Data Visualization and D3.js
Sections:
- What is Data Visualization
- Types of Visual Diagrams
- D3 API Docs
- List of D3 Modules
- Selections and Data
- Enter and Append
- SVG Basic Shapes
- Scales and Axis
- Enter and Update
- Exit and Merge
- Transitions
- Force Layout
- D3 and Vuejs
- Data Visualization Best Practices
- General Data Visualization Resources
- Data Visualization Experts and Companies
- GitBook Link
- Github Repo
What is Data Visualization
- Data visualization is the presentation of data in a pictorial or graphical format.
- It enables decision makers to see analytics presented visually
- Decision makers can then grasp difficult concepts or identify new patterns.
- With interactive visualization, you can take concepts further and teach concepts better.
- You can drill down into charts and graphs for more detail,
- and interactively change what data you see and how it’s processed.
Types of Visual Diagrams
A diagram is a symbolic representation of information according to some visualization technique.
Bar Charts
- A bar chart or bar graph is a chart or graph that presents categorical data with rectangular bars with heights or lengths proportional to the values that they represent.
- The bars can be plotted vertically or horizontally.
- A vertical bar chart is sometimes called a line graph.
Line Charts
- A line chart or line graph is a type of chart which displays information as a series of data points called ‘markers’ connected by straight line segments.
- It is a basic type of chart common in many fields.
- It is similar to a scatter plot except that the measurement points are ordered (typically by their x-axis value) and joined with straight line segments.
- A line chart is often used to visualize a trend in data over intervals of time – a time series – thus the line is often drawn chronologically.
Scatter Plots
- A scatter plot (also called a scatter graph, scatter chart, scattergram, or scatter diagram) is a type of plot or mathematical diagram using Cartesian coordinates to display values for typically two variables for a set of data.
- If the points are color-coded, one additional variable can be displayed.
- The data is displayed as a collection of points, each having the value of one variable determining the position on the horizontal axis and the value of the other variable determining the position on the vertical axis
D3 API Docs
D3 4.0 is a collection of modules that are designed to work together * You can use the modules independently, or you can use them together as part of the default build. * The source and documentation for each module is available in its repository.
Follow the links below to learn more:
- Introduction
- API Reference
- Release Notes
- Gallery
- Examples
- Tutorials
- Plugins
- d3.js on Stack Overflow
- d3-js Google Group
- d3-js Slack Channel (Invite)
- d3-js Gitter Channel
- d3-js IRC Channel => #d3.js on irc.freenode.net
List of D3 Modules
Data space
query
- d3-request
- d3-queue
generation
- d3-random
parsing
- d3-dsv
- d3-time
formatting
- d3-time-format
- d3-format
manipulation
- d3-array
- d3-collection
Graphic space
data transform
- d3-scale
- d3-geo-projection
geometry computation
- d3-voronoi
- d3-hull
- d3-quadtree
- d3-interpolate
- d3-geo
dynamic geometry computation
- d3-transition
- d3-timer
- d3-ease
visual variables mapping
- d3-hierarchy
- d3-sankey
- d3-chord
- d3-hexbin
- d3-force
generation
- d3-shape
- d3-path
- d3-polygon
converter
- d3-color
View space
visual variables mapping (selection, data-binding, attributes)
- d3-selection
- d3-selection-multi
high level set of visual variables mapping (component)
- d3-axis
Interaction space
internal events
- d3-dispatch
user events and geometry computation
- d3-zoom
- d3-brush
- d3-drag
Selections and Data
- Selections are immutable.
- All selection methods that affect which elements are selected (or their order) return a new selection rather than modifying the current selection.
- However, note that elements are necessarily mutable, as selections drive transformations of the document!
var anchor = d3.select("a");
This will select the first element that matches the specified selector string.
const enter = svg.selectAll('rect')
This will select all elements that match the specified selector string
- If the selector is not a string, instead selects the specified array of nodes
this is useful if you already have a reference to nodes, such as this.childNodes within an event listener or a global such as document.links
d3.selectAll(document.links).style("color", "red");
var even = d3.selectAll("tr").filter(":nth-child(even)");
Notice here that you can a css pseudo selector and you can also pass a function
var even = d3.selectAll("tr").filter(function(d, i) { return i & 1; });
A very nice editor to build d3 visualizations that get saved as gists
Click
START CODING
buttonClick Login and you will be routed to github page to authorize application
You can then save your code here and get interactive editor
Playing with D3
Selections Demo
Selections and Data Block Builder Demo
If a value is specified, sets the attribute with the specified name to the specified value on the selected elements and returns this selection.
If the value is a constant, all elements are given the same attribute value
Otherwise, if the value is a function, it is evaluated for each selected element, in order, being passed the current datum (d), the current index (i), and the current group (nodes), with this as the current DOM element (nodes[i]).
The function’s return value is then used to set each element’s attribute. A null value will remove the specified attribute.
- Joins the specified array of data with the selected elements, returning a new selection that represents the update selection: the elements successfully bound to data
Invokes the specified function exactly once, passing in this selection along with any optional arguments.
Returns this selection. This is equivalent to invoking the function by hand but facilitates method chaining.
For example, to set several styles in a reusable function:
function name(selection, first, last) {
selection
.attr("first-name", first)
.attr("last-name", last);
}
If a value is specified, sets the text content to the specified value on all selected elements, replacing any existing child elements.
If the value is a constant, then all elements are given the same text content; otherwise, if the value is a function, it is evaluated for each selected element, in order, being passed the current datum (d), the current index (i), and the current group (nodes), with this as the current DOM element (nodes[i]).
The function’s return value is then used to set each element’s text content. A null value will clear the content.
If the specified type is a string, appends a new element of this type (tag name) as the last child of each selected element, or before the next following sibling in the update selection if this is an enter selection.
The latter behavior for enter selections allows you to insert elements into the DOM in an order consistent with the new bound data; however, note that selection.order may still be required if updating elements change order (i.e., if the order of new data is inconsistent with old data).
If the specified type is a function, it is evaluated for each selected element, in order, being passed the current datum (d), the current index (i), and the current group (nodes), with this as the current DOM element (nodes[i]). This function should return an element to be appended. (The function typically creates a new element, but it may instead return an existing element.)
For example, to append a DIV element to each paragraph:
d3.selectAll("p").append("div");
This is equivalent to:
d3.selectAll("p").append(function() {
return document.createElement("div");
});
Which is equivalent to:
d3.selectAll("p").select(function() {
return this.appendChild(document.createElement("div"));
});
D3 style class attr and more play
Enter and Append
enter
:
- Returns the enter selection: placeholder nodes for each datum that had no corresponding DOM element in the selection.
The enter selection is empty for selections not returned by selection.data.
The enter selection is typically used to create “missing” elements corresponding to new data.
For example, to create DIV elements from an array of numbers:
const div = d3.select("body") .selectAll("div") .data([4, 8, 15, 16, 23, 42]) .enter().append("div") .text(d => d);
If the body is initially empty, the above code will create six new DIV elements, append them to the body in-order, and assign their text content as the associated (string-coerced) number:

4

8

15

16

23

42

Enter and Append Demo
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Enter and Append with Existing Rects
SVG Basic Shapes
SVG Basic Shapes:
- Rectangle
- Circle
- Ellipse
- Straight Line
- Polyline
- Polygon
- Path
The basic shapes that SVG provides are:
rectangle
circle
ellipse
straight line
polyline, polygon and path
Rectangles
<svg width="50" height="50">
<rect x="0" y="0" width="50" height="50" />
</svg>
For us to be able to use an SVG rectangle it must be defined inside of the SVG tags.
The x and y - which is where the rectangle is drawn from and the height and width
The SVG coordinate space starts at the top left and goes to the bottom right as x and y coordinates increase.
So as the height increases, the rectangle will get longer down
And as the width increases, the rectangle will get longer to the right.
var rectangles = [
{"x": 0, "y": 0, "width": 30, "height": 40},
{"x": 50, "y": 50, "width": 30, "height": 40},
{"x": 100, "y": 100, "width": 30, "height": 40},
{"x": 150, "y": 150, "width": 30, "height": 40}
];
var svgContainer = d3.select("body")
.append("svg")
.attr("width","560")
.attr("height","900");
var svgRectangles = svgContainer
.selectAll("rect")
.data(rectangles)
.enter()
.append("rect");
This binds each JSON object to an SVG rectangle DOM element
svgRectangles
.attr("x", function (d,i) { return d.x; })
.attr("y", function (d,i) { return d.y; })
.attr("width", function (d,i) { return d.width; })
.attr("height", function (d,i) { return d.height; });
We use an anonymous function to extract the relevant information from each JSON object For the rectangle, this means the x, y, width and height information.
Circles
<svg width="50" height="50">
<circle cx="25" cy="25" r="25" />
</svg>
SVG circles must be defined inside of the SVG tags
The SVG circle takes in three main inputs:
- cx which is where the center of the circle is drawn from
- cy which is where the center of the circle is drawn from
- r which is the radius of the circle.
The JSON objects should have the cx, cy and r properties.
var svgContainer = d3.select("body")
.append("svg")
.attr("width","560")
.attr("height","900");
First, we define the SVG Container the rectangles will live in.
Note that we define the width and height of the SVG viewport container
var circles = [
{"cx": 25, "cy": 25, "r": 20},
{"cx": 75, "cy": 75, "r": 20},
{"cx": 125, "cy": 125, "r": 20},
{"cx": 175, "cy": 175, "r": 20}
];
The circles array contains 4 circle JSON Objects.
This will be the data source used to construct the circles
var svgCircles = svgContainer.selectAll("circle").data(circles).enter().append("circle");
This binds each JSON object to an SVG circle DOM element
svgCircles
.attr("cx", function (d,i) { return d.cx; })
.attr("cy", function (d,i) { return d.cy; })
.attr("r", function (d,i) { return d.r; });
We use an anonymous function to extract the relevant information from each JSON object
For the circle, this means the cx, cy and r information.
Bonus if you can set the first SVG Circle to Red Color
Tip use the filter function with the svgCircles variable
Ellipses
<svg width="50" height="50">
<ellipse cx="25" cy="25" rx="15" ry="10" />
</svg>
SVG ellipses must be defined inside of the SVG tags.
The SVG ellipse takes in four main inputs:
- cx which is where the center of the ellipse is drawn from
- cy which is where the center of the ellipse is drawn from
- x radius of the ellipse
- y radius of the ellipse
The JSON object should have the cx, cy, rx and ry properties.
var svgContainer = d3.select("body")
.append("svg")
.attr("width","560")
.attr("height","900");
Here we define the SVG Container the ellipses will live in.
Note that we define the width and height of the SVG viewport container
var ellipses = [
{"cx": 25, "cy": 25, "rx": 15, "ry": 20},
{"cx": 75, "cy": 75, "rx": 15, "ry": 20},
{"cx": 125, "cy": 125, "rx": 15, "ry": 20},
{"cx": 175, "cy": 175, "rx": 15, "ry": 20}
];
The ellipses array contains 4 ellipse JSON Objects.
This will be the data source used to construct the ellipses
var svgEllipses = svgContainer
.selectAll("ellipse")
.data(ellipses)
.enter()
.append("ellipse");
svgEllipses
.attr("cx", function (d,i) { return d.cx; })
.attr("cy", function (d,i) { return d.cy; })
.attr("rx", function (d,i) { return d.rx; })
.attr("ry", function (d,i) { return d.ry; });
We use an anonymous function to extract the relevant information from each JSON object
For the ellipse, this means the cx, cy, rx and ry information.
d3.selectAll('ellipse').data()
This will return the data bound to each ellipse
d3.selectAll('ellipse').nodes()
This will return each dom node for each ellipse
This binds each JSON object to an SVG ellipse DOM element
Straight Lines
<svg width="50" height="50">
<line x1="5" y1="5" x2="40" y2="40" stroke="gray" stroke-width="5" />
</svg>
SVG Straight Lines must be defined inside of the SVG tags.
The SVG Straight Line takes in six main inputs:
- x1 which is where the line starts
- y1 which is where the line starts
- x2 which is where the line ends
- y2 which is where the line ends
- stroke which is the color of the line
- stroke-width which is the stroke width
The stroke and stroke-width are necessary because an SVG line is dimensionless.
So by applying a stroke-width greater than zero, we can see the line.
The JSON object should have the x1, y1, x2, y2, stroke and stroke-width properties.
var svgContainer = d3.select("body")
.append("svg")
.attr("width","200")
.attr("height","200");
First, we define the SVG Container the straight lines will live in.
Note that we define the width and height of the SVG viewport container
var straightLines = [
{ "x1": 0, "y1": 0, "x2": 40, "y2": 40, "stroke":"black", "stroke_width":5 },
{ "x1": 50, "y1": 50, "x2": 90, "y2": 90, "stroke":"black", "stroke_width":5 },
{ "x1":100, "y1":100, "x2":140, "y2":140, "stroke":"black", "stroke_width":5 },
{ "x1":150, "y1":150, "x2":190, "y2":190, "stroke":"black", "stroke_width":5 }
];
The straight lines array contains 4 straight line JSON Objects.
This will be the data source used to construct the straight lines
Note that for the stroke_width, we use an underscore to separate the stroke and width words
Why this is important will be seen shortly.
var svgStraightLines = svgContainer
.selectAll("line")
.data(straightLines)
.enter()
.append("line");
This binds each JSON object to an SVG Straight Line DOM element
svgStraightLines
.attr("x1", function (d,i) { return d.x1; })
.attr("y1", function (d,i) { return d.y1; })
.attr("x2", function (d,i) { return d.x2; })
.attr("y2", function (d,i) { return d.y2; })
.attr("stroke", function (d,i) { return d.stroke; })
.attr("stroke-width", function (d,i) { return d.stroke_width; });
We use an anonymous function to extract the relevant information from each JSON object
For the straight line, this means the x1, y1, x2, y2, stroke and stroke-width information.
Note, the stroke-width anonymous function uses the d.stroke {underscore} width.
If we have written stroke {dash} width, then JavaScript would have thought we were trying to do a subtraction.
This is very important to keep in mind as this can often cause bugs in the code.
Scales and Axis
Key Functions:
- Constructs a new band scale with the empty domain, the unit range [0, 1], no padding, no rounding and center alignment.
Constructs a new continuous scale with the unit domain [0, 1], the unit range [0, 1], the default interpolator and clamping disabled.
Linear scales are a good default choice for continuous quantitative data because they preserve proportional differences.
Each range value y can be expressed as a function of the domain value x: y = mx + b.
- If domain is specified, sets the scale’s domain to the specified array of numbers.
- The array must contain two or more elements.
- If the elements in the given array are not numbers, they will be coerced to numbers.
If domain is not specified, returns a copy of the scale’s current domain.
var color = d3.scaleLinear() .domain([-1, 0, 1]) .range(["red", "white", "green"]); color(-0.5); // "rgb(255, 128, 128)" color(+0.5); // "rgb(128, 192, 128)"
Notice in this file that I make a call to d3.csv
d3 request docs for csv and tsv files
- Returns a new request for the CSV file at the specified url with the default mime type text/csv.
If no callback is specified, this is equivalent to:
d3.request(url) .mimeType("text/csv") .response(function(xhr) { return d3.csvParse(xhr.responseText, row); });
d3.request(url) .mimeType("text/csv") .response(function(xhr) { return d3.csvParse(xhr.responseText, row); }) .get(callback);
Here is our function in the blockbuilder file
// dataset for city demographics by city
d3.csv('demographic-states-by-city.csv', (err, data) => {
data.forEach(d => {
d[COUNT_HISPANICS] = Number(d[COUNT_HISPANICS]) + 0; // y
});
// get min/max
var min = d3.min(data, d => d[COUNT_HISPANICS]);
var max = d3.max(data, d => d[COUNT_HISPANICS]);
// or use extent, which gives back [min, max]
const extent = d3.extent(data, d => d[COUNT_HISPANICS]);
// try different scales, change the ranges, see what happens
const yScale = d3.scaleLinear()
.domain(extent)
.range([height, 0]);
// try passing in tick valuess
const yAxis = d3.axisLeft()
.scale(yScale);
const axis = d3.select('svg').append('g')
.attr('transform', 'translate(40, 20)')
.call(yAxis);
const text = axis.selectAll('text')
.attr('fill', d => d === 35 ? 'blue' : 'green')
});
d3.csv(url, row, callback);
Notice we provided a url and a callback but not row
D3 scale and axis methods
Returns the minimum and maximum value in the given array using natural order.
If the array is empty, returns [undefined, undefined].
An optional accessor function may be specified, which is equivalent to calling array.map(accessor) before computing the extent.
- Constructs a new time scale with the domain [2000-01-01, 2000-01-02]
- the unit range [0, 1], the default interpolator and clamping disabled.
- Constructs a new bottom-oriented axis generator for the given scale, with empty tick arguments, a tick size of 6 and padding of 3.
- In this orientation, ticks are drawn below the horizontal domain path.
Introduction to D3 Scales by Mike Bostock
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Shapes
SVG Elements
Path Attribute
d3-shape
calculates the path attribute
Imagine if you had to hand code this:
<svg width="190" height="160" xmlns="http://www.w3.org/2000/svg">
<path d="M10 10 C 20 20, 40 20, 50 10" stroke="black" fill="transparent"/>
<path d="M70 10 C 70 20, 120 20, 120 10" stroke="black" fill="transparent"/>
<path d="M130 10 C 120 20, 180 20, 170 10" stroke="black" fill="transparent"/>
<path d="M10 60 C 20 80, 40 80, 50 60" stroke="black" fill="transparent"/>
<path d="M70 60 C 70 80, 110 80, 110 60" stroke="black" fill="transparent"/>
<path d="M130 60 C 120 80, 180 80, 170 60" stroke="black" fill="transparent"/>
<path d="M10 110 C 20 140, 40 140, 50 110" stroke="black" fill="transparent"/>
<path d="M70 110 C 70 140, 110 140, 110 110" stroke="black" fill="transparent"/>
<path d="M130 110 C 120 140, 180 140, 170 110" stroke="black" fill="transparent"/>
</svg>
Pie
- The pie generator does not produce a shape directly, but instead computes the necessary angles to represent a tabular dataset as a pie or donut chart
- These angles can then be passed to an arc generator
- Constructs a new pie generator with the default settings.
- Constructs a new arc generator with the default settings.
If the radii and angles are instead defined as constants, you can generate an arc without any arguments:
var arc = d3.arc()
.innerRadius(0)
.outerRadius(100)
.startAngle(0)
.endAngle(Math.PI / 2);
arc(); // "M0,-100A100,100,0,0,1,100,0L0,0Z"
Enter and Update
Mikes Blog Post on Object Constancy
Animated transitions are pretty, but they also serve a purpose: they make it easier to follow the data. This is known as object constancy: a graphical element that represents a particular data point (such as Ohio) can be tracked visually through the transition. This lessens the cognitive burden by using preattentive processing of motion rather than sequential scanning of labels.
- To achieve object constancy with D3.js, specify a key function as the second argument to selection.data.
- This function takes a data point as input and returns a corresponding key: a string, such as a name, that uniquely identifies the data point.
For example, the bar chart above defines data as objects:
{
"State": "ND",
"Total": 641481,
"Under 5 Years": 0.065,
"5 to 13 Years": 0.105,
"14 to 17 Years": 0.053,
"18 to 24 Years": 0.129,
"16 Years and Over": 0.804,
"18 Years and Over": 0.777,
"15 to 44 Years": 0.410,
"45 to 64 Years": 0.260,
"65 Years and Over": 0.147,
"85 Years and Over": 0.028
}
with a suitable key function
function key(d) {
return d.State;
}
Thinking with Joins
Mike Bostock’s Blog Post on Thinking with Joins
- Data points joined to existing elements produce the update (inner) selection.
- Leftover unbound data produce the enter selection (left), which represents missing elements.
- Likewise, any remaining unbound elements produce the exit selection (right), which represents elements to be removed.
Now we can unravel the mysterious enter-append sequence through the data join
:
First, svg.selectAll(“circle”) returns a new empty selection, since the SVG container was empty. The parent node of this selection is the SVG container.
This selection is then joined to an array of data, resulting in three new selections that represent the three possible states: enter, update, and exit. Since the selection was empty, the update and exit selections are empty, while the enter selection contains a placeholder for each new datum.
The update selection is returned by selection.data, while the enter and exit selections hang off the update selection; selection.enter thus returns the enter selection.
The missing elements are added to the SVG container by calling selection.append on the enter selection. This appends a new circle for each data point to the SVG
Exit and Merge
Transitions
- A transition is a selection-like interface for animating changes to the DOM.
- Instead of applying changes instantaneously, transitions smoothly interpolate the DOM from its current state to the desired target state over a given duration.
To apply a transition, select elements, call selection.transition, and then make the desired changes.
For example:
d3.select("body")
.transition()
.style("background-color", "red");
- Transitions are derived from selections via selection.transition.
- You can also create a transition on the document root element using d3.transition.
- Returns a new transition on the given selection with the specified name.
- If a name is not specified, null is used.
The new transition is only exclusive with other transitions of the same name.
var t = d3.transition() .duration(750) .ease(d3.easeLinear); d3.selectAll(".apple").transition(t) .style("fill", "red"); d3.selectAll(".orange").transition(t) .style("fill", "orange");
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Force Layout
In the domain of information visualization, physical simulations are useful for studying networks and hierarchies!
Force Layout is good at providing insights on the relationships between connections
To give credit where it is due, the following content below is derived from the above url
D3 force layout uses a physics based simulator for positioning visual elements.
Forces can be set up between elements, For example:
all elements repel one another
elements are attracted to center(s) of gravity
linked elements are a fixed distance apart (network visualisation)
elements may not overlap (collision detection)
Force Simulation
There are 4 steps in setting up force simulation:
Create an array of objects
Call forceSimulation, passing in the array of objects.
Add one or more force functions (forceManyBody, forceCenter, forceCollide, etc) to the system
Set up callback function to update the element positions after each tick.
const dimensions = { width: 300, height: 300 }; const nodes = [{}, {}, {}, {}, {}]; let simulation = d3.forceSimulation(nodes) .force('charge', d3.forceManyBody()) .force('center', d3.forceCenter(dimensions.width / 2, dimensions.height / 2)) .on('tick', ticked); function ticked() { var u = d3.select('svg') .selectAll('circle') .data(nodes) u.enter() .append('circle') .attr('r', 5) .merge(u) .attr('cx', function(d) { return d.x }) .attr('cy', function(d) { return d.y }) u.exit().remove() }
D3 Force Functions
Force functions are added to the simulation using .force() where the first argument is a user defined id and the second argument the force function:
simulation.force('charge', d3.forceManyBody())
forceCenter
- forceCenter (for setting the center of gravity of the system)
Creates a new centering force with the specified x- and y- coordinates. If x and y are not specified, they default to ⟨0,0⟩.
forceCenter is useful (if not essential) for centering your elements as a whole about a center point. (Without it elements might disappear off the page.)
Initialis with a center position:
d3.forceCenter(100, 100)
or using the configuration functions .x() and .y():
d3.forceCenter().x(100).y(100)
simulation.force('center', d3.forceCenter(100, 100))
forceManyBody
- forceManyBody (for making elements attract or repel one another)
Creates a new many-body force with the default parameters.
forceManyBody causes all elements to attract or repel one another. The strength of the attraction or repulsion can be set using .strength() where a positive value will cause elements to attract one another while a negative value causes elements to repel each other. The default value is -30.
simulation.force('charge', d3.forceManyBody().strength(-20))
forceCollide
- forceCollide (for preventing elements overlapping)
Creates a new circle collision force with the specified radius. If radius is not specified, it defaults to the constant one for all nodes.
forceCollide is used to stop elements overlapping and is useful when ‘clumping’ circles together.
We must specify the radius of the elements using .radius():
var numNodes = 100
var nodes = d3.range(numNodes).map(function(d) {
return {radius: Math.random() * 25}
})
var simulation = d3.forceSimulation(nodes)
.force('charge', d3.forceManyBody().strength(5))
.force('center', d3.forceCenter(width / 2, height / 2))
.force('collision', d3.forceCollide().radius(function(d) {
return d.radius
}))
forceX and forceY
forceX and forceY cause elements to be attracted towards specified position(s).
forceX
- forceX for attracting elements to a given point
Creates a new positioning force along the x-axis towards the given position x. If x is not specified, it defaults to 0.
simulation.force('x', d3.forceX().x(function(d) {
return xCenter[d.category];
}));
forceY
- forceY for attracting elements to a given point
Creates a new positioning force along the y-axis towards the given position y. If y is not specified, it defaults to 0.
forceLink
- forceLink for creating a fixed distance between connected elements
Creates a new link force with the specified links and default parameters. If links is not specified, it defaults to the empty array.
- forceLink pushes linked elements to be a fixed distance apart.
It requires an array of links that specify which elements we want to link together. * Each link object specifies a source and target element, where the value is the element’s array index:
var links = [ {source: 0, target: 1}, {source: 0, target: 2}, {source: 0, target: 3}, {source: 1, target: 6}, {source: 3, target: 4}, {source: 3, target: 7}, {source: 4, target: 5}, {source: 4, target: 7} ]
We pass our links array into the forceLink function using .links():
simulation.force('link', d3.forceLink().links(links))
Once again all credit for this content goes to d3indepth.com/force-layout/
Force Layout
D3 and Vuejs
Data Visualization Best Practices
There is a wonderful illustration in this Tableau White Paper on Data Visualization Best Practices
General Data Visualization Resources
- Dashing D3js
- Visualizing Data - a fantastic blog about data visualization.
- Flowing Data - another data visualization blog.
- Information Aesthetics - Another good blog.
- Shirley Wu - Excellent blog on Data Visualization.
Data Visualization Experts and Companies
- Jer Thorp - Data artist.
- Nicolas Feltron - Data artist.
- Stamen - Data visualization company, excellent blog, heavy focus on maps.
- Fathom - Another interesting data visualization company.
Gitbook Link
Github Repo
If you like this information please get more details and challenges at Data Visualization Workshop and star the repository.


