Monitoring Apache Flink Applications 101
February 21, 2019 - Konstantin Knauf (@snntrable)
This blog post provides an introduction to Apache Flink’s built-in monitoring and metrics system, that allows developers to effectively monitor their Flink jobs. Oftentimes, the task of picking the relevant metrics to monitor a Flink application can be overwhelming for a DevOps team that is just starting with stream processing and Apache Flink. Having worked with many organizations that deploy Flink at scale, I would like to share my experience and some best practice with the community.
With business-critical applications running on Apache Flink, performance monitoring becomes an increasingly important part of a successful production deployment. It ensures that any degradation or downtime is immediately identified and resolved as quickly as possible.
Monitoring goes hand-in-hand with observability, which is a prerequisite for troubleshooting and performance tuning. Nowadays, with the complexity of modern enterprise applications and the speed of delivery increasing, an engineering team must understand and have a complete overview of its applications’ status at any given point in time.
Flink’s Metrics System #
The foundation for monitoring Flink jobs is its metrics
system
which consists of two components; Metrics
and MetricsReporters
.
Metrics #
Flink comes with a comprehensive set of built-in metrics such as:
- Used JVM Heap / NonHeap / Direct Memory (per Task-/JobManager)
- Number of Job Restarts (per Job)
- Number of Records Per Second (per Operator)
- …
These metrics have different scopes and measure more general (e.g. JVM or operating system) as well as Flink-specific aspects.
As a user, you can and should add application-specific metrics to your functions. Typically these include counters for the number of invalid records or the number of records temporarily buffered in managed state. Besides counters, Flink offers additional metrics types like gauges and histograms. For instructions on how to register your own metrics with Flink’s metrics system please check out Flink’s documentation. In this blog post, we will focus on how to get the most out of Flink’s built-in metrics.
MetricsReporters #
All metrics can be queried via Flink’s REST API. However, users can configure MetricsReporters to send the metrics to external systems. Apache Flink provides reporters to the most common monitoring tools out-of-the-box including JMX, Prometheus, Datadog, Graphite and InfluxDB. For information about how to configure a reporter check out Flink’s MetricsReporter documentation.
In the remaining part of this blog post, we will go over some of the most important metrics to monitor your Apache Flink application.
Monitoring General Health #
The first thing you want to monitor is whether your job is actually in a RUNNING state. In addition, it pays off to monitor the number of restarts and the time since the last restart.
Generally speaking, successful checkpointing is a strong indicator of the general health of your application. For each checkpoint, checkpoint barriers need to flow through the whole topology of your Flink job and events and barriers cannot overtake each other. Therefore, a successful checkpoint shows that no channel is fully congested.
Key Metrics
| Metric | Scope | Description |
|---|---|---|
uptime |
job | The time that the job has been running without interruption. |
fullRestarts |
job | The total number of full restarts since this job was submitted. |
numberOfCompletedCheckpoints |
job | The number of successfully completed checkpoints. |
numberOfFailedCheckpoints |
job | The number of failed checkpoints. |
Example Dashboard Panels
Uptime (35 minutes), Restarting Time (3 milliseconds) and Number of Full Restarts (7)
Completed Checkpoints (18336), Failed (14)
Possible Alerts
ΔfullRestarts
>threshold
ΔnumberOfFailedCheckpoints
>threshold
Monitoring Progress & Throughput #
Knowing that your application is RUNNING and checkpointing is working fine is good, but it does not tell you whether the application is actually making progress and keeping up with the upstream systems.
Throughput #
Flink provides multiple metrics to measure the throughput of our application. For each operator or task (remember: a task can contain multiple chained tasks Flink counts the number of records and bytes going in and out. Out of those metrics, the rate of outgoing records per operator is often the most intuitive and easiest to reason about.
Key Metrics
| Metric | Scope | Description |
|---|---|---|
numRecordsOutPerSecond |
task | The number of records this operator/task sends per second. |
numRecordsOutPerSecond |
operator | The number of records this operator sends per second. |
Example Dashboard Panels
Mean Records Out per Second per Operator
Possible Alerts
recordsOutPerSecond
=0
(for a non-Sink operator)
Note: Source operators always have zero incoming records. Sink operators always have zero outgoing records because the metrics only count Flink-internal communication. There is a JIRA ticket to change this behavior.
Progress #
For applications, that use event time semantics, it is important that watermarks progress over time. A watermark of time t tells the framework, that it should not anymore expect to receive events with a timestamp earlier than t, and in turn, to trigger all operations that were scheduled for a timestamp < t. For example, an event time window that ends at t = 30 will be closed and evaluated once the watermark passes 30.
As a consequence, you should monitor the watermark at event time-sensitive operators in your application, such as process functions and windows. If the difference between the current processing time and the watermark, known as even-time skew, is unusually high, then it typically implies one of two issues. First, it could mean that your are simply processing old events, for example during catch-up after a downtime or when your job is simply not able to keep up and events are queuing up. Second, it could mean a single upstream sub-task has not sent a watermark for a long time (for example because it did not receive any events to base the watermark on), which also prevents the watermark in downstream operators to progress. This JIRA ticket provides further information and a work around for the latter.
Key Metrics
| Metric | Scope | Description |
|---|---|---|
currentOutputWatermark |
operator | The last watermark this operator has emitted. |
Example Dashboard Panels
Event Time Lag per Subtask of a single operator in the topology. In this case, the watermark is lagging a few seconds behind for each subtask.
Possible Alerts
currentProcessingTime - currentOutputWatermark
>threshold
“Keeping Up” #
When consuming from a message queue, there is often a direct way to monitor if your application is keeping up. By using connector-specific metrics you can monitor how far behind the head of the message queue your current consumer group is. Flink forwards the underlying metrics from most sources.
Key Metrics
| Metric | Scope | Description |
|---|---|---|
records-lag-max |
user | applies to FlinkKafkaConsumer . The maximum lag in terms of the number of records for any partition in this window. An increasing value over time is your best indication that the consumer group is not keeping up with the producers. |
millisBehindLatest |
user | applies to FlinkKinesisConsumer . The number of milliseconds a consumer is behind the head of the stream. For any consumer and Kinesis shard, this indicates how far it is behind the current time. |
Possible Alerts
records-lag-max
>threshold
millisBehindLatest
>threshold
Monitoring Latency #
Generally speaking, latency is the delay between the creation of an event and the time at which results based on this event become visible. Once the event is created it is usually stored in a persistent message queue, before it is processed by Apache Flink, which then writes the results to a database or calls a downstream system. In such a pipeline, latency can be introduced at each stage and for various reasons including the following:
- It might take a varying amount of time until events are persisted in the message queue.
- During periods of high load or during recovery, events might spend some time in the message queue until they are processed by Flink (see previous section).
- Some operators in a streaming topology need to buffer events for some time (e.g. in a time window) for functional reasons.
- Each computation in your Flink topology (framework or user code), as well as each network shuffle, takes time and adds to latency.
- If the application emits through a transactional sink, the sink will only commit and publish transactions upon successful checkpoints of Flink, adding latency usually up to the checkpointing interval for each record.
In practice, it has proven invaluable to add timestamps to your events at multiple stages (at least at creation, persistence, ingestion by Flink, publication by Flink, possibly sampling those to save bandwidth). The differences between these timestamps can be exposed as a user-defined metric in your Flink topology to derive the latency distribution of each stage.
In the rest of this section, we will only consider latency, which is introduced inside the Flink topology and cannot be attributed to transactional sinks or events being buffered for functional reasons (4.).
To this end, Flink comes with a feature called Latency Tracking. When enabled, Flink will insert so-called latency markers periodically at all sources. For each sub-task, a latency distribution from each source to this operator will be reported. The granularity of these histograms can be further controlled by setting metrics.latency.granularity as desired.
Due to the potentially high number of histograms (in particular for metrics.latency.granularity: subtask), enabling latency tracking can significantly impact the performance of the cluster. It is recommended to only enable it to locate sources of latency during debugging.
Metrics
| Metric | Scope | Description |
|---|---|---|
latency |
operator | The latency from the source operator to this operator. |
restartingTime |
job | The time it took to restart the job, or how long the current restart has been in progress. |
Example Dashboard Panel
Latency distribution between a source and a single sink subtask.
JVM Metrics #
So far we have only looked at Flink-specific metrics. As long as latency & throughput of your application are in line with your expectations and it is checkpointing consistently, this is probably everything you need. On the other hand, if you job’s performance is starting to degrade among the firstmetrics you want to look at are memory consumption and CPU load of your Task- & JobManager JVMs.
Memory #
Flink reports the usage of Heap, NonHeap, Direct & Mapped memory for JobManagers and TaskManagers.
-
Heap memory - as with most JVM applications - is the most volatile and important metric to watch. This is especially true when using Flink’s filesystem statebackend as it keeps all state objects on the JVM Heap. If the size of long-living objects on the Heap increases significantly, this can usually be attributed to the size of your application state (check the checkpointing metrics for an estimated size of the on-heap state). The possible reasons for growing state are very application-specific. Typically, an increasing number of keys, a large event-time skew between different input streams or simply missing state cleanup may cause growing state.
-
NonHeap memory is dominated by the metaspace, the size of which is unlimited by default and holds class metadata as well as static content. There is a JIRA Ticket to limit the size to 250 megabyte by default.
-
The biggest driver of Direct memory is by far the number of Flink’s network buffers, which can be configured.
-
Mapped memory is usually close to zero as Flink does not use memory-mapped files.
In a containerized environment you should additionally monitor the overall memory consumption of the Job- and TaskManager containers to ensure they don’t exceed their resource limits. This is particularly important, when using the RocksDB statebackend, since RocksDB allocates a considerable amount of memory off heap. To understand how much memory RocksDB might use, you can checkout this blog post by Stefan Richter.
Key Metrics
| Metric | Scope | Description |
|---|---|---|
Status.JVM.Memory.NonHeap.Committed |
job-/taskmanager | The amount of non-heap memory guaranteed to be available to the JVM (in bytes). |
Status.JVM.Memory.Heap.Used |
job-/taskmanager | The amount of heap memory currently used (in bytes). |
Status.JVM.Memory.Heap.Committed |
job-/taskmanager | The amount of heap memory guaranteed to be available to the JVM (in bytes). |
Status.JVM.Memory.Direct.MemoryUsed |
job-/taskmanager | The amount of memory used by the JVM for the direct buffer pool (in bytes). |
Status.JVM.Memory.Mapped.MemoryUsed |
job-/taskmanager | The amount of memory used by the JVM for the mapped buffer pool (in bytes). |
Status.JVM.GarbageCollector.G1 Young Generation.Time |
job-/taskmanager | The total time spent performing G1 Young Generation garbage collection. |
Status.JVM.GarbageCollector.G1 Old Generation.Time |
job-/taskmanager | The total time spent performing G1 Old Generation garbage collection. |
Example Dashboard Panel
TaskManager memory consumption and garbage collection times.
JobManager memory consumption and garbage collection times.
Possible Alerts
container memory limit
<container memory + safety margin
CPU #
Besides memory, you should also monitor the CPU load of the TaskManagers. If your TaskManagers are constantly under very high load, you might be able to improve the overall performance by decreasing the number of task slots per TaskManager (in case of a Standalone setup), by providing more resources to the TaskManager (in case of a containerized setup), or by providing more TaskManagers. In general, a system already running under very high load during normal operations, will need much more time to catch-up after recovering from a downtime. During this time you will see a much higher latency (event-time skew) than usual.
A sudden increase in the CPU load might also be attributed to high garbage collection pressure, which should be visible in the JVM memory metrics as well.
If one or a few TaskManagers are constantly under very high load, this can slow down the whole topology due to long checkpoint alignment times and increasing event-time skew. A common reason is skew in the partition key of the data, which can be mitigated by pre-aggregating before the shuffle or keying on a more evenly distributed key.
Key Metrics
| Metric | Scope | Description |
|---|---|---|
Status.JVM.CPU.Load |
job-/taskmanager | The recent CPU usage of the JVM. |
Example Dashboard Panel
TaskManager & JobManager CPU load.
System Resources #
In addition to the JVM metrics above, it is also possible to use Flink’s metrics system to gather insights about system resources, i.e. memory, CPU & network-related metrics for the whole machine as opposed to the Flink processes alone. System resource monitoring is disabled by default and requires additional dependencies on the classpath. Please check out the Flink system resource metrics documentation for additional guidance and details. System resource monitoring in Flink can be very helpful in setups without existing host monitoring capabilities.
Conclusion #
This post tries to shed some light on Flink’s metrics and monitoring system. You can utilise it as a starting point when you first think about how to successfully monitor your Flink application. I highly recommend to start monitoring your Flink application early on in the development phase. This way you will be able to improve your dashboards and alerts over time and, more importantly, observe the performance impact of the changes to your application throughout the development phase. By doing so, you can ask the right questions about the runtime behaviour of your application, and learn much more about Flink’s internals early on.
Last but not least, this post only scratches the surface of the overall metrics and monitoring capabilities of Apache Flink. I highly recommend going over Flink’s metrics documentation for a full reference of Flink’s metrics system.


