The first single off our upcoming EP is out now, and we just wrapped shooting the video. Check out the track!
CØASTLINE is a pop punk band based in the Sarasota area. Forming just over a year ago, the band has released a single and is currently hard at work producing their first EP.
Born and raised in North Port, seemingly an unassuming man. By day, a boring insurance agent, but when the sun goes down he can be found at “Laundry Room Studios” -- aka his laundry room -- playing drums, laying down backup vocals, and engineering some audio.
“I liked to bang on pots and pans as a child and always was tapping.” And thanks to his loving parents, nudging him to practice and take lessons, EJ went from banging on pots and pans to making Drumline Captain by his senior year of high school. Combine all the years of experience + his exceptional speed and power = the badass drummer we see today.
When he’s not banging on the drums, he enjoys banging himself up at the North Port Skate Park riding BMX bikes.
Follow his adventures on Insta @ej_coastline
In his own words, “I bring the awkward”. Born a Floridian, and raised in SC, he decided it was time to come back to his roots.
Chris brought with him an uncanny ability to write an array of brilliant and witty original music. Was it mentioned that he also has a voice so sexy all the guys and girls swoon? *swoon*
Anytime he’s not being a videographer, making “the silky smooth videos for the virals”, he moonlights as a professional cookie eater. However, his passion for cookies is no match for his love of Mike Myers, who has inspired him to be the goofball we know and love.
When writer’s block sets in, or his vocals are fried, he enjoys bird watching, while eating cookies.
FanBoy him on Instas @chris_coastline
FanGirl him on FB ChrisLawENT
Like Father, like son. “My Dad played, and guitars were always around the house growing up.” It might have also helped that he was born in New Orleans, the birthplace of jazz. Which also explains why he’s a die hard Saints fan -- Geaux Saints!
The biggest influencer in Keith’s life was his Dad, passing along his passions and values. As the years rolled on, other artists were an inspiration, including Kurt Cobain and Billie Joe Armstrong. You can hear, and see, traces of all of them throughout his lyrical riffs and in his technique.
On the weekends, after horticulture’ing all week, he can be found out on a boat, or golfing at one of the many courses in Sarasota. And after a long day out in the FL sunshine, he likes to chill at one of our local breweries.
Among his other interests, he counts traveling and popping into record stores he happens upon.
Stalk him on Instagram @keith_coastline
A rare specimen, 2nd generation Floridian, Wayne is the band’s bass mechanic.
His musical influences range from punk to funk, encompassing bands as far afield as Vulfpeck, Rancid, and Rage Against the Machine. He occasionally lends an ear down at Roseland Park Studios, helping out with audio engineering or sitting in as a session bassist.
After a fun-filled day making sure websites are mostly not on fire, he likes to unwind by playing video games, listen to music, and watching soccer.
Forget you follow him on Instagram @wayne_coastline


GLAM defines a right-handed Cartesian coordinate space with the positive x-axis pointing to the right, the positive y-axis pointing up, and the positive z-axis pointing out of the screen. See Figure 1.
GLAM uses a single unit measure, the meter. Unlike 2D CSS coordinates, there is no concept of pixel, point, or other non-physical measurements such as em spaces. Conversions from CSS physical units other than meters (cm, mm, inch) can be achieved by using 3D scaling transformations.
Elements in the scene graph inherit the transform properties of their ancestors. All visual and transformable elements are transformed by composing their transforms (known as local space transforms) with the transforms of their ancestor grouping elements to create the final transformation of the element in the global coordinate system (or world space ). This nested composition of transforms is known as the transformation hierarchy.
The following example creates a 'group' element, GROUP1, that is rotated by 30 degrees about its Y-axis. The mesh that is a direct descendant of GROUP1 is thus also rotated. A second group, GROUP2 is also a descendant of GROUP1. GROUP2 is also rotated about the Y-axis by 30 degrees, and is additionally scaled on the X-axis. GROUP2 contains a child mesh element that, because of the hierarchy of transforms under which it is defined, will be rotated about the Y-axis and scaled along the X-axis.
<style>
#GROUP1 {
transform: rotateY(30deg);
}
#GROUP2 {
transform: translate3d(2, 1, 0) scaleX(2);
}
</style>
<glam>
<scene>
<group id='GROUP1'>
<mesh></mesh>
<group id='GROUP2'>
<mesh></mesh>
</group>
</group>
</scene>
</glam>
Camera elements define a position and direction from which the scene is viewed, and a viewing angle (field of view) for perspective rendering. Cameras also define near and far clipping planes to create a viewing volume outside of which no objects are visible. The following fragment defines a perspective camera with a 60 degree field of view, a near clipping plane at z=.01 units, and a far clipping plane at z=100000 units.
<camera fov='60deg' near='.01' far='100000'></camera>
Both perspective and orthographic camera types are supported.
A GLAM document does not require a camera element to render the scene. If no camera element is present, the implementation provides a default perspective camera element with default values.
The GLAM scene is ultimately rendered to a 2D surface within the client window, also known as the viewport. The viewport is a a rectangular subregion corresponding to the entire bounds of the GLAM root element.
The camera parameters, taken together with the viewport definition, determine how 3D graphics are transformed from 3D world space into 2D screen space. For perspective cameras, a perspective projection is performed as depicted in Figure 1.
GLAM defines several visual elements, including geometric solids such as boxes and spheres, 3D text, triangle meshes, points, lines and particle systems. There are also supporting elements which define the 3D data for these types, e.g. vertices, normals, colors and texture coordinates.
GLAM defines common geometric solids, or primitives: boxes, cones, cylinders and spheres. These elements are shorthand for creating triangle meshes of the same shape. Once created, these elements can be accessed with the mesh DOM interfaces described in the reference.
Triangle meshes are defined as a set of vertices and triangular faces. Child elements of the mesh include the vertices element and faces element, which define the basic shape. Additional elements are used to define texture coordinates (uvs), normals and colors for the mesh.
The following fragment creates a mesh in the shape of rectangle made out of two triangular faces.
<mesh>
<vertices>-.5 -.5 0 .5 -.5 0 .5 .5 0 -.5 .5 0</vertices>
<normals>0 1 1 0 0 1</normals>
<uvs>0 0 1 0 1 1 0 0 1 1 0 1</uvs>
<faces>0 1 2 0 2 3</faces>
</mesh>
The vertices and faces elements are required to define a mesh; the normals, uvs, and colors elements are optional. If they are not supplied GLAM will supply defaults and/or generate appropriate values.
GLAM supports the creation of text rendered as polygons. The 'text' element is shorthand for creating triangle meshes of the same shape. Once created, the polygons in the text element can be accessed with the mesh DOM interfaces described elsewhere. The text value rendered is supplied in the textContent property of the element.
Text can be flat or extruded. There are also several CSS properties used to control beveling when text is extruded.
The following example creates a an extruded, beveled text element that displays the text "GLAM" using the Helvetica font.
<head>
<style>
#text1 {
font-depth:0.5;
font-bevel:bevel;
bevel-size:.01;
bevel-thickness:.02;
font-family:helvetica;
}
</style>
</head>
<glam>
<scene>
<text id="text1">GLAM</text>
</scene>
</glam>
GLAM supports sets of rendered points. Points contain 'vertices', 'colors' and 'sizes' elements, which the specify those respective properties. The following fragment defines a point set of four points of default size, colored red, green, yellow and blue, respectively.
<points id="points1">
<vertices>-.5 -.5 0 .5 -.5 0 .5 .5 0 -.5 .5 0</vertices>
<colors>1 0 0 0 1 0 0 1 1 0 0 1</colors>
<points>
The 'colors' element is not required; if all points in the point set are the same color, the color of the points' material can be used instead.
GLAM supports sets of rendered lines. Lines contain 'vertices' and 'colors' elements, which the specify those respective properties. The following fragment defines a line set that draws a rectangular outline with colors red, green, cyan, and blue.
<lines id="line1">
<vertices>-.5 -.5 0 .5 -.5 0 .5 .5 0 -.5 .5 0 -.5 -.5 0</vertices>
<colors>1 0 0 0 1 0 0 1 1 0 0 1 1 0 0</colors>
<lines>
The 'colors' element is not required; if all lines in the line set are the same color, the color of the lines' material can be used instead.
The surface color of GLAM objects is computed by combining their material values with lights in the scene in a process known as shading.
For authoring convenience, several built-in shading models based on common 3D graphics techniques are defined:
Authors may also choose to implement their own shading by using programmable shaders.
Materials define the surface properties of meshes and the color properties of points and lines. Using a material on an object determines the shading model that will be applied to render the object. GLAM defines a set of built-in materials based on its built-in shading models: blinn/phong, lambert and unlit.
Authors specify materials via CSS. The type of material is specified using the CSS property shader. Valid values are phong, lambert, and unlit.
GLAM uses the CSS Level 3 Color Module color model for all visual and material color values.
Depending on the type of material, the following CSS properties can be used:
In the following example, the sphere primitive sphere1 is styled with a phong-shaded material that has a diffuse texture map, a normal map (together specified in the image property), and a light gray diffuse color (the color property):
#sphere1 {
shader:phong;
image:diffuse url(./images/earth.jpg) normal url(./images/earth-normal.jpg);
color:lightgray;
}
Lights are elements that define lighting characteristics of the scene. Light values are combined with material values to shade objects.
For authoring convenience, several built-in light types based on common 3D graphics usage are defined:
The following fragment demonstrates scene lighting for each type:
<light id="ambLight1" type='ambient'></light>
<light id="dirLight1" type='directional' dz='0' dy='-1' dx='0'></light>
<light id="pointLight1" type='point'></light>
<light id="spotLight1" type='spot' angle='15deg' exponent='1'></light>
The type attribute specifies the light type. Each type of light defines different attributes, though some attributes are shared among some lights. For example, both directional lights and spot lights define attributes dx, dy and dz for the x, y and z components of the lights' direction vectors, respectively.
Light elements are transformable, i.e. they can be positioned and oriented using transform properties, and they inherit the transforms of their ancestors. Light colors are specified in CSS using the color property.
Authors may also choose to implement their own light types for use with custom shading models by using programmable shaders.
GLAM allows authors to access the programmable pipeline in order to define custom shading models, deform geometry, animate the scene, and implement many other effects. This is done by creating programmable shaders as a combination of GLSL programs and CSS material properties that bind the rendered element to the shader program.
The following CSS fragment defines a class, fresnel, for shading objects using a fresnel shader program.
.fresnel {
vertex-shader:url(./shaders/fresnel.vs);
fragment-shader:url(./shaders/fresnel.fs);
shader-uniforms:mRefractionRatio f 1.02 mFresnelBias f 0.1 mFresnelPower f 2.0 mFresnelScale f 1.0 tCube t cube;
}
Because GLAM supplies out-of-the-box behavior, it by necessity has to maintain internal state of the scene graph that a shader may need to access as uniforms. Examples of this include the world matrix for each object, the inverted view matrix for the active camera, and the world space position values and colors of lights. The specification defines several uniforms that are reserved words for use in the shader-uniforms property (i.e. not allowed to be specified in the property). Some examples of built-in uniform reserved words:
For complete information, refer to the section on predefined uniform declarations.
GLAM provides authors a way to embed external 3D models and scenes into the main scene. This data is stored in other standard 3D formats such as OBJ, COLLADA or glTF. This is analogous to embedding image files in JPEG or PNG format into a 2D HTML document. GLAM is not designed for compact representation, but rather for ease of authoring and interactivity. Therefore, as a practical matter it will often be desirable to embed models in formats. GLAM achieves this through use of imports.
The following example shows a GLAM scene that imports an OBJ model and adds a camera. The import element's src property specifies a URI to the imported scene file.
<glam>
<scene>
<import id="imported_scene" src="./models/model.obj">
</import>
<camera></camera>
</scene>
</glam>
A GLAM scene can contain any number of 'import' elements. This is useful for importing multiple models into the same scene. 'import' elements can be transformed (translated, rotated, scaled) and animated just like any other GLAM element.
GLAM defines new DOM event types for handling 3D interaction with the scene. These events generate 3D picking information
MouseEvent3D is a superset of MouseEvent that adds the following properites:For touch input, TouchEvent3D extends TouchEvent by containing an array of Touch3D objects instead of 2D Touch objects. Each Touch3D contains the 3D new properties defined by MouseEvent3D (see above).
The following JavaScript pseudocode listens for MouseEvent3D events on a mesh, placing an arrow that points out of the object along the intersected normal, from the point of intersection:
mesh.addEventListener("click", function(event) {
// handle click event by calling a user-defined function
// that adds geometric annotations to the scene graph
addNormalToMesh(mesh, event.point, event.normal);
});
GLAM defines events for when the camera is looking at an object; that is, when the ray cast from the camera position to the back plane of the view frustrum intersects an object. The events viewover and viewout are generated when the ray first interesects the object, and when it stops intersecting the object, respectively.
3D viewing events are generally useful, but in particular are quite valuable in virtual reality applications, where the object is being looked at is used as a selection mechanism.
The following JavaScript code fragment listens for viewover and viewout events on a sphere, using that to save away which sphere is being looked at:
sphereelt.addEventListener("viewover", function(event) {
selectedBubble = groupelt;
});
sphereelt.addEventListener("viewout", function(event) {
selectedBubble = null;
});
For complete information on 3D input events, refer to the Events Reference.
3D animation can be used to animate GLAM elements over time. 3D animation is not limited to transform values. Any element's attribute or CSS property can be animated to create a 3D special effect, such as colors, opacity and material uniforms for shaders.
Standard CSS Animations can be applied to animate GLAM elements over time. The following CSS fragment defines a keyframe animation to rotate the cube cube1 about its y-axis over a 10-second duration with looping:
/* keyframe animation for the cube: 10-second looping rotation about y-axis */
@keyframes kfRotateY {
from {
transform: rotateY(0deg);
}
to {
transform: rotateY(360deg);
}
}
#cube1 {
animation-duration: 10s;
animation-name: kfRotateY;
animation-iteration-count: infinite;
animation-timing-function:linear;
}
GLAM elements can also be animated using the 'animation' element, a tag that can be defined within the GLAM document. This not only provides an alternate, more concise syntax, but is ultimately intended to support animation data that cannot be defined using the CSS animation standard.
Animations are defined using a combination of the 'animation' element and 'keyframe' elements to define the individual keyframes. Animations are bound to an element by setting the element's animation attribute.
The following example animates cube1 about its y-axis over a 10-second duration with looping:
<glam>
<scene>
<box id="photocube" animation="animRotateY"></box>
<animation id="animRotateY" duration="10s" iteration-count="infinite" timing-function="linear">
<keyframe time="0%" property="transform" value="rotateY(0deg);"></keyframe>
<keyframe time="50%" property="transform" value="rotateY(180deg);"></keyframe>
<keyframe time="100%" property="transform" value="rotateY(360deg);"></keyframe>
</animation>
</scene>
</glam>
3D transitions are a good way to produce one-shot effects such as changing a color from one value to another over time (also known as a tween).
Rather than requiring the programmer to implement mouse-based control of a scene, for example to rotate a model or walk through a scene, GLAM provides built-in behavior in the form of camera controllers:
Controllers are added to a scene using the 'controller' element. This element has a type attribute that defines the interaction type, with valid values of "FPS" and "model".
By default, GLAM creates a camera controller with type "model" so that simple scenes and models can be rotated with the mouse or touch device.
GLAM renders scenes using WebGL. By default, GLAM scenes are rendered in mono, but this behavior can be overridden using the <renderer> element and setting the type attribute to one of the following values:
For example, the following GLAM document fragment renders a scene in side-by-side stereo for Google Cardboard:
<glam>
<scene>
<renderer type="cardboard"></renderer>
<controller type="deviceOrientation"></controller>
<background id="sb1" class="skybox"></background>
</scene>
</glam>
In the future, GLAM may support Perhaps other rendering models such as physically based and deferred.
GLAM scenes can be rendered in multiple layers that are blended (or composited) back-to-front. Currently this is only used to render backgrounds via the <background> element but it may be used to support additional layer types in the future.
Background elements use cube map or spherical images to render an infinitely far away backdrop that re-orients with changes to the camera's orientation. The following example creates a spherical background for a scene using the <background> element and the sphere-image CSS property:
<style>
#ss1 {
sphere-image:url(../../images/spherepano/pan0.jpg);
}
</style>
<glam>
<scene>
<background id="ss1" type="sphere"></background>
</scene>
</glam>
GLAM scenes support multi-pass postprocessing effects. Rather than the having to explicitly render the scene in multiple passes to achieve the desired effect, the developer can create effects simply by adding tags to the GLAM document.
This feature is still experimental; only a few effects are currently supported. The following example shows the <effect> element used to define various effects, only one of which, the "Bloom" effect, is active for the scene. The disabled property is used to disable a specific effect. If multiple effects are enabled, they will be active and rendered in the order the elements appear in the GLAM document.
<effect type="Film" grayscale="0" disabled></effect>
<effect type="DotScreenRGB" scale="3" disabled></effect>
<effect type="Bloom" strength="3"></effect>
<effect type="RGBShift" amount=".005" disabled></effect>
<effect> elements can be placed anywhere in the scene, for example in child elements of a group, for convenience. They are not affected by the transform hierarchy.
The CSS layout rules for the page stop at the root <glam> element. For all descendants of the GLAM element, the CSS properties specify 3D scene graph units, not page units. With the exception of 3D transforms, standard CSS layout properties do not apply.
GLAM uses the existing CSS transform property to place objects in the 3D scene. GLAM also uses the CSS Animations and CSS Transitions properties to dynamically animate or transition property values. For more information, see 3D animation.
Visual properties specify values for various visual elements such the width of lines and sizes of points, e.g. dash-size, gap-size, line-width, and point-size.
GLAM defines new CSS properties to control the appearance of 3D extruded text, including bevel and thickness, including bevel-size, bevel-thickness, font-bevel and font-depth.
GLAM defines several new CSS properties for controlling the material of a visual element:


Harry Redknapp suggests Chris Wilder and Eddie Howe as potential Arsenal bosses
Current Gunners boss Unai Emery is coming under serious pressure right now.
by Sam PrestonFormer Tottenham manager Harry Redknapp has named Eddie Howe and Chris Wilder as options to manage Arsenal as Unai Emery comes under increasing pressure.
Wilder, 52, led Sheffield United to a 1-0 win over Arsenal at Bramall Lane last month, while Howe has been impressing in the Premier League with Bournemouth since 2015.
In the Daily Mail, Redknapp said: “I’ve got to be honest, I don’t think Emery can turn things around. What amazes me, every time a top managerial job comes up, you have to go to someone big. That about the kid at Sheffield United, [Chris] Wilder, what about Eddie Howe? These kind of people.
“You haven’t got to be a genius to look at Arsenal and go hang on, they need a couple of central defenders and they need a midfielder player, but they keep buying forwards.”
TBR’s View – Wilder or Howe would do a better job of offering an identity and fixing Arsenal’s weaknesses
Howe’s Bournemouth side have had a clear identity for a number of years and are now working on the defensive side of their game.
Emery’s Arsenal do not have a clear idea of what they’re trying to do, in either attack or defence, unlike Wilder’s Sheffield United side, who were superior in every aspect back in October.
That said, it’s unlikely they will be on the shortlist whenever Emery is removed from his post, because they will seek European experience because the club wants to get back into the Champions League.
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Let us know


new Authenticator()
Google Authenticator adapter
References
- http://en.wikipedia.org/wiki/Google_Authenticator
Algorithm
secret := base32decode(secret)
message := floor(current Unix time / 30)
hash := HMAC-SHA1(secret, message)
offset := last nibble of hash
truncatedHash := hash[offset..offset+3] //4 bytes starting at the offset
set the first bit of truncatedHash to zero //remove the most significant bit
code := truncatedHash mod 1000000
pad code with 0 until length of code is 6
return code
- Since:
- 3.0.0
- License:
- MIT
- Source:
Extends
Members
chart :string
Type:
- string
- Source:
epoch :number
Type:
- number
- Inherited From:
- Source:
step :number
Type:
- number
- Overrides:
- Source:


Note
Click here to download the full example code or run this example in your browser via Binder
Comparing randomized search and grid search for hyperparameter estimation¶
Compare randomized search and grid search for optimizing hyperparameters of a random forest. All parameters that influence the learning are searched simultaneously (except for the number of estimators, which poses a time / quality tradeoff).
The randomized search and the grid search explore exactly the same space of parameters. The result in parameter settings is quite similar, while the run time for randomized search is drastically lower.
The performance is slightly worse for the randomized search, though this is most likely a noise effect and would not carry over to a held-out test set.
Note that in practice, one would not search over this many different parameters simultaneously using grid search, but pick only the ones deemed most important.
Out:
RandomizedSearchCV took 4.14 seconds for 20 candidates parameter settings.
Model with rank: 1
Mean validation score: 0.934 (std: 0.024)
Parameters: {'bootstrap': False, 'criterion': 'entropy', 'max_depth': None, 'max_features': 7, 'min_samples_split': 3}
Model with rank: 2
Mean validation score: 0.932 (std: 0.024)
Parameters: {'bootstrap': False, 'criterion': 'gini', 'max_depth': None, 'max_features': 6, 'min_samples_split': 6}
Model with rank: 3
Mean validation score: 0.932 (std: 0.021)
Parameters: {'bootstrap': False, 'criterion': 'entropy', 'max_depth': None, 'max_features': 4, 'min_samples_split': 2}
GridSearchCV took 12.51 seconds for 72 candidate parameter settings.
Model with rank: 1
Mean validation score: 0.935 (std: 0.019)
Parameters: {'bootstrap': False, 'criterion': 'entropy', 'max_depth': None, 'max_features': 10, 'min_samples_split': 2}
Model with rank: 2
Mean validation score: 0.933 (std: 0.030)
Parameters: {'bootstrap': False, 'criterion': 'entropy', 'max_depth': None, 'max_features': 3, 'min_samples_split': 2}
Model with rank: 3
Mean validation score: 0.930 (std: 0.025)
Parameters: {'bootstrap': True, 'criterion': 'gini', 'max_depth': None, 'max_features': 10, 'min_samples_split': 2}
print(__doc__)
import numpy as np
from time import time
from scipy.stats import randint as sp_randint
from sklearn.model_selection import GridSearchCV
from sklearn.model_selection import RandomizedSearchCV
from sklearn.datasets import load_digits
from sklearn.ensemble import RandomForestClassifier
# get some data
X, y = load_digits(return_X_y=True)
# build a classifier
clf = RandomForestClassifier(n_estimators=20)
# Utility function to report best scores
def report(results, n_top=3):
for i in range(1, n_top + 1):
candidates = np.flatnonzero(results['rank_test_score'] == i)
for candidate in candidates:
print("Model with rank: {0}".format(i))
print("Mean validation score: {0:.3f} (std: {1:.3f})".format(
results['mean_test_score'][candidate],
results['std_test_score'][candidate]))
print("Parameters: {0}".format(results['params'][candidate]))
print("")
# specify parameters and distributions to sample from
param_dist = {"max_depth": [3, None],
"max_features": sp_randint(1, 11),
"min_samples_split": sp_randint(2, 11),
"bootstrap": [True, False],
"criterion": ["gini", "entropy"]}
# run randomized search
n_iter_search = 20
random_search = RandomizedSearchCV(clf, param_distributions=param_dist,
n_iter=n_iter_search)
start = time()
random_search.fit(X, y)
print("RandomizedSearchCV took %.2f seconds for %d candidates"
" parameter settings." % ((time() - start), n_iter_search))
report(random_search.cv_results_)
# use a full grid over all parameters
param_grid = {"max_depth": [3, None],
"max_features": [1, 3, 10],
"min_samples_split": [2, 3, 10],
"bootstrap": [True, False],
"criterion": ["gini", "entropy"]}
# run grid search
grid_search = GridSearchCV(clf, param_grid=param_grid)
start = time()
grid_search.fit(X, y)
print("GridSearchCV took %.2f seconds for %d candidate parameter settings."
% (time() - start, len(grid_search.cv_results_['params'])))
report(grid_search.cv_results_)
Total running time of the script: ( 0 minutes 16.754 seconds)


--- layout: default ---
Welcome to the official website of Data Science Africa
Data from a vast array of sources is becoming available in many African countries. Machine learning and analysis are being applied to solve real problems on the ground.
We at Data Science Africa aim to create a hub in the network of data science researchers across Africa, by,


NOTE: For this example to work you have to run it in a web server context. This example shows both the current plan and the original baseline. To see the data loaded into the gantt chart, click these links:
Note that the js for the example code is not minified so it is readable. See baseline.js.


procedure_kind procedure[entity ret, entity arg1, entity arg2] {
^^^^^^^^^
testdata/bootstrap.i:198: Primary type already defined
procedure_kind procedure[entity ret, entity arg1] {
^^^^^^^^^
testdata/bootstrap.i:194: This is the primary
procedure_kind function[entity ret, entity arg1, entity arg2] {
^^^^^^^^
testdata/bootstrap.i:208: Primary type already defined
procedure_kind function[entity ret, entity arg1] {
^^^^^^^^
testdata/bootstrap.i:203: This is the primary
interface collection[data element] {
^^^^^^^^^^
testdata/bootstrap.i:255: Primary type already defined
interface collection[value element] {
^^^^^^^^^^
testdata/bootstrap.i:227: This is the primary
test
Root type in the ideal type system.
It is the supertype of value and reference.
There should be no need to subtype entity directly; in fact,
it's unlikely that you'll use this type in your code at all.
concept entity
pass
Root type for regular values (as opposed to references).
Before using this type as a direct supertype, consider
whether your objects satisfy the contract for the data type.
Subtypes of data have library support for a lot of useful functionality.
Data is a value that can be fully represented by bits.
It can be serialized for persistent storage or transfer
over the network. The fields of the data object must
also be data. Most entities in a typical program--such
as integers and strings--are data.
The library provides a lot of functionality for subtypes of data,
such as equivalence predicates, hash functions, and serializers.
Examples of values that are not data are a clock or a file
descriptor--since they refer to entities that cannot be packaged and
sent over the network.
Related concepts in Java are Serializable and Cloneable.
Describes types that have a natural equivalence relation,
such as an integer. There are types for which multiple good
equivalence relationships exist--consider a modifiable sequence, that
can be compared either element-by-element or by reference.
On the other hand, for an immutable sequence
element-by-element comparison makes more sense.
When obviously best choice doesn't exist, it is preferrable to
force the programmer to make decision which equivalence relation
to use explicitly. Data structures have been designed to
allow the relation to be selected.
For operators == and != to work on values of a type, the type
must implement this interface.
A type that has two values: true and false.
Logical operators and, or, not, xor are defined
on the type. Note that and and or operators
are short-circuiting: if the second operand
can't affect the value of the result, it's not
evaluated, as is the case when the first operand to and is false.
An integer value with an unlimited range. The runtime
should hide the distinction between integers that can be
represented as one machine word and arbitrary-precision integers
(bigints).
When integers with a specific representation are needed,
types such int32 from ideal.library.interop should be used.
A type whose values are distinct from valid values of other types.
Unlike many languages in which null is a value, in ideal
null is type, and values are specific--missing, not_applicablenot_a_number and so on. The motivation behind this is to allow
the programmer to specify the nature of the exceptional value.
Developers can subtype null if necessary, though the
need for this should be quite rare.
The check for null should be of the form if (x is null).
The program shouldn't depend on what type of null value is being returned.
A subroutine that given values as arguments, returns a value
that is a result of computation. The arguments of the type
are interpreted as follows: the first argument is the type of
return value, the second through last argument types correspond
to first through last arguent type of procedure. For example,
procedure[boolean, integer] is a procedure that takes an integer
argument and returns boolean.


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| Concept Framework 2.2 documentation | Contents | Index |
| Name | Version | Deprecated |
| fopen | version 1.0 | no |
| number fopen(string filename, string mode) |
| filename | [in] Filename |
| mode | [in] Type of access permitted |
|
The fopen function opens the file specified by filename.
The function returns a number representing the file descriptor for the open file. A null value indicates an error. The character string mode specifies the type of access requested for the file, as follows: "r" Opens for reading. If the file does not exist or cannot be found, the fopen call fails. "w" Opens an empty file for writing. If the given file exists, its contents are destroyed. "a" Opens for writing at the end of the file (appending) without removing the EOF marker before writing new data to the file; creates the file first if it doesn't exist. "r+" Opens for both reading and writing. (The file must exist.) "w+" Opens an empty file for both reading and writing. If the given file exists, its contents are destroyed. "a+" Opens for reading and appending; the appending operation includes the removal of the EOF marker before new data is written to the file and the EOF marker is restored after writing is complete; creates the file first if it doesn't exist. In addition to the above values, the following characters can be included in mode to specify the translation mode for newline characters: b Open in binary (untranslated) mode; translations involving carriage-return and linefeed characters are suppressed. S Specifies that caching is optimized for, but not restricted to, sequential access from disk. R Specifies that caching is optimized for, but not restricted to, random access from disk. T Specifies a file as temporary. If possible, it is not flushed to disk. D Specifies a file as temporary. It is deleted when the last file pointer is closed. |
import standard.C.io class Main { function Main() { // Open for read (will fail if file "test1.txt" does not exist) if(!(var fd1 = fopen( "test1.txt", "r" ))) echo "The file 'test1.txt' was not opened\n"; else { echo "The file 'test1.txt' was opened\n"; // Close the file if(fclose(fd1) != 0) echo "The file 'test1.txt' was not closed\n"; } // Open for write if(!(var fd2 = fopen( "test2.txt", "w+" ))) echo "The file 'test2.txt' was not opened\n"; else { echo "The file 'test2.txt' was opened\n"; // Close the file if(fclose(fd2) != 0) echo "The file 'test2.txt' was not closed\n"; } } } Results The file 'test1.txt' was not opened The file 'test2.txt' was opened |
| Documented by Simona Plesuvu, generation time: Sun Jan 27 18:15:15 2013 GMT | (c)2013 Devronium Applications |


Swapping of Two Numbers
By: Ajay James
This algorithm is used to swap two numbers.
- Start
- Declare variables a, b and temp
- Read values for a and b
- Display values a and b
- Assign temp = a
- Assign a = b
- Assign b = temp
- Display values a and b after swapping
- Stop


