.stop.count:1|c|#plug:Elixir.QuantumWeb.PageController,plug_opts:index,status:200"
Notice that now the metric is tagged with the response status. This will make it easy for us to visualize counts of failed and successful requests in Datadog.
More Phoenix Telemetry Events
So far, we’ve taken advantage of just one of several Telemetry events executed by Phoenix source code. There are a number of helpful events we can have our Telemetry pipeline handle. Let’s take a brief look at some of these events now.
The [:phoenix, :error_rendered]
Telemetry Event
The Phoenix.Endpoint.RenderErrors
module executes a Telemetry event after rendering the error view. We can see the call to execute this event in source code here:
# phoenix/lib/phoenix/endpoint/render_errors.ex
defp instrument_render_and_send(conn, kind, reason, stack, opts) do
start = System.monotonic_time()
metadata = %{status: status, kind: kind, reason: reason, stacktrace: stack, log: level}
try do
render(conn, status, kind, reason, stack, opts)
after
duration = System.monotonic_time() - start
:telemetry.execute([:phoenix, :error_rendered], %{duration: duration}, metadata)
end
end
We can tell our Telemetry pipeline to handle this event as a counter and tag it with the request path and response status in our Quantum.Telemetry.metrics/0
function like this:
# lib/quantum/telemetry.ex
def metrics do
[
counter(
"phoenix.error_rendered.count",
tag_values: &__MODULE__.error_request_metadata/1,
tags: [:request_path, :status]
)
]
end
def error_request_metadata(%{conn: %{request_path: request_path}, status: status}) do
%{status: status, request_path: request_path}
end
Now, we’ll see the following counter metric incremented in StatsD when a user visits, /blah
, a path that does not exist:
"phoenix.error_rendered.count:1|c|#request_path:blah,status:404"
Phoenix.Socket
Telemetry Event
Phoenix also provides some out-of-the-box instrumentation for Socket and Channel interactions.
The Phoenix.Socket
module executes a Telemetry event whenever the socket is connected to. We can see that event in source code here:
# phoenix/lib/phoenix/socket.ex
def __connect__(user_socket, map, socket_options) do
%{
endpoint: endpoint,
options: options,
transport: transport,
params: params,
connect_info: connect_info
} = map
start = System.monotonic_time()
case negotiate_serializer(Keyword.fetch!(options, :serializer), vsn) do
{:ok, serializer} ->
result = user_connect(user_socket, endpoint, transport, serializer, params, connect_info)
metadata = %{
endpoint: endpoint,
transport: transport,
params: params,
connect_info: connect_info,
vsn: vsn,
user_socket: user_socket,
log: Keyword.get(options, :log, :info),
result: result(result),
serializer: serializer
}
duration = System.monotonic_time() - start
:telemetry.execute([:phoenix, :socket_connected], %{duration: duration}, metadata)
result
:error ->
:error
end
end
We can see that the event is executed with the duration measurement and a metadata map that includes the connection params and other contextual info. We can tell our Telemetry pipeline to handle this event by adding metrics for the "phoenix.socket_connected"
event in our Quantum.Telemetry.metrics/0
list:
For example:
# lib/quantum/telemetry.ex
def metrics do
[
counter(
"phoenix.socket_connected.count",
tags: [:endpoint]
)
]
end
Now we will increment a StatsD metric every time the socket is joined.
Phoenix.Channel
Telemetry Events
The Phoenix.Channel.Server
module executes two Telemetry events–one when the channel is joined and one whenever the channel invokes handle_info/2
.
We can see the [:phoenix, :channel_joined]
Telemetry event in source code here:
# phoenix/lib/phoenix/channel/server.ex
def handle_info({:join, __MODULE__}, {auth_payload, {pid, _} = from, socket}) do
%{channel: channel, topic: topic, private: private} = socket
start = System.monotonic_time()
{reply, state} = channel_join(channel, topic, auth_payload, socket)
duration = System.monotonic_time() - start
metadata = %{params: auth_payload, socket: socket, result: elem(reply, 0)}
:telemetry.execute([:phoenix, :channel_joined], %{duration: duration}, metadata)
GenServer.reply(from, reply)
state
end
And we can see the [:phoenix, channel_handled_in]
event here
# phoenix/lib/phoenix/channel/server.ex
def handle_info(
%Message{topic: topic, event: event, payload: payload, ref: ref},
%{topic: topic} = socket
) do
start = System.monotonic_time()
result = socket.channel.handle_in(event, payload, put_in(socket.ref, ref))
duration = System.monotonic_time() - start
metadata = %{ref: ref, event: event, params: payload, socket: socket}
:telemetry.execute([:phoenix, :channel_handled_in], %{duration: duration}, metadata)
handle_in(result)
end
We can add some metrics reporting for these events by defining metrics in Quantum.Telemetry
for either of the "phoenix.channel_joined"
and "phoenix.channel_handled_in"
events.
Now that we’ve taken a brief tour of Phoenix Telemetry events, let’s hook up some reporting for Ecto events.
Ecto Telemetry Events
Ecto provides some out-of-the-box instrumentation for queries. Let’s take a look at and define metrics for some of these Telemetry events now.
Ecto will execute a Telemetry event, [:my_app, :repo, :query]
for every query sent to the Ecto adapter. It will emit this event with a measurement map and a metadata map.
The measurement map will include:
* `:idle_time` - the time the connection spent waiting before being checked out for the query
* `:queue_time` - the time spent waiting to check out a database connection
* `:query_time` - the time spent executing the query
* `:decode_time` - the time spent decoding the data received from the database
* `:total_time` - the sum of the other measurements
The metadata map will includes:
* `:type` - the type of the Ecto query. For example, for Ecto.SQL
databases, it would be `:ecto_sql_query`
* `:repo` - the Ecto repository
* `:result` - the query result
* `:params` - the query parameters
* `:query` - the query sent to the database as a string
* `:source` - the source the query was made on (may be nil)
* `:options` - extra options given to the repo operation under
`:telemetry_options`
If we want to establish metrics for Ecto query counts aggregated by table and command, we could establish the following metric in our Quantum.Telemetry
metrics list:
def metrics do
[
counter(
"quantum.repo.query.count",
tag_values: &__MODULE__.query_metatdata/1,
tags: [:source, :command]
)
]
end
def query_metatdata(%{source: source, result: {_, %{command: command}}}) do
%{source: source, command: command}
end
This will increment a counter in StatsD for each query to a given table with a given command. For example:
"quantum.repo.query:1|c|#source:users,command:select"
We can also establish a timing metric with the use of the summary
metric function:
def metrics do
[
summary(
"quantum.repo.query.total_time",
unit: {:native, :millisecond},
tag_values: &__MODULE__.query_metadata/1,
tags: [:source, :command]
)
]
end
def query_metadata(%{source: source, result: {_, %{command: command}}}) do
%{source: source, command: command}
end
This will report timing metrics to StatsD for each query executed with a given command to a given table. For example:
"quantum.repo.query.total_time:1.7389999999999999|ms|#source:users,command:select"
More Metrics
This post has mainly focused on the counter/2
and summary/2
Telemetry.Metrics
functions, corresponding to the “count” and “timing” StatsD metric type respectively. Telemetry.Metrics
implements five metrics functions, each of which map to a specific metric type. To learn how to define and report on these various metric types, check out the docs here and here
Conclusion
Instrumenting our Phoenix app by taking advantage of the Telemetry events that are executed for us by Phoenix and Ecto allowed us to achieve a high degree of observability without writing a lot of custom code.
We simply defined our Telemetry.Metrics
module, configured it to start up the TelemetryMetricsStatsd
reporter and defined the list of existing Telemetry events to observe as metrics. Now we’re reporting a valuable set of information-rich metrics to StatsD, formatted for Datadog, without manually executing a single Telemetry event or defining any of our own event handlers.
Next Up
There’s one more flavor of out-of-the-box metrics reporting we’ll explore in this series. In our next post, we’ll use the telemetry_poller
Erlang library to emit Erlang VM measurements as Telemetry events and we’ll use Telemetry.Metrics
and TelemetryMetricsStatsd
to observe and report those events as metrics.
Caught a mistake or want to contribute to the article? Edit this page on GitHub!


