|
BLE_API
v2.1.3
|
BLE SIG defined characteristic UUID definitions.
| #define GATT_SPEC_CHARC_AGGREGATE_INPUT 0x2A5A |
Aggregate Input Characteristic UUID.
| #define GATT_SPEC_CHARC_ALERT_CATEGORY_ID 0x2A43 |
Alert Category Id Characteristic UUID.
| #define GATT_SPEC_CHARC_ALERT_CATEGORY_ID_BIT_MASK 0x2A42 |
Alert Category Id Bit Mask Characteristic UUID.
| #define GATT_SPEC_CHARC_ALERT_LEVEL 0x2A06 |
Alert Level Characteristic UUID.
| #define GATT_SPEC_CHARC_ALERT_NOTIFICATION_CONTROL_POINT 0x2A44 |
Alert Notification Control Point Characteristic UUID.
| #define GATT_SPEC_CHARC_ALERT_STATUS 0x2A3F |
Alert Status Characteristic UUID.
| #define GATT_SPEC_CHARC_ANALOG_INPUT 0x2A58 |
Analog Input Characteristic UUID.
| #define GATT_SPEC_CHARC_ANALOG_OUTPUT 0x2A59 |
Analog Output Characteristic UUID.
| #define GATT_SPEC_CHARC_APPEARANCE 0x2A01 |
Appearance Characteristic UUID.
| #define GATT_SPEC_CHARC_BATTERY_LEVEL 0x2A19 |
Battery Level Characteristic UUID.
| #define GATT_SPEC_CHARC_BATTERY_LEVEL_STATE 0x2A1B |
Battery Level State Characteristic UUID.
| #define GATT_SPEC_CHARC_BATTERY_POWER_STATE 0x2A1A |
Battery Power State Characteristic UUID.
| #define GATT_SPEC_CHARC_BLOOD_PRESSURE_FEATURE 0x2A49 |
Blood Pressure Feature Characteristic UUID.
| #define GATT_SPEC_CHARC_BLOOD_PRESSURE_MEASUREMENT 0x2A35 |
Blood Pressure Measurement Characteristic UUID.
| #define GATT_SPEC_CHARC_BODY_SENSOR_LOCATION 0x2A38 |
Body Sensor Location Characteristic UUID.
| #define GATT_SPEC_CHARC_BOOT_KEYBOARD_INPUT_REPORT 0x2A22 |
Boot Keyboard Input Report Characteristic UUID.
| #define GATT_SPEC_CHARC_BOOT_KEYBOARD_OUTPUT_REPORT 0x2A32 |
Boot Keyboard Output Report Characteristic UUID.
| #define GATT_SPEC_CHARC_BOOT_MOUSE_INPUT_REPORT 0x2A33 |
Boot Mouse Input Report Characteristic UUID.
| #define GATT_SPEC_CHARC_CSC_FEATURE 0x2A5C |
Cycling Speed and Cadence Feature Characteristic UUID.
| #define GATT_SPEC_CHARC_CSC_MEASUREMENT 0x2A5B |
Cycling Speed and Cadence Measurement Characteristic UUID.
| #define GATT_SPEC_CHARC_CURRENT_TIME 0x2A2B |
Current Time Characteristic UUID.
| #define GATT_SPEC_CHARC_CYCLING_POWER_CONTROL_POINT 0x2A66 |
Cycling Power Control Point Characteristic UUID.
| #define GATT_SPEC_CHARC_CYCLING_POWER_FEATURE 0x2A65 |
Cycling Power Feature Characteristic UUID.
| #define GATT_SPEC_CHARC_CYCLING_POWER_MEASUREMENT 0x2A63 |
Cycling Power Measurement Characteristic UUID.
| #define GATT_SPEC_CHARC_CYCLING_POWER_VECTOR 0x2A64 |
Cycling Power Vector Characteristic UUID.
| #define GATT_SPEC_CHARC_DATE_TIME 0x2A08 |
Date Time Characteristic UUID.
| #define GATT_SPEC_CHARC_DAY_DATE_TIME 0x2A0A |
Day Date Time Characteristic UUID.
| #define GATT_SPEC_CHARC_DAY_OF_WEEK 0x2A09 |
Day Of Week Characteristic UUID.
| #define GATT_SPEC_CHARC_DEVICE_NAME 0x2A00 |
Device Name Characteristic UUID.
| #define GATT_SPEC_CHARC_DIGITAL_INPUT 0x2A56 |
Digital Input Characteristic UUID.
| #define GATT_SPEC_CHARC_DIGITAL_OUTPUT 0x2A57 |
Digital Output Characteristic UUID.
| #define GATT_SPEC_CHARC_DST_OFFSET 0x2A0D |
Dst Offset Characteristic UUID.
| #define GATT_SPEC_CHARC_EXACT_TIME_100 0x2A0B |
Exact Time 100 Characteristic UUID.
| #define GATT_SPEC_CHARC_EXACT_TIME_256 0x2A0C |
Exact Time 256 Characteristic UUID.
| #define GATT_SPEC_CHARC_FIRMWARE_REVISION_STRING 0x2A26 |
Firmware Revision String Characteristic UUID.
| #define GATT_SPEC_CHARC_GLUCOSE_FEATURE 0x2A51 |
Glucose Feature Characteristic UUID.
| #define GATT_SPEC_CHARC_GLUCOSE_MEASUREMENT 0x2A18 |
Glucose Measurement Characteristic UUID.
| #define GATT_SPEC_CHARC_GLUCOSE_MEASUREMENT_CONTEXT 0x2A34 |
Glucose Measurement Context Characteristic UUID.
| #define GATT_SPEC_CHARC_HARDWARE_REVISION_STRING 0x2A27 |
Hardware Revision String Characteristic UUID.
| #define GATT_SPEC_CHARC_HEART_RATE_CONTROL_POINT 0x2A39 |
Heart Rate Control Point Characteristic UUID.
| #define GATT_SPEC_CHARC_HEART_RATE_MEASUREMENT 0x2A37 |
Heart Rate Measurement Characteristic UUID.
| #define GATT_SPEC_CHARC_HID_CONTROL_POINT 0x2A4C |
Hid Control Point Characteristic UUID.
| #define GATT_SPEC_CHARC_HID_INFORMATION 0x2A4A |
Hid Information Characteristic UUID.
| #define GATT_SPEC_CHARC_IEEE_11073_REGULATORY_CERTIFICATION_DATA_LIST 0x2A2A |
IEEE Regulatory Certification Data List Characteristic UUID.
| #define GATT_SPEC_CHARC_INTERMEDIATE_CUFF_PRESSURE 0x2A36 |
Intermediate Cuff Pressure Characteristic UUID.
| #define GATT_SPEC_CHARC_INTERMEDIATE_TEMPERATURE 0x2A1E |
Intermediate Temperature Characteristic UUID.
| #define GATT_SPEC_CHARC_LN_CONTROL_POINT 0x2A6B |
Location Navigation Control point Characteristic UUID.
| #define GATT_SPEC_CHARC_LN_FEATURE 0x2A6A |
Location Navigation Feature Characteristic UUID.
| #define GATT_SPEC_CHARC_LOCAL_TIME_INFORMATION 0x2A0F |
Local Time Information Characteristic UUID.
| #define GATT_SPEC_CHARC_LOCATION_AND_SPEED 0x2A67 |
Location and Speed Characteristic UUID.
| #define GATT_SPEC_CHARC_MANUFACTURER_NAME_STRING 0x2A29 |
Manufacturer Name String Characteristic UUID.
| #define GATT_SPEC_CHARC_MEASUREMENT_INTERVAL 0x2A21 |
Measurement Interval Characteristic UUID.
| #define GATT_SPEC_CHARC_MODEL_NUMBER_STRING 0x2A24 |
Model Number String Characteristic UUID.
| #define GATT_SPEC_CHARC_NAVIGATION 0x2A68 |
Navigation Characteristic UUID.
| #define GATT_SPEC_CHARC_NETWORK_AVAILABILITY 0x2A3E |
Network Availability Characteristic UUID.
| #define GATT_SPEC_CHARC_NEW_ALERT 0x2A46 |
New Alert Characteristic UUID.
| #define GATT_SPEC_CHARC_PERIPHERAL_PREFERRED_CONNECTION_PARAMETERS 0x2A04 |
Peripheral Preferred Connection Parameters Characteristic UUID.
| #define GATT_SPEC_CHARC_PERIPHERAL_PRIVACY_FLAG 0x2A02 |
Peripheral Privacy Flag Characteristic UUID.
| #define GATT_SPEC_CHARC_PNP_ID 0x2A50 |
PnP Id Characteristic UUID.
| #define GATT_SPEC_CHARC_POSITION_QUALITY 0x2A69 |
Position Quality Characteristic UUID.
| #define GATT_SPEC_CHARC_PROTOCOL_MODE 0x2A4E |
Protocol Mode Characteristic UUID.
| #define GATT_SPEC_CHARC_PULSE_OXIMETRY_CONTINUOUS_MEASUREMENT 0x2A5F |
Pulse Oximetry Continuous Measurement Characteristic UUID.
| #define GATT_SPEC_CHARC_RECONNECTION_ADDRESS 0x2A03 |
Reconnection Address Characteristic UUID.
| #define GATT_SPEC_CHARC_RECORD_ACCESS_CONTROL_POINT 0x2A52 |
Record Access Control Point Characteristic UUID.
| #define GATT_SPEC_CHARC_REFERENCE_TIME_INFORMATION 0x2A14 |
Reference Time Information Characteristic UUID.
| #define GATT_SPEC_CHARC_REPORT 0x2A4D |
Report Characteristic UUID.
| #define GATT_SPEC_CHARC_REPORT_MAP 0x2A4B |
Report Map Characteristic UUID.
| #define GATT_SPEC_CHARC_RINGER_CONTROL_POINT 0x2A40 |
Ringer Control Point Characteristic UUID.
| #define GATT_SPEC_CHARC_RINGER_SETTING 0x2A41 |
Ringer Setting Characteristic UUID.
| #define GATT_SPEC_CHARC_RSC_FEATURE 0x2A54 |
Running Speed and Cadence Feature Characteristic UUID.
| #define GATT_SPEC_CHARC_RSC_MEASUREMENT 0x2A53 |
Running Speed and Cadence Measurement Characteristic UUID.
| #define GATT_SPEC_CHARC_SC_CONTROL_POINT 0x2A55 |
Speed and Cadence Control Point Characteristic UUID.
| #define GATT_SPEC_CHARC_SCAN_INTERVAL_WINDOW 0x2A4F |
Scan Interval Window Characteristic UUID.
| #define GATT_SPEC_CHARC_SCAN_REFRESH 0x2A31 |
Scan Refresh Characteristic UUID.
| #define GATT_SPEC_CHARC_SCIENTIFIC_TEMPERATURE_IN_CELSIUS 0x2A3C |
Scientific Temperature in Celsius Characteristic UUID.
| #define GATT_SPEC_CHARC_SECONDARY_TIME_ZONE 0x2A10 |
Secondary Time Zone Characteristic UUID.
| #define GATT_SPEC_CHARC_SENSOR_LOCATION 0x2A5D |
Sensor Location Characteristic UUID.
| #define GATT_SPEC_CHARC_SERIAL_NUMBER_STRING 0x2A25 |
Serial Number String Characteristic UUID.
| #define GATT_SPEC_CHARC_SERVICE_CHANGED 0x2A05 |
Service Changed Characteristic UUID.
| #define GATT_SPEC_CHARC_SOFTWARE_REVISION_STRING 0x2A28 |
Software Revision String Characteristic UUID.
| #define GATT_SPEC_CHARC_STRING 0x2A3D |
String Characteristic UUID.
| #define GATT_SPEC_CHARC_SUPPORTED_NEW_ALERT_CATEGORY 0x2A47 |
Supported New Alert Category Characteristic UUID.
| #define GATT_SPEC_CHARC_SUPPORTED_UNREAD_ALERT_CATEGORY 0x2A48 |
Supported Unread Alert Category Characteristic UUID.
| #define GATT_SPEC_CHARC_SYSTEM_ID 0x2A23 |
System Id Characteristic UUID.
| #define GATT_SPEC_CHARC_TEMPERATURE_IN_CELSIUS 0x2A1F |
Temperature in Celsius Characteristic UUID.
| #define GATT_SPEC_CHARC_TEMPERATURE_IN_FAHRENHEIT 0x2A20 |
Temperature in Fahrenheit Characteristic UUID.
| #define GATT_SPEC_CHARC_TEMPERATURE_MEASUREMENT 0x2A1C |
Temperature Measurement Characteristic UUID.
| #define GATT_SPEC_CHARC_TEMPERATURE_TYPE 0x2A1D |
Temperature Type Characteristic UUID.
| #define GATT_SPEC_CHARC_TIME_ACCURACY 0x2A12 |
Time Accuracy Characteristic UUID.
| #define GATT_SPEC_CHARC_TIME_BROADCAST 0x2A15 |
Time Broadcast Characteristic UUID.
| #define GATT_SPEC_CHARC_TIME_SOURCE 0x2A13 |
Time Source Characteristic UUID.
| #define GATT_SPEC_CHARC_TIME_UPDATE_CONTROL_POINT 0x2A16 |
Time Update Control Point Characteristic UUID.
| #define GATT_SPEC_CHARC_TIME_UPDATE_STATE 0x2A17 |
Update State Characteristic UUID.
| #define GATT_SPEC_CHARC_TIME_WITH_DST 0x2A11 |
Time With Dst Characteristic UUID.
| #define GATT_SPEC_CHARC_TIME_ZONE 0x2A0E |
Time Zone Characteristic UUID.
| #define GATT_SPEC_CHARC_TX_POWER_LEVEL 0x2A07 |
TX Power Level Characteristic UUID.
| #define GATT_SPEC_CHARC_UNREAD_ALERT_STATUS 0x2A45 |
Unread Alert Status Characteristic UUID.