Around 4AM I crushed 2x10mg pill.  Had been drinking whisky and smoked a joint before I tried it.  I kept going back to the washroom to add small amounts for about 2 hrs, having a shot every now and then.  I think my girlfriend might be convinced that this is the way to try anal.
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.


Zombie ipsum reversus ab viral inferno, nam rick grimes malum cerebro. De carne lumbering animata corpora quaeritis. Summus brains sit, morbo vel maleficia? De apocalypsi gorger omero undead survivor dictum mauris. Hi mindless mortuis soulless creaturas, imo evil stalking monstra adventus resi dentevil vultus comedat cerebella viventium. Qui animated corpse, cricket bat max brucks terribilem incessu zomby. The voodoo sacerdos flesh eater, suscitat mortuos comedere carnem virus.
- White dwarf extraplanetary
- Worldlets, white dwarf
- Cambrian explosion, hydrogen
- Euclid Sea of Tranquility
Coffin quarter pipe NoMeansNo switch sponsored hospital flip. Fastplant 270 skater boned out yeah. Stoked boardslide hardware air nose-bump. Manual hang ten ledge Vision Streetwear backside hang-up. Streets on Fire wall ride nose grab rail speed wobbles hang ten. Invert hand rail snake skate key hurricane. Hanger concave rail no comply rail slide. Nose bump gnarly 180 soul skate shinner. Jason Dill Japan air hang ten camel back goofy footed frontside air. Melancholy axle set handplant kickflip Donger fakie.
Reviews
Jim J. Platz
jan 31, 2015
Trout Burrowing
Burbot yellow-eye mullet sailback scorpionfish sandroller snake mudhead limia sea chub Asiatic glassfish marblefish pikehead snook. Atlantic eel Rio Grande perch stingray longjaw mudsucker albacore northern sea robin spotted dogfish northern sea robin river stingray.
Jim J. Platz
feb 6, 2015
Trout Burrowing
Burbot yellow-eye mullet sailback scorpionfish sandroller snake mudhead limia sea chub Asiatic glassfish marblefish pikehead snook. Atlantic eel Rio Grande perch stingray longjaw mudsucker albacore northern sea robin spotted dogfish northern sea robin river stingray.


I'm having a strange problem. When trying to write comments with the double forward slash // in C, I get a compiler error. It says something like "error: expected expression before //". This problem has come from nowhere as the // has always worked before. Also, I do not get an error when I use /*...*/ for comments, however it would be impractical to use that for every little comment I want to make.
Any help with this matter would be much appreciated.
Thanks for the reply. Do you know how I can change the version of C I'm using? I can't find the option in Code::Blocks.
Edit:
Here is the full compiler error.
||=== Build: Debug in a (compiler: GNU GCC Compiler) ===|
C:\Users\dell\Desktop\a\main.c||In function 'main':|
C:\Users\dell\Desktop\a\main.c|6|error: expected expression before '/' token|
C:\Users\dell\Desktop\a\main.c|8|warning: control reaches end of non-void function [-Wreturn-type]|
||=== Build failed: 1 error(s), 1 warning(s) (0 minute(s), 0 second(s)) ===|
Edit 2:
It's okay, I figured it out. It was just a simple compiler flag option I had enabled telling the compiler to support C90 programs. Unticking it has solved the // comments problem.


Now please copy the content of the textboard to your clipboard (ctrl+c on windows) (command+c on mac)
Follow this link to continue to the survey


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To guide you through this broad ecosystem, this popular guide provides essential concepts, methods, and techniques for digital design that have withstood the test of time. UX designers, product managers, developers, and anyone involved in digital design will learn how to create semantic structures that will help people engage with your message.
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Information Architecture, 4e
Louis Rosenfeld & co.
To guide you through this broad ecosystem, this popular guide provides essential concepts, methods, and techniques for digital design that have withstood the test of time. UX designers, product managers, developers, and anyone involved in digital design will learn how to create semantic structures that will help people engage with your message.
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Louis Rosenfeld & co.
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Information Architecture, 4e
Louis Rosenfeld & co.
To guide you through this broad ecosystem, this popular guide provides essential concepts, methods, and techniques for digital design that have withstood the test of time. UX designers, product managers, developers, and anyone involved in digital design will learn how to create semantic structures that will help people engage with your message.
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Information Architecture, 4e
Louis Rosenfeld & co.
To guide you through this broad ecosystem, this popular guide provides essential concepts, methods, and techniques for digital design that have withstood the test of time. UX designers, product managers, developers, and anyone involved in digital design will learn how to create semantic structures that will help people engage with your message.
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To guide you through this broad ecosystem, this popular guide provides essential concepts, methods, and techniques for digital design that have withstood the test of time. UX designers, product managers, developers, and anyone involved in digital design will learn how to create semantic structures that will help people engage with your message.
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Overview and Source Code: DISTAR 16342 - Approved for Public Release, Distribution Unlimited
Installation Guide, User Guide and Client Application Guide: DISTAR 17200 - Approved for Public Release, Distribution Unlimited
The views expressed are those of the author and do not reflect the official policy or position of the Department of Defense or the U.S. Government.