Cameron Crowe is the Stanley Kubrick of rock n' roll cinema. Here is a man who takes his time to develop his stories before unveiling them to the public. Consider "Say Anything" in 1989, followed by "Singles" (his best film) in 1992, to the classic Tom Cruise comedy-drama "Jerry Maguire" in 1996. Four years later, Crowe has created his most personal film by far, and certainly one of his most insightful. "Almost Famous" is an autobiographical look at an ambitious reporter who loves rock n' roll music, and decides to interview a reluctant band. The only catch is that the reporter is 15 years old!
Newcomer Patrick Fugit plays overachiever William Miller (based on Crowe's own days as a teen reporter), who lands an unusual assigment - Rolling Stone has asked him to cover a story on the up-and-coming fictional band Stillwater. Apparently, Rolling Stone is astounded by his in-depth story of the band in the magazine "Creem." Low and behold, the youthful, naive William now travels with Stillwater, on the road across the United States. He stays in hotels, loses his virginity to a few groupies, develops a crush on Penny Lane (Kate Hudson), a groupie who is in love with the band's lead guitarist, Russell (Billy Crudup), and in short soaks up their grungy atmosphere while trying to record their thoughts on fame and their band's future on tape. As Penny grows charmed by the young man, she lets him know that he is "too sweet for rock n' roll." And so he is, to the point where William is continuously called by his overprotective mother, a college professor (Frances McDormand), who warns him "Don't do drugs."
There are many people that dominate William's life. The most significant is Russell, whom he develops a strong friendship with based on mutual respect. Penny is an even stronger friend who helps to get William laid, but she is so obsessed over her relationship with Russell that she forgets he may not love her. There is also the "uncool" rock journalist Lester Bangs (Philip Seymour Hoffman), who warns William that rock music's genesis, the need to lose control, is losing its potency and to be wary of rock musicians who will only use him to get a nice cover story. The last thing a band needs is negative press.
"Almost Famous" floats by on Patrick Fugit's charm and elfish eyes - he has the sympathetic ooze and trustworthiness of Tobey Maguire. He is so enamored by this band that he is willing to take risks along with them. This also means that William has to abandon his school career and pending graduation. But who cares when you have sex, drugs and rock n' roll!
Also worth mentioning is the up-and-coming actor Billy Crudup ("Jesus's Son") who shows a tempermental nature in Russell, particularly at a party where he does acid and begins to badger the kid. Russell is also changed by William, and realizes his mistakes in his affairs. Kate Hudson, Goldie Hawn's daughter, is also quite good as the emotionally fraught Penny, affected by William's puppy-dog eyes and sweetness - her near-overdose scene is also effective as William tries to get help and admits his love for her. Philip Seymour Hoffman is delightfully witty and on-target as Lester Bangs - he has the best one-liners in the film and should get a deserved Best Supporting Actor nomination. Frances McDormand offers fine support as William's mother who has a disdain for rock music on purely immoral grounds. Also memorable are Jason Lee as the group's loud lead singer who considers William the "enemy", and Fairuza Balk and Anna Paquin as groupies who are there for the music.
I could have lived without the tumultuous scene in a plane where everyone feels the need to confess to their sins or the far too tidy final scene, and yet there is nothing in "Almost Famous" that does not work. Every scene feels honest and truthful, and Cameron Crowe's gift is in keeping the camera static and observational. He has a gift for colorful dialogue and situations, and for bringing the appropriate mix of pathos and realism from his actors. My favorite scene is when the band is on a bus tour and they sing-along to Elton John's "Tiny Dancer." A scene like that might have been laughable or contrived under lesser hands, but Crowe manages to find a family connection between the members of the band and it pays off with poignance. Maybe someone like Paul Thomas Anderson might have shown the grittier, soulless side of the 70's rock music era whereas Crowe's affection for his characters and his own tumultuous, personal connection to them does not allow for it. By refusing to be sentimental, Crowe has made o ne of the livelier, soulful films about the 1970's that I've seen in quite a long time.
For more reviews, check out JERRY AT THE MOVIES at http://buffs.moviething.com/buffs/faust/
E-mail me with any questions, comments or general complaints at<EMAIL_ADDRESS>or at<EMAIL_ADDRESS>The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Compiler Services: Project Analysis
This tutorial demonstrates how to can analyze a whole project using services provided by the F# compiler.
NOTE: The FSharp.Compiler.Service API is subject to change when later versions of the nuget package are published.
Getting whole-project results
As in the previous tutorial (using untyped AST), we start by referencing
FSharp.Compiler.Service.dll
, opening the relevant namespace and creating an instance
of InteractiveChecker
:
1: 2: 3: 4: 5: 6: 7: 8: 9: 10: |
|
Here are our sample inputs:
1: 2: 3: 4: 5: 6: 7: 8: 9: 10: 11: 12: 13: 14: 15: 16: 17: 18: 19: 20: 21: 22: 23: 24: 25: 26: 27: 28: 29: 30: 31: 32: 33: 34: 35: |
|
We use GetProjectOptionsFromCommandLineArgs
to treat two files as a project:
1: 2: 3: 4: 5: 6: 7: 8: 9: 10: 11: 12: 13: 14: 15: 16: 17: 18: 19: 20: 21: 22: 23: 24: 25: 26: 27: 28: 29: 30: 31: 32: 33: 34: 35: 36: 37: 38: 39: 40: 41: |
|
Now check the entire project (using the files saved on disk):
1:
|
|
Now look at the errors and warnings:
1: 2: 3: 4: 5: 6: 7: |
|
Now look at the inferred signature for the project:
1: 2: 3: 4: |
|
You can also get all symbols in the project:
1: 2: 3: 4: 5: 6: 7: 8: 9: 10: 11: 12: |
|
After checking the whole project, you can access the background results for individual files in the project. This will be fast and will not involve any additional checking.
1: 2: 3: |
|
You can now resolve symbols in each file:
1: 2: 3: 4: 5: 6: 7: |
|
You can find out more about a symbol by doing type checks on various symbol kinds:
1: 2: 3: 4: 5: |
|
For each symbol, you can look up the references to that symbol:
1: 2: 3: |
|
You can iterate all the defined symbols in the inferred signature and find where they are used:
1: 2: 3: 4: |
|
You can also look at all the symbols uses in the whole project (including uses of symbols with local scope)
1: 2: 3: |
|
You can also request checks of updated versions of files within the project (note that the other files in the project are still read from disk, unless you are using the FileSystem API):
1: 2: 3: 4: 5: 6: 7: 8: 9: 10: 11: 12: 13: 14: 15: 16: 17: |
|
Again, you can resolve symbols and ask for references:
1: 2: 3: 4: 5: 6: 7: 8: 9: 10: 11: |
|
Or ask for all the symbols uses in the file (including uses of symbols with local scope)
1: 2: 3: |
|
Or ask for all the uses of one symbol in one file:
1: 2: 3: 4: 5: 6: 7: |
|
Analyzing multiple projects
If you have multiple F# projects to analyze which include references from some projects to others,
then the simplest way to do this is to build the projects and specify the cross-project references using
a -r:path-to-output-of-project.dll
argument in the ProjectOptions. However, this requires the build
of each project to succeed, producing the DLL file on disk which can be referred to.
In some situations, e.g. in an IDE, you may wish to allow references to other F# projects prior to successful compilation to
a DLL. To do this, fill in the ProjectReferences entry in ProjectOptions, which recursively specifies the project
options for dependent projects. Each project reference still needs a corresponding -r:path-to-output-of-project.dll
command line argument in ProjectOptions, along with an entry in ProjectReferences.
The first element of each tuple in the ProjectReferences entry should be the DLL name, i.e. path-to-output-of-project.dll
.
This should be the same as the text used in the -r
project reference.
When a project reference is used, the analysis will make use of the results of incremental analysis of the referenced F# project from source files, without requiring the compilation of these files to DLLs.
To efficiently analyze a set of F# projects which include cross-references, you should populate the ProjectReferences correctly and then analyze each project in turn.
NOTE: Project references are disabled if the assembly being referred to contains type provider components - specifying the project reference will have no effect beyond forcing the analysis of the project, and the DLL will still be required on disk.
Cracking a project file
F# projects normally use the '.fsproj' project file format.
A project cracking facility is provided as a separate NuGet package:
FSharp.Compiler.Service.ProjectCracker. This NuGet package contains a
library FSharp.Compiler.Service.ProjectCracker.dll, which should be
referenced by your application directly, and an executable
FSharp.Compiler.Service.ProjectCrackerTool.exe, which should be copied
into the output folder of your application by the build process. If
you install using Paket or NuGet, then this will be configured for you
automatically. If not, you should reference the provided .targets
file manually in your application. This can be found in the NuGet
package at build/net45/FSharp.Compiler.Service.ProjectCrackerTool.targets
.
The reason for this split is so that the analysis of an F# project file is performed out of process, in order that the necessary assembly binding redirects can be applied without requiring the caller to arrange this. In this way MSBuild versions from 4 up to 14 can be accommodated transparently.
In this example we get the project options for one of the project files in the F# Compiler Service project itself - you should also be able to use this technique for any project that builds cleanly using the command line tools 'xbuild' or 'msbuild'.
1: 2: 3: |
|
You can also request RELEASE mode and set other build configuration parameters:
1:
|
|
For debugging purposes it is also possible to obtain a detailed log from the assembly resolution process.
1:
|
|
Summary
As you have seen, the ParseAndCheckProject
lets you access results of project-wide analysis
such as symbol references. To learn more about working with symbols, see Symbols.
Using the FSharpChecker component in multi-project, incremental and interactive editing situations may involve knowledge of the FSharpChecker operations queue and the FSharpChecker caches.


