Optimisation Package¶
This module contains code for automatically optimising parametric models for a given sequence.
Submodules¶
isambard.optimisation.base_evo_opt module¶
Base class for bio-inspired optimizers.
-
class
isambard.optimisation.base_evo_opt.
BaseOptimizer
(specification, sequences, parameters, build_fn=None, eval_fn=None, **kwargs)[source]¶ Bases:
object
Abstract base class for the evolutionary optimizers.
Notes
Not intended to be used directly, see the evolutionary optimizers for full documentation.
-
assign_fitnesses
(targets)[source]¶ Assigns fitnesses to parameters.
Notes
Uses self.eval_fn to evaluate each member of target.
Parameters: targets – Parameter values for each member of the population.
-
best_model
¶ Rebuilds the top scoring model from an optimisation.
Returns: model – Returns an AMPAL model of the top scoring parameters. Return type: AMPAL Raises: AttributeError
– Raises a name error if the optimiser has not been run.
-
static
funnel_rebuild
()[source]¶ Rebuilds a model and compares it to a reference model.
Parameters: psg_trm ((([float], float, int), AMPAL, specification)) – A tuple containing the parameters, score and generation for a model as well as a model of the best scoring parameters. Returns: energy_rmsd_gen – A triple containing the BUFF score, RMSD to the top model and generation of a model generated during the minimisation. Return type: (float, float, int)
-
log_results
(output_path=None, run_id=None)[source]¶ Saves files for the minimization.
Notes
Currently saves a logfile with best individual and a pdb of the best model.
-
make_energy_funnel_data
(cores=1)[source]¶ Compares models created during the minimisation to the best model.
Parameters: cores (int) – Number of CPU cores to rebuild models and measure RMSD. Returns: energy_rmsd_gen – A list of triples containing the BUFF score, RMSD to the top model and generation of a model generated during the minimisation. Return type: [(float, float, int)]
-
parse_individual
(individual)[source]¶ Converts a deap individual into a full list of parameters.
Parameters: individual (deap individual from optimization) – Details vary according to type of optimization, but parameters within deap individual are always between -1 and 1. This function converts them into the values used to actually build the model Returns: fullpars – Full parameter list for model building. Return type: list
-
run_opt
(pop_size, generations, cores=1, plot=False, log=False, log_path=None, run_id=None, store_params=True, **kwargs)[source]¶ Runs the optimizer.
Parameters: - pop_size (int) – Size of the population each generation.
- generation (int) – Number of generations in optimisation.
- cores (int, optional) – Number of CPU cores used to run the optimisation. If the ‘mp_disabled’ keyword is passed to the optimizer, this will be ignored and one core will be used.
- plot (bool, optional) – If true, matplotlib will be used to plot information about the minimisation.
- log (bool, optional) – If true, a log file describing the optimisation will be created. By default it will be written to the current directory and named according to the time the minimisation finished. This can be manually specified by passing the ‘output_path’ and ‘run_id’ keyword arguments.
- log_path (str) – Path to write output file.
- run_id (str) – An identifier used as the name of your log file.
- store_params (bool, optional) – If true, the parameters for each model created during the optimisation will be stored. This can be used to create funnel data later on.
-
-
class
isambard.optimisation.base_evo_opt.
Parameter
(label, parameter_type, value)[source]¶ Bases:
object
Defines a parameter used in the evolutionary optimizers.
-
default_value
¶
-
isambard.optimisation.evo_optimizers module¶
Bio-inspired optimizers.
-
class
isambard.optimisation.evo_optimizers.
CMAES
(specification, sequences, parameters, eval_fn, build_fn=<function default_build>, sigma=0.3, weight_type='superlinear', **kwargs)[source]¶ Bases:
isambard.optimisation.base_evo_opt.BaseOptimizer
Covariance matrix adaptation evolutionary strategy optimizer.
Notes
Basically uses a covariance matrix at each step to identify the ‘direction’ of the optimal solution in the search space, and generates new individuals accordingly. Bound handling is achieved by moving any out of bounds parameters to the boundary condition. Other than that the implementation used here is as in the originating code from the deap module.
Parameters: - specification (ampal.specification.assembly_specification) – An Assembly level specification to be optimised.
- sequences ([str]) – A list of sequences, one for each polymer.
- parameters ([base_ev_opt.Parameter]) – A list of Parameter objects in the same order as the function signature expects.
- build_fn (function((spec, seq, params)) -> ampal) – A function for building a model using parameters supplied by the optimizer.
- eval_fn (function(ampal) -> float) – An evaluation function that assesses an AMPAL object and returns a float. This float will be used to compare models. The optimizer uses the thermodynamic convention that lower numbers are better.
- sigma (float) – Initial standard deviation of the distribution.
- weight_type (str) – Can be ‘linear’, ‘superlinear’ or ‘equal’. Used to decrease speed of particles.
-
compute_params
()[source]¶ Computes the parameters depending on \(\lambda\).
Notes
It needs to be called again if \(\lambda\) changes during evolution.
-
class
isambard.optimisation.evo_optimizers.
DE
(specification, sequences, parameters, eval_fn, build_fn=<function default_build>, cxpb=0.75, diff_weight=1, neighbours=None, **kwargs)[source]¶ Bases:
isambard.optimisation.base_evo_opt.BaseOptimizer
Differential evolution optimisation algorithm.
Notes
Can use neighbourhood model to reduce chance of getting stuck in local optima. This is a very versatile algorithm, and its use is recommended.
Parameters: - specification (ampal.specification.assembly_specification) – An Assembly level specification to be optimised.
- sequences ([str]) – A list of sequences, one for each polymer.
- parameters ([base_ev_opt.Parameter]) – A list of Parameter objects in the same order as the function signature expects.
- build_fn (function((spec, seq, params)) -> ampal) – A function for building a model using parameters supplied by the optimizer.
- eval_fn (function(ampal) -> float) – An evaluation function that assesses an AMPAL object and returns a float. This float will be used to compare models. The optimizer uses the thermodynamic convention that lower numbers are better.
- cxpb (float) – The probability of crossing two individuals.
- diff_weight (float) – A scaling factor for crossing.
- neighbours (int or None) – If not None, uses a neighbourhood model to reduce the likelihood of the optimisation getting stuck in a local optima. The number of particles to use as neighbours can be provided as an int.
-
class
isambard.optimisation.evo_optimizers.
GA
(specification, sequences, parameters, eval_fn, build_fn=<function default_build>, cxpb=0.5, mutpb=0.2, **kwargs)[source]¶ Bases:
isambard.optimisation.base_evo_opt.BaseOptimizer
A classic genetic algorithm optimization algorithm.
Notes
Very good for eliminating unfavourable regions of the search space. Can be heavily customized in terms of mutation and crossover operators etc. Bound handling is achieved simply by amending any out of bounds parameters to the boundary value.
Parameters: - specification (ampal.specification.assembly_specification) – An Assembly level specification to be optimised.
- sequences ([str]) – A list of sequences, one for each polymer.
- parameters ([base_ev_opt.Parameter]) – A list of Parameter objects in the same order as the function signature expects.
- build_fn (function((spec, seq, params)) -> ampal) – A function for building a model using parameters supplied by the optimizer.
- eval_fn (function(ampal) -> float) – An evaluation function that assesses an AMPAL object and returns a float. This float will be used to compare models. The optimizer uses the thermodynamic convention that lower numbers are better.
- cxpb (float) – The probability of crossing two individuals.
- mutpb (float) – Probability of mutating an individual.
-
class
isambard.optimisation.evo_optimizers.
PSO
(specification, sequences, parameters, eval_fn, build_fn=<function default_build>, max_speed=0.75, neighbours=None, **kwargs)[source]¶ Bases:
isambard.optimisation.base_evo_opt.BaseOptimizer
A particle swarm optimization algorithm.
Notes
This is good for avoiding bias and premature minimization, though it may struggle to find the ultimate optimum solution. Supports the neighbourhood model. Bound handling is achieved by allowing particles to exceed permitted bounds, but not assigning them a fitness in this case.
Parameters: - specification (ampal.specification.assembly_specification) – An Assembly level specification to be optimised.
- sequences ([str]) – A list of sequences, one for each polymer.
- parameters ([base_ev_opt.Parameter]) – A list of Parameter objects in the same order as the function signature expects.
- build_fn (function((spec, seq, params)) -> ampal) – A function for building a model using parameters supplied by the optimizer.
- eval_fn (function(ampal) -> float) – An evaluation function that assesses an AMPAL object and returns a float. This float will be used to compare models. The optimizer uses the thermodynamic convention that lower numbers are better.
- max_speed (float) – The maximum speed that a particle can have in the swarm.
- neighbours (int or None) – If not None, uses a neighbourhood model to reduce the likelihood of the optimisation getting stuck in a local optima. The number of particles to use as neighbours can be provided as an int.
isambard.optimisation.mmc_optimizer module¶
Provides optimisation of structure using Metropolis Monte Carlo.
-
class
isambard.optimisation.mmc_optimizer.
MMCParameter
(label, parameter_type, static_dist_or_list, starting_value=None)[source]¶ Bases:
object
Defines parameters used in the MMC optimizer.
Parameters: - label (str) – The name of the parameter.
- parameter_type (MMCParameterType) – The type of the parameter.
- static_dist_or_list – The values used to create the parameter. For example, if the parameter types is “STATIC_VALUE” then this can be any object, if it is “LIST” then it should be a list of values and if it is “UNIFORM_DIST” then it should be (mu, sigma) etc.
- optional (starting_value,) – The initial value of the parameter.
-
label
¶ str – The name of the parameter.
-
parameter_type
¶ MMCParameterType – The type of the parameter.
-
static_dist_or_list
¶ The values used to create the parameter. For example, if the parameter types is “STATIC_VALUE” then this can be any object, if it is “LIST” then it should be a list of values and if it is “UNIFORM_DIST” then it should be (mu, sigma) etc.
-
starting_value
¶ The initial value of the parameter.
-
current_value
¶ The currently accepted value for the parameter.
-
proposed_value
¶ A new value proposed for the parameter that has not been accepted.
-
class
isambard.optimisation.mmc_optimizer.
MMCParameterOptimisation
(specification, parameters, sequences, eval_function)[source]¶ Bases:
object
Performs Metropolis Monte Carlo opimisation on a specification.
References
[0] Metropolis N, Rosenbluth AW, Rosenbluth MN, Teller AH and Teller E (1953) Equations of State Calculations by Fast Computing Machines, Journal of Chemical Physics. 21 (6), 1087-1092. Parameters: - specification (isambard.Specification) – Any ISAMBARD specification. This will be used to create models during the optimisation.
- parameters ([MMCParameter]) – Parameters to be optimised. The order of the parameters should match the init signiture of the specification.
- sequences ([str]) – The sequences to be used during the optimisation.
- eval_function (f(ampal) -> float) – A function that takes an AMPAL object as an input and returns a float. By default the buff_interaction_energy will be used to evaluate the structure.
-
specification
¶ isambard.Specification – Any ISAMBARD specification. This will be used to create models during the optimisation.
-
parameters
¶ [MMCParameter] – Parameters to be optimised. The order of the parameters should match the init signiture of the specification.
-
sequences
¶ [str] – The sequences to be used during the optimisation.
-
eval_function
¶ f(ampal) -> float – A function that takes an AMPAL object as an input and returns a float. By default the buff_interaction_energy will be used to evaluate the structure.
-
current_energy
¶ float – The energy of the current structure.
-
best_energy
¶ float – The best energy observed for any model.
-
best_parameters
¶ [MMCParameter] – The parameters associated with the best_energy.
-
best_model
¶ AMPAL Object – The model associated with the best_energy.
-
best_energy
= None
-
best_model
= None
-
best_parameters
= None
-
static
check_move
(old, t)[source]¶ Determines if a model will be accepted.
Uses Boltzmann distribution scaled by temperature in Kelvin.
-
current_energy
= None