Hi, I'm Eugene. I like to build things that make life easier + more interesting. I just graduated from UC Berkeley with a Chemistry B.S. I've a background in computational chemistry, microfluidics, circuit design, mechanical part design, and recently haptics + augmented reality. In my free time, I build electronic musical instruments and interactive, multimedia art installations. Now, I am studying web development. Very excited to meet/work with y'all. Meow <3.


Documentation is an important part of any project. On the projects I maintain I put a lot of effort on documentation, and, frankly, the majority of time spent on my projects is on documentation.
The matter of keeping the documentation faithful is a topic of interest. I'd like to outline a few documentation bundling possibilities, and the present the coming new documentation method for common_schema. I'll talk about any bundling that is NOT man pages.
High level: web docs
This is the initial method of documentation I used for openark kit and mycheckpoint. It's still valid for mycheckpoint. Documentation is web-based. You need Internet access to read it. It's in HTML format.
Well, not exactly HTML format: I wrote it in WordPress. Yes, it's HTML, but there's a lot of noise around (theme, menus, etc.) which is not strictly part of the documentation.
While this is perhaps the easiest way to go, here's a few drawbacks:
- You're bound to some framework (WordPress in this case)
- Docs are split between MySQL database (my underlying WordPRess storage) & WordPress files (themes, style, header, footer etc.)
- Documentation is separate from your code - they're just not in the same place
- There is no version control over the documentation.
The result is a single source of documentation, which applies to whatever version is latest. It's impossible to maintain docs for multiple versions. You must manually synchronize your WordPress updates with code commits (or rather - code release!).
Mid level: version controlled HTML docs
I first saw this approach on Baron's Aspersa gets a user manual post. I loved it: the documentation is HTML, but stored as part of your project's code, in same version control.
This means one can browse the documentation (openark kit in this example) exactly as it appears in the baseline. Depending on your project hosting, one may be able to do so per version.
The approach has the great benefit of having the docs tightly coupled with the code in terms of development. Before committing code, one updates documentation for that code, then commits/releases both together.
You're also not bound to any development framework. You may edit with vim, emacs, gedit, bluefish, eclipse, ... any tool of your choice. It's all down to plain old text files.
Mid level #2: documentation bundling
One thing I started doing with common_schema is to release a doc bundle with the code. So one can download a compressed bundle of all HTML files. That way one is absolutely certain what's the right documentation for revision 178. There's no effort about it: the docs are already tightly coupled with code versions. Just compress and distribute.
Low level: documentation coupled with your code
Perl scripts can be written as Perl modules, in which case they are eligible for using the perldoc convention. You code your documentation within your script itself, as comment. Perldoc can extract the documentation and present in man-like format. Same happens with Python's pydoc. Baron's When documentation is code illustrates that approach. Maatkit (now Percona Toolkit) has been using it for years.
This method has the advantage of having the documentation ready right within your shell. You don't need a browser, nor firewall access. The docs are just there for you in the same environment where you're executing the code.
SQL Low level: CALL for help()
common_schema is a different type of project. It is merely a schema. There's no Perl nor Python. One imports the schema into one's MySQL server.
What's the low-level approach for this type of code?
For common_schema I use three levels of documentation: the mid-level, where one can browse through the versioned docs, the 2nd mid-level, where one can download bundled documentation, and then a low-level approach: documentation embedded within the code.
MySQL's documentation is also built into the server: see the help_* tables within the mysql schema. The mysql command line client allows one to access help by supporting the help command, e.g.
mysql> help create table;
The client intercepts this command (this is not server side command) and searches through the mysql.help_* docs.
With common_schema, I don't have control over the client; it's all on server side. But the code being a schema, what with stored routines and tables, it's easy enough to set up documentation.
As of the next version of common_schema, and following MySQL's method, common_schema provides a help table:
DESC help; +--------------+-------------+------+-----+---------+-------+ | Field | Type | Null | Key | Default | Extra | +--------------+-------------+------+-----+---------+-------+ | topic | varchar(32) | NO | PRI | NULL | | | help_message | text | NO | | NULL | | +--------------+-------------+------+-----+---------+-------+
And a help() procedure, so that you can call for help(). The procedure will look for the best matching document based on your search expression:
<EMAIL_ADDRESS>CALL help('match'); +-------------------------------------------------------------------------------+ | help | +-------------------------------------------------------------------------------+ | | | NAME | | | | match_grantee(): Match an existing account based on user+host. | | | | TYPE | | | | Function | | | | DESCRIPTION | | | | MySQL does not provide with identification of logged in accounts. It only | | provides with user + host:port combination within processlist. Alas, these do | | not directly map to accounts, as MySQL lists the host:port from which the | | connection is made, but not the (possibly wildcard) user or host. | | This function matches a user+host combination against the known accounts, | | using the same matching method as the MySQL server, to detect the account | | which MySQL identifies as the one matching. It is similar in essence to | | CURRENT_USER(), only it works for all sessions, not just for the current | | session. | | | | SYNOPSIS | | | | | | | | match_grantee(connection_user char(16) CHARSET utf8, | | connection_host char(70) CHARSET utf8) | | RETURNS VARCHAR(100) CHARSET utf8 | | | | | | Input: | | | | * connection_user: user login (e.g. as specified by PROCESSLIST) | | * connection_host: login host. May optionally specify port number (e.g. | | webhost:12345), which is discarded by the function.  I think it's a good format, provided you don't start doing funny things. Perhaps TROFF is more suitable; certainly more popular on Unix machines. But I already have everything in HTML. So, what do I do?
My decision was to keep documentation in HTML, and use the handy html2text tool to do the job. And it does it pretty well! The sample you see above is an automated translation of HTML to plain text.
I add a few touches of my own: SELECTing long texts is ugly, whether you do it via ";" or "\G". The help() routine breaks the text by '\n', returning a multi row result set. The above sample makes for some 60+ rows, nicely formatted, broken from the original single text appearing in the help table.
So now you have an internal help method for common_schema, right where the code is. You don't have to leave the command line client in order to get help.
Giuseppe offered me the idea for this, even while my own thinking about it was in early stages.
The next version of common_schema will be available in a few weeks. The code is pretty much ready. I just need to work on, ahem..., the documentation.
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Module ActionInstance
All actions created by this class.
The most of this API you should use only on develop your own custom actions.
-
initialize(trigger_callback[, release_callback])
-
Action Instance constructor function
Parameters:
- trigger_callback
function
The main action function
