Created by Rafael Gutiérrez / @abaddon_gtz
General Purpose Programming Language
Dynamic
Functional
Lisp
JVM/CRL/Javascript
Homoiconic
Read Evaluate Print Loop
java -cp clojure.jar clojure.main
user=>
But you can Sublime and SublimeREPL
Or LightTable
Integers, doubles, floats and fractions
user=> 1
user=> 1.0
user=> 1/2
user=> (/ 34 5)
user=> (int 1)
user=> (long 1)
user=> (float 1)
user=> (double 1)
user=> (type 1)
user=> (type 1.0)
user=> (type 1/2)
user=> (type (int 1))
user=> (type (long 1))
user=> (type (float 1))
user=> (type (double 1))
true
and false
nil
values are evaluated as false
(falsey).
user=> true
user=> false
user=> (false? nil)
user=> (if nil "true" "false")
user=> (type true)
user=> (type false)
Denoted by double quotes and can span multiple lines
user=> "this is a string"
user=> (type "string")
Denoted by a forward slash
user=> \a
user=> (type \a)
user=> (char 64)
Used to identify variables
user=> a
user=> (type a)
user=> (type (quote a))
user=> (type 'a)
user=> (symbol "a")
Symbols that reference themselves and are denoted by a colon ':'; these are often used as keys in maps
user=> :a
user=> (type :a)
user=> (keyword "a")
( )
Lists are collections of things
Those things come in a given order
user=> (quote (1 :a "item"))
user=> '(1 :a "item")
user=> (list 1 :a "item")
Lists are 'linked' lists
user=> (first (list 1 :a "item"))
user=> (rest (list 1 :a "item"))
nil
is the end of the list
user=> (first (rest (rest (rest (list 1 :a "item")))))
Building a list
user=> (cons :item '())
user=> (cons 1 nil)
user=> (cons "string" (cons :item (cons 5 nil)))
[ ]
Like 'arrays' because they have index access
user=> [1 :item "string"]
user=> (first [1 :item "string"])
user=> (rest [1 :item "string"])
Access by index
user=> (nth [1 :item "string"] 2)
Building a vector
user=> (cons 1/2 [1 :item "string"])
user=> (vector (cons 1/2 [1 :item "string"]))
Using conj[oin] function
user=> (conj [1 :item "string"] 1/2)
user=> (conj '(1 :item "string") 1/2)
{ }
Key-value pairs of data
user=> {:name "Your name" :last-name "Your lastname"}
Getting a value
user=> (get {:name "tomato" :price 1.25} :price)
user=> (get {:name "tomato" :price 1.25} :weight "Not found")
user=> (:price {:name "tomato" :price 1.25})
Building a Map
user=> (assoc {:name "tomato" :price 1.25} :weight {:quantity 4 :unit :ounces})
user=> (dissoc {:name "tomato" :price 1.25 :weight {:quantity 4 :unit :ounces}} :name)
user=> (merge {:name "tomato"} {:price 1.25} {:weight {:quantity 4 :unit :ounces}})
Values and Keys
user=> (keys {:name "tomato" :price 1.25})
user=> (vals {:name "tomato" :price 1.25})
#{ }
Collections of elements with no duplicates
user=> #{:apple :banana :melon :blue-berry :apple}
user=> #{:apple :banana :melon :blue-berry}
Getting a value
user=> (get #{:apple :banana :melon :blue-berry} :banana)
user=> (#{:apple :banana :melon :blue-berry} :banana)
Building a Set
user=> (conj #{:apple :banana :melon :blue-berry} :black-berry)
user=> (disj #{:apple :banana :melon :blue-berry} :melon)
Interesting operations
user=> (clojure.set/union #{:r :b :w} #{:w :p :y})
user=> (clojure.set/difference #{:r :b :w} #{:w :p :y})
user=> (clojure.set/intersection #{:r :b :w} #{:w :p :y})
Clojure symbols refer to values.
user=> (def my-vector [1 2 3])
What if I dont need a temporary var?
user=> (let [msg "Say Hello"] (println msg))
What happens in let
, stays in let
user=> (def my-number 1)
user=> (let [my-number 2] (println my-number))
Declaring a funcion with fn
user=> (fn [])
user=> ((fn []))
user=> ((fn [] "Hello"))
user=> (def say-hello (fn [] "Hello"))
user=> (say-hello)
user=> #("Hello")
user=> (#("Hello"))
user=> (#(str "Hello"))
Using defn
user=> (defn sum [a b] (+ a b))
user=> (sum 1 2)
To keep everything organized and group similar funtionality
user=> (ns com.nearsoft)
com.nearsoft=> (def my-email<EMAIL_ADDRESS>com.nearsoft=> my-email
com.nearsoft=> com.nearsoft/my-email
com.nearsoft=> *ns*
com.nearsoft=> (ns user)
user=> com.nearsoft/my-email
Accesing symbols in namespaces with require
user=> (require 'com.nearsoft)
user=> (require '[com.nearsoft :as ns])
user=> (require '[com.nearsoft :refer [my-email]])
user=> (require '[com.nearsoft :refer :all)
Using require
inside ns
user=> (ns com.acme
(:require [com.nearsoft :refer :all]))
com.acme=> my-email
if
Takes three params: logical test, expression to be evaluated when logical test is true, and expression if logical test is false
user=> (if true "This is true" "This is false")
user=> (if false "This is true" "This is false")
user=> (if (= :beer (keyword "beer")) "Lets drink!" "Dont drink!")
What about nil
?
user=> (if nil "This is true" "This is false")
if-let
Sames as if
but also allows you to bind an expression to a symbol and use it ONLY WHEN IT IS TRUE.
user=> (if-let [logical-value true]
(println (str "true is " logical-value))
(println (str "false is " logical-value)))
user=> (if-let [logical-value true]
(println (str "true is " logical-value))
(println (str "This is false")))
when
If the predicate is true, evaluates the body. Otherwise, it returns nil.
user=> (when (= 5 (+ 2 3)) "Its a five!")
when-let
Exactly same idea as if-let
user=> (defn drop-first
[coll]
(when-let [s (seq coll)]
(rest s)))
user=> (drop-first [1 2 3])
user=> (drop-first [])
cond
What if we want to test multiple things?
user=> (defn buy-a-beer?
[price]
(if (> price 5)
"Its expensive!"
(if (< price 5)
"Nah, I can buy a better beer"
(if (= price 5)
"Shut up and take my money!"))))
user=> (defn buy-a-beer-cond?
[price]
(cond
(> price 5) "Its expensive!"
(< price 5) "Nah, I can buy a better beer"
(= price 5) "Shut up and take my money!"))
Warning: The order of the test are important
Default clause? Add :else at the end
user=> (defn buy-a-beer-cond?
[price]
(cond
(> price 5) "Its expensive!"
(< price 5) "Nah, I can buy a better beer"
:else "Shut up and take my money!"))
case
Shortcut for cond when there is only one test value and it can be compared using =
user=> (defn should-drink?
[beverage]
(case beverage
"beer" "Yeah, go ahead"
"wine" "A little"
"rum" "hmm, I pass"
"I dont know"))
user=> (should-drink? "beer")
user=> (should-drink? "tequila")
High Order Functions
Sequence Comprehensions
Destructuring
Recursion
Java Interop
Macros
Concurrency


|
ActiveTcl User Guide
|
||
Tk_GetUid, Tk_Uid - convert from string to unique identifier
#include <tk.h>
#typedef char *Tk_Uid
Tk_Uid
Tk_GetUid(string)
Tk_GetUid returns the unique identifier corresponding to string. Unique identifiers are similar to atoms in Lisp, and are used in Tk to speed up comparisons and searches. A unique identifier (type Tk_Uid) is a string pointer and may be used anywhere that a variable of type ``char *'' could be used. However, there is guaranteed to be exactly one unique identifier for any given string value. If Tk_GetUid is called twice, once with string a and once with string b, and if a and b have the same string value (strcmp(a, b) == 0), then Tk_GetUid will return exactly the same Tk_Uid value for each call (Tk_GetUid(a) == Tk_GetUid(b)). This means that variables of type Tk_Uid may be compared directly (x == y) without having to call strcmp. In addition, the return value from Tk_GetUid will have the same string value as its argument (strcmp(Tk_GetUid(a), a) == 0).
Copyright © 1990 The Regents of the University of California. Copyright © 1994-1996 Sun Microsystems, Inc. Copyright © 1995-1997 Roger E. Critchlow Jr.


Events
Events are provided by Owl Carousel in strategic code locations. This gives you the ability to listen for any changes and perform your own actions.
var owl = $('.owl-carousel');
owl.owlCarousel();
// Listen to owl events:
owl.on('changed.owl.carousel', function(event) {
...
})
You could also trigger events by yourself to control Owl Carousel:
var owl = $('.owl-carousel');
owl.owlCarousel();
// Go to the next item
$('.customNextBtn').click(function() {
owl.trigger('next.owl.carousel');
})
// Go to the previous item
$('.customPrevBtn').click(function() {
// With optional speed parameter
// Parameters has to be in square bracket '[]'
owl.trigger('prev.owl.carousel', [300]);
})
Callbacks
Instead of attaching an event handler you can also just add a callback to the options of Owl Carousel.
$('.owl-carousel').owlCarousel({
onDragged: callback
});
function callback(event) {
...
}
Data
Each event passes very useful information within the event object . Based on the example above:
function callback(event) {
// Provided by the core
var element = event.target; // DOM element, in this example .owl-carousel
var name = event.type; // Name of the event, in this example dragged
var namespace = event.namespace; // Namespace of the event, in this example owl.carousel
var items = event.item.count; // Number of items
var item = event.item.index; // Position of the current item
// Provided by the navigation plugin
var pages = event.page.count; // Number of pages
var page = event.page.index; // Position of the current page
var size = event.page.size; // Number of items per page
}
Carousel
initialize.owl.carousel
Type: attachable
Callback: onInitialize
When the plugin initializes.
initialized.owl.carousel
Type: attachable
Callback: onInitialized
When the plugin has initialized.
resize.owl.carousel
Type: attachable
Callback: onResize
When the plugin gets resized.
resized.owl.carousel
Type: attachable
Callback: onResized
When the plugin has resized.
refresh.owl.carousel
Type: attachable, cancelable, triggerable
Callback: onRefresh
Parameter: [event, speed]
When the internal state of the plugin needs update.
refreshed.owl.carousel
Type: attachable
Callback: onRefreshed
When the internal state of the plugin has updated.
drag.owl.carousel
Type: attachable
Callback: onDrag
When the dragging of an item is started.
dragged.owl.carousel
Type: attachable
Callback: onDragged
When the dragging of an item has finished.
translate.owl.carousel
Type: attachable
Callback: onTranslate
When the translation of the stage starts.
translated.owl.carousel
Type: attachable
Callback: onTranslated
When the translation of the stage has finished.
change.owl.carousel
Type: attachable
Callback: onChange
Parameter: property
When a property is going to change its value.
changed.owl.carousel
Type: attachable
Callback: onChanged
Parameter: property
When a property has changed its value.
next.owl.carousel
Type: triggerable
Parameter: [speed]
Goes to next item.
prev.owl.carousel
Type: triggerable
Parameter: [speed]
Goes to previous item.
to.owl.carousel
Type: triggerable
Parameter: [position, speed]
Goes to position.
destroy.owl.carousel
Type: triggerable
Destroys carousel.
replace.owl.carousel
Type: triggerable
Parameter: data
Removes current content and add a new one passed in the parameter.
add.owl.carousel
Type: triggerable
Parameter: [data, position]
Adds a new item on a given position.
remove.owl.carousel
Type: triggerable
Parameter: position
Removes an item from a given position.
Lazy
load.owl.lazy
Type: attachable
Callback: onLoadLazy
When lazy image loads.
loaded.owl.lazy
Type: attachable
Callback: onLoadedLazy
When lazy image has loaded.
Autoplay
play.owl.autoplay
Type: triggerable
Parameter: [timeout, speed]
Runs autoplay.
stop.owl.autoplay
Type: triggerable
Stops autoplay.
Video
stop.owl.video
Type: attachable
Callback: onStopVideo
When video has unloaded.
play.owl.video
Type: attachable
Callback: onPlayVideo
When video has loaded.