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netflix
Businessmodel of Netflix
Customer Segments
Netflix has always sought to appeal to a mass-market by providing an affordable, convenient way to consume video media.
Initially, before the advent of online streaming, they sought to take customers away from established brick-and-mortar video rental stores such as Blockbuster by providing the consumer with a more convenient way to choose films with the added benefit that they didn’t impose exorbitant late fees.
Since 2007, their target customer base has expanded to include almost everyone in the world with a high-speed internet connection. They have been central players in bringing on-demand premium video streaming to the mass market.
Value Proposition
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They are also appealing for many consumers because unlike some competitors such as Hulu Plus, they do not currently include advertisements for subscribers.
There is nothing inherently non-replicable about Netflix’s streaming-business model, and increasingly, as the world of online streaming develops, they find themselves in a market with a lot of strong competition. Their current dominant position in the market is due to their status as pioneering and well-funded early developers in the field, and they continue to offer users access to an unparalleled range of content. Nonetheless, it remains to be seen whether they can maintain this status, or whether disruptive newcomers may eat into their market-share in the future.
Channels
Netflix’s main channel has always been their website. Initially, customers could mail-order film rentals from it, and the convenience of this online channel that enabled them to usurp their rival Blockbuster’s market-share.
Nowadays, subscribers stream video directly from netflix.com, but Netflix also offer a mobile app for subscribers which serves as a key secondary channel.
TV set top boxes provide another channel, as Netflix has done much work to ensure the compatibility of their platform with many main brands.
Customer Relationships
Netflix maintains its relationships with customers on a subscription fee basis, offering unlimited on-demand streaming in exchange for a monthly fee.
Netflix has created a platform in which the user experience is entirely self-service, and yet still easy to use. The company was an early pioneer of film-recommendation algorithms, which they developed to give the user a better experience.
Key Activities
Over the years Netflix’s key activities have shifted from mail-order processing to focus on developing online video player software, content licensing and original content development.
Key Partners
Content providers have always been key partners, as their entire business model is completely dependent on third-party video content. Netflix have negotiated deals with studios the world over to obtain rights for streaming the content they offer.
Another key partner used to be the United States Postal service, who processed the hundreds of millions of rentals that at one point they were posting yearly. This end of the business has since declined, and as streaming took over, internet service providers have replaced them as key distribution partners.
Key Resources
Netflix’s original key resource was its massive inventory of DVDs and efficient mail-order processing capabilities, but today, Netflix’s key resource is the rights it owns to stream virtual content. It has deals with more content producers than its rivals and is therefore able to offer its users a wider array of content.
The platform itself is also a key asset. They have invested heavily in ensuring it is as user-friendly and reliable as possible while offering a wide range of highly developed features such as algorithmic film recommendation.
An increasingly lucrative resource for Netflix is their original content. They own the exclusive rights to a number of in-house productions that regularly draw audiences of millions.
Cost Structure
Netflix’s biggest expenditure is paying for the rights to stream its third-party content. Netflix’s cost structure is cost-driven, and its business is based on its ability to sell cheap streaming to a mass market. These days, because it is such a large and important channel for content producers, Netflix is often able to negotiate more favorable licensing deals than its competitors, allowing it to offer its services so cheaply.
To provide customer service and to update and innovate its platform, Netflix employs over 3,700 employees, whose salaries constitute another key expenditure.
Revenue Streams
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[ aws ]
Amazon EC2 Container Registry (Amazon ECR) is a managed AWS Docker registry service. Customers can use the familiar Docker CLI to push, pull, and manage images. Amazon ECR provides a secure, scalable, and reliable registry. Amazon ECR supports private Docker repositories with resource-based permissions using AWS IAM so that specific users or Amazon EC2 instances can access repositories and images. Developers can use the Docker CLI to author and manage images.


ku4js-data
node
ele
Field
File
FirstName
LastName
Birthday
Salary
Title
Select One
Director
Senior
Middle
Skilled
General
Save
Load
Event


A member of a set.
x ∈ S means that element x is in set S.
$ \mathrm{x} \notin \mathrm{S} $ means that element x is not in set S.


