Page maintained by Ke-Sen Huang.
If you have additions or changes, send an e-mail.
Note that when possible I link to the page containing the link to the actual PDF or PS of the preprint.
I prefer this as it gives some context to the paper and avoids possible copyright problems with direct linking.
Thus you may need to search on the page to find the actual document.
Eurographics Digital Library: Computer Graphics Forum Volume 31 - Issue 2 (EG 2012 Proceedings)
Eurographics Digital Library Link for the paper
Paper Abstract
Author Preprint
Paper Video
Paper Presentation
Paper Images
Paper Data
Demo Program or Source Code
Related Links
Changelog
State-of-the-Art Reports (STARs)
- ST1: A Survey of Urban Reconstruction
-
Przemyslaw Musialski,
Peter Wonka,
Daniel G. Aliaga,
Michael Wimmer,
Luc van Gool,
Werner Purgathofer
- ST2: Symmetry in 3D Geometry: Extraction and Applications
()
()
-
Niloy J. Mitra,
Mark Pauly,
Michael Wand,
Duygu Ceylan
- ST3: Interactive Volume Rendering with Volumetric Illumination
-
Daniel Jonsson,
Erik Sunden,
Timo Ropinski
- ST4: Illustrative Flow Visualization: State of the Art, Trends and Challenges
-
Andrea Brambilla,
Robert Carnecky,
Ronald Peikert,
Ivan Viola,
Helwig Hauser
- ST5: Interactive Simulation of Rigid Body Dynamics in Computer Graphics
-
Jan Bender,
Kenny Erleben,
Jeff Trinkle,
Erwin Coumans
- ST6: Perceptual Metrics for Static and Dynamic Triangle Meshes
-
Massimiliano Corsini,
Mohamed-Chaker Larabi,
Guillaume Lavoue,
Oldrich Petrik,
Libor Vasa,
Kai Wang
- ST7: State of the Art in Quad Meshing
-
David Bommes,
Bruno Levy,
Nico Pietroni,
Enrico Puppo,
Claudio Silva,
Marco Tarini,
Denis Zorin
- ST8: Facial Rigging
-
Pedro Bastos,
Xenxo Alvarez,
Veronica Orvalho
FP1: Image and Video Retargeting
- How Not to Be Seen ¡X Object Removal from Videos of Crowded Scenes
-
Miguel Granados,
James Tompkin,
Kwang In Kim,
O. Grau,
Jan Kautz,
Christian Theobalt
- Robust Image Retargeting via Axis-Aligned Deformation
-
Daniele Panozzo,
Ofir Weber,
Olga Sorkine
- Iterative Image Warping
-
Huw Bowles,
Kenny Mitchell,
Bob Sumner,
Jeremy Moore,
Markus Gross
- Coherent Spatiotemporal Filtering, Upsampling and Rendering of RGBZ Videos
-
Christian Richardt,
Carsten Stoll,
Neil A. Dodgson,
Hans-Peter Seidel,
Christian Theobalt
FP2: Photo Manipulation
- Creating Picture Legends for Group Photos
-
Junhong Gao,
Seon Joo Kim,
Michael S. Brown
- Data-Driven Object Manipulation in Images
-
Chen Goldberg,
Tao Chen,
Fang-Lue Zhang,
Ariel Shamir,
Shi-Min Hu
- Realtime Disparity Map based Pictorial Depth Cue Enhancement
-
Christoph Rößing,
Johannes Hanika,
Hendrik P. A. Lensch
- Interactive Multi-perspective Imagery from Photos and Videos
(
)
(
)
-
Henrik Lieng,
James Tompkin,
Jan Kautz
FP3: Light Fields and Reflectance
- Light-Field Retargeting
-
Clemens Birklbauer,
Oliver Bimber
- Unstructured Light Fields
-
Abe Davis,
Marc Levoy,
Fredo Durand
- Data-Driven Surface Reflectance from Sparse and Irregular Samples
-
Roland Ruiters,
Reinhard Klein
- Novel-View Synthesis of Outdoor Sport Events Using an Adaptive View-Dependent Geometry
-
Marcel Germann,
Tiberiu Popa,
Richard Keiser,
Remo Ziegler,
Markus Gross
FP4: Image and Color Processing
- Analytic Anti-Aliasing of Linear Functions on Polytopes
-
Thomas Auzinger,
Michael Guthe,
Stefan Jeschke
- SimpleFlow: A Non-iterative, Sublinear Optical Flow Algorithm
-
Michael Tao,
Jiamin Bai,
Pushmeet Kohli,
Sylvain Paris
- SMAA: Enhanced Subpixel Morphological Antialiasing
-
Jorge Jimenez,
Jose I. Echevarria,
Tiago Sousa,
Diego Gutierrez
- Black Is Green: Adaptive Color Transformation For Reduced Ink Usage
-
Lior Shapira,
Boris Oicherman
FP5: Massive Models
- Real-time Realistic Rendering and Lighting of Forests
-
Eric Bruneton,
Fabrice Neyret
- Interactive Editing of GigaSample Terrain Fields
-
Marc Treib,
Florian Reichl,
Stefan Auer,
Rudiger Westermann
- A GPU-based Approach for Massive Model Rendering with Frame-to-Frame Coherence
-
Chao Peng,
Yong Cao
- Rasterized Bounding Volume Hierarchies
(
)
(
)
-
Jan Novak,
Carsten Dachsbacher
FP6: Textures and Materials
- Procedural Texture Preview
-
Anass Lasram,
Sylvain Lefebvre,
Cyrille Damez
- Mesh Colorization
-
George Leifman,
Ayellet Tal
- 3D Material Style Transfer
-
Chuong Nguyen,
Tobias Ritschel,
Elmar Eisemann,
Karol Myszkowski,
Hans-Peter Seidel
- Repetition Maximization based Texture Rectification
-
Dror Aiger,
Daniel Cohen-Or,
Niloy Mitra
FP7: Computational Photography
- Practical Spectral Photography
-
Ralf Habel,
Michael Kudenov,
Michael Wimmer
- Coding Depth through Mask Structure
-
Manuel M. Oliveira,
Horacio Fortunato
- Soft Stacking
-
Jim McCann,
Nancy Pollard
- Metering for Exposure Stacks
-
Orazio Gallo,
Marius Tico,
Roberto Manduchi,
Natasha Gelfand,
Kari Pulli
FP8: Crowds, Cloths and Shape Deformation
- A realistic model of following behavior for crowd simulation
-
Samuel Lemercier,
Asja Jelic,
Richard Kulpa,
Jiale Hua,
Jerome Fehrenbach,
Pierre Degond,
Cecile Appert-Rolland,
Stephane Donikian,
Julien Pettre
- Manipulation of Flexible Objects by Geodesic Control
-
He Wang,
Taku Komura
- Super-Clothoids
-
Florence Bertails-Descoubes
- Data-Driven Estimation of Cloth Simulation Models
-
Eder Miguel,
Miguel Otaduy,
Bernd Bickel,
Wojciech Matusik,
Bernhard Thomaszewski,
Steve Marschner,
Derek Bradley
FP9: Perceptual Graphics
- A Computational Model of Afterimages
-
Tobias Ritschel,
Elmar Eisemann
- Perceptually Linear Parameter Variations
-
Norbert Lindow,
Daniel Baum,
Hans-Christian Hege
- NoRM: No-Reference Image Quality Metric for Realistic Image Synthesis
-
Robert Herzog,
Martin Cadik,
Tunc Ozan Aydin,
Kwawng In Kim,
Karol Myszkowski,
Hans-Peter Seidel
- Unsharp Masking, Countershading and Halos: Enhancements or Artifacts?
(
)
(
)
-
Matthew Trentacoste,
Rafal Mantiuk,
Wolfgang Heidrich,
Florian Dufrot
- Crowd Light: Evaluating the Perceived Fidelity of Illuminated Dynamic Scenes
-
Adrian Jarabo,
Tom Van Eyck,
Veronica Sundstedt,
Kavita Bala,
Diego Gutierrez,
Carol O'Sullivan
FP10: Making and Shadowing
- Pixel Art with Refracted Light by Rearrangeable Sticks
-
Yonghao Yue,
Kei Iwasaki,
Bing-Yu Chen,
Yoshinori Dobashi,
Tomoyuki Nishita
- crdbrd: Shape Fabrication by Sliding Planar Slices
-
Kristian Hildebrand,
Bernd Bickel,
Marc Alexa
- ShadowPIX: Multiple Images from Self-Shadowing
-
Amit Bermano,
Ilya Baran,
Marc Alexa,
Wojciech Matusik
- Manufacturing Layered Attenuators for Multiple Prescribed Shadow Images
-
Ilya Baran,
Philipp Keller,
Derek Bradley,
Stelian Coros,
Wojciech Jarosz,
Derek Nowrouzezahrai,
Markus Gross
- Rationalization of Triangle-Based Point-Folding Structures
-
Henrik Zimmer,
Marcel Campen,
David Bommes,
Leif Kobbelt
FP11: Interactive Modeling and User Interfaces
- Interactive Self-Organizing Windows
-
Markus Steinberger,
Manuela Waldner,
Dieter Schmalstieg
- Exploring Shape Variations by 3D-Model Decomposition and Part-based Recombination
-
Arjun Jain,
Thorsten Thormahlen,
Tobias Ritschel,
Hans-Peter Seidel
- Linear Analysis of Nonlinear Constraints for Interactive Geometric Modeling
-
Martin Habbecke,
Leif Kobbelt
- Multitouch Gestures for Constrained Transformation of 3D Objects
-
Oscar Kin-Chung Au,
Hongbo Fu,
Chiew-Lan Tai
FP12: Cities and Buildings
- Interactive Coherence-Based Facade Modeling
-
Przemyslaw Musialski,
Michael Wimmer,
Peter Wonka
- Factored Facade Acquisition using Symmetric Line Arrangements
-
Duygu Ceylan,
Niloy J. Mitra,
Hao Li,
Thibaut Weise,
Mark Pauly
- Procedural Generation of Parcels in Urban Modeling
-
Carlos Vanegas,
Tom Kelly,
Basil Weber,
Jan Halatsch,
Daniel Aliaga,
Pascal Muller
- Procedural Interpolation of Historical City Maps
-
Lars Krecklau,
Christopher Manthei,
Leif Kobbelt
FP13: Lighting and Rendering
- Importance Caching for Complex Illumination
-
Iliyan Georgiev,
Jaroslav Krivanek,
Stefan Popov,
Philipp Slusallek
- Selective Inspection and Interactive Visualization of Light Transport in Virtual Scenes
-
Tim Reiner,
Anton Kaplanyan,
Marcel Reinhard,
Carsten Dachsbacher
- Stochastic Progressive Photon Mapping for Dynamic Scenes
-
Maayan Weiss,
Thorsten Grosch
- Real-time Rendering of Dynamic Scenes under All-frequency Lighting using Integral Spherical Gaussian
-
Kei Iwasaki,
Wataru Furuya,
Yoshinori Dobashi,
Tomoyuki Nishita
FP14: Animation
- A continuous, editable representation for deforming mesh sequences with separate signals for time, pose and shape
-
Thomas J. Cashman,
Kai Hormann
- Retrieval of Interactions by abstraction of spacetime relationships
-
Jeff K.T. Tang,
Jacky C.P. Chan,
Howard Leung,
Taku Komura
- Automatically Rigging Multi-component Characters
-
Gaurav Bharaj,
Thorsten Thormahlen,
Hans-Peter Seidel,
Christian Theobalt
- Fast Grasp Synthesis for Various Shaped Objects
-
Fumihito Kyota,
Suguru Saito
FP15: Computational Geometry and Geometry Processing
- Centroidal Voronoi Tessellations for Line Segments and Graphs
-
Lin Lu,
Bruno Levy,
Wenping Wang
- A Simple Algorithm for Maximal Poisson-Disk Sampling in High Dimensions
-
Mohamed S. Ebeida,
Scott A. Mitchell,
Anjul Patney,
Andrew A. Davidson,
John D. Owens
- Medial Kernels
-
Matthew Berger,
Claudio Silva
- Generalized Swept Mid-Structure for Polygonal Models
-
Tobias Martin,
Guoning Chen,
Suraj Musuvathy,
Elaine Cohen,
Charles Hansen
FP16: Visualization and Simulation
- Explicit Mesh Surfaces for Particle Based Fluids
-
Jihun Yu,
Chris Wojtan,
Greg Turk,
Chee Yap
- Advected Tangent Curves: A General Scheme for Characteristic Curves of Flow Fields
-
Tino Weinkauf,
Hans-Christian Hege,
Holger Theisel
- Computational Design of Rubber Balloons
-
Melina Skouras,
Bernhard Thomaszewski,
Bernd Bickel,
Markus Gross
- A Cell-Based Light Interaction Model for Human Blood(Thesis)
-
Daniel Yim,
Gladimir Baranoski,
Brad Kimmel,
T. Francis Chen,
Erik Miranda
SP1: Rendering and Lighting
- Skeleton based importance sampling for path tracing
-
Venceslas Biri,
John Chaussard
- Forward+: Bringing Deferred Lighting to the Next Level
-
Takahiro Harada,
Jay McKee,
Jason Yang
- Reflective Shadow Map Clustering for Real-Time Global Illumination
-
Roman Prutkin,
Anton Kaplanyan,
Carsten Dachsbacher
- Hybrid CPU/GPU KD-Tree Construction for Versatile Ray Tracing
-
Jean-Patrick Roccia,
Christophe Coustet,
Mathias Paulin
- Perceptually Based Afterimage Synthesis
-
Michihiro Mikamo,
Marcos Slomp,
Raytchev Bisser,
Toru Tamaki,
Kazufumi Kaneda
SP2: Modeling and Reconstruction
- Robust Outlier Removal from Point Clouds Acquired with Structured Light
-
Johannes Kohler,
Tobias Noll,
Gerd Reis,
Dider Stricker
- Automatic multi-view surface matching
-
Umberto Castellani,
Simone Fantoni,
Andrea Fusiello
- Growing Cell Structures Learning a Progressive Mesh During Surface Reconstruction
-
Tom Vierjahn,
Guido Lorenz,
Sina Mostafawy,
Klaus Hinrichs
- Shape Reconstruction from Raw Point Clouds using Depth Carving
-
Fabio Guggeri,
Riccardo Scateni,
Renato Pajarola
- Variation-Factored Encoding of Facade Images
-
Suhib Alsisan,
Niloy J. Mitra
- Efficient Evaluation of Semi-Smooth Creases in Catmull-Clark Subdivision Surfaces
-
Matthias Niessner,
Charles Loop,
Gunther Greiner
SP3: Procedural Techniques and Flow
- Scented Sliders for Procedural Textures
-
Anass Lasram,
Sylvain Lefebvre,
Cyrille Damez
- Geometric details on skeleton-based implicit surfaces
-
Cedric Zanni,
P. Bares,
Ares Lagae,
M. Quiblier,
Marie-Paule Cani
- Example-based Road Network Synthesis
-
Qizhi Yu,
Anthony Steed
- Steady state Stokes flow interpolation for fluid control
-
Haimasree Bhattacharya,
Michael Nielsen,
Robert Bridson
- FTLE Computation Beyond First-Order Approximation
-
Markus Uffinger,
Filip Sadlo,
Chuck Hansen,
Mike Kirby,
Thomas Ertl
SP4: Deformation and Animation
- Solid-state Culled Discrete Element Granular Systems
-
Seth Holladay,
Parris Egbert
- Image-based Animation of Clothes
-
Anna Hilsmann,
Peter Eisert
- Improved Obstacle Relevancy, Distance, and Angle for Crowds Constrained to Arbitrary Manifolds in 3D Space
-
Brian Ricks,
Peter Eisert
- Fast Response and Quick Progressive Transitions using Body Part Motion Graphs
-
Adso Fernandez-Baena,
David Miralles
- Automatic Line Handles for Freeform Deformation
-
Leila Schemali,
Jean-Marc Thiery,
Tamy Boubekeur
- GPU based ARAP Deformation using Volumetric Lattices
-
Michael Zollhofer,
Ezgi Sert,
Gunther Greiner,
Jochen Suessmuth
SP5: Rendering and Rasterization
- Physically-Based Depth of Field in Augmented Reality
-
Peter Kan,
Hannes Kaufmann
- Real-Time Metaball Ray Casting with Fragment Lists
-
Laszlo Szecsi,
David Illes
- Incoherent Ray Tracing without Acceleration Structures
-
Attila Tamas Afra
- S-buffer: Sparsity-aware Multi-Fragment Rendering
-
Andreas Vasilakis,
Ioannis Fudos
- Hyperplane Culling for Stochastic Rasterization
-
Jacob Munkberg,
Tomas Akenine-Moller
kesen.huang@gmail.com