|
Graphitti
A toolkit/software architecture to ease creating high-performance neural network simulators
|
Public Member Functions | |
| XmlSTDPRecorder () | |
| THe constructor and destructor. More... | |
| virtual void | initDefaultValues () |
| Init radii and rates history matrices with default values. More... | |
| virtual void | initValues () |
| InitValues gets the values for weights, source index and dest index at the time of simulation start. More... | |
| virtual void | getValues () |
| Get the current synapse weight information. More... | |
| virtual void | compileHistories (IAllVertices &neurons) |
| virtual void | saveSimData (const IAllVertices &neurons) |
| virtual void | printParameters () |
| virtual string | toXML (string name, vector< vector< BGFLOAT >> MatrixToWrite) const |
| convert Matrix to XML string | |
| virtual string | toXML (string name, vector< vector< int >> MatrixToWrite) const |
| convert Matrix to XML string | |
| Public Member Functions inherited from XmlRecorder | |
| XmlRecorder () | |
| constructor | |
| ~XmlRecorder () | |
| destructor | |
| virtual void | init () override |
| virtual void | term () override |
| Terminate process. | |
Static Public Member Functions | |
| static IRecorder * | Create () |
| Static Public Member Functions inherited from XmlRecorder | |
| static IRecorder * | Create () |
Protected Attributes | |
| vector< vector< BGFLOAT > > | weightsHistory_ |
| vector< vector< int > > | sourceNeuronIndexHistory_ |
| vector< vector< int > > | destNeuronIndexHistory_ |
| Protected Attributes inherited from XmlRecorder | |
| ofstream | stateOut_ |
| VectorMatrix | burstinessHist_ |
| VectorMatrix | spikesHistory_ |
| Protected Attributes inherited from IRecorder | |
| string | resultFileName_ |
| File path to the file that the results will be printed to. | |
| log4cplus::Logger | fileLogger_ |
| Loggers used to print to using log4cplus logging macros, prints to Results/Debug/logging.txt. | |
Additional Inherited Members | |
| Protected Member Functions inherited from XmlRecorder | |
| void | getStarterNeuronMatrix (VectorMatrix &matrix, const bool *starterMap) |
Definition at line 40 of file XmlSTDPRecorder.h.
| XmlSTDPRecorder::XmlSTDPRecorder | ( | ) |
THe constructor and destructor.
The constructor and destructor.
Definition at line 18 of file XmlSTDPRecorder.cpp.
|
virtual |
Compile history information in every epoch
| [in] | neurons | The entire list of neurons. |
Reimplemented from XmlRecorder.
Definition at line 77 of file XmlSTDPRecorder.cpp.
|
virtual |
Get the current synapse weight information.
Get the current radii and rates vlaues
Reimplemented from XmlRecorder.
Definition at line 61 of file XmlSTDPRecorder.cpp.
|
virtual |
Init radii and rates history matrices with default values.
Init radii and rates history matrices with default values
Reimplemented from XmlRecorder.
Definition at line 39 of file XmlSTDPRecorder.cpp.
|
virtual |
InitValues gets the values for weights, source index and dest index at the time of simulation start.
Init radii and rates history matrices with current radii and rates
Reimplemented from XmlRecorder.
Definition at line 48 of file XmlSTDPRecorder.cpp.
|
virtual |
Prints out all parameters to logging file. Registered to OperationManager as Operation::printParameters
Reimplemented from XmlRecorder.
Definition at line 207 of file XmlSTDPRecorder.cpp.
|
virtual |
Writes simulation results to an output destination.
| neurons | the Neuron list to search from. |
Reimplemented from XmlRecorder.
Definition at line 147 of file XmlSTDPRecorder.cpp.