Pat's Daily Sales
More Stores to Come
Home Page
Store Name
Minimum Customers
Maximum Customers
Average Sales per Customer


Workspaces¶
Workspaces provide a means to collect multiple typed objects (TOs) into one container and share the container with other people. This documentation will demonstrate some of the most common operations on workspaces (see Workspace API documentation for the full API). It assumes that a functional client is available (see Build and initialize the workspace client). The examples use the Python client, but translating to other clients is trivial.
Creating workspaces¶
Create a workspace called MyWorkspace:
In [4]: ws.create_workspace({'workspace': 'MyWorkspace'})
Out[4]:
[12, # workspace numerical ID
u'MyWorkspace', # workspace name
u'kbasetest', # workspace creator
u'2015-12-13T20:48:00+0000', # modification date of the workspace
0, # number of objects created in this workspace
u'a', # user's permission for the workspace
u'n', # global permissions for the workspace
u'unlocked', # whether the workspace is locked
{}] # user provided metadata
Once created, a workspace’s numerical ID is permanent and unchangeable. A locked workspace cannot be altered (other than making it world-readable).
Note that the object count is the total objects ever created in this workspace, not the currently existing objects.
Permissions¶
Permissions are coded according to the following table:
| Permission | Allows |
|---|---|
| n | No access |
| r | Read access |
| w | Write access, see permissions of other users |
| a | Admin access, set permissions of other users |
A workspace can have a description and arbitrary key-value metadata associated with it:
In [5]: ws.create_workspace({'workspace': 'MyOtherWorkspace',
...: 'description': 'Workspace for other things',
...: 'meta': {'contents': 'other things',
...: 'project_id': '42'}
...: })
Out[5]:
[13,
u'MyOtherWorkspace',
u'kbasetest',
u'2015-12-13T20:51:57+0000',
0,
u'a',
u'n',
u'unlocked',
{u'contents': u'other things', u'project_id': u'42'}]
Retrieving information about workspaces¶
The workspace description and information list can be retrieved:
In [6]: ws.get_workspace_description({'id': 13}) # retrieving by ID
Out[6]: u'Workspace for other things'
In [11]: ws.get_workspace_info({'workspace': 'MyOtherWorkspace'})
Out[11]:
[13,
u'MyOtherWorkspace',
u'kbasetest',
u'2015-12-13T20:51:57+0000',
0,
u'a',
u'n',
u'unlocked',
{u'contents': u'other things', u'project_id': u'42'}]
Listing workspaces¶
Workspaces with at least read access can be listed:
In [8]: ws.list_workspace_info({})
Out[8]:
[12,
u'MyWorkspace',
u'kbasetest',
u'2015-12-13T20:48:00+0000',
0,
u'a',
u'n',
u'unlocked',
{}],
[13,
u'MyOtherWorkspace',
u'kbasetest',
u'2015-12-13T20:51:57+0000',
0,
u'a',
u'n',
u'unlocked',
{u'contents': u'other things', u'project_id': u'42'}]]
The list can be filtered in several ways. Here it’s filtered by the user provided metadata:
In [10]: ws.list_workspace_info({'meta': {'project_id': '42'}})
Out[10]:
[[13,
u'MyOtherWorkspace',
u'kbasetest',
u'2015-12-13T20:51:57+0000',
0,
u'a',
u'n',
u'unlocked',
{u'contents': u'other things', u'project_id': u'42'}]
Sharing workspaces¶
Users with admin privileges with to a workspace can allow other users to read, write to, and administrate the workspace. These privileges apply to all objects contained in the workspace.
In [12]: ws.set_permissions({'workspace': 'MyWorkspace',
'users': ['kbasetest2'],
'new_permission': 'a'
})
In [13]: ws.set_permissions({'workspace': 'MyWorkspace',
'users': ['kbasetest8'],
'new_permission': 'r'
})
In [16]: ws.get_permissions_mass([{'id': 12},
{'workspace': 'MyOtherWorkspace'}
])
Out[16]:
[{u'kbasetest': u'a', u'kbasetest2': u'a', u'kbasetest8': u'r'},
{u'kbasetest': u'a'}]


--- layout: page title: Speaking tags: [training,live,speaking] date: 2019-11-5 thumbnail: https://walkingriver.com/assets/img/Mike-2016_devdays_session_small.jpg feature: https://walkingriver.com/assets/img/Mike-2016_devdays_session.jpg cover_image: https://walkingriver.com/assets/img/Mike-2016_devdays_session.jpg comments: false ---
In addition to being a software developer, mentor, and Pluralsight author, I am also available to do technical talks and workshops on software development for your company, user group, or technical conference. If you would like me to appear at your event, please contact me via my contact page. If you would like me to speak at your event, I have a few simple requests, depending on the type of the event.
If you would like me to speak at your company about software development, web or mobile development, then please get in touch with me to discuss the options. For corporate talks, there will be a speaker fee that we will need to agree ahead of time and travel costs, as well as accommodation costs, if your company is more than 2 hours by car from the Orlando, Florida area.
If you want me to speak in the morning, then I will require travelling the night before and staying in a hotel.
If you run a commercial conference that charges its attendees to attend, then I have some specific requirements. I do not expect to be paid to speak at your event, but I don’t expect to be out of pocket to do so. Therefore I expect my full travel and accommodation expenses to be booked and paid in advance of the event. For all conferences, I would expect a pass to the entire event, and I will make sure I am present to network and talk to attendees during the event.
You are welcome to produce video recordings of my talks and then make them available to the conference, with no additional conditions on my part. Please let me know ahead of time if you plan to record the talk.
If the conference is within Florida and more than a 2 or 3-hour drive, I will require an airline ticket and hotel. I would want to arrive the night before the event and either return the evening of the event or the next morning which will be arranged ahead of time.
If the conference is inside of the United States and is less than a 4-hour flight, then I would need to be flown in the day before the conference and return the day after the conference. I am happy to fly economy.
If the conference is inside the United States but longer than a 4-hour flight, then I would want to be flown in 2 days early to adjust to local time zones and leave the day after the conference finishes.
My talks are normally written and produced in advance of the event. Therefore I will not adapt my talks to fit with your slide templates. I am happy to put your conference logo on the slides or have a branded first slide to display before the talk starts.
If you run a community event that does not charge its attendees and you would like me to speak at your event, then please do get in touch to see what we can arrange. Because speaking at community events requires me typically to fund the travel and accommodation myself, I have to limit the amount I do, but I will try to accommodate community events as best I can as they are critical to helping people learn.
If your event has sponsorship and you are in a position to assist with travel and hotels, then this will significantly increase the chance of me being able to come to your event.
In any case, please get in touch with me, and we will see what we can arrange. Community events are crucial to local communities to help promote shared learning and networking.


This company was established by Mr. Krishna Reddy in the year 1996,who is a dynamic techno craft with rich experience in high Precision Component manufacturing.
The unit was Setup with a few Conventional machines which were later replaced by CNC turning Centre and Vertical machining Centre ,to meet the customers need and to stay in the race of fast growing field of Industries.
We have been able to meet the quality and delivery requirements of our customers over two decade ,which in turn was favored with constant orders from our customers. This has given us Confidence to upgrade our facility Constantly.
The company is located near Peenya with a build up space of around 6000Sq ft.


This is the API documentation for 'facter-1.6.17 Documentation'.
[Validate]
Generated with the Darkfish Rdoc Generator 2.


--- layout: page title: About header-img: "img/about-bg.png" ---
Business professional who is looking to make a career change and is venturing into the world of coding. Enjoying the experience so far, the trials, tribulations and minor success' that have come along the way. Stay tuned for more.


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{% for script in page.scripts %} {% include {{ script }} %} {% endfor %} {%
if jekyll.environment == "development" %}
{% else %}
{% endif %}


--- layout: post title: Some Self-Promotion date: 2014-06-26 20:28:08.000000000 -05:00 type: post published: true status: publish categories: [feed] tags: - agriculture - development - growth - productivity - technology meta: _edit_last: '8005175' _publicize_pending: '1' geo_public: '0' author: login: dvollrath email<EMAIL_ADDRESS>display_name: dvollrath first_name: '' last_name: '' ---
The CSAE blog has put up a research summary about my paper with Markus Eberhardt, on agricultural technology and agricultural productivity (which are different things).