--- layout: blogpost meta_title: "Weaving in ends: a life philosophy | Blind Dog Yarns" meta_description: "Our Maker Life is a conference put on for makers by makers. I attended this year's event and loved it." display_title: "Weaving in ends: a life philosophy" description: "As I was crocheting and moving the ends from my color work out of the way, I had a thought about how your approach to weaving in ends says a lot of your life philosophy." open_graph_img: /assets/images/blog/StockingEnds.jpg twitter_img: /assets/images/blog/StockingEnds.jpg ---
I was on the bus earlier this week and I was working on a crochet Christmas stocking. I always do some color work on my stockings and this one is a vintage red truck with some evergreens in the background for a family who has ordered stockings from me in the past.
As I was crocheting and moving the ends from my color work out of the way, I had a thought about how your approach to weaving in ends says a lot of your life philosophy. Weaving in ends is often a laborious and dreaded process for crocheters (and I imagine knitters). When I finish crocheting a project, I just want to use it or give it, not spend an hour tediously weaving in the little ends of yarn. But it must be done.
If you are a person who weaves in ends as you go (instead of waiting until the project is finished), I would say you are committed, confident, and proactive in your approach to life.
Weaving in ends as you go means that if you find a mistake later, it is much harder to frog (undo) and fix. If you’ve woven in your ends and then find a mistake 3 rows up, you have to try to find that end you cut and finagle it back out of the stitches in order to frog back enough to fix your mistake. Because of that I would say you are committed and confident. There’s no going back for you. You are at peace with your decisions.
  For this reason, I consider the as-you-goer to be proactive. You know that awful feeling of 30+ ends staring you in the face and instead, you take steps to avoid having to do it all at once. You’re proactive and I would venture to guess you’re the same person who does just a couple chores a day so that your Sunday isn’t spent cleaning the house.
On the other hand, if you are a person who waits until the end to weave in your ends, I would consider you to be sensible, prepared, and dynamic.
By waiting until the end to weave in your ends, you leave your options open if you change your mind. You can always go back and make adjustments if something doesn’t look quite right because you’ve left the ability to frog your work quickly and easily. No one is perfect, everyone makes mistakes. You’re ready for when that inevitably happens to you.
Because you don’t have to pause to weave in your ends, you get to crochet quickly and relish in your progress. It's so exciting to see your project take shape. Even though when you finish you have to weave in all those ends, it’s worth it to get to your completed project faster and see the results of your handiwork.
For me personally (and I would guess most people), I fall somewhere in the middle. For large projects, like my temperature blanket I worked on for all of 2017, I wove in my ends as I went. The thought of weaving in all 756+ ends at once was gut wrenching.
But for my smaller projects, like my Christmas stockings, I definitely wait until the end to weave in my ends because I want to give myself the option to go back and fix any mistakes I find.
What about you? Are you an as-you-goer or an at-the-ender?


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Our users include many major service providers running CloudStack to offer public cloud services, product vendors who incorporate or integrate with Cloudstack in their own products, organisations who have used Cloudstack to build their own private clouds, and systems integrators that offer CloudStack related services.
If you are using CloudStack in your organisation and your company is not listed here, please send a pull request to the GitHub page.
If you noticed something wrong with your entry here (or if you’d like us to remove it), please send a pull request to the GitHub page or write your concerns to the mail-list users@cloudstack.apache.org.


| Action | Device | IP | Date |
|---|---|---|---|
| Edit product(#00102) | Desktop - Google Chrome | <IP_ADDRESS> | An hour ago |
| Delete products(#31003) | Desktop - Mozilla Firefox | 185.321.1.421 | Three hours ago |
| Edit product(#00402) | Desktop - Google Chrome | <IP_ADDRESS> | Five hours ago |
| Add product(#00402) | Desktop - Google Chrome | <IP_ADDRESS> | Five hours ago |


Your Client Order Id
Shows 0
Shows if this trade has moved the book price up, down, or no change. Values:
The ID of this account’s side of the trade. Every trade has two sides.
The fee for this trade in units and fractions of units (a $10 USD fee would be 10.00, a .5-BitCoin fee would be 0.5).
The ID of the product that denominates the fee. Product types will vary on each trading venue. See GetProduct.
The ID of the instrument being traded. See GetInstrument to find information about this instrument by its ID.
Returns true if the trade was a reported trade; false otherwise.
The ID of the Order Management System to which the user belongs. A user will belong only to one OMS.
The ID of the order causing the trade.
The user ID of the user who entered the order that caused the trade for this account. (Multiple users can have access to an account.)
This value increments if the trade has changed. Default is 1. For example, if the trade busts (fails to conclude), the trade will need to be modified and a revision number then will apply.
The unit price at which the instrument traded.
The unit quantity of the trade.
The number of units remaining to be traded by the order after this execution. This number is not revealed to the other party in the trade. This value is also known as “leave size” or “leave quantity.”
Buy or Sell
Not currently used.
The ID of the overall trade.
The time at which the trade took place, in POSIX format and UTC time zone
The date and time stamp of the trade in Microsoft tick format and UTC time zone
The total value of the deal. The system calculates this as: unit price X quantity executed
Generated using TypeDoc
The Account ID that made the trade.
{number}
AccountTradesResult