Image Preprocessing
ImageDataGenerator class
keras.preprocessing.image.ImageDataGenerator(featurewise_center=False, samplewise_center=False, featurewise_std_normalization=False, samplewise_std_normalization=False, zca_whitening=False, zca_epsilon=1e-06, rotation_range=0, width_shift_range=0.0, height_shift_range=0.0, brightness_range=None, shear_range=0.0, zoom_range=0.0, channel_shift_range=0.0, fill_mode='nearest', cval=0.0, horizontal_flip=False, vertical_flip=False, rescale=None, preprocessing_function=None, data_format='channels_last', validation_split=0.0, interpolation_order=1, dtype='float32')
Generate batches of tensor image data with real-time data augmentation. The data will be looped over (in batches).
Arguments
- featurewise_center: Boolean. Set input mean to 0 over the dataset, feature-wise.
- samplewise_center: Boolean. Set each sample mean to 0.
- featurewise_std_normalization: Boolean. Divide inputs by std of the dataset, feature-wise.
- samplewise_std_normalization: Boolean. Divide each input by its std.
- zca_epsilon: epsilon for ZCA whitening. Default is 1e-6.
- zca_whitening: Boolean. Apply ZCA whitening.
- rotation_range: Int. Degree range for random rotations.
- width_shift_range: Float, 1-D array-like or int
- float: fraction of total width, if < 1, or pixels if >= 1.
- 1-D array-like: random elements from the array.
- int: integer number of pixels from interval
(-width_shift_range, +width_shift_range)
- With
width_shift_range=2
possible values are integers[-1, 0, +1]
, same as withwidth_shift_range=[-1, 0, +1]
, while withwidth_shift_range=1.0
possible values are floats in the interval [-1.0, +1.0).
- height_shift_range: Float, 1-D array-like or int
- float: fraction of total height, if < 1, or pixels if >= 1.
- 1-D array-like: random elements from the array.
- int: integer number of pixels from interval
(-height_shift_range, +height_shift_range)
- With
height_shift_range=2
possible values are integers[-1, 0, +1]
, same as withheight_shift_range=[-1, 0, +1]
, while withheight_shift_range=1.0
possible values are floats in the interval [-1.0, +1.0).
- brightness_range: Tuple or list of two floats. Range for picking a brightness shift value from.
- shear_range: Float. Shear Intensity (Shear angle in counter-clockwise direction in degrees)
- zoom_range: Float or [lower, upper]. Range for random zoom.
If a float,
[lower, upper] = [1-zoom_range, 1+zoom_range]
. - channel_shift_range: Float. Range for random channel shifts.
- fill_mode: One of {"constant", "nearest", "reflect" or "wrap"}.
Default is 'nearest'.
Points outside the boundaries of the input are filled
according to the given mode:
- 'constant': kkkkkkkk|abcd|kkkkkkkk (cval=k)
- 'nearest': aaaaaaaa|abcd|dddddddd
- 'reflect': abcddcba|abcd|dcbaabcd
- 'wrap': abcdabcd|abcd|abcdabcd
- cval: Float or Int.
Value used for points outside the boundaries
when
fill_mode = "constant"
. - horizontal_flip: Boolean. Randomly flip inputs horizontally.
- vertical_flip: Boolean. Randomly flip inputs vertically.
- rescale: rescaling factor. Defaults to None. If None or 0, no rescaling is applied, otherwise we multiply the data by the value provided (after applying all other transformations).
- preprocessing_function: function that will be applied on each input. The function will run after the image is resized and augmented. The function should take one argument: one image (Numpy tensor with rank 3), and should output a Numpy tensor with the same shape.
- data_format: Image data format,
either "channels_first" or "channels_last".
"channels_last" mode means that the images should have shape
(samples, height, width, channels)
, "channels_first" mode means that the images should have shape(samples, channels, height, width)
. It defaults to theimage_data_format
value found in your Keras config file at~/.keras/keras.json
. If you never set it, then it will be "channels_last". - validation_split: Float. Fraction of images reserved for validation (strictly between 0 and 1).
- dtype: Dtype to use for the generated arrays.
Examples
Example of using .flow(x, y)
:
(x_train, y_train), (x_test, y_test) = cifar10.load_data()
y_train = np_utils.to_categorical(y_train, num_classes)
y_test = np_utils.to_categorical(y_test, num_classes)
datagen = ImageDataGenerator(
featurewise_center=True,
featurewise_std_normalization=True,
rotation_range=20,
width_shift_range=0.2,
height_shift_range=0.2,
horizontal_flip=True)
# compute quantities required for featurewise normalization
# (std, mean, and principal components if ZCA whitening is applied)
datagen.fit(x_train)
# fits the model on batches with real-time data augmentation:
model.fit_generator(datagen.flow(x_train, y_train, batch_size=32),
steps_per_epoch=len(x_train) / 32, epochs=epochs)
# here's a more "manual" example
for e in range(epochs):
print('Epoch', e)
batches = 0
for x_batch, y_batch in datagen.flow(x_train, y_train, batch_size=32):
model.fit(x_batch, y_batch)
batches += 1
if batches >= len(x_train) / 32:
# we need to break the loop by hand because
# the generator loops indefinitely
break
Example of using .flow_from_directory(directory)
:
train_datagen = ImageDataGenerator(
rescale=1./255,
shear_range=0.2,
zoom_range=0.2,
horizontal_flip=True)
test_datagen = ImageDataGenerator(rescale=1./255)
train_generator = train_datagen.flow_from_directory(
'data/train',
target_size=(150, 150),
batch_size=32,
class_mode='binary')
validation_generator = test_datagen.flow_from_directory(
'data/validation',
target_size=(150, 150),
batch_size=32,
class_mode='binary')
model.fit_generator(
train_generator,
steps_per_epoch=2000,
epochs=50,
validation_data=validation_generator,
validation_steps=800)
Example of transforming images and masks together.
# we create two instances with the same arguments
data_gen_args = dict(featurewise_center=True,
featurewise_std_normalization=True,
rotation_range=90,
width_shift_range=0.1,
height_shift_range=0.1,
zoom_range=0.2)
image_datagen = ImageDataGenerator(**data_gen_args)
mask_datagen = ImageDataGenerator(**data_gen_args)
# Provide the same seed and keyword arguments to the fit and flow methods
seed = 1
image_datagen.fit(images, augment=True, seed=seed)
mask_datagen.fit(masks, augment=True, seed=seed)
image_generator = image_datagen.flow_from_directory(
'data/images',
class_mode=None,
seed=seed)
mask_generator = mask_datagen.flow_from_directory(
'data/masks',
class_mode=None,
seed=seed)
# combine generators into one which yields image and masks
train_generator = zip(image_generator, mask_generator)
model.fit_generator(
train_generator,
steps_per_epoch=2000,
epochs=50)
Example of using .flow_from_dataframe(dataframe, directory,
:
train_df = pandas.read_csv("./train.csv")
valid_df = pandas.read_csv("./valid.csv")
train_datagen = ImageDataGenerator(
rescale=1./255,
shear_range=0.2,
zoom_range=0.2,
horizontal_flip=True)
test_datagen = ImageDataGenerator(rescale=1./255)
train_generator = train_datagen.flow_from_dataframe(
dataframe=train_df,
directory='data/train',
x_col="filename",
y_col="class",
target_size=(150, 150),
batch_size=32,
class_mode='binary')
validation_generator = test_datagen.flow_from_dataframe(
dataframe=valid_df,
directory='data/validation',
x_col="filename",
y_col="class",
target_size=(150, 150),
batch_size=32,
class_mode='binary')
model.fit_generator(
train_generator,
steps_per_epoch=2000,
epochs=50,
validation_data=validation_generator,
validation_steps=800)
ImageDataGenerator methods
apply_transform
apply_transform(x, transform_parameters)
Applies a transformation to an image according to given parameters.
Arguments
- x: 3D tensor, single image.
- transform_parameters: Dictionary with string - parameter pairs
describing the transformation.
Currently, the following parameters
from the dictionary are used:
'theta'
: Float. Rotation angle in degrees.'tx'
: Float. Shift in the x direction.'ty'
: Float. Shift in the y direction.'shear'
: Float. Shear angle in degrees.'zx'
: Float. Zoom in the x direction.'zy'
: Float. Zoom in the y direction.'flip_horizontal'
: Boolean. Horizontal flip.'flip_vertical'
: Boolean. Vertical flip.'channel_shift_intencity'
: Float. Channel shift intensity.'brightness'
: Float. Brightness shift intensity.
Returns
A transformed version of the input (same shape).
fit
fit(x, augment=False, rounds=1, seed=None)
Fits the data generator to some sample data.
This computes the internal data stats related to the data-dependent transformations, based on an array of sample data.
Only required if featurewise_center
or
featurewise_std_normalization
or zca_whitening
are set to True.
Arguments
- x: Sample data. Should have rank 4. In case of grayscale data, the channels axis should have value 1, in case of RGB data, it should have value 3, and in case of RGBA data, it should have value 4.
- augment: Boolean (default: False). Whether to fit on randomly augmented samples.
- rounds: Int (default: 1).
If using data augmentation (
augment=True
), this is how many augmentation passes over the data to use. - seed: Int (default: None). Random seed.
flow
flow(x, y=None, batch_size=32, shuffle=True, sample_weight=None, seed=None, save_to_dir=None, save_prefix='', save_format='png', subset=None)
Takes data & label arrays, generates batches of augmented data.
Arguments
- x: Input data. Numpy array of rank 4 or a tuple. If tuple, the first element should contain the images and the second element another numpy array or a list of numpy arrays that gets passed to the output without any modifications. Can be used to feed the model miscellaneous data along with the images. In case of grayscale data, the channels axis of the image array should have value 1, in case of RGB data, it should have value 3, and in case of RGBA data, it should have value 4.
- y: Labels.
- batch_size: Int (default: 32).
- shuffle: Boolean (default: True).
- sample_weight: Sample weights.
- seed: Int (default: None).
- save_to_dir: None or str (default: None). This allows you to optionally specify a directory to which to save the augmented pictures being generated (useful for visualizing what you are doing).
- save_prefix: Str (default:
''
). Prefix to use for filenames of saved pictures (only relevant ifsave_to_dir
is set). - save_format: one of "png", "jpeg"
(only relevant if
save_to_dir
is set). Default: "png". - subset: Subset of data (
"training"
or"validation"
) ifvalidation_split
is set inImageDataGenerator
.
Returns
An Iterator
yielding tuples of (x, y)
where x
is a numpy array of image data
(in the case of a single image input) or a list
of numpy arrays (in the case with
additional inputs) and y
is a numpy array
of corresponding labels. If 'sample_weight' is not None,
the yielded tuples are of the form (x, y, sample_weight)
.
If y
is None, only the numpy array x
is returned.
flow_from_dataframe
flow_from_dataframe(dataframe, directory=None, x_col='filename', y_col='class', weight_col=None, target_size=(256, 256), color_mode='rgb', classes=None, class_mode='categorical', batch_size=32, shuffle=True, seed=None, save_to_dir=None, save_prefix='', save_format='png', subset=None, interpolation='nearest', validate_filenames=True)
Takes the dataframe and the path to a directory and generates batches of augmented/normalized data.
A simple tutorial can be found here.
Arguments
-
dataframe: Pandas dataframe containing the filepaths relative to
directory
(or absolute paths ifdirectory
is None) of the images in a string column. It should include other column/s depending on theclass_mode
:- if
class_mode
is"categorical"
(default value) it must include they_col
column with the class/es of each image. Values in column can be string/list/tuple if a single class or list/tuple if multiple classes. - if
class_mode
is"binary"
or"sparse"
it must include the giveny_col
column with class values as strings. - if
class_mode
is"raw"
or"multi_output"
it should contain
the columns specified in
y_col
.- if
class_mode
is"input"
orNone
no extra column is needed. - directory: string, path to the directory to read images from. If
None
, data inx_col
column should be absolute paths. - x_col: string, column in
dataframe
that contains the filenames (or absolute paths ifdirectory
isNone
). - y_col: string or list, column/s in
dataframe
that has the target data. - weight_col: string, column in
dataframe
that contains the sample weights. Default:None
. - target_size: tuple of integers
(height, width)
, default:(256, 256)
. The dimensions to which all images found will be resized. - color_mode: one of "grayscale", "rgb", "rgba". Default: "rgb". Whether the images will be converted to have 1 or 3 color channels.
- classes: optional list of classes (e.g.
['dogs', 'cats']
). Default: None. If not provided, the list of classes will be automatically inferred from they_col
, which will map to the label indices, will be alphanumeric). The dictionary containing the mapping from class names to class indices can be obtained via the attributeclass_indices
. - class_mode: one of "binary", "categorical", "input", "multi_output", "raw", sparse" or None. Default: "categorical". Mode for yielding the targets:
"binary"
: 1D numpy array of binary labels,"categorical"
: 2D numpy array of one-hot encoded labels. Supports multi-label output."input"
: images identical to input images (mainly used to work with autoencoders),"multi_output"
: list with the values of the different columns,"raw"
: numpy array of values iny_col
column(s),"sparse"
: 1D numpy array of integer labels,None
, no targets are returned (the generator will only yield batches of image data, which is useful to use inmodel.predict_generator()
).- batch_size: size of the batches of data (default: 32).
- shuffle: whether to shuffle the data (default: True)
- seed: optional random seed for shuffling and transformations.
- save_to_dir: None or str (default: None). This allows you to optionally specify a directory to which to save the augmented pictures being generated (useful for visualizing what you are doing).
- save_prefix: str. Prefix to use for filenames of saved pictures
(only relevant if
save_to_dir
is set). - save_format: one of "png", "jpeg"
(only relevant if
save_to_dir
is set). Default: "png". - follow_links: whether to follow symlinks inside class subdirectories (default: False).
- subset: Subset of data (
"training"
or"validation"
) ifvalidation_split
is set inImageDataGenerator
. - interpolation: Interpolation method used to resample the image if the
target size is different from that of the loaded image.
Supported methods are
"nearest"
,"bilinear"
, and"bicubic"
. If PIL version 1.1.3 or newer is installed,"lanczos"
is also supported. If PIL version 3.4.0 or newer is installed,"box"
and"hamming"
are also supported. By default,"nearest"
is used. - validate_filenames: Boolean, whether to validate image filenames in
x_col
. IfTrue
, invalid images will be ignored. Disabling this option can lead to speed-up in the execution of this function. Default:True
.
- if
Returns
A DataFrameIterator
yielding tuples of (x, y)
where x
is a numpy array containing a batch
of images with shape (batch_size, *target_size, channels)
and y
is a numpy array of corresponding labels.
flow_from_directory
flow_from_directory(directory, target_size=(256, 256), color_mode='rgb', classes=None, class_mode='categorical', batch_size=32, shuffle=True, seed=None, save_to_dir=None, save_prefix='', save_format='png', follow_links=False, subset=None, interpolation='nearest')
Takes the path to a directory & generates batches of augmented data.
Arguments
- directory: string, path to the target directory. It should contain one subdirectory per class. Any PNG, JPG, BMP, PPM or TIF images inside each of the subdirectories directory tree will be included in the generator. See this script for more details.
- target_size: Tuple of integers
(height, width)
, default:(256, 256)
. The dimensions to which all images found will be resized. - color_mode: One of "grayscale", "rgb", "rgba". Default: "rgb". Whether the images will be converted to have 1, 3, or 4 channels.
- classes: Optional list of class subdirectories
(e.g.
['dogs', 'cats']
). Default: None. If not provided, the list of classes will be automatically inferred from the subdirectory names/structure underdirectory
, where each subdirectory will be treated as a different class (and the order of the classes, which will map to the label indices, will be alphanumeric). The dictionary containing the mapping from class names to class indices can be obtained via the attributeclass_indices
. - class_mode: One of "categorical", "binary", "sparse",
"input", or None. Default: "categorical".
Determines the type of label arrays that are returned:
- "categorical" will be 2D one-hot encoded labels,
- "binary" will be 1D binary labels, "sparse" will be 1D integer labels,
- "input" will be images identical to input images (mainly used to work with autoencoders).
- If None, no labels are returned
(the generator will only yield batches of image data,
which is useful to use with
model.predict_generator()
). Please note that in case of class_mode None, the data still needs to reside in a subdirectory ofdirectory
for it to work correctly.
- batch_size: Size of the batches of data (default: 32).
- shuffle: Whether to shuffle the data (default: True) If set to False, sorts the data in alphanumeric order.
- seed: Optional random seed for shuffling and transformations.
- save_to_dir: None or str (default: None). This allows you to optionally specify a directory to which to save the augmented pictures being generated (useful for visualizing what you are doing).
- save_prefix: Str. Prefix to use for filenames of saved pictures
(only relevant if
save_to_dir
is set). - save_format: One of "png", "jpeg"
(only relevant if
save_to_dir
is set). Default: "png". - follow_links: Whether to follow symlinks inside class subdirectories (default: False).
- subset: Subset of data (
"training"
or"validation"
) ifvalidation_split
is set inImageDataGenerator
. - interpolation: Interpolation method used to
resample the image if the
target size is different from that of the loaded image.
Supported methods are
"nearest"
,"bilinear"
, and"bicubic"
. If PIL version 1.1.3 or newer is installed,"lanczos"
is also supported. If PIL version 3.4.0 or newer is installed,"box"
and"hamming"
are also supported. By default,"nearest"
is used.
Returns
A DirectoryIterator
yielding tuples of (x, y)
where x
is a numpy array containing a batch
of images with shape (batch_size, *target_size, channels)
and y
is a numpy array of corresponding labels.
get_random_transform
get_random_transform(img_shape, seed=None)
Generates random parameters for a transformation.
Arguments
- seed: Random seed.
- img_shape: Tuple of integers. Shape of the image that is transformed.
Returns
A dictionary containing randomly chosen parameters describing the transformation.
random_transform
random_transform(x, seed=None)
Applies a random transformation to an image.
Arguments
- x: 3D tensor, single image.
- seed: Random seed.
Returns
A randomly transformed version of the input (same shape).
standardize
standardize(x)
Applies the normalization configuration in-place to a batch of inputs.
x
is changed in-place since the function is mainly used internally
to standarize images and feed them to your network. If a copy of x
would be created instead it would have a significant performance cost.
If you want to apply this method without changing the input in-place
you can call the method creating a copy before:
standarize(np.copy(x))
Arguments
- x: Batch of inputs to be normalized.
Returns
The inputs, normalized.