Index
Dynamic HTML TABLE Tag
An example of an HTML Table populated by JavaScript
This table has information
Name
Amount
Alan
12
Bob
23
Aleister
33.3
Douglas
42
Table Data
Caption:
Id:
Refresh Table


Hello Node from gcloud platforms with jenkins-x
Jenkins
X
Adding Login page from gke
Application Version: v1.2


- Canvas - Class in eu.zidek.augustin.minuscule
-
A canvas which supports easy drawing of elementary geometric objects.
- Canvas(int, int) - Constructor for class eu.zidek.augustin.minuscule.Canvas
-
Creates a new Canvas with the given width and weight.
- CanvasPopUpMenu - Class in eu.zidek.augustin.minuscule
-
Pop-up menu which shows on a right click on the canvas.
- CanvasPopUpMenu(Canvas, MinusculeWindow) - Constructor for class eu.zidek.augustin.minuscule.CanvasPopUpMenu
-
Creates a new pop up menu
- clear() - Method in class eu.zidek.augustin.minuscule.GeometricObjectQueue
-
Clears the queue, i.e.
- clearAll() - Method in class eu.zidek.augustin.minuscule.Canvas
-
Clears the canvas: deletes permanently all objects, labels and the grid
and repaints the canvas.
- clearAllButGrid() - Method in class eu.zidek.augustin.minuscule.Canvas
-
Clears the canvas, but leaves the grid in place: deletes permanently all
objects, labels and repaints the canvas.
- color(Color) - Method in class eu.zidek.augustin.minuscule.MGeometricObject
-
Sets the object's color to the given color.
- color(Color) - Method in class eu.zidek.augustin.minuscule.MLabel
-
- color(Color) - Method in class eu.zidek.augustin.minuscule.MLine
-
- color(Color) - Method in class eu.zidek.augustin.minuscule.MPoint
-
- color(Color) - Method in class eu.zidek.augustin.minuscule.MPolygon
-
- color(Color) - Method in class eu.zidek.augustin.minuscule.MRectangle
-
- color(Color) - Method in class eu.zidek.augustin.minuscule.MShape
-
- compareTo(MGeometricObject) - Method in class eu.zidek.augustin.minuscule.MGeometricObject
-
- copy(MLabel) - Method in class eu.zidek.augustin.minuscule.MLabel
-
A copy constructor for MLabel.


YourBetterAssistant
Toggle navigation
Commands
Price
We don't Currently offer any subscriptions
yet
but we will eventually


I am a student of systems engineering and I do a double program with industrial engineering. In addition, I am 22 years old, I graduated from the Gimnasio Británico school in 2015 and I speak Spanish, English and French.
Online music application, in which you can consult different songs according to your musical preference. It should be noted that recognition was obtained for this project.
Taking into account the problem when analyzing and monitoring a large number of servers, an online application was made that shows in real time the behavior of each of the servers of a company in addition to generating alerts in case of failures or future failures.
Programming Languages & Tools
In addition to the development of web pages, I am interested in the issues derived from Big Data, such as data mining and related to industrial engineering, how to improve processes obtaining as a basis the results obtained from an analysis in data mining.
Likewise, I would like in the future after finishing my career to be able to expand my knowledge through new experiences in different countries, to understand how in each country the needs are different and there are different solutions to similar problems.


CMPXCHG16B Instruction
The compare-and-exchange 16 bytes (128 bits) instruction is supported (implicitly locked and atomic).


{% extends 'layouts/base.html' %} {% block content %}
This project aims to provide an example of an API that follows some of the Best Practices for designing a REST API.
This page lists out some of the Best Practices and Guidelines that should be followed when designing a REST API to make it easy for the developers to use and implement.
Upgrading your API with a breaking change may break the existing products/services using your API. Versioning ensures that your users can still access the older version of your API for some time while they transition to the newer version.
Example - http://flrestdev.vrtx.com/api/v1/buildings
HTTP methods define the types of actions that can be performed on a resource.
GET /buildings
will get a list of all the buildings.
GET /buildings/1
will get the building with ID 1.POST /buildings
can be used to insert one or more buildings into the database. PUT /buildings/1
will update the building with ID 1 or create it if it doesn't exist.PATCH /buildings/1
will update the building with ID 1.DELETE /buildings/1
can be used to delete the building with ID 1.Endpoints should include nouns, not verbs or actions.
Avoid
Use
Only Plural nouns should be used for consistency.
But how do you tell the endpoint what action to perform?
Solution - Use HTTP verbs (GET, POST, PUT, PATCH, DELETE) to perform CRUD actions.
Examples -
GET /buildings
will get a list of all the buildings.GET /buildings/1
will get the building with ID 1.POST /buildings
can be used to insert one or more buildings into the database. Do not use /building
to post a single building. /buildings
should be able to handle one or more buildings.DELETE /buildings/1
will delete the building with ID 1.PUT/PATCH /buildings/1
will update the building with ID 1.HTTP defines a set of Status Codes that must be included in your API responses to tell the developer that status of his/her request. Here are some of the commonly used Status Codes -
200 OK
- GET, PUT, PATCH or DELETE was successful.201 Created
- POST request was successful.204 No Content
- DELETE was successful.400 Bad Request
- There were inavlid parameters in the request. Developer must fix them.401 Unauthorized
- Invalid Credentials were provided.404 Not Found
- URL does not exist.405 Method Not Allowed
- Requested method is not allowed on the resource.500 Internal Server Error
- Problem with the server.Docs should be easily accessible and readable. Should provide examples of requests and responses. Should always be upto date. Your docs should follow the Open API standards. We have used two types of docs in this example, both of which depend on the Open API spec.
Your API should validate the requests being sent to the server and provide appropriate responses. POST, PUT and PATCH requests should provide field specific errors to help the developer locate and fix the issue.
Your API should always use SSL for all endpoints to ensure the safety of the data.


Constructing Computer Vision (CV) systems can be complicated and varied based on the objective of the system. This site will help to guide you through the development of a CV system that runs on the Edge using AWS IoT Greengrass (Greengrass). Greengrass v2 is an open source system to orchestrate and manage components running on Edge computing equipment, but under cloud control and with a wide variety of options to integrate with other local and cloud systems and services.
Part workshop, part Cookbook, this site can be used to build sample applications and as a reference for composing sample components into CV applications. Numerous hardware platforms are supported by Greengrass, Docker, GluonCV, Python, and many of the other building blocks that will be presented here. While there are some described “Combinations” of platform and components to accomplish specific goals, making your own combination of these blocks as best fits your application is possible.
This is not an introductory workshop and will not repeat information that is readily available elsewhere, like how to set up an EC2 instance or revise a Greengrass deployment. Rather, the focus of this workshop is on overall system design and composition of components to deliver a CV application. Consult the Spells section for activities in bold italics when needed. This helps keep the text focused on the logic and concept of the activity and keeps common actions collected in one spot for ready reference.
Here’s how to get started!
The services this site explores inlcude:
These Labs are hands-on activities to explore using AWS Services for Computer Vision at the Edge. The activities use a mix of AWS Command Line Interface (CLI) and the web based AWS Management Console.


A Tool Bundle for AI Fairness in Practice
Ruf B., Detyniecki M.2022
ACM Conference on Human Factors in Computing Systems (CHI) 2022
Fairness Compass: Towards the Right Kind of Fairness
[English]
[German]
[Infographic]
[Tool]
[Code]
Ruf B., Detyniecki M.2021
ECML/PKDD 2021 Industry Track
Explaining How Your AI System is Fair
Ruf B., Detyniecki M.2021
ACM CHI 2021 Workshop on Operationalizing Human-Centered Perspectives in Explainable AI
Implementing Fair Regression In The Real World
Ruf B., Detyniecki M.2021
Preprint Arxiv
Adversarial Learning for Counterfactual Fairness
Grari V., Lamprier S., Detyniecki M.2020
Preprint Arxiv
Learning Unbiased Representations via Rényi Minimization
Grari V., El Hajouji O., Lamprier S., Detyniecki M.2020
Preprint Arxiv
Achieving Fairness with Decision Trees: An Adversarial Approach
Grari V., Ruf B., Lamprier S., Detyniecki M.2020
Journal Data Science and Engineering
Active Fairness Instead of Unawareness
Ruf B., Detyniecki M.2020
Position paper on the use of personal attributes in AI.
Getting Fairness Right: Towards a Toolbox for Practitioners
Ruf B., Boutharouite C., Detyniecki M.2020
Workshop on Fair and Responsible AI at CHI 2020
Fair Adversarial Gradient Tree Boosting
Grari V., Ruf B., Lamprier S., Detyniecki M.2019
IEEE International Conference on Data Mining (ICDM)
Fairness-Aware Neural Réyni Minimization for Continuous Features
Grari V., Ruf B., Lamprier S., Detyniecki M.2019
This research article presents a method to ensure some independence level between the outputs of regression models and any given continuous sensitive variables.
Understanding and Mitigating Bias
Ruf B., Grari V., Detyniecki M.2019
Booklet explaining the most fundamental sources of unwanted bias in machine learning algorithms and possible mitigation strategies.