In his brilliant turn-of-the-century documentary The American Nightmare, Adam Simon located John Carpenter’s 1978 Halloween as the end point of a decade of countercultural horror movies. Starting with George Romero’s 1968 Night of the Living Dead, Simon unpicked the rebellious socio-political threads of films such as Last House on the Left, The Texas Chain Saw Massacre and Shivers before arriving at the more conservative inflections of Carpenter’s ruthlessly efficient modern morality tale.  (“I didn’t mean to put an end to the sexual revolution,” Carpenter laughingly told Simon, “and for that I deeply apologise.”) Yet it also had a punky power that inspired a slew of titillating teen-terror slashers. Friday the 13th may have lifted its gory riffs from Mario Bava’s A Bay of Blood (just as Carpenter looked back to Bob Clark’s Black Christmas), but it was Halloween that paved the way for its blockbuster success. A string of inferior sequels and reboots followed Carpenter’s low-budget hit, from Rick Rosenthal’s 1981 Halloween II (written by original screenwriters Carpenter and Debra Hill) to Rob Zombie’s dreary 2007 “reimagining” and its dispiriting follow-up. Now David Gordon Green, whose career has swerved from Terrence Malick-esque indie-hit George Washington to the stoner comedy of Pineapple Express and Your Highness, retreads familiar ground with added PTSD. Like the 20th-anniversary outing Halloween H20, which effectively overrode instalments four to six (the superior Halloween III: Season of the Witch follows an entirely separate narrative), this latest incarnation effectively dumps the sequels and simply picks up 40 years after the events of the first film, with surprisingly sprightly results. Sign up to our Film Today email Read more Former knife-wielding maniac Michael Myers (James Jude Courtney, with contributions from the original’s masked-madman Nick Castle) is now in a mental institution, serving his incarceration in silence. Meanwhile, survivor and “final-girl” archetype Laurie Strode (Jamie Lee Curtis, terrific) is living in a remote home-cum-security-compound. Haunted by the murderous spectre of Myers (aka “the shape”), Laurie’s paranoia has taken its toll; she’s seen her marriages collapse, become estranged from her daughter, Karen (a sharply cast Judy Greer), who was taken away as a child, and now fears for the safety of her teenage granddaughter Allyson (Andi Matichak). As Laurie tells the annoying podcasters who show up looking for a story: “I’m a basket case.” When Michael escapes during transfer to a maximum security prison (a nod to Halloween 4?), Laurie is hardly surprised. “He’s waited for me,” she says. “I’ve waited for him…”
Another unashamedly juvenile comedy from the awe-inspiringly busy Judd Apatow production line: Apatow produces, and the director is Adam McKay, who made the very funny Anchorman: The Legend of Ron Burgundy. Will Ferrell and John C Reilly play two 40-year-old guys who live with their respective single parents and have regressed, horribly, to being 13 (a parable, some would say, for the people who make these movies and those who enjoy them). When the boys' long-suffering parents (Richard Jenkins and Mary Steenburgen) happen to meet, fall in love at a medical-technology conference and then get married, Ferrell and Reilly have to share a bedroom as stepbrothers. There are certainly one or two funny, broad moments, especially when the "boys" get it into their heads to convert their beds into bunk beds, and their impersonation of 13-year-olds is scarily accurate. But Reilly has always been more actor than comic, and this goofy comedy is a DVD rental only.
Stallone! Statham! Willis! Li! Lundgren! Rourke! Schwarzenegger! The lineup makes it sound like it's set in the world's most macho prostate clinic. Sylvester Stallone has called in some favours and created an old-school, pre-Bourne action movie, featuring only pampered beefcakes of a certain age: spiritually located Where Eagles Dare to Fumble for Their Reading Glasses. Sly plays Barney Ross, a cigar-smoking tough guy who heads up a crew of golden-hearted mercenaries. But wait. If you're a Bruce Willis fan, or an Arnie fan, and you're expecting your heroes to have equal screen time with the rest – think again. Willis and Governor Schwarzenegger only get the briefest of cameos at the beginning, but their unsuspecting fanbases will pump up the box office receipts. He's not called "Sly" for nothing, you know: if it was just a diminutive, he'd be "Syl". Anyway, Barney and his compadres are paid to fly in to "Vilena", a Spanish-speaking island somewhere in the "Gulf" and topple a military dictatorship, without worrying over much about leaving behind a stable infrastructure. Poor old Jet Li is mightily dissed with loads of "Chinese people are short" jokes in this lumbering, humourless film, and he never gets to win a single punch-up.


--- title: Getting Started Proxying shortTitle: Getting Started layout: page pageOrder: 1 section: 'Proxy' subsection: true sitemap: priority: 0.9 changefreq: 'monthly' lastmod: 2019-11-10T08:00:00+01:00 ---
To use MockServer to analysis an existing system:
To use MockServer to verify requests:
For example code see the code examples folder in the git repository.
The page on configuring clients gives full details on how to configure clients to proxy requests via MockServer and includes code examples for the following clients:


sealed class AttachmentQueryCriteria : GenericQueryCriteria<AttachmentQueryCriteria, AttachmentsQueryCriteriaParser>, ChainableQueryCriteria<AttachmentQueryCriteria, AttachmentsQueryCriteriaParser>
AndComposition |
class AndComposition : AttachmentQueryCriteria, AndVisitor<AttachmentQueryCriteria, AttachmentsQueryCriteriaParser, AttachmentSort> |
AttachmentsQueryCriteria |
AttachmentsQueryCriteria: data class AttachmentsQueryCriteria : AttachmentQueryCriteria |
OrComposition |
class OrComposition : AttachmentQueryCriteria, OrVisitor<AttachmentQueryCriteria, AttachmentsQueryCriteriaParser, AttachmentSort> |
and |
open fun and(criteria: AttachmentQueryCriteria): AttachmentQueryCriteria |
or |
open fun or(criteria: AttachmentQueryCriteria): AttachmentQueryCriteria |


Have you seen how the browser was auto-refreshed?
When the slide is loaded, the browser polls the url it has been given. It stops polling as soon as a non-error status code is replied.
Inside a shell window, your shell's history is replaced with what's in ./.demoit/.bash_history
.
So, you don't have to remember the python -m SimpleHTTPServer
command. It's already in your shell's history.
Any small window can be made fullscreen by clicking on its green button


Diacritícál
Bahá’í Term Suggestion Script
View project on
GitHub
Suggestion Report for "Summons of the Lord of Hosts"
Verified Correct
Misspelled
Suggestion
Unrecognized
Processed Text


Tropical Storm Sebastien forms in the Atlantic
by Associated PressMIAMI (AP) — Tropical Storm Sebastien has formed in the Atlantic but is expected to stay over open waters.
ABC Action News Hurricane Center
The storm's maximum sustained winds Tuesday are near 45 mph (75 kph). The U.S. National Hurricane Center says some slight strengthening is possible but Sebastien is expected to be absorbed by a cold front in a few days.
The storm is centered about 275 miles (445 kilometers) northeast of the Leeward Islands and is moving north-northwest near 8 mph (13 kph).


A senior, Quinn has a strong passion in math, science, and engineering. He is a 2014 USAMO qualifier and currently serves as the president of Math Circles & Green Energy Innovation Club at Gunn. Quinn also loves music, sports, studying languages, and traveling. He has played the piano before.
A [year], [fname] likes green stuff.
A [year], [fname] likes green stuff.
A [year], [fname] likes green stuff.
fb.me/groups/[profile link]
info@greengunn.com


{% extends "base.html" %} {% load static %} {% block content %}
{% if results %}{{obj.attractionDescription}}
We did most of the heavy lifting for you to provide a default stylings that incorporate our custom components. Additionally, we refined animations and transitions to provide a smoother experience for developers.
By utilizing elements and principles of Material Design, we were able to create a framework that incorporates components and animations that provide more feedback to users. Additionally, a single underlying responsive system across all platforms allow for a more unified user experience.
We have provided detailed documentation as well as specific code examples to help new users get started. We are also always open to feedback and can answer any questions a user may have about Materialize.


VRaptor3 supports two different validation styles: classic and fluent. The starting point to both styles is the Validator interface. In order to access the Validator, your resource must receive it in the constructor:
import br.com.caelum.vraptor.Validator;
...
@Resource
class EmployeeController {
private Validator validator;
public EmployeeController(Validator validator) {
this.validator = validator;
}
}
The classic style is very similar to VRaptor2's validation. Inside your business logic, all you have to do is check the data you want, and if you find any validation errors, add them to the errors list. For example, to validate that employee name is 'John Doe':
public void add(Employee employee) {
if (!employee.getName().equals("John Doe")) {
validator.add(new ValidationMessage("invalid.name", "error"));
}
validator.onErrorUsePageOf(EmployeeController.class).form();
dao.add(employee);
}
When you call validator.onErrorUse, if there are any validation errors, VRaptor will stop execution and redirect to the page you specified. This redirect has the same behavior as the result.use(..) redirects.
The goal of fluent style is to write the validation code in such way that it feels natural. For example, if we want the employee name to be required:
public add(Employee employee) {
validator.checking(new Validations() {{
that(!employee.getName().isEmpty(), "error", "name.is.required");
}});
validator.onErrorUsePageOf(EmployeeController.class).form();
dao.add(employee);
}
You can read the code above like this: "Validator, check my validations. First one is that employee name cannot be empty". Much closer to natural language.
So, if employee name is empty, the flow will be redirected to the "form" logic, which shows the user a form to insert employee data again. Also, the error message is sent back to the form.
There are validations that may occur only if other validation succeeded, for instance I will check user age only if the user is not null. The that method will return a boolean that represents the success of the validation:
validator.checking(new Validations() {{
if (that(user != null, "user", "null.user")) {
that(user.getAge() >= 18, "user.age", "user.is.underage");
}
}});
So the second validation will execute only if the first didn't fail.
You can add parameters to you message keys:
greater.than = {0} should be greater than {1}
And use it on your validations code:
validator.checking(new Validations() {{
that(user.getAge() >= 18, "user.age", "greater.than", "Age", 18);
// Age should be greater than 18
}});
You can even i18n your parameters, with i18n method:
user.age = User age
validator.checking(new Validations() {{
that(user.getAge() >= 18, "user.age", "greater.than", i18n("user.age"), 18);
// User age should be greater than 18
}});
You can use Hamcrest matchers for making validation even more fluent and readable, with the advantage of matcher composition and the creation of new matchers that Hamcrest allows:
public admin(Employee employee) {
validator.checking(new Validations() {{
that(employee.getRoles(), hasItem("ADMIN"), "admin", "employee.is.not.admin");
}});
validator.onErrorUsePageOf(LoginController.class).login();
dao.add(employee);
}
VRaptor 3 also supports Bean Validation and Hibernate Validator. To use these features you only need to put any implementation of Bean Validation or Hibernate Validator jars in your classpath.
In the example above, to validate the employee object using HibernateValidator, just add one line to your code:
public add(Employee employee) {
// Validation with Bean Validation or Hibernate Validator
validator.validate(funcionario);
validator.checking(new Validations() {{
that(!employee.getName().isEmpty(), "error", "name.is.required");
}});
validator.onErrorUsePageOf(EmployeeController.class).form();
dao.add(employee);
}
Another issue that one must consider when validating data is where to redirect when an error occurs. How do one redirect the user to another resource using VRaptor3 in case of validation errors?
Easy, just tell your validator to do just that: when you find any validation error, send the user to the specified resource. See the example:
public add(Employee employee) {
// Fluent validation
validator.checking(new Validations() {{
that(!employee.getName().isEmpty(), "error", "name.is.required");
}});
// Classic validation
if (!employee.getName().equals("John Doe")) {
validator.add(new ValidationMessage("error", "invalid.name"));
}
validator.onErrorUse(page()).of(EmployeeController.class).form();
dao.add(employee);
}
If your logic may add any validation error you must specify where to go in case of error. Validator.onErrorUse works just like result.use: you can use any view from Results class.
Some redirections are pretty common, so there are shortcuts on Result interface for them. The available shortcuts are:
validator.onErrorForwardTo(ClientController.class).list() ==> validator.onErrorUse(logic()).forwardTo(ClientController.class).list();
validator.onErrorRedirectTo(ClientController.class).list() ==> validator.onErrorUse(logic()).redirectTo(ClientController.class).list();
validator.onErrorUsePageOf(ClientController.class).list() ==> validator.onErrorUse(page()).of(ClientController.class).list();
validator.onErrorSendBadRequest() ==> validator.onErrorUse(status()).badRequest(errors);
Furthermore, if one are redirecting to a method on the same controller, one can use:
validator.onErrorForwardTo(this).list() ==> validator.onErrorUse(logic()).forwardTo(this.getClass()).list();
validator.onErrorRedirectTo(this).list() ==> validator.onErrorUse(logic()).redirectTo(this.getClass()).list();
validator.onErrorUsePageOf(this).list() ==> validator.onErrorUse(page()).of(this.getClass()).list();
To force translation the parameters of the i18n() methods, simply inject the Localization and use it bundle on the constructor of the Validations():
private final Validator validator;
private final Localization localization;
public UserController(Validator validator, Localization localization) {
this.validator = validator;
this.localization = localization;
}
validator.checking(new Validations(localization.getBundle()) {{
that(user.getAge() >= 18, "user.age", "greater.than", i18n("user.age"), 18);
}});
Note that here is passed manually the ResourceBundle, so the key "user.age" will be translated correctly in the change of the Locale.
When there are validation errors, VRaptor will set a request attribute named errors
with the error list, so you can show them on your JSP with:
<c:forEach var="error" items="${errors}">
${error.category} - ${error.message}<br />
</c:forEach>