Installation¶
Note
It is recommended that you create a virtual environment to facilitate easy management.
Tip
Virtual Environment Example
First, create the virtual environment.
python3 -m venv bas_env
Second, active the virtual environment.
source bas_env/bin/activate
Option 1:
pip install buildaspider
Option 2:
git clone git@github.com:joedougherty/buildaspider.git
cd buildaspider/
python3 setup.py install
Getting Started¶
Step 1: Set Up the Config File¶
A config file is required. You can copy and paste the example below to get started.
[buildaspider]
; +++ REQUIRED ATTRIBUTES +++ ;
; log_dir
; seed_urls
; include_patterns
; exclude_patterns
; max_num_retries
; Absolute path to directory containing per-run logs
log_dir = /path/to/logs
; Literal URLs to visit -- there must be at least one!
seed_urls =
http://httpbin.org/
; List of regex patterns to include
include_patterns =
httpbin.org
; List of regex patterns to exclude
exclude_patterns =
^#$
^javascript
max_num_retries = 5
; +++ OPTIONAL ATTRIBUTES +++ ;
; login = true
; In order to programatically login, uncomment the line above and ensure login = true
;
; You will also need to ensure that:
; + the username line is uncommented and set correctly
; + the password line is uncommented and set correctly
; + the login_url line is uncommented and set correctly
; username = <USERNAME>
; password = <PASSWORD>
; login_url = http://example.com/login
Note down the full, absolute path to the config file. This will be the first, required argument to the Spider
instance. See the code sample in the Basic Usage section for an example.
Step 2: Understand What to Expect from Logging¶
Attention
Ensure that the log_dir line is uncommented and that the specified path exists on the file system.
Each run generates four distinct logs:
Log |
Information Provided |
Default Log name pattern |
|---|---|---|
Status log |
Status messages |
|
Broken links log |
Broken links, HTTP Codes |
|
Checked links log |
All checked links |
|
Exception links log |
Broken links, Exception details |
|
Step 2A: Investigate the .setup_logging()
method [Optional]¶
The log locations are defined in the .setup_logging()
method of the Spider
base class.
def setup_logging(self):
now = datetime.now().strftime(self.time_format)
logging.basicConfig(
filename=os.path.join(self.log_dir, f"spider_{now}.log"),
level=logging.INFO,
format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
)
self.status_logger = logging.getLogger(__name__)
self.broken_links_logpath = os.path.join(
self.log_dir, f"broken_links_{now}.log"
)
self.checked_links_logpath = os.path.join(
self.log_dir, f"checked_links_{now}.log"
)
self.exception_links_logpath = os.path.join(
self.log_dir, f"exception_links_{now}.log"
)
Step 3: Verify Setup¶
The Spider
object provides a .verify()
method that you can use to confirm details.
from buildaspider import Spider
myspider = Spider('/path/to/config.ini')
myspider.verify()
This will produce console output similar to the following:
+-----------------------+-------------------------+
| ATTRIBUTE | VALUE |
+-----------------------+-------------------------+
| Config File | /home/joe/demo/conf.ini |
| Log Directory | /home/joe/demo/logs |
| Seed URL | http://httpbin.org/ |
| Include Patterns | ['httpbin.org'] |
| Exclude Patterns | ['^#$', '^javascript'] |
| Max Number of Retries | 5 |
| Login | False |
| Max Workers | 8 |
| Time Format | %Y-%m-%d_%H:%M |
+-----------------------+-------------------------+
Note
Only the first of the Seed URLs will be listed in the console output.
Now that you have confirmed these values make sense, you are ready to kick off the crawling process!
Basic Usage¶
Now that the config file is set up and its settings have been confirmed, it is time to call .weave()
.
from buildaspider import Spider
myspider = Spider(
'/path/to/cfg.ini', # Full, absolute path to config file
)
myspider.weave()
This will start the web crawling process, beginning with the URLs specified in seed_urls
in the config file.
Beyond Basic Usage¶
Adding the Ability to Login¶
You can extend the functionality of buildaspider by inheriting from the Spider
class and overriding methods.
This is how you implement the ability for your spider to programmatically login.
Here’s the documentation from the base Spider
class:
def login(self):
# If your session doesn't require logging in, you can leave this method unimplemented.
#
# Otherwise, this method needs to return an instance of `requests.Session`.
#
# A new session can be obtained by calling `mint_new_session()`.
#
raise NotImplementedError("You'll need to implement the login method.")
Here’s an example of a fleshed-out login method to POST
credentials (as obtained from the config file) to the login_url
.
from buildaspider import Spider, mint_new_session, FailedLoginError
class MySpider(Spider):
def login(self):
new_session = mint_new_session()
login_payload = {
'username': self.cfg.username,
'password': self.cfg.password,
}
response = new_session.post(self.cfg.login_url, data=login_payload)
if response.status_code != 200:
raise FailedLoginError("Login Failed :(")
return response
myspider = MySpider('/path/to/cfg.ini')
myspider.weave()
Note
For more details on logging in with requests see: https://pybit.es/requests-session.html.
Providing Custom Functionality by Attaching to Event Hooks¶
There are a few events that occur during the crawling process that you may want to attach some additional functionality to.
There are pre-visit and post-visit methods you can override/extend.
Event |
Method |
|---|---|
link visit is about to begin |
|
link visit is about to end |
|
a link has been marked as checked |
|
a link has been marked as broken |
|
a link has been marked as causing an exception |
|
crawling is complete |
|
.pre_visit_hook()
provides the ability to run custom code when .visit()
is called.
Code specified in .pre_visit_hook()
will execute prior to library-provided functionality in .visit()
.
.post_visit_hook()
provides the ability to run code right before .visit()
returns.
The overridden methods .pre_visit_hook()
and .post_visit_hook()
ought to pass in link
in order to keep the current link in scope and available as a variable with that name.
Here is an example that demonstrates storing visited links in a custom container:
custom_visited_links = list()
def pre_visit_hook(self, link):
# The `link` being referenced here
# is the link about to be visited
custom_visited_links.append(link)
Warning
This provides direct access to the current link
object in scope.
If you intend to mutate the link
in scope, a safer strategy is to make a copy deepcopy
. This will help prevent you from inadvertently mutating the original link
object.
from copy import deepcopy
custom_visited_links = list()
def pre_visit_hook(self, link):
current_link_copy = deepcopy(link)
custom_visited_links.append(current_link_copy)
Extending/Overriding Pre-Defined Events¶
By default, broken links are logged to the location specified by .broken_links_logpath
.
We can see this in the Spider
class:
def log_broken_link(self, link):
append_line_to_log(self.broken_links_logpath, f'{link} :: {link.http_code}')
What if you want to extend (not merely override) the functionality of .log_broken_link()
?
def log_broken_link(self, link):
super().log_broken_link(link)
# You've now retained the original functionality
# by running the method as defined on the parent instance
# Perhaps now you want to:
# + cache this value?
# + run some action(s) as a result of this event firing?
# + ???
Running the Test Suite¶
Note
You will need to ensure that the log_dir
config file field is set correctly before you run the test suite.
cd tests/
pytest


We have updated our privacy policy to make it easier for you to understand how we collect, use, disclose, store, and transfer your information. It also reflects recent developments in applicable privacy laws. The changes are effective as of Jan 01, 2021 so please take the time to familiarize yourself with our privacy practices.
The changes will take effect automatically and by continuing to use our services you agree to the updated privacy policy.


Timestamp Microservice
Pass a unix or natural date in the URL to return a JSON object containing both
Example: https://backend-ajohn1215.c9users.io/December%2015%20,1996


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[include "/chrome/nativeclient/_local_variables.ezt"] [# this file should be at root of your document hierarchy ] [define section]docs[end] [# this should be "docs" if the file lives in the "Docs" section (top nav)] [# Otherwise, it's "home," "articles," "download," or "terms" ] [define page_title][end] [# this is the title for only this page ] [define css_includes] [end] [include "/_boilerplate_header.ezt"] [verbatim]


# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/kernel/debugger.rb, line 11 11: def breakpoint 12: message = "\n***** The 'breakpoint' command has been renamed 'debugger' -- please change *****\n" 13: defined?(Rails) ? Rails.logger.info(message) : $stderr.puts(message) 14: debugger 15: end
class_eval on an object acts like singleton_class.class_eval.
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/kernel/singleton_class.rb, line 10 10: def class_eval(*args, &block) 11: singleton_class.class_eval(*args, &block) 12: end
Starts a debugging session if ruby-debug has been loaded (call rails server —debugger to do load it).
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/kernel/debugger.rb, line 4 4: def debugger 5: message = "\n***** Debugger requested, but was not available (ensure ruby-debug is listed in Gemfile/installed as gem): Start server with --debugger to enable *****\n" 6: defined?(Rails) ? Rails.logger.info(message) : $stderr.puts(message) 7: end
Sets $VERBOSE to true for the duration of the block and back to its original value afterwards.
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/kernel/reporting.rb, line 15 15: def enable_warnings 16: with_warnings(true) { yield } 17: end
Require a library with fallback to RubyGems. Warnings during library loading are silenced to increase signal/noise for application warnings.
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/kernel/requires.rb, line 6 6: def require_library_or_gem(library_name) 7: silence_warnings do 8: begin 9: require library_name 10: rescue LoadError => cannot_require 11: # 1. Requiring the module is unsuccessful, maybe it's a gem and nobody required rubygems yet. Try. 12: begin 13: require 'rubygems' 14: rescue LoadError => rubygems_not_installed 15: raise cannot_require 16: end 17: # 2. Rubygems is installed and loaded. Try to load the library again 18: begin 19: require library_name 20: rescue LoadError => gem_not_installed 21: raise cannot_require 22: end 23: end 24: end 25: end
Silences any stream for the duration of the block.
silence_stream(STDOUT) do puts 'This will never be seen' end puts 'But this will'
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/kernel/reporting.rb, line 39 39: def silence_stream(stream) 40: old_stream = stream.dup 41: stream.reopen(Config::CONFIG['host_os'] =~ /mswin|mingw/ ? 'NUL:' : '/dev/null') 42: stream.sync = true 43: yield 44: ensure 45: stream.reopen(old_stream) 46: end
Sets $VERBOSE to nil for the duration of the block and back to its original value afterwards.
silence_warnings do value = noisy_call # no warning voiced end noisy_call # warning voiced
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/kernel/reporting.rb, line 10 10: def silence_warnings 11: with_warnings(nil) { yield } 12: end
Returns the object‘s singleton class.
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/kernel/singleton_class.rb, line 3 3: def singleton_class 4: class << self 5: self 6: end 7: end
Blocks and ignores any exception passed as argument if raised within the block.
suppress(ZeroDivisionError) do 1/0 puts "This code is NOT reached" end puts "This code gets executed and nothing related to ZeroDivisionError was seen"
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/kernel/reporting.rb, line 56 56: def suppress(*exception_classes) 57: begin yield 58: rescue Exception => e 59: raise unless exception_classes.any? { |cls| e.kind_of?(cls) } 60: end 61: end
Sets $VERBOSE for the duration of the block and back to its original value afterwards.
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/kernel/reporting.rb, line 20 20: def with_warnings(flag) 21: old_verbose, $VERBOSE = $VERBOSE, flag 22: yield 23: ensure 24: $VERBOSE = old_verbose 25: end


ociping.rwl − Find OCIPing rates over a database connection
rwloadsim -u -l u/p@c [--no-timestamp] [--csvoutput=file] [--interval=N] [--period=N] ociping.rwl
The ociping.rwl utility executes something similar to ping repeatedly showing the time it takes to execute a single OCIPing over a database connection. If you also want to show the time taking to establish connections, use connping(2rwl).
-u
Compulsory option to find the ociping.rwl script in the public directory.
-l u/p
-l u/p@c
Compulsory option to provide the username, password, and potentially connect string for a database connection. If you omit /p, rwloadsim will prompt for the password.
--interval=N
The interval (in seconds) between each ping; default 1s.
--period=N
The period in seconds to run ping; default 60s.
--no-timestamp
Do not include timestamp (in seconds) in output.
--csvoutput=file
Output timestamp (unless --no-timestamp) and the OCIPing time separated by space to the named file.
When executing, it will show timestamp (unless --no-timestamp is provided) and the time to perform an OCIPing until the run period is over, and at the end show averages and standard deviation. You can kill execution prematurely by typing ctrl-c.
rwloadsim --csvoutput=ping.csv --period=10 -ul username/{password} ociping.rwl
RWP*Load
Simulator Release <IP_ADDRESS> Development on Wed, 05 May 2021
08:45:05 UTC
RWL-206: warning: OCI compile environment (19.10) is
different from runtime (19.9)
Connected default database to:
Oracle Database 19c Enterprise Edition Release <IP_ADDRESS>.0 -
Production
0.000 0.050
1.000 0.052
2.000 0.050
3.000 0.050
4.000 0.081
5.000 0.049
6.000 0.049
7.000 0.049
8.000 0.051
9.000 0.051
ociping mean=0.053 stddev=0.009
You could subsequently plot the results using gnuplot with an input like this:
set yrange[0:*]
plot "ping.csv" using 1:2 with lines title
"OCIPing"
Copyright
© 2021 Oracle Corporation
Licensed under the Universal Permissive License v 1.0 as
shown at https://oss.oracle.com/licenses/upl
rwloadsim(1rwl), connping(2rwl)


Build magic, explaining root causes, and making our apps more accessibility to the visually impaired. Just another day in the office...
1/9/2009, 2:05:46 PM
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Build magic, explaining root causes, and making our apps more accessibility to the visually impaired. Just another day in the office...
1/9/2009, 2:05:46 PM
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Pratt & Whitney to open new ceramic matrix composites facility 22 Nov 2019, 12:01 by Michael Tyrrell Share This Article Tweet ShareShareShare Subscribe to our FREE Newsletter Author