The logic of foreign aid is simple: the more money a country is given, the more it will be able to secure the resources it needs to cultivate success that extends into the future. Unfortunately, that simple formula rarely holds true in the real world.
The chart below shows OECD data on the total amount given -- since 1960 -- to every aid recipient country. Two other data points underlie the simple bar graph: the 2011 Corruption Perceptions Index produced by Transparency International, and rates of internet use per 100 people, provided by the World Bank (for 2011 or the bank's most recent figures). You can use the menu below to manipulate how these data points affect the order and coloring of the chart.
The picture that emerges is one in which the countries that have received greater amounts of aid are more likely to be corrupt and technologically backward. Try, for example, to sort the data by foreign aid received, and color it by the Corruption Perceptions Index. The obvious trend is that a disproportionate number of red (corrupt) countries sit atop this mountain of aid. The same is true for coloring related to internet users per 100 people in the country. One of the most striking examples is South Korea, which despite being given less than US$2 billion since 1960 is ranked second in terms of internet penetration.
Internet access and fair government are two things we would have expected to result from significant amounts of aid. In fact, the opposite appears to be the case.


Time
Service Name
Service Instance
Action
2016-08-01 12:13:14
SomeService
AnyInstance
Online/Offline


distributed
hierarchical
transitions
of
individuality
It's an evolution experiment where computer programs are evolving!
Each little grid title --- something like a biological cell --- is controlled by four virtual CPUs working in tandem (one for each side of the tile).
Depending on the program loaded into the cell, different decisions are made in response to environmental events and messages from neighboring cells.
For those in the know, virtual CPUs are being implemented using SignalGP [Lalejini and Ofria, 2018].
These cells are presented with a cooperative resource collection task.
In order to maximize their resource-collection rate, they need to organize into family resource-collecting groups (which we call "channels") that are just the right size... not too big and not too small!
Better-configured resource-collecting groups will tend to outcompete other groups for space on the grid.
Cells use resource they collect to reproduce.
When a cell has enough resource, it can copy its program into a neighboring cell.
The copy isn't perfect, though... usually, the program changes slightly (mutates) during this process.
My Darwin fanboys out there are probably onto it already, but
heritable variation + differential reproductive success (some programs are better at competing for space in the population) = ... evolution!
In previous work [Moreno and Ofria, 2019], we found that in response to this particular resource-collection task, strategies built on
reproductive division of labor,
resource sharing between cells, and
parental care for offspring
tend to evolve.
Such traits are suggestive of multicellularity... or, in fancy science-speak a fraternal transition in individuality [Smith and Szathmary, 1997].
So, why do this type of thing at all?
On one hand, we're using this model to ask and answer scientific questions about the evolution of multicellularity in order to better understand the processes at play behind life on Earth.
On the other, we hope that transitions in individuality --- which were key to the complexification and diversification of life on Earth --- can help us evolve sophisticated --- and perhaps useful --- computational systems, like reinforcement-learning agents.
But this web viewer is here so you can get a peek at evolution in action!
We reccomend letting the simulation run maybe 10,000 updates with rendering off (so it runs faster).
Then, render every update and look at
resource sharing in the Resource Sharing Viewer and
signs of reproductive cooperation in the Reproductive Pause Viewer and Resource Stockpile Viewer.
You might need to go get a cup of coffee before there's anything interesting to look at.
Pressed for time?
Watch a pre-rendered timelapse on YouTube here.
And, for extra credit be sure to
twiddle parameters in Configuration,
look at a program in the Dominant Genotype viewer (... can you figure out what it evolved to do?),
check out how the software is put together in Source & Ingredients, and
click over to Let's Chat and let us know what you think!
The Channel Viewer shows the arrangement of hereditarily-defined resource-collecing cell groups.
Color saturation (e.g.,
light green
vs.
intense green
) differentiates low-level groups.
Color hue (e.g.,
light blue
/
intense blue
vs.
light purple
/
intense purple
) differentiates high-level groups, which are groups of low-level groups.
White
borders divide low-level groups that are part of the same high-level group.
Black
borders divide high-level groups.
The Stockpile Viewer depicts the resource that each cell-like organism has accumulated.
Black
grid tiles are dead cells.
Red
indicates a resource defecit (which, if it becomes too extreme, will result in that cell's death).
White
indicates zero resource.
Blue
indicates positive resource, but below the threshold required for reproduction.
Green
indicates enough resource to reproduce.
Yellow
indicates an excess of resource, more than enough to reproduce.
The Contribution Viewer depicts the amount of resource has received from neighbors during the previous update.
Black
grid tiles are dead cells.
White
indicates zero resource was received.
Blue
indicates a small amount of resource was received.
Green
indicates an intermediate amount of resource was received.
Yellow
indicates a large amount of resource was received.
The Apoptosis Viewer shows cells that have registered themselves for imminent cellular suicidie.
Black
grid tiles are dead cells.
White
grid tiles are live cells.
Blue
cells are registered for partial apoptosis, where a underlying cell is destroyed but its channel structure is preserved.
Red
cells are registered for complete apoptosis, where a cell and its channel structure are totally destroyed.
The Taxa Viewer depicts the distribution of groups of genetically-identical cells.
Black
grid tiles are dead cells.
White
grid tiles are live cells.
White
lines divide cells with identical genotypes.
Red
lines divide cells with different genotypes.
The Resource Wave Viewer depicts the cells' cooperative resource-collection task.
Activation propagates outward in same-channel groups from an environmentally-triggered seed.
Green
cells are activated within the beneficial radius of the seed and are gaining resource.
Red
cells are activated outside the beneficial radius of the seed and are losing resource.
White
cells are in the ready state, meaning they can be activated by adjacent cooperating cells.
Blue
cells are in a quiescent state, meaning they cannot be activated by adjacent cooperating cells.
Black
grid tiles are dead cells.
The Channel Generation Viewer depicts generation counters that enforce a birth-death lifecycle.
White
cells are young members of a same-channel group.
They are capable of collecting resource and producing offspring that are group members.
Blue
cells are older members of a same-channel group, which still retain all the capabilities of younger cells.
Red
cells are oldest members of a same-channel group.
As coloring progress from light to dark red, cells lose their ability to create same-channel offspring and then to collect resource.
Black
grid tiles are dead cells.
The Expiration Viewer depicts end-of-the-road channel generation state in greater detail.
White
cells are young and retain all reproductive and resource-collection capabilities.
Blue cells are older and have lost same-channel reproductive capability.
Red
cells are oldest and have additionally lost resource-collection capability.
Black
grid tiles are dead cells.
The Reproductive Pause Viewer depicts reproductive cooperation.
White
cells have registered zero reproductive forbearance.
Green
cells have temporarily registred to pause reproduction in one direction.
Blue
cells have temporariliy registered to pause reproduction in two directions.
Purple
cells have temporariliy registered to pause reproduction in three directions.
Red
cells have temporarily registered to pause reproduction in all four directions.
Black
grid tiles are dead cells.
Hey!
You can adjust any of these parameters right in your web browser using URL query parameters.
For example, appending
?SEED=2&MUTATION_RATE=0.1
in your web browser's URL bar and refreshing will change the random number generator seed and mutation rate.
Parameters below are locked in at compile time, so you can't adjust them here...
:(
Comments, questions, concerns?
I started a twitter thread so we can chat!
Find the C++ and HTML source on GitHub.
MIT licensed, contributions welcome!
Data from and tutorials for the native version of the software is hosted on the
Open Science Framework.
The
Empirical C++ Library
for efficient, reliable, and accessible scientific software is the secret sauce behind the web visualization and digital evolution framework.
Emscripten
compiled it to javascript so it can run in your web browser.
Bootstrap
makes it look pretty and play nice with mobile devices.
Charles Ofria, Emily Dolson, Alex Lalejini, Jake Fenton, Matthew Andres Moreno, Steven Jorgensen, … Anya Vostinar. (2019, February 22). Empirical (Version v0.0.3). Zenodo. http://doi.org/10.5281/zenodo.2575607
Smith, John Maynard, and Eors Szathmary. The major transitions in evolution. Oxford University Press, 1997.
Lalejini, Alexander, and Charles Ofria. "Evolving event-driven programs with SignalGP." Proceedings of the Genetic and Evolutionary Computation Conference. ACM, 2018.
Moreno, Matthew Andres, and Charles Ofria. "Toward open-ended fraternal transitions in individuality." Artificial life 25.2 (2019): 117-133.
This research was supported in part by NSF grants DEB-1655715 and DBI-0939454.
This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1424871.