- release_callback
function
The release function. Clean up stuff, it you need
(optional)
-
ActionInstance.static.copy(prefab)
-
Copy constructor
Parameters:
- prefab
ActionInstance
The action to copy
Returns:
ActionInstance
Copy of prefab action
-
event(event_name)
-
Trigger event to action's FSM
Parameters:
- event_name
string
Name of trigger event
-
get_value(variable_name)
-
Return variable value from FSM variables
Parameters:
- variable_name
string
The name of variable in FSM
-
set_value(variable_name, value)
-
Set variable value in action's FSM
Parameters:
- variable_name
string
The name of variable in FSM
- value
any
New value for variable
-
get_param(param)
-
Check if param value is from FSM variables. If not - return itself or return variable from FSM
Pass this values to action args via `actions.value()`
Parameters:
Returns:
any
See also:
-
set_every_frame()
-
Set action triggered every frame. Initial call will be skipped
Returns:
ActionInstance
Self
-
set_with_context()
-
Add context to this actions. It's cross call table, the second arg in
trigger and release callbacks
Returns:
ActionInstance
Self
-
set_periodic([seconds[, skip_initial_call]])
-
Set periodic trigger of action.
Parameters:
- seconds
number
The time between triggers
(optional)
- skip_initial_call
boolean
If true, skip first initial call on state enter
(optional)
Returns:
ActionInstance
Self
-
set_delay(seconds)
-
Add delay before action is triggered. Every frame and periodic trigger will start
after delay is happened. You should call finished method in action trigger function.
You can pass action.param as second argument
Parameters:
- seconds
number, variable or nil
Action delay
Returns:
ActionInstance
Self
-
set_deferred([state])
-
Set action to deferred state. To complete the action `finished` should be called
Parameters:
- state
boolean
The deferred state
(optional)
-
is_deferred()
-
Return action deferred state. If action is deferred - it can be executed in one frame
Returns:
boolean
Action deferred state
-
set_name(name)
-
Set the name of the action
Parameters:
Returns:
ActionInstance
Self
-
get_name()
-
Return the name of the action
Returns:
string
The action name
-
finish(trigger_event)
-
Function called when action is done. Never called on actions with "is_every_frame"
or "is_periodic". Deferred actions should call manually this function
Parameters:
- trigger_event
string
Event to trigger before finish call
-
force_finish(trigger_event)
-
Force finish action, even with "is_every_frame" or "is_periodic". This call
will stop any updates of this action
Parameters:
- trigger_event
string
Event to trigger before finish call
-
set_debug(state)
-
Set debug state of action. If true, will print debug info to console
Parameters:
- state
boolean
The debug state
Returns:
ActionInstance
Self
-
context
-
Action context table
-
_name
-
The action instance name
-
_trigger_callback
-
desc
- _trigger_callback
function(ActionInstance)
-
_release_callback
-
desc
- _release_callback
function(ActionInstance)
(optional)
-
_state_instance
-
desc
- _state_instance
StateInstance
-
_is_every_frame
-
desc
-
_is_deferred
-
desc
-
_is_periodic
-
desc
-
_periodic_timer
-
desc
-
_periodic_timer_current
-
desc
- _periodic_timer_current
number
-
update(dt)
-
Update function, called by StateInstance
Parameters:
-
trigger()
-
Trigger action, called by StateInstance
-
release()
-
Release action (cleanup), called by StateInstance
-
get_adam_instance()
-
Return action's AdamInstance. Used internally
Returns:
AdamInstance
-
set_state_instance(state_instance)
-
Set StateInstance for this action instance. Called by StateInstance
Parameters:
- state_instance
StateInstance
-
_get_delay_seconds()
-
Get seconds to delay for trigger action
Returns:
number
Seconds to delay
-
_trigger_action()
-
Actual call of trigger callback. Used internally


Supply Converter Motor Load System (SCML)¶
The technical structure of the SCML-Systems in the GEM-toolbox can bee seen in the figure below.
The system consists of a Voltage Supply, a Power Electronic Converter, an Electrical Motor and the Mechanical Load. Additionally, each SCML-System has got an ODE-Solver for the simulation.
The abstract SCML-System defines the overall structure. From this, the DcMotorSystem and the SynchronousMotorSystem derive. They only implement private methods. Therefore, the interface to the user stays the same in all cases.
-
class
gym_electric_motor.physical_systems.physical_systems.
SCMLSystem
(converter, motor, load=None, supply='IdealVoltageSupply', ode_solver='euler', solver_kwargs=None, noise_generator=None, tau=0.0001, **kwargs)[source]¶ The SCML(Supply-Converter-Motor-Load)-System is used for the simulation of a technical setting consisting of these components as well as a noise generator and a solver for the electrical ODE of the motor and mechanical ODE of the load.
Parameters: - converter (PowerElectronicConverter) – Converter for the physical system
- motor (ElectricMotor) – Motor of the system
- load (MechanicalLoad) – Mechanical Load of the System
- supply (VoltageSupply) – Voltage Supply
- ode_solver (OdeSolver) – Ode Solver to use in this setting
- solver_kwargs (dict) – Special keyword arguments to be passed to the solver
- noise_generator (NoiseGenerator) – Noise generator
- tau (float) – discrete time step of the system
- kwargs (dict) – Further arguments to pass to the modules while instantiation
-
converter
¶ The power electronic converter instance in the system
-
electrical_motor
¶ The electrical motor instance of the system
-
limits
¶ **Returns* – ndarray(float)* – An array containing the maximum allowed physical values for each state variable.
-
mechanical_load
¶ The mechanical load instance in the system
-
nominal_state
¶ **Returns* – ndarray(float)* – An array containing the nominal values for each state variable.
-
reset
(*_)[source]¶ Reset all the systems modules to an initial state.
Returns: The new state of the system.
-
simulate
(action, *_, **__)[source]¶ Simulation of the Physical System for one time step with the input action. This method is called in the environment in every step to update the systems state.
Parameters: action (element of action_space) – The action to play on the system for the next time step. Returns: The systems state after the action was applied. Return type: element of state_space
-
supply
¶ The voltage supply instance in the physical system
Dc Motor System¶
-
class
gym_electric_motor.physical_systems.physical_systems.
DcMotorSystem
(converter, motor, load=None, supply='IdealVoltageSupply', ode_solver='euler', solver_kwargs=None, noise_generator=None, tau=0.0001, **kwargs)[source]¶ SCML-System that can be used for all DC Motors.
Parameters: - converter (PowerElectronicConverter) – Converter for the physical system
- motor (ElectricMotor) – Motor of the system
- load (MechanicalLoad) – Mechanical Load of the System
- supply (VoltageSupply) – Voltage Supply
- ode_solver (OdeSolver) – Ode Solver to use in this setting
- solver_kwargs (dict) – Special keyword arguments to be passed to the solver
- noise_generator (NoiseGenerator) – Noise generator
- tau (float) – discrete time step of the system
- kwargs (dict) – Further arguments to pass to the modules while instantiation
Synchronous Motor System¶
The Synchronous Motor System is an SCML-System that was internally
-
class
gym_electric_motor.physical_systems.physical_systems.
SynchronousMotorSystem
(converter, motor, load=None, supply='IdealVoltageSupply', ode_solver='euler', solver_kwargs=None, noise_generator=None, tau=0.0001, **kwargs)[source]¶ SCML-System that can be used with all Synchronous Motors
Parameters: - converter (PowerElectronicConverter) – Converter for the physical system
- motor (ElectricMotor) – Motor of the system
- load (MechanicalLoad) – Mechanical Load of the System
- supply (VoltageSupply) – Voltage Supply
- ode_solver (OdeSolver) – Ode Solver to use in this setting
- solver_kwargs (dict) – Special keyword arguments to be passed to the solver
- noise_generator (NoiseGenerator) – Noise generator
- tau (float) – discrete time step of the system
- kwargs (dict) – Further arguments to pass to the modules while instantiation