This is a default UDPv4 implementation.
More...
#include <UDPv4Transport.h>
|
| RTPS_DllAPI | UDPv4Transport (const UDPv4TransportDescriptor &) |
| |
| virtual | ~UDPv4Transport () |
| |
| bool | init () override |
| |
| virtual bool | IsInputChannelOpen (const Locator_t &) const override |
| | Checks whether there are open and bound sockets for the given port. More...
|
| |
| virtual bool | IsOutputChannelOpen (const Locator_t &) const override |
| | Checks whether there are open and bound sockets for the given port. More...
|
| |
| virtual bool | IsLocatorSupported (const Locator_t &) const override |
| | Checks for UDPv4 kind. More...
|
| |
| virtual bool | DoLocatorsMatch (const Locator_t &, const Locator_t &) const override |
| | Reports whether Locators correspond to the same port. More...
|
| |
| virtual Locator_t | RemoteToMainLocal (const Locator_t &) const override |
| | Converts a given remote locator (that is, a locator referring to a remote destination) to the main local locator whose channel can write to that destination. More...
|
| |
| virtual bool | OpenInputChannel (const Locator_t &) override |
| | Starts listening on the specified port, and if the specified address is in the multicast range, it joins the specified multicast group,. More...
|
| |
| virtual bool | OpenOutputChannel (Locator_t &) override |
| | Opens a socket on the given address and port (as long as they are white listed). More...
|
| |
| virtual bool | CloseInputChannel (const Locator_t &) override |
| | Removes the listening socket for the specified port. More...
|
| |
| virtual bool | CloseOutputChannel (const Locator_t &) override |
| | Removes all outbound sockets on the given port. More...
|
| |
| virtual bool | Send (const octet *sendBuffer, uint32_t sendBufferSize, const Locator_t &localLocator, const Locator_t &remoteLocator) override |
| | Blocking Send through the specified channel. More...
|
| |
| virtual bool | Receive (octet *receiveBuffer, uint32_t receiveBufferCapacity, uint32_t &receiveBufferSize, const Locator_t &localLocator, Locator_t &remoteLocator) override |
| | Blocking Receive from the specified channel. More...
|
| |
| virtual LocatorList_t | NormalizeLocator (const Locator_t &locator) override |
| |
| virtual LocatorList_t | ShrinkLocatorLists (const std::vector< LocatorList_t > &locatorLists) override |
| |
| virtual bool | is_local_locator (const Locator_t &locator) const override |
| |
| UDPv4TransportDescriptor | get_configuration () |
| |
| virtual | ~TransportInterface () |
| | Aside from the API defined here, an user-defined Transport must define a descriptor data type and a constructor that expects a constant reference to such descriptor. More...
|
| |
This is a default UDPv4 implementation.
- Opening an output channel by passing a locator will open a socket per interface on the given port. This collection of sockets constitute the "outbound channel". In other words, a channel corresponds to a port + a direction.
- It is possible to provide a white list at construction, which limits the interfaces the transport will ever be able to interact with. If left empty, all interfaces are allowed.
- Opening an input channel by passing a locator will open a socket listening on the given port on every whitelisted interface, and join the multicast channel specified by the locator address. Hence, any locator that does not correspond to the multicast range will simply open the port without a subsequent join. Joining multicast groups late is supported by attempting to open the channel again with the same port + a multicast address (the OpenInputChannel function will fail, however, because no new channel has been opened in a strict sense).
◆ UDPv4Transport() [1/2]
◆ ~UDPv4Transport()
◆ UDPv4Transport() [2/2]
Constructor with no descriptor is necessary for implementations derived from this class.
◆ CloseInputChannel()
| virtual bool CloseInputChannel |
( |
const Locator_t & |
| ) |
|
|
overridevirtual |
◆ CloseOutputChannel()
| virtual bool CloseOutputChannel |
( |
const Locator_t & |
| ) |
|
|
overridevirtual |
◆ DoLocatorsMatch()
◆ get_configuration()
◆ init()
◆ is_local_locator()
| virtual bool is_local_locator |
( |
const Locator_t & |
locator | ) |
const |
|
overridevirtual |
◆ IsInputChannelOpen()
| virtual bool IsInputChannelOpen |
( |
const Locator_t & |
| ) |
const |
|
overridevirtual |
Checks whether there are open and bound sockets for the given port.
Implements TransportInterface.
◆ IsInterfaceAllowed()
| bool IsInterfaceAllowed |
( |
const asio::ip::address_v4 & |
ip | ) |
|
|
protected |
◆ IsLocatorSupported()
| virtual bool IsLocatorSupported |
( |
const Locator_t & |
| ) |
const |
|
overridevirtual |
◆ IsOutputChannelOpen()
| virtual bool IsOutputChannelOpen |
( |
const Locator_t & |
| ) |
const |
|
overridevirtual |
Checks whether there are open and bound sockets for the given port.
Implements TransportInterface.
◆ NormalizeLocator()
◆ OpenAndBindInputSocket()
| std::shared_ptr<asio::ip::udp::socket> OpenAndBindInputSocket |
( |
uint32_t |
port, |
|
|
bool |
is_multicast |
|
) |
| |
|
protected |
◆ OpenAndBindInputSockets()
| bool OpenAndBindInputSockets |
( |
uint32_t |
port, |
|
|
bool |
is_multicast |
|
) |
| |
|
protected |
◆ OpenAndBindOutputSockets()
| bool OpenAndBindOutputSockets |
( |
Locator_t & |
locator | ) |
|
|
protected |
◆ OpenAndBindUnicastOutputSocket()
| std::shared_ptr<asio::ip::udp::socket> OpenAndBindUnicastOutputSocket |
( |
const asio::ip::address_v4 & |
, |
|
|
uint32_t & |
port |
|
) |
| |
|
protected |
◆ OpenInputChannel()
| virtual bool OpenInputChannel |
( |
const Locator_t & |
| ) |
|
|
overridevirtual |
Starts listening on the specified port, and if the specified address is in the multicast range, it joins the specified multicast group,.
Implements TransportInterface.
◆ OpenOutputChannel()
| virtual bool OpenOutputChannel |
( |
Locator_t & |
| ) |
|
|
overridevirtual |
Opens a socket on the given address and port (as long as they are white listed).
Implements TransportInterface.
◆ Receive()
| virtual bool Receive |
( |
octet * |
receiveBuffer, |
|
|
uint32_t |
receiveBufferCapacity, |
|
|
uint32_t & |
receiveBufferSize, |
|
|
const Locator_t & |
localLocator, |
|
|
Locator_t & |
remoteLocator |
|
) |
| |
|
overridevirtual |
Blocking Receive from the specified channel.
- Parameters
-
| receiveBuffer | vector with enough capacity (not size) to accomodate a full receive buffer. That capacity must not be less than the receiveBufferSize supplied to this class during construction. |
| localLocator | Locator mapping to the local channel we're listening to. |
| [out] | remoteLocator | Locator describing the remote restination we received a packet from. |
Implements TransportInterface.
◆ RemoteToMainLocal()
Converts a given remote locator (that is, a locator referring to a remote destination) to the main local locator whose channel can write to that destination.
In this case it will return a <IP_ADDRESS> address on that port.
Implements TransportInterface.
◆ Send()
| virtual bool Send |
( |
const octet * |
sendBuffer, |
|
|
uint32_t |
sendBufferSize, |
|
|
const Locator_t & |
localLocator, |
|
|
const Locator_t & |
remoteLocator |
|
) |
| |
|
overridevirtual |
Blocking Send through the specified channel.
In both modes, using a localLocator of <IP_ADDRESS> will send through all whitelisted interfaces provided the channel is open.
- Parameters
-
| sendBuffer | Slice into the raw data to send. |
| sendBufferSize | Size of the raw data. It will be used as a bounds check for the previous argument. It must not exceed the sendBufferSize fed to this class during construction. |
| localLocator | Locator mapping to the channel we're sending from. |
| remoteLocator | Locator describing the remote destination we're sending to. |
Implements TransportInterface.
Reimplemented in test_UDPv4Transport.
◆ SendThroughSocket()
| bool SendThroughSocket |
( |
const octet * |
sendBuffer, |
|
|
uint32_t |
sendBufferSize, |
|
|
const Locator_t & |
remoteLocator, |
|
|
std::shared_ptr< asio::ip::udp::socket > |
socket |
|
) |
| |
|
protected |
◆ ShrinkLocatorLists()
◆ currentInterfaces
| std::vector<IPFinder::info_IP> currentInterfaces |
|
protected |
◆ ioServiceThread
| std::unique_ptr<std::thread> ioServiceThread |
|
protected |
◆ mConfiguration_
◆ mInputMapMutex
| std::recursive_mutex mInputMapMutex |
|
mutableprotected |
◆ mInputSockets
| std::map<uint32_t, std::shared_ptr<asio::ip::udp::socket> > mInputSockets |
|
protected |
For both modes, an input channel corresponds to a port.
◆ mInterfaceWhiteList
| std::vector<asio::ip::address_v4> mInterfaceWhiteList |
|
protected |
◆ mOutputMapMutex
| std::recursive_mutex mOutputMapMutex |
|
mutableprotected |
◆ mOutputSockets
| std::map<uint32_t, std::vector<SocketInfo> > mOutputSockets |
|
protected |
The notion of output channel corresponds to a port.
◆ mReceiveBufferSize
| uint32_t mReceiveBufferSize |
|
protected |
◆ mSendBufferSize
◆ mService
| asio::io_service mService |
|
protected |
The documentation for this class was generated from the following file:
- /home/ricardo/workspace/curro/eProsima/desarrollo/proyectos/fastrtps/include/fastrtps/transport/UDPv4Transport.h