Modular online encoding, encryption and conversion tool
Web app that encodes, decodes, encrypts, decrypts, converts, translates, simulates and views content online offering a variety of ciphers, formats, algorithms and methods
Web app that encodes, decodes, encrypts, decrypts, converts, translates, simulates and views content online offering a variety of ciphers, formats, algorithms and methods


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Uganda Gorilla Adventures, Chimp Trekking Safaris & Murchison Falls Mountain Golliras are found in three states of uganda, Rwanda and congo and from the current studyis uganda shares 51% of the worlds Golliras population. with our expertise, we shall plan for you a gollira trip to uganda or rwanda which best fits your budget. start planning your next gollira trekking safari with our help. we have a couple of planned gollira trekking safaris and wildlife safaris but they may not interest you and you may want some help.
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Say hello to Mille Fiori. Present your work and business using the Mille fiori theme and any of it's four fresh, beautiful and customizable versions.


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LATEST BLOG POST:
There Is No Such Thing As A Stupid Question...
on January 11, 2015
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ARCHIVE:
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01/09/15 -
It all seemed to simple.
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Dynamic vs. Static Typing
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Conflict. Conflict Resolved.
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Epic Battle: Ruby vs. JavaScript
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I Have Values.
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Stereotype Threat
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BPL: OMG!
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Add Some Class to Your Life with Ruby
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Feedback: Garbage In, Garbage Out
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Map in Ruby: Following Directions
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Concrete Randomness: It Is What It Is
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The battle of CSS selectors: ID vs. Class
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The DBC Way: Building a well rounded bi-pedal carbon life form, that just happens to know how to program using Ruby
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Version Control Will Save Your Bacon


--- layout: post title: Opengl / c# source - Paul Bourke 3d Supershapes ---
(Programmers only !!! )
While checking out some stuff on my PC I noticed some old sloppy code lying around : A quick and dirty hack to show how Paul Bourke's supershape works in 3d. It was a quick hack from a c#/TAO nehe OpenGl Example, so don't expect to much from it.
It uses the same parameters for both dimensions, so it is not fully identical to the program of Paul Bourke...
More info on Paul Bourke's supershapes can be found here.
The link does not work anymore; you can find it here: http://paulbourke.net/geometry/supershape3d/
a screenshot :
Keys to use :
U I O P
J K L M
=> Change supershape parameters
End : Reset Supershape parameters to 1
F1 => Switch Fullscreen/Windowed mode
W => Show wireframe
PgUp/PgDn => faster/slower rotation
Home => Stop rotation
You can download it here : http://users.pandora.be/bull/core/SupershapeGL.cs .
Have fun !!!


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Japun Mulia is a modern company that is active in several sectors. We create solutions for several industries and provide consultancy services. We work closely with our stakeholders, improving data quality, reliability & efficiency of the individual components & the complete system. We try to stimulate an innovative mindset in the projects and teams we engage with.
Most often humans are over complicating life, business and reality. Therefore Japun Mulia has created a no-nonsense approach to handling projects and clients, creating true experiences. Japun Mulia will show how anything can be achieved in rapid and efficient way, without overly and unnecessary discussions or technical difficulties.
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The way we work and why we founded our company is to get away from conventional company structures and think out of the box. We utilise small Mission Critical teams and really focus on what clients want and deliver it to them; innovative, quick and painful. This saves time, effort, costs and lot of headaches.
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When clients have high-level requirements or use cases for a blockchain idea/platform/application, we can help them to analyse the requirements, break them down to more specific lower level requirements. We can then see what kind of technologies and consensus algorithm would suit best for their idea. We also have the expertise to look at the real business benefits for using blockchain.
Known as a decentralized application, or 'DAPP' for short, the concept has been one of the more novel ideas to emerge from the blockchain community. Armed with self-executing smart contracts, proponents of the technology have envisioned ways to replace everything that today requires a centralized leadership, from businesses and solutions to governments.
Your one pager with mobile presentation ready in just 1 to 3 days. All you need to provide is a Domain Name, basic content and your colors, we do the rest.
We offer you 100% Free Hosting.
We provide additional services such as expert IT advise and Management Consultancy Services.
Learn about public, private and consortium Blockchains. Explore the different use cases of Blockchain in todays economy.
Our themes are updated regularly to keep them bug free!
All dependencies are kept current to keep things fresh.
You can use this design as is, or you can make changes!
Is it really open source if it's not made with love?


The Pack object is used to generate EntityContainers and fill them with incoming entities.
EntityContainers are created automatically on demand by the Pack object. The number of entities to be packed in each EntityContainer is determined by the NumberOfEntities keyword. Once the specified number of entities is available in the Queue, the entities are packed one by one in the EntityContainer in the same order as the Queue. The time to pack each entity is specified by the ServiceTime keyword.


Source code for climlab.solar.orbital
"""This module defines the class :class:`OrbitalTable` which holds orbital data,
and includes a method :func:`~OrbitalTable.lookup_parameters`
which interpolates the orbital data for a specific year
(- works equally well for arrays of years).
The base class :class:`OrbitalTable()` is designed to work with 5 Myears of orbital data
(**eccentricity, obliquity, and longitude of perihelion**) from :cite:`Berger_1991`.
Data will be read from the file orbit91, which was originally obtained from
ftp://ftp.ncdc.noaa.gov/pub/data/paleo/insolation/
If the file isn't found locally, the module will attempt to read it remotely
from the above URL.
A subclass :class:`LongOrbitalTable()` works with La2004 orbital data for
-51 to +21 Myears as calculated by :cite:`Laskar_2004`.
See http://vo.imcce.fr/insola/earth/online/earth/La2004/README.TXT
"""
import numpy as np
from scipy import interpolate
import os
[docs]class OrbitalTable:
"""Invoking OrbitalTable() will load 5 million years of orbital data
from :cite:`Berger_1991` and compute linear interpolants.
The data can be accessed through the method :func:`lookup_parameters()`.
**Object attributes** \n
Following object attributes are generated during initialization:
:ivar array kyear: time table with negative values are before present
(*unit:* kyears)
:ivar array ecc: eccentricity over time (*unit:* dimensionless)
:ivar array long_peri: longitude of perihelion (precession angle) (*unit:* degrees)
:ivar array obliquity: obliquity angle (*unit:* degrees)
:ivar float kyear_min: minimum value of time table (*unit:* kyears)
:ivar float kyear_max: maximum value of time table (*unit:* kyears)
"""
def __init__(self):
self.kyear = None
self.ecc = None
self.long_peri = None
self.obliquity = None
# call a method that reads data from a file and populates the arrays
self._get_data()
self._compute_interpolants()
# find and store min and max years. lookup_parameters should throw an exception
# if you ask for something outside this range -- not yet implemented.
self.kyear_max = np.max(self.kyear)
self.kyear_min = np.min(self.kyear)
[docs] def lookup_parameters( self, kyear = 0 ):
"""Look up orbital parameters for given kyear measured from present.
.. note::
Input ``kyear`` is thousands of years after present.
For years before present, use ``kyear < 0``.
**Function-call argument** \n
:param array kyear: Time for which oribtal parameters should be given.
Will handle scalar or vector input (for multiple years).
[default: 0]
:returns: a three-member dictionary of orbital parameters:
* ``'ecc'``: eccentricity (dimensionless)
* ``'long_peri'``: longitude of perihelion
relative to vernal equinox (degrees)
* ``'obliquity'``: obliquity angle or axial tilt (degrees).
Each member is an array of same size as kyear.
:rtype: dict
"""
# linear interpolation:
this_ecc = self.f_ecc(kyear)
this_obliquity = self.f_obliquity(kyear)
this_long_peri = self.f_long_peri(kyear)
# convert long_peri to an angle (in degrees) between 0 and 360
long_peri_converted = this_long_peri % 360.
# Build a dictionary of all the parameters
orb = {'ecc':this_ecc, 'long_peri':long_peri_converted, 'obliquity':this_obliquity}
return orb
def _get_data(self):
past_file = 'orbit91'
base_url = 'ftp://ftp.ncdc.noaa.gov/pub/data/paleo/insolation/'
# This gives the full path to the data file, assuming it's in the same directory
local_path = os.path.dirname(__file__)
fullfilename = os.path.join(local_path, past_file)
num_lines_past = 5001
self.kyear = np.empty(num_lines_past)
self.ecc = np.empty_like(self.kyear)
self.long_peri = np.empty_like(self.kyear)
self.obliquity = np.empty_like(self.kyear)
# This gives the full path to the data file, assuming it's in the same directory
fullfilename = os.path.join(os.path.dirname(__file__), past_file)
try:
record = open(fullfilename,'r')
print 'Loading Berger and Loutre (1991) orbital parameter data from file ' + fullfilename
except:
print 'Failed to load orbital locally, trying to access it via remote ftp.'
try:
import urllib2
record = urllib2.urlopen( base_url + past_file )
print 'Accessing Berger and Loutre (1991) orbital data from ' + base_url
print 'Reading file ' + past_file
except:
raise StandardError('Failed to load the data via remote ftp.')
# loop through each line of the file, read it into numpy array
# skip first three lines of header
toskip = 3
for i in range(toskip):
record.readline()
for index,line in enumerate(record):
str1 = line.rstrip() # remove newline character
thisdata = np.fromstring(str1, sep=' ')
# ignore after the 4th column
self.kyear[index] = thisdata[0]
self.ecc[index] = thisdata[1]
self.long_peri[index] = thisdata[2]
self.obliquity[index] = thisdata[3]
record.close()
def _compute_interpolants(self):
# add 180 degrees to long_peri (see lambda definition, Berger 1978 Appendix)
long_peri0rad = np.deg2rad(self.long_peri + 180.)
long_peri0 = np.rad2deg( np.unwrap( long_peri0rad ) ) # remove discontinuities (360 degree jumps)
# calculate linear interpolants
self.f_ecc = interpolate.interp1d(self.kyear, self.ecc)
self.f_long_peri = interpolate.interp1d(self.kyear, long_peri0)
self.f_obliquity = interpolate.interp1d(self.kyear, self.obliquity)
[docs]class LongOrbitalTable(OrbitalTable):
"""Loads orbital parameter tables for -51 to +21 Myears.
Based on calculations by :cite:`Laskar_2004`
http://vo.imcce.fr/insola/earth/online/earth/La2004/README.TXT
Usage is identical to parent class :class:`OrbitalTable()`.
"""
def _get_data(self):
base_url = 'http://vo.imcce.fr/insola/earth/online/earth/La2004/'
past_file = 'INSOLN.LA2004.BTL.ASC'
future_file = 'INSOLP.LA2004.BTL.ASC'
num_lines_past = 51001
num_lines_future = 21001
num_columns = 4
data_past = np.empty((num_lines_past,num_columns))
data_future = np.empty((num_lines_future, num_columns))
print 'Attempting to access La2004 orbital data from ' + base_url
# loop through each line of the file, read it into numpy array
for (data,filename) in zip((data_past,data_future),
(past_file,future_file)):
try:
import urllib2
print 'Reading file ' + filename
record = urllib2.urlopen( base_url + filename )
for index,line in enumerate(record):
str1 = line.rstrip() # remove newline character
str2 = str1.replace('D','E') # put string into numpy format
data[index,:] = np.fromstring(str2, sep=' ')
record.close()
except:
raise StandardError('Failed to access file ' + filename )
# need to flip it so the data runs from past to present
data_past = np.flipud(data_past)
# and expunge the first line of the future data because it repeats year 0
data = np.concatenate((data_past,data_future[1:,:]), axis=0)
self.kyear = data[:,0]
self.ecc = data[:,1]
self.obliquity = np.rad2deg(data[:,2])
self.long_peri = np.rad2deg(data[:,3])