CLSA sees Nifty at 13,700-13,800 levels if index surpasses its earlier high
The sideways movement begun after the index rallied 1,300 points from 10,700 to around 12,000 in a span of just two months on the back of several government measures
by Moneycontrol NewsThe Nifty has been finding it tough to breach the psychological 12,000 mark on continuous profit booking around that level.
In fact, it remains in consolidation mode for the third consecutive week and is trading between 11,850 and 12,000 levels.
The sideways movement begun after the index rallied 1,300 points from 10,700 to around 12,000 in a span of just two months on the back of several government measures including a cut in the corporate tax rate by 10 percentage points.
The recent September quarter earnings and cut in corporate tax rate made analysts confident about future corporate earnings growth.
Laurence Balanco, Technical Analyst at CLSA, believes 12,070-12,118 should provide a platform for resumption of the market long-term uptrend. "A break above 12,070-12,118 would project an upside target of 13,700-13,800, with a shelf of support at 11,098-11,310 levels."
Disclaimer: The above report is compiled from information available on public platforms. Moneycontrol.com advises users to check with certified experts before taking any investment decisions.


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39 references to StateChanged
System.Management.Automation (39)
engine\debugger\debugger.cs (4)
3178
jobArgs.Job.
StateChanged
+= HandleJobStateChanged;
3181
jobArgs.Job.
StateChanged
-= HandleJobStateChanged;
3264
job.
StateChanged
-= HandleJobStateChanged;
4018
job.
StateChanged
-= HandleJobStateChanged;
engine\hostifaces\LocalConnection.cs (2)
1333
_job.
StateChanged
+= HandleJobStateChanged;
1385
_job.
StateChanged
-= HandleJobStateChanged;
engine\remoting\client\Job.cs (9)
312
/// <see cref="Job.
StateChanged
"/> event.
930
this.
StateChanged
+= stateChangedEventHandler;
969
this.
StateChanged
-= stateChangedEventHandler;
1439
StateChanged
.SafeInvoke(this, new JobStateEventArgs(JobStateInfo.Clone(), previousState));
1792
childJob.
StateChanged
+= HandleChildJobStateChanged;
1827
job.
StateChanged
+= HandleChildJobStateChanged;
1857
job.
StateChanged
+= HandleChildJobStateChanged;
2058
_psRemoteChildJob.
StateChanged
+= ChildJobStateChangedHandler;
2118
_psRemoteChildJob.

StateChanged
+= HandleChildJobStateChanged;
2017
StateChanged
-= HandleMyStateChanged;
engine\remoting\client\ThrottlingJob.cs (6)
418
childJob.
StateChanged
+= this.childJob_StateChanged;
723
childJob.
StateChanged
-= childJob_StateChanged;
897
job.
StateChanged
+= MonitoredJob_StateChanged;
911
job.
StateChanged
-= this.MonitoredJob_StateChanged;
1203
throttlingJob.
StateChanged
+= helper.ThrottlingJob_StateChanged;
1238
throttlingJob.
StateChanged
-= helper.ThrottlingJob_StateChanged;
engine\remoting\commands\DebugJob.cs (2)
318
_job.
StateChanged
+= HandleJobStateChangedEvent;
338
_job.
StateChanged
-= HandleJobStateChangedEvent;
engine\remoting\commands\InvokeCommandCommand.cs (2)
1422
_job.
StateChanged
+= HandleJobStateChanged;
1461
_job.
StateChanged
-= HandleJobStateChanged;
engine\remoting\commands\ReceiveJob.cs (3)
1018
job.
StateChanged
+= HandleJobStateChanged;
1026
job.
StateChanged
-= HandleJobStateChanged;
1398
job.
StateChanged
-= HandleJobStateChanged;
engine\remoting\commands\WaitJob.cs (2)
215
job.
StateChanged
+= this.HandleJobStateChangedEvent;
227
job.
StateChanged
-= this.HandleJobStateChangedEvent;


--- layout: post title: Episode 040 | Yves Goeleven - Look at Users link: http://traffic.libsyn.com/developeronfire/DeveloperOnFire-40-YvesGoeleven.mp3 length: 29360128 speaker: Dave Rael duration: '29:56' subtitle: 'Developer On Fire: Yves Goeleven' guest_name: Yves Goeleven image: /assets/images/YvesGoeleven.jpg guest_blog: http://www.goeleven.com/ guest_twitter: YvesGoeleven disqus_url: http://developeronfire.com/Podcast/Episodes/yves-goeleven-look-at-users episode_number: 40 book_recommendations: - { url: "http://www.amazon.com/dp/0321322118/?tag=devonfir-20", title: "Event-Driven Architecture: How SOA Enables the Real-Time Enterprise", author: "Hugh Taylor, Angela Yochem, Les Phillips, Frank Martinez"} tags: - { url: "http://www.amazon.com/dp/0321322118/?tag=devonfir-20", title: "Event-Driven Architecture: How SOA Enables the Real-Time Enterprise", author: "Hugh Taylor, Angela Yochem, Les Phillips, Frank Martinez"} redirect_from: - "/40/" - "/040/" - "/0040/" - "/yves-goeleven-look-at-users/" - "/Yves-Goeleven/" - "/YvesGoeleven/" - "/Podcast/Episodes/40/" - "/Podcast/Episodes/040/" - "/Podcast/Episodes/0040/" - "/Podcast/Episodes/yves-goeleven-look-at-users/" - "/Podcast/Episodes/Yves-Goeleven/" - "/Podcast/Episodes/YvesGoeleven/" guid: http://developeronfire.com:80/Podcast/Episodes/yves-goeleven-look-at-users ---
Yves has been shipping enterprise and cloud software since 2001. He is specialized in the design of distributed software systems using messaging. Next to being the founder of MessageHandler.net, an online platform for the co-creation of message processing logic, he is also active as a Solution Architect for Particular Software (NServiceBus), which provides a messaging platform for developing such logic. Yves has been awarded Windows Azure MVP for the last 5 years and is a regular on the speaking circuit.
1. Look at users - don't ask them what they want, they don't know - watch what they do instead
2. Try to fix real problems
3. Keep doing 1 and 2


I can see you are the rain that falls at night
I can see it -you are moonlight
that reflection on the dew; the grass,
cool beneath our feet
Its the hallow edge of time
tick the hour clock and go away you
I need it not be beckoned forth
for this reason:
humans were born here
humans died and were buried
the stone's mass toss and turn
-[even they cannot stand forever]
I want you to go out
burn up -so that you feel no loss in feeling's less
the earth will shake the sun will
rise up- over again and over,
Where will you be- out there?
I will not let you be forgotten
so when you die
our memories will not be
left to the rubble that cannot keep
-no names that wash away
-no noises
-no moss and earth raised up
-no one-hundred years spent after we die
-living not in children
-no-
beings not there- nor will you
come again as
running animals or something awful
-your life - if you give me
your hand- will be
as I give you my hand
-in the here and now
And so forth will we live in this moment
until the sun fails to rise
the moon fails to set:
for a hundred years long winter waits behind
Part two:
Raise from the ground
all those who are gone
for fear them not
they are so let them be-
for all they are I know they are-
their apparatus reach above the ground
This place is a grave land
lights flash to illuminate the
sour and uneven earth
interspersed strangely small trees
I have not the strength to move against it
the metaphysics are not mine
but in them I share with you,
I can not be more further from your eyes than you make me out to be and go,
predicate where I go with your mind
and you follow me out there because for what feeling were you looking for?
What but the sensation that is the circumstance of our commotion
that your mind follows me-
I track you with my dreams at night
and am ready for when in you are there
I will shroud you in the metaphysics
that cloak the stars
though they be it not your body
though they be it not some dreams
I will move over, trace you, when mention to me
my metaphysics
Let be what will change you
for all that I
know your there
when the rain came and the moon-light shown you
thought that before that if it fails you now
you will only widen your eyes more
before that
dawn came
Let me elaborate with what strength I have left, my metaphysics.