C
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WORLD
Palette
Change
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Palette
Resources
Tools
paletton.com
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Pot Roast
Yields: 6
Preparation time: 15
Cooking time: 360
Ingredients
-
1 chuck roast (mine was 3 pounds)Olive oil1 pound carrots, peeled and cut into large chunks2 pounds potatoes, peeled and cut into large chunks1 onion, peeled and cut into large chunks2 stalks celery, cut into large chunks (optional)1 cup beef broth1 tablespoon corn starch2 tablespoons steak seasoning1 tablespoon kosher salt1 tablespoon dried thyme1 tablespoon dried rosemary
Directions
-
Mix all of the seasonings together in a small bowl, and set aside.Coat both sides of meat with olive oil. Sprinkle on a third of the seasoning mix onto each side.Sear both sides of the meat in a large skillet over medium-high heat. Transfer roast to slow cooker. Optionally use a slow cooker liner for easier cleanup.Place the vegetables in a large bowl. Drizzle on a little olive oil to coat vegetables. Sprinkle on the remaining seasoning mix. Add the vegetables to the same skillet that was used to sear the meat. Sauté for about five minutes - stirring occasionally.Transfer the vegetables to the top of the roast in the slow cooker. Pour in the beef broth. Cover with lid.Cook on low for 9 hours or on high for 6 hours in the slow cooker.Using a turkey baster or ladle, retrieve most of the cooking juices from the slow cooker and transfer to a small sauce pan.Bring to a simmer over medium heat on the stovetop.


LWP-DOWNLOAD
Section: User Contributed Perl Documentation (1)Updated: 2009-06-15
Index Return to Main Contents
NAME
lwp-download - Fetch large files from the webSYNOPSIS
lwp-download [-a] <url> [<local path>]DESCRIPTION
The lwp-download program will save the file at url to a local file.If local path is not specified, then the current directory is assumed.
If local path is a directory, then the basename of the file to save is picked up from the Content-Disposition header or the URL of the response. If the file already exists, then lwp-download will prompt before it overwrites and will fail if its standard input is not a terminal. This form of invocation will also fail is no acceptable filename can be derived from the sources mentioned above.
If local path is not a directory, then it is simply used as the path to save into.
The lwp-download program is implemented using the libwww-perl library. It is better suited to down load big files than the lwp-request program because it does not store the file in memory. Another benefit is that it will keep you updated about its progress and that you don't have much options to worry about.
Use the "-a" option to save the file in text (ascii) mode. Might make a difference on dosish systems.
EXAMPLE
Fetch the newest and greatest perl version:
$ lwp-download http://www.perl.com/CPAN/src/latest.tar.gz Saving to 'latest.tar.gz'... 11.4 MB received in 8 seconds (1.43 MB/sec)
AUTHOR
Gisle Aas<EMAIL_ADDRESS>Index
This document was created by man2html, using the manual pages.
Time: 05:29:05 GMT, December 24, 2015


Just loop through the characters and print first names:
Loop through and use polymorphic templates depending on characters role:


Welcome to the Department Of Homeless Services HOPE Quarterly Count Command Center
© Copyright 2016, NYC Department Of Homeless Services


Usage (Pytest plugin)¶
Once you install this package you can use it as a pytest plugin.
The following options are made available when running pytest:
--reload-loop
Running this flag starts an autoreloader when you start your tests. When you reach a test failure, you will be dropped into pdb to examine the error.
While you are in
pdb
mode, you can edit your project files and the autoreloader will install the new code. After you are confident that you have fixed the issue, you can leave the debugger with thec
(continue) command and the test will be run again.
--reload-dir
Choose what directory the autoreloader should look at. This directory is then considered the package root for puprposes of determining what package a file belongs to (and thus what directory to reload)
This defaults to the
pytest
invocation directory, but you might need to point to another directory if you do things like splitting your code intosrc
andtests
(wheresrc
is the package root)
Caveats (Pytest plugin)¶
Because the debugger needs to handle standard input, currently you always need to pass in -s when invoking pytest to avoid the default “capture standard input and output” behaviour of pytest.
I have hit some issues with editing the test code itself (that is to say the actively running test class/test function rather than the application code). This requires a bit more investigation
As always, when in doubt, tear down the entire program and restart


I'm sorry to disapoint you, but this very personal website of mine ain't awesome yet.
Why don't you try passing by again some other time? You might be surprised.
Meanwhile, you might drop me a mail at
renzocarbonara.com.ar.
Moreover, in case you need to send me something top-secret or check my signature, use
this PGP key.