In preparation for Version1, I dug into the Snow Dots Ethernet messaging code. The result is faster Ethernet transactions.
Some of the speed-up comes from removed overhead in m-code function calls. Some of the speed-up is optional, with the introduction of two flavors of synchronization between client and server Matlab instances: strong synchronization and weak synchronization.
This included work at several levels of organization, from mex-function c-code through object-oriented m-code:
mexUDP()
mexUDP() is a Snow Dots mex-function for doing UDP Ethernet messaging from systems that use use Berkeley sockets.
As of r892, the mexUDP('check') sub-command accepts an optional timeout parameter. hasData = mexUDP('check', id [, timeoutSeconds])
This allows mexUDP() to block for the given timeoutSeconds, or until a UDP message arrives. If timeoutSeconds is omitted, the old behavior results: mexUDP('check') returns immediately and callers must to poll for messages themselves.
The new blocking behavior reduces the number of m-code loops and function calls necessary to receive and respond to an expected message. The blocking is implemented with the POSIX select() function.
dotsAllSocketObjects
dotsAllSocketObjects is an abstract class defining the interface that Snow Dots expects from objects doing Ethernet messaging.
As of r892, the dotsAllSocketObjects.check() methods may take an optional timeoutSecs argument.
dotsSocketMexUDP is an implementation of dotsAllSocketObjects that uses the mexUDP() mex-function. It treats timeoutSecs as described above for mexUDP().
dotsSocketPnet is an implementation of dotsAllSocketObjects that uses the pnet() mex-function. It treats timeoutSecs similarly to dotsSocketMexUDP.
dotsTheMessenger
dotsTheMessenger is the "front end" for doing Ethernet messaging in Snow Dots. It uses dotsAllSocketObjects and adds robustness and convenience.
Before r892, dotsTheMessenger had a waitForMessageAtSocket() method. This used an m-code loop to poll for arriving messages. As of r892, this method is gone.
Instead, receiveMessageAtSocket() accepts an optional receiveTimeout argument. If receiveTimeout is positive, the method is allowed to block for up to receiveTimeout seconds until a message arrives.
Likewise, sendMessageFromSocket() accepts an optional ackTimeout argument. If ackTimeout is positive, the method is allowed to block for up to ackTimeout seconds until it receives a message acknowledgement.
dotsClientEnsemble and dotsClientEnsemble
dotsClientEnsemble and dotsEnsembleServer are complimentary classes that allow Snow Dots to span multiple Matlab instances. They use dotsTheMessenger, so they benefit directly from the above changes.
As of r892, they also conserve messaging traffic by sending shorter messages. Instead of exchanging full "transactions", they agree on a transaction template and only send deviations from the template.
Smarter timeout behaviors and shorter messages result in significantly faster client-server communication. In rough numbers, using two instances of Matlab running on the same MacBook, transactions that previously took 5ms now take about 2-3ms.
Strong vs. Weak Synchronization
Before r892, dotsClientEnsemble and dotsClientEnsemble communicated with what I'm now calling strong synchronization. This meant that the client requested a server behavior, then waited until the server reported that it was all done. This allowed the server to return a lot of timing data, as well as the results of method calls or property access. But it meant that the client spent a lot of time waiting.
r892 introduces "weak synchronization": when the client doesn't need to collect timing data, and doesn't expect any returned results, it can wait only for the server to acknowledge a behavior request. The client is able to continue doing other things while the server actually carries out the behavior. This improves parallelism.
Here is a sketch of client and server communications. Each table row represents a step that happens after the step above. Extra steps required for strong synchronization are in bold.
| client | server | |:-------|:-------| | request behavior | ready | | wait for acknowledgement | receive request | | | acknowledge request | | receive acknowledgement | do behavior | | wait for data | reply with data | | receive data | wait for acknowledgement | | acknowledge data | | | continue | receive acknowledgement |
Weakly synchronized transactions take half as many steps as strongly synchronized transactions. In rough numbers, using two instances of Matlab running on the same MacBook, weakly synchronized transactions can take as little as 1-2ms as seen by the client.
dotsClientEnsemble has a new isSynchronized property for choosing the flavor of synchronization. When isSynchronized is true, an object always does strong synchronization. When isSynchronized is false, an object does weak synchronization, unless it's expecting return data from a method call or property access.
As of r892, client-server communications include an isSynchronized hint, so that dotsEnsembleServer objects know whether to reply with data.