For as long as I could remember I have always wanted to create. To create programs, to create art, to create ideas -- to just create! And these creations never had to be in any creative or even practical capacity. Hell, they don't even have to be good or useful in anyway. There lay an incredible feeling of joy in my ability to make something that did not exist before.
Stemming from these notions, it always seemed to me that the natural state of my progression would be towards entrepreneurship. These were folks who were the ultimate creators. From nothing but sweat, blood, and tears their ideas were turned into tangible goods and services that have added some sort of value to thousands if not millions of lives.
And now here I am, in San Francisco trying to do just that. I, along with a good friend of mine, are in two well-known accelerators in the heart of city. We are turning what have been grand visions, grand ideas, and grand delusions into something more tangible. And while the honeymoon period hasn't quite ended, the stress and the fear is bubbling up.
Imposter Syndrome
I feel the pressure, under more scrutiny,
and what I do? Act more stupidly.
I always felt a tinge of what I would later find out to be called the imposter syndrome. For most of my life I have felt lucky. Lucky to have parents who have looked out for me, lucky to have been placed in crazy opportune moments, lucky to have gathered the skills that placed me in the very position I am now. Behind all this luck, there lies doubt. Doubt that someday that luck which has brought me so much will finally run out. It's a truly terrifying thought.
Every extra slice of success adds to the tension. Parents expect more. Friends expect more. People expect more. And perhaps worse of all, I expect more. Its easy to see how it can all go wrong, but what happens when it all goes right?
The Long Road Ahead
All for freedom and for pleasure
Nothing ever lasts forever
Everybody wants to rule the world.
Demo day is a long ways away. A lot can happen between now and then. Everyone is currently all hopped on energy and the newness of it all. The impending crunch is barely on the horizon.
Looking back, I felt it would be interesting to document the ups and downs over the next couple months. Writing helps put the whirlwind of thoughts and emotions into something coherent. At the very least it'll be therapeutic. Maybe someone out there will find it useful. Maybe someone else in the same situation will stumble upon this and feel some sort of solidarity. All I know is that there is a vast unknown in front of me and a long difficult journey ahead.
But boy is it exciting.


Server Class
Monobrow server constructor. The server handles the creation of a nodejs socket server as well as as an instance of the monobrow connection manager.
Constructor
Server
()
Item Index
Methods
Properties
- _address
- CLIENT_DID_CONNECT static
- CLIENT_DID_DISCONNECT static
- INITIALIZED static
- RUNNING static
- STATE_CHANGE static
- STOPPED static
Methods
__initialize
(
private
-
options
Initialized the server instance
Parameters:
-
options
ObjectThe options passed through the constructor
start
()
Starts the TCP server on the specified port and host


Your contributions to the project are very welcome. If you would like to fix a bug or propose a new feature, you can submit a Pull Request.
To help us merge your Pull Request, please make sure you follow these points:
jquery.handsontable.js
, jquery.handsontable.css
, jquery.handsontable.full.js
, jquery.handsontable.full.css
. Instead, try to edit files inside the src/
directory and then use grunt
to make a build. More information about this on wiki page Building.tests/jasmine/spec/
or src/3rdparty/walkontable/test/jasmine/spec/
. This helps us understand the issue and make sure that it will stay fixed forever.Thank you for your commitment!


Welcome to Home Team Supply's Vinal Technical High School Online Catalog. We hope to give you a glimpse at the styles and fashions acceptable at school this year. And we've made ordering easy - you can choose what fits your lifestyle the best -- stop by our store in Middletown, mail us your order or make your selections online.
At the store, we'll gladly accept cash, check or credit card; or you can mail in your order with a check or if you wish to use a credit card, order online. We don't ask for ANY personal financial information online, we'll get that when we talk to you -- we double-check and finalize every order, making sure that you get exactly what you want.
|
|
We would love for you to stop by and see us at 24 Broad Street.
|
|
If it's more convienent, print off the forms and mail them to us.
|
|
The easiest and fastest way is to order ONLINE.
|


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{% raw %}APPENDIX.{% endraw %}
{% raw %}213{% endraw %}
{% raw %}against Colonial Slavery. American judicial courts had imprisoned{% endraw %}
{% raw %}and fined many who had spoken against slavery. All these historic{% endraw %}
{% raw %}facts called the attention of philanthropists in the United States to{% endraw %}
{% raw %}the evils and crime of slavery ; Dr. Beecher's seminary could not{% endraw %}
{% raw %}resist the rising discussion of that crowned iniquity ! The moli{% endraw %}
{% raw %}threatened, and Kentucky slaveholders went over to urge it on to{% endraw %}
{% raw %}violence. To save the property, the trustees interfered, and calmed{% endraw %}
{% raw %}the mob by the assurance that slavery should not further be dis¬{% endraw %}
{% raw %}cussed in the seminary. Another rebellion came from within, for{% endraw %}
{% raw %}the students refused to obey the order of the trustees, and left the{% endraw %}
{% raw %}seminary in a body. For years Beecher and Stowe sought in vain{% endraw %}
{% raw %}to restore the prosperity of that seminary. In 1850 the}- returned{% endraw %}
{% raw %}to the Eastern States—Stowe to the Professor's chair of Biblical{% endraw %}
{% raw %}literature in Andover Theological Seminary, and Lyman Beecher{% endraw %}
{% raw %}to the work of the ministry in Cincinnati.{% endraw %}
{% raw %}Harriet Beecher spent eighteen years in this Lane Seminary ;{% endraw %}
{% raw %}having previously assisted her sister Catharine, in the conduct of a{% endraw %}
{% raw %}training school for female teachers. Cincinnati is a city situated{% endraw %}
{% raw %}on the northern bank of the Ohio ; and upon the high hill, whose{% endraw %}
{% raw %}point, crowned with an observatory, overhanging the city on the{% endraw %}
{% raw %}west, was Lane Seminary. The village nearest to it was called{% endraw %}
{% raw %}the Walnut Hills and one of the prettiest in the environs. It was{% endraw %}
{% raw %}here, therefore, that Harriet Beecher lived, and helped her sister{% endraw %}
{% raw %}in teaching, until her marriage, at the age of twenty-five, with{% endraw %}
{% raw %}Professor Calvin E. Stowe, of the Seminary, over which her father{% endraw %}
{% raw %}then was president. But few of Mrs. H. Beecher-Stowe's numerous{% endraw %}
{% raw %}offspring have survived. Mrs. Stowe says :—{% endraw %}
{% raw %}"Charlie, the most beautiful of my children, and the most be¬{% endraw %}
{% raw %}loved, lies buried near my Cincinnati residence. It was at his{% endraw %}
{% raw %}dying bed and at his grave that I learnt what a poor slave-mother{% endraw %}
{% raw %}may feel when her child is torn from her. In the depths of my{% endraw %}
{% raw %}sorrow, which seemed to me immeasurable, it was my only prayer to{% endraw %}
{% raw %}God that such anguish might not be suffered in vain.{% endraw %}
{% raw %}" There were circumstances connected with this child's death of{% endraw %}
{% raw %}such peculiar bitterness—of what might seem almost cruel suffering{% endraw %}
{% raw %}—that I felt 1 could never be consoled for it, unless it should appear{% endraw %}
{% raw %}that the crushing of my own heart might enable me to work out{% endraw %}
{% raw %}some great good to others.{% endraw %}
{% raw %}"His death took place during the cholera-summer, when in a{% endraw %}
{% raw %}circle of five miles around me, 9,000 were buried—a mortality{% endraw %}
{% raw %}which I have never heard exceeded anywhere.{% endraw %}
{% raw %}"My husband, in feeble health, was obliged to be absent the{% endraw %}
{% raw %}whole 'time, and I had sole charge of a family of fifteen persons.{% endraw %}
{% raw %}He did not return to me, because I would not permit it ; for in{% endraw %}
{% raw %}many instances where parents had returned from a distance to their{% endraw %}
{% raw %}families, and to the infected atmosphere, the result had been sudden{% endraw %}
{% raw %}death, and the physicians warned me that if he returned, it would{% endraw %}
{% raw %}only be to die. My poor Charlie died for want of timely medical{% endraw %}
{% raw %}aid ; for in the universal confusion and despair that prevailed, it{% endraw %}
{% raw %}was often impossible to obtain assistance till it was too late'{% endraw %}