Package engine
Class Animation
java.lang.Object
engine.Animation
public class Animation
extends java.lang.Object
this class is used to manage animation
- Author:
- gautier
-
Constructor Summary
Constructors Constructor Description Animation(int maxFrame, boolean hasAnimation, GraphicsManager graphicsManager, int id, int faction)
Constructor of this class defaultAnimation(int maxFrame, boolean hasAnimation, java.awt.image.BufferedImage[][] graphics)
using this constructor if taking bufferedImage directly is more speed -
Method Summary
Modifier and Type Method Description float
getCurrentFrame()
get the currentFrameint
getDirection()
get the direction of the frame, left or rightvoid
getEntityNoAnimationTexture(GraphicsManager graphicsManager, int id, int faction)
this method init frame of entity, who haven't a animationvoid
getEntityWithAnimationTexture(GraphicsManager graphicsManager, int id, int faction)
this method init frame of entity, who have a animationjava.awt.image.BufferedImage
getFrame()
this method permit to print a frameint
getFrameState()
get the current frameState, harvest, attack....boolean
isHasAnimation()
true if entity has animationvoid
setCurrentFrame(float frame)
setting currentFramevoid
setDirection(int direction)
set the direction of the framevoid
setFrameState(int state)
set the current FrameStatevoid
update()
core function who charge to modify animation in term of situationMethods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
-
Constructor Details
-
Animation
public Animation(int maxFrame, boolean hasAnimation, GraphicsManager graphicsManager, int id, int faction)Constructor of this class default- Parameters:
maxFrame
- number of framehasAnimation
- if he has an animationgraphicsManager
- to get animation bufferedImageid
- id to entity who need animationfaction
- faction of the entity
-
Animation
public Animation(int maxFrame, boolean hasAnimation, java.awt.image.BufferedImage[][] graphics)using this constructor if taking bufferedImage directly is more speed- Parameters:
maxFrame
- number of framehasAnimation
- if he has an animationgraphics
- if we give him bufferredImage directly
-
-
Method Details
-
update
public void update()core function who charge to modify animation in term of situation -
getFrame
public java.awt.image.BufferedImage getFrame()this method permit to print a frame- Returns:
- BufferedImage the current frame to draw
-
getEntityWithAnimationTexture
this method init frame of entity, who have a animation- Parameters:
graphicsManager
- to get animation bufferedImageid
- id to entity who need animationfaction
- faction of the entity
-
getEntityNoAnimationTexture
this method init frame of entity, who haven't a animation- Parameters:
graphicsManager
- to get animation bufferedImageid
- id to entity who need animationfaction
- faction of the entity
-
isHasAnimation
public boolean isHasAnimation()true if entity has animation- Returns:
- boolean
-
setCurrentFrame
public void setCurrentFrame(float frame)setting currentFrame- Parameters:
frame
- frame to set
-
getCurrentFrame
public float getCurrentFrame()get the currentFrame- Returns:
- float the currentFrame
-
getDirection
public int getDirection()get the direction of the frame, left or right- Returns:
- int direction of the frame
-
setDirection
public void setDirection(int direction)set the direction of the frame- Parameters:
direction
- setting direction
-
getFrameState
public int getFrameState()get the current frameState, harvest, attack....- Returns:
- int frameState
-
setFrameState
public void setFrameState(int state)set the current FrameState- Parameters:
state
-
-


Are you sure you want to store this entity, "{{entityName}}", to Umbraco Cloud?
This will add it to the Git repository for this environment, after which you
will be able to transfer this entity to another environment via the Umbraco
Cloud UI.
If this entity already exists in Umbraco Cloud, the latest changes will be
stored to Umbraco Cloud.


Dear Sir, Let me first apologise to you for any mbarrassment this mail might cause you. I am MAHOYI BELLO, a cousin to the Vice Presidentof the Federal Republic of Nigeria (Alhaji Atiku) and Executive Director of SADIQ PETROLUEM LTD.I have decided to contact you for this business proposal based on the mutual understanding I know that can exist between us, having known that people of your Country are trustworthy. Since May 1999 when the new Government came to power,large sums of money have been recovered from our past military leaders who siphoned money from Nigeria and deposited it in offshore accounts in Europe,America,Asia and some parts of Africa, for their own selfish benefits. This happened during the military regime,Now we are under a democratically elected government. This fund was among the money recovered and seized by the Federal Government of Nigeria. Hence, my elder cousin (Alhaji Atiku Abubakar) the Vice-President of Nigeria is in charge of all off-shore accounts seized and retrieved from our past military leaders.Therefore, we urged you to assist us provide a very vital offshore account, where the sum of US$25,000,000.00 (Twenty Five Million) US Dollars will be transferred for safe keeping. Presently, this money is in a foreign Country I cannot mention now.Please note that other information will be detailed to you on the receipt of your reply. My elder cousin and I have agreed to give you (the account owner)for this transaction 30% of the total amount remitted while 60%is for me and Cousin Atiku, for the purchase of foreign investments, with your assistance after the money have been disbursed, while 10% is for expenses both of us will incur. Note, I have been mandated by my elder cousin to handle this deal with you, due to his position in the Nigerian Government as the second citizen. Therefore, if my proposal satisfies you, kindly contact me via my e-mail address and enclose your phone and fax numbers for urgent confidential discussion.Your letter of acceptance indicating your personal telephone and fax numbers to enable us move ahead. Besides, this transaction is risk-free and hoped to last 7 (seven) banking days upon my elder cousin Alhaji Atiku Abubakar's authorisation.I thank you for your expected co-operation. God Bless you.Best Regards. MAHOYI BELLO. _________________________________________________________ Gagne une PS2 ! Envoie un SMS avec le code PS au 61166 (0,35€ Hors coût du SMS)


- Project 1: September 28 (graded with feedback)
- Project 2: November 2 (graded with feedback)
- Project 3: December 7 (graded with feedback)
Projects are handed in using
Canvas. We use Github as repository for codes, benchmark calculations etc. Comments and feedback on projects only via
Canvas.
Basic knowledge in programming and mathematics, with an emphasis on
linear algebra. Knowledge of Python or/and C++ as programming
languages is strongly recommended and experience with Jupiter notebook
is recommended. Required courses are the equivalents to the University
of Oslo mathematics courses MAT1100, MAT1110, MAT1120 and at least one
of the corresponding computing and programming courses INF1000/INF1110
or MAT-INF1100/MAT-INF1100L/BIOS1100/KJM-INF1100. Most universities
offer nowadays a basic programming course (often compulsory) where
Python is the recurring programming language.
This course aims at giving you insights and knowledge about many of the central algorithms used in Data Analysis and Machine Learning. The course is project based and through various numerical projects, normally three, you will be exposed to fundamental research problems in these fields, with the aim to reproduce state of the art scientific results. Both supervised and unsupervised methods will be covered. The emphasis is on a frequentist approach, although we will try to link it with a Bayesian approach as well. You will learn to develop and structure large codes for studying different cases where Machine Learning is applied to, get acquainted with computing facilities and learn to handle large scientific projects. A good scientific and ethical conduct is emphasized throughout the course. More specifically, after this course you will
- Learn about basic data analysis, statistical analysis, Bayesian statistics, Monte Carlo sampling, data optimization and machine learning;
- Be capable of extending the acquired knowledge to other systems and cases;
- Have an understanding of central algorithms used in data analysis and machine learning;
- Understand linear methods for regression and classification, from ordinary least squares, via Lasso and Ridge to Logistic regression;
- Learn about neural networks and deep learning methods for supervised and unsupervised learning. Emphasis on feed forward neural networks, convolutional and recurrent neural networks;
- Learn about about decision trees, random forests, bagging and boosting methods;
- Learn about support vector machines and kernel transformations;
- Reduction of data sets, from PCA to clustering;
- Autoencoders and Reinforcement Learning;
- Work on numerical projects to illustrate the theory. The projects play a central role and you are expected to know modern programming languages like Python or C++ and/or Fortran (Fortran2003 or later).
Statistical analysis and optimization of data.
The following topics will be covered
- Basic concepts, expectation values, variance, covariance, correlation functions and errors;
- Simpler models, binomial distribution, the Poisson distribution, simple and multivariate normal distributions;
- Central elements of Bayesian statistics and modeling;
- Gradient methods for data optimization,
- Monte Carlo methods, Markov chains, Gibbs sampling and Metropolis-Hastings sampling;
- Estimation of errors and resampling techniques such as the cross-validation, blocking, bootstrapping and jackknife methods;
- Principal Component Analysis (PCA) and its mathematical foundation
The following topics will be covered
- Linear Regression and Logistic Regression;
- Neural networks and deep learning, including convolutional and recurrent neural networks
- Decisions trees, Random Forests, Bagging and Boosting
- Support vector machines
- Bayesian linear and logistic regression
- Boltzmann Machines
- Unsupervised learning Dimensionality reduction, from PCA to cluster models
Hands-on demonstrations, exercises and projects aim at deepening your understanding of these topics.


|
iDreamSky Game Engine
v1.0.0
|
#include <BillBoard.h>
複合項目 | |
| struct | Vertex |
公開型態 | |
| enum | { NUM_TEXTURES = 2 } |
| enum | Alignment { CAMERA_Z = 0, ROTATE_ABOUT_CAMERA, ROTATE_ABOUT_AXIS, ROTATE_ABOUT_PIVOT } |
| 公開型態 繼承自 Magnum::Graphics3Component | |
| enum | Mode { DEFAULT = 0, TRANSLATE = 1, ROTATE = 2, SCALE = 3 } |
| enum | CoordSys { LOCAL = 0, PARENT = 1, WORLD = 2, VIEW = 3 } |
公開方法(Public Methods) | |
| BillBoard (Component::Owner &owner_) | |
| BillBoard Constructor. 更多... | |
| virtual | ~BillBoard () |
| BillBoard Destructor. 更多... | |
| DECLARE_COMPONENT (BillBoard, Graphics3Component, false) PROPERTY(ResourcePath | |
| Set the Path of Shader of the ParticleEmitter. 更多... | |
| PROPERTY (ResourcePath, Texture0Path) | |
| Set the Path of Texture0 of the ParticleEmitter. 更多... | |
| PROPERTY (ResourcePath, Texture1Path) | |
| Set the Path of Texture1 of the ParticleEmitter. 更多... | |
| PROPERTY (Vector2, Size) | |
| Set the Size of the Particle of the ParticleEmitter. 更多... | |
| void | setAlignmentMode (const Alignment &mode) |
| Set the Alignment Mode of the Particle of the ParticleEmitter. 更多... | |
| const Alignment & | getAlignmentMode () const |
| void | setAlignmentAxis (const Vector3 &axis) |
| Set the Alignment Axis of the Particle of the ParticleEmitter. 更多... | |
| const Vector3 & | getAlignmentAxis () const |
| void | setRotationPivot (const Vector3 &pivot) |
| Set the Rotation Pivot of the Particle of the ParticleEmitter. 更多... | |
| const Vector3 & | getRotationPivot () const |
| 公開方法(Public Methods) 繼承自 Magnum::Graphics3Component | |
| Graphics3Component (Component::Owner &owner_) | |
| Graphics3Component Constructor. 更多... | |
| virtual | ~Graphics3Component () |
| Graphics3Component Destructor. 更多... | |
| 公開方法(Public Methods) 繼承自 Magnum::Component | |
| Component (Component::Owner &owner_) | |
| CLASS (Component, agm::reflection::NullClass) | |
| PROPERTY (bool, Enabled) | |
| Set the Enabled State of Owner, if the component is not active, it become non functional. 更多... | |
| PROPERTY (String, Name) | |
| Set the Name of Owner. 更多... | |
| Component::Owner & | getOwner () |
| const Component::Owner & | getOwner () const |
| virtual bool | isEditorModeActive () const =0 |
公開屬性 | |
| ShaderPath | |
類別朋友(Friends) | |
| class | BillBoardRenderer |
| BillBoard::BillBoard | ( | Component::Owner & | owner_ | ) |
BillBoard Constructor.
To Construct the BillBoard for the owner.
| owner_,the | Component::Owner which owns this component. |
| Magnum::BillBoard::DECLARE_COMPONENT | ( | BillBoard | , |
| Graphics3Component | , | ||
| false | |||
| ) |
Set the Path of Shader of the ParticleEmitter.
| value_,ResourcePath,the | Path of Shader of the ParticleEmitter. Get the Path of Shader of the ParticleEmitter. |
| Magnum::BillBoard::PROPERTY | ( | ResourcePath | , |
| Texture0Path | |||
| ) |
Set the Path of Texture0 of the ParticleEmitter.
| value_,ResourcePath,the | Path of Texture0 of the ParticleEmitter. Get the Path of Texture0 of the ParticleEmitter. |
| Magnum::BillBoard::PROPERTY | ( | ResourcePath | , |
| Texture1Path | |||
| ) |
Set the Path of Texture1 of the ParticleEmitter.
| value_,ResourcePath,the | Path of Texture1 of the ParticleEmitter. Get the Path of Texture1 of the ParticleEmitter. |
| Magnum::BillBoard::PROPERTY | ( | Vector2 | , |
| Size | |||
| ) |
Set the Size of the Particle of the ParticleEmitter.
| value_,Vector2,the | Size of the Particle of Texture of the ParticleEmitter. Get the Size of the Particle of Texture of the ParticleEmitter. |
| void BillBoard::setAlignmentAxis | ( | const Vector3 & | axis | ) |
Set the Alignment Axis of the Particle of the ParticleEmitter.
| value_,Vector3,the | Alignment Axis of the Particle of the ParticleEmitter. |
| void BillBoard::setAlignmentMode | ( | const Alignment & | mode | ) |
Set the Alignment Mode of the Particle of the ParticleEmitter.
| value_,ParticleEmitter::Alignment,the | Alignment Mode of the Particle of the ParticleEmitter. |
| void BillBoard::setRotationPivot | ( | const Vector3 & | pivot | ) |
Set the Rotation Pivot of the Particle of the ParticleEmitter.
| value_,Vector3,the | Rotation Pivot of the Particle of the ParticleEmitter. |