Equipment class that can create scriptable object.
More...
Equipment class that can create scriptable object.
◆ Use()
| override void Equipment.Use |
( |
| ) |
|
|
virtual |
◆ AgilityModifier
| int Equipment.AgilityModifier |
Agility modifier to be applied to PlayerStat.
◆ AttackModifier
| int Equipment.AttackModifier |
Attack modifier to be applied to PlayerStat.
◆ DefenceModifier
| int Equipment.DefenceModifier |
Defence modifier to be applied to PlayerStat.
◆ equipmentSlot
◆ MagicAttackModifier
| int Equipment.MagicAttackModifier |
Magic Attack modifier to be applied to PlayerStat.
◆ MagicDefenceModifier
| int Equipment.MagicDefenceModifier |
Magic Defence modifier to be applied to PlayerStat.
The documentation for this class was generated from the following file:
- C:/Users/Shaki/Desktop/Final Year/Final Year Project/Withering/Withering/Assets/Scripts/Items/Equipment.cs


Team Checklist
Date: ____________ | Time start: ________ | Time end: ________
Team Name/ID: ____________________
Team Key/Hash: ____________________
Team Members:
Scenario/Description:
Hosts/virtual machines given (Hostname, OS, IP address, purpose)
Tasks (Description, time given, time deadline, time complete, status)


|
Pog Engine
|
Class that represents an animate object Inherits from GameObject Differs by not being allowed to handle input. More...
#include <AnimateObject.hpp>
Public Member Functions | |
| AnimateObject (std::string name, float w, float h) | |
| Constrcutor for AnimateObject. More... | |
| void | updatePosition (Vec2 pos) |
| Updates the position of the object. More... | |
| void | updateVelocity (Vec2 vel) |
| Updates the velocity of the object. More... | |
| void | setPosition (Vec2 pos) |
| Sets the position of the object. More... | |
| void | setVelocity (Vec2 vel) |
| Sets the velocity of the object. More... | |
| void | handleCollision (std::vector< GameObject * > objs, std::vector< AnimateObject * > animObjs) |
| Handles and detects the collision of other objects. More... | |
| void | updateSprite () |
| Updates the Sprite Component of this object. More... | |
| void | updateTransform () |
| Updates the Transform Component of this object. | |
| void | Destroy () |
| Destroys the class. | |
| void | addCollisionCallback (py::object) |
| Upon a collision, add the inputted argument as a callback. More... | |
| Public Member Functions inherited from GameObject | |
| GameObject () | |
| constructs our GameObject | |
| GameObject (std::string gameObjectName, float width, float height) | |
| constructs our GameObject More... | |
| ~GameObject () | |
| Destructs our GameObject. | |
| void | addTransformComponent (TransformComponent *transformComponent) |
| adds a transformComponent to our GameObject More... | |
| void | addSpriteComponent (SpriteComponent *spriteComponent) |
| adds a SpriteComponent to our GameObject More... | |
| void | addCharacterSpriteComponent (CharacterSpriteComponent *characterSpriteComponent) |
| adds a CharacterSpriteComponent to our GameObject More... | |
| void | addSoundComponent (SoundComponent *soundComponent) |
| adds a SoundComponent to our GameObject More... | |
| TransformComponent * | getTransformComponent () |
| CharacterSpriteComponent * | getCharacterSpriteComponent () |
| SpriteComponent * | getSpriteComponent () |
| SoundComponent * | getSoundComponent () |
| void | render () |
| renders this GameObject | |
| float | getWidth () |
| float | getHeight () |
| void | Destroy () |
| Destroys the class. | |
| std::string | getGameObjectName () |
| Returns the name of the GameObject as a string. | |
Protected Attributes | |
| CollisionComponent * | m_collisioncomp |
| Protected Attributes inherited from GameObject | |
| float | width |
| float | height |
| std::string | m_gameObjectName |
| TransformComponent * | m_transformComponent |
| SpriteComponent * | m_spriteComponent |
| CharacterSpriteComponent * | m_characterSpriteComponent |
| SoundComponent * | m_soundComponent |
Class that represents an animate object Inherits from GameObject Differs by not being allowed to handle input.
| AnimateObject::AnimateObject | ( | std::string | name, |
| float | w, | ||
| float | h | ||
| ) |
Constrcutor for AnimateObject.
| name | string that represents the name of the object. |
| w | float that represents the width of the object. |
| h | float that represents the height of the object. |
| void AnimateObject::addCollisionCallback | ( | py::object | ) |
Upon a collision, add the inputted argument as a callback.
| object | A python function object |
| void AnimateObject::handleCollision | ( | std::vector< GameObject * > | objs, |
| std::vector< AnimateObject * > | animObjs | ||
| ) |
Handles and detects the collision of other objects.
| objs | A vector of game objects that we want to detect for collision. |
| void AnimateObject::setPosition | ( | Vec2 | pos | ) |
Sets the position of the object.
| pos | Vec2 that represents the position of the object we want to change it to. |
| void AnimateObject::setVelocity | ( | Vec2 | vel | ) |
Sets the velocity of the object.
| pos | Vec2 that represents the velocity of the object we want to change it to. |
| void AnimateObject::updatePosition | ( | Vec2 | pos | ) |
Updates the position of the object.
| pos | Vec2 that represents the position of the object. |
| void AnimateObject::updateSprite | ( | ) |
Updates the Sprite Component of this object.
| void AnimateObject::updateVelocity | ( | Vec2 | vel | ) |
Updates the velocity of the object.
| pos | Vec2 that represents the velocity of the object. |


Go to the source code of this file.
Moved to external file to avoid cluttering source code files. The mainpage.h file itself is not intended to be included in release packages, only used in documentation generation prior to release.
Definition in file mainpage.h.


{% extends 'bas.html'%} {% load bootstrap3 %} {% load static %} {%block content%}
We work together to improve our neighbourhood by holding some cleaning events once per week to safe guard our environment.
Simply just create your account and login
On the home page you will have a number of neighbourhood you can choose select one to join
You can also create your own neighbourhood of which others can join.
All it is needed is that you have to be a residence of around the neighbourhood.


We have rented out the whole campground. Our hope is that you all stay with us the whole weekend.
Accommodation info here.


|
Four Seasons
Apple Music:
#22 Vietnam (=)
#79 Cambodia (-6)
#79 Thailand (-13)
#128 Malaysia (-21)
#140 Singapore (-23)
#182 Indonesia (-43)
|
Blue
|
Album: I - The 1st Mini Album - EP
|
|


|
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Privacy and Security The 2000 employees of Altoro Mutual are dedicated to protecting your privacy and security. We pledge to provide you with the information and resources that you need to help secure your information and keep it confidential. This is our promise. Win a Samsung Galaxy S10 smartphone Completing this short survey will enter you in a draw for 1 of 5 Samsung Galaxy S10 smartphones! We look forward to hearing your important feedback. |


django-textvariation v0.1 documentation
There are several variations:
There are two variations:
A combination of both methods will be used in a non-normalized way to provide flexibility and performance. A variation table for each model with variations will store each variation for each field. A JSON/serialized field on the model will store a cached version of the same information.
The fields in the variation table are:
| field | Description |
|---|---|
| <model>_id | Foreign key to the row in the master table |
| fieldname | Name of the field in which this variation applies |
| <name>_dim | A field for each defined dimension to contain the dimension variant |
| is_invalid | A boolean flag to indicate the variation is currently invalid, as the default variation has changed. Declaring variations invalid instead of deleting them should be an option as to allow the site to continue to display the content. |
| value | The value of this variation for this field |
The cache field contains a structure based on the current DIMENSION_PRIORITY settings.
Warning
If this setting changes the cache field for each item in every table will need to be recalculated. There is a management command to do this.
The cache is a hierarchical dictionary with each field at the top level and then each dimension hierarchically contained in order of priority.
{
'field': {
'dim1-variant1': {
'dim2-variant1': 'variation value',
'dim2-variant2': 'variation value',
}
}
}
Assuming that we have three dimensions: audience, text difficulty, and language; a table called article with three variable fields: headline, subhead, and content; the table and metadata table might look like:
Note
See Example Settings for the configuration.
If you added a row into article, you might have
| Id | Headline | Subhead | Byline | Content | Text Variations |
|---|---|---|---|---|---|
| 1 | First article | Carmen | Lots of ... | {'headline':{'en':{'ad'... |
The Text Variations field would contain a serialized dictionary:
{
'headline': {
'en': { 'ad': { 's': 'First Article',},},},
'subhead': {
'en': { 'ad': { 's': '',},},},
'content': {
'en': { 'ad': { 's': 'Lots of ...',},},},
}
And the Audience Variation table contains
| Id | Article Id | Fieldname | Audience Dim | Language Dim | Text Difficulty Dim | Is Invalid | Value |
|---|---|---|---|---|---|---|---|
| 1 | 1 | headline | ad | en | s | False | First Article |
| 2 | 1 | subhead | ad | en | s | False | |
| 3 | 1 | content | ad | en | s | False | Lots of ... |
If you add a spanish variation to the headline and content fields, the Text Variations field would contain:
{
'headline': {
'en': { 'ad': { 's': 'First Article',},},
'es': { 'ad': { 's': u'Artículo Primero',},},},
'subhead': {
'en': { 'ad': { 's': '',},},},
'content': {
'en': { 'ad': { 's': 'Lots of ...',},},
'es': { 'ad': { 's': 'Mucho ...',},},},
}
And the Audience Variation table contains
| Id | Article Id | Fieldname | Audience Dim | Language Dim | Text Difficulty Dim | Is Invalid | Value |
|---|---|---|---|---|---|---|---|
| 1 | 1 | headline | ad | en | s | False | First Article |
| 2 | 1 | subhead | ad | en | s | False | |
| 3 | 1 | content | ad | en | s | False | Lots of ... |
| 4 | 1 | headline | ad | es | s | False | Artículo Primero |
| 5 | 1 | content | ad | es | s | False | Mucho ... |


BREAKING: Man left in critical condition following shooting in North Dublin
by Nick FitzgeraldThe incident took place in Coolock
A man in his 20s has been left critically injured following a shooting that occurred in Coolock in north Dublin.
The incident took place on Clonshaugh Avenue in Dublin 17 at approximately 5:15pm on Sunday.
Gardai and emergency services were called to the scene where they discovered the man with "a number of apparent gunshot wounds."
He was treated at the scene and has since been removed by ambulance to Beaumont Hospital.
His condition is understood to be critical.
A garda spokesperson said:
"The scene has been preserved for a forensic and technical examination. No arrests have been made to-date and enquires are ongoing.
"Anyone with information is asked to contact Coolock Garda Station 01-6664200 or the Garda Confidential Line 1800 666 111."