Hamilton in Chicago was quite the concert!
And the "Hamilton" actor for Lafayette did not throw away his shot.
Here's an example of one of his most difficult verses:
And I’m never gonna stop until I make ‘em / Drop and burn ‘em up and scatter their remains
What makes it difficult is that it's one of the fastest line ever spoken on Broadway, according to analysis form FiveThirtyEight.
And just how fast?
Belmont student Chris Lee stepped into the big shoes of Daveed Diggs, a professional rapper, to the thunderous applause of the Chicago audience when he rapped that fast line. Major props to Chicago's Lafayette character!
Here's how the line's speed compares to other musicals that have all come to Chicago, according to FiveThirtyEight:
| Musical | Song | Words | Length | Speed (Words/Sec.) |
|---|---|---|---|---|
| Pirates of Penzance | Modern Major-General | 34 | 9 | 3.8 |
| Hamilton | Satisfied | 121 | 24 | 5.0 |
| Company | Not Getting Married Today | 68 | 11 | 6.2 |
| Hamilton | Guns and Ships | 19 | 3 | 6.3 |
While Lee's verse in "Guns and Ships" isn't the fastest in history, I couldn't believe it is delivered in one breathe. That's what seems like what made it so unique.
Hamilton in Chicago by the numbers
Here's a list of some other important and fun numbers from my visit to the show:
Another Site Did Hamilton Chicago Pretty Well
The pictures' padding looks pretty good. Like how they're centered within the column. The height and the width are designated for the photos, which makes them look nice and uniform. In the source code, there's a border of zero. When I added a border by editing it, the border looked kind of silly. So that's good that they don't use that.
Next, I like the h3 attribute stylings. In the .css page, there's font family, font style, and font weight. So the main css determines the style of the html page. Next, there's a user agent profile that determines some of the color and margins that really work well for breaking up the text in a way that doesn't draw attention to the headers. It also gives the reader some room to breath beneath the fold and scrolling through the article. There's a nice graphic determining the margin, border, padding, and the sub-heading size. At the same time, I don't like the spacing above the sub-heading. It seems like there's more room than necessary above it: I might want that to be more uniform.


NZ police say no more survivors expected from volcano eruption
WHAKATANE (New Zealand), Dec 10 — New Zealand police said early today they did not expect to find any more survivors from a volcanic eruption on White Island that killed at least five people and injured up to 20.
“No signs of life have been seen at any point,” the police said in a statement after rescue helicopters and other aircraft had carried out a number of aerial reconnaissance flights over the island following the eruption on Monday afternoon.
“Police believe that anyone who could have been taken from the island alive was rescued at the time of the evacuation,” the statement said. — Reuters


HOME
SEARCH-PAGE
TASTE-MAKER
Menu Items Containing Vegetables
Vegetable Jiaozi
Includes: Carrots, Ginger, Mushrooms (Shiitake or Portabella), Cabbage, Chives, Sesame Oil, Egg, Soy, Pepper (Black or White)
Check out some of our other recipes!
Baked Zucchini with Mozzarella
Includes: Zucchini, Mozzarella, Seasoning Salt
Check out some of our other recipes!
Ratatouille
Includes: Onion, Garlic, Eggplant, Zucchini, Bell Pepper, Tomatoes, Oregano, Basil
Check out some of our other recipes!
Garlic Sweet Potatoes
Includes: Sweet Potatoes, Garlic, Rosemary, Olive Oil, Kosher Salt, Black Pepper
Check out some of our other recipes!
Vegetable Salad
Includes: Cucumber, Tomatoes, Green Onion, Bell Pepper, Radishes, Jicama, Romaine Lettuce Leaves, Minced Garlic, Lemon Juice
Check out some of our other recipes!


Hello, welcome to Yousif Azami's first Assignment
Use the following to test movement:
a: move left
d: move right
s: move down
w: move up
space: dance


--- layout: page title: Calvin Brown #centered title at top of page subtitle: Data Analyst, Urban Planner, Cartographer, Transit and Safe Streets Advocate #use-site-title: true ---


| Simulink Blocks and resources | Level | Description |
| DAC_SIM_HL/Digital_Up_Converter | Error | To guarantee data integrity in generated HDL code, set the "Multitask rate transition" and "Single task rate transition" options to "Error" on the Diagnostics > Sample Time pane of the Configuration Parameters dialog. Additionally on the Solver pane, set the Solver type to "Fixed-step" and, in the Additional options > Tasking and sample time options section select "Treat each discrete rate as a separate task". |
| DAC_SIM_HL/Digital_Up_Converter | Warning | Signals of type 'Double' will not generate synthesizable HDL. Consider enabling native floating-point mode and retyping all 'Double' typed signals to 'Single' to generate synthesizable code. More information |
| DAC_SIM_HL/Digital_Up_Converter | Warning | HDL test bench generation for multirate models requires a fixed step, discrete solver in single tasking mode. In the configuration parameters under 'Solver -> Solver options', ensure the solver type is set to "Fixed-step" and the solver to "discrete". To configure the solver to single tasking mode, under 'Solver -> Additional options -> Tasking and sample time options' uncheck the options "Treat each discrete rate as a separate task" and "Automatically handle rate transition for data transfer". |
| DAC_SIM_HL/Digital_Up_Converter/Halfband_1_61_44/InterpSys/upsamp1 | Message | The initial condition is not used when the model is in single-tasking mode. Multi-tasking mode is not supported for HDL. |
| DAC_SIM_HL/Digital_Up_Converter/Halfband_1_61_44/InterpSys/upsamp2 | Message | The initial condition is not used when the model is in single-tasking mode. Multi-tasking mode is not supported for HDL. |


To view this video please enable JavaScript, and consider upgrading to a web browser that supports HTML5 video


Preparation time
1-2 hours
Cooking time
30 mins to 1 hour
Serves
Serves 4
Cure the salmon:place the 4 fillets of salmon into a small bowl and mix with the salt, pepper, dill and lemon zest. Marinade for 30 mins, only. Wash under running water, and pat dry the fish. Refrigerate covered with cling film.
Make the cucumber salad:finely slice the cucumber. Place in a bowl, sprinkle with salt and leave and marinade for 30 mins. (The salt will remove the enzymes which can cause indigestion). Rinse under cold water, pat dry. Add vinegar, sunflower oil, dill and pepper. Taste to correct seasoning.
Make the horseradish cream: combine all the ingredients and season to taste, for more of a twang add some freshly grated horseradish.
To confit the salmon: preheat the olive oil to 55C: drop in the four pieces of salmon and cook for approximately 16-18 minutes at 45C. Probe temperature of oil. The aim here is not to cook the salmon but to change its texture and taste. Once you put the 4 fillets into the oil, the oil temperature will drop to approx 45C. It must be kept at this temperature so use a probe to check. The salmon will be uncooked yet creating a very pleasing taste and texture. If over cooked the salmon fillet will leak white proteins (albumen).
Serve by arranging the cucumber in the centre of the plates; place on the confit salmon pieces. Drizzle the horseradish sauce around. Arrange a few sprigs of dill and trout eggs on the sauce. When serving sprinkle a little fleurs de sel onto the salmon.


{% include analytics.html %}
{% include open-graph.html %} {% include twitter-card.html %}
{{ page.title | default: 'PHP North East' }}
{% include header.html %} {% include main.html %} {% include sponsors.html %} {% include footer.html %}


Sometimes within a table row we might need to show child rows related to the row, this is when the table child rows should be implemented. The table child rows feature provides a dropdown for each table row that when opened will render child rows as defined by the implementor. With the table child rows template we allow the implementor to provide a template for each column to use for the row and then we inject that template into the correct place in the interface (this works exactly like the normal table columns).
childRowsKey
on the go-table
component for this to work.
childRowsKey
refers to the key on the parent row object where the child array resides.
There could be instances when implementing child rows where more formatting is required on a child row column,
or access to the parent row is necessary. Implementation here is very similar to the
column templates for the parent rows.
To access the parent row, you must add let-parentItem="parentItem"
to the template.