Fire 'n Ice
A remake of the game from NES with the same name.
View project page
CLICK TO START
Controls
Level Selector
Select a level
Left
and
Right
move player
Down / Space / Circle
creates an ice block
Enter / Cog
reloads current Level


WITNESS LIST Human Services Committee April 20, 1999-2:00P HB 3470 For: Bresette, Patrick (Center for Public Policy Priorities) On: Denton, Judy (DHS) Dyson, Lela (Texas Workforce Commission) HB 3636 For: Brown, Steve (Self) Franklin, Regina (THCA) Hardy, Alan (AARP) Hernandez, Leslie (NASW) Hricik, Kay (Alzheimer's Association Coalition of Texas) Oliver, W. Laurence (Texas Dental Assoc.) Pierce, Jack (Texas Dental Association) Reed, Micheal (Self) Willis, John (Texas Department on Aging) On: Gold, Marc (DHS) SB 558 For: Quoyeser, Cay (Self and Volunteer -Child Abuse Prevention Advocate) On: Heeney, John (Texas Licensed Child Care Association) Marsh, Mark (DPRS) SB 1423 For: Bressette, Patrick (Center for Public Policy Priorities) On: Denton, Judy (DHS) Prox, Chante (Self and Senator Royce West) SB 1574 For: Gantt, Melanie (Mental Health Association in Texas) Munson, Yolanda (FWISD-Parents as Teachers) Steele, Mike (Communities in Schools of Texas, Inc.) Tod, Theresa (Texas Network of Youth Services) Presentation On: Elliott, Roger (TX Higher Education Coordinating Board) Martinez, Barbara (Texas Commission for the Blind) Murphy, Terry (Texas Commission for the Blind)


See more on Github.
The factory execution sequence will be logged out below. Open the "network" panel in your inspector to see how the script-loading sequence differs.


gamejs/graphics
This module holds the important Surface
class which is the general container for image data.
var surface = new gamejs.graphics.Surface([width, height]);
The functions to draw geometric lines like circles, lines, rectangles, etc. are also all in this module:
gamejs.graphics.line(surface, '#ff0000', centerPoint, radius);
Each Surface instance has methods to create a new rotated, flipped, scaled, etc. instance of itself:
// the original `surface` remains untouched by the
// filp operation. A new Surface instance
// is returned by `flip()`.
var horizontalFlippedSurface = surface.flip(true);
If you want to put images (png, jpg) on the screen, also see the gamejs.image
module and gamejs.preload()
.
There are several ways to specify colors. Whenever the docs says "valid #RGB string"
you can pass in any of the following formats: "#ff00ff"
, "rgb(255, 0, 255)"
or "rgba(255, 0, 255, 1)"
.
See
Functions
- arc(surface, color, pos, startAngle,, stopAngle, radius, width)
- bezierCurve(surface, color, startPos, endPos, ct1Pos, ct2Pos, width)
- blitArray(surface, surfaceArray)
- circle(surface, color, pos, radius, width)
- line(surface, color, startPos, endPos, width)
- lines(surface, color, closed, pointlist, width)
- polygon(surface, color, pointlist, width)
- quadraticCurve(surface, color, startPos, endPos, controlPos, width)
- rect(surface, color, rect, width)
Surface (dimensions)
A Surface represents a bitmap image with a fixed width and height. The
most important feature of a Surface is that they can be blitted
onto each other.
Example
new gamejs.graphics.Surface([width, height]);
new gamejs.graphics.Surface(width, height);
new gamejs.graphics.Surface(rect);
Parameters
| Array | dimensions | Array holding width and height |
Surface.prototype.blit (src, dst, area, compositionOperation)
Blits another Surface on this Surface. The destination where to blit to can be given (or it defaults to the top left corner) as well as the Area from the Surface which should be blitted (e.g., for cutting out parts of a Surface).
Example
// blit flower in top left corner of display
displaySurface.blit(flowerSurface);
// position flower at 10/10 of display
displaySurface.blit(flowerSurface, [10, 10])
// ... `dest` can also be a rect whose topleft position is taken:
displaySurface.blit(flowerSurface, new gamejs.Rect([10, 10]);
// only blit half of the flower onto the display
var flowerRect = flowerSurface.rect;
flowerRect = new gamejs.Rect([0,0], [flowerRect.width/2, flowerRect.height/2])
displaySurface.blit(flowerSurface, [0,0], flowerRect);
Parameters
| gamejs.graphics.Surface | src | The Surface which will be blitted onto this one |
| gamejs.Rect|Array | dst | the Destination x, y position in this Surface. If a Rect is given, it's top and left values are taken. If this argument is not supplied the blit happens at [0,0]. |
| gamesjs.Rect|Array | area | the Area from the passed Surface which should be blitted onto this Surface. |
| Number | compositionOperation | how the source and target surfaces are composited together; one of: source-atop, source-in, source-out, source-over (default), destination-atop, destination-in, destination-out, destination-over, lighter, copy, xor; for an explanation of these values see: http://dev.w3.org/html5/2dcontext/#dom-context-2d-globalcompositeoperation |
Returns
| gamejs.Rect | Rect actually repainted FIXME actually return something? |
Surface.prototype.fill (CSS, a)
Fills the whole Surface with a color. Usefull for erasing a Surface.
Parameters
| String | CSS | color string, e.g. '#0d120a' or '#0f0' or 'rgba(255, 0, 0, 0.5)' |
| gamejs.Rect | a | Rect of the area to fill (defauts to entire surface if not specified) |
Surface.prototype.flip (flipHorizontal, flipVertical)
Flip a Surface either vertically, horizontally or both. This returns a new Surface (i.e: nondestructive).
Parameters
| Boolean | flipHorizontal | |
| Boolean | flipVertical |
Returns
| Surface | new, flipped surface |
Surface.prototype.getImageData ()
The data must be represented in left-to-right order, row by row top to bottom, starting with the top left, with each pixel's red, green, blue, and alpha components being given in that order for each pixel.
Returns
| ImageData | an object holding the pixel image data {data, width, height} |
Surface.prototype.rotate (angle)
Returns a new surface which holds this surface rotate by angle degrees. Unless rotating by 90 degree increments, the image will be padded larger to hold the new size.
Parameters
| angel | angle | Clockwise angle by which to rotate |
Returns
| Surface | new, rotated surface |
Surface.prototype.scale (dimensions)
Returns a new surface holding the scaled surface.
Parameters
| Array | dimensions | new [width, height] of surface after scaling |
Returns
| Surface | new, scaled surface |
Surface.prototype.setAlpha (alpha)
Set the alpha value for the whole Surface. When blitting the Surface on a destination, the pixels will be drawn slightly transparent.
Parameters
| Number | alpha | value in range 0.0 - 1.0 |
Returns
| Number | current alpha value |
SurfaceArray (surfaceOrDimensions)
Fast pixel access. The SurfaceArray can be constructed with a surface whose values are then used to initialize the pixel array.
The surface passed as argument is not modified by the SurfaceArray.
If an array is used to construct SurfaceArray, the array must describe the dimensions of the SurfaceArray [width, height].
Example
// create array from display surface
var srfArray = new SurfaceArray(display);
// direct pixel access
srfArray.set(50, 100, [255, 0, 0, 100]);
console.log(srfArray.get(30, 50));
// blit modified array back to display surface
blitArray(display, srfArray);
Parameters
| gamejs.graphics.Surface|Array | surfaceOrDimensions |
SurfaceArray.prototype.get (x, y)
Get rgba value at position xy,
Parameters
| Number | x | |
| Number | y |
Returns
| Array | [red, green, blue, alpha] |
SurfaceArray.prototype.getSize ()
SurfaceArray.prototype.set (x, y, rgba)
Set rgba value at position x, y.
For performance reasons this function has only one signature being Number, Number, Array4.
Parameters
| Number | x | x position of pixel |
| Number | y | y position of pixel |
| Array | rgba | [red, green, blue, alpha] values [255, 255, 255, 255] (alpha, the last argument defaults to 255) |
Throws
SurfaceArray.prototype.surface
a new gamejs.graphics.Surface on every access, representing the current state of the SurfaceArray.
arc (surface, color, pos, startAngle,, stopAngle, radius, width)
Parameters
| gamejs.graphics.Surface | surface | the Surface to draw on |
| String | color | a valid #RGB String, #ff00cc |
| Array | pos | [x, y] position of the circle center |
| Number | startAngle, | both angles in radians |
| Number | stopAngle | |
| Number | radius | |
| Number | width | the width of line, if 0 or not given the arc is filled. |
bezierCurve (surface, color, startPos, endPos, ct1Pos, ct2Pos, width)
Draw a bezier curve with two control points on the surface. The control point positions define the shape of the bezier curve.
Parameters
| gamejs.graphics.Surface | surface | the Surface to draw on |
| String | color | valid #RGB string, e.g., "#ff0000" |
| Array | startPos | [x, y] the start position for the bezier curve |
| Array | endPos | [x, y] the end position for the bezier curve |
| Array | ct1Pos | [x, y] position of the first control point |
| Array | ct2Pos | [x, y] position of the second control point |
| Number | width | of the bezier curve, defaults to 1 |
blitArray (surface, surfaceArray)
Directly copy values from an array into a Surface.
This is faster than blitting the surface
property on a SurfaceArray
The array must be the same dimensions as the Surface and will completely replace all pixel values.
Parameters
| gamejs.graphics.Surface | surface | |
| gamejs.graphics.Surfacearray.SurfaceArray | surfaceArray |
circle (surface, color, pos, radius, width)
Draw a circle on Surface
Parameters
| gamejs.graphics.Surface | surface | the Surface to draw on |
| String | color | a valid #RGB String, #ff00cc |
| Array | pos | [x, y] position of the circle center |
| Number | radius | of the circle |
| Number | width | width of the circle, if not given or 0 the circle is filled |
line (surface, color, startPos, endPos, width)
Parameters
| gamejs.graphics.Surface | surface | the Surface to draw on |
| String | color | valid #RGB string, e.g., "#ff0000" |
| Array | startPos | [x, y] position of line start |
| Array | endPos | [x, y] position of line end |
| Number | width | of the line, defaults to 1 |
lines (surface, color, closed, pointlist, width)
Draw connected lines. Use this instead of indiviudal line() calls for better performance
Parameters
| gamejs.graphics.Surface | surface | the Surface to draw on |
| String | color | a valid #RGB string, "#ff0000" |
| Boolean | closed | if true the last and first point are connected |
| Array | pointlist | holding array [x,y] arrays of points |
| Number | width | width of the lines, defaults to 1 |
polygon (surface, color, pointlist, width)
Draw a polygon on the surface. The pointlist argument are the vertices for the polygon.
Parameters
| gamejs.graphics.Surface | surface | the Surface to draw on |
| String | color | a valid #RGB String, #ff00cc |
| Array | pointlist | array of vertices [x, y] of the polygon |
| Number | width | the width of line, if 0 or not given the polygon is filled. |
quadraticCurve (surface, color, startPos, endPos, controlPos, width)
Draw a quadratic curve with one control point on the surface. The control point position defines the shape of the quadratic curve.
Parameters
| gamejs.graphics.Surface | surface | the Surface to draw on |
| String | color | valid #RGB string, e.g., "#ff0000" |
| Array | startPos | [x, y] the start position for the quadratic curve |
| Array | endPos | [x, y] the end position for the quadratic curve |
| Array | controlPos | [x, y] position of the control point |
| Number | width | of the quadratic curve, defaults to 1 |
rect (surface, color, rect, width)
Parameters
| gamejs.graphics.Surface | surface | the Surface to draw on |
| String | color | a valid #RGB String, #ff00cc |
| gamejs.Rect | rect | the position and dimension attributes of this Rect will be used |
| Number | width | the width of line drawing the Rect, if 0 or not given the Rect is filled. |