Currently I work at Mews.
You can check a talk on accessibility in design systems I gave recently and have a look at what I'm working on right now: Mews design system.
I built stuff like Hackney design system, Iran Open Data, Cisco pattern library, The Royal Institution, Wadham College and The National Centre for Circus Arts.
I worked at Bulb, Hackney Council, Small Media, Cisco, Spektrix, Bureau for Visual Affairs and Beyond.
You can find me here: Twitter, Mastodon, Bluesky Instagram, GitHub, CodePen.
Check my CV and contact me if you want to hire me.


| Name | Location | Truck | |
|---|---|---|---|
| {{ incident.Name }} |
{{ incident.Location.AddressLine1 }}
{{ incident.Location.AddressLine2 }}
{{ incident.Location.City }}, {{ incident.Location.State }} {{ incident.Location.Zip }}
|
{{ incident.Truck.Name }} | {{ incident.Status }} |


Events
Events is a package for logging high-cardinality events in your Mac or iOS app.
Installation
Events can be installed using SwiftPM. If you’re using it from another Swift package, add this snippet to the dependencies
in your Package.swift
:
.package(url: "https://github.com/mjm/Events", .branch("master"))
You can also use Events from your macOS or iOS app using Xcode 11’s SwiftPM support.
- Click on your project in Xcode’s Project navigator.
- Select the project in the sidebar of the editor.
- Hit the + button on the Swift Packages tab.
- Enter
https://github.com/mjm/Events
for the package repository URL. - Choose
Branch
and usemaster
as the branch. - Be sure the Events library is added to the target for your app.
- Choose
Finish.


Anti The Good Parts
Presented by Joy Ge
//Which assertion will fail?
var a;
assert.equal("undefined", typeof a);
a = "hello world";
assert.equal("string", typeof a);
a = null;
assert.equal("null", typeof a);
a = undefined;
assert.equal("undefined", typeof a);
a = [];
assert.equal("object", typeof a);
//coercion and equality
var a = "28";
var b = 28;
assert.equal(true, a == b);
assert.equal(false, a === b);
//Which assertion will fail?
var a = [1, 2, 3];
var b = [1, 2, 3];
var c = "1,2,3";
assert.equal(true, a == c);
assert.equal(true, b == c);
assert.equal(true, a == b);
var a = 28;
var b = "foo";
assert.equal(false, a > b);
assert.equal(false, a < b);
assert.equal(false, a == b);
var a = 2;
foo(); // works because `foo()`
// declaration is "hoisted"
function foo() {
a = 3;
console.log( a ); // 3
var a; // declaration is "hoisted"
// to the top of `foo()`
}
console.log( a ); // 2
function foo() {
var a = 1;
function bar() {
var b = 2;
function baz() {
var c = 3;
console.log( a, b, c ); // 1 2 3
}
}
}
You can think of closure as a way to "remember" and continue to access a function's scope (its variables) even once the function has finished running.
Write a function that takes an argument and returns a function that returns that argument.
describe('closure', function() {
it('should return a function that returns the given parameter', function() {
var mirror1 = makeFun(1);
assert.equal(1, mirror1());
});
});
var makeFun = function(x) {
return function() {
return x;
}
}
If a function has a this reference inside it, that this reference usually points to an object. But which object it points to depends on how the function was called.
It's important to realize that this does not refer to the function itself, as is the most common misconception.
//Fill ? with the actual expected value
function foo() {
return this.bar;
}
var obj1 = {
bar : "obj1",
foo : foo
}
var obj2 = {
bar : "obj2",
}
bar = "global";
it('which object is this', function() {
assert.equal(?, foo());
assert.equal(?, obj1.foo());
assert.equal(?, foo.call(obj2));
});
Everything is Object?
Function is Object?
Object is Function?
// Rectangle is an ordinary function.
var Rectangle = function() {};
// Every function has a property named 'prototype' whose value is an object
// with a property named 'constructor' that points back to the original
// function. It is possible to add more properties to this object.
Rectangle.prototype.width = 3;
Rectangle.prototype.height = 4;
// Creates an instance of a Rectangle, which is an object whose
// __proto__ property points to Rectangle.prototype. This is discussed
// in more detail in Chapter 5 on Classes and Inheritance.
var rect = new Rectangle();
//Draw the prototype chain diagram of the following code
var Programmer = function(language, level) {
this.language = language;
this.level = level;
}
var joy = new Programmer("JavaScript", 1);
var stike = Object.create(joy);
stike.level = 2;
欢迎关注ISD上海技术论坛


Affecting an estimated 11% of American households in 2018, food insecurity is defined as the disruption of food intake resulting from a lack of money and other resources. School lunch is critical to the health and well-being of students, especially for those affected by food insecurity. In fact, for some children, school meals may be the only meal they have on a given day. When schools transitioned to a remote format in the spring of 2020, many vulerable students were left without school meals. By some estimates, only 15% of students who qualify for free or reduced-price school meals have been getting them. Some school districts have created a pick-up system for school meals, but the need for a parent to come to the pick-up site is a barrier for families where parents are busy working or have disabilities. As remote education continues, food insecurity is expected to continue to pose a challenge to students in food-insecure households.


Utilizing UI icon fonts.
Many icon fonts contain sets of UI icons that indicate various states. This could include things like battery levels, signal strength, or volume indication. There are many ways that you can indicate the changes in the state of an icon. You could use the :hover pseudo-class to change icons based on user interaction. A more robust way of displaying icon states is to tie the icon to the scripting of interactive elements. Doing this requires you to re-examine your deployment strategy for icon fonts, as many UI–widgets have built-in constraints on styling and functionality. Just be sure that any approach to displaying interactive states of icons doesn't interfere with any of your existing deployment strategies.


Grant proposals will be considered twice a year. Application deadlines are:
Grant awards are made approximately 45 days after the application deadlines.
The WUHS Endowment Association has found it helpful to consult with the grant applicants prior to submission of a proposal. Applicants are encouraged to contact a trustee (contact information can be found at the bottom of this page) or their principal before beginning the application process.
Grant applicants may choose whether to submit their proposals online or by mail. Please note that online submissions require a Google account.


Brian's Brain
Brian's Brain
is a celluar automaton, similar to the Game of Life, but where each cell can be in one of three states (on / off / dying. In the grid below you can set up a pattern and press play. Communication goes back to a
Haskell
Your browser does not support canvas
Step