To convert images or layers to draggable DHTML items, simply pass their names/IDs to a function call 'SET_DHTML()'.


The front end of a website is the part that users interact with. Everything that you see when you're ...
The backend of a web application is an enabler for a frontend experience. Backend code is run on the server, ...
Blog PostThe backend frameworks consist of languages and tools used in server-side programming in a web application. Whereas the frontend frameworks...
Blog PostA database is a collection of information that is organized so that it can be easily accessed, managed and updated. Data is organized into rows, col...
Blog PostThis section features some of my web apps designed using HTML5, CSS3, JavaScript, Bootstrap 4 and some jQuery. They are intended to show design & functionality. Click and try them, the code is on Github and it is free to use and/or modify.
This section features four programming projects where some moderate to intensive programming was needed using the object oriented paradigm. I chose these because they required some thinking before diving into coding. I am aware that I could think deffirently now as I got exposure to asymptotic analysis of programs (Famous big O, big Θ & big Ω); but overall it's been a rewarding experience for me while thinking about how the classes should be designed to interact with each other so that the problems can be solved and give back the desired results.
Encrypting and decrypting text files using a software-simulated Enigma Machine without the plugboard (A WWII German Encryption Machine). The encryption as well as decryption goes through a process of 7 stages simulating a series of 6 rotors and a reflector each with the 26 letters of the alphabet. A particular setting of rotor positions determines how encrypting or decrypting is carried out.
The System is designed following a use-case oriented architecture and implemented following an object-oriented approach (using Java) where different actors (roles) (passenger, conductor, cashier.) trigger different scenarios (actions and reactions). A typical scenario would be when a traveler (The passenger: use-case) requests a ticket, the system (The cashier: use-case) checks for availability with regards to time, departure location, destination location, and seat availability. If a ticket is available, a reservation is made. At the time of boarding, the traveler presents the ticket and the system (The conductor: use-case) verifies its validity. If the ticket is valid, the traveler boards the train to destination. When conditions are not satisfied, handlers to those events are also implemented. The system is backed with a MySQL database for CRUD operations.
An Android application that allows a user to upload or take a picture of a human face. After this initial phase, the file is sent to a Face & Emotions detection API (Used the Microsoft Azure Platform). Once processing is complete by the API, results will be sent back to the user for display (in JSON). Among the results are: (1) clear detection of the face (if it belongs to a human and it is visible) by placing a colored rectangle around it, (2) Emotions detected from the face such as happiness, anger, fear, neutrality, ...etc.
This project solves the Minimum Spanning Tree (MST) problem using Kruskal’s Algorithm with path compression. To achieve our goal, data for weighted graphs with (n) vertices and (m) edges are given in text files. An MST, if it exists, is a subgraph containing (n – 1) edges such that when their weights are added together, they give the minimum possible cost needed to visit all vertices exactly once without creating any cycles. An MST is not possible to compute if the graph is not connected as the algorithm runs out of edges to consider before satisfying the above condition. The implementation of Kruskal’s algorithm uses a disjoint-set data structure implemented using an array of integers called “sets”. In this data structure at start, the cell at index “i” is the single representative (or label) of the element “i”. Thus, we make (n) disjoint subsets where one of them contains one single vertex. As the subsets merge together, if the index “i” is not the representative of its subset, we go through the subsets until we find its representative. Once this operation is achieved, we proceed to path. The compression of the path that led to our target can be achieved by introducing a caching mechanism into the find operation where all elements in the path to the representative will, after that, point to the target label. This way it speeds up the subsequent find operations and speeds up the overall running time of Kruskal’s algorithm. At the end, if an MST is computed, all edges that make it will be displayed along with their total weight.
This section exposes two practical exercises using the functional programming paradigm. The first is Hoffman Coding using Lisp and the second is solving CNFs with the ML programming language.
Hoffman Coding in LISP
In this project, the Huffman coding algorithm, which is a divide and conquer approach, is used to encode a message into binary code and decode the binary back to the original message. In order to achieve this, a Huffman Tree is constructed using the frequency list of the content of the message. Generating the frequency list requires counting the occurrence of each symbol (or its weight) in the original message and pair each count with its corresponding symbol. After this first phase, every pair is put in a list and the entire list in a list itself; then sort the whole thing in increasing order of weight. This way, we now have a list of Huffman sub-trees (sub-htrees). The objective is to compress data using variable length coding rather than fixed length coding all in a lossless manner
Solving CNFs in ML
This project intended to compute the conjunctive normal form "cnf" of a sentential logic. It implements a datatype called "sentence" and logical connectives. In order to get the cnf of a sentence, function in the program the following: remove arrows, distribute negeation, distribute disjunction in conjunction, and finally print the results out.