Measuring the effect of information on peace agreement support
The country of Absurdistan has had an ongoing civil conflict for the past 60 years. The fighting between national government forces and guerrilla members from the National Revolutionary Army (NRA) has lead to more than 200,000 deaths, 8 million internally displaced persons, and countless victims between 1960 to 2020. The civil war in Absurdistan has been a low-intensity asymmetric war. The legacies of the conflict have been bore largely by regions in the periphery of the country. Large cities and industrial regions have been spared from most of the fighting.
The government and the leadership of the NRA reached a peace agreement a couple of months ago; however, the agreement has been received poorly by the general population of Absurdistan. The opposition party the Undemocratic Center (UC) has allegedly ran campaigns misrepresenting the contents of the agreement in partisan media outlets and social media.
The Special Envoy for Peace has established a taskforce to design a strategy to increase support for the peace agreement. Many in the taskforce suspect that if the public were properly informed about the agreement reached, the levels of support would be higher.
You are hired as a scientific consultant for the taskforce. You run a survey experiment on a sample of 1000 respondents. You randomly assign respondents to watch an educational 40 second video about the peace agreement. Here are the results:
1.1 Exploring the data
set.seed(42) #for consistent results
library(dplyr) # to wrangle our data
library(tidyr) # to wrangle our data - pivot_longer()
library(ggplot2) # to render our graphs
library(readr) # for loading the .csv data
library(kableExtra) # to render better formatted tables
library(stargazer) # for formatting your model output
library(margins) #for calculating MARGINAL/PARTIAL EFFECT
library(ggeffects) # easily calculating PREDICTIVE MARGINS
moderation_df <- readr::read_csv("https://raw.githubusercontent.com/seramirezruiz/hertiestats2/master/data/moderation_df.csv") # simulated data
names(moderation_df) # to check the names of the variables in our data
## [1] "subject_id" "treatment" "victim_verbose"
## [4] "victim" "female" "female_verbose"
## [7] "support_thermometer"
Our dataset moderation_df, contains the following information:
subject_id
: A unique numeric identification for each respondenttreatment
: A binary marker for treatmentvictim_verbose
: A verbose binary marker of the respondents' victimhood status (Not a Victim-Victim)victim
: A numeric binary marker of the respondents' victimhood status (0-1)female
: A numeric binary marker of the respondents' sex (0-1)female_verbose
: A verbose binary marker of the respondents' sex (Male-Female)support_thermometer
: A continuous measure of support for the agreement (0-100)
Let's explore who is in our sample
We can use what we have learned about the base R table() function, to check who was in our sample:
table(moderation_df$treatment) %>%
knitr::kable(col.names = c("Treatment", "Frequency")) %>% # create kable table
kableExtra::kable_styling() # view kable table
| Treatment | Frequency |
|---|---|
| 0 | 500 |
| 1 | 500 |
table(moderation_df$treatment, moderation_df$victim_verbose) %>%
knitr::kable() %>% # create kable table
kableExtra::kable_styling() # view kable table
| Not a victim | Victim | |
|---|---|---|
| 0 | 250 | 250 |
| 1 | 250 | 250 |
Let's explore visually the observed levels of public support for the agreement
ggplot(moderation_df, aes(x = support_thermometer)) +
geom_density(fill = "#af8dc3", alpha = 0.5) +
theme_minimal() +
labs(x = "Support thermometer",
y = "Density")
Let's explore visually the observed levels of public support for the agreement conditional on the treatment status
ggplot(moderation_df, aes(x = support_thermometer, fill = factor(treatment))) +
geom_density(alpha = 0.5) +
theme_minimal() +
labs(x = "Support thermometer",
y = "Density",
fill = "Treatment") +
theme(legend.position = "bottom")
Let's explore visually the observed levels of public support for the agreement conditional on the treatment and victimhood status
ggplot(moderation_df, aes(x = support_thermometer, fill = factor(treatment))) +
geom_density(alpha = 0.5) +
facet_wrap(victim_verbose~treatment, nrow = 4) +
theme_bw() +
labs(x = "Support thermometer",
y = "Density",
fill = "Treatment") +
theme(legend.position = "bottom")
1.2 Modeling and estimating
During this week's lecture, we learned that we can explicitly model heterogeneity in treatment effects for subgroups. Thus, we can address the tension between having to do inference at the group level, and the recognition of individual differences.
The analysis of heterogeneity can be very important for the design of our strategy. There are competing theories about the effects of conflict victimization on political behavior and attitudes. Some of the literature points to victims developing pro-social attitudes, while others suggest that victims become intransigent towards out-groups. Could factual information about the peace agreement be received differently by victims and non-victims?
How to estimate heterogenous treatment effects
Heterogeneous treatment effects are usually estimated with regression models that include an interaction between the treatment and the moderator. In our case, the formula would look like this:
\[Y_{i} = β_0 + β_1D_{i} + β_2Victim_{i} + β_3D_i * Victim_{i}+ ϵ_i \]
- \(β_0\): Constant
- \(β_1\): Effect of \(D_i\) on \(Y_i\) if \(Victim_i\) is zero
- \(β_2\): Effect of \(Victim_i\) on \(Y_i\) if \(D_i\) is zero
- \(β_3\): Difference in treatment effects of \(D_i\) depending on \(Victim_i\)
or in lm()
terms:
lm(outcome ~ treatment + moderator + (treatment*moderator))
lm(outcome ~ treatment + moderator + treatment:moderator)
lm(outcome ~ treatment * moderator)
Let's model our results
We will move forward by creating two models:
- A naive model, where we will regress
support_thermometer
ontreatment
. - An interaction model, where we will add an interaction between
treatment
andvictim
1.2.1 Naive modeling
naive_model <- lm(support_thermometer ~ treatment, data = moderation_df)
stargazer::stargazer(naive_model, type = "text")
##
## ===============================================
## Dependent variable:
## ---------------------------
## support_thermometer
## -----------------------------------------------
## treatment 18.898***
## (1.026)
##
## Constant 35.055***
## (0.725)
##
## -----------------------------------------------
## Observations 1,000
## R2 0.254
## Adjusted R2 0.253
## Residual Std. Error 16.220 (df = 998)
## F Statistic 339.360*** (df = 1; 998)
## ===============================================
## Note: *p<0.1; **p<0.05; ***p<0.01
The naive model suggests that the subjects that the support for the peace agreement is about 18.9 percentage points higher on average for the subjects that watched the educational video. We suspect, however, that the video may affect differently victims from non-victims of the conflict.
Here is a visual illustration of the values rendered by the naive regression
ggplot(moderation_df, aes(x = support_thermometer, fill = factor(treatment))) +
geom_density(alpha = 0.5) +
theme_minimal() +
geom_vline(xintercept = 35.055, linetype = "longdash", color = "red") + #D=0
geom_vline(xintercept = 35.055 + 18.898, linetype = "longdash", color = "darkblue") + #D=1
labs(x = "Support thermometer",
y = "Density",
fill = "Treatment") +
theme(legend.position = "bottom")
1.2.2 Interaction model
Following any of the different formats renders the same results.
interaction_model <- lm(support_thermometer ~ treatment + victim + (treatment*victim), data = moderation_df)
interaction_model_2 <- lm(support_thermometer ~ treatment + victim + treatment:victim, data = moderation_df)
interaction_model_3 <- lm(support_thermometer ~ treatment*victim, data = moderation_df)
stargazer::stargazer(interaction_model, interaction_model_2, interaction_model_3, type = "text")
##
## =====================================================================
## Dependent variable:
## --------------------------------------
## support_thermometer
## (1) (2) (3)
## ---------------------------------------------------------------------
## treatment 8.013*** 8.013*** 8.013***
## (0.776) (0.776) (0.776)
##
## victim 14.256*** 14.256*** 14.256***
## (0.776) (0.776) (0.776)
##
## treatment:victim 21.771*** 21.771*** 21.771***
## (1.097) (1.097) (1.097)
##
## Constant 27.927*** 27.927*** 27.927***
## (0.549) (0.549) (0.549)
##
## ---------------------------------------------------------------------
## Observations 1,000 1,000 1,000
## R2 0.787 0.787 0.787
## Adjusted R2 0.786 0.786 0.786
## Residual Std. Error (df = 996) 8.673 8.673 8.673
## F Statistic (df = 3; 996) 1,227.193*** 1,227.193*** 1,227.193***
## =====================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
- \(β_0\): Constant = The average support for non-victims who were not exposed to the video was 27.92
- \(β_1\): Effect of \(D_i\) on \(Y_i\) if \(Victim_i\) is zero = The educational video results in an increase of about 8 percentage points of the peace agreement for the non-victims
- \(β_2\): Effect of \(Victim_i\) on \(Y_i\) if \(D_i\) is zero = On average, victims’ support for the peace agreement is 14.3 percentage points higher than that of the non-victims in the control group
- \(β_3\): Difference in treatment effects of \(D_i\) depending on \(Victim_i\) = The educational video results in an additional increase for victims of about 21.8 percentage points, compared to the effect for non-victims
Here is a visual illustration of the values rendered by the model with interaction terms
moderation_df %>%
dplyr::group_by(treatment,victim_verbose) %>%
dplyr::mutate(avg_support = mean(support_thermometer)) %>%
ggplot(., aes(x = support_thermometer, fill = factor(treatment))) +
geom_density(alpha = 0.5) +
geom_vline(aes(xintercept = avg_support), linetype = "longdash") +
facet_wrap(victim_verbose~treatment, nrow = 4) +
theme_bw() +
labs(x = "Support thermometer",
y = "Density",
fill = "Treatment") +
theme(legend.position = "bottom")
1.3. Extracting marginal/partial effects from our interaction models
For this portion, we are interested in marginal/partial effects, which we will extract through the margins()
function from the margins
package.
Some packages in R aimed at rendering marginal effects do render the predictive margins instead. For the purposes of the class, when asked to render marginal or partial effects you are expected to render them as introduced in the lecture (i.e., \(\frac{\partial Y_i}{\partial {D}_i}\)). When asked for this, you will utilize margins()
.
You can check the documentation here. The syntax for the margins()
function for extracting partial effects of the treatment at different levels of the moderator is the following:
margins::margins(name_of_your_model, variables = "treatment_var", at = list(moderator_variable = values))
Let's say we are interested in the marginal/partial effect of our video treatment for victims and non-victims. We would do:
summary(margins::margins(interaction_model, variables = "treatment", at = list(victim = 0:1)))
## factor victim AME SE z p lower upper
## treatment 0.0000 8.0125 0.7757 10.3288 0.0000 6.4921 9.5330
## treatment 1.0000 29.7831 0.7758 38.3895 0.0000 28.2626 31.3037
Let's plot the the marginal/partial effect of the treatment for victims and non-victims
pe_margins <- margins::margins(interaction_model, variables = "treatment", at = list(victim = 0:1))
pe_plotting <- summary(pe_margins) %>% #NOTE we use the summary output, instead of the margins object
dplyr::select(victim, AME, lower, upper) %>% # you will need to adapt this based your moderator
dplyr::mutate(victim_labels = ifelse(victim == 1, "Victim", "No Victim")) # you will need to adapt this based your moderator
ggplot(pe_plotting, aes(x = victim_labels,
y = AME)) +
geom_point(size = 1.5) +
geom_segment(aes(x = victim_labels, xend = victim_labels, y = lower, yend = upper), size = 0.5) + # render whiskers from confidence intervals
theme_minimal() +
scale_y_continuous(limits = c(0,45)) + # you may need to change the limits for your plots
labs(x = "Respondent status\n",
y = "\nPartial effect of educational video",
caption = "Note: You can utilize it to describe what the plot illustrates during your assignment.") +
coord_flip()
1.4. Extracting predictive margins from our interaction models
For this portion, we are interested in predictive margins. In here, our interest is to return the expectation for each level of a predictor. We will extract this through the ggeffects()
function from the ggeffects
package. You can check the documentation here. The syntax is the following:
ggeffects::ggeffect(name_of_your_model, terms = c("termA", "termB"))
Let's say we are interested in the predictive margins for all out victim and treatment permutations. We would do:
ggeffects::ggeffect(interaction_model, terms = c("victim","treatment"))
##
## # Predicted values of support_thermometer
## # x = victim
##
## # treatment = 0
##
## x | Predicted | SE | 95% CI
## -------------------------------------
## 0 | 27.93 | 0.55 | [26.85, 29.00]
## 1 | 42.18 | 0.55 | [41.11, 43.26]
##
## # treatment = 1
##
## x | Predicted | SE | 95% CI
## -------------------------------------
## 0 | 35.94 | 0.55 | [34.86, 37.02]
## 1 | 71.97 | 0.55 | [70.89, 73.04]
Let's plot these predictive margins
In this exercise we will meet a very important function from dplyr
, dplyr::case_when()
. This function allows us to vectorize multiple ifelse() statements. The syntax is the following:
dplyr::case_when(condition ~ what to do if met)
Let's see it at play.
extracted_me <- ggeffects::ggeffect(interaction_model, terms = c("victim","treatment")) %>%
dplyr::mutate(group_labels = dplyr::case_when(x == 1 & group == 1 ~ "Victim (1) - Treatment (1)",
x == 1 & group == 0 ~ "Victim (1) - Treatment (0)",
x == 0 & group == 1 ~ "Victim (0) - Treatment (1)",
x == 0 & group == 0 ~ "Victim (0) - Treatment (0)"
)) # adding labels to x groups to plot
extracted_me
##
## # Predicted values of support_thermometer
## # x = victim
##
## # treatment = 0
##
## x | Predicted | SE | group_labels | 95% CI
## ------------------------------------------------------------------
## 0 | 27.93 | 0.55 | Victim (0) - Treatment (0) | [26.85, 29.00]
## 1 | 42.18 | 0.55 | Victim (1) - Treatment (0) | [41.11, 43.26]
##
## # treatment = 1
##
## x | Predicted | SE | group_labels | 95% CI
## ------------------------------------------------------------------
## 0 | 35.94 | 0.55 | Victim (0) - Treatment (1) | [34.86, 37.02]
## 1 | 71.97 | 0.55 | Victim (1) - Treatment (1) | [70.89, 73.04]
ggplot(extracted_me, aes(x = group_labels,
y= predicted,
fill = group_labels)) +
geom_bar(stat = "identity",
alpha = 0.5) + # we set dodge instead of default stacked
geom_point(size = 1.5) +
geom_segment(aes(x = group_labels,
xend = group_labels,
y = conf.high,
yend = conf.low), size = 0.5) + # render whiskers from confidence intervals
theme_minimal() +
labs(x = "\nRespondent status",
y = "Effect of educational video",
fill = "Treatment",
caption = "Note: You can utilize it to describe what the plot illustrates during your assignment.") +
theme(legend.position = "none")
1.4 Drafting some brief recommedations
After conducting your experiment, you report back to the taskforce. Based on your results, you suggest that the educational videos may be a useful tool to encourage the wider public to hold a warmer opinion about the peace agreement. You also tell the taskforce that, although the videos have an average positive effect, they affect with a higher intensity victims of the conflict. You suggest to develop alternative strategies to tackle the non-victims, so that they do not fall through the cracks.