Categories: Core Battalion
Battalion Abilities: Unified, Battalion Organisation: Core Battalion: Battle Regiment
| Battalion Abilities | Battalion Ability Details | Ref |
|---|---|---|
| Unified | One-drop Deployment (see 26.2.1). |
| Battalion Organisation | Required | Ref |
|---|---|---|
| Core Battalion: Battle Regiment | 1 Commander 0-2 Sub-commanders 2-5 Troops 0-1 Monster or Artillery |
Selections: 1. Overwhelming Dread, 1. Pack Alpha, 5. Terminus Clock, Battle Regiment - 0-2 Sub-Commander, General, Mortis Staff
Categories: DEATH, DEATHMAGES, HERO, NECROMANCER, WIZARD, Leader, SOULBLIGHT GRAVELORDS, 9 or less wounds Leader, General
Artefact: Terminus Clock, Command Trait: Pack Alpha, Magic: Magic, Spell: Arcane Bolt, Mystic Shield, Overwhelming Dread, Vanhel's Danse Macabre, Unit: Necromancer, Unit Abilities: Undead Minions, Weapon: Mortis Staff
| Artefact | Artefact Details | Ref |
|---|---|---|
| Terminus Clock | Once per battle, at the start of the enemy hero phase, you can say that the bearer will stop the Terminus Clock. If you do so, until the end of that phase, subtract 1 from casting rolls for enemy WIZARDS . |
| Command Trait | Command Trait Details | Ref |
|---|---|---|
| Pack Alpha | Once per turn, this general can use a command ability without a command point being spent. |
| Magic | Cast/Unbind | Spells Known | Ref |
|---|---|---|---|
| Magic | 1/1 | Arcane Bolt, Mystic Shield, Vanhel’s Danse Macabre |
| Spell | Casting Value | Range | Description | Ref |
|---|---|---|---|---|
| Arcane Bolt | 5 | 12" | If successfully cast, at the start of any 1 phase before your next hero phase, you can pick 1 enemy unit within range and visible to the caster. That unit suffers 1 mortal wound. If that unit is within 3" of the caster, it suffers D3 mortal wounds instead of 1. | |
| Mystic Shield | 5 | 12" | If successfully cast, pick 1 friendly unit wholly within range and visible to the caster. Add 1 to save rolls for attacks that target that unit until your next hero phase. | |
| Overwhelming Dread | 5 | 18" | If successfully cast, pick 1 enemy unit within 18" of the caster that is visible to them. Until your next hero phase, subtract 1 from hit rolls for attacks made by that unit. | |
| Vanhel's Danse Macabre | 6 | 18" | If successfully cast, pick 1 friendly SOULBLIGHT GRAVELORDS SUMMONABLE unit wholly within 18" of the caster. Until your next hero phase, if that unit has fought only once in the combat phase, when it is your turn to pick a unit to fight, that unit can be picked to fight for a second time if it is within 3" of any enemy units. |
| Unit | Move | Wounds | Bravery | Save | Ref |
|---|---|---|---|---|---|
| Necromancer | 5" | 5 | 10 | 6+ |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Undead Minions | Roll a dice before you allocate a wound or mortal wound to this model if it is within 3" of any friendly SOULBLIGHT GRAVELORDS SUMMONABLE units. On a 3+, that wound or mortal wound is allocated to 1 of those units instead of this model. |
| Weapon | Type | Range | Attacks | To Hit | To Wound | Rend | Damage | Ref |
|---|---|---|---|---|---|---|---|---|
| Mortis Staff | Melee | 1" | 2 | 3+ | 3+ | -1 | D3 |
Selections: Battle Regiment - 1 Commander, Blood-slick Claws, Piercing Blade
Categories: DEATH, VAMPIRE, VAMPIRE LORD, HERO, WIZARD, Leader, VYRKOS DYNASTY, SOULBLIGHT GRAVELORDS, RADUKAR THE BEAST
Command Abilities: Call to the Hunt, Mustering Howl, Unit: Radukar the Beast, Unit Abilities: Bounding Charge, Supernatural Reflexes, The Hunger, Unleashed Ferocity, Weapon: Blood-slick Claws, Piercing Blade
| Command Abilities | Command Ability Details | Ref |
|---|---|---|
| Call to the Hunt | You can use this command ability at the start of the combat phase. If you do so, pick 1 friendly model with this command ability that made a charge move in the same turn. Add 1 to the Attacks characteristic of melee weapons used by friendly SOULBLIGHT GRAVELORDS units wholly within 18" of that model until the end of that phase. A unit cannot benefit from this command ability more than once per phase. | |
| Mustering Howl | You can use this command ability once per battle at the end of your movement phase. If you do so, you can add 1 unit of 10 DIRE WOLVES to your army. The unit must be setup wholly within 12" of this model and more than 9" from all enemy units. |
| Unit | Move | Wounds | Bravery | Save | Ref |
|---|---|---|---|---|---|
| Radukar the Beast | 8" | 12 | 10 | 4+ |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Bounding Charge | This model can run and still charge later in the same turn. | |
| Supernatural Reflexes | Subtract 1 from hit rolls for attacks that target this model. | |
| The Hunger | At the end of the combat phase, if any enemy models were slain by wounds inflicted by this model’s attacks in that phase, you can heal up to D3 wounds allocated to this model. | |
| Unleashed Ferocity | If the unmodified hit roll for an attack made with this model's Blood-slick Claws is 6, that attack inflicts 2 mortal wounds on the target and the attack sequence ends (do not make a wound or save roll). |
| Weapon | Type | Range | Attacks | To Hit | To Wound | Rend | Damage | Ref |
|---|---|---|---|---|---|---|---|---|
| Blood-slick Claws | Melee | 2" | 6 | 3+ | 3+ | -1 | 2 | |
| Piercing Blade | Melee | 1" | 6 | 3+ | 3+ | -1 | D3 |
Selections: 40 Deadwalker Zombies [115pts], Battle Regiment - 2-5 Troops, Crude Weapons and Infectious Bites, Reinforced [115pts]
Categories: Battleline, DEATH, DEADWALKER ZOMBIES, DEADWALKERS, SUMMONABLE, SOULBLIGHT GRAVELORDS, Reinforced
Unit: Deadwalker Zombies, Unit Abilities: Dragged Down and Torn Apart, The Newly Dead, Weapon: Crude Weapons and Infectious Bites
| Unit | Move | Wounds | Bravery | Save | Ref |
|---|---|---|---|---|---|
| Deadwalker Zombies | 4" | 1 | 10 | - |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Dragged Down and Torn Apart | This unit is eligible to fight in the combat phase if it is within 6" of an enemy unit instead of 3", and it can move an extra 3" when it piles in. | |
| The Newly Dead | If the unmodified hit roll for an attack made by this unit is 6, that attack inflicts 1 mortal wound on the target and the attack sequence ends. In addition, at the end of the combat phase, you can roll a dice for each enemy model that was slain by wounds inflicted by this unit’s attacks in that phase. For each 2+, you can add 1 DEADWALKER ZOMBIE model to this unit. |
| Weapon | Type | Range | Attacks | To Hit | To Wound | Rend | Damage | Ref |
|---|---|---|---|---|---|---|---|---|
| Crude Weapons and Infectious Bites | Melee | 1" | 1 | 5+ | 5+ | - | 1 |
Selections: 40 Deadwalker Zombies [115pts], Battle Regiment - 2-5 Troops, Crude Weapons and Infectious Bites, Reinforced [115pts]
Categories: Battleline, DEATH, DEADWALKER ZOMBIES, DEADWALKERS, SUMMONABLE, SOULBLIGHT GRAVELORDS, Reinforced
Unit: Deadwalker Zombies, Unit Abilities: Dragged Down and Torn Apart, The Newly Dead, Weapon: Crude Weapons and Infectious Bites
| Unit | Move | Wounds | Bravery | Save | Ref |
|---|---|---|---|---|---|
| Deadwalker Zombies | 4" | 1 | 10 | - |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Dragged Down and Torn Apart | This unit is eligible to fight in the combat phase if it is within 6" of an enemy unit instead of 3", and it can move an extra 3" when it piles in. | |
| The Newly Dead | If the unmodified hit roll for an attack made by this unit is 6, that attack inflicts 1 mortal wound on the target and the attack sequence ends. In addition, at the end of the combat phase, you can roll a dice for each enemy model that was slain by wounds inflicted by this unit’s attacks in that phase. For each 2+, you can add 1 DEADWALKER ZOMBIE model to this unit. |
| Weapon | Type | Range | Attacks | To Hit | To Wound | Rend | Damage | Ref |
|---|---|---|---|---|---|---|---|---|
| Crude Weapons and Infectious Bites | Melee | 1" | 1 | 5+ | 5+ | - | 1 |
Selections: Balefire Brazier, Battle Regiment - 2-5 Troops, Corpse Lash, Rusty Blades
Categories: DEATH, DEADWALKERS, CORPSE CART, Other, SOULBLIGHT GRAVELORDS
Unit: Corpse Cart with Balefire Brazier, Unit Abilities: Balefire Brazier, Malefic Fumes, Weapon: Corpse Lash, Rusty Blades
| Unit | Move | Wounds | Bravery | Save | Ref |
|---|---|---|---|---|---|
| Corpse Cart with Balefire Brazier | 4" | 6 | 10 | 6+ |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Balefire Brazier | Subtract 1 from casting rolls for enemy WIZARDS within 18" of any friendly models with this ability. | |
| Malefic Fumes | Subtract 1 from wound rolls for attacks made with melee weapons by enemy units while they are within 9" of any friendly models with this ability. |
| Weapon | Type | Range | Attacks | To Hit | To Wound | Rend | Damage | Ref |
|---|---|---|---|---|---|---|---|---|
| Corpse Lash | Melee | 1" | 3 | 4+ | 4+ | - | 1 | |
| Rusty Blades | Melee | 1" | 2D6 | 5+ | 5+ | - | 1 |
Categories: Allegiance
Selections: Vyrkos Dynasty
Categories: Allegiance
Battle Trait: Deathless Minions, Deathly Invocation, Endless Legions, Locus of Shyish, Reanimated Horrors, The Strength of the Pack is the Wolf, The Strength of the Wolf is the Pack, The Unquiet Dead, Spell: Invigorating Aura
| Battle Trait | Battle Trait Details | Ref |
|---|---|---|
| Deathless Minions | Roll a dice each time you allocate a wound or mortal wound to a friendly SOULBLIGHT GRAVELORDS unit wholly within 12" of a friendly SOULBLIGHT GRAVELORDS HERO or gravesite. On a 6+, that wound or mortal wound is negated. | Battletome: Soulblight Gravelords p73 |
| Deathly Invocation | At the start of your hero phase, you can pick a number of different friendly SOULBLIGHT GRAVELORDS SUMMONABLE units wholly within 12" of a friendly SOULBLIGHT GRAVELORDS HERO to be affected by a deathly invocation. The number of different friendly SOULBLIGHT GRAVELORDS SUMMONABLE units you can pick is determined by the keyword on that HERO's warscroll. MORTARCH: up to 4 VAMPIRE: up to 3 DEATHMAGES: up to 2 DEATHRATTLE: up to 2 If the HERO has more than 1 of the above keywords on its warscroll, choose 1 of them. For each of the units you picked, you can heal up to D3 wounds allocated to that unit or, if no wounds are allocated to it, you can return a number of slain models to that unit that have a combined Wounds characteristic of D3 or less. Roll separately for each unit. The same unit cannot benefit from this ability more than once per turn. In addition, a unit cannot benefit from this ability and the Invocations of Nagash ability in the same turn. |
Battletome: Soulblight Gravelords p73 |
| Endless Legions | At the end of the battleshock phase, count the number of enemy units that were destroyed during that turn and roll a dice, adding the number of destroyed enemy units to the roll. On a 5+, you can pick 1 friendly SOULBLIGHT GRAVELORDS SUMMONABLE DEADWALKERS or SOULBLIGHT GRAVELORDS SUMMONABLE DEATHRATTLE unit in your army that has been destroyed. If you do so, a new replacement unit with half the number of models in the unit that was destroyed (rounding up) is added to your army. Set up that unit wholly within 12" of a gravesite and more than 9" from all enemy units. Each destroyed unit can only be replaced once – replacement units cannot themselves be replaced. | Battletome: Soulblight Gravelords p73 |
| Locus of Shyish | If the unmodified casting roll for a friendly SOULBLIGHT GRAVELORDS WIZARD attempting to cast a spell from the Lore of the Deathmages or the Lore of the Vampires is 9+ and that spell is not unbound, after the effects of that spell have been resolved, you can immediately resolve the effects of that spell for a second time. | Battletome: Soulblight Gravelords p73 |
| Reanimated Horrors | Subtract 1 from the Bravery characteristic of enemy units while they are within 6" of 1 friendly SOULBLIGHT GRAVELORDS DEADWALKERS or SOULBLIGHT GRAVELORDS DEATHRATTLE unit. Subtract 2 from the Bravery characteristic of enemy units instead of 1 while they are within 6" of 2 or more friendly SOULBLIGHT GRAVELORDS DEADWALKERS or SOULBLIGHT GRAVELORDS DEATHRATTLE units. DEATH units are not affected by this ability. | Battletome: Soulblight Gravelords p73 |
| The Strength of the Pack is the Wolf | Add 1 to wound rolls for attacks made with melee weapons by friendly VYRKOS DYNASTY DEATHRATTLE and VYRKOS DYNASTY DEADWALKERS units while they are wholly within 9" of any friendly VYRKOS DYNASTY VAMPIRE HEROES. | |
| The Strength of the Wolf is the Pack | You can re-roll casting rolls for friendly VYRKOS DYNASTY VAMPIRE WIZARDS. | |
| The Unquiet Dead | After territories have been determined, but before any units have been set up, you can pick up to 2 points within your territory and up to 2 points anywhere on the battlefield outside your territory to be gravesites. Each gravesite must be more than 1" from all terrain features and objectives. If both players can set up gravesites at the same time, or if one player can set up faction terrain features at the same time as the other player can set up gravesites, they must roll off, and the winner chooses who sets up their faction terrain features or gravesites first. Instead of setting up a SOULBLIGHT GRAVELORDS SUMMONABLE unit on the battlefield before the battle begins, you can place it to one side and say that it is set up in the grave as a reserve unit. You can set up 1 reserve unit in the grave for each unit you have already set up on the battlefield. At the end of any of your movement phases, you can set up 1 or more of these units on the battlefield wholly within 12" of a gravesite and more than 9" from all enemy units. At the start of the fourth battle round, reserve units that are still in the grave are destroyed. |
Battletome: Soulblight Gravelords p73 |
| Spell | Casting Value | Range | Description | Ref |
|---|---|---|---|---|
| Invigorating Aura | 8 | 18" | Add 1 to the casting roll for each friendly SOULBLIGHT GRAVELORDS HERO on the battlefield. If successfully cast, pick 1 friendly SOULBLIGHT GRAVELORDS SUMMONABLE unit wholly within 18" of the caster. You can either heal up to 3 wounds allocated to that unit or, if no wounds are allocated to it, you can return a number of slain models to that unit that have a combined Wounds characteristic of 3 or less. The same unit cannot benefit from this spell more than once per turn. Any number of SOULBLIGHT GRAVELORDS WIZARDS can attempt to cast Invigorating Aura in the same hero phase. |
Selections: 2000 Points - Battlehost
Categories: Game Options, Battlehost
Categories: Game Options
Categories: ENDLESS SPELL, AQSHY, THE BURNING HEAD, Malign Sorcery
Spell: Summon Burning Head, Unit Abilities: Flaming Skull, Fly, Predatory
| Spell | Casting Value | Range | Description | Ref |
|---|---|---|---|---|
| Summon Burning Head | 7 | 6" | If successfully cast, set up the endless spell wholly within range of the caster. |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Flaming Skull | After this endless spell has moved, if any units are within 1" of it, roll a dice for each unit within 1" of this endless spell. ON a 2+, that unit suffers D3 mortal wounds. Then, this endless spell is removed from play. | |
| Fly | This unit can fly. | |
| Predatory | This endless spell is a predatory endless spell. It can be moved up to 8" and can fly. |
Created with BattleScribe