Chapter 6 Programs:
- wireSphere: wire frame of recursively generated sphere
- shadedCube: rotating cube with modified Phong shading
- shadedSphere1: shaded sphere using true normals and per vertex shading
- shadedSphere2: shaded sphere using true normals and per fragment shading
- shadedSphere3: shaded sphere using vertex normals and per vertex shading
- shadedSphere4: shaded sphere using vertex normals and per fragment shading
- shadedSphereEyeSpace shows how lighting computations can be carried out in eye space
- shadedSphereObjectSpace shows how lighting computations can be carried out in object space


 I don't{% endraw %}
{% raw %}think' I should have known him if he had not related his{% endraw %}
{% raw %}experience to the congregation-which he did with great{% endraw %}
{% raw %}effect. WhUe he was expatiating eloquently on the dangers{% endraw %}
{% raw %}youth are exposed to from the influence of bad men of superior{% endraw %}
{% raw %}minds and powers of persuasion, he suddenly fixed his eye on{% endraw %}
{% raw %}some one iu the immense crowd, and caUed out: ' Jim ! I{% endraw %}
{% raw %}see you! WiU you not repent and be saved?' 'Yes,'{% endraw %}
{% raw %}answered a voice which I remembered, ' I Tiave repented—but{% endraw %}
{% raw %}I am not yet saved. I want you aU to pray for me' Here¬{% endraw %}
{% raw %}upon the minister made one of the most touching prayers I{% endraw %}
{% raw %}ever heard, and the hardened viUian wept like a chUd, while{% endraw %}
{% raw %}the congregation shouted, sung, and responded to the prayer.{% endraw %}
{% raw %}It was the strangest scene I ever witnessed."{% endraw %}
{% raw %}" I doubt if Jim was saved by all their prayers. What has{% endraw %}
{% raw %}become of Mauv.ais—is he still trading with the Indians ?"{% endraw %}
{% raw %}" No ; he has pretty much shaken off the Omahas, who{% endraw %}
{% raw %}were his last friends among the tribes. Any day you may see{% endraw %}
{% raw %}the little Frenchman driving over the country, pell-mell, as if{% endraw %}
{% raw %}the furies were after him, never stopping for lull or bridge, or{% endraw %}
{% raw %}any thing else It's a way he has of working off the extra vim of{% endraw %}
{% raw %}his excitable French nature. He still lives at the old trading-{% endraw %}
{% raw %}post, and when he is not driving is smoking cigars on the piazza.{% endraw %}
{% raw %}He gets thinner aud thinner, and one of these days must dry{% endraw %}
{% raw %}up and blow away, if he don't break his neck. He is nevei{% endraw %}
{% raw %}without friends, and never without something to treat them{% endraw %}
{% raw %}with ; and his eye twinkles as merrily as it used to, when he{% endraw %}
{% raw %}utters his pious benediction, ' the Lord be good to you, my{% endraw %}
{% raw %}friend !" or, his stUl more familiar expression, ' such is life on{% endraw %}
{% raw %}the upper Missouri!' But here we are at my door."{% endraw %}
{% raw %}Here we will leave them, reader; only pausing to assure{% endraw %}
{% raw %}you that the constable and his wife are no longer straitened in{% endraw %}
{% raw %}their circumstances, and that the Newcome claim has become{% endraw %}
{% raw %}their property.{% endraw %}
{% raw %}THE END.{% endraw %}


>>
<<
Usr
Pri
JfC
LJ
Phr
Dic
Voc
!:
Help
Primer
Atom
A noun that is a single entity is an atom.
23 'a' b =. 23 a =. 'q'
An atom has 0 dimensions.
>>
<<
Usr
Pri
JfC
LJ
Phr
Dic
Voc
!:
Help
Primer


Currently we support to fold files (path + name) contains "test/spec" or generated by program, such as ".pb.go/.pb.gw.go/.swagger.json".
Automatically fold files when pages initialize
Automatically set filters when pages initialize
Author Assignee


{% extends "layout.html" %} {% block styles %} {% endblock %} {% block body %}
Your password has been reset. You can now log in.
{% endif %}{{ errors }}
{% endif %}Have you forgotten your password?
Or maybe you want to create a new account?
If you run into any trouble, please get in touch.
{% for provider in oauth_providers %} {% set provider_icon = oauth_providers[provider].icon %} {% set provider_full_name = oauth_providers[provider].full_name %} {% endfor %}


Our goal is to help new independent musicians gain recognition by using the power their fanbase and supporters to reach new corners.
Stream a song for 1 beatcoin ($1 = 100 beatcoins), which goes to the artist. You can also download songs for 100 beatcoins. This will give you unlimited streams and the option to save that song to your desktop
As a musician, you earn money when someone streams or downloads your songs. If you need money now, you can raise a lump sum now in return for a chosen percentage of the song's earnings
Fund your favorite songs, and get a claim on the earnings. Then, share it with as many people. As the views increase, so will your earning! You can then pass the claim forward to another music fanatic in our easy to use secondary market.
Receive a welcome package of 100 beatcoins to stream. Over time, you will notice that the music keeps getting fresher - but your beatcoins never expire!
Create an accountA musician uploads a song, for which they are paid 1 cent each time it is streamed (over 30 seconds) and one dollar for each paid download. To meet current obligations, the musician can raise money against the a portion of earnings of the song.
True music fans are able to use this website to find the latest and least known songs from talented musicians - at only 1 cent per play. If they love a song, and beleive that it will reach heights, fans are able to fund the artist in return for claims of the song's earnings. Once invested in a song, the fan shares the link to their network - to introduce their friends to newest and best music, as well as increase the value of their claims. Later, the fan can sell his claims to other fans who want in on the action on our easy to use marketplace.
In addition to the 100 beatcoins we give you when you get started, we will deposit a 50 additional beatcoins for each successful referral. Of course, your friend will receive a welcome package too!
Share NowWhy are you doing this?
We believe that too many talented people are going unnoticed - and providing motivation for people to tell others about the incredible work is a great way for a new musician to reach a network beyond two degrees of separation.
How does Alphabeats Music make money?
Providing this platform is a costly affair. The way we make up for it is by taking 5 percent of transaction fees when claims of a song's income changes hands. We do not take a cut from streaming and downloads. Another revenue stream is in the form of featured song real estate. Artists are able to pay for their song to be displayed on one out of eight boxes in the home page.


Pranesh
PRESENTS
Handles Hover and JS Events
Easy To Use
A Pure CSS Plugin to flip your HTML contents
Flip in ALL Axis
Add Anything
Click to know more about me.
Need the Source Code???
Click here..


HOME
SERVICES
ABOUT
CONTACT
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1 week ago
Post Two
Skills for Success
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Skills Development
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The Importance of Ethics
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Best in the Outdoors category.
Shine at your next event.
For skateboarders, by skateboarders.
Rep that drip boy.
High School Vibes.
Glides like butter.


emnlp emnlp2012 emnlp2012-82 emnlp2012-82-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Yang Feng ; Yang Liu ; Qun Liu ; Trevor Cohn
Abstract: Decoding algorithms for syntax based machine translation suffer from high computational complexity, a consequence of intersecting a language model with a context free grammar. Left-to-right decoding, which generates the target string in order, can improve decoding efficiency by simplifying the language model evaluation. This paper presents a novel left to right decoding algorithm for tree-to-string translation, using a bottom-up parsing strategy and dynamic future cost estimation for each partial translation. Our method outperforms previously published tree-to-string decoders, including a competing left-to-right method.