This class represents Spaces
in HDF5. These are mostly useful to define the
dimensions of a dataset as well as the maximum dimensions to which it can grow. By default, the
maximum dimension is equal to the initial dimension. If you want the array to be able to grow arbitrarily
large in one dimension, set the maximum dimension for this index to Inf
. See the examples below
for code how to do this.
Object of class H5S
.
new(type = c("simple", "scalar", "null"), dims = NULL,
maxdims = dims, decode_buf = NULL, id = NULL)
Create a new HDF5-space. This can be done by either specifying a space with appropriate dimensions or by decoding a character string that represents an encoded spaceParameters
Either a simple
space, for which dims
and maxdims
have to be given
or a scalar
or null
space. See the HDF5 user guide on spaces to explain the differences.
The dimension of the space in case it is of type simple
The maximal dimensions of the space
The character string that holds the encoded representation of a space
An existing HDF5 id; internal use only
copy()
This function implements the HDF5-API function H5Scopy. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_COPY for details.
encode()
This function implements the HDF5-API function H5Sencode. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_ENCODE for details.
is_simple()
This function implements the HDF5-API function H5Sis_simple. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_IS_SIMPLE for details.
get_simple_extent_ndims()
This function implements the HDF5-API function H5Sget_simple_extent_ndims. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_GET_SIMPLE_EXTENT_NDIMS for details.
offset_simple(offset)
This function implements the HDF5-API function H5Soffset_simple. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_OFFSET_SIMPLE for details.
get_simple_extent_dims()
This function implements the HDF5-API function H5Sget_simple_extent_dims. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_GET_SIMPLE_EXTENT_DIMS for details.
get_simple_extent_npoints()
This function implements the HDF5-API function H5Sget_simple_extent_npoints. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_GET_SIMPLE_EXTENT_NPOINTS for details.
get_simple_extent_type()
This function implements the HDF5-API function H5Sget_simple_extent_type. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_GET_SIMPLE_EXTENT_TYPE for details.
extent_copy(h5s_source)
This function implements the HDF5-API function H5Sextent_copy. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_EXTENT_COPY for details.
extent_equal(h5s_cmp)
This function implements the HDF5-API function H5Sextent_equal. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_EXTENT_EQUAL for details.
set_extent_simple(dims, maxdims)
This function implements the HDF5-API function H5Sset_extent_simple. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_SET_EXTENT_SIMPLE for details.
set_extent_none()
This function implements the HDF5-API function H5Sset_extent_none. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_SET_EXTENT_NONE for details.
get_select_type()
This function implements the HDF5-API function H5Sget_select_type. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_GET_SELECT_TYPE for details.
get_select_npoints()
This function implements the HDF5-API function H5Sget_select_npoints. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_GET_SELECT_NPOINTS for details.
get_select_hyper_nblocks()
This function implements the HDF5-API function H5Sget_select_hyper_nblocks. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_GET_SELECT_HYPER_NBLOCKS for details.
get_select_hyper_blocklist(startblock = 0,
numblocks = (self$get_select_hyper_nblocks() - startblock))
This function implements the HDF5-API function H5Sget_select_hyper_blocklist. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_GET_SELECT_HYPER_BLOCKLIST for details.
get_select_elem_npoints()
This function implements the HDF5-API function H5Sget_select_elem_npoints. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_GET_SELECT_ELEM_NPOINTS for details.
get_select_elem_pointlist(startpoint = 0,
numpoints = (self$get_select_elem_npoints() - startpoint))
This function implements the HDF5-API function H5Sget_select_elem_pointlist. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_GET_SELECT_ELEM_POINTLIST for details.
get_select_bounds()
This function implements the HDF5-API function H5Sget_select_bounds. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_GET_SELECT_BOUNDS for details.
select_all()
This function implements the HDF5-API function H5Sselect_all. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_SELECT_ALL for details.
select_none()
This function implements the HDF5-API function H5Sselect_none. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_SELECT_NONE for details.
select_valid()
This function implements the HDF5-API function H5Sselect_valid. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_SELECT_VALID for details.
select_elements(coord, op = h5const$H5S_SELECT_SET, byrow = TRUE)
This function implements the HDF5-API function H5Sselect_elements. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_SELECT_ELEMENTS for details.
select_hyperslab(start, count, stride = NULL, block = NULL,
op = h5const$H5S_SELECT_SET)
This function implements the HDF5-API function H5Sselect_hyperslab. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_SELECT_HYPERSLAB for details.
subset(args, op = h5const$H5S_SELECT_SET, envir = parent.frame())
Subsetting the space. This is mainly intended as a helper function for the '[' function, but can also be used on its own.Parameters
The indices for each dimension to subset given as a list. This makes this easier to use as a programmatic API.
For interactive use we recommend the use of the [
operator.
The operator to use. Same as for the other HDF5 space selection functions. One of the elements shown in
h5const$H5S_seloper_t
The environment in which to evaluate args
print(...)
Prints information for the groupParameters
ignored
dims()
Get the dimensions of the space. Return NULL if the space is not simple (i.e. NULL-space) or a length-0 integer if it is a scalar
maxdims()
Get the maximal dimensions of the space.Return NULL if the space is not simple (i.e. NULL-space) or a length-0 integer if it is a scalar
rank()
This function implements the HDF5-API function H5Sget_simple_extent_ndims. Please see the documentation at https://portal.hdfgroup.org/display/HDF5/H5S_GET_SIMPLE_EXTENT_NDIMS for details.
#> Class: H5S #> Type: Simple #> Dims: 5 x 2 #> Maxdims: 5 x 2#> Class: H5S #> Type: Simple #> Dims: 5 x 2 #> Maxdims: Inf x 2#> Class: H5S #> Type: Simple #> Dims: 10 x 2 #> Maxdims: Inf x 2# now select a subset of points # argument evaluation has a heuristic; here it chooses point selection h5s_variable[c(1, 3, 8), 1]#> Class: H5S #> Type: Simple #> Dims: 10 x 2 #> Maxdims: Inf x 2h5s_variable$get_select_type()#> [1] H5S_SEL_POINTS #> 6 Levels: H5S_SEL_ERROR H5S_SEL_NONE H5S_SEL_POINTS ... H5S_SEL_N #> 6 Values: -1 0 1 ... 4h5s_variable$get_select_elem_pointlist()#> [,1] [,2] #> [1,] 1 1 #> [2,] 3 1 #> [3,] 8 1# and a hyperslab (chosen by the argument heuristic) h5s_variable[2:7, 1:2]#> Class: H5S #> Type: Simple #> Dims: 10 x 2 #> Maxdims: Inf x 2h5s_variable$get_select_type()#> [1] H5S_SEL_HYPERSLABS #> 6 Levels: H5S_SEL_ERROR H5S_SEL_NONE H5S_SEL_POINTS ... H5S_SEL_N #> 6 Values: -1 0 1 ... 4h5s_variable$get_select_hyper_blocklist()#> [,1] [,2] #> block_1_start 2 1 #> block_1_end 7 2


Los Angeles, CA
Looks great on any screen size!

Tiny kitten shorts
Get your neko photos fast.


May 24, 2015
Initially, my adjustment from Java / JavaScript to Ruby was a little rocky. With JavaScript, you have to be careful about semicolons, curly braces, and placement of commas in respect to object properties. But Ruby is far more forgiving.After a while, I didn't miss having to use semicolons or curly braces. I'm really loving Ruby. It's beautiful, clean, and easy to read.
I will quickly go over one of the differences between Ruby and JavaScript in terms of: classes! (we can do syntax later)
In Ruby, the syntax and format for creating a class is really straightforward. Here's a sample class:
class Employee
attr_accessor :firstName, :lastName, :title
def initialize(firstName, lastName, title)
@firstName = firstName
@lastName = lastName
@title = title
end
def display
puts "Employee is " + firstName + " " + lastName
end
end
christine = Employee.new("Christine","Schatz",
"software engineer")
christine.display # Employee is Christine Schatz
In JavaScript, classes are trickier. You will never see the word "class." Rather, you'll see what look like functions, the first here of which is called a "constructor.":
function Employee(firstName, lastName, title) {
this.firstName = firstName;
this.lastName = lastName;
this.title = title;
}
Employee.prototype.fullName = function() {
return this.firstName + " " + this.lastName;
}
var christine = new Employee("Christine", "Schatz",
"software engineer");
christine.fullName(); // "Christine Schatz"
That's all for now! Thanks for reading :-)


Trying out Fitnesse for acceptance testing. Hard to get away from unit testing perspective in how to write the fixture tables.
7/29/2009, 11:39:15 AM
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link--- layout: tweet ---
Trying out Fitnesse for acceptance testing. Hard to get away from unit testing perspective in how to write the fixture tables.
7/29/2009, 11:39:15 AM
Favs: 0
Retweets: 0
link


Click a node's employee count to expand or collapse its "child" node(s), ie the employee's immediate subordinates. A node without an employee count has no "child" employees.
Click a node to "drill into" the node, ie that clicked node becomes the new "root" (top level) node. The "breadcrumb" updates to display his/her manager(s).
Breadcrumb names are links that, like clicking a node, drill into the clicked name's node.


My name is Robert Whitney. I've recently graduated from the Master of Engineering Program at Cornell University in the Fall of 2020, a full semester early. I've always been fascinated by robots, airplanes, rockets, drones, anything that moves fast!
This portfolio showcases a few of the projects I worked on, either for my education or for my own enjoyment. I continue to dedicate time to these projects and update this website in my spare time.
I am looking for a position to apply what skills I mastered and continue developing new skills in robotics, controls, dynamics, and programming. I would be thrilled to work with ...
The best way to contact me is to message me on LinkedIn or send me an email at<EMAIL_ADDRESS>A competition quadcopter. Go fast, don't crash.
A course on systems level design and implementation of dynamic autonomous robots
My Senior capstone extended into hardware development


Demo not fully styled, shows a demo game in progress.
If BALL IS NOT MOVING then go back one screen and pick demo again.
Current demo setup is to move the ball 20x faster than normal
Ball is moving and its coordinates are constantly being computed. In addition, the distance between the players
is constantly being calculated. For this demo, player positions are pulled from a pre-programed list.
To really see a neat demo, click on the maximize button on the map, then select the satellite image to watch
the ball sail over houses and landmarks
×
How it works:
Player positions are moved whenever player #1 hits enough preset hits and is ready to hit again.
Player #2 moves to player #1 position and player #2 is picked from the next one in a list of pre-programed addresses.
A separate computer on the internet, called the pong physics engine is constantly running and looking for a game to simulate.
Currently, the physics engine can compute the trajectories for up to 50 games at 4x per second. When a signal is sent to the
engine, it solves basic kinematic equations for acceleration, velocity, and distance.
For every sample period the player's coordinates and distances are calculated. After that
the players latitude, longitude, and azimuth are calculated, using navigation equations.
From there the balls coordinates are calculated by using kinematic equations.
×
What this demonstrates:
1. Running an "engine" to do simultaneous calculations
2. Solving navigational and kinematic calculation efficiently
3. Using an API to convert an address into a geo location (latitude and longitude)
4. Using Google Maps to display data
5. Update and move data points on a map real-time
6. Rescale the map to contain all points if a player moves
7. Using built in device sensors to detect a swing (game mode)
8. Writing to simultaneous databases (real-time and sql)