Chapter 2 Multiple Linear Regression
This chapter has not yet been summarized completely.
Since liner models are well known (at least to me), the chapter is kept very brief.
The goal of linear modelling is
- A good fit: Explain a lot of variance and keep the errors small.
- Good parameter estimates.
- Prediction: Predict new values.
- Inference: Say something about whether a variable has an influence or not on the response via significance levels and confidence intervals.
Note that a good (in-sample) fit conflicts with good prediction out-of-sample.
Linear models are stochastic, since \(\epsilon\) is stochastic and hence the response variable \(Y_i\) also. We can assume that the predictors are non-random.
Linear models are called linear because they are linear in the coefficients, not linear in the predictors. The predictors can be transformed arbitrary.
Note the difference between the residuals \(r_i\) and the errors \(\epsilon_i\). The residuals are the estimates of the errors. The variance of the error can be estimated with
\[ \hat{\sigma}^2 = \frac{1}{n - p} \sum\limits_{i = 1}^n {r_i}^2\] The solution linear models is computed via ordinary least squares and can be derived analytically.
\[\hat{\beta} = (X'X)^{-1}X'Y\] For numerical stability reasons, do not compute the inverse of a matrix if possible, but do a QR decomposition instead. Here, we can do that by using the normal equations \[ \begin{split} \hat{\beta} & = (X'X)^{-1}X'Y\;\;\;\;\, | \times (X'X) \;\; \text{from left} \\ (X'X)\hat{\beta} &= X'Y \;\;\; \;\;\; \;\;\; \;\;\; \;\;\; | X = QR \;\;\; \text{whereas} \;\;Q \;\; \text{is orthogonal} \\ R'R\hat{\beta} &= X'Y \;\;\; \;\;\; \;\;\; \;\;\; \;\;\; | \;\; \text{set} \;\; c= R\beta \\ R'c & = X'Y \\ \end{split} \]
Since \(R'\) is a lower triangular matrix, you can now solve for \(c\) recursively.
\[\begin{pmatrix} r_{11} & & & & \large 0 \\ \cdots & \cdots & & & \\ \cdots &\cdots & \cdots & & \\ \cdots & \cdots &\cdots & \cdots & \\ \cdots & \cdots & \cdots & \cdots & \cdots \end{pmatrix} \times \begin{pmatrix} c_1 \\ \vdots \\ \vdots \\\vdots \\ c_n \\ \end{pmatrix} = (X'Y)_{n \times 1} \] First, solve \(c_1\) using \(r_{11} c_1 = (X'Y)_{1}\), then for \(c_{2}\) etc. when \(c\) is solved, solve \[ R\beta = c\]
Which has the same structure.
2.1 Assumptions of the linear model
- The functional form of the model is correct \(\mathbb{E}[\epsilon_i] = 0\). If violated, you cannot use linear models.
- The \(x_i\)s are exact.
- The variance of the errors is constant (homoskedasticity). If violated, use weighted least squares.
- The errors are uncorrelated. If violated, use generalized least squares (pre-whitening)
- The errors are jointly normally distributed. If violated, use robust methods or variable transformation.
2.2 Geometric interpretation
The respone variable is a vector in \(\mathbb{R}^n\). The fitted values \(\hat{Y} = X \hat{\beta}\) span are a \(p\) dimensional subspace in \(\mathbb{R}^n\) when varying \(\hat{\beta}\). The least square solution is the solution for \(\hat{\beta}\) such that the eucledian distance between \(Y\) and \(\hat{Y}\) is minimal. Note that the true \(\beta\) (i.e. the one that from the data-generatling process) corresponds to the solution \(\mathbb{E}[Y]\), which also lays within the subspace, but due to the error introduced, in the process, the two do not coincide.
Hence, \(X\beta\) is the orthogonal projection of \(Y\) onto \(\mathcal{X}\).
Note that the vector [1, …, 1] is contained in the \(p\)-dimensional subspace if our model has an interecept. You can see that if you imagine we only had a model with an intercept. The design matrix would then just be such a [1, …, 1] vector. Setting \(\beta\) equal to any number will yield a scaled unit vector as a prediction, i.e. just \(\beta \times [1, ..., 1]\). This subspace contains the vector [1, …, 1], since you can connect any two points in the space with a scaled version of this vector.
Therefore, the residuals are orthogonal to the vector [1, …, 1] , as one can see from the picture. This means \(r'\textbf{1} = 0\) and hence \[ \frac{1}{n} \sum r'\textbf{1} = \bar{r} = 0\] I.e. the residuals are zero on average.
2.3 Hat matrix
We can also look at another projection or mapping. \[ P: \; Y \rightarrow \hat{Y}\] Using \[X \hat{\beta} = X(X'X)^{-1}X'y = Py \;\; \text{with} \;\; P = X(X'X)^{-1}X'\] We call \(P\) the hat matrix. The aforementioned projection is an orthogonal projection since:
- \(P\) is symmetric: \(P = P'\)
- \(P\) is idempotent: \(P^2 = P\)
- The trace of \(P_{p\times p}\) is equal to \(p\)
The last one can be shown as follows: \[ tr(X(X'X)^{-1}X') = tr((X'X)^{-1}X'X) = tr(I_{p \times p}) = p\]
2.4 Multiple regression vs. simple regression
Doing many simple regressions instead of one multiple linear regression does not give the same result in general. Let’s consider two predictors. If they are positively correlated and we omit one, we will overestimate the effect of the remaining predictor. If they are negatively correlated, we will underestimate it. Simple regressions only yield the same result as multiple linear regression if the variables are not correlated. This can be seen well algebraically.
Orthogonal predictors means \[ (X'X) = diag(\sum\limits_{i = 1}^n {x_{1i}}^2, ..., \sum\limits_{i = 1}^n{x_{pi}}^2)\] Which yields \[ \beta_j = \sum\limits_{i = 1}^n x_{ij} Y_i / \sum\limits_{i = 1}^n {x_{ij}}^2\] So we can easily see that the coefficient \(\beta_j\) only depends on the j-th predictor.
2.5 Properties
2.6 Tests
We know that, if \(\epsilon \sim \mathcal{N}_p(0, \sigma^2)\) the distribution of our coefficients is as follows: \(\hat{\beta} \sim \mathcal{N}_p(\beta, \sigma^2(X'X)^{-1})\). Hence, we know that the standardized versions of the coefficients, i.e. \[\frac{\hat{\beta}_j - \beta_j}{\sigma^2(X'X)_{jj}} \sim \mathcal{N}_p(0, 1)\]
If our Null Hypothesis is \(\beta_j = 0\) the above becomes \[\frac{\hat{\beta}_j}{\sigma^2(X'X)_{jj}} \sim \mathcal{N}_p(0, 1)\] We can plug in our estimate for \(\sigma^2\),
\[\frac{\hat{\beta}_j}{\hat{\sigma}^2(X'X)_{jj}} \sim \mathcal{t}_{n-p}(0, 1)\]
Individual tests measure the significance of a variable given all the other variables in the model. If you want to look at whether a group of variables is significant, i.e. your Null Hypothesis is \(H_0: \beta_1 = ... = \beta_k = 0\)
If you recall the picture from above, we can see that we can decompose the total sum of squares into \[ SST = SSR + SSE\]
The F-ratio is nothing else than the share of variance we can explain with our mode, scaled by some degree of freedom related stuff.
\[F = \frac{\|\hat{Y} - \bar{Y}\|^2 / (p-1)}{\|Y - \bar{Y}\|^2/(n-p)}\]
For the goodness of fit measure \(R^2\) drop those scaling factors.
\[R^2 = \frac{\|\hat{Y} - \bar{Y}\|^2}{\|Y - \bar{Y}\|^2}\]
Similarly to t-tests derived above, we can construct confidence intervals. \[\hat{\beta}_j ± \sqrt{\hat{\sigma}^2 {(X'X)_{jj}}^{-1}} * t_{n-p, 1-\alpha/2}\]
2.7 Diagnostics
The Tuskey-Anscombe plot is a good tool to detect model violations. It takes advantage of the fact that the residuals are never correlated with the predictors and we can display the response versus the residuals also for \(p>1\), which is not possible if we plot against the predictors (at least not in one plot). Ideally, the points fluctuate randomly around the horizontal zero-line.
The Normal-plot helps to identify violations of the normality assumption.
You can also plot the residuals against time or calculate auto-correlation to detect serial dependency in the residuals.
2.8 Generalized least squares
Applies to the situation where
\[ Y = X\beta + \epsilon \;\;\; |\; \epsilon \sim \mathcal{N}(0, \Sigma)\] Where \(\Sigma\) takes a more general form than previously:
- The errors can be correlated (so \(\Sigma\) does not have to be diagonal matrix)
- The errors do not need to have identical variance (homoscedasticity)
We can transform the data with a matrix \(A\) such that we end up with \[ \tilde{Y} = \tilde{X}\beta + \tilde{\epsilon} \;\;\; |\; \tilde{\epsilon} \sim \mathcal{N}(0, \bf{1_{p \times p}})\] The following must hold
\[ \begin{split} Cov(A \epsilon) &:= \bf{1_{n \times n}} \\ \mathbb{E}[A\epsilon \epsilon' A'] & = A \Sigma A' \;\; \;\;\;\;| \;\text{decomposing} \; \Sigma \; \text{e.g. with Cholesky} \;\; \\ &= ACC'A' \;\; | \text{now choosing}\; A = C^{-1} \\ & = \bf{1_{n \times n}} \\ \end{split} \] Hence, we transform the data with the inverse of the (for example) lower triangular matrix resulting from the Cholesky decomposition and we will get uncorrelated errors.
A special case is when we have uncorrelated errors, but heteroskedasticity. Choose the weight \(\tilde{w}\) such that \(Var(\tilde{w}_i x_i) = 1\). If \(Var(x_i) = {\sigma_i}^2\) set \(\tilde{w}_i = 1 / {\sigma_i}\) to fulfill the above equation. The optimization problem becomes
\[ \begin{split} \hat{\beta} &= \arg\min\limits_{\beta} \sum {\tilde{r}_i}^2 = \arg\min\limits_{\beta} \sum (\tilde{w}_i r_i)^2 \\ &=\arg\min\limits_{\beta} \sum w {r_i}^2 = \arg\min\limits_{\beta} \sum w {(y_i - {x_i}'\beta)}^2 \end{split} \] So \(w_i = \tilde{w_i}^2 = 1/ \sigma_i^2\) is just a weighted regression.
2.9 Model Selection
If we have a set of \(\mathcal{M}\) predictors, which ones should we use in our model? Every variable we add to the model adds a bit of variability to the estimated hyper plane. Hence, having irrelevant predictors in the model is not desirable. In fact, we face a bias-variance trade-off, which we can derive more formally. The mean square error of a model is
\[ \begin{split} MSE(x) &= n^{-1} \sum\limits_{i = 1}^n \mathbb{E}[(m(x_i) - \hat{m}(x_i))^2] \\ &= n^{-1} \sum\limits_{i = 1}^n \mathbb{E}[\hat{m}(x_i) - (m(x_i) )^2] \\ \end{split} \]
Due to the fundamental law \(Var(x) = \mathbb{E}[x^2] - \mathbb{E}[x]^2\), we can rewrite this as
\[ \begin{split} MSE(x) &= n^{-1} \sum\limits_{i = 1}^n Var[\hat{m}(x_i) - m(x_i)] + n^{-1} \sum\limits_{i = 1}^n \mathbb{E}[\hat{m}(x_i) - m(x_i)]^2 \\ \end{split} \] Since \(m(x)\) is constant but unknown, it drops out of the variance expression. The bias is the expected deviation of our estimate from the true value, so \(\mathbb{E}[(\hat{m}(x_i) - m(x_i))]^2\) is the squared bias. We can plug in our the regression model for our estimator \(\hat{m}(x)\) end we end up with
\[ \begin{split} MSE(x) &= n^{-1} \sum\limits_{i = 1}^n Var[\sum\limits_{j = 1}^q \hat{\beta}_j x_{ij}] + n^{-1} \sum\limits_{i = 1}^n \mathbb{E}[\sum\limits_{j = 1}^q \hat{\beta}_j x_{ij} - m(x_i)]^2 \\ &= Var(\cdot) + bias(\cdot)^2 \end{split} \]
The bias is decreasing exponentially with growing \(q\), the variance decreases linearly. This means there will be a unique minimum.
2.9.1 Mallow’s cp statistic
The problem with the above equation is that since \(m(x)\) is unknown, there is no way we can estimate (and hence optimize) the mean squared error. However, you can estimate the mean squared error indirectly by the following quantity
\[ n^{-1} SSE(\mathcal{M}) - \hat{\sigma}^2 + 2 \hat{\sigma}^2|\mathcal{M}| / n\]
Since \(\hat{\sigma}^2\) and \(n\) are constants for each sub-model, we can also optimize the well-known cp statistic \[\mathcal{C}_p = \frac{SSE(\mathcal{M})}{\hat{\sigma}^2} - n + 2 |\mathcal{M}| \]
Hence, multiplying \(\mathcal{C}_p\) by \(\frac{\hat{\sigma}^2}{n}\), you end up again with an estimate of the mean square error.
2.9.2 Search strategies
Note that there are \(2^p-1\) possible models (every variable is in the model or not, and the empty model is not considered). You can use forward or backward search.
Forward Search
- Start with the model that contains only an intercept.
- Add the predictor variable to the model that decreases the residual sum of squares the most.
- Proceed until a large number of predictors is chosen.
- Select the model that has the lowest cp statistic.
Backward selection
- Start with the full model that contains all variables.
- Remove the variable from the model such that the residual sum of squares increases the least.
- Continue until you reached the empty model
- Among those models, select the one that has the smallest cp score.
Note that the algorithm is greedy so it is for example not possible to add a variable to the model once it has been removed in the backward selection. Also, backward selection is typically a bit better, but also way more expensive. Note that for \(p>n\), backward selection is not possible. Also, p-values are not honest anymore.