{% include head.html %}
w.
home
posts by tag
posts
publications
talks
software
about
{{ content }}
{% include body_end.html %}


Anyone know a good build? I need to take 4 lvls of Assasin on the pw I play before I can take sd.
Thanks
something like 12 monk 5 SD 23 assassin.. would be good.. get's some SR.. self conceal later.. good death attack.. i'll go bash my head later for the actual build outline


jbLib is a MaxScript extension that contains a collection of new functions for use in MaxScript.
The current version is 7. This is defined in a global read-only variable jbLibVersion
, which you can use to check that jbLib.dlx is installed and up-to-date for your script. If you use these functions, it is encouraged that you wrap your script in an if
statement that does these checks, and gracefully bails if they fail. ie:
if (
local requiredVer = XXX
local str, failed = FALSE
if (jbLibVersion == undefined) then (
failed = TRUE; str = "This script requires jbLib.dlx to run properly."
) else if (requiredVer > jbLibVersion) then (
failed = TRUE; str = "The installed version of jbLib.dlx is out of date."
)
if (failed) then (
str += "\n\nYou can get the latest version at http://www.footools.com/.\n\nWould you like to connect there now?"
if (QueryBox str title:"Error") then ( try (ShellLaunch "http://www.footools.com/" "") catch () )
FALSE
) else ( TRUE )
) then (
... -- your script body goes here
)
Important: replace "XXX
" in the "local requiredVer = XXX
" line above with the current value of jbLibVersion
at the time you write the script. This way, your script becomes "locked" to require the jbLib version you're currently using.
If your script is a macroscript, the script body would be wrapped inside the above if
statement, and the macroscript definition (the "macroScript myMacro category:"MyCategory""
lines) would go around all of the above.
ApplyVertexColors <collapsedMesh> <lightModel> <doMix> <castShadows> <useMaps>
TRUE
on success, otherwise FALSE
.collapsedMesh
must be a collapsed editable mesh node, with no modifiers applied.lightModel
is an integer, where 0 is "Scene Lights" and 1 is "Diffuse".DeleteDirectory <pathName>
ElementFromFace <meshObject> <faceIndex>
EscapeHit
TRUE
if the escape key has been hit since the last time function has been called, otherwise FALSE
.TRUE
even if max does not have window focus.FALSE
, and forget to call this function inside your main loop, at which point max will appear to have crashed (since you can't break out of the loop by holding escape).
escapeEnable = FALSE
do (
-- your code here
) while NOT EscapeHit()
escapeEnable = TRUE
EvalTextureColorPoint <texture> <XYZ> <UVW>
GetClosestVertex <meshObject> <point3>
GetHitDistances <meshObject> <point3 p1> <point3 p2>
p1
and p2
).IntersectRay
, but returns all hit points along the "ray" instead of just the front-most.GetRegistrySetting <rootKeyName> <keyPath> <valueName>
SetRegistrySetting <rootKeyName> <keyPath> <valueName> <value>
rootKeyName
can be one of:
#HKEY_CLASSES_ROOT
#HKEY_CURRENT_CONFIG
#HKEY_CURRENT_USER
#HKEY_LOCAL_MACHINE
(Get only)
#HKEY_USERS
(Get only)
keyPath
is the full path to the key in question. (ie. "Software\\Microsoft\\Internet Explorer"
)valueName
is the name of the value in question (ie. "Download Directory"
)value
is the value to be set (ie. "C:\\MyDownloads"
)Get
is the value in question, or undefined if it doesn't exist.Set
is true
on success.try()catch()
block.GetSpaceWarpForce <spaceWarpNode> <point3>
SpaceWarpSupportsForce
to check if the given spacewarp will work or not.GetUNCPath <filenamePath>
undefined
if the path can't be converted (ie. is a local drive).IsActive <atmospheric | effect>
IsParticleSystem <node>
MoveFile <oldName> <newName>
oldName
and newName
must be full paths, including the filename). TRUE on success, otherwise FALSE.scanlineRenderEx struct
antiAliasing (boolean)
shadows (boolean)
mapping (boolean)
filterMaps (boolean)
forceWireframe (boolean)
autoReflect (boolean)
imageMotionBlur (boolean)
objectMotionBlur (boolean)
wireThickness (float, write only)
autoReflectLevels (integer, write only)
objectBlurDuration (float, write only)
objectBlurSubdivisions (integer, write only)
objectBlurSamples (integer, write only)
imageBlurDuration (float, write only)
SpaceWarpSupportsForce <spaceWarpNode>
GetSpaceWarpForce
function.