The Devops Introduction I Wish I Had
Buzzwords are everywhere. You may have noticed that I am not a big fan of them. They are used everywhere (sometimes in a wrong fashion) and because of that, most people afraid to ask the 101-questions as they don’t want to sound ignorant.
Some years ago, my back-then-manager asked me if I wanted to do some devops work as part of my software engineer job. Of course, I was young and afraid (for the above reasons) to ask so I just said “yeah, let’s give it a try.
Thank God, I am still alive, torturing people with my writings. So now I want to give you a nice and round overview of the terms I encountered in my initial steps and wish I knew back then, plus some more that were not invented but it is good to know them now.
Lets start
(Credits to William Stitt, unsplash)
Devops
The devops discipline was created to bridge the gap between the developers and the operation guys (eg IT, system engineers, DBAs etc). The main vision is to (mostly) make the transition from the development environments to the testing/production environments flawless, quick, automated and completely transparent.
Before that, the deployments were causing a constant pillow fight and nerf-shooting wars (sometimes even keyboard throwing) between the two “tribes” and the deployments were slow, painful and required lots of working hours. You can verify that easily if you are aware of a software company that doesn’t employ such practices.
The movement was influenced by the increase in popularity of Agile methodologies, as you can imagine, where fast deployments are highly encouraged and are the norm when talking about serious software companies.
IaaS
Infrastructure as a service. You are given the ability to launch a VM with an OS of your choice (well, the cloud provider has to support it, but most known Windows and Linux flavors are there), specs of your choice (RAM, persistent storage, number of CPUs etc).
As with all stripped-down VMs, you have to set up everything yourself, with the tradeoff of being more in control.
The most known examples are EC2 from AWS, Google compute engine from Google Cloud.
PaaS
Platform as a Service. You can think of it as an abstraction of IaaS.
Everything apart from your business logic and the database part is a black box to you. You might know details about the infrastructure but you have very little control over it.
For example, you might be able to change the versions of the software you use, but this will happen:
- From the vendor’s UI
- The version modification will happen in the range the vendor supports. If the vendor doesn’t support python 3.7, you can’t have it and if you try and update manually, it most probably is painful and there is a strong chance you will screw everything. At least, that’s my experience.
The most known examples are ElasticBeanStalk from AWS, Google AppEngine from Google Cloud.
Note: there is a combination of the *aaS components in real-world cases. PaaS and IaaS working together, are especially common. This is called hybrid cloud.
Saas
Software as a Service. In that case, you want to access a piece of software (cloud-based) and you pay according to the use you do (if there are no free plans).
You have no control over the software, apart from what the UI and a potential API allows. The most known examples are Netflix, Dropbox and most of the Google services.
You can see a visual comparision of IaaS, Saas and PaaS in this article.
Provisioning
Provisioning, in the devops context, means to (automatically) bootstrap the infrastructure.
So if someone wants to provision a test environment, then he probably has to set up a few VMs (not random VMs, a specific type of VM or a certain image that is used as a template) and then set up the software required, setup any web servers etc. Sounds boring, huh?
It totally is, that’s why people are using provisioning tools that do the job for them automatically (so that they can browse Reddit and 9gag with no guilt while waiting).
Two of the most beknown tools for provisioning are Ansible and Terraform. I won’t go into details for now, as this will require a 5-times longer article, but I will show an example in Terraform to show you how straightforward it is.
resource "aws_instance" "example" {
ami = "ami-b374d5a5"
instance_type = "t2.micro"
provisioner "local-exec" {
command = "echo ${aws_instance.example.public_ip} > ip_address.txt"
}
}
A short explanation might be required for the example above; ami stands from Amazon Image and is pretty much a VM template.
t2.micro refers to the computational features of a machine (CPU, RAM etc). If you haven’t seen this before and you are curious, you can check out this page.
Pretty much it setups a t2.micro instance with the predefined ami and when up runs the echo command, in the local-exec section.
Ansible plays at a lower level, where you define a setup of commands, called playbook, with more detailed commands. There are great articles around, like this one, I would suggest you read it.
Dockerization
Dockerazition means that you need to make some certain steps to make your application work with docker.
Docker, in a nutshell, is a means of lightweight virtualization (a bit simplified, you could read more here).
You can define a docker image, by using the so-called DockerFile, which is pretty much a set of commands that build a Docker image step by step.
Here is one of the simplest docker files you could find, along with explanations. More images to start from can be found in docker hub.
Why is all this fuss about docker though? What does docker offer?
There are lots of benefits in using docker but for me the most important use cases are:
-
Portable environments. I can use the exact same environment for development, for production, for staging environments, for reproducing a production issue, for making a demo to the client…and the list goes on. No more “works on my machine” excuses.
-
Setup the environment in a couple of commands. This fits greatly with provisioning as can be seen in this article.
Serverless
Contrary to what the name implies, we still have servers where the backend logic runs on. What is really happening is:
When you want to execute a certain piece of code (called a function, thus this computation model sometimes is also called function as a service - FaaS) the cloud provider allocates the necessary resources (in a dynamic way) to execute it.
After the end of the execution, it releases those resources.
The functions run in various occasional triggers or run periodically in a cron-like way.
Ideally, the functions should be pure, which means they only rely on their arguments to compute a result and not on any external state (eg database), though there is no problem using an external database server or so.
The main advantages are that you only care about your business logic and that you can scale your functions in a glimpse of an eye.
If you want more insights on that, it might be specific to AWS but this article is a great read.
A pretty good video for a quick intro would be this one from Traversy Media.
CI/CD
Continuous integration and continuous delivery. The story is: Various devs work against an upcoming release or a set of parallel in-progress features. When the code is committed (usually to the main branch, though this is configurable), a set of operations run automatically and the goal is to have all the operations succeed.
Such operations would be to make sure the code compiles, to run the unit tests successfully, to ensure the test coverage is above an acceptable threshold, the docker image of the product was generated without errors, the image was deployed to a cloud environment successfully etc.
I think you can understand how important is to have continuous feedback and perform all the necessary steps without having to think about them, and worse, having to rely on your willpower to do it. Do you know many devs that like testing? I don’t :D
Conclusion
Thank you for reading this article. If you are now entering devops, it is a fascinating field. I hope this article made the ultra-basic terminology a little bit clearer. As always, feel free to comment on any feedback you may have.


The Chicago breakwater system extends from just north of Navy Pier to where you are now. Its history is rooted in protecting one of the region’s greatest assets—shipping on the Chicago River. In the mid-1800s, rock was placed near the river mouth to shield against heavy waves and prevent sand from clogging the entrance to the river. Over more than a century, these structures helped the city become one of the busiest commercial centers in the world. Over time, the breakwater system was expanded to protect the surrounding shoreline from heavy waves that cause flooding and erosion, a function it continues to serve. Today, hundreds of recreational boaters also take advantage of the calm water near downtown to dock their boats and safely move between the river and the lake.
The breakwater is not without its downsides. The structures require constant, and often costly, maintenance. Over the decades, portions of the breakwater have been entirely rebuilt after the base of the structure collapsed. Also, by their very design, breakwaters change the natural movement of water and sediment. Sand building up along the man-made structure helps keep rivers and harbors open. But this prevents sand from replenishing beaches down shore.


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Start Survey


1.What is JavaScript?
2.Which of the following is not a JavaScript data type?
3.What will the following code return: Boolean(26 > 48)
4.Which sign is used to mean "either of them may be true"?
5.Which of these functions parses a string and returns an integer?


{% extends "base.html" %} {% block title %} Reserved judgments {{block.super}} {% endblock %} {% block css-override %} {% endblock %} {% block content %}
Please use this form to tell us that
We currently don't have capacity to handle magistrate courts. The sole purpose of this is to record reserved judgments. This is not a complaint form about any other court problems.