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12/6/2018
Ohio University’s campus is not new to flooding issues from the nearby Hocking River.
The original settlers came up the Hocking River to the land the university sits on in 1797 and built houses and established a town, according to the 1804-2004 edition of Ohio University Press. During those days, the river provided a means of transportation and the start of a milling industry.
The community continued to grow and the Hocking Canal was opened in 1843, but soon began losing business to railroads. Its use came to an end in 1873 when the canal bed and its towpath were ruined by a flood.
Provided via the Mahn Center for Archives and Special Collections
One of the first floods documented on OU’s campus from 1873, with The Ridges visible in the background.
Various floods happened throughout the 1900s, however, it wasn’t until later in the 1960s when the campus endured its more devastating floods.
Provided via the Mahn Center for Archives and Special Collections
A headline from the March, 7 1963 edition of The Post.
In March of 1963, a flood said to be Athens’ worst in 35 years, hit nearby areas along the Hocking River and the Ohio River Valley, according to a previous Post article. The flood overtook four residence hall’s electricity on East Green. The entire West Green landscape was also flooded.
About 700 West Green residents and 200 Athens residents were evacuated for eight days and the flood caused $1 million dollars in damages, according to a previous Post article.
Water flooded the basements of McCracken Hall, Grover Center, Peden Stadium and others, according to the April 1963 edition of The Ohio Alumnus. The Hocking River reached a crest of approximately 24 feet.
Provided via the Mahn Center for Archives and Special Collections
An aerial view of Hocking River flooding West Green in 1963.
Again in March of 1964, the campus saw its second record-breaking flood, according to a previous Post article.
The flood caused $14,000 in damages in Grover Center alone, according to the article.
Provided via the Mahn Center for Archives and Special Collections
Outside of Grover Center during the 1964 flood.
In March 1966, a Post headline read “‘Harvard’ slides into the Hocking.”
A third flood, equal in wreckage from the floods that occurred in 1963 and 1964, embraced the campus once again. Attention became focused on the need for a flood protection system.
A previous Post article states the Army Corps of Engineers were working on a plan to control the current of the river and planned to have it finalized by the summer, which would then be presented to Congress for approval in the fall.
“The fun will soon be gone,” a May 1969 Post article read. “Ohio University students will no longer be able to dive out third floor windows into swirling flood waters. There will be no more floating around campus in homemade rafts, no more wading through waist-high water to attend parties.”
According to the article, the university rid themselves of an average of $800,000 in flood damage costs from the new flood protection project which re-routed the Hocking River.
Groundbreaking for the project, which had an estimated cost of $10 million, began April 12, 1969 and was expected to be complete in the spring of 1976. The project would move 5.5 miles of the river south of its location at that time.
Provided via the Mahn Center for Archives and Special Collections
Ohio University campus map from 1938.
While there have not been any major floods at OU since the 1960s with the help from the relocation of the Hocking River, floods are still possible.
In a previous Post article, it was noted that Ohio receives the most rain in the months of March, April and May which increases the risk of flooding. In 2008, the Hocking River rose to 22 feet, which led to road closures.
“Although campus hasn’t seen any major flooding in recent years, Emergency Programs Coordinator Jill Harris said OU does have certain measures it has to take,” read A Post article from 2008.
The river is monitored constantly, according to the article.
During the last academic year, OU anticipated potential flooding to its campus. Students had a three day weekend due to the anticipation of the severe weather.
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Tweet of the Moment
by Ryan HenningAlfalfa, pictured above, has just received a smooch from his sweetheart Darla. He doesn’t want his pals Milan and DIllon to find out, though!
Alfalfa, pictured above, has just received a smooch from his sweetheart Darla. He doesn’t want his pals Milan and DIllon to find out, though!


{% comment %} Three columns, a question in each. {% endcomment %} {% for questiongroup in questiongroups %}


As we know, a stock market index tracks the price changes of a select group of stocks and compiles those stock price changes into a single value. For example, S&P500 is composed of only 500 large-cap stocks. A broad market index is characterized by including stocks from companies of all sizes(large, mid and small-cap based on their values). The most popular U.S. broad market indexes include the Russell 3000, the Wilshire 5000 Total Market Index and the MSCI U.S. Broad Market Index. Those broad-based market indexes attempt to cover the entire market and their return can be a good benchmark of the current market state.
class MomentumandStateofMarkeFiltersAlgorithm(QCAlgorithm): def Initialize(self): self.SetStartDate(2011, 1, 1) self.SetEndDate(2018, 1, 1) self.SetCash(100000) # add Wilshire 5000 Total Market Index data from Dropbox self.AddData(Wilshire5000, "W5000", Resolution.Daily) # calculate the index yearly return self.W5000Return = self.ROC("W5000", 252) # initialize the RateOfChange indicator of Wilshire 5000 total market index history = self.History(["W5000"], 500, Resolution.Daily) for tuple in history.loc["W5000"].itertuples(): self.W5000Return.Update(tuple.Index, tuple.value)
In this algorithm, we choose the Wilshire 5000 Total Market Index to be the market state measure. For the period of index return, longer horizons should capture more dramatic changes in the state of the market, but longer horizons also reduce the number of observations of changes in the market's state. Here we choose 12 months return according to the paper Market States and Momentum from Guttierez, Cooper and Hameed. The daily index price comes from the Yahoo Finance.
class Wilshire5000(PythonData): "Class to import Wilshire 5000 Total Market Index data from Dropbox" def GetSource(self, config, date, isLiveMode): return SubscriptionDataSource("https://www.dropbox.com/s/z9rof4fr9cqzgpt/W5000.csv?dl=1", SubscriptionTransportMedium.RemoteFile) def Reader(self, config, line, date, isLiveMode): if not (line.strip() and line[1].isdigit()): return None index = Wilshire5000() index.Symbol = config.Symbol try: # Example File Format: (Data starts from 01/04/2010) # Date Open High Low Close Adj Close Volume # 1/4/10 11549.13965 11749.37012 11549.13965 11743.54004 11743.54004 0 data = line.split(',') index.Time = datetime.strptime(data[0], "%Y-%m-%d") index.Value = Decimal(data[5]) except: return None return index
The investment universe contains all stocks on NYSE and NASDAQ with a price higher than $1. We use the momentum indicator to gauge the momentum effect.
In CoarseSelectionFunction
, the MOM indicator value for each symbol in coarse is updated with the adjusted price and saved in the dictionary self.mom
.
def CoarseSelectionFunction(self, coarse): coarse = [x for x in coarse if (x.HasFundamentalData and x.AdjustedPrice > 1)] for i in coarse: if i.Symbol not in self.mom: self.mom[i.Symbol] = SymbolData(i.Symbol, self.lookback) self.mom[i.Symbol].MOM.Update(self.Time, i.AdjustedPrice)
When the indicator is ready, stocks are then sorted based on the previous six months momentum value. Top 20 Stocks with the highest MOM are in the long stock list, 20 Stocks with the lowest MOM are in the short stock list.
self.MOMReady = {symbol: SymbolData for symbol, SymbolData in self.mom.items() if SymbolData.MOM.IsReady} if self.MOMReady: # sort stocks by 6 months' momentum sortByMOM = sorted(self.MOMReady, key = lambda x: self.MOMReady[x].MOM.Current.Value, reverse = True) self.long = sortByMOM[:20] self.short = sortByMOM[-20:] return self.long+self.short
The strategy is rebalanced monthly. At the beginning of each month, we identify the state of the market. If the market’s one-year return is positive, we define the state of the market as "UP" otherwise the state is "DOWN". When the market is in "UP" state, we go long on the previous six-month winners (highest Momentum) and goes short on the last six-month losers (lowest Momentum). Stocks are equally weighted. If the market is in "DOWN" state, we liquidate all asset holdings and invest in the long-term Treasury bond ETF to control the downside risk.
def OnData(self, data): if self.month_start and self.selection: self.month_start = False self.selection = False if self.long is None or self.short is None: return # if the previous 12 months return on the broad equity market was positive if self.W5000Return.Current.Value > 0: stocks_invested = [x.Key for x in self.Portfolio if x.Value.Invested] for i in stocks_invested: if i not in self.long+self.short: self.Liquidate(i) short_weight = 0.5/len(self.short) # goes short on the prior six-month losers (lowest decile) for short_symbol in self.short: self.SetHoldings(short_symbol, -short_weight) # goes long on the prior six-month winners (highest decile) long_weight = 0.5/len(self.long) for long_symbol in self.long: self.SetHoldings(long_symbol, long_weight) else: self.Liquidate() self.SetHoldings(self.tlt, 1)


{{ $ctrl.allyAppName }} provides custom email addresses that allow to easily send messages to certain groups within your association. Simply send an email to one of the addresses below how you would normally send any old email, and it will be sent to the people listed.


Our greatest glory is not in never falling, but in rising every time we fall. - ConfucioWe approach to the Koding Hackathon with innovation as our value.
Our idea was start revolutionary something simple, and keep the simplicity as core value of it.So we choose one of the oldest game, Chess, and we exploit his dimensions.
Unfortunately the capacities and the deadline didn't match the requirements of delivery something playable, and this for now is just a concept.We crafted everything by hands, and we spend a lot of time on thinking the game logics (Unfortunately, un-experienceable in the current state).
We're still proud of the result.
The codebase is fine crafted with the latest technology JavaScript libraries and in our opinion represent a good example in how to build next-generation App with JavaScript(ES6/ES7).Since you can't enjoy playing,
we hope you can enjoy reading.


For what usage ??
- load testing, captain obvious !
- but also...
- functionnal REST API tests (SPA)
- SLA validation on PR like response time
Functionnal testing really ??
- Tried on a developpement team of 7 developpers
- From the first REST API
- With few user, but more than 1 to challenge conccurency
- On a macro (~6) services + SPA
- On a dedicated cloud, with Jenkins :)
- Once a day, on the last version (git::master)
Functionnal testing really ??
- The first time I succeed to have functional tests coverage (and I tried, cucumber,
gauge, Selenium...)
- The day we needed load tests, all developper was up to speed
- The day we needed load tests, scenario where half written already
Some additional features
- Recorder included (proxy to requests)
- Lots of assertion (time, status, request body content, ..)
Pricing model
- Open source: free
- Enterprise: more feature, never tried :)


--- title: Model blocks keywords: fastai sidebar: home_sidebar nb_path: "nbs/blocks.ipynb" ---
class
BaseRate
BaseRate() :: ModelBlockABC
ModelBlockABC
Estimate average goalscoring rate as a separate parameter.
This can be useful, since it results in both team offence and team defence parameters being centered around 1.0
HomeAdvantage
HomeAdvantage() :: ModelBlockABC
Estimate home advantage.
Assumes constant home advantage is present in every match in the dataset
TeamStrength
TeamStrength() :: ModelBlockABC
Estimate team offence and team defence parameters.
KeyBlock
KeyBlock(key) :: ModelBlockABC
key
Generic model block for adding arbitrary model terms from the data to both home and away team
ConstantBlock
ConstantBlock(*args) :: ModelBlockABC
args
A model block for adding specific model terms to the parameter keys.
Can be useful in conjunction with LumpedAdapter to ensure that certain parameters are in the model (even if they aren't estimated)
LumpedAdapter


Conference Updates
{{ range where .Pages "Section" "news" }}
{{ partial "summary.html" . }}
{{ end }}
{{ partial "header.html" . }}
We had a wonderful conference this year with fantastic speakers, workshops and lovely attendees. Can't wait to see you next year! Come see us at DjangoDay CPH.