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Data processing, Machine learning, everything that simplifies life


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Edit the domain size and simulation length in the Config Basics tab. Edit diffusion parameters in the Microenvironment tab, and model-specific parameters in the User Params tab. Once you are satisfied with your settings, click the Run button to start the simulation. (After the run starts, the the Run button is replaced with a Cancel button.)
As the simulation runs, an "Output" widget can be clicked/expanded to reveal the progress (text) of the simulation. Model outputs can be visualized in the Out: Plots tab while the simulation is running. The "# cell frames" will be dynamically updated as the simulation progresses. Note that the simulation images (SVG files) and raw output data (in MultiCellDS format) can be downloaded in this tab once the simulation is done.
Once the simulation is done running, use the Animate tab to create a movie. Please be patient: it may take a few minutes for the script to finish running before the movie is embedded in the tab. You can download the generated movie once it's done.
This app demonstrates the evaluation of the effects of mechanical interactions between liver parenchyma (normal liver tissue) and tumor cells on metastatic seeding and growth.
Legend:
In this model [4], We simulate a small tumor growing in liver parenchyma (maximum size is 1 cm × 1 cm). The liver tissue is elastic-plastic: Elastic: on short times, when it’s deformed it elastically tries to return to its rest position and imparts forces on nearby tumor cells; Plastic: on long times, the resting position of these tissue elements relaxes back to the current position.
We found that:
(1) In high-flow / well-perfused liver tissues, growth substrate limitations (oxygen in our case) alone are an insufficient growth control to prevent non-physical overlap of cells. Mechanobiologic feedbacks are necessary. These are modeled as a pressure that can reduce or completely shut down cycle entry.
(2) In some tissue regimes, this can arrest the growth of micrometastases.
Try rE = 0.2 min-1, rP = 0.0005 min-1, and
a maximum parenchyma displacement of 3 μm to see this behavior.
(3) In other tissue regimes, tumors will develop invasive fingers into the surrounding tissue
along mechanical weaknesses.
Try rE = 0.05 min-1, rP = 0.0005 min-1, and
a maximum parenchyma displacement of 3 μm to see this behavior.
We used agent-based models to simulation the cell-cell interactions, where the liver parenchyma are stress-based apoptosis and no birth, while tumor cells are pressure-regulated cycling and stochastic apoptosis.
In details, if parenchymal agent’s magnitude of displacement exceeds the maximum tolerated deformation, the parenchyma would enter apoptosis immediately. For the tumor agent, its cycling rate is controlled by the pressure between them and surrounding liver tissue, when the pressue is greater than the threshold value (it is 1 in our default), the birth rate would be set to 0.
All chemical signals move by chemical diffusion in the simulated environment, using BioFVM [1] to solve the reaction-diffusion equations. A key property is the diffusion length scale. Diffusion (with a diffusion coefficient D) helps spread a signal over large distances, while decay (and uptake) (with coefficient λ) eliminates the signal to slow its spread. These effects compete to determine the characteristic distance Lthat a chemical signal travels.
In our model, the only substrate is oxygen. We used BioFVM [1] to simulate diffusive transport. By investigating a poroviscoelastic (PVE) model, we constructed a quasi-steady single-lobule model, and extended this for the far-field oxygen solution. See [4] for details.
In details, Outside tumors: it's advection-dominated transport. We useed quasi-steady analytic solution for O2 transport; Inside tumors: it's diffusion-dominated transport. We used BioFVM-based numeric solution for O2 transport.
The agent-based model was created using PhysiCell [2] as follows:
Cells can proliferate (divide into two daughter cells of half size), with division rates regulated by cell rules. In our model, cells continuously work to grow towards a "target" mature volume.
Note that birth and death are stochastic events for each cell agent: if such a process occurs at rate r, then between now (t) and soon (t + Δt), the probability of the event occurring for that agent is rΔt.
In our model, liver parenchyma have no birth rate, and their death rate is controlled by the displacement as explained by section of Modeling approach. For the tumor cells, they have normal apoptosis rate, while the cycling rate is regulated by the pressue and oxygen function.
Cells can secrete chemical factors, or they can remove them (i.e., consume or uptake). This can contribute to gradients in chemical factors, and it's a key method of communication between cells. Moreover, cells can "sample" the chemical state of their surrounding environment. Secreting is sending a signal. Uptaking and sampling is receiving a signal.
In our model, tumor cells uptake oxygen, which is particularly important in the center area of big tumor. Because, if the tumor radius is greater than diffusion length scale the tumor cells in the center of tumor would have limited oxygen, as a result, their cycling rate would decrease to zero and enter necrosis state.
Cell agents can stick to one another within a prescribed interaction distance (some multiple of their radius), and they can exert a pushing force on neighbors. PhysiCell [2] uses potential functions to implement these simple mechanics. Notably, PhysiCell is an off-lattice model, meaning that cells can have variable sizes, and can move freely without grid artifacts.
They aren't required to move some prescribed number of spatial steps. They also can divide without checking for an open neighbor "site". Instead, they can divide and push their neighbors out of the way.
In the model, two types of cell contacted with each other and produce force/pressue, which regulated their birth rate or death rate. See the details in the following Liver parenchyma cells and Tumor cells.
Each parenchymal agent follows regular adhesion-repulsion mechanics (with a position xi). In addition, mechanical interactions are modeled with underlying ECM. Each agent i is attached to the ECM at xi,ECM, and experiences an elastic force. Let di = xi,ECM − xi, and let di = ∥di∥ − Ri (Ri is cell’s equivalent radius) denote the elastic deformation; let rE and rP denote the elastic rate and plastic relaxation rate respectively, both the elastic and plastic reorganization show as following:
Liver parenchyma cells are originally homeostatic. If parenchymal agent’s magnitude of displacement exceeds the maximum tolerated deformation (dmax), the parenchyma would enter apoptosis immediately.
The built-in " Ki67_advanced " cell cycle model is used in our model, with the default models of apoptosis and necrosis. Thus, each cell agent can be transited from the Ki67- phase to the pre-mitotic Ki67+ cycle phase, Apoptotic, or Necrotic. For the transition rate, the regular "oxygen-dependent" cycle entry rate is scaled by the pressure. See [4] for more details.
Apoptosis is modeled as microenvironment-independent, with a constant apoptotic death rate dA and a stochastic duration with mean TA. Necrosis is modeled as oxygen-dependent: cells enter the necrotic state if σ < σN (necrosis threshold), and then progress as described in PhysiCell [2]. We also added a rule of pressure-regulated proliferation here, so the cycling rate is:
The first part is transition rate with oxygen levels as described in [2]. The normalized cell pressure in conﬂuent tissue (no gaps in the tissue) is 0.5 (2D). We deﬁned as p2 and p1 as 1.0 and 0 respectively here, which means if pressure the tumor cell experiences is greater than 1.0, we set the tumor cell proliferation rate as zero, also labeled as yellow in the simulation.
This model [4] and cloud-hosted demo are part of the education and outreach for the IU Engineered nanoBIO Node. The models are built using PhysiCell: a C++ framework for multicellular systems biology [2] for the core simulation engine and xml2jupyter [3] to create the graphical user interface (GUI).