Report: Founder of White Helmets found dead in Istanbul
by The Associated Press, StaffISTANBUL -- Turkey's state-run news agency says a former British army officer who helped found the "White Helmets" volunteer organization in Syria, has been found dead in Istanbul.
Anadolu Agency said James Le Mesurier's body was found early Monday near his home in Istanbul's Beyoglu district by worshippers on their way to a mosque to pray.
An investigation has been launched into his death, Anadolu said, adding that police believe he may have fallen to his death.
Police had established that no one had entered or left his home at the time of his death, Anadolu reported.
Le Mesurier described himself on his Twitter account as the founder and CEO of the May Day Rescue, which founded and trained the "White Helmets" also known as the Syria Civil Defence.


Bit masks can be used to select out rows from bit columns (TFORMn = #X) in FITS files. To represent the mask, binary, octal, and hex formats are allowed:
binary: b0110xx1010000101xxxx0001 octal: o720x1 -> (b111010000xxx001) hex: h0FxD -> (b00001111xxxx1101)
In all the representations, an x or X is allowed in the mask as a wild card. Note that the x represents a different number of wild card bits in each representation. All representations are case insensitive.
To construct the boolean expression using the mask as the boolean equal operator described above on a bit table column. For example, if you had a 7 bit column named flags in a FITS table and wanted all rows having the bit pattern 0010011, the selection expression would be:
flags == b0010011 or flags .eq. b10011
It is also possible to test if a range of bits is less than, less than equal, greater than and greater than equal to a particular boolean value:
flags <= bxxx010xx flags .gt. bxxx100xx flags .le. b1xxxxxxx
Notice the use of the x bit value to limit the range of bits being compared.
It is not necessary to specify the leading (most significant) zero (0) bits in the mask, as shown in the second expression above.
Bit wise AND, OR and NOT operations are also possible on two or more bit fields using the '&'(AND), ''(OR), and the '!'(NOT) operators. All of these operators result in a bit field which can then be used with the equal operator. For example:
(!flags) == b1101100 (flags & b1000001) == bx000001
Bit fields can be appended as well using the '+' operator. Strings can be concatenated this way, too.


What is your full name ?
Do you like travelling ?
Yes
No
Not Sure
How often do you travel ?
Weekly
Monthly
Annually
Never
How much are you willing to spend on travel?
$0 -$500
$500 -$1000
$1000 -$5000
Above $5000
What type of holidays do you prefer?
Romantic
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AMIQ OFC Python FPGA Connector¶
Copyright 2021 AMIQ Consulting
Licensed under the Apache License, Version 2.0 (the “License”); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an “AS IS” BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
MODULE: amiq_ofc_python_fpga_connector PROJECT: Amiq Open-Source Framework for Co-Emulation
-
class
amiq_ofc_python_fpga_connector.
amiq_ofc_python_fpga_connector
(bit_file)[source]¶ This framework was tested and on pynq version v2.5 (Glasgow Release).
To create the co-emulation enviroment you have to instantiate the co_emulation class by giving the bitstream file.
- @note: A hardware file (.hwh or .tcl) should also be present and it should have the same name as the bitstreamfile
(It is recommended to use .hwh file, since the .tcl is deprecated)
-
recv_from_dma
(dma_name)[source]¶ Function which expects a received item (or a list of items) from the corresponding DMA, using the corresponding buffer. The function returns the received items in a non-blocking manner, due to the recvchannel.wait_async() call.
@note: The <size(buffer)> gives the maximum number of expected items
@param dma_name: Is the name of the DMA module from which you want to collect data. @type dma_name: string
@return: dma_buffer: The buffer containing the collected items @rtype: amiq_ofc_buffers.recv
@see pynq.lib.dma.DMA.recvchannel.transfer() @see pynq.lib.dma.DMA.recvchannel.wait_async()
-
send_to_dma
(to_send, dma_name, force_send=False)[source]¶ Function which sends an item (or a list of items) to the corresponding DMA, using the corresponding buffer
The items are sent in a blocking manner, due to the sendchannel.wait() call. (A possibility could be using wait_async() to turn it into a non-blocking function)
@param to_send: Is an item (or a list of items) in packed form, which has to match the dma_buffer dtype @type to_send: packed amiq_ofc_item or a list<packed amiq_ofc_items> @param dma_name: Is the name of the DMA module used to transfer to_send to the PL side @type dma_name: string @param force_send: The flag that establishes if the send will be completed despite size differences @type force_send: boolean
@see pynq.lib.dma.DMA.sendchannel.transfer() @see pynq.lib.dma.DMA.sendchannel.wait() @see pynq.lib.dma.DMA.sendchannel.wait_async() @see amiq_ofc_buffers.allocate_buffers


Planet Coaster is heading to Xbox One and PS4
I'm glad someone's bringing these sim titles over
by Jordan DevoreIt's been slim pickings for console players who want to build and run their own theme parks, but that's changing soon, at least for one notable game. Today at Microsoft's X019 event, Frontier Developments announced it's bringing Planet Coaster: Console Edition to Xbox One and also PlayStation 4.
Soak in these RollerCoaster Tycoon vibes.
The port is scheduled for summer 2020, and for now, that's all she wrote. I hope it runs okay!


Umrah Guide
Step by Step Guide for Umrah
Prepared by Mohamed Baianonie, Imam at the Islamic Center of Raleigh
Al-Ihraam (Clothing)
Ihraam is mandatory (waajib) clothing to be worn during Umrah. The requirements for men and women are different. Men must take off their regular clothes and put on the two unstitched pieces of clothes (Ezaar and Redaa). Additionally, men cannot wear shoes that cover the top of their feet. Women can wear any loose-fitting, decent dress which covers the entire body except face and hands.
During the state of Ihraam, the additional requirements have to be followed by both men and women.
It is recommended that before ihraam, one takes a shower (performs ghusl) with the intention to purify your self and to be ready for Umrah. Only men can perfume (fragrance) his body (not his ihraam garments). However after you have entered a state of ihraam, men are not allowed to use any cologne/perfume or fragranced items (including soaps, deodorants, etc.) on their body or garments.
Women should not use perfumes (or fragrances) at all.
An-Niyyah (Intention)
This is the intention to make Umrah. It has to be made at the place of Miqaat before entering the jurisdiction of the Haram.
Upon making the intention (niyyah) for umrah, one should say:
"LABBAYAKA ALLAAHUMMA UMRAH"
Which means: "O Allah I answered your call to perform Umrah."
It is recommended to repeat the well-known dhikr of ihraam, called Talbeyah, as frequently as possible from the time of ihraam (after making niyyah at Miqaat). This should be said loudly be the men, and softly by the women.
This Talbeyah is the following:
"LABBAYKA ALLAAHUMMA LABBAYK. LABBAYKA LAA SHAREEKA LAKA LABBAYK. INNALHAMDA WAN-N'IMATA LAKA WALMULK. LAA SHAREEKA LAK.""
which means: "Here I am at your service. O my Lord, Here I am. No partner you have. Here I am. Truly, the praise and the provisions are yours, and so is the dominion. No partner do you have."
Tawaaf around the Ka'bah
When you reach Makkah, you should make Tawaaf around the Ka'bah (while having wudu). This is done by circling the Ka'bah seven times in the counterclockwise direction, starting from the black stone (raising the hand towards it) with Takbeer ("Allahu Akbar") and ending each circle at the black stone (raising the hand towards it) with Takbeer, keeping the Ka'bah to one's left. This is called Tawaaf al-Umrah.
And this Tawaaf is pillar of Umrah.
From Sunnah acts for the men only during the Tawaaf
- Putting the ends of the upper loose garment (redaa) under the right armpit, exposing the right shoulder (idtibaa). Once the seven rounds of tawaaf are completed, return the upper garment (redaa) to the previous position.
- Walking quickly (ramal) during the first three rounds of the first Tawaaf around the Ka'bah. For the final four rounds of Tawaaf, walk normally.
It is not necessary to kiss the black stone. If one cannot easily do so, one is encouraged to touch it with their hand, and if they cannot do that, one can simply raise their hand towards it.
If salaah time comes before you finish your Tawaaf, simply line up for salaah. Upon finishing your salaah, immediately resume your Tawaaf until you are finished with your seven circles.
Praying Two Rak'ah behind Maqaamu Ibraheem:
After finishing Tawaaf, one then goes to Maqaamu Ibraaheem (Ibrahim's station), and performs two Rak'ah behind it, (close to it if possible), but away from the path of the people making Tawaaf. In all cases one should be facing the Ka'bah when praying behind Maqaamu Ibraaheem. After the prayer, it is a Sunnah to drink from water of Zamzam, and (it is recommended to) make any du'aa you would like to offer.
Sa'i between Safaa and Marwah:
After praying two rak'ah behind Maqaamu Ibraaheem, the next rite is to make Sa'i between Safaa and Marwah. You start Sa'i by ascending the Safaa. While facing the direction of the Ka'bah he praises Allah, raises his hands and says "Allah-u-Akbar" three times, then makes supplication to Allah. Then you descend from the Safaa and head towards Marwah.
One should increase the pace between the clearly marked (and illuminated) green posts, but should walk at a normal pace before and after them (for the men only).
When you reach the Marwah, you should ascend it, praise Allah and do as he did at the Safaa. This is considered one round and so is the other way from the Marwah to the Safaa. A total of seven rounds are required to perform the Sa'i. And this Sa'i is pillar of Umrah.
Trimming or shaving the hair:
It is mandatory (waajib) for men to trim or shave their hair, and for women to trim only a fingertip-length of their hair after completing all of the above rituals of Umrah. After this you can wear regular clothes and engage in all actions that were prohibited during the Ihraam. This completes and concludes your Umrah. You can now (and are encouraged to) continue to engage in various forms of ibaadah at the ka'abah including, but not limited to: duaa, salaah, dhikr, Qur'an, and extra tawaaf (in sets of seven, while having wudu'u).


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