Mastery Version: 4.17.1
Masteries
|
Name |
ID |
|
Alchemist |
4324 |
|
Arcane Blade |
4154 |
|
Arcane Mastery |
4133 |
|
Archmage |
4143 |
|
Bandit |
4352 |
|
Blade Weaving |
4141 |
|
Bladed Armor |
4224 |
|
Block |
4211 |
|
Brute Force |
4122 |
|
Butcher |
4114 |
|
Culinary Master |
4334 |
|
Dangerous Game |
4144 |
|
Devastating Strikes |
4152 |
|
Double-Edged Sword |
4111 |
|
Enchanted Armor |
4213 |
|
Evasive |
4244 |
|
Executioner |
4134 |
|
Expanded Mind |
4343 |
|
Expose Weakness |
4121 |
|
Feast |
4124 |
|
Fleet of Foot |
4312 |
|
Frenzy |
4151 |
|
Fury |
4112 |
|
Greed |
4331 |
|
Hardiness |
4233 |
|
Havoc |
4162 |
|
Inspiration |
4344 |
|
Intelligence |
4353 |
|
Juggernaut |
4232 |
|
Legendary Guardian |
4252 |
|
Martial Mastery |
4132 |
|
Meditation |
4313 |
|
Mental Force |
4123 |
|
Oppression |
4231 |
|
Perseverance |
4241 |
|
Phasewalker |
4311 |
|
Recovery |
4212 |
|
Reinforced Armor |
4243 |
|
Resistance |
4234 |
|
Runic Affinity |
4332 |
|
Runic Blessing |
4253 |
|
Scavenger |
4341 |
|
Scout |
4314 |
|
Second Wind |
4251 |
|
Sorcery |
4113 |
|
Spell Weaving |
4131 |
|
Strength of Spirit |
4323 |
|
Summoner's Insight |
4322 |
|
Swiftness |
4242 |
|
Tenacious |
4262 |
|
Tough Skin |
4214 |
|
Unyielding |
4221 |
|
Vampirism |
4333 |
|
Veteran's Scars |
4222 |
|
Wanderer |
4362 |
|
Warlord |
4142 |
|
Wealth |
4342 |


--- title: Italian bloggers call for support date: 2009-03-12 16:06:59.000000000 +02:00 categories: - politics tags: - bebe grillo - blogging - free speech - italy status: publish type: post published: true meta: _edit_last: '600927' delicious: a:3:{s:5:"count";s:1:"0";s:9:"post_tags";s:0:"";s:4:"time";s:10:"1275237054";} reddit: a:2:{s:5:"count";s:1:"0";s:4:"time";s:10:"1275848360";} author: login: kouk email<EMAIL_ADDRESS>display_name: Konstantinos Koukopoulos first_name: '' last_name: '' excerpt: !ruby/object:Hpricot::Doc options: {} ---
From Bebe Grillo comes another initiative against the Italian Governments attempts to censor bloggers:
Send in your photos with the words: "FREE BLOGGER":
Send an email to<EMAIL_ADDRESS>with:
- subject: your name
- text: the address of your blog
- attached: a photo of you with a sign saying “FREE BLOGGER”.
So here's my photo:
[caption id="attachment_109" align="aligncenter" width="300" caption="for bebe grillo\'s free bloggers campaign"][/caption]
Read more about it on Athena's post here.


The cover image is from http://www.clipart.com. The cover fonts are Akzidenz Grotesk and Orator.
The text font is Adobe's Meridien; the heading font is ITC Bailey.


Articles
A selection of articles is available in this section.
-
Usage options
14 March 2016
What type of project could benefit from Metalsmith?
-
Gotchas
10 March 2016
Issues and workarounds when using Metalsmith.
-
Gulp
2 March 2016
Do you need Gulp? Can it be integrated with Metalsmith?
-
Future publication
1 March 2016
This article will be published after 1 March, 2016.


Open a new account:
Name:
Initial Deposit:
Submit
Access your funds:
Deposit Amount:
Widthdrawal Amount:
Submit
Current Balance:$


resume
LEAP Apprentice at Microsoft, 2017
• Five weeks in classroom being mentored by senior Microsoft engineers.
• Learned basics of C# and .NET application building.
• Covered topics including maintainable coding techniques, test driven development, object oriented programming, and learning a new codebase.
• On a team of five, created a database schema for the internship program’s website to prepare it for expansion across different chapters.
Web Developer at IUNU LLC, 2016-2017
• Delivered client facing MVC framework React.js web application using Mongo, Redux, HTML, CSS, and JavaScript.
• Create an MVP data aggregation tool over the course of four weeks in a three-person team.
• Redesigned a second iteration of the same tool over two weeks featuring a robust front end, code review and refactoring, incorporated Redux into a new boilerplate, and implemented a Redux feature for the app contributed bug fixes.
• Learn Redux, Meteor, and MongoDB through self-study over the course of working at IUNU.
• Researched industry standard image processing tools, cloud storage systems, as well as doing data comparison.
• Contributed to the product roadmap the team used throughout the second iteration of the React tool.
Full stack web developer at General Assembly, 2016
• Website development programming with 480 hours of classroom instruction on web technologies and computer science basics
• 50-70 hours per week of technical website design that produced 4 web apps and learning new technologies, debugging code, and basics of QA
• Proficient in JavaScript, HTML, CSS, the MEAN stack, AngularJS, and algorithm design
• Acted as Project Manager for Sharkfile, a project management and overview suite
• Won a one day hackathon in a four person team, incorporating web scraping, a SQL database, focusing mainly on the front end


--- title: "COVID-19 and R Part VII" author: "Drew Tyre" date: "2020-03-19" output: word_document: default html_document: code_folding: hide draft: no slug: COVID-19_and_R_VII tags_include: - R - OPD - COVID19 categories: Research og_image: /post/covid-19_in_r_vii_files/figure-html/featured_image-1.png ---
Wednesday’s number of new cases in the USA was still inside the prediction interval, and still below expectations. Italy’s numbers appear to have leveled off from exponential to linear growth. Nonetheless, Italy continues to add more severe cases per day than their ICU bed capacity. Unless things change drastically, I predict the USA will start to exceed local ICU bed capacity by March 23, in places like New York, Washington state, and the Bay Area. Certainly by the end of March. Places like Nebraska may not experience these problems, because measures to reduce transmission started while case numbers were still low.
That outcome is not set in stone. The time to act is now. Even a one day delay in reducing transmission rate dramatically increases the peak number of sick people. If you’re lucky to be in a low risk group, you can still spread the virus. Although your symptoms are mild, the person you hand the virus off to could experience much worse symptoms. You don’t have to hermetically seal your house. I like this graphic:
This all started a week ago, in case you’re just joining.
DISCLAIMER: These unofficial results are not peer reviewed, and should not be treated as such. My goal is to learn about forecasting in real time, how simple models compare with more complex models, and even how to compare different models.
The figure below is complex, so I’ll highlight some features first. The y axis is now cases / 100,000 population to make it easier to compare Italy and the USA. As before, the BLUE LINES are exponential growth models that assume the rate of increase is constant. The dashed black lines are predictions from that model. To make comparison easier, the estimated model and predictions for both countries are on both panels. The lines and intervals for the other country are faded out. The RED LINES are 20 times the number of ICU beds per 100,000 population in each country. Note that the y axis is logarithmic.
Much as yesterday, new cases in the USA are inside the prediction interval, and still below expectations1. Italy’s numbers appear to have leveled off from exponential to linear growth. Look at the new case numbers starting around March 12 – they are going along at a constant level, a flat line on this graph. Each day Italy adds about the same number of cases as the day before. In exponential growth, the number of cases per day increases at the same rate. On a log axis exponential growth looks like an increasing straight line. Nonetheless, Italy continues to add more severe cases per day than their ICU bed capacity.
Unless things change drastically, I predict the USA will start to exceed local ICU bed capacity by March 23, in places like New York, Washington state, and the Bay Area. Certainly by the end of March. Places like Nebraska may not experience these problems, because measures to reduce transmission started while case numbers were still low.
That is a bit more nuanced than yesterday’s prediction. I was looking at maps of the USA outbreak last night and realized that the country level totals are obscuring a lot of variation between states. This matters because when a locale starts reducing transmission by social distancing relative to the size of the outbreak makes a big difference. Consider this figure2 comparing two Italian provinces: The first confirmed case in Italy was in Lodi province on February 21. The Italian government prohibited movement in or out of 10 municipalities in Lodi on February 23, only two days later. Although cases began to increase in Bergamo province on February 28, movement prohibitions were not extended there until March 8, more than a week after the first cases were reported. Cases increased in both provinces, but in Lodi the increase is linear, while Bergamo the increase is exponential. I fear New York and friends are like Bergamo. I’m hoping Nebraska and other small states are like Lodi.
Remember – coding while thinking, no coherent story, ymmv.
I want to break down Canada and the USA to state / province, and see if there is anything useful I can get at that level. I’ll stick to the simple exponential model as a “null model” for now. UGH, I just remembered why I haven’t done that before … needed to be able to map the county rows with 2 letter state abbreviations to the state names in the state rows. So that took an hour. I took the opportunity to follow a suggestion from brilliant quantitative ecologist JB and put the data munging code that isn’t changing into a separate script file. And then that fancy new code broke everything in my base plot, so spent another hour figuring out how I broke everything.
us_by_state <- us_wide2long_old(jhu_wide,"USA") # see, fancy!
## Warning: Missing column names filled in: 'X12' [12]
canada_by_prov <- other_wide2long_old(jhu_wide, countries = "Canada")
# reload the country data because I messed it up above
country_data <- read_csv("data/countries_covid-19.csv") %>%
mutate(start_date = mdy(start_date))
all_by_province <- bind_rows(us_by_state, canada_by_prov) %>%
left_join(country_data, by = c("province" ="Region")) %>%
group_by(country_region, province) %>%
mutate(incident_cases = c(0, diff(cumulative_cases)),
max_cases = max(cumulative_cases)) %>%
ungroup() %>%
mutate(icpc = incident_cases * 10 / popn,
group = as.numeric(factor(country_region))) %>%
# remove early rows from each state/province
# remove 0 rows in the middle that are probably reporting errors
filter(incident_cases > 0, Date >= start_date,
province %in% c("California", "Washington", "New York", "British Columbia", "Alberta", "Ontario")) %>%
mutate(province = factor(province, levels = c("California", "Washington", "New York", "British Columbia", "Alberta", "Ontario")))
base_plot <- ggplot(data = all_by_province,
mapping = aes(x = Date)) +
geom_point(mapping = aes(y = icpc, color = province)) +
facet_wrap(~province, dir="v") +
scale_y_log10() +
theme(legend.position = "none") +
labs(y = "Incident cases / 100K people")
# fit the models
all_models <- all_by_province %>%
mutate(log10_ic = log10(incident_cases),
day = as.numeric(Date - start_date)) %>%
filter(day <= 12) %>%
group_by(province) %>%
nest() %>%
mutate(model = map(data, ~lm(log10_ic~day, data = .)))
all_fit <- all_models %>%
mutate(fit = map(model, augment, se_fit = TRUE),
fit = map(fit, select, -c("log10_ic","day"))) %>%
select(-model) %>%
unnest(cols = c("data","fit")) %>%
mutate(fit = 10^.fitted,
lcl = 10^(.fitted - .se.fit * qt(0.975, df = 10)),
ucl = 10^(.fitted + .se.fit * qt(0.975, df = 10)),
fitpc = fit * 10 / popn,
lclpc = lcl * 10 / popn,
uclpc = ucl * 10 / popn)
all_predicted <- all_by_province %>%
mutate(day = as.numeric(Date - start_date)) %>%
filter(day > 12) %>% #these are the rows we want to predict with
group_by(province) %>%
nest() %>%
left_join(select(all_models, province, model), by="province") %>%
mutate(predicted = map2(model, data, ~augment(.x, newdata = .y, se_fit = TRUE)),
sigma = map_dbl(model, ~summary(.x)$sigma)) %>%
select(-c(model,data)) %>%
unnest(cols = predicted) %>%
mutate(
fit = 10^.fitted,
pred_var = sigma^2 + .se.fit^2,
lpl = 10^(.fitted - sqrt(pred_var)*qt(0.975, df = 10)),
upl = 10^(.fitted + sqrt(pred_var)*qt(0.975, df = 10)),
fitpc = fit * 10 / popn,
lplpc = lpl * 10 / popn,
uplpc = upl * 10 / popn)
base_plot +
geom_line(data = all_fit,
mapping = aes(y = fitpc, color = province),
size = 1.25) +
geom_ribbon(data = all_fit,
mapping = aes(ymin = lclpc, ymax = uclpc),
alpha = 0.2) +
geom_line(data = all_predicted,
mapping = aes(y = fitpc, color = province),
linetype = 2) +
geom_ribbon(data = all_predicted,
mapping = aes(ymin = lplpc, ymax = uplpc),
alpha = 0.2)
That figure is all per capita, so by that metric the two places that are worst off are New York and British Columbia, both adding around 0.5% of the population per day and accelerating. The worst news is that both New York and California continue to grow consistent with the exponential model. It’s a bit harder to tell with the Canadian provinces because the outbreaks are shorter there, so not much left after using 12 days to fit the model. Ontario is interesting because the total number of cases is highest there (for Canada), but per capita they are lower.
So tomorrow I should be able to fiddle the state/province graphs a bit more and get localized predictions for when ICU capacity might become a problem. I guess it’s getting time to find an alternative model to the exponential as well. The logistic curves from a few days ago were terrible at forecasting, so not sure what else to try. Suggestions in the comments please!
I’d also like to refine the prediction of ICU capacity. I finally found someone making predictions that include confidence limits and Dr. Higgie predicts the time at which Australia will start to experience issues with ICU capacity (early April). She makes a great point that cases occupy an ICU bed for some weeks, so just looking at the new cases is optimistic. Instead there needs to be a kind of sliding window sum of the new cases.
Code not shown in the post can be found on Github. This post benefited from comments by Ramona Sky, Kelly Helm-Smith, and Jessica Burnett.↩
This preprint is the source of the figure, and discusses age structure effects↩