{$comment this is a master template not intended to be used directly, but extended and then used. /$} {$define "#master" }


Recall that the highlighting in the experiment was automatically generated.
Again, please rate the following statements, where "the system" refers to any similar system that automatically generates text highlighting to aid problem solving.
Your ratings may or may not have changed since last time.
| Disagree | Agree | ||||||
|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | |
| The system is deceptive. | |||||||
| The system behaves in an underhanded manner. | |||||||
| I am suspicious of the system’s intent, action, or outputs. | |||||||
| I am wary of the system. | |||||||
| The system’s actions will have a harmful or injurious outcome. | |||||||
| I am confident in the system. | |||||||
| The system provides security. | |||||||
| The system has integrity. | |||||||
| The system is dependable. | |||||||
| The system is reliable. | |||||||
| I can trust the system. | |||||||
| I am familiar with the system. |


Description
General
Kwik EFIS is a Glass Cockpit application designed to work on most Android devices equipped with a GPS, gyroscope, accelerometer and a CPU with reasonable performance.
Initial test flights with Kwik EFIS has been encouraging. Results are better on the Nexus 7 tablet then the Galaxy S2 phone but that is to be expected since the sensors on the various Android devices vary greatly in quality and performance.
Fusing for GPS inputs now take a greater precedence over the gyros. This helps with stabilizing the roll filter a little better.
The slip/roll coupling uses a low pass filter on all the sensors. This helps with some of the inferior gyroscrope and accelerometer sensors on some of the cheaper Android devices.
Kwik EFIS has a fully functional flight director built in. It uses the standard V-Bar symbology common to modern flight directors. The target waypoint and altitude is set on-screen by means of the spinner controls on the right top and bottom of the screen.
There is also a "Demo Mode" available in the application. It is fairly rudimentary and basically works like a crude flight simulator. The heading and altitude can be changed by pitching and banking the device. The speed runs up and down automatically based on the pitch.


Damn You, Stereotype Threat
July 31.2014
In 1995, Steele and Aronson published a study that formally introduced the stereotype threat. The researchers gave a difficult portion of the GRE to African-American and European-American participants. They attempted to indirectly evoke the cognitive availability of a stereotype in the participants by describing one of the tests as "diagnostic of intellectual ability". They found that African-Americans scored lower on this test. They attributed this underperformance to the risk that an individual felt that doing so would confirm as self-characteristic the negative stereotype about one's group. The negative stereotype in this study presumably being that African-Americans perform more poorly than European-Americans on standardized tests.
Hundreds of studies exhibit the effects of stereotype threat on performance, and it transcends race to gender, age and so on. The key that makes this threat damaging appears to be in the awareness of the stereotype. An individual commented on The Atlantic article entitled "Thin Ice: Stereotype Threat and Black College Students". He claims to be an African who recently came to America, and so had not been exposed to the negative stereotypes regarding intelligence that are directed at African-Americans. As such, he had been able to "disregard [his] group identity as a factor in most roles". He had no conception of how his "blackness" affected him academically, so it did not affect him.
The preceding anecdote offers a helpful point when considering how to attenuate the stereotype threat. While awareness of stereotypes weighs on an individual in certain situations, perhaps awareness of the concept of the stereotype threat is enough to mitigate it to some degree. In a 100-level psychology or sociology class, you might learn about a number of biases or predispositions that seem to come pre-loaded in the human brain. Some serve as helpful heuristics, but many can be harmful to making the best judgments (i.e. stereotyping). I find that learning about and becoming aware that these notions can sneak into cognition is paramount to optimum critical thinking, from big-time resolutions down to every-day decisions.
As individuals, we will have a tough time directly combating prevalent stereotypes, but we do have some control over how these stereotypes affect our performance.  When we find ourselves in those situations, we are prepared for our fears because they are familiar, and we can gain confidence in our abilities in spite of what we perceive the stereotype to dictate of our aptitude. The stereotype may be alive and well, but the threat we feel that apprehends our flair is but within ourselves.


- Read Reviews for the Broadway Revival of Miss Saigon
- Upcoming Auditions for School of Rock, Godspell, The Odd Couple, and On Your Feet!
- The Color Purple Performance on The Today Show, Led by Cynthia Erivo, Receives Daytime Emmy Nomination
- See Phillipa Soo Return to Broadway in Amélie, A New Musical
- MTC Announces New Broadway and Off-Broadway Shows
Men's Hamilton Tee
$19.99
Women's Wicked Tee
$24.99
Unisex Newsies Tee
$22.99
Unisex Lion King Tee
$29.99


#include <testing.h>
◆ Testing()
Creates a Testing object with default attributes.
◆ check_switch_time()
| bool Testing::check_switch_time |
( |
const double |
time | ) |
|
Check if time to change values and change them if yes.
- Parameters
-
| time | - current simulation time |
- Returns
- True if values were changed
◆ get_exp_tested_prob()
| double Testing::get_exp_tested_prob |
( |
| ) |
const |
|
inline |
Probability exposed gets tested.
◆ get_prob_flu_tested()
| double Testing::get_prob_flu_tested |
( |
| ) |
const |
|
inline |
Probability flu (non-covid symptomatic) gets tested.
◆ get_sy_tested_prob()
| double Testing::get_sy_tested_prob |
( |
| ) |
const |
|
inline |
Probability symptomatic gets tested.
◆ initialize_testing()
| void Testing::initialize_testing |
( |
const double |
tst, |
|
|
const double |
neg, |
|
|
const double |
fneg, |
|
|
const double |
fpos, |
|
|
const double |
sy_ini, |
|
|
const double |
exp_ini |
|
) |
| |
Sets initial testing attributes.
- Parameters
-
| tst | - time when testing starts |
| neg | - fraction of negative tests |
| fneg | - fraction of false negative tests |
| fpos | - fraction of false positive tests |
| sy_ini | - initial fraction of symptomatic agents to test |
| exp_ini | - initial fraction of exposed agents to test |
◆ set_time_varying()
| void Testing::set_time_varying |
( |
const std::vector< std::vector< double >> |
time_vec | ) |
|
Sets the vector of times vs. testing fractions.
◆ started()
| bool Testing::started |
( |
const double |
time | ) |
const |
|
inline |
True if period of testing has started.
The documentation for this class was generated from the following files:


This application uses an internet connection to download weather data based on your location, no information is saved, stored or used outside of this application.
This application will not function without the location service turned on.
By installing and using this app you agree to this privacy policy!


Coding Comics: Recursion
Table of Contents
What Is This?
This is a re-working of the Coding Strip Recursion example. Not because I can do it better, but because I've never done one before so stealing their idea seems like an easier way to start.  They then followed up the comics with some code that translated the comic to a concrete function.
The Comic
(Coming Soon)
In English-Ish
Forward
To find the length of the line, each person asks the person in front how many people are in front of them.
Base Case
When the person at the front of the line is reached, he reports that there's no one in front of him (zero).
Backwards
Once the front of the line is reached, each person then relays back how many people the person in front reports and adds one to include the person who reported the count until the back of the line is reached.

A Person
I originally thought of using a list, but then you'd have to criple the length method… so I'm making a linked list of a sorts, where each person knows the person in front of them.
class Person:
"""A person in line
"""
person_in_front = None
The Recursion
def hey_fella_how_many_people_are_in_front_of_me(fella: Person):
"""Finds out how many people are in front of current person
Args:
fella: the current person being asked
Returns:
Number of people in front (including last person)
"""
COUNT_THIS_FELLA = 1
if fella.person_in_front is None:
return COUNT_THIS_FELLA
return (hey_fella_how_many_people_are_in_front_of_me(fella.person_in_front)
+ COUNT_THIS_FELLA)
Check If It Works
Now I'll create a line of unknown length so we can check it.
from string import ascii_letters
import random
waiting = random.randrange(1, 1000)
def line_of_people(people: int) -> Person:
"""Builds the lengthless line
Args:
people: how many people to queue up
Returns:
line of people
"""
line = this_person = Person()
for person in range(1, waiting):
this_person.person_in_front = Person()
this_person = this_person.person_in_front
return line
in_line = line_of_people(waiting)
So at this point we have a line of people of unknown length. Each person only knows the existence of the person in front of them so there's no way to get the length of the line directly, but we can use the recursive function to find out how many people there are.
reported = hey_fella_how_many_people_are_in_front_of_me(in_line)
print(f"Expected: {waiting}, Actual: {reported}")
assert waiting == reported
Expected: 539, Actual: 539
Seems to be working.


Provides type-specific classes for object elements or keys.
Whenever possible, {@code fastutil} provides both typical collections, which compare objects using {@code equals()}, and reference-based collections, which use equality ({@code ==}). See the related comments in the overview.
Of course, reference-based sorted sets and maps make no sense, and are not generated.


--- layout: null section-type: territory title: Territory --- ## Territory Based in Minot, ND. Serving the greater Bakken oil patch.