Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/shogun-toolbox/shogun-demo
Shogun Toolbox Interactive Web Demos
https://github.com/shogun-toolbox/shogun-demo
Last synced: about 2 months ago
JSON representation
Shogun Toolbox Interactive Web Demos
- Host: GitHub
- URL: https://github.com/shogun-toolbox/shogun-demo
- Owner: shogun-toolbox
- Created: 2013-05-17T15:16:49.000Z (over 11 years ago)
- Default Branch: master
- Last Pushed: 2019-05-28T11:56:57.000Z (over 5 years ago)
- Last Synced: 2024-03-26T08:13:49.501Z (9 months ago)
- Language: JavaScript
- Size: 1020 KB
- Stars: 7
- Watchers: 7
- Forks: 17
- Open Issues: 13
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
- Author : Shogun.
- Description : Shogun demos, done in django.
Running Demos Locally
----------------------
- To server the static files (required to run the demos) in the development server
- In /settings.py change `PRODUCTION = True` to `PRODUCTION = False`
- Start the Django development server using `python manage.py runserver`
- On doing `python manage.py runserver` you should see the \:\ its running at. (Typically http://127.0.0.1:8000/)
- Third Party distributions for Django
Explanation of directory content
---------------------------------
- /demos : Handles the requests, present the demos
- /toy_data : Handles the requests, and generate/import toy data.
- /static : css, js used by demo
- /template : All templates for each different page.
- /shogun_demo:
- settings.py : Configuration.
- urls.py : Urls and method in demos.
Currently available demos
---------------------------
- http://\:\/regression/svr/ : A demo for support vector regression
- http://\:\/regression/regression/ : A demo for ridge regression
- http://\:\/regression/gp/ : A demo for gaussian process regression
- http://\:\/classifier/binary/ : A demo for binary classification
- http://\:\/classifier/perceptron/ : A demo for binary perceptron
- http://\:\/classifier/multiclass/ : A demo for multiclass classification
- http://\:\/classifier/gp/ : A demo for gaussian process classification
- http://\:\/misc/kernel_matrix/ : A demo for kernel matrix visualization
- http://\:\/application/ocr/ : A demo for recognizing hand-written digits.
- http://\:\/application/language_detect/ : A demo for language detection
- http://\:\/clustering/kmeans/ : A demo for clustering using kmeans
Docs
------
An Example contains a front-end script(javascript) and a backend controller(python).
- front-end
- Entrance Generator
Entrance generator is a python method used to generate the entrance page of the demo. All the demo's entrance page will be in same layout(a main title, a canvas section and a panel section). The Entrance Generator takes an HttpRequest Object as its first parameter, which is typically named request. The method returns an rendered template HttpResponse. A python dict is needed to define the property of the entrance page.
- Property Dict
- 'title': define title of the entrance page,
- 'template': a python dict to specify the property of the canvas
- 'type': specify the type of the canvas
- option 'coordinate-2dims': use the canvas as a coordinate system of 2 dimensions
- option 'drawing': use the canvas as a mouse drag drawing area
- 'mouse_click_enabled': specify if mouse click input is enabled. only used with type 'coordinate-2dims'
- option 'none' [default]: disable the mouse
- option 'left': only allow left mouse click for 1 feature input
- option 'both': allow left and right mouse click, left for feature 1 and right for feature 2.
- 'heatmap': specify if heatmap data is allowed to draw on the page
- 'contour'
- option False [default]: do not display contour
- option true: display contour(using conrec.js)
- 'coordinate_system': a dict specifys the property of the coordinate system
- 'horizontal_axis': a dict specifys the property of the horizontal axis
- 'vertical_axis': a dict specifys the property of the vertical axis
- 'range': an 2-item list specifys the range of the axis, eg. [-5.0, 5.0]
- 'description': A brief introduction to the demo, like how it works and its capabilities. Wll be displayed beneath the title.
- 'panels': an list of dicts, each item is a configuration of a single panel in panel section
item dict info:
- 'panel_name': the html id of the panel
, in other word, you can access the panel by document.getElementById() in javascript.
- if 'panel_name' is 'arguments', the generator will generate a form with the argument type information set in panel_property
- if 'panel_name' is 'toy_data', the generator will make a toy data generator/importer panel in the panel section.
- 'panel_label' [default same as 'panel_name']: the title of the panel.
- 'panel_property': use along with 'panel_name' equals 'argument', which provide the argument information of the particular argument panel.
- Arguments List, an list of dicts, each item of the list represents a profile of input zone for a single argument.
item dict info:
- 'argument_type': set as one of ['integer', decimal', 'select'],
- 'integer': make the text input zone only accepts integer.
- 'decimal': make the text input zone only accepts decimal number.
- 'select': make the zone as a drop-down menu. in this case, an string list of 'argument_items' must be set to specify the items in the menu.
- 'button-group': create a button group. in this case, a dict list of 'argument_items' must be set to specify each button information in the group.
- 'argument_label': the label(or name) of the input.
- 'argument_name': the html id of the input
- 'argument_explain': pop-up explanation of the argument. html tags allowed.
- 'argument_default': use with argument_type equals 'integer' or 'decimal', specify the default value of the input zone.
- 'argument_items': use with argument_type equals 'select' or 'button-group', specify the items under the drop-down menu or button group.
- when use with 'argument_type' == 'select', a list of the drop-down menu items' name need to be provided.
- when use with 'argument_type' == 'button-group', a list of button's information dicts need to be provided.
button info:
- 'button_name': the html id of , in other word, you can access the button by document.getElementId() in javascript.
- 'button_label': the caption shown on the button.
- 'button_type': if 'button_type' == 'json_up_down_load', a json interactive javascript will be generate. The function upload all the parameter specified in the argument list, and send a ajax request. The target URL is the correspond 'button_name', which means if a button named 'generate', and it's a 'json_up_down_load' button, when hit the button, it'll send 'generate/' a ajax request. When the browser received the data sent back from server, a custom function named 'button_name' will be called to do further work, such as draw the data on the canvas section.
- frontend script
Detailed javascript is needed to specify the way data input and output, and it can be done by modifying the {% block javascript %} block in the template file. Meanwhile, when there's a button group defined in the panel section, you can add the mousedown event to the button by creating functions named _action.
- python backend
A python backend is needed to specify the algorithm. The backend method is better in the same file with the entrance generator. Just like the entrance generator, the backend is a method which needs a HttpRequest object as input argument and provide with a HttpResponse object. The HttpRequest object contains the input data of the algorithm, and we can access a single parameter with request.POST[]. When the calculation is down, it'd be better to dump it in a json file and send.