Exercise. Ready queue order
Statement.
The system is configured to multiprogramming.
Given exercise processes data, answer the questions:
- In what order are the processes placed in the ready queue for each
of the following algorithms:
- FCFS algorithm
- SJF algorithm (non preemptive)
- SJF algorithm (preemptive)
- Priority Algorithm (non preemptive)
- Priority Algorithm (preemptive)
- Round Robin algorithm (quantum: 1)
Data
| Process |
Submission
Time |
Priority |
Bursts
(Duration and type) |
| P1 |
0 |
3 |
2 CPU + 2 I + 1 cpu |
| P2 |
0 |
1 |
4 cpu |
| P3 |
0 |
9 |
3 cpu + 2 I + 2 cpu |
| P4 |
0 |
10 |
5 cpu |


GolombRuler Class Reference
[Scripts for problems]
Inherits Example.
Detailed Description
Example: Finding optimal Golomb rulersThe script makes use of two lower bounds taken from: Barbara Smith, Kostas Stergiou, Toby Walsh, Modelling the Golomb Ruler Problem. In IJCAI 99 Workshop on Non-binary Constraints, 1999.
See also problem 6 at http://www.csplib.org/.
Definition at line 57 of file golomb-ruler.cc.
Public Types | |
| enum | { MODEL_NONE, MODEL_SUM, MODEL_RULER } |
| Model variants. More... | |
| enum | { SEARCH_DFS, SEARCH_BAB, SEARCH_RESTART } |
| Search variants. More... | |
Public Member Functions | |
| int | diag (int i, int j) |
| Return index for mark difference between mark i and mark j. | |
| GolombRuler (const SizeOptions &opt) | |
| Actual model. | |
| void | constrain (Space *s) |
| Add constraint for next better solution. | |
| virtual void | print (std::ostream &os) |
| Print solution. | |
| GolombRuler (bool share, GolombRuler &s) | |
| Constructor for cloning s. | |
| virtual Space * | copy (bool share) |
| Copy during cloning. | |
Protected Attributes | |
| const int | n |
| Number of marks. | |
| IntVarArray | m |
| Array for ruler marks. |
Member Enumeration Documentation
| anonymous enum |
Model variants.
- Enumerator:
-
MODEL_NONE No lower bound. MODEL_SUM Use sum of ticks as lower bound. MODEL_RULER Use size of smaller rulers as lower bound.
Definition at line 65 of file golomb-ruler.cc.
| anonymous enum |
Search variants.
- Enumerator:
-
SEARCH_DFS Use depth first search to find the smallest tick. SEARCH_BAB Use branch and bound to optimize. SEARCH_RESTART Use restart to optimize.
Definition at line 71 of file golomb-ruler.cc.
Constructor & Destructor Documentation
| GolombRuler::GolombRuler | ( | const SizeOptions & | opt | ) | [inline] |
| GolombRuler::GolombRuler | ( | bool | share, | |
| GolombRuler & | s | |||
| ) | [inline] |
Member Function Documentation
| int GolombRuler::diag | ( | int | i, | |
| int | j | |||
| ) | [inline] |
Return index for mark difference between mark i and mark j.
Definition at line 78 of file golomb-ruler.cc.
| void GolombRuler::constrain | ( | Space * | s | ) | [inline] |
| virtual void GolombRuler::print | ( | std::ostream & | os | ) | [inline, virtual] |
| virtual Space* GolombRuler::copy | ( | bool | share | ) | [inline, virtual] |
Member Data Documentation
const int GolombRuler::n [protected] |
IntVarArray GolombRuler::m [protected] |
The documentation for this class was generated from the following file:
- examples/golomb-ruler.cc (Revision: 5524)


class: center, middle, inverse, title-slide # Some data viz advice ### Daniel Anderson ### Wednesday, April 24 --- # #whoami .pull-left[ * Research Assistant Professor: Behavioral Research and Teaching, University * Dad (two daughters: 7 and 4 (almost 5)) * Primary areas of interest + 💗💗R💗💗 and computational research + Open data, open science, and reproducible workflows + Growth modeling, achievement gaps, and variance between educational institutions (particularly spatially) ]  --- # Resources (free) .pull-left[ Healy (http://socviz.co)

 ] .pull-right[ Wilke (https://serialmentor.com/dataviz/)

 ] --- # Other Resources * My classes! * Sequence + [Intro to R and reproducible/transparent research](https://github.com/uo-datasci-specialization/c1-intro_data_sci) + [Communicating and Transforming Data](https://uo-datasci-specialization.github.io/c2-communicate_transform_data/) + [Functional Programming in R](https://uo-datasci-specialization.github.io/c3-fun_program_r/) + Applied Predictive Modeling + Capstone --- # Where to start? * I *really* recommend moving to R as quickly as possible -- .pull-left[ http://r4ds.had.co.nz