[gecode-users] Help me with Maximum density still life in Gecode
trinh cong quy
trinhcongquy at gmail.com
Mon Oct 5 22:34:29 CEST 2009
*Hi All,
I am stuck on this Maximum density **still life problem with Gecode. I use
this constraint
post(*this,
tt(imp(m(i-1,j-1)+m(i-1,j)+m(i-1,j+1)+m(i,j-1)+m(i,j+1)+m(i+1,j-1)+m(i+1,j)+m(i+1,j+1)
== 3,m(i,j)==1)));
post(*this,
tt(imp(m(i-1,j-1)+m(i-1,j)+m(i-1,j+1)+m(i,j-1)+m(i,j+1)+m(i+1,j-1)+m(i+1,j)+m(i+1,j+1)
< 2,m(i,j)==0)));
post(*this,
tt(imp(m(i-1,j-1)+m(i-1,j)+m(i-1,j+1)+m(i,j-1)+m(i,j+1)+m(i+1,j-1)+m(i+1,j)+m(i+1,j+1)
> 3,m(i,j)==0)));
However, it is only with 7*7 board. For 8*8 board, my program run very
slowly. I am trying to improve by dividing the board into 3*3 squares but
still do not have solution
Anyone give suggestion, Thank you very much!!!!*
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This repository is dedicated to the attempt to classify human intentions using EEG and Deep Learning as a part of developing a Brain-Computer Interface (BCI).
Tai Nguyen, Liangyu Tao, Cherelle Conors
The dataset used come from the paper: Upper limb movements can be decoded from the time-domain of low-frequency EEG by Ofner et. al (August 2017), and it's available at: http://bnci-horizon-2020.eu/database/data-sets (dataset #001-2017)
It's description is also available at: http://bnci-horizon-2020.eu/database/data-sets/001-2017/dataset_description.pdf
The data extraction code is located in the data_extraction/src
folder. You can
run the code by:
virtualenv
under data_extraction/
:
virtualenv data_extraction/ --python=python3
data_extraction
folder: cd data_extraction
source bin/activate
on Linuxpip install -r requirements.txt
src
folder: cd src
database_dir = "/home/sweet/1-workdir/eeg001-2017/"
) to your own path. Run
the data_extract script: python data_extract.py
. (lots of data processing,
so expect your computer working at 100%)python create_databases.py
The final step above will create a few files:
prelim_ME_db_128.pickle
: 1 The database of EEG signals from 64
channelsnoneeg_ME_db_128.pickle
: The database of nonEEG signals (movement
sensors)reject_ME_db_128.pickle
: The database of contain trial rejection
informationThe current state of the code will only deal with the Motor Execution (ME) dataset. For the Motor Imagination (MI) dataset, the MI's databases can be created in very similar manner.
prelim_ME_db_128.pickle
will contain of a python map with 7 keys representing
7 classes (6 movement classes + 1 rest class). The value at each key is a python
list, where each element in the list is a trial of that class. Each trial is a
timesteps x 64 matrix (64 is the number of available EEG channels).
The post-preliminary data processing is also located in the
data_extraction/src
folder. You can run the code by:
python post_prelim_processing.py
Running this script will produce a single file called
mesh_ME_db_128.pickle
2, a python map with 7 keys representing 7 classes
(6 movement classes + 1 rest class). The value at each key is a python list,
where each element in the list is a trial of that class. Each trial is a
timesteps x 9 x 9 matrix.
The post-preliminary data processing steps include, but not limited to:
The neural network constructed in this project comes from the paper: Cascade
and Parallel Convolutional Recurrent Neural Networks on EEG-Based Intention
Recognition for Brain Computer Interface by Zhang et. al (2018). The neural
network code is located in the neural_network/src
folder. You can run the code
by:
virtualenv
under neural_network/
:
virtualenv neural_network/ --python=python3
neural_network
folder: cd neural_network
source bin/activate
on Linuxpip install -r requirements.txt
jupyter notebook
neural_network.ipynb
db_dir
variable to indicate the location of the
mesh_ME_db_128.pickle
file generated in the above section.IS_RUNNING_PAIRWISE
, IS_SAVE_TRAINING_HISTORY
,
and GEN_PICKLE_INPUT_TARGET
to your own settings.The notebook will run the code which does all 7 class classfication and report
the accuracies after 50 epochs (the number of epochs can be adjusted in the
variable n_epochs
).
Finally, the confusion matrix available in our report are generated using the
confusion_matrix.ipynb
notebook.
To be written...
Our results are shown in the paper attached in the file EEG_BCI_CNN_LSTM.pdf
.
The paper includes all of our methods, data processing pipelines and final
results.
1: 128 means 128Hz. The original dataset is 512Hz. We downsampled to 128Hz.
2: This database file is also available at https://drexel0-my.sharepoint.com/:u:/g/personal/tdn47_drexel_edu/EdobbPf6Qm5Cpcr-36cQz_EByAIyC44n25WX0-WuiujCog?e=1ao3bu Please cite our work if you decided to use this database.


Click to continue
Tap to continue
mece
Starting parameter
industry rise
Tax level
Max sales
Bank Percent
Product per player
Credit Line
Factory Capacity: ##
Capital Utilization: 100%
Production Cost/Unit: ##
Inventory: ##
Orders Received: ##
Sales Made: ##
Unfilled Orders: ##
Price/Unit Sold: ##
Total Cost/Unit Sold: ##
Margin/Unit Sold: ##
Sales: ##
Marketing: ##
Depresation: ##
R and G: ##
Profit before Tax: ##
Tax: ##
Net Profit: ##
industry changes ##
Total orders: ##
Total Produced: ##
Avg price: ##
Total marketing: ##
Total quality investment: ##
Cash: ##
Capital Investment: ##
Total Assets: ##
credit: #
Bank percent: #
Your parameter


[name] can be used to generate a convex hull for a given array of 3D points. The average time complexity for this task is considered to be O(nlog(n)).
[name] is an add-on, and must be imported explicitly. See [link:#manual/introduction/Installation Installation / Addons].
import { ConvexGeometry } from 'three/addons/geometries/ConvexGeometry.js';
const geometry = new ConvexGeometry( points );
const material = new THREE.MeshBasicMaterial( { color: 0x00ff00 } );
const mesh = new THREE.Mesh( geometry, material );
scene.add( mesh );
[example:webgl_geometry_convex geometry / convex ]
points — Array of [page:Vector3 Vector3s] that the resulting convex hull will contain.
[link:https://github.com/mrdoob/three.js/blob/master/examples/jsm/geometries/ConvexGeometry.js examples/jsm/geometries/ConvexGeometry.js]


Download and include parallax.min.js
in your document after including jQuery.

To easily add a parallax effect behind an element, add data-parallax
data-mirror-selector=".mirrorContainer"
data-scrolling-selector=".scrollingElement"="scroll"
to the element you want to use,
and specify an image with data-src="/path/to/image.jpg"
.

To call the parallax plugin manually, simply select your target element with jQuery and do the following:
$('.parallax-window').parallax({src: '/path/to/image.jpg'});
What parallax.js will do is create a fixed-position element for each parallax image at the start of the document’s body. This mirror element will sit behind the other elements and match the position and dimensions of its target object.
Due to the nature of this implementation, you must ensure that these parallax objects and any layers below them are transparent so that you can see the parallax effect underneath. Also, if there is no other content in this element, you will need to ensure that it has some fixed dimensions otherwise you won’t see anything.
.parallax-window {
min-height: 400px;
background: transparent;
}
Options can be passed in via data attributes of JavaScript. For data attributes, append the option name
to data-
, as in data-src=""
.
Note that when specifying these options as html data-attributes, you
should convert “camelCased” variable names into “dash-separated” lower-case
names (e.g. zIndex
would be data-z-index=""
).
| Name | type | default | description |
|---|---|---|---|
| imageSrc | path | null | You must provide a path to the image you wish to apply to the parallax effect. |
| naturalWidth | number | auto | You can provide the natural width and natural height of an image to speed up loading and reduce error when determining the correct aspect ratio of the image. |
| naturalHeight | number | auto | |
| position | xPos yPos | center center | This is analogous to the background-position css property. Specify coordinates as top, bottom, right, left, center, or pixel values (e.g. -10px 0px). The parallax image will be positioned as close to these values as possible while still covering the target element. |
| positionX | xPos | center | |
| positionY | yPos | center | |
| speed | float | 0.2 | The speed at which the parallax effect runs. 0.0 means the image will appear fixed in place, and 1.0 the image will flow at the same speed as the page content. |
| zIndex | number | -100 | The z-index value of the fixed-position elements. By default these will be behind everything else on the page. |
| bleed | number | 0 | You can optionally set the parallax mirror element to extend a few pixels above and below the mirrored element. This can hide slow or stuttering scroll events in certain browsers. |
| iosFix | boolean | true | iOS devices are incompatable with this plugin. If true, this option will set the parallax image as a static, centered background image whenever it detects an iOS user agent. Disable this if you wish to implement your own graceful degradation. |
| androidFix | boolean | true | If true, this option will set the parallax image as a static, centered background image whenever it detects an Android user agent. Disable this if you wish to enable the parallax scrolling effect on Android devices. |


List Marker Position - Inside
- Fasten your seatbelt
- Start the car's engine and take a closer look the instrument cluster for any warning sign
- Look around carefully and go
List Marker Position - Outside
- Fasten your seatbelt
- Start the car's engine and take a closer look the instrument cluster for any warning sign
- Look around carefully and go


Lena
Fabulous short story, Lena by qntm, riffs on SCP's idea of a work of fiction as a wiki entry. But this is entirely standalone, not part of the SCP universe, and more resembles a Wikipedia entry. Seems both genuinely scary and almost inevitable.
The title stems from the image above, head-and-shoulders hurriedly torn from the centerfold of a colleague's issue of Playboy in 1972, while searching for an image to use in an image processing conference paper. From this, we can infer the proper pronunciation is Lenna, as in the name of the model.
This image has been widely re-used in scientific journals for decades. It has some objectively useful properties - good dynamic range, details and flat regions, shading and texture. However, its viral popularity most probably stems overwhelmingly from its racy nature, featuring an attractive woman, used in male-dominated fields. This was in contrast to other common test images of the time, derived from dull 1960s television standards work.
The common long term use of the image was done without the knowledge or permission of Playboy magazine - the copyright holder - or Lena herself. Over the years they each became aware of it, and made their peace with it. By 2019, though, Lena stated that the image, like her, ought to be retired.