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Evolutionary Biologist Investigating Dynamics of Genome Size Evolution and Sex Chromosome Differentiation
Preferred Pronouns: He/Him
Updated CV
During my PhD, I focused on genome size evolution in Drosophila species. By using Drosophila species as a model, I was able to utilize the long history of research, broad knowledge of this group, and the ease of attaining species from the species stock center to cheaply and quickly investigate genome size with comparative phylogenetic methods. One of the most rewarding aspects of this research has been the ability to include undergraduate research students in the data collection, analysis, and manuscript preparation stages. I know these experiences greatly benefited me as an undergraduate researcher, and I am proud to be able to provide these opportunities for others.
After my PhD, I had two differnet postdoctoral research positions, which allowed me to greatly increase my skills in bioinformatic analyses. In my first postdoctoral position with Dr. Aaron Tarone, I investigated miRNA and protein makers of immature development in forensically relevant flies. In my second postdoctoral position with Dr. Heath Blackmon, I continued to investigate genome size evolution in insects, as well as whole genome sequencing of a variety of insect species. I am happy to still be working with my PhD advisor and both of my postdoctoral advisors on projects which include undergraduate researchers.
Education & Experience
Assistant Professor of Bioinformatics and Genomics
Postdoctoral Research Associate
Advised by Heath Blackmon
Postdoctoral Research Associate
Advised by Aaron Tarone
Ph.D. in Entomology
Advised by J. Spencer Johnston
Interests
Outside of the lab I like to try to fill my time with hobbies, such as:
Playing music: I'm a classically trained bassist and self-taught guitarist.
Listening to music: I'm a big fan of classical music and hard rock.
Woodworking
Hiking. and
Hanging out with my dog, Guinness (lots of pictures of him on my instagram)


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TagVis
a Visualisation of Relationships Between Tags
Master - Thesis Defense by
Jan Maushagen
structure of the talk
Tags and Tweets
Flexible classification technique to suit any context!
Solves the classification problem
Problem
How do you search and navigate tagged information?
Tagged Information Spaces
Complex Structure is hard to make sense of.
Starting point is the Tag Graph.
Tags are difficult to explore
By default, there is no navigation behaviour:
- Directed search
- Visual exploration
Directed Search
Query-Response technique enables sense making of tags.
Visual Exploration
- Using Information Visualisation techniques for search.
- Strolling throough the information space.
| Query-Response |
Exploration |
| specific
| Engaging |
| low level |
High-level |
| ranked |
multi-faceted |
| textual |
multi-modal |
Background
Set Visualisation and related techniques.
Tag Cloud
- Only tag frequency is depicted
- Visual pleasing representation engages in search activity
Venn Diagram
Depicting sets by circles and intersections by overlaps
Node-Link Diagram
- Nodes represent tag sets
- Every two nodes are connected if the corresponding tags intersect
Thesis Aims
Design of a new Tag Visualisation technique for search with the following properties:
- Support visual exploration and directed search
- Navigation structure
- Better scaling
- Visual appealing
Design of TagVis
- Personal Information Domain
- User-centered Design (Personas)
- Iterative Development of Prototypes
Personal Information
Research Training: The role of exploration in personal information.
- Already experienced information
- Existing search cues (location, time, context)
- People like to have orientation
User Analysis
Requirements are specified with Personas.
Design Methodology
3 Prototypes are integrated into one solution.
Venn Node Diagram
Facet Viewer
Bubble Sets
Hybrid Approach
Combine Bubble Sets and Node-Link diagram
Tag Graph simplified
- The Tag Graph is traversed with BFS.
- Nodes are selected based on generality:
Result: new Tag Graph
with less edges
Component Graph
TagVis uses connected components for the final layout.
Each component is limited in size by maximal path length.
Participant Observation technique
- Personas are matched with real users
- Task performance is observed in user's environment
Evaluation Design
Conclusion
What are the benefits and drawbacks of TagVis over its competitors?
| Benefits |
Drawbacks |
| superior scaling
| overview is limited |
| easy navigation |
links are not always accurate |
| exploration and directed search |
touch interactions are not supported |
|
time attribute not exploited |


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Object References
Some components are supposed to work with other objects, but those objects are not in their hierarchy as a parent or child node, but may instead be any arbitrary object that the user wants to select. Such use cases are supported through object references, meaning that a component can have properties that store a reference to another object (within the same scene or prefab document).
A very basic example is the DrawLineToObject component, which literally just draws a line between itself and a referenced object.
Object Reference UI
In the editor UI an object reference property looks like this:
Left-clicking the arrow button will switch to object selection mode and turn the mouse cursor into a crosshair. Click on any object in the 3D viewport to select it as the referenced object.
Important:
You can also right-click the arrow button to bring up a menu with additional options.
Be aware that you can right click any node in the tree view or in the viewport and select Copy Object Reference
, then use Paste Object Reference
in the menu above to set the reference. This is sometimes easier than clicking on an object in the viewport.
Object References in Custom Components
When you create a custom component you may want to have an object reference property. The easiest way to achieve this, is to get inspiration from existing code, such as ezLineToComponent
.
Object references are a 'non-trivial' (complicated) feature. They need to be remapped within instances of prefabs, they work differently in the editor and the runtime, and it is possible to use them as exposed parameters. Consequently, you have to stick to a certain pattern to make them work.
Expose them as a string property and use custom functions as accessors. Also decorate them with ezGameObjectReferenceAttribute
:
EZ_ACCESSOR_PROPERTY("Target", GetLineToTargetGuid, SetLineToTargetGuid)->AddAttributes(new ezGameObjectReferenceAttribute()),
The 'getter' accessor function is actually never called, but since EZ_ACCESSOR_PROPERTY
expects a valid function, you need to have at least one dummy function that you can pass in. In your 'setter' function you need to query a 'reference resolver' from the world and use that to map the string to an actual game object handle. Here you also need to pass in information about the component and the property. This is mainly needed by the editor to handle undo/redo correctly.
void ezLineToComponent::SetLineToTargetGuid(const char* szTargetGuid)
{
auto resolver = GetWorld()->GetGameObjectReferenceResolver();
if (resolver.IsValid())
{
// tell the resolver our component handle and the name of the property for the object reference
m_hTargetObject = resolver(szTargetGuid, GetHandle(), "Target");
}
}
const char* ezLineToComponent::GetLineToTargetGuid() const
{
// this function is never called
return nullptr;
}
Finally, during component serialization you just use ezWorldWriter::WriteGameObjectHandle()
and ezWorldReader::ReadGameObjectHandle()
to save and restore the actual game object handle.
Limitations
Object references are not possible across scene layers.


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§243-8 License taxes payable monthly. License taxes imposed by this chapter shall be paid in monthly installments to the department of taxation. [L 1932 1st, c 19, §5; RL 1935, §2014; am L Sp 1941, c 26, pt of §1; RL 1945, §5407; RL 1955, §123-5; am L Sp 1959 2d, c 1, §16; HRS §243-8]


GM’s 40-day strike drives the biggest drop in US factory output since April
by Ben Winck, Business Insider US- US factory output plunged the most since April as the 40-day General Motors strike pulled the metric lower.
- Manufacturing output dropped 0.6% in October, according to a Friday release from the Federal Reserve.
- Factory output of motor vehicles and related parts dropped 7.1% last month. Excluding the motor vehicles sector, US factory production only fell 0.1%.
- Visit the Business Insider homepage for more stories.
US factory output plummeted the most since April as the 40-day General Motors strike dragged on the crucial automotive sector.
Manufacturing output dropped 0.6% in October after falling 0.5% the previous month, according to a Friday release from the Federal Reserve. Output of motor vehicles and parts plummeted 7.1% last month as members of the United Auto Workers union walked out of factories in a strike to demand improved contracts.
Total industrial production fell roughly 0.8% in October, its biggest decline since May 2018.
Excluding motor vehicles and parts, factory production fell only 0.1% in October, the same decrease seen in September. The GM strike lasted from September 16 to October 25, and cost the automaker nearly $3 billion.
Roughly 49,000 UAW workers went on strike across 55 GM facilities to secure low-cost healthcare, wage increases, quicker access to full-time status for temporary workers, and increased profit-sharing. The workers ratified a new, four-year contract to end the strike in October.
“We are all so incredibly proud of UAW-GM members who captured the hearts and minds of a nation,” UAW Vice President Terry Dittes said in a statement following the contract’s ratification. “Their sacrifice and courageous stand addressed the two-tier wages structure and permanent temporary worker classification that has plagued working-class Americans.”
GM also announced it would build an electric truck in an “unallocated” Detroit plant, and that it plans to build a new battery factory near an idled plant in Ohio.
UAW’s new contract is now being used as a template for negotiations with Ford and other US automakers.
Now read more markets coverage from Markets Insider and Business Insider:
Apple is now worth more than the entire US energy sector: BAML