 ] .pull-right[ http://www.moderndive.com ![](img/moderndive.png) ] --- # ggplot2! .pull-left[ https://r-graphics.org ![](https://r-graphics.org/cover.jpg) ] .pull-right[ available through [amazon](https://www.amazon.com/ggplot2-Elegant-Graphics-Data-Analysis/dp/331924275X/ref=dp_ob_title_bk) ![](https://images-na.ssl-images-amazon.com/images/I/31uoy-qmhEL._SX331_BO1,204,203,200_.jpg) ] --- # Last note before we really start * These slides were produced with R * See the source code [here](https://github.com/datalorax/psych-seminar19) * The focus of this particular talk is not on the code itself --- class: middle center # Different ways of encoding data ![](talk_files/figure-html/data-encoding-1.png) --- # Other elements to consider * Text + How is the text displayed (e.g., font, face, location)? + What is the purpose of the text? -- * Transparency + Are there overlapping pieces? + Can transparency help? -- * Type of data + Continuous/categorical + Which can be mapped to each aesthetic? - e.g., shape and line type can only be mapped to categorical data, whereas color and size can be mapped to either. --- class: middle center # Basic Scales ![](talk_files/figure-html/scales-wilke-1.png) --- # Talk with a neighbor How would you encode these data into a display? | Month | Day | Location | Temperature | |:-----:|:---:|:-------------| ------------| | Jan | 1 | Chicago | 25.6 | | Jan | 1 | San Diego | 55.2 | | Jan | 1 | Houston | 53.9 | | Jan | 1 | Death Valley | 51.0 | | Jan | 2 | Chicago | 25.5 | | Jan | 2 | San Diego | 55.3 | | Jan | 2 | Houston | 53.8 | | Jan | 2 | Death Valley | 51.2 | | Jan | 3 | Chicago | 25.3 | --- class: middle center # Putting it to practice ![](talk_files/figure-html/temp-change-1.png) --- class: middle center # Alternative representation ![](talk_files/figure-html/temp-change2-1.png) --- # Comparison * Both represent three scales + Two position scales (x/y axis) + One color scale (categorical for the first, continuous for the second) -- * More scales are possible ![](talk_files/figure-html/five-scales-1.png) --- background-image:url(http://socviz.co/dataviz-pdfl_files/figure-html4/ch-01-multichannel-1.png) background-size:contain Additional scales can become lost without high structure in the data --- # Thinking more about color ### Three fundamental uses -- 1. Distinguish groups from each other -- 1. Represent data values -- 1. Highlight --- # Discrete items * Often no intrinsic order -- ### Qualitative color scale * Finite number of colors + Chosen to maximize distinctness, while also be equivalent + Equivalent - No color should stand out - No impression of order --- background-image:url(https://serialmentor.com/dataviz/color_basics_files/figure-html/qualitative-scales-1.png) background-size:contain # Some examples .footnote[See more about the Okabe Ito palette origins here: http://jfly.iam.u-tokyo.ac.jp/color/] --- background-image:url(https://serialmentor.com/dataviz/color_basics_files/figure-html/sequential-scales-1.png) background-size:contain # Sequential scale examples ### Colors to represent continuous values --- background-image:url(https://serialmentor.com/dataviz/color_basics_files/figure-html/diverging-scales-1.png) background-size:contain # Diverging palettes --- # Earth palette ![](talk_files/figure-html/or1-1.png) --- ![](talk_files/figure-html/ca1-1.png) --- # Common problems with color ### Too many More than 5-ish categories generally becomes too difficult to track ![](talk_files/figure-html/too-many-colors-1.png) --- # Use labels More than 5-ish categories generally becomes too difficult to track ![](talk_files/figure-html/states-labeled-1.png) --- # Better Get a subset ![](talk_files/figure-html/subset-states-1.png) --- # Best ![](talk_files/figure-html/best-label-1.png) --- ## Problem with default ggplot2 palette ![](talk_files/figure-html/colorblind1-1.png) --- # Alternative: viridis ![](talk_files/figure-html/viridis1-1.png) --- # Revised version ![](talk_files/figure-html/unnamed-chunk-1-1.png) --- # Last few note on palettes * Do some research, find what you like .bold[and] what tends to work well * Check for colorblindness * Look into http://colorbrewer2.org/ --- class: inverse center middle # Data ink ratio --- # What is it? -- > ### Above all else, show the data
 \-Edward Tufte -- * Data-Ink Ratio = Ink devoted to the data / total ink used to produce the figure -- * Common goal: Maximize the data-ink ratio --- # Example ![](img/six-boxplots.png) -- * First thought might be... Cool! --- background-image:url(https://theamericanreligion.files.wordpress.com/2012/10/lee-corso-sucks.jpeg?w=660) background-size:cover --- # Minimize cognitive load * Empirically, Tufte's plot was .bolder[the most difficult] for viewers to interpret. -- * Visual cues (labels, gridlines) reduce the data-ink ratio, but can also reduce cognitive load. --- # An example ### Which do you prefer? .pull-left[ ![](talk_files/figure-html/h3_bad-1.png) ] .pull-right[ ![](talk_files/figure-html/h3_good-1.png) ] --- # Advice from Wilke > Whenever possible, .bolder[visualize your data with solid, colored shapes] rather than with lines that outline those shapes. Solid shapes are more easily perceived, are less likely to create visual artifacts or optical illusions, and do more immediately convey amounts than do outlines. .gray[emphasis added] --- # Another example .pull-left[ ![](talk_files/figure-html/iris_lines-1.png) ] .pull-right[ ![](talk_files/figure-html/iris_colored_lines-1.png) ] --- class: center middle ![](talk_files/figure-html/iris_filled-1.png) --- # Labels in place of legends Prior slide is a great example of when annotations can be used in place of a legend to * reduce cognitive load * increase clarity * increase beauty * maximize the figure size --- class: inverse center middle # Practical advice so far -- ### Avoid line drawings -- ### Maximize the data-ink ratio within reason (but preference reduction of cognitive load) -- ### Use color to your advantage (and think critically about the palettes you choose) -- ### Consider plot annotations over legends --- # Grouped data ### Distributions How do we display more than one distribution at a time? --- # Boxplots ![](talk_files/figure-html/boxplots-1.png) --- # Violin plots ![](talk_files/figure-html/violin-1.png) --- # Jittered points ![](talk_files/figure-html/jittered-1.png) --- # Sina plots ![](talk_files/figure-html/sina-1.png) --- # Stacked histograms ![](talk_files/figure-html/stacked-histo-1.png) --- # Overlapping densities ![](talk_files/figure-html/overlap-dens-1.png) --- # Ridgeline densities ![](talk_files/figure-html/ridgeline-1.png) --- class: inverse center middle # Quick empirical examples --- # Titanic data ``` ## # A tibble: 1,313 x 5 ## name class age sex survived ## <chr> <chr> <dbl> <chr> <int> ## 1 Allen, Miss Elisabeth Walton 1st 29 female 1 ## 2 Allison, Miss Helen Loraine 1st 2 female 0 ## 3 Allison, Mr Hudson Joshua Creighton 1st 30 male 0 ## 4 Allison, Mrs Hudson JC (Bessie Waldo Daniels) 1st 25 female 0 ## 5 Allison, Master Hudson Trevor 1st 0.92 male 1 ## 6 Anderson, Mr Harry 1st 47 male 1 ## # … with 1,307 more rows ``` --- # Boxplots ![](talk_files/figure-html/boxplots-empirical-1.png) --- # Violin plots ![](talk_files/figure-html/violin-empirical-1.png) --- # Jittered point plots ![](talk_files/figure-html/jittered-empirical-1.png) --- # Sina plot ![](talk_files/figure-html/sina-empirical-1.png) --- # Stacked histogram ![](talk_files/figure-html/stacked-histo-empirical-1.png) -- # 🤨 --- # Dodged ![](talk_files/figure-html/dodged-histo-empirical-1.png) --- # Better ![](talk_files/figure-html/wrapped-histo-empirical-1.png) --- # Overlapping densities ![](talk_files/figure-html/overlap-dens-empirical-1.png) -- Note the default colors really don't work well in most of these --- ![](talk_files/figure-html/overlap-dens-empirical2-1.png) --- # Ridgeline densities ![](talk_files/figure-html/ridgeline-dens-empirical-1.png) --- class: inverse center middle # Visualizing amounts --- # Bar plots ![](talk_files/figure-html/bars-1.png) --- # Flipped bars ![](talk_files/figure-html/flipped_bars-1.png) --- # Dotplot ![](talk_files/figure-html/dots-1.png) --- # Heatmap ![](talk_files/figure-html/heatmap-1.png) --- class: inverse center middle # A short journey ### How much does college cost? --- # Tuition data ``` ## # A tibble: 6 x 13 ## State `2004-05` `2005-06` `2006-07` `2007-08` `2008-09` `2009-10` ## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> ## 1 Alab… 5682.838 5840.550 5753.496 6008.169 6475.092 7188.954 ## 2 Alas… 4328.281 4632.623 4918.501 5069.822 5075.482 5454.607 ## 3 Ariz… 5138.495 5415.516 5481.419 5681.638 6058.464 7263.204 ## 4 Arka… 5772.302 6082.379 6231.977 6414.900 6416.503 6627.092 ## 5 Cali… 5285.921 5527.881 5334.826 5672.472 5897.888 7258.771 ## 6 Colo… 4703.777 5406.967 5596.348 6227.002 6284.137 6948.473 ## # … with 6 more variables: `2010-11` <dbl>, `2011-12` <dbl>, ## # `2012-13` <dbl>, `2013-14` <dbl>, `2014-15` <dbl>, `2015-16` <dbl> ``` --- # By state: 2015-16 ![](talk_files/figure-html/state-tuition1-1.png) -- # 🤮🤮🤮 --- # Two puke emoji version # 🤮🤮 ![](talk_files/figure-html/state-tuition2-1.png) --- # One puke emoji version # 🤮 ![](talk_files/figure-html/state-tuition3-eval-1.png) --- # Kinda smiley version # 😏 ![](talk_files/figure-html/state-tuition4-eval-1.png) --- # Highlight Oregon # 🙂 ![](talk_files/figure-html/oregon-highlight-eval-1.png) --- # Not always good to sort ![](talk_files/figure-html/income_df-sorted-1.png) --- # Much better ![](talk_files/figure-html/income_df-1.png) --- # Heatmap ![](talk_files/figure-html/heatmap2-eval-1.png) --- # Better heatmap ![](talk_files/figure-html/heatmap3-eval-1.png) --- # Even better heatmap ![](talk_files/figure-html/heatmap4-eval-1.png) --- background-image: url("img/heatmap.png") class: inverse bottom background-size:contain --- # Quick aside * Think about the data you have * Given that these are state-level data, they have a geographic component --- background-image: url("img/states-heatmap.png") class: inverse bottom background-size:contain --- class: inverse center middle # Some things to avoid --- # Line drawings ### As discussed earlier .pull-left[ ### 😫 ![](talk_files/figure-html/dens-titanic-1.png) ] .pull-right[ ### Change the fill ![](talk_files/figure-html/dens-titanic-blue-1.png) ] --- class: middle .pull-left[ ![](talk_files/figure-html/iris_lines2-1.png) ] .pull-right[ ![](talk_files/figure-html/iris_filled2-1.png) ] --- # Much worse ### Unnecessary 3D .pull-left[ ![](img/3d-pie-10-v2.png) ] .pull-right[ ![](img/3d-pie-20-v2.png) ] --- # Much worse ### Unnecessary 3D .pull-left[ ![](img/3d-pie-40-v2.png) ] .pull-right[ ![](img/3d-pie-80-v2.png) ] --- # Horrid example ### Used relatively regularly ![](img/3d_bar.png) --- # Pie charts ### Especially w/lots of categories ![](https://serialmentor.com/dataviz/visualizing_proportions_files/figure-html/marketshare-pies-1.png) --- # Alternative representation ![](https://serialmentor.com/dataviz/visualizing_proportions_files/figure-html/marketshare-side-by-side-1.png) --- # A case for pie charts * `\(n\)` categories low, * differences are relatively large * familiar for some audiences ![](talk_files/figure-html/pie-1.png) --- # The anatomy of a pie chart Pie charts are just stacked bar charts with a radial coordinate system ![](talk_files/figure-html/stacked_bars_nopie-1.png) --- # Horizontal ![](talk_files/figure-html/horiz_stacked-1.png) --- # My preference ![](talk_files/figure-html/dodged_bars-1.png)![](talk_files/figure-html/dodged_bars-2.png) --- # Dual axes * One exception - if second axis is a direct transformation of the first + e.g., Miles/Kilometers, Fahrenheit/Celsius ![](img/dual_axes.png) .footnote[See many examples here: http://www.tylervigen.com/spurious-correlations] --- # Truncated axes ![](img/truncated_axes.png) --- class: middle ![](img/truncated_axes2.png) --- # Not always a bad thing > It is tempting to lay down inflexible rules about what to do in terms of producing your graphs, and to dismiss people who don’t follow them as producing junk charts or lying with statistics. But being honest with your data is a bigger problem than can be solved by rules of thumb about making graphs. In this case there is a moderate level of agreement that bar charts should generally include a zero baseline (or equivalent) given that bars encode their variables as lengths. But it would be a mistake to think that a dot plot was by the same token deliberately misleading, just because it kept itself to the range of the data instead. --- class: middle .pull-left[ ![](http://socviz.co/dataviz-pdfl_files/figure-html4/ch-01-bar-simple-1.png) ] .pull-right[ ![](http://socviz.co/dataviz-pdfl_files/figure-html4/ch-01-bar-simple-2.png) ] --- class: middle .pull-left[ ![](http://socviz.co/dataviz-pdfl_files/figure-html4/ch-01-law-enrollments-1.png) ] .pull-right[ ![](http://socviz.co/dataviz-pdfl_files/figure-html4/ch-01-law-enrollments-2.png) ] --- # Scaling issues ![](img/area_size.png) --- class: middle center # Poor binning choices ![](img/poor_binning.png) --- # Conclusions ### Practical takeaways to make better visualizations 1. Avoid line drawings 2. Sort bar charts in ascending/descending order as long as the other axis does not have implicit meaning 3. Consider dropping legends and using annotations, when possible 4. Use color to your advantage, but be sensitive to color-blindness, and use the right kind of palette 5. Consider double-encoding data (shapes and color) 6. Make your labels bigger! .gray[Didn't talk about this one much but it's super common and really important] --- # Some things to avoid * Essentially never + Use dual axes (produce separate plots instead) + Use 3D unnecessarily * Be wary of + Truncated axes + Pie charts (usually (always?) use bars instead) --- class: inverse center middle # Thanks! ### Questions
[@datalorax_](https://twitter.com/datalorax_)
[@datalorax](https://github.com/datalorax)
[daniela<EMAIL_ADDRESS>Slides available at http://www.datalorax.com/talks/psych-seminar19/


Netflix Assistant
GitHub:
MichaelCurrin/netflix-assistant
Shows
Please enable JavaScript to see results here
Loading...


Syntax:
eval-when (situation*) form* => result*
Arguments and Values:
situation---One of the symbols :compile-toplevel, :load-toplevel, :execute, compile, load, or eval.
The use of eval, compile, and load is deprecated.
forms---an implicit progn.
results---the values of the forms if they are executed, or nil if they are not.
Description:
The body of an eval-when form is processed as an implicit progn, but only in the situations listed.
The use of the situations :compile-toplevel (or compile) and :load-toplevel (or load) controls whether and when evaluation occurs when eval-when appears as a top level form in code processed by compile-file. See Section 3.2.3 (File Compilation).
The use of the situation :execute (or eval) controls whether evaluation occurs for other eval-when forms; that is, those that are not top level forms, or those in code processed by eval or compile. If the :execute situation is specified in such a form, then the body forms are processed as an implicit progn; otherwise, the eval-when form returns nil.
eval-when normally appears as a top level form, but it is meaningful for it to appear as a non-top-level form. However, the compile-time side effects described in Section 3.2 (Compilation) only take place when eval-when appears as a top level form.
Examples:
One example of the use of eval-when is that for the compiler to be able to read a file properly when it uses user-defined reader macros, it is necessary to write
(eval-when (:compile-toplevel :load-toplevel :execute) (set-macro-character #\$ #'(lambda (stream char) (declare (ignore char)) (list 'dollar (read stream))))) => TThis causes the call to set-macro-character to be executed in the compiler's execution environment, thereby modifying its reader syntax table.
;;; The EVAL-WHEN in this case is not at toplevel, so only the :EXECUTE ;;; keyword is considered. At compile time, this has no effect. ;;; At load time (if the LET is at toplevel), or at execution time ;;; (if the LET is embedded in some other form which does not execute ;;; until later) this sets (SYMBOL-FUNCTION 'FOO1) to a function which ;;; returns 1. (let ((x 1)) (eval-when (:execute :load-toplevel :compile-toplevel) (setf (symbol-function 'foo1) #'(lambda () x)))) ;;; If this expression occurs at the toplevel of a file to be compiled, ;;; it has BOTH a compile time AND a load-time effect of setting ;;; (SYMBOL-FUNCTION 'FOO2) to a function which returns 2. (eval-when (:execute :load-toplevel :compile-toplevel) (let ((x 2)) (eval-when (:execute :load-toplevel :compile-toplevel) (setf (symbol-function 'foo2) #'(lambda () x))))) ;;; If this expression occurs at the toplevel of a file to be compiled, ;;; it has BOTH a compile time AND a load-time effect of setting the ;;; function cell of FOO3 to a function which returns 3. (eval-when (:execute :load-toplevel :compile-toplevel) (setf (symbol-function 'foo3) #'(lambda () 3))) ;;; #4: This always does nothing. It simply returns NIL. (eval-when (:compile-toplevel) (eval-when (:compile-toplevel) (print 'foo4))) ;;; If this form occurs at toplevel of a file to be compiled, FOO5 is ;;; printed at compile time. If this form occurs in a non-top-level ;;; position, nothing is printed at compile time. Regardless of context, ;;; nothing is ever printed at load time or execution time. (eval-when (:compile-toplevel) (eval-when (:execute) (print 'foo5))) ;;; If this form occurs at toplevel of a file to be compiled, FOO6 is ;;; printed at compile time. If this form occurs in a non-top-level ;;; position, nothing is printed at compile time. Regardless of context, ;;; nothing is ever printed at load time or execution time. (eval-when (:execute :load-toplevel) (eval-when (:compile-toplevel) (print 'foo6)))
Affected By: None.
Exceptional Situations: None.
See Also:
compile-file, Section 3.2 (Compilation)
Notes:
The following effects are logical consequences of the definition of eval-when:
Wrong:
(defmacro foo () (really-foo) `(really-foo))
Right:
(defmacro foo () `(eval-when (:compile-toplevel :execute :load-toplevel) (really-foo)))
Adherence to this convention means that such macros behave intuitively when appearing as non-top-level forms.
(let ((x 3)) (eval-when (:execute :load-toplevel :compile-toplevel) (print x)))
prints 3 at execution (i.e., load) time, and does not print anything at compile time. This is important so that expansions of defun and defmacro can be done in terms of eval-when and can correctly capture the lexical environment.
(defun bar (x) (defun foo () (+ x 3)))
might expand into
(defun bar (x) (progn (eval-when (:compile-toplevel) (compiler::notice-function-definition 'foo '(x))) (eval-when (:execute :load-toplevel) (setf (symbol-function 'foo) #'(lambda () (+ x 3))))))
which would be treated by the above rules the same as
(defun bar (x) (setf (symbol-function 'foo) #'(lambda () (+ x 3))))
when the definition of bar is not a top level form.