Package org.apache.qpid.protonj2.engine
Interface Engine
-
- All Superinterfaces:
Consumer<ProtonBuffer>
- All Known Implementing Classes:
ProtonEngine
public interface Engine extends Consumer<ProtonBuffer>
AMQP Engine interface.
-
-
Method Summary
All Methods Instance Methods Abstract Methods Default Methods Modifier and Type Method Description default void
accept(ProtonBuffer input)
Provide data input for this Engine from some external source.EngineConfiguration
configuration()
Gets the Configuration for this engine.Connection
connection()
Gets theConnection
instance that is associated with thisEngine
instance.EngineStateException
engineFailed(Throwable cause)
Transition theEngine
to a failed state if not already closed or closing.Engine
errorHandler(EventHandler<Engine> engineFailure)
Sets a handler instance that will be notified when the engine encounters a fatal error.Throwable
failureCause()
Engine
ingest(ProtonBuffer input)
Provide data input for this Engine from some external source.boolean
isFailed()
boolean
isRunning()
boolean
isShutdown()
boolean
isWritable()
Returns true if the engine is accepting input from the ingestion entry points.default Engine
outputConsumer(Consumer<ProtonBuffer> consumer)
Sets aConsumer
instance that will be notified when data from the engine is ready to be written to some output sink (socket etc).Engine
outputHandler(BiConsumer<ProtonBuffer,Runnable> output)
Sets aBiConsumer
instance that will be notified when data from the engine is ready to be written to some output sink (socket etc).default Engine
outputHandler(EventHandler<ProtonBuffer> output)
Sets a handler instance that will be notified when data from the engine is ready to be written to some output sink (socket etc).EnginePipeline
pipeline()
Gets the EnginePipeline for this Engine.EngineSaslDriver
saslDriver()
Gets the SASL driver for this engine, if no SASL layer is configured then a default no-op driver must be returned that indicates this.Engine
shutdown()
Shutdown the engine preventing any future outbound or inbound processing.Engine
shutdownHandler(EventHandler<Engine> engineShutdownEventHandler)
Sets a handler instance that will be notified when the engine is shut down via a call to theshutdown()
method is called.Connection
start()
Starts the engine and returns theConnection
instance that is bound to this Engine.EngineState
state()
long
tick(long currentTime)
Prompt the engine to perform idle-timeout/heartbeat handling, and return an absolute deadline in milliseconds that tick must again be called by/at, based on the provided current time in milliseconds, to ensure the periodic work is carried out as necessary.Engine
tickAuto(ScheduledExecutorService executor)
Allows the engine to manage idle timeout processing by providing it the single threaded executor context where all transport work is done which ensures singled threaded access while removing the need for the client library or server application to manage calls to thetick(long)
methods.
-
-
-
Method Detail
-
isWritable
boolean isWritable()
Returns true if the engine is accepting input from the ingestion entry points.When false any attempts to write more data into the engine will result in an error being returned from the write operation. An engine that has not been started or that has been failed or shutdown will report as not writable.
- Returns:
- true if the engine is current accepting more input.
-
isRunning
boolean isRunning()
- Returns:
- true if the Engine has entered the running state and is not failed or shutdown.
-
isShutdown
boolean isShutdown()
- Returns:
- true if the Engine has been shutdown and is no longer usable.
-
isFailed
boolean isFailed()
- Returns:
- true if the Engine has encountered a critical error and cannot produce new data.
-
failureCause
Throwable failureCause()
- Returns:
- the error that caused the
Engine
fail and shutdown (or null if not failed).
-
state
EngineState state()
- Returns:
- the current state of the engine.
-
connection
Connection connection()
Gets theConnection
instance that is associated with thisEngine
instance. It is valid for an engine implementation to not return aConnection
instance prior to the engine having been started.- Returns:
- the
Connection
that is linked to this engine instance.
-
start
Connection start() throws EngineStateException
Starts the engine and returns theConnection
instance that is bound to this Engine. A non-started Engine will not allow ingestion of any inbound data and a Connection linked to the engine that was obtained from theconnection()
method cannot produce any outbound data.- Returns:
- the Connection instance that is linked to this
Engine
- Throws:
EngineStateException
- if the Engine state has already transition to shutdown or failed.
-
shutdown
Engine shutdown()
Shutdown the engine preventing any future outbound or inbound processing. When the engine is shut down any resources,Connection
,Session
orLink
instances that have an engine shutdown event handler registered will be notified and should react by locally closing that resource if they wish to ensure that the resource's local close event handler gets signaled if that resource is not already locally closed.- Returns:
- this
Engine
-
engineFailed
EngineStateException engineFailed(Throwable cause)
Transition theEngine
to a failed state if not already closed or closing. If called when the engine has not failed the engine will be transitioned to the failed state and the method will return an appropriateEngineFailedException
that wraps the given cause. If called after the engine was shutdown the method returns anEngineShutdownException
indicating that the engine was already shutdown. Repeated calls to this method while the engine is in the failed state must not alter the original failure error or elicit new engine failed event notifications.- Parameters:
cause
- The exception that caused the engine to be forcibly transitioned to the failed state.- Returns:
- an
EngineStateException
that can be thrown indicating the failure and engine state.
-
ingest
Engine ingest(ProtonBuffer input) throws EngineStateException
Provide data input for this Engine from some external source. If the engine is not writable when this method is called anEngineNotWritableException
will be thrown if unless the reason for the not writable state is due to engine failure or the engine already having been shut down in which case the appropriateEngineStateException
will be thrown to indicate the reason.- Parameters:
input
- The data to feed into to Engine.- Returns:
- this
Engine
- Throws:
EngineStateException
- if the Engine state precludes accepting new input.
-
accept
default void accept(ProtonBuffer input) throws EngineStateException
Provide data input for this Engine from some external source. If the engine is not writable when this method is called anEngineNotWritableException
will be thrown if unless the reason for the not writable state is due to engine failure or the engine already having been shut down in which case the appropriateEngineStateException
will be thrown to indicate the reason.- Specified by:
accept
in interfaceConsumer<ProtonBuffer>
- Parameters:
input
- The data to feed into to Engine.- Throws:
EngineStateException
- if the Engine state precludes accepting new input.
-
tick
long tick(long currentTime) throws IllegalStateException, EngineStateException
Prompt the engine to perform idle-timeout/heartbeat handling, and return an absolute deadline in milliseconds that tick must again be called by/at, based on the provided current time in milliseconds, to ensure the periodic work is carried out as necessary. It is an error to call this method if the connection has not been opened. A returned deadline of 0 indicates there is no periodic work necessitating tick be called, e.g. because neither peer has defined an idle-timeout value. The provided milliseconds time values should be derived from a monotonic source such asSystem.nanoTime()
to prevent wall clock changes leading to erroneous behaviour. Note that forSystem.nanoTime()
derived values in particular that the returned deadline could be a different sign than the originally given value, and so (if non-zero) the returned deadline should have the current time originally provided subtracted from it in order to establish a relative time delay to the next deadline. SupplyingSystem.currentTimeMillis()
derived values can lead to erroneous behaviour during wall clock changes and so is not recommended. It is an error to call this method iftickAuto(ScheduledExecutorService)
was called.- Parameters:
currentTime
- the current time of this tick call.- Returns:
- the absolute deadline in milliseconds to next call tick by/at, or 0 if there is none.
- Throws:
IllegalStateException
- if theEngine
is already performing auto tick handling.EngineStateException
- if the Engine state precludes accepting new input.
-
tickAuto
Engine tickAuto(ScheduledExecutorService executor) throws IllegalStateException, EngineStateException
Allows the engine to manage idle timeout processing by providing it the single threaded executor context where all transport work is done which ensures singled threaded access while removing the need for the client library or server application to manage calls to thetick(long)
methods.- Parameters:
executor
- The single threaded execution context where all engine work takes place.- Returns:
- this
Engine
- Throws:
IllegalStateException
- if theEngine
is already performing auto tick handling.EngineStateException
- if the Engine state precludes accepting new input.
-
pipeline
EnginePipeline pipeline()
Gets the EnginePipeline for this Engine.- Returns:
- the
EnginePipeline
for thisEngine
.
-
configuration
EngineConfiguration configuration()
Gets the Configuration for this engine.- Returns:
- the configuration object for this engine.
-
saslDriver
EngineSaslDriver saslDriver()
Gets the SASL driver for this engine, if no SASL layer is configured then a default no-op driver must be returned that indicates this. The SASL driver provides the engine with client and server side SASL handshaking support. AnEngine
implementation can support pluggable SASL drivers or exert tight control over the driver as it sees fit.- Returns:
- the SASL driver for the engine.
-
outputHandler
default Engine outputHandler(EventHandler<ProtonBuffer> output)
Sets a handler instance that will be notified when data from the engine is ready to be written to some output sink (socket etc).- Parameters:
output
- TheProtonBuffer
handler instance that performs IO for the engine output.- Returns:
- this
Engine
-
outputConsumer
default Engine outputConsumer(Consumer<ProtonBuffer> consumer)
Sets aConsumer
instance that will be notified when data from the engine is ready to be written to some output sink (socket etc).- Parameters:
consumer
- TheProtonBuffer
consumer instance that performs IO for the engine output.- Returns:
- this
Engine
-
outputHandler
Engine outputHandler(BiConsumer<ProtonBuffer,Runnable> output)
Sets aBiConsumer
instance that will be notified when data from the engine is ready to be written to some output sink (socket etc). TheRunnable
value provided (if non-null) should be invoked once the I/O operation has completely successfully. If the event of an error writing the data the handler should throw an error or if performed asynchronously theEngine
should be marked failed via a call toengineFailed(Throwable)
.- Parameters:
output
- TheProtonBuffer
handler instance that performs IO for the engine output.- Returns:
- this
Engine
-
errorHandler
Engine errorHandler(EventHandler<Engine> engineFailure)
Sets a handler instance that will be notified when the engine encounters a fatal error.- Parameters:
engineFailure
- TheProtonException
handler instance that will be notified if the engine fails.- Returns:
- this
Engine
-
shutdownHandler
Engine shutdownHandler(EventHandler<Engine> engineShutdownEventHandler)
Sets a handler instance that will be notified when the engine is shut down via a call to theshutdown()
method is called.
-
-


Excellent so to no sincerity smallness. Removal request delight if on he we.
The booking amount will be debited from your credit card once the booking is completed.
The booking amount will be debited from your account once the booking is completed.
After clicking 'Book Now' you will be directed to Paypal to complete payment. You must complete the process or the booking will not occur . Afterwards you will be redirected to us again.
Prepared is me marianne: pleasure likewise debating. Wonder an unable except better stairs do ye admire.
Maids table how learn drift but purse stand yet set. Music me house could among oh as their. Piqued our sister shy nature almost his wicket. Hand dear so we hour to.