a distribution group
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Project fanta was created by 3 dudes meming during the HackTheMidlands hackathon 2019 in birmingham.
We hope you find great convenience from this simple app powered by Twilio!


Data Handling¶
Megapode uses DbUtils for it’s persistance handling. Each actor has it’s own connection, and they operate in isolation. Transaction handling is up to you. Remember what Stan Lee said...
Unlike and ORM, you will need to define and build all your database tables.
Like tasks and calculations, Data Accessors need custom interfaces to interact via their proxy.
TODO: rename
Once again, you need to annotate the Accessor class with PerstanceAccessor, implement IDataAccesor or extend PersistanceBase.
You will need to define your methods and a matching interface. Remember that you should always return a future.
The data accessor will be provided with the database connection.
Example update and data extraction that maps to the data you want to extract
// First define a bean: Comment.java
public class Comment {
Integer id;
String comment;
public Integer getId() {
return id;
}
public void setCommentId(Integer id) {
this.id = id;
}
public String getComment() {
return comment;
}
public void setComment(String comment) {
this.comment = comment;
}
}
// The interface
public interface ICommentAccessor {
Future<Integer> insert(Comment comment);
Future<List<Comment>> getComments();
}
// The implementation
@PersistanceAccessor
public class CommentAccessor extends PersistanceBase implements
IDataAccessor, IUserProfileData {
public UserProfileData(Map<Layers, ActorRef> routers,
ActorRef coordinatingActor, UntypedActorContext actorContext,
Connection connection) {
super(routers, coordinatingActor, actorContext, connection);
}
@Override
public Future<Integer> insert(Comment comment){
//TODO: Implement
}
@Override
public Future<List<Comment>> getComments(){
QueryRunner run = new QueryRunner();
ResultSetHandler<List<User>> handler = new BeanListHandler(Comment.class);
try {
List<Comment> results = run.query(this.connection,
"select * from comment, handler);
return Futures.successful(results);
} catch (SQLException e) {
return Futures.failed(e);
}
}
}
The callable then is implemented as such
ICommentAccessor commentAccess = DataAccessors.get(ICommentAccessor.class, CommentAccessor.class, this);
Future<List<Comment>> comments = commentAccess.getComments();


Curious, Resourceful, Super Awesome and Extremely Humble. I am a constant learner; always seeking out new information, new hobbies, new skills. I believe that with the right tools and enough gumption mountains can be moved and the world can be changed.


{% extends "base.html" %} {% block title %}Safespace Policy{% endblock %} {% block breadcrumb %}
The InnoGames Jam is dedicated to providing a harassment-free social experience for everyone, regardless of gender, gender identity and expression, sexual orientation, disability, physical appearance, body size, race, age, religion or game preferences. We do not tolerate harassment of participants in any form. Anyone violating these rules will be expelled from the events at the discretion of the organisers.
 Participants asked to stop any harassing behaviour are expected to comply immediately.
If a participant engages in harassing behaviour, the organisers may take any action they deem appropriate, including warning the offender or expulsion from the gamejam with no refund. If you are being harassed, notice that someone else is being harassed, or have any other concerns, please contact the event's official contact person or a member of the event staff immediately.
The staff will be happy to help participants contact security or police, provide escorts, or otherwise assist those experiencing harassment to feel safe for the duration of the event. We value your attendance.