{% extends "limited/base.html" %} {% block panels %} {% include "limited/includes/info.html" %} {% endblock %} {% block main %}


"literally, cookies with salmon in them"
Estimated sales by store
Get hourly estimates on a new store
Store name:
Min. customers/hour:
Max. customers/hour:
Average # cookies per customer:
ADD STORE


James Patterson
All book by this authorIt is no surprise that in January, 2010, The New York Times Magazine featured James Patterson on its cover and hailed him as having "transformed book publishing," and that Time magazine hailed him as "The Man Who Can't Miss." Recently, NBC's Rock Center with Brian Williams profiled Patterson's prolific career, AARP named him one of the "50 Most Influential People Who Make Our Days a Little Brighter," and Variety featured him in a cover story highlighting his adventures in Hollywood.


The {@code objexj} project is a library for pattern matching over {@link java.util.List}s of {@link java.lang.Object}s.
The {@code objexj} project is a library for pattern matching over {@link java.util.List}s of {@link java.lang.Object}s.
Just like with regular regular expressions you can build up pattern strings and match input sequences against them. The difference here is that the input sequences aren't {@link java.lang.String}s, but {@link java.util.List}s of arbitrary {@link java.lang.Object}s.
This toolkit has applications in diagnostics and error analysis (translating particular sequences of {@link java.lang.Throwable}s into meaningful error messages), stream-oriented pattern analysis (extracting {@link java.util.List}s out of a stream and determining what to do based on pattern matching) and other domains.
Please see the Syntax Guide for more information.


| DOSE: |
25 mg |
oral |
2C-I |
(powder / crystals) |
My experience began in some friday night, I went to an outdoor party. I took 25mg of 2C-I orally at 02:00, more or less. I was with good friends, and I felt comfy. We laughed a lot and there was a good chemistry between us 4. Me and a female friend of mine took the substance, the 2 others took LSD. Well, I tried to dance here and there but I didn't like the music (wasn't enough psychedelic:) . That was in the first 2-3 hours after taking the material. I did'nt really figured out why it's not working (I felt a slight buzz, that's all), I'm very sensitive to materials. My friend was in my state as well. But I felt less comfortable with the music, close to the speakers. When I eat research chemicals I usually stomach-sensitive and I tend to puke so I walked about 300 meters away from the party and my friends.
It was about 5:00, and it wasn't dark anymore. I lied down under a tree and looked at the sky. Then I realized that the body needs rest to let the material come to life, not activity. As I calmed more, living visuals began forming in the sky. They seemed far and real, I liked that (unlike LSD when I feel the visuals more inside of my head and eyes).
The substance was definetly present after 15 minutes, I played a sensory-visual game- trying to load myself with sensations and emotions I get from the surroundings and form these to visuals, then back to feelings. That's quite easy and very fun on the 2C family, because my head is clean and I can remember things and build a good thought-train, and the visuals always has a certain distance so they kind of twist themselfs (they don't have an LSD like impact on the followings) and these features are great for what I call a 'hi-fi' psychedelic expereince. I have plenty of room left for MYSELF to achieve the most of what that is happening. I enjoy myself first before all of the psychedelic effects.
The body is soft on that substance. Let it rest for less body load. Well it developed in an hour to a very nice peak. Not too strong but very fun. It's a very funny drug, one of the best IMO. We joked a lot and didn't have any need to have a real conversation - communication is good but not too much (and less good for the 2 on LSD). Bit confusion, but very little for a psychedelic experience. If I smoke weed, I'm much more mind-fucked, but that's me..
I did'nt feel very close emotionaly to my friends (huging someone is hard, also my body did'nt want a human touch for some reason), but it was minor and I know I'm like that when I'm tripping. I got just a bit far from them in that aspect.
The sound is GREAT. It's not clean (such as AMT which is a great substance for listening and making music). It's echoing, and has a great vibe. Very 'sonic' feeling , you can feel the sound waves, you can hear great details ,and their textures are very pleasant and futuristic (I can't explain that too good). I think it gives the overall 2C-I experience a futuristic feel. I have'nt noticed this in other drugs, and it's great to feel that with good music on (that was pink floyd in the car)
The insight is very powerful when nature is a part of the experience. We went to a cliff above a beautiful beach, and I had the greatest time of my life with good and true insights. Felt more true then any other substance. It's very meditative.
So the real trip began after more then 3 hours, in the morning. I stopped feeling trippy in about 7 hours (and felt safe to drive, yet I still saw things), 2 hours later I got home. Sleep was very hard to achieve and took about 3 hours, but was deep.
I believe this substance is good for sensitive people who like the more peaceful side of a psychedelic experience. This is not a ride. It wants you to be gentle in many ways. So listening and dancing trance isn't really a good thing for that. I enjoyed most the hours of being away from the party, in and next to the car, no music or with good music (or really crappy music like leonard cohen on full volume on my crappy car speakers, when his voice and everything there is totaly distorted), and the beach was the best. I went home just because my friend's girlfriend is sensitive to the sun and they had to force me. Could have stayed there forever, on the ground, listening, watching and learning.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Top
Things I have seen on my Travels
Even a fool is counted wise when he holds his peace; When he shuts his lips, he is considered perceptive. Pr 17:28
Home
Rambling Thoughts
Biblical Thoughts
Dragons
Seen on Road
Murals
The following images were taken by me on my travels around southern West Virgina and Virginia. I hope you enjoy them.
This was in a rural Auto Repair shop in Lebanon, VA. It appears to be a late '50's Buick Sedan with the passenger compartment and trunk replaced with a Camper Shell. When I went by there a few years later it was gone.
The view looking north from a pullout on
The Back of The Dragon
, a twisting scenic road in southwest Viginia. Another good site for scenic road trips is
Appalachian Back Roads
You are looking at the Thompson Valley, a farming area.
I found this information sign on "The Crooked Road" just outside of Abingdon, Va. The link in the sign no longer works, it takes you to a place in England.
This will take you to the official site
This is on the road between Richlands and Lebanon, both in Virginia. The stump is quite large and it is just off the road. The people who own the land decorate it for different seaons. The locals told me that sometimes at Christmas it is illuminated with strings of lights, some of which are in the picture.
On the back of a PC monitor in the warehouse office at a coal mine near Grundy, Va.
Sign in an Auto Repair Shop in Abingdon, Va. The building has since been torn down.
Funny sign on a door in Abingdon, Va.
I saw these at a Storage Facility on a side road between Abingdon, Va. and Bristol, Va.
Funny Trailor Hitch Cover I saw on a truck at a Sawmill
Play Set at Poplar Gap Park in Grundy, Va. It sits on the top of a reclaimed strip mine, which is the only way to get a large area of flat land in the mountains. Click to go to the official site
Buchanan County Tourism
, scroll down to get to the Park link.
An old Oak tree with sign along the
Virigina Creeper Trail
Abingdon, Virginia.
Fighting Chickens in coops. I found them in a rural area of Virginia.


Toolbar prototypes
Prototypes for T175953. See each on desktop and on mobile. Even though they are responsive you in some cases you might need to refresh the page for the JavaScript to kick in.
- Simple (full toolbar not shown)
- Full width menu (full toolbar not shown)
- Tool disappears on mobile (Undo and redo)
- Label disappears on mobile
- Tool group collapses to dropdown
- Toolbar pagination
- Extra tools in menu
- Extra tools in panel
- Extra tools in sub toolbar
- Extra tools in grid


Responsive Design Practices
Practicing and learning responsive web design paradigms.
Tweet
Templates
Basic Sidebar
Blog
brought by
dbtek
github project


Base class for TCP Client.
More...
|
|
bool | Connected [get] |
| |
|
string | Address [get] |
| |
|
int | Port [get] |
| |
| RemoteCertificateValidationCallback | CertificateValidationCallback [get, set] |
| | Callback function used to determine if the remote certificate is valid. More...
|
| |
Base class for TCP Client.
Definition at line 19 of file Client.cs.
◆ AddExceptionHandler()
Adds an exception handler to the client.
- Parameters
-
| handler | Exception handler to be added. |
- Returns
- This client object.
Definition at line 120 of file Client.cs.
◆ AddHandler()
Adds a handler onto the client.
- Parameters
-
| handler | Connection handler object. |
- Returns
- This client object.
Definition at line 110 of file Client.cs.
◆ AddLogger()
Adds a logger onto the client.
- Parameters
-
| logger | Logger to be added. |
- Returns
- This client object.
Definition at line 130 of file Client.cs.
◆ Connect()
| bool MTSC.Client.Client.Connect |
( |
| ) |
|
Attemps to connect to the specified server.
- Returns
- True if connection was successful.
Definition at line 143 of file Client.cs.
◆ ConnectAsync()
| Task<bool> MTSC.Client.Client.ConnectAsync |
( |
| ) |
|
Attempts to connect to the specified server.
- Returns
- True if the connection was successful.
Definition at line 193 of file Client.cs.
◆ Disconnect()
| void MTSC.Client.Client.Disconnect |
( |
| ) |
|
Disconnects from the server.
Definition at line 200 of file Client.cs.
◆ Log()
| void MTSC.Client.Client.Log |
( |
string |
log | ) |
|
Logs the message onto the associated loggers.
- Parameters
-
Definition at line 67 of file Client.cs.
◆ LogDebug()
| void MTSC.Client.Client.LogDebug |
( |
string |
debugMessage | ) |
|
Logs the debug message onto the associated loggers.
- Parameters
-
Definition at line 78 of file Client.cs.
◆ QueueMessage()
| void MTSC.Client.Client.QueueMessage |
( |
byte [] |
message | ) |
|
Add a message to the message queue.
- Parameters
-
Definition at line 59 of file Client.cs.
◆ SetPort()
| Client MTSC.Client.Client.SetPort |
( |
int |
port | ) |
|
Sets the server port.
- Parameters
-
- Returns
- This client object.
Definition at line 100 of file Client.cs.
◆ SetServerAddress()
| Client MTSC.Client.Client.SetServerAddress |
( |
string |
address | ) |
|
Sets the server address.
- Parameters
-
| address | Address of the server. |
- Returns
- This client object.
Definition at line 90 of file Client.cs.
◆ CertificateValidationCallback
| RemoteCertificateValidationCallback MTSC.Client.Client.CertificateValidationCallback |
|
getset |
Callback function used to determine if the remote certificate is valid.
Definition at line 138 of file Client.cs.
The documentation for this class was generated from the following file:


Purpose of this site
This is the main portal to the EIC software, repositories, documentation and resources.
It is developed and maintained by the EICUG and the ePIC Collaboration.
{% if site.display_news %}
{% include news/homenews.md %}
{% endif %}
©2023 EIC User Group and ePIC Collaboration
|
Site built at {{ site.time }}
|


|
BitShares-Core
6.1.0
BitShares blockchain implementation and command-line interface software
|
#include <account_object.hpp>
Public Member Functions | |
| bool | has_some_core_voting () const |
| Whether this account owns some CORE asset and is voting. More... | |
| bool | has_pending_fees () const |
| Whether this account has pending fees, no matter vested or not. More... | |
| bool | need_maintenance () const |
| Whether need to process this account during the maintenance interval. More... | |
| void | process_fees (const account_object &a, database &d) const |
| Split up and pay out pending_fees and pending_vested_fees. More... | |
| void | pay_fee (share_type core_fee, share_type cashback_vesting_threshold) |
| Public Member Functions inherited from graphene::db::abstract_object< account_statistics_object, implementation_ids, impl_account_statistics_object_type > | |
| abstract_object () | |
| object_id< SpaceID, TypeID > | get_id () const |
| Public Member Functions inherited from graphene::db::base_abstract_object< account_statistics_object > | |
| std::unique_ptr< object > | clone () const override |
| void | move_from (object &obj) override |
| fc::variant | to_variant () const override |
| std::vector< char > | pack () const override |
| Public Member Functions inherited from graphene::db::object | |
| object ()=default | |
| object (uint8_t space_id, uint8_t type_id) | |
| virtual | ~object ()=default |
Public Attributes | |
| account_id_type | owner |
| string | name |
| redundantly store account name here for better maintenance performance More... | |
| account_history_id_type | most_recent_op |
| uint64_t | total_ops = 0 |
| uint64_t | removed_ops = 0 |
| share_type | total_core_in_orders |
| share_type | total_core_inactive |
| Total amount of core token in inactive lock_forever tickets. More... | |
| share_type | total_core_pob |
| Total amount of core token in active lock_forever tickets. More... | |
| share_type | total_core_pol |
| Total amount of core token in other tickets. More... | |
| share_type | total_pob_value |
| Total value of tickets whose current type is lock_forever. More... | |
| share_type | total_pol_value |
| Total value of tickets whose current type is not lock_forever. More... | |
| share_type | core_in_balance |
| bool | has_cashback_vb = false |
| redundantly store this for better maintenance performance More... | |
| bool | is_voting = false |
| redundately store "if this account is voting" for better maintenance performance More... | |
| time_point_sec | last_vote_time |
| last time voted More... | |
| share_type | lifetime_fees_paid |
| share_type | pending_fees |
| share_type | pending_vested_fees |
| uint64_t | vp_all = 0 |
| all voting power. More... | |
| uint64_t | vp_active = 0 |
| active voting power, if there is no attenuation, it is equal to vp_all. More... | |
| uint64_t | vp_committee = 0 |
| the final voting power for the committees. More... | |
| uint64_t | vp_witness = 0 |
| the final voting power for the witnesses. More... | |
| uint64_t | vp_worker = 0 |
| time_point_sec | vote_tally_time |
| Public Attributes inherited from graphene::db::object | |
| object_id_type | id |
Additional Inherited Members | |
| Static Public Attributes inherited from graphene::db::abstract_object< account_statistics_object, implementation_ids, impl_account_statistics_object_type > | |
| static constexpr uint8_t | space_id |
| static constexpr uint8_t | type_id |
This object contains regularly updated statistical data about an account. It is provided for the purpose of separating the account data that changes frequently from the account data that is mostly static, which will minimize the amount of data that must be backed up as part of the undo history everytime a transfer is made.
Definition at line 46 of file account_object.hpp.
|
inline |
Whether this account has pending fees, no matter vested or not.
Definition at line 136 of file account_object.hpp.
|
inline |
Whether this account owns some CORE asset and is voting.
Definition at line 109 of file account_object.hpp.
|
inline |
Whether need to process this account during the maintenance interval.
Definition at line 139 of file account_object.hpp.
| void graphene::chain::account_statistics_object::pay_fee | ( | share_type | core_fee, |
| share_type | cashback_vesting_threshold | ||
| ) |
Core fees are paid into the account_statistics_object by this method
Definition at line 100 of file account_object.cpp.
| void graphene::chain::account_statistics_object::process_fees | ( | const account_object & | a, |
| database & | d | ||
| ) | const |
Split up and pay out pending_fees and pending_vested_fees.
Definition at line 53 of file account_object.cpp.
| share_type graphene::chain::account_statistics_object::core_in_balance |
Redundantly store core balance in this object for better maintenance performance. Only updates on maintenance.
Definition at line 87 of file account_object.hpp.
| bool graphene::chain::account_statistics_object::has_cashback_vb = false |
redundantly store this for better maintenance performance
Definition at line 89 of file account_object.hpp.
| bool graphene::chain::account_statistics_object::is_voting = false |
redundately store "if this account is voting" for better maintenance performance
Definition at line 91 of file account_object.hpp.
| time_point_sec graphene::chain::account_statistics_object::last_vote_time |
last time voted
Definition at line 93 of file account_object.hpp.
| share_type graphene::chain::account_statistics_object::lifetime_fees_paid |
Tracks the total fees paid by this account for the purpose of calculating bulk discounts.
Definition at line 118 of file account_object.hpp.
| account_history_id_type graphene::chain::account_statistics_object::most_recent_op |
Keep the most recent operation as a root pointer to a linked list of the transaction history.
Definition at line 57 of file account_object.hpp.
| string graphene::chain::account_statistics_object::name |
redundantly store account name here for better maintenance performance
Definition at line 52 of file account_object.hpp.
| account_id_type graphene::chain::account_statistics_object::owner |
Definition at line 50 of file account_object.hpp.
| share_type graphene::chain::account_statistics_object::pending_fees |
Tracks the fees paid by this account which have not been disseminated to the various parties that receive them yet (registrar, referrer, lifetime referrer, network, etc). This is used as an optimization to avoid doing massive amounts of uint128 arithmetic on each and every operation.
These fees will be paid out as vesting cash-back, and this counter will reset during the maintenance interval.
Definition at line 128 of file account_object.hpp.
| share_type graphene::chain::account_statistics_object::pending_vested_fees |
Same as pending_fees, except these fees will be paid out as pre-vested cash-back (immediately available for withdrawal) rather than requiring the normal vesting period.
Definition at line 133 of file account_object.hpp.
| uint64_t graphene::chain::account_statistics_object::removed_ops = 0 |
Total operations related to this account that has been removed from the database.
Definition at line 61 of file account_object.hpp.
| share_type graphene::chain::account_statistics_object::total_core_in_orders |
When calculating votes it is necessary to know how much is stored in orders (and thus unavailable for transfers). Rather than maintaining an index of [asset,owner,order_id] we will simply maintain the running total here and update it every time an order is created or modified.
Definition at line 68 of file account_object.hpp.
| share_type graphene::chain::account_statistics_object::total_core_inactive |
Total amount of core token in inactive lock_forever tickets.
Definition at line 71 of file account_object.hpp.
| share_type graphene::chain::account_statistics_object::total_core_pob |
Total amount of core token in active lock_forever tickets.
Definition at line 74 of file account_object.hpp.
| share_type graphene::chain::account_statistics_object::total_core_pol |
Total amount of core token in other tickets.
Definition at line 77 of file account_object.hpp.
| uint64_t graphene::chain::account_statistics_object::total_ops = 0 |
Total operations related to this account.
Definition at line 59 of file account_object.hpp.
| share_type graphene::chain::account_statistics_object::total_pob_value |
Total value of tickets whose current type is lock_forever.
Definition at line 80 of file account_object.hpp.
| share_type graphene::chain::account_statistics_object::total_pol_value |
Total value of tickets whose current type is not lock_forever.
Definition at line 83 of file account_object.hpp.
| time_point_sec graphene::chain::account_statistics_object::vote_tally_time |
Timestamp of the last count of votes. If there is no statistics, the date is less than _db.get_dynamic_global_properties().last_vote_tally_time
.
Definition at line 105 of file account_object.hpp.
| uint64_t graphene::chain::account_statistics_object::vp_active = 0 |
active voting power, if there is no attenuation, it is equal to vp_all.
Definition at line 98 of file account_object.hpp.
| uint64_t graphene::chain::account_statistics_object::vp_all = 0 |
| uint64_t graphene::chain::account_statistics_object::vp_committee = 0 |
the final voting power for the committees.
Definition at line 99 of file account_object.hpp.
| uint64_t graphene::chain::account_statistics_object::vp_witness = 0 |
the final voting power for the witnesses.
Definition at line 100 of file account_object.hpp.
| uint64_t graphene::chain::account_statistics_object::vp_worker = 0 |
the final voting power for the workers.
Definition at line 101 of file account_object.hpp.


Skills
Java, HTML, CSS, PHP, JavaScript, MySQL, Swift, C++
Tools
Firebase, Git, GitHub, Xcode, Visual Studio Code, Cypress, Arduino
Education
- B. S. Computer Science and Technology (2018 - currently)
- Interactive Design Fundamentals, Object-Oriented Programming, Probability and Statistics, Data Structures, Advanced Database Systems, Network Interconnection, Software Quality and Testing, Mobile Application Development
- 2022 expected graduation year
Activities & Leadership
- 2016 - Current. Mentor of FRC Robotics Team Nautilus 4010.
- 2019 - Current. Programming Club: participating in ICPC
Contact


Instructions
Type "Add" in the console to add an item to the list.
Type "Remove" in the console to remove an item from the list.
Type "List" in the console to list the items from the list.
Type "Quit" in the console to exit, Your Todo List.
This is what I have learnt so far, I am currently learning more about JavaScipt at the time I am making this.
Sorry I haven't added button functions yet. I will probably add them in a later version.
© 2021 Made By Zeerak Asim 😎.


0
Executive Decision
Nationality:
Training/Specialty:
KILLS: 8
Broken Bones
Comments:
Seagal dies exactly 43 minutes and 35 seconds into this movie, but manages to kill 8 people within the first 5 or 10.


DCS - 3.1. Cubic Lagrange interpolation
Pink is uniform BUT , Orange is uniform with equally-distributed weights, blue is non-uniform


You can add one or more Framework Universe Selection Models to your algorithm and it will operate normally. You can also combine it with the AddUniverse
method of the classic approach. The following example initializes a classic algorithm with framework universe selection models:
public override void Initialize() { SetUniverseSelection(new ManualUniverseSelectionModel(QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA))); AddUniverseSelection(new ManualUniverseSelectionModel(QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA))); AddUniverse(CoarseSelection); }
def Initialize(self): self.SetUniverseSelection(ManualUniverseSelectionModel([ Symbol.Create("SPY", SecurityType.Equity, Market.USA) ])) self.AddUniverseSelection(ManualUniverseSelectionModel([ Symbol.Create("AAPL", SecurityType.Equity, Market.USA) ])) self.AddUniverse(self.CoarseSelection)


Hi, I'm Annie.
I am currently a Software Development student. Prior to this, I was a Finance Professional for technology start-up companies.
I am always open to new opportunities to further my passion in software development.
I am currently a Software Development student. Prior to this, I was a Finance Professional for technology start-up companies.
I am always open to new opportunities to further my passion in software development.