Unsolved crimes: DLC - Crime Stoppers
by Crime StoppersYou could have the missing piece of the puzzle that will help the RCMP put someone behind bars. Here are some recent crimes that Central Okanagan Crime Stoppers hope you can help solve by calling our anonymous tips line at 1-800-222-TIPS (8477) or visit our website at www.crimestoppers.net
CRIME: BREAK-IN AT PUB
DATE: November 17, 2019
RCMP FILE: 2019-72088
Security personnel from Turtle Bay Pub located on Woodsdale Road in Lake Country contacted RCMP at about 5 a.m. on November 8th when an alarm was activated at the premises. Upon arrival, the front door was found damaged and insecure, however nothing else was damaged or missing. Surveillance video shows two suspects entering the premises and attempting to move the ATM before being spooked by the alarm.  A witness watched the two suspects run to an older model dark truck, possible a Ford, and drive northbound toward Vernon.
?
If you know anything about this crime, or any other crime, call the Central Okanagan Crime Stoppers’ anonymous tips line at 1-800-222-TIPS or visit our website at www.crimestoppers.net. Your information will be kept confidential and could lead to a reward of up to $2000.00.
CRIME: MISCHIEF
DATE: November 14, 2019
RCMP FILE: 2019-71487
An act of vandalism was reported to Lake Country RCMP on November 14, 2019. Sometime overnight someone threw white paint on the passenger side of a 2019 Nissan Murano parked on the 10700 block of Hare Road, located near Okanagan Centre Road West. If you know anything about this random act, please contact Lake Country RCMP.
You can help catch these suspects and qualify for a reward by calling Crime Stoppers’ anonymous tips line at 1-800-222-TIPS (8477) or visit our website at www.crimestoppers.net.


Components of A Full-Stack Development System
- Editor
- Documentation System
- Debugger, Profiler (sometimes mine)
- Test System
- REPL (Read/Eval/Print loop)
- Version Control
- A Virtual environment (e.g. rvm, pythonbrew, perlbrew)
- Virtual servers (VMPlayer, virtualbox, Xen, AWS, Google App, Heroku)
Some of the above are covered in an IDE. Some are covered in Project hosting
Smallish things I'm going to briefly cover
- Project Hosting
- Continuous Testing
- REPL (Read/Eval/Print loop)
- Virtual Environment
Project Hosting: Github
- The Gold Standard — for git
- Constantly Improving
- Social rating via: stars, follow, and fork
- Service hooks
- Private repositories
- One of the first
- git, hg, or svn
- Downloads Section and Stats
- Import from code.google.com
Fun fact: is part of slashdot, thinkgeek, and now dice
But what about private repositories?
- Unlimited private repositories
- Pay to make public
- Same folks as Jira
Continuous Integration: travis.org
- Hooks into github
- Multiple Versions of a Programming-Languages
- For some things, can be real simple
But what about for code.google.com?
Continuous Integration: drone.io
And bitbucket?
REPLs and Debuggers
REPL — Read, Eval, Print, Loop
Debuggers often contain a REPL. Debugger is a REPL with context set up
REPL Examples
- Python:
python
...
or ipython
- Ruby:
irb
- Perl:
perl -e '...'
...
- And for bash, zsh,...?
bash
, zsh
non-Programming Languages REPLs
- Rails:
rails console
- Mysql:
mysql
- Mongo:
mongo
But what about Go?
Virtual Environments
But what about a virtual environment for Databases, e.g. mysql, postgres?


biotmle
vignettes/exposureBiomarkers.Rmd
exposureBiomarkers.Rmd
The biotmle
R package can be used to isolate biomarkers in two ways: based on the associations of genomic objects with an exposure variable of interest. In this vignette, we illustrate how to use biotmle
to isolate and visualize genes associated with an exposure, using a data set containing microarray expression measures from an Illumina platform. In the analysis described below, targeted maximum likelihood estimation (TMLE) is used to transform the microarray expression values based on the influence curve representation of the Average Treatment Effect (ATE). Following this transformation, the moderated t-statistic of Smyth (Smyth 2004) is used to test for a binary group-wise difference (based on the exposure variable), using the tools provided by the R package limma
).
For a general discussion of the framework of targeted maximum likelihood estimation and the role this approach plays in statistical causal inference, the interested reader is invited to consult van der Laan and Rose (2011) and van der Laan and Rose (2018). For a more general introduction to the principles of statistical causal inference, Pearl (2000) serves well.
First, we load the biotmle
package and the (included) illuminaData
data set:
library(dplyr)
library(biotmle)
library(biotmleData)
library(BiocParallel)
library(SuperLearner)
library(SummarizedExperiment, quietly=TRUE)
data(illuminaData)
set.seed(13847)
In order to perform Targeted Minimum Loss-Based Estimation, we need three separate data structures: (1) W, baseline covariates that could potentially confound the association of biomarkers with the exposure of interest; (2) A, the exposure of interest; and (3) Y, the biomarkers of interest. All values in W and A ought to be discretized, in order to avoid practical violations of the assumption of positivity. With the illuminaData
data set below, we discretize the age variable in the phenotype-level data below (this can be accessed via the colData
of the SummarizedExperiment
object). To invoke the biomarker assessment function (biomarkertmle
), we also need to specify a variable of interest (or the position of said variable in the design matrix). We do both in just a few lines below:
# discretize "age" in the phenotype-level data
colData(illuminaData) <- colData(illuminaData) %>%
data.frame %>%
mutate(age = as.numeric(age > median(age))) %>%
DataFrame
benz_idx <- which(names(colData(illuminaData)) %in% "benzene")
The TMLE-based biomarker discovery process can be invoked using the biomarkertmle
function. The procedure is quite resource-intensive because it evaluates the association of each individual potential biomarker (of which there are over 20,000 in the included data set) with an exposure of interest, while accounting for potential confounding based on all other covariates included in the design matrix. We demonstrate the necessary syntax for calling the biomarkertmle
function below, on a small number of the probes:
# compute TML estimates to evaluate differentially expressed biomarkers
biotmle_out <- biomarkertmle(se = illuminaData[1:20, ],
varInt = benz_idx,
g_lib = c("SL.mean", "SL.glm"),
Q_lib = c("SL.bayesglm", "SL.ranger"),
cv_folds = 2,
bppar_type = SerialParam()
)
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Note that parallelization is controlled entirely through the BiocParallel
package, and we set SerialParam()
here for sequential evaluation.
The output of biomarkertmle
is an object of class bioTMLE
, containing four new slots: (1) call
, the call to biomarkertmle
; (2) topTable
, an empty slot meant to hold the output of limma::topTable
, after a later call to modtest_ic
; and (3) tmleOut
, a data.frame
containing the point estimates of the associations of each biomarker with the exposure of interest based on the influence curve representation of the Average Treatment Effect.
The output of biomarkertmle
can be directly fed to modtest_ic
, a wrapper around limma::lmFit
and limma::topTable
that outputs a biotmle
object with the slots described above completely filled in. The modtest_ic
function requires as input a biotmle
object containing a data frame in the tmleOut
field as well as a design matrix indicating the groupwise difference to be tested. The design matrix should contain an intercept term and a term for the exposure of interest (with discretized exposure levels). Based on the relevant statistical theory, it is not appropriate to include any further terms in the design matrix (n.b., this differs from standard calls to limma::lmFit
).
modtmle_out <- modtest_ic(biotmle = biotmle_out)
After invoking modtest_ic
, the resultant bioTMLE
object will contain all information relevant to the analytic procedure for identifying biomarkers: that is, it will contain the original call to biomarkertmle
, the result of running limma::topTable
, and the result of running biomarkertmle
. The statistical results of this procedure can be extracted from the topTable
object in the bioTMLE
object produced by modtest_ic
.
This package provides several plotting methods that can be used to visualize the results of the TMLE-based biomarker discovery process. We demonstrate the syntax for calling the generic plotting methods below but refrain from showing the plots themselves since they are not particularly informative.
The plot
method for a bioTMLE
object will produce a histogram of the adjusted p-values of each biomarker (based on the Benjamini-Hochberg procedure for controlling the False Discovery Rate) as generated by limma::topTable
:
plot(x = modtmle_out, type = "pvals_adj")
Setting the argument type = "pvals_raw"
will instead produce a histogram of the raw p-values (these are less informative and should, in general, not be used for inferential purposes, as the computation producing these p-values ignores the multiple testing nature of the biomarker discovery problem):
plot(x = modtmle_out, type = "pvals_raw")
Heatmaps are useful graphics for visualizing the relationship between measures on genomic objects and covariates of interest. The heatmap_ic
function provides this graphic for bioTMLE
objects, allowing for the relationship between the exposure variable and some number of “top” biomarkers (as determined by the call to modtest_ic
) to be visualized. In general, the heatmap for bioTMLE
objects expresses how the contributions of each biomarker to the Average Treatment Effect (ATE) vary across differences in the exposure variable (that is, there is a causal interpretation to the findings). The plot produced is a ggplot2
object and can be modified in place if stored properly. For our analysis:
benz_idx <- which(names(colData(illuminaData)) %in% "benzene")
designVar <- as.data.frame(colData(illuminaData))[, benz_idx]
designVar <- as.numeric(designVar == max(designVar))
# build heatmap
heatmap_ic(x = modtmle_out, left.label = "none", scale = TRUE,
clustering.method = "hierarchical", row.dendrogram = TRUE,
design = designVar, FDRcutoff = 1, top = 10)
The heatmap produced in this way is actually a form of supervised clustering, as described more generally (as supervised distance matrices) by Pollard and van der Laan (2008), wherein the notion of deriving clustering procedures from the results of supervised learning methods is formulated. Since the heatmap is based on the contributions of observations to the efficient influence function (EIF) of the target parameter, it directly visualizes the degree to which each biomarker informs the difference (due to the treatment effect) represented by the average treatment effect.
The volcano plot is standard graphical tools for examining how changes in expression relate to the raw p-value. The utility of such plots lies in their providing a convenient way to identify and systematically ignore those genomic objects that have extremely low p-values due to extremely low variance between observations. The volcano_ic
function provides much of the same interpretation, except that the fold change values displayed in the x-axis refer to changes in the contributions of each biomarker to the Average Treatment Effect (in standard practice, for microarray technology, these would be fold changes in gene expression). The plot produced is a ggplot2
object and, as such, can be modified in place.  Causality: Models, Reasoning, and Inference. Cambridge University Press.
Pollard, Katherine S, and Mark J van der Laan. 2008. “Supervised Distance Matrices.” Statistical Applications in Genetics and Molecular Biology 7 (1).
Smyth, Gordon K. 2004. “Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments.” Statistical Applications in Genetics and Molecular Biology 3 (1): 1–25. https://doi.org/10.2202/1544-6115.1027.
van der Laan, Mark J., and Sherri Rose. 2011. Targeted Learning: Causal Inference for Observational and Experimental Data. Springer Science & Business Media.
van der Laan, Mark J, and Sherri Rose. 2018. Targeted Learning in Data Science: Causal Inference for Complex Longitudinal Studies. Springer Science & Business Media.