Directions and Contact information
Phone
(530) 752-3766
Email
Manager: David M. Tricoli
Address
Plant Transformation Facility 192 Robbins Hall University of California Davis, CA 95616


About the App and Our Team
What's the likelihood that your Kickstarter campaign will be successful?
Using NLP and / or regression techniques, Kickstarter Success can help predict
how successful a kickstarter campaign will be based on the monetary goal, description,
campaign length, or categories.
MEET OUR TEAM:


I have a very weird behavior about chips and dpow, I don't know if anybody have the same problem. I though it was due to my apow changes but I had the problems on new fresh nodes synced without apow. Do you know why notarized count is way below the blocks count ?
"chain": "main",
"blocks": 4876620,
"headers": 4876620,
"bestblockhash": "000000000000be8271f683e86e00ed0c2670a0e9ea585a6c80a8425e75514bb7",
"notarizedhash": "000000000001094bc5a31d3462084e7e3dad049fb43c838bf535e4f21d5aceca",
"notarizedtxid": "2364cdf9a9fcfcdadf71934eee40e05b444bb2aa86f9ef5b5d1817df0482e020",
"notarized": 4173500,
"prevMoMheight": 4173500,
700k blocks is not nothing. I tried to reindex, delete notarizations file and restart but it didn't help. I deleted the whole content of .chips folder (except wallet.dat and chips.conf) but I had the same result. btw, I don't have this behavior of my NN Chips node nor on some on my test nodes
Do you have any idea why I have this behavior ?


SKIP 2 — scikit-image mission statement¶
- Author
Juan Nunez-Iglesias<EMAIL_ADDRESS>- Author
Stéfan van der Walt<EMAIL_ADDRESS>- Author
Josh Warner
- Author
François Boulogne
- Author
Emmanuelle Gouillart
- Author
Mark Harfouche
- Author
Lars Grüter
- Author
Egor Panfilov
- Author
Gregory Lee
- Status
Active
- Type
Process
- Created
2018-12-08
- Resolved
- Resolution
- skimage-Version
0.16
Abstract¶
scikit-image should adopt the document below as its mission statement. This statement will feature prominently in the scikit-image home page and readme, as well as the contributor and core developer guides. Decisions about the API and the future of the library would be referenced against this document. (See SKIP 1 — scikit-image governance and decision-making.)
In July 2018, I (Juan) published a blog post that broadly outlined what I would want from a roadmap for scikit-image 1, but requested comments from the community before it would be finalized. I consider that we have collected comments for long enough and can move forward with formal adoption. Most comments were positive, so below I’ll just summarize the “negative” comments under “rejected ideas”.
Detailed description¶
(Or: What problem does this proposal solve?)
Over the past few years, scikit-image has been slightly “adrift”, with new and old contributors coming in, adding what small bits they need at the time, and disappearing again for a while. This is fine and we want to encourage more of it, but it also lacks direction. Additionally, without a concerted roadmap to concentrate effort, many of these contributions just fall by the wayside, as it is difficult for new contributors to live up to our stringent (and largely unwritten) standards of code.
Implementation¶
Our mission¶
scikit-image aims to be the reference library for scientific image analysis in Python. We accomplish this by:
being easy to use and install. We are careful in taking on new dependencies, and sometimes cull existing ones, or make them optional. All functions in our API have thorough docstrings clarifying expected inputs and outputs.
providing a consistent API. Conceptually identical arguments have the same name and position in a function signature.
ensuring correctness. Test coverage is close to 100% and code is reviewed by at least two core developers before being included in the library.
caring for users’ data. We have a functional 2 API and don’t modify input arrays unless explicitly directed to do so.
promoting education in image processing, with extensive pedagogical documentation.
Our values¶
We are inclusive. We continue to welcome and mentor newcomers who are making their first contribution.
We are community-driven. Decisions about the API and features are driven by our users’ requirements, not by the whims of the core team. (See SKIP 1 — scikit-image governance and decision-making.)
We serve scientific applications primarily, over “consumer” image editing in the vein of Photoshop or GIMP. This often means prioritizing n-dimensional data support, and rejecting implementations of “flashy” filters that have little scientific value.
We value simple, readable implementations over getting every last ounce of performance. Readable code that is easy to understand, for newcomers and maintainers alike, makes it easier to contribute new code as well as prevent bugs. This means that we will prefer a 20% slowdown if it reduces lines of code two-fold, for example.
We value education and documentation. All functions should have NumPy-style docstrings 3, preferably with examples, as well as gallery examples that showcase how that function is used in a scientific application. Core developers take an active role in finishing documentation examples.
We don’t do magic. We use NumPy arrays instead of fancy façade objects 12, and we prefer to educate users rather than make decisions on their behalf. This does not preclude sensible defaults. 4
This document¶
Much in the same way that the Zen of Python 5 and PEP8 guide style and implementation details in most Python code, this guide is meant to guide decisions about the future of scikit-image, be it in terms of code style, whether to accept new functionality, or whether to take on new dependencies, among other things.
References¶
To find out more about the history of this document, please read the following:
Footnotes
- 12
The use of NumPy arrays was the most supported of the statement’s components, together with the points about inclusivity, mentorship, and documentation. We had +1s from Mark Harfouche, Royi Avital, and Greg Lee, among others.
Backward compatibility¶
This SKIP formalizes what had been the unwritten culture of scikit-image, so it does not raise any backward compatibility concerns.
Alternatives¶
Two topics in the original discussion were ultimately rejected, detailed below:
Handling metadata¶
In my original post, I suggested that scikit-image should have some form of metadata handling before 1.0. Among others, Mark Harfouche, Curtis Rueden, and Dan Allan all advised that (a) maybe scikit-image doesn’t need to handle metadata, and can instead focus on being a robust lower-level library that another like XArray can use to include metadata handling, and (b) anyway, metadata support can be added later without breaking the 1.0 API. I think these are very good points and furthermore metadata handling is super hard and I don’t mind keeping this off our plate for the moment.
Discussion¶
See References below.
References¶
- 1(1,2)
https://ilovesymposia.com/2018/07/13/the-road-to-scikit-image-1-0/
- 2
- 3
- 4
https://forum.image.sc/t/request-for-comment-road-to-scikit-image-1-0/20099/4
- 5
- 6
- 7
https://forum.image.sc/t/request-for-comment-road-to-scikit-image-1-0/20099
- 8
- 9
https://forum.image.sc/t/request-for-comment-road-to-scikit-image-1-0/20099/3
- 10
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication, https://creativecommons.org/publicdomain/zero/1.0/
- 11


Welcome to Flexbox.

Welcome to Flexbox.

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Welcome to Flexbox.

Welcome to Flexbox.

Welcome to Flexbox.

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Price: $22
Our famous macarons stem from Danita's favorite Auntie's recipe. With this bundle, you get 14 delicious, freshly-made macarons to share, or to have on your own!
Buy Now


Products:
CSI-2140 eCommerce Template
Product Details
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Graphic Design &
Web Development
We do quality Graphic and Website design & Development delivered on time and at affordable prices.
Creative, independent and detail-oriented graphic designer,logo design and layout design. Highly skilled with
Adobe Photoshop .Coachable and passionate about collaborating with a team when working on projects


Across: 2. Enter Fife for a sunshine holiday? (9) 8. Rescuers return for vehicle (3) 10. I have article for him (3) 11. Man experiencing sympathy? (6 7) 14. Ready later? (5) 15. Riddle is about First Lady (5) 16. Expert is in best division (5) 19. Credit Queen with heart (6) 20. Covet a long-legged bird! (6) 21. Boy follows master builder (5) 22. Run and see to make certain (6) 23. Sort of light sum I do badly (6) 24. Study needs cleaning (5) 27. Turns and cuts back (5) 29. Without it, pintail is drab! (5) 30. Herod fled town in panic at Armageddon! (3 2 3 5) 32. Can a chat be so wonderful? (3) 33. Eggheads left with fish (3) 34. Edna rises in anticipation (9) Down: 1. Lout comes into a fortune! (3) 3. The French act about with great style (5) 4. Prince makes journalist draw back (6) 5. Relief for hothead at the North Pole? (3 3) 6. Wraps up pens (5) 7. Artillery force may be in tabloid (3) 9. Sounds like death softens reactions (13) 10. Bernice is bald? Amazing! (13) 12. Gone rigid, in a manner of speaking (4 5) 13. Proof in trial about part-time male soldiers (9) 16. Ready for bad dream (5) 17. Moves carefully in grease spillage (5) 18. Plant poles in river (5) 25. Joined Leeds or West Ham? (6) 26. Local gets five-er in whip-round (6) 28. Nicked fur around neck (5) 29. Turns boat in shallow water (5) 30. Swallow stewed tea?... (3) 31. ...We would return for a drop in the morning (3)


Football: Ederson doubtful for Liverpool clash after coming off against Atalanta
MILAN: Manchester City goalkeeper Ederson could be a doubt for this weekend's Premier League clash against Liverpool after being substituted at half-time in their Champions League game against Atalanta in Milan on Wednesday.
Claudio Bravo was introduced after the break for the Premier League champions.
Liverpool lead second-placed Man City by six points, and a win at Anfield on Sunday would be a massive boost for Pep Guardiola's side in their bid to defend the Premier League title.
City are already without defenders Aymeric Laporte and Oleksandr Zinchenko, while David Silva is also struggling with a thigh problem ahead of the weekend.


@(title: String)(content: Html)
Quest for Immortality
There has never been a moment until now where such an idea became even remotely possible
From stem cell therapies to personalized medicine combined with regenerative therapies
Humantiy is fast approaching the point of eliminating our greatest enemy... death itself
What can I do to help?
Romans 5:12 " Wherefore, as by one man sin entered into the world, and death by sin; and so death passed upon all men, for that all have sinned:"
Biological Immortality 4
Biological immortality is an absence of aging, specifically the absence of a sustained increase in rate of mortality as a function of chronological age. A cell or organism that does not experience aging, or ceases to age at some point, is biologically immortal.
Are there any beings like that? 5
Virus, Bacteria -- Only single celled organisms?
No -- Seeds, Fungi, Plant species, even Lobsters?
250 Years old Tortoise: Adwaita the Tortoise
Stem Cell Therapies 7
Nano Technology 8
Cybernetics 9
Qi Gong 10
Alchemy 11
Core Approach: Replace aging/defective cells with new cells
Telemerase is an enzyme found in stem cells that allow infinite replication
New born cells replicate at an astonishing rate before cells transform from stem stage
Organ regeneration, treatment of neurodegenerative diseases such as Parkinson's Alzheimer's is also possible with this approach
Core Approach: Use medical nano robots to repair aging/defective cells/organs
Nano robots is a future technology showing promise in rapid production of industrial chemicals and parts
An intended research direction is to develop medical nano robots that are designed to conduct repair work on aging cells and organs
This approach can also assist in trauma support and ensure enhanced regenerative capabilities over and beyond just repair of aging cells
Core Approach: Transfer individual personality to a durable storage media such as a robot
Taking advantage of advances in computer systems and robotics
Intention is to develop a semi-permanent or permanent electro-mechanical body to obsolete organic aging
Core Approach: Utilize body's energy fields to enhance regeneration
Ancient ideas of subtle energy fields in body referred as chakras and meridians
Utilization of breathe control assisted meditation and awareness techniques to optimize body's inherent regenerative capabilities
Core Approach: Make use of specially prepared mercury containing compounds to repair aging cells
Rasayana (Indian alchemy) texts contain 18 step processing of mercury that results in body digestible form that can be utilized for preserving life
Life preservation thought to be achieved via preservation of living essence within the body. This approach may be considered an ancient attempt at cybernetics
Rasayana quite literally means the science of life preservation


{% extends 'general/include/head_argon.html'%} {% load staticfiles %} {% load filters %} {% block main_content %}
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum.
Sed ut perspiciatis unde omnis iste natus error sit voluptatem accusantium doloremque laudantium, totam rem aperiam, eaque ipsa quae ab illo?