2018-06-10 23:06:04,319 : INFO : training model with 4 workers on 13351 vocabulary and 300 features, using sg=1 hs=0 sample=0.001 negative=5 window=7
2018-06-10 23:06:05,342 : INFO : PROGRESS: at 3.73% examples, 160036 words/s, in_qsize 7, out_qsize 0
2018-06-10 23:06:06,389 : INFO : PROGRESS: at 8.22% examples, 171593 words/s, in_qsize 7, out_qsize 0
2018-06-10 23:06:07,409 : INFO : PROGRESS: at 12.59% examples, 174664 words/s, in_qsize 7, out_qsize 0
2018-06-10 23:06:08,414 : INFO : PROGRESS: at 17.04% examples, 176645 words/s, in_qsize 7, out_qsize 0
2018-06-10 23:06:09,428 : INFO : PROGRESS: at 21.37% examples, 178994 words/s, in_qsize 7, out_qsize 0
2018-06-10 23:06:10,470 : INFO : PROGRESS: at 25.35% examples, 176095 words/s, in_qsize 7, out_qsize 0
2018-06-10 23:06:11,471 : INFO : PROGRESS: at 29.53% examples, 176031 words/s, in_qsize 7, out_qsize 0
2018-06-10 23:06:12,483 : INFO : PROGRESS: at 33.42% examples, 174908 words/s, in_qsize 8, out_qsize 0
2018-06-10 23:06:13,552 : INFO : PROGRESS: at 37.95% examples, 174545 words/s, in_qsize 7, out_qsize 0
2018-06-10 23:06:14,597 : INFO : PROGRESS: at 42.06% examples, 174654 words/s, in_qsize 7, out_qsize 0
2018-06-10 23:06:15,617 : INFO : PROGRESS: at 46.55% examples, 175824 words/s, in_qsize 7, out_qsize 0
2018-06-10 23:06:16,665 : INFO : PROGRESS: at 51.14% examples, 176453 words/s, in_qsize 7, out_qsize 0
2018-06-10 23:06:17,680 : INFO : PROGRESS: at 55.48% examples, 176822 words/s, in_qsize 7, out_qsize 0
2018-06-10 23:06:18,696 : INFO : PROGRESS: at 59.75% examples, 177108 words/s, in_qsize 7, out_qsize 0
2018-06-10 23:06:19,729 : INFO : PROGRESS: at 64.01% examples, 177182 words/s, in_qsize 8, out_qsize 0
2018-06-10 23:06:20,747 : INFO : PROGRESS: at 68.31% examples, 177407 words/s, in_qsize 7, out_qsize 0
2018-06-10 23:06:21,750 : INFO : PROGRESS: at 72.68% examples, 177766 words/s, in_qsize 6, out_qsize 1
2018-06-10 23:06:22,787 : INFO : PROGRESS: at 77.13% examples, 177748 words/s, in_qsize 6, out_qsize 1
2018-06-10 23:06:23,797 : INFO : PROGRESS: at 81.46% examples, 178328 words/s, in_qsize 7, out_qsize 0
2018-06-10 23:06:24,812 : INFO : PROGRESS: at 85.61% examples, 178113 words/s, in_qsize 6, out_qsize 1
2018-06-10 23:06:25,830 : INFO : PROGRESS: at 90.19% examples, 178609 words/s, in_qsize 7, out_qsize 0
2018-06-10 23:06:26,859 : INFO : PROGRESS: at 94.06% examples, 177939 words/s, in_qsize 7, out_qsize 0
2018-06-10 23:06:27,934 : INFO : PROGRESS: at 98.58% examples, 177623 words/s, in_qsize 7, out_qsize 0
2018-06-10 23:06:28,176 : INFO : worker thread finished; awaiting finish of 3 more threads
2018-06-10 23:06:28,205 : INFO : worker thread finished; awaiting finish of 2 more threads
2018-06-10 23:06:28,272 : INFO : worker thread finished; awaiting finish of 1 more threads
2018-06-10 23:06:28,295 : INFO : worker thread finished; awaiting finish of 0 more threads
2018-06-10 23:06:28,297 : INFO : training on 5551440 raw words (4258565 effective words) took 24.0s, 177726 effective words/s


| Home | Trees | Indices | Help |
|
|---|
|
|
Geoid models and geoid height interpolations.
Classes GeoidG2012B, GeoidKarney and GeoidPGM to
interpolate the height of various geoids at
LatLon
locations or separate lat-/longitudes using different
interpolation methods and geoid
model files.
GeoidKarney is a transcoding of Charles Karney's C++ class Geoid to pure Python. The GeoidG2012B and GeoidPGM interpolators both depend on scipy and numpy and require those packages to be installed.
In addition, each geoid interpolator needs grid knots
(down)loaded from a geoid
model file, specific to the
interpolator, more details below and in the documentation of the
interpolator class. For each interpolator, there are several
interpolation choices, like linear, cubic, etc.
geoid
model
file, containing locations with known heights also referred to as
the grid knots
. See the documentation of interpolator
class for references to available grid
models.
>>> from pygeodesy import GeoidG2012B # or
-Karney or -PGM as GeoidXyz
geoid
model file
and use keyword arguments to select different interpolation options
>>> ginterpolator = GeoidXyz(geoid_model_file,
**options)
LatLon
location(s) with
>>> ll = LatLon(1, 2, ...)
>>> h = ginterpolator(ll)
or
>>> h0, h1, h2, ... = ginterpolator(ll0, ll1,
ll2, ...)
or a list, tuple, generator, etc. of LatLon
s
>>> hs = ginterpolator(lls)
.height
method as
>>> h = ginterpolator.height(lat, lon)
or as 2 lists, 2 tuples, etc.
>>> hs = ginterpolator.height(lats,
lons)
scipy
are raised as SciPyErrors. Warnings issued by
scipy
can be thrown as SciPyWarning exceptions, provided Python
warnings
are filtered accordingly, see SciPyWarning.
See Also: Karney's GeographicLib, Geoid height and Installing the Geoid datasets, SciPy interpolation RectBivariateSpline and interp2d, functions elevations.elevation2 and elevations.geoidHeight2, Ellispoid vs Orthometric Elevations and Pitfalls Related to Ellipsoid Height and Height Above Mean Sea Level (AMSL).
Version: 23.08.15
| Classes | |
|
_GeoidBase (INTERNAL) Base class for Geoid... s.
|
|
|
GeoidError Geoid interpolator Geoid... or interpolation issue.
|
|
|
GeoidG2012B Geoid height interpolator for GEOID12B Model grids CONUS, Alaska, Hawaii, Guam and Northern Mariana Islands, Puerto Rico and U.S. Virgin Islands and American Samoa based on SciPy RectBivariateSpline or interp2d interpolation.
|
|
|
GeoidHeight5Tuple 5-Tuple (lat, lon, egm84, egm96, egm2008) for GeoidHeights.dat tests with the heights for 3
different EGM grids at degrees90 and
degrees180 degrees (after converting lon
from original 0 <= EasterLon <= 360 ).
|
|
|
GeoidKarney Geoid height interpolator for Karney's GeographicLib Earth Gravitational Model (EGM) geoid egm*.pgm datasets using bilinear or cubic interpolation and caching in pure Python, transcoded from Karney's C++ class Geoid. |
|
|
GeoidPGM Geoid height interpolator for Karney's GeographicLib Earth Gravitational Model (EGM) geoid egm*.pgm datasets but based on SciPy
RectBivariateSpline or interp2d interpolation.
|
|
|
PGMError Issue parsing or cropping an egm*.pgm geoid dataset.
|
| Functions | |||
|
| Variables | |
__all__ = _ALL_LAZY.geoids
|
| Function Details |
Generate geoid egm*.pgm height tests from GeoidHeights.dat Test data for Geoids.
Note:
Function egmGeoidHeights is used to test the geoids GeoidKarney and GeoidPGM, see PyGeodesy module
|
| Home | Trees | Indices | Help |
|
|---|
| Generated by Epydoc 3.0.1 on Sun Aug 20 14:42:07 2023 | http://epydoc.sourceforge.net |


{% extends 'layout.html' %} {% block content %}
PyLadies is an international mentorship group with a focus on helping more women become active participants and leaders in the Python open-source community. PyLadies' mission is to promote, educate and advance a diverse Python community through outreach, education, conferences, events and social gatherings. PyLadies also aims to provide a friendly support network for women and a bridge to the larger Python world. Anyone with an interest in Python is encouraged to participate!
PyLadies Remote was established with the idea in mind to reach those women interested in Python who don’t live near a PyLadies group. All of the PyLadies Remote classes will be online classes in order to be easily accessible for PyLadies all over the world.
If you would like to teach a class for PyLadies Remote, have ideas for future classes, or questions, please get in touch at<EMAIL_ADDRESS>Anna works for Eldarion, helping them with community management and talent development. She is a director of the Python Software Foundation, PyCon Open Spaces-Chair, DjangoCon US Communications Chair, and group leader of the PyLadies Remote group.
She is very passionate about diversity and community outreach and wants to encourage more women to learn programming because it's awesome! In her free time she writes a blog. You can follow Anna on Twitter at @ossanna16.
Cea comes to software via a circuitous journey involving years of CSS and PHP hobbying, a degree in Religious Studies, another degree, and lots of meandering. She works primarily in Ruby by day and Python (and other languages) by, er, night. Cea enjoys Open Source software, co-organizing PyLadies Remote and her local Python meetup, running, swing dancing, biking, sewing and general tomfoolery. She's also always happy to add a little unapologetic awkwardness to most conversations.
To view mostly nonsensical ramblings, see her on twitter @ceaess, otherwise more software activities are on github, gitlab, and Cea's website.


Arsene Wenger's old staff 'shocked' by Raul Sanllehi and Edu's Arsenal changes
Some long-serving Arsenal staff members are reportedly shocked by the number of changes that have taken place since Arsene Wenger’s departure, with the club almost unrecognisable.
The Gunners currently sit in sixth place in the Premier League table, with the pressure heating up on Unai Emery after a run of four games without a league win coupled with sub-par performances throughout the season.
Arsenal head of football Raul Sanllehi has publically backed Emery, and The Mirror report that a number of people behind the scenes feel the club’s issues extend far beyond the manager.
Sanllehi and technical director Edu have rung the changes since taking up their positions, removing a number of key personnel who served under Wenger.
Steve Morrow is the latest high-profile casualty, with the head of recruitment axed in a massive shake-up of the academy, while chief scout Steve Rowley was similarly shown the door two years ago.
Advertisement Advertisement
The majority of Wenger’s old backroom have now left, while others – like former assistant manager Steve Bould – have been demoted.
Long-serving members are ‘shocked by what’s happening to the club’, with the wholesale changes eroding the ‘DNA’ Wenger had spent so long establishing.
Morrow’s exit has not gone down well, with the former Gunner deemed to be a huge loss and someone who had the potential to rise up through the ranks.
The jury is still out on Arsenal’s hierarchy, but there is a feeling that they should share some of the blame for Arsenal’s struggles – not Emery alone.
Nevertheless, the Spanish coach is believed to have only a few games left to turn things around and cannot afford any slip ups against Southampton, Norwich, Brighton or West Ham despite Arsenal wanting to hold out and reassess his position in the summer.


Strictly's Bruno Tonioli 'reshoots' line over fears he would offend the audience
He didn't want to offend anyone
by Paul HironsWith the final three couples announced for the Strictly Come Dancing Grand Final next week, there was heartbreak when comedian Chris Ramsey and his pro partner Karen Hauer were eliminated from this weekend's semi-final.
But during last night's results show (8.12.19), judge Bruno Tonioli had to stop and reshoot a line because he feared he would offend the audience.
Read more: Claudia Winkleman fears being axed from Strictly Come Dancing
Chris and Karen - along with Karim Zeroual and his partner Amy Dowden - competed in the dance-off.
As Chris and Karen prepared to re-dance the rumba, The Sun reports that Bruno offered some advice: "It’s not over until the fat lady sings," he said.
But he reportedly asked for a re-shoot, saying: "Oh, I can’t say that any more. You can’t say ‘fat’ on TV."
The publication quotes a source as saying: "Bruno is just conscious about offending people.
"It’s the last thing he’d want to do so it’s better just to be safe.
"The BBC are incredibly sensitive right now. Obviously it’s filtering down to its stars. The audience didn’t have any issue but accepted it’s the new world we’re living in."
ED! has contacted the BBC for comment.
Read more: Strictly viewers in hysterics over Shirley Ballas' remarks to Kelvin Fletcher
Unfortunately for Chris, 33, the judges unanimously voted to keep Karim and Amy and send them into next week's final.
Already there was EastEnders' Emma Barton and her pro partner Anton Du Beke - making only his second final in 15 years - and ex-Emmerdale actor Kelvin Fletcher and his partner, Oti Mabuse.
Paying tribute to his partner Karen, Chris said: "I'm very proud of myself. I had genuinely no expectations. I thought I'd be gone by week two.
"I've got to thank [Karen]... she's amazing, the best teacher. She's so good at her job, and so patient. So patient!"
Leave us a comment on our Facebook page @EntertainmentDailyFix and let us know what you think of this story.


Tab 1
Tab 2
Tab 3
Click on tab 1 or tab 2 to see examples
Checkbox
Date
Datetime
email
Number
Radio
Search
Time
Name:
Price:
Description:
Release year:
Release year gt:
Release year lt:
Price lt:
Manufacturer name:
Name:
Price:
Description:
Release date:
Price gt:
Price lt:
Release year lt:
Manufacturer name:


{{driver.forename}} {{ driver.surname }} details
Date of birth: {{ driver.dob | date }}
Nationality: {{ driver.nationality }}
Entries: {{ driver.starts }}
Wins: {{ driver.wins }}
Podiums: {{ driver.podiums }}
Career points: {{ driver.career_points }}
Fastest laps (since 2004): {{ driver.fastest_laps }}