I am currently working as a Research Assistant at University of Pennsylvania,under Professor Chris Callison-Burch. My project involves constructing a formalized ontology of event types. Given the semantic representations of the event's, we find the similar sentences from an unlabeled-unstructured corpora that describe that event.In collaboration with University of Colorado, we extract the semantic roles and participants for each of those event types, to build this formalized ontology. All annotations there within will be used for classification and semantic role-labeling tasks.
May 2020-PresentI am a second year Master's in DataScience student at University of Pennsylvania (graduating in Spring 2021). My key coursework includes Machine Perception, Computer Linguistics, Data Mining, Machine Learning, Statistics for Data Science
August 2019- May 2021I was a part of Applied AI team in Deloitte consulting. I have worked on multiple client-facing projects in the domain of Data Science. Most of my projects involved extensive use of core ML techniques and algorithms and expertise in Python and PyTorch.
August 2018 - August 2019I have done my undergraduate in Computer Science and Engineering. My key-coursework includes Pattern Recognition, AI, Image & Vision Computing, Data Mining & Warehousing, Operations Research, Linear Algebra, Numerical Analysis, Cloud Computing, Database System
July 2014- May 2018


Template Articulated Simulink¶
This template shows how to simulate an articulated vehicle in Simulink using a s-function. The graphics are also plotted.
This model uses the s-function ArticulatedVehicleSFunction.m in Simulink. The package and this s-function must be in Matlab path.
The “ArticulatedVehicleSimulink.slx” available in the repository (“examples/TemplateArticulatedSimulink”) is illustrated below:
It can be seen that the longitudinal forces of the tire are zero for the entire simulation. The steering angle recieve a step input.
Template¶
To simulate the model run
sim('ArticulatedVehicleSimulink');
Each vehicle state variable goes to a scope. And the output of the model is saved in the workspace.
To generate the graphics, the same model used in Articulated Vehicle S-Function must be defined.
Todo
Improve generation of graphics. Define parameters once -> Run Simulink -> Retrieve responses -> Graphics
First, define the tire model.
TireModel = TirePacejka(); % Choosing tire model
Defining the tire parameters to match the parameters used in the S-Function.
TireModel.a0 = 1;
TireModel.a1 = 2;
TireModel.a2 = 700;
TireModel.a3 = 5000;
TireModel.a4 = 80;
TireModel.a5 = 0;
TireModel.a6 = 0;
TireModel.a7 = 0.6;
TireModel.a8 = 0;
TireModel.a9 = 0;
TireModel.a10 = 0;
TireModel.a11 = 0;
TireModel.a12 = 0;
TireModel.a13 = 0;
The vehicle model is defined as
VehicleModel = VehicleArticulatedNonlinear();
Defining the vehicle parameters to match the parameters used in the S-Function.
VehicleModel.mF0 = 5200;
VehicleModel.mR0 = 2400;
VehicleModel.mF = 6000;
VehicleModel.mR = 10000;
VehicleModel.mM = 17000;
VehicleModel.IT = 46000;
VehicleModel.IS = 450000;
VehicleModel.lT = 3.5;
VehicleModel.lS = 7.7;
VehicleModel.c = -0.3;
VehicleModel.nF = 2;
VehicleModel.nR = 4;
VehicleModel.nM = 8;
VehicleModel.wT = 2.6;
VehicleModel.wS = 2.4;
VehicleModel.muy = 0.8;
VehicleModel.deltaf = 0;
VehicleModel.Fxf = 0;
VehicleModel.Fxr = 0;
VehicleModel.Fxm = 0;
VehicleModel.tire = TireModel;
Defining the simulation object.
simulator = Simulator(VehicleModel, tout);
Retrieving state responses from Simulink model
simulator.XT = simout.Data(:,1);
simulator.YT = simout.Data(:,2);
simulator.PSI = simout.Data(:,3);
simulator.PHI = simout.Data(:,4);
simulator.VEL = simout.Data(:,5);
simulator.ALPHAT = simout.Data(:,6);
simulator.dPSI = simout.Data(:,7);
simulator.dPHI = simout.Data(:,8);
Frame and animation can be generated defining a graphic object (Graphics
). The only argument of the graphic object is the simulator object after the simulation.
g = Graphics(simulator);
To change the color of the tractor and the semitrailer run
g.TractorColor = 'r';
g.SemitrailerColor = 'g';
After that, just run
g.Frame();
g.Animation();
Both graphics feature can be seen below.
Todo
Include Template Simple Simulink Animation
As expected the vehicle starts traveling in a straight line and starts a turn at (t = 1 , s) because of the step function.
Articulated Vehicle S-Function¶
The articulated vehicle S-Function is depicted below.
function [sys,x0,str,ts] = ArticulatedVehicleSFunction(t,x,u,flag)
% This file is a s-function template for simulating the articulated vehicle model in Simulink.
% Choosing tire model
TireModel = TirePacejka();
% Defining tire parameters
TireModel.a0 = 1;
TireModel.a1 = 2;
TireModel.a2 = 700;
TireModel.a3 = 5000;
TireModel.a4 = 80;
TireModel.a5 = 0;
TireModel.a6 = 0;
TireModel.a7 = 0.6;
TireModel.a8 = 0;
TireModel.a9 = 0;
TireModel.a10 = 0;
TireModel.a11 = 0;
TireModel.a12 = 0;
TireModel.a13 = 0;
% Choosing vehicle model
VehicleModel = VehicleArticulatedNonlinear();
% Defining vehicle parameters
VehicleModel.mF0 = 5200;
VehicleModel.mR0 = 2400;
VehicleModel.mF = 6000;
VehicleModel.mR = 10000;
VehicleModel.mM = 17000;
VehicleModel.IT = 46000;
VehicleModel.IS = 450000;
VehicleModel.lT = 3.5;
VehicleModel.lS = 7.7;
VehicleModel.c = -0.3;
VehicleModel.nF = 2;
VehicleModel.nR = 4;
VehicleModel.nM = 8;
VehicleModel.wT = 2.6;
VehicleModel.wS = 2.4;
VehicleModel.muy = 0.8;
VehicleModel.deltaf = 0;
VehicleModel.Fxf = 0;
VehicleModel.Fxr = 0;
VehicleModel.Fxm = 0;
VehicleModel.tire = TireModel;
switch flag,
%%%%%%%%%%%%%%%%%%
% Initialization %
%%%%%%%%%%%%%%%%%%
case 0,
[sys,x0,str,ts]=mdlInitializeSizes();
%%%%%%%%%%%%%%%
% Derivatives %
%%%%%%%%%%%%%%%
case 1,
sys=mdlDerivatives(t,x,u,VehicleModel);
%%%%%%%%%%%
% Outputs %
%%%%%%%%%%%
case 3,
sys=mdlOutputs(t,x,u,VehicleModel);
%%%%%%%%%%%%%%%%%%%
% Unhandled flags %
%%%%%%%%%%%%%%%%%%%
case { 2, 4, 9 },
sys = [];
%%%%%%%%%%%%%%%%%%%%
% Unexpected flags %
%%%%%%%%%%%%%%%%%%%%
otherwise
DAStudio.error('Simulink:blocks:unhandledFlag', num2str(flag));
end
% end csfunc
%
%=============================================================================
% mdlInitializeSizes
% Return the sizes, initial conditions, and sample times for the S-function.
%=============================================================================
%
function [sys,x0,str,ts]=mdlInitializeSizes()
% Definitions
sizes = simsizes;
sizes.NumContStates = 8;
sizes.NumDiscStates = 0;
sizes.NumOutputs = 8;
sizes.NumInputs = 4;
sizes.DirFeedthrough = 1;
sizes.NumSampleTimes = 1;
sys = simsizes(sizes);
% Setting initial conditions
x0 = [0 0 0 0 15 0 0 0];
str = [];
ts = [0 0];
% end mdlInitializeSizes
%
%=============================================================================
% mdlDerivatives
% Return the derivatives for the continuous states.
%=============================================================================
%
function sys = mdlDerivatives(t,x,u,vehicle)
% Defining input
vehicle.deltaf = u(1);
vehicle.Fxf = u(2);
vehicle.Fxr = u(3);
vehicle.Fxm = u(4);
% Getting the vehicle model function (state equations)
ModelFunction = @vehicle.Model;
% Getting the mass matrix function of the model
MassMatrixFunction = @vehicle.MassMatrix;
% The derivatives are calculated with the inverse of the MassMatrix
sys = MassMatrixFunction(t,x)\ModelFunction(t,x,0);
% end mdlDerivatives
%
%=============================================================================
% mdlOutputs
% Return the block outputs.
%=============================================================================
%
function sys=mdlOutputs(~,x,~,~)
% Output are all state variables
sys = x;
% end mdlOutputs


ErrorType
in package
Indicates the type of an error. Think of this as a broad category rather than a specific error.
Tags
Table of Contents
- ACCOUNT_STATUS = 'account_status'
- There is a problem with your account. This may be your ShipEngine account or a third-party account. See the the error source to determine which account needs your attention.
- BUSINESS_RULES = 'business_rules'
- There was a business rule violation. Business rules are requirements or limitations of a system. If the error source is ShipEngine, then please read the relevant documentation to find out what limitations or requirements apply. Or contact our support for help. If the error source is the carrier or order source, then ShipEngine support may still be able to help clarify the problem or propose a solution, or you may need to contact the third-party for assistance.
- SECURITY = 'security'
- A security error will occur if your API key is invalid or expired, or if you attempt to perform an operation that is not permitted for your account.
- SYSTEM = 'system'
- An unknown or unexpected error occurred in our system. Or an error occurred that has not yet been assigned a specific error_type. If you receive persistent system errors, then please contact our support or check our API status page to see if there's a known issue.
- VALIDATION = 'validation'
- Something is wrong with the input provided, such as missing a required field, or an illegal value or combination of values. This error type always means that some change needs to be made to the input before retrying.
Constants
ACCOUNT_STATUS
There is a problem with your account. This may be your ShipEngine account or a third-party account. See the the error source to determine which account needs your attention.
public
mixed
ACCOUNT_STATUS
= 'account_status'
BUSINESS_RULES
There was a business rule violation. Business rules are requirements or limitations of a system. If the error source is ShipEngine, then please read the relevant documentation to find out what limitations or requirements apply. Or contact our support for help. If the error source is the carrier or order source, then ShipEngine support may still be able to help clarify the problem or propose a solution, or you may need to contact the third-party for assistance.
public
mixed
BUSINESS_RULES
= 'business_rules'
SECURITY
A security error will occur if your API key is invalid or expired, or if you attempt to perform an operation that is not permitted for your account.
public
mixed
SECURITY
= 'security'
SYSTEM
An unknown or unexpected error occurred in our system. Or an error occurred that has not yet been assigned a specific error_type. If you receive persistent system errors, then please contact our support or check our API status page to see if there's a known issue.
public
mixed
SYSTEM
= 'system'
VALIDATION
Something is wrong with the input provided, such as missing a required field, or an illegal value or combination of values. This error type always means that some change needs to be made to the input before retrying.
public
mixed
VALIDATION
= 'validation'


APPS ☺
This is content text and nothing else. Just like a "fish text" named as Lorem Ipsum...
Fish text was created to fill page of your book or website with randomed text in latin.
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§431:10F-104 Release from liability. A surety insurer may be released from its liability on the same terms and conditions as are provided by law for the release of individuals as sureties. [L 1987, c 347, pt of §2]