Before using the Mapbox renderer, you must have an access token. Get one for free here, then enter it in the Options dialog.


{% extends "Default/default.html" %} {% block content %}
If a user wishes to upload a file from a device onto the board without needing to ssh into the board this is a quick and easy to use alternative.
To upload a file simply press the grey "Browse..." button. This will open up a window on your browser allowing you to locate and add the desired file. One selected the name of the file should be shown beside the "Browse..." button. Then simply press the "Upload" and the file will be uploaded onto the board. The file can be edited or deleted. If the user wishes to edit the file, it will open up the file contents in an editor.
By pressing the "Edit Webapp" button a user will be brought to another page where they can create the front end and/or back end for their own webpage. Because the user can write both front and backend their webpage can be as complicated or simple as desired. Templates for both front and back end are provided as a starting point. In order to add a file to the webapp both a front end and back end must be created with the same name (excluding suffix) and all appropriate changes must be made that are specified in the templates.
The back end is written using the Flask microframework in Python which is based on Werkzeug and Jinja 2. More information of how to use Flask can be found here (internet connection needed to view page). The front end is in HTML which a user can embed JavaScript, CSS, Flask, and more into.
Once both front end and back end is completed you can either edit them by clicking on the name of the file on the "Webapp Reload" page, delete the files, or include them in the new webapp. To add your files to the actual webapp check the "Include" button on the files that you wish to include and press "Reload Webapp". This will return a message of success and then reboot the board. To see your changes you will have to reconnect to the boards AP again.  From your webpage the power is all in the users hands.
For any custom code a user wishes to write can be done by pressing the "Custom Project" button. This will open up the editor in which a user can create their own piece of code and run it. At the moment only Python can be ran but all other forms of code can be written and saved. The user can also change the settings of the editor if they prefer to use different backgrounds, editor types (vim, emacs, etc), or language syntax highlighting.


This is my Cat
My Cat is 3 years old and I got him from a friend who's cat had kittens.
My Cat's favorite things to do
Going outside
Sleeping
Eating
Playing with animals


Books Analysis
Starting from the queries:
- Internet Addiction
- Digital Addiction
- Social Media Addiction (abandoned throughout the analysis)
1. Each query has been typed into Amazon.com (using Google Chrome)
selecting the voice “books”. The first 200 results have been selected (approximately 20 pages each)
in order of relevance for each query
2. Once opened the first results page for each query,
the following voices have been created on Kimono:
- Title
- Author
- Data
- Reviews
- Image
In “Data Model View”, from the page “Advanced” for each voice,
“Including href” has been taken off; selecting “Crawl Setup” has been used “Manual Crawl”
and inserted the URL for the 20 following pages; once ended the Crawling the .cvs is dowloaded
3. The .csv is opened in TextWrangler,
reworked substituting “,” with “;” (dividers), then saved
as “unix (LF)-Unicode (UTF-8)”
4. Three tables have been created using Excel (one for each query)
keeping the following voices:
- Title
- Author
- Data
- Reviews
Data cleaned and fixed
5. For each result the abstract has been read (Amazon.com) and labeled “relevant" or "non-relevant",
Three labels have been associated to each voice:
Speaker, who speaks:
- Medical (1)
- Non medical (0)
Typology, what kind of text:
- Manual (1)
- Essay (2)
- Narrative (3)
Self help, do-it-yourself remedies:
- Self Help (1)
- Others (2)
The resulting file .csv has been sorted like following:
- Query
- Title
- Author
- Reviews
- Year
- Relevant
- Speaker
- Typology
- Self Help
6. Dataset has been put in Raw generating different graphics then
arranged to compose the final one


The increasing number of entities created online raises the problem of integrating and relating entities from different sources. In this work, we focus on product entities. In E-commerce, product data pose some important problems e.g., entity resolution, which is the difficult problem of matching products from one domain (e.g., Amazon) to another domain (e.g., eBay); link prediction and personalized recommendation (which product should be targeted to which user), and product canonicalization (clustering products and materializing prototypes for each cluster and sub-cluster).
There are several challenges in tackling product databases for tasks like link prediction and entity resolution. The first challenge, which mostly arises when the data is scoured from external sources like schema.org markup on webpages, is due to the poor quality of data, such as different spellings, missing values and ambiguity. This makes traditional pairwise distance measures approaches less effective with noisy content and context. The second challenge is due to the one-to-many and many-to-many relation between entities. For instance, in the product entity resolution example, a product might be associated with many prices (normal or discount), and each manufacturer is associated with many products. The heterogeneous nature of relationships brings in an additional challenge when using a collective approach such as Probabilistic Soft Logic: to determine which kind of relationship is best suited for resolving a particular type of entity.
It was usually the case that all of these different tasks (such as entity resolution and recommendation) were tackled piecemeal by researchers from different communities, without much sharing of algorithmic methodology between the communities (notwithstanding the common use of machine learning and statistical algorithms). However, with the advent of neural networks, including both deep nets but also shallower architectures like ‘skip-gram’, representation learning has emerged as a powerful unifying methodology within machine learning that takes the guesswork out of important problems like feature engineering. Many (though not all) representation learning algorithms work in an unsupervised fashion on big datasets, taking the dataset itself as input (e.g., a corpus of sentences, or a large social network or graph, which is the closest analog to the problem we are tackling) and returning continuous, low-dimensional vectors for elements in the dataset.
The E-Commerce project explores how best to learn such representations on product and E-commerce graphs in order to support tasks like entity resolution, product categorization and recommendation. Beyond algorithmic research, it is also focused on gathering resources to support open innovation in E-commerce knowledge graphs. We anticipate making available a range of resources, including datasets compiled and cleaned from sources like the Web Common Crawl, ground-truth datasets on public sources and open-source codebases on GitHub exposing graph modeling and representation learning best practices for product and E-commerce graphs.


Author: Marius Bogoevici
Level: Beginner
Technologies: Spring MVC, JSP, JPA
Summary: The spring-greeter
quickstart is based on the greeter
quickstart, but differs in that it uses Spring MVC for Mapping GET and POST requests.
Target Product: JBoss EAP
Source: https://github.com/jboss-developer/jboss-eap-quickstarts/
The application this project produces is designed to be run on Red Hat JBoss Enterprise Application Platform 7.1 or later.
The spring-greeter
quickstart is based on the greeter
quickstart, but differs in that it uses Spring MVC for Mapping GET and POST requests:
<mvc:annotation-driven\>
configured in src/main/webapp/WEB-INF/spring-mvc-context.xml
tells Spring to look for @RequestMapping
in our controllers.CreateController.java
and GreetController
Spring's XML configurations are used to get hold of the database and entity manager (via jndi) to perform transactional operations:
<tx:jta-transaction-manager/>
and <tx:annotation-driven/>
are configured in /src/main/webapp/WEB-INF/spring-business-context.xml
@Transactional
, which Spring, using aspect oriented programming, surrounds with boilerplate code to make the methods transactionalWhen you deploy this example, two users are automatically created for you: emuster and jdoe. This data is located in the src/main/resources/init-db.sql
file.
To test this example:
The application this project produces is designed to be run on Red Hat JBoss Enterprise Application Platform 7.1 or later.
All you need to build this project is Java 8.0 (Java SDK 1.8) or later and Maven 3.3.1 or later. See Configure Maven for JBoss EAP 7.1 to make sure you are configured correctly for testing the quickstarts.
For Linux: bin/standalone.sh
For Windows: bin\standalone.bat
This will deploy target/spring-greeter.war to the running instance of the server.
If you do not have maven configured you can manually copy target/spring-greeter.war to EAP7_HOME/standalone/deployments.
The application will be running at the following URL: http://localhost:8080/spring-greeter/
mvn wildfly:undeploy
Or you can manually remove the application by removing spring-greeter.war from EAP7_HOME/standalone/deployments
This quickstart provides Arquillian functional tests as well. They are located in the functional-tests/ subdirectory under the root directory of this quickstart. Functional tests verify that your application behaves correctly from the user's point of view. The tests open a browser instance, simulate clicking around the page as a normal user would do, and then close the browser instance.
To run these tests, you must build the main project as described above.
mvn clean package
Navigate to the functional-tests/ directory in this quickstart.
mvn clean verify -Parq-remote
If you prefer to run the functional tests using managed instance of the JBoss EAP server, meaning the tests will start the server for you, type the following command:
mvn clean verify -Parq-managed
You can also start the server and deploy the quickstarts or run the Arquillian tests from Eclipse using JBoss tools. For general information about how to import a quickstart, add a JBoss EAP server, and build and deploy a quickstart, see Use JBoss Developer Studio or Eclipse to Run the Quickstarts.
If you want to debug the source code or look at the Javadocs of any library in the project, run either of the following commands to pull them into your local repository. The IDE should then detect them.
mvn dependency:sources
mvn dependency:resolve -Dclassifier=javadoc