class CMAESDataLogger(_BaseDataLogger):
data logger for class CMAES
, that can record and plot data.
Examples
The data may come from fmin
or CMAES
and the simulation may
still be running in a different Python shell.
Use the default logger from CMAES
:
>>> try: import cma.purecma as pcma ... except ImportError: import purecma as pcma >>> es = pcma.CMAES(3 * [0.1], 1) >>> isinstance(es.logger, pcma.CMAESDataLogger) # type(es.logger) True >>> while not es.stop(): ... X = es.ask() ... es.tell(X, [pcma.ff.elli(x) for x in X]) ... es.logger.add(es) # doctest: +SKIP >>> es.logger.save() >>> # es.logger.plot() #
Load and plot previously generated data:
>>> logger = pcma.CMAESDataLogger().load() >>> logger.filename == "_CMAESDataLogger_datadict.py" True
>>> # logger.plot()
TODO: the recorded data are kept in memory and keep growing, which may well lead to performance issues for (very?) long runs. Ideally, it should be possible to dump data to a file and clear the memory and also to downsample data to prevent plotting of long runs to take forever. "], 'key': " or "]}" is the place where to prepend/append new data in the file.
| Method | __init__ |
verb_modulo controls whether and when logging takes place for each call to the method add |
| Method | add |
append some logging data from CMAES class instance es , if number_of_times_called modulo verb_modulo equals zero |
| Method | load |
load data from file name or self.filename |
| Method | plot |
plot the stored data in figure fig_number . |
| Method | save |
save data to file name or self.filename |
| Class Variable | plotted |
plot count for all instances |
| Instance Variable | counter |
Undocumented |
| Instance Variable | filename |
file to save to or load from unless specified otherwise |
| Instance Variable | modulo |
Undocumented |
| Instance Variable | optim |
object instance to be logging data from |
| Instance Variable | _data |
dict of logged data |
Inherited from BaseDataLogger
:
| Method | disp |
abstract method, display some data trace |
| Method | register |
register an optimizer optim, only needed if method add is called without passing the optim argument |
| Property | data |
logged data in a dictionary |
cma.interfaces.BaseDataLogger.__init__
verb_modulo
controls whether and when logging takes place
for each call to the method add
cma.interfaces.BaseDataLogger.add
append some logging data from CMAES class instance es
,
if number_of_times_called modulo verb_modulo equals zero
cma.interfaces.BaseDataLogger.plot
plot the stored data in figure fig_number
.
Dependencies: matlabplotlib.pylab
cma.interfaces.BaseDataLogger.filename
file to save to or load from unless specified otherwise


Macbeth
Plot Overview
The play begins with the brief appearance of a trio of witches and then moves to a military camp, where the Scottish King Duncan hears the news that his generals, Macbeth and Banquo, have defeated two separate invading armies—one from Ireland, led by the rebel Macdonwald, and one from Norway. Following their pitched battle with these enemy forces, Macbeth and Banquo encounter the witches as they cross a moor.
The witches prophesy that Macbeth will be made thane (a rank of Scottish nobility) of Cawdor and eventually King of Scotland. They also prophesy that Macbeth’s companion, Banquo, will beget a line of Scottish kings, although Banquo will never be king himself. The witches vanish, and Macbeth and Banquo treat their prophecies skeptically until some of King Duncan’s men come to thank the two generals for their victories in battle and to tell Macbeth that he has indeed been named thane of Cawdor.


{% extends "layouts/jumbotron_layout.html" %} {# is rendered in the content block of main.html view view #} {% block content %}
You can watch the 10 Minute intro video or follow the 3 step quickstart documentation below.
Generate you first model (including controller and scaffolding) by:"
python generate_model.py modelname
This will automatically generate a model, the related controller, the scaffolding as well as the REST-routes to access it. All fully automatic.
python do_migrate -d up
python server.py
localhost:8000/modelname