|
dynamic_graph_manager
|
this is this package namespace in order to avoid naming conflict More...
Namespaces | |
| specific | |
| Types dedicated to identify pairs of (dg,ros) data. | |
Typedefs | |
| typedef dynamicgraph::Signal< dynamicgraph::Vector, int > | OutSignal |
| typedef dynamicgraph::SignalPtr< dynamicgraph::Vector, int > | InSignal |
| typedef std::map< std::string, OutSignal * > | DeviceOutSignalMap |
| typedef std::map< std::string, InSignal * > | DeviceInSignalMap |
| typedef std::chrono::steady_clock | clock |
| clock is the std::chrono::high_resolution_clock object. More... | |
| typedef std::map< std::string, dynamicgraph::Vector > | VectorDGMap |
| VectorDGMap is a shortcut for the very long type of the map. | |
| typedef boost::posix_time::ptime | ptime |
| typedef boost::posix_time::seconds | seconds |
| typedef boost::posix_time::microseconds | microseconds |
| typedef boost::posix_time::time_duration | time_duration |
| typedef boost::gregorian::date | date |
| typedef dynamicgraph::Vector | Vector |
| typedef dynamicgraph::Matrix | Matrix |
| typedef Eigen::Transform< double, 3, Eigen::Affine > | MatrixHomogeneous |
| typedef Eigen::Matrix< double, 3, 3 > | MatrixRotation |
| typedef Eigen::AngleAxis< double > | VectorUTheta |
| typedef Eigen::Quaternion< double > | VectorQuaternion |
| typedef Eigen::Vector3d | VectorRotation |
| typedef Eigen::Vector3d | VectorRollPitchYaw |
| typedef Eigen::Matrix< double, 6, 6 > | MatrixForce |
| typedef Eigen::Matrix< double, 6, 6 > | MatrixTwist |
| typedef dynamicgraph::SignalTimeDependent< int, int > | SignalOUT |
| Simple shortcut for code writing convenience. | |
| typedef dynamicgraph::SignalPtr< dynamicgraph::Vector, int > | SignalIN |
| Simple shortcut for code writing convenience. | |
| typedef boost::function< void(int)> | callback_t |
| Simple shortcut for code writing convenience. | |
| typedef realtime_tools::RealtimePublisher< tf2_msgs::TFMessage > | TfRtPublisher |
| Renaming of the tf publisher type. | |
| typedef realtime_tools::RealtimePublisher< sensor_msgs::JointState > | JointStateRtPublisher |
| Renaming of the joint position publisher type. | |
Functions | |
| ros::NodeHandle & | ros_init (std::string node_name) |
| rosInit is a global method that uses the structure GlobalRos. More... | |
| ros::AsyncSpinner & | ros_spinner (std::string node_name) |
| ros_spinner return the async_spinner_. More... | |
| void | ros_shutdown (std::string node_name) |
| ros_shutdown shuts down ros and stop the ros spinner with the associate name | |
| void | ros_shutdown () |
| ros_shutdown shuts down ros and stop the ros spinners | |
| bool | ros_exist (std::string node_name) |
| Check if a node handle has been created or not. | |
| void | parse_yaml_node (const YAML::Node &sensors_and_controls, VectorDGMap &out_sensors_map, VectorDGMap &out_motor_controls_map) |
| parse_yaml_node allows to parse the yaml node to create the according maps of dynamicgraph::Vector. More... | |
| void | makeHeader (std_msgs::Header &header) |
| template<typename D , typename S > | |
| void | converter (D &dst, const S &src) |
| Handle ROS <-> dynamic-graph conversion. More... | |
| DG_TO_ROS_IMPL (double) | |
| ROS_TO_DG_IMPL (double) | |
| DG_TO_ROS_IMPL (unsigned int) | |
| ROS_TO_DG_IMPL (unsigned int) | |
| DG_TO_ROS_IMPL (Vector) | |
| ROS_TO_DG_IMPL (Vector) | |
| DG_TO_ROS_IMPL (specific::Vector3) | |
| ROS_TO_DG_IMPL (specific::Vector3) | |
| DG_TO_ROS_IMPL (Matrix) | |
| ROS_TO_DG_IMPL (Matrix) | |
| DG_TO_ROS_IMPL (MatrixHomogeneous) | |
| ROS_TO_DG_IMPL (MatrixHomogeneous) | |
| DG_TO_ROS_IMPL (specific::Twist) | |
| ROS_TO_DG_IMPL (specific::Twist) | |
| DG_BRIDGE_TO_ROS_MAKE_STAMPED_IMPL (specific::Vector3, vector, ;) | |
| DG_BRIDGE_TO_ROS_MAKE_STAMPED_IMPL (MatrixHomogeneous, transform, dst.child_frame_id="";) | |
| DG_BRIDGE_TO_ROS_MAKE_STAMPED_IMPL (specific::Twist, twist, ;) | |
| DG_BRIDGE_MAKE_SHPTR_IMPL (double) | |
| DG_BRIDGE_MAKE_SHPTR_IMPL (unsigned int) | |
| DG_BRIDGE_MAKE_SHPTR_IMPL (Vector) | |
| DG_BRIDGE_MAKE_SHPTR_IMPL (specific::Vector3) | |
| DG_BRIDGE_MAKE_SHPTR_IMPL (Matrix) | |
| DG_BRIDGE_MAKE_SHPTR_IMPL (MatrixHomogeneous) | |
| DG_BRIDGE_MAKE_SHPTR_IMPL (specific::Twist) | |
| DG_BRIDGE_MAKE_STAMPED_IMPL (specific::Vector3, vector, ;) | |
| DG_BRIDGE_MAKE_STAMPED_IMPL (MatrixHomogeneous, transform, ;) | |
| DG_BRIDGE_MAKE_STAMPED_IMPL (specific::Twist, twist, ;) | |
| DG_BRIDGE_MAKE_STAMPED_SHPTR_IMPL (specific::Vector3, vector, ;) | |
| DG_BRIDGE_MAKE_STAMPED_SHPTR_IMPL (MatrixHomogeneous, transform, ;) | |
| DG_BRIDGE_MAKE_STAMPED_SHPTR_IMPL (specific::Twist, twist, ;) | |
| template<typename U , typename V > | |
| void | converter (U &dst, V &src) |
| If an impossible/unimplemented conversion is required, fail. More... | |
| boost::posix_time::ptime | rosTimeToPtime (const ros::Time &rosTime) |
| ros::Time | pTimeToRostime (const boost::posix_time::ptime &time) |
| std::string | makeSignalString (const std::string &className, const std::string &instanceName, bool isInputSignal, const std::string &signalType, const std::string &signalName) |
| void | buildFrom (const MatrixHomogeneous &MH, MatrixTwist &MT) |
| template<> | |
| void | RosPublish::sendData< std::pair< MatrixHomogeneous, Vector > > (boost::shared_ptr< realtime_tools::RealtimePublisher< DgToRos< std::pair< MatrixHomogeneous, Vector > >::ros_t > > publisher, boost::shared_ptr< DgToRos< std::pair< MatrixHomogeneous, Vector > >::signalIn_t > signal, int time) |
| DYNAMICGRAPH_FACTORY_ENTITY_PLUGIN (DeviceSimulator, "DeviceSimulator") | |
| dynamic_graph::Device::CLASS_NAME must be the name as the actual device class. | |
| ostream & | operator<< (ostream &os, const ExceptionAbstract &error) |
| DYNAMICGRAPH_FACTORY_ENTITY_PLUGIN (RosPublish, "RosPublish") | |
| DYNAMICGRAPH_FACTORY_ENTITY_PLUGIN (RosQueuedSubscribe, "RosQueuedSubscribe") | |
| DYNAMICGRAPH_FACTORY_ENTITY_PLUGIN (RosRobotStatePublisher, "RosRobotStatePublisher") | |
| DYNAMICGRAPH_FACTORY_ENTITY_PLUGIN (RosRobotStatePublisherMt, "RosRobotStatePublisherMt") | |
| DYNAMICGRAPH_FACTORY_ENTITY_PLUGIN (RosSubscribe, "RosSubscribe") | |
| DYNAMICGRAPH_FACTORY_ENTITY_PLUGIN (RosTfListener, "RosTfListener") | |
| DYNAMICGRAPH_FACTORY_ENTITY_PLUGIN (RosTime, "RosTime") | |
Variables | |
| static std::map< std::string, std::unique_ptr< GlobalRos > > | GLOBAL_ROS_VAR |
| GLOBAL_ROS_VAR is global variable that acts as a singleton on the ROS node handle and the spinner. More... | |
| static const int | queueSize = 5 |
this is this package namespace in order to avoid naming conflict
| typedef std::chrono::steady_clock dynamic_graph::clock |
clock is the std::chrono::high_resolution_clock object.
This typedef is here as a shortcut to simplify the code readability.
| void dynamic_graph::converter | ( | D & | dst, |
| const S & | src | ||
| ) |
Handle ROS <-> dynamic-graph conversion.
Implements all ROS/dynamic-graph conversions required by the bridge.
Relies on the DgToRos type trait to make sure valid pair of types are used.
|
inline |
If an impossible/unimplemented conversion is required, fail.
IMPORTANT, READ ME:
If the compiler generates an error in the following function, this is /normal/.
This error means that either you try to use an undefined conversion. You can either fix your code or provide the wanted conversion by updating this header.
| void dynamic_graph::parse_yaml_node | ( | const YAML::Node & | sensors_and_controls, |
| VectorDGMap & | out_sensors_map, | ||
| VectorDGMap & | out_motor_controls_map | ||
| ) |
parse_yaml_node allows to parse the yaml node to create the according maps of dynamicgraph::Vector.
| [in] | sensors_and_controls | is the node that contains the hardware info. |
| [out] | out_sensors_map | is the map that contains the sensors data. |
| [out] | out_motor_controls_map | is the map that contains the motor controls data. |
| ros::NodeHandle & dynamic_graph::ros_init | ( | std::string | node_name | ) |
rosInit is a global method that uses the structure GlobalRos.
Its role is to create the ros::nodeHandle and the ros::spinner once at the first call. It always returns a reference to the node hanlde.
call ros::init
ros::NodeHandle instanciation
If spinner is not created we create it. Here we can safely assume that ros::init was called before.
create the spinner
run the spinner in a different thread
Return a reference to the node handle so any function can use it
call ros::init
ros::NodeHandle instanciation
If spinner is not created we create it. Here we can safely assume that ros::init was called before.
create the spinner
run the spinner in a different thread
Return a reference to the node handle so any function can use it
| ros::AsyncSpinner & dynamic_graph::ros_spinner | ( | std::string | node_name | ) |
ros_spinner return the async_spinner_.
Call dynamic_graph ros_init if ros has not been initialized
|
static |
GLOBAL_ROS_VAR is global variable that acts as a singleton on the ROS node handle and the spinner.
The use of the std::unique_ptr allows to delete the object and re-create at will. It is usefull to reset the ros environment specifically for unittesting.
If the node handle does not exist we call the global method ros::init. This method has for purpose to initialize the ROS environment. The creation of ROS object is permitted only after the call of this function. After ros::init being called we create the node hanlde which allows in turn to advertize the ROS services, or create topics (data pipe).


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$93.6M awarded to former Port Terminal operator for losses
PORTLAND, Ore. (AP) - A federal jury has awarded $93.6 million to the former operator of the Port of Portland’s container terminal, finding the dock workers union sabotaged shipping traffic through years of labor slowdowns and stoppages.
The Oregonian/OregonLive reports the Philippine-owned ICTSI Oregon, which signed a 25-year lease in 2010 to operate Terminal 6, left the port in 2017.
The company says the terminal was idled by labor strife it says the International Longshore and Warehouse Union and its Local 8 chapter encouraged.
That marked the effective end to Oregon’s only container terminal assessible by large ocean-crossing cargo vessels.
The verdict followed a civil trial before U.S. District Judge Michael H. Simon in Portland and years of disputes in court and before the National Labor Relations Board.
The union’s lawyers said declines in productivity at Terminal 6 resulted from a range of factors: market forces, geographic limitations of the port situated so far inland with a shallow river depth for big vessels and dismissive management that caused a demoralized workforce.
Information from: The Oregonian/OregonLive, http://www.oregonlive.com
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