LND SDK for Lightning Network (BTC) nodes
This is a SDK for ruby applications that can help you communicate with your Lightning Network node. There is still a lot to do before this gem can be used by others, but I will try to update it and create a stable version as soon as possible. If you would like to help, check out the Contributing section below.
Requirements
This SDK requires that you have access to the macaroon file and a tls certificate generated by your LND node. By default, these can be found at ~/.lnd/data/chain/bitcoin/mainnet/admin.macaroon
and ~/.lnd/tls.cert
.
This SDK does not work with other servers than LND. If your node is running on c-lightning, it wont work.
Installation
Add this line to your application’s Gemfile:
gem 'lnd_ruby_sdk', '~> 0.1.0'
And then execute:
$ bundle install
Or install it yourself as:
$ gem install lnd_ruby_sdk
Configuration
Here’s an example of how to configure your app. If you are using this gem with Rails, you may create a new initializer in your config/initializers
folder named lightning.rb
ruby
Lightning.configure do |config|
config.grcp_host = '<IP_ADDRESS>'
config.grcp_port = '10009'
config.macaroon_path = '~/.lnd/data/chain/bitcoin/mainnet/admin.macaroon'
config.certificate_path = '~/.lnd/tls.cert'
end
Documentation
SDK documentation and all available commands can be found at https://lnpay.github.io/lnd_ruby_sdk/Lightning.html
Development
After checking out the repo, run bin/setup
to install dependencies. Then, run rake spec
to run the tests. You can also run bin/console
for an interactive prompt that will allow you to experiment.
A good way to start would be by running rake spec
to check out the list of Pending
tests.
Progress
| Method | Added to SDK version |
|---|---|
| genseed | |
| initwallet | |
| unlockwallet | |
| changepassword | |
| walletbalance | |
| channelbalance | |
| gettransactions | |
| estimatefee | |
| sendcoins | |
| listunspent | |
| subscribetransactions | |
| sendmany | |
| newaddress | |
| signmessage | |
| verifymessage | |
| connectpeer | |
| disconnectpeer | |
| listpeers | |
| getinfo | 0.1.0 |
| pendingchannels | 0.1.1 |
| listchannels | 0.1.1 |
| subscribechannelevents | |
| closedchannels | 0.1.1 |
| openchannelsync | |
| openchannel | |
| closechannel | |
| abandonchannel | |
| sendpayment | |
| sendpaymentsync | |
| sendtoroute | |
| sendtoroutesync | |
| addinvoice | 0.1.0 |
| listinvoices | 0.1.0 |
| lookupinvoice | |
| subscribeinvoices | 0.1.1 |
| decodepayreq | 0.1.0 |
| listpayments | |
| deleteallpayments | |
| describegraph | |
| getchaninfo | |
| getnodeinfo | 0.1.1 |
| queryroutes | |
| getnetworkinfo | 0.1.1 |
| stopdaemon | |
| subscribechannelgraph | |
| debuglevel | |
| feereport | |
| updatechannelpolicy | |
| forwardinghistory | |
| exportchannelbackup | |
| exportallchannelbackups | |
| verifychanbackup | |
| restorechannelbackups | |
| subscribechannelbackups |
Contributing
Bug reports and pull requests are welcome on GitHub at https://github.com/lnpay/lnd_ruby_sdk.
License
The gem is available as open source under the terms of the MIT License.


Home
my favorite Youtubers
For your Enjoyment. (will be updated occasionally)
Other
Arthur Arcturus
ItsBlitzzz
Luke Smith
Practical Engineering
Real Engineering
Yuttadhammo Bhikku
Thinking Ape
YMDRP
Nessa Elessar
OurChangingClimate
Arthur Moore
Study Tube
Study Vibes
(Personality-) Psychology
Casual Cognition
Wounded Healer (INFJ)
Love Who (INTP)
superseniorsydney (INTP)
Programming
Cave of Programming
Ben Awad
Ben Eater
Computerphile
Context Free
Errichto
Frederico Tomassetti
Jonathan Blow
LLVM
Marco Steinke
The Linux Channel
Tutorial Linux
TechLead
MentalOutlaw
Quantic Dev
C Programming
Jacob Sorber
Eric O Meehan
Math
blackpenredpen
BootsToBooks
BriTheMathGuy
DorFuchs
Dr Peyam
einfach Mathe
Epic Math Time
Fematika
Flammable Maths
Flo's Study Diary
MasterWuMathematics
Mathe by Daniel Jung
Mathe-Seite
Mathematiqua
Mathe Peter
Michael Penn
Numberphile
standupmaths
Wolfgang Schmid
The Math Sorcerer


Class: Aws::CodeCommit::Types::PostCommentForPullRequestInput
| Relationships & Source Files | |
| Super Chains via Extension / Inclusion / Inheritance | |
|
Class Chain:
self,
Struct
|
|
|
Instance Chain:
self,
::Aws::Structure ,
Struct
|
|
| Inherits: |
Struct
|
| Defined in: | gems/aws-sdk-codecommit/lib/aws-sdk-codecommit/types.rb |
Overview
Constant Summary
Instance Attribute Summary
-
#after_commit_id ⇒ String
rw
The full commit ID of the commit in the source branch that is the current tip of the branch for the pull request when you post the comment.
-
#before_commit_id ⇒ String
rw
The full commit ID of the commit in the destination branch that was the tip of the branch at the time the pull request was created.
-
#client_request_token ⇒ String
rw
A unique, client-generated idempotency token that, when provided in a request, ensures the request cannot be repeated with a changed parameter.
-
#content ⇒ String
rw
The content of your comment on the change.
-
#location ⇒ Types::Location
rw
The location of the change where you want to post your comment.
-
#pull_request_id ⇒ String
rw
The system-generated ID of the pull request.
-
#repository_name ⇒ String
rw
The name of the repository where you want to post a comment on a pull request.
Instance Method Summary
::Aws::Structure
- Included
| #to_hash | Alias for Structure#to_h. |
Instance Attribute Details
#after_commit_id ⇒ String
(rw)
The full commit ID of the commit in the source branch that is the current tip of the branch for the pull request when you post the comment.
# File 'gems/aws-sdk-codecommit/lib/aws-sdk-codecommit/types.rb', line 5261
class PostCommentForPullRequestInput < Struct.new( :pull_request_id, :repository_name, :before_commit_id, :after_commit_id, :location, :content, :client_request_token) SENSITIVE = [] include Aws::Structure end
#before_commit_id ⇒ String
(rw)
The full commit ID of the commit in the destination branch that was the tip of the branch at the time the pull request was created.
# File 'gems/aws-sdk-codecommit/lib/aws-sdk-codecommit/types.rb', line 5261
class PostCommentForPullRequestInput < Struct.new( :pull_request_id, :repository_name, :before_commit_id, :after_commit_id, :location, :content, :client_request_token) SENSITIVE = [] include Aws::Structure end
#client_request_token ⇒ String
(rw)
A unique, client-generated idempotency token that, when provided in a request, ensures the request cannot be repeated with a changed parameter. If a request is received with the same parameters and a token is included, the request returns information about the initial request that used that token.
A suitable default value is auto-generated. You should normally not need to pass this option.
# File 'gems/aws-sdk-codecommit/lib/aws-sdk-codecommit/types.rb', line 5261
class PostCommentForPullRequestInput < Struct.new( :pull_request_id, :repository_name, :before_commit_id, :after_commit_id, :location, :content, :client_request_token) SENSITIVE = [] include Aws::Structure end
#content ⇒ String
(rw)
The content of your comment on the change.
# File 'gems/aws-sdk-codecommit/lib/aws-sdk-codecommit/types.rb', line 5261
class PostCommentForPullRequestInput < Struct.new( :pull_request_id, :repository_name, :before_commit_id, :after_commit_id, :location, :content, :client_request_token) SENSITIVE = [] include Aws::Structure end
#location ⇒ Types::Location (rw)
The location of the change where you want to post your comment. If no location is provided, the comment is posted as a general comment on the pull request difference between the before commit ID and the after commit ID.
# File 'gems/aws-sdk-codecommit/lib/aws-sdk-codecommit/types.rb', line 5261
class PostCommentForPullRequestInput < Struct.new( :pull_request_id, :repository_name, :before_commit_id, :after_commit_id, :location, :content, :client_request_token) SENSITIVE = [] include Aws::Structure end
#pull_request_id ⇒ String
(rw)
The system-generated ID of the pull request. To get this ID, use ListPullRequests.
# File 'gems/aws-sdk-codecommit/lib/aws-sdk-codecommit/types.rb', line 5261
class PostCommentForPullRequestInput < Struct.new( :pull_request_id, :repository_name, :before_commit_id, :after_commit_id, :location, :content, :client_request_token) SENSITIVE = [] include Aws::Structure end
#repository_name ⇒ String
(rw)
The name of the repository where you want to post a comment on a pull request.
# File 'gems/aws-sdk-codecommit/lib/aws-sdk-codecommit/types.rb', line 5261
class PostCommentForPullRequestInput < Struct.new( :pull_request_id, :repository_name, :before_commit_id, :after_commit_id, :location, :content, :client_request_token) SENSITIVE = [] include Aws::Structure end


Table
File name
Location
Modified
Type
File name
Location
Modified
Type
File name
Location
Modified
Type
File name
Location
Modified
Type
File name
Location
Modified
Type
File name
Location
Modified
Type


In the HTML / CSS, create three boxes, each with identical initial style.
Include jQuery via Google CDN, or downloading it and linking it locally.
Creat your own Javascript file and use jQuery to change the color, inner text, and default style of two of the boxes.
Clicking on any box hides that specific box from the user.


--- layout: post title: '30 Days in April: Day 13' date: 2009-04-13 22:27:40.000000000 -07:00 type: post published: true status: publish categories: - 30 Days in April tags: [] meta: _publicize_pending: '1' _edit_last: '6192' aktt_tweeted: '1' original_post_id: '166' _wp_old_slug: '166' author: login: falsefridays email<EMAIL_ADDRESS>display_name: Jim Withington first_name: '' last_name: '' ---
Click on the image to see it without distortion caused by my wordpress theme.
Props to Nate for showing me this site a while back.
Un-props to strip generator for not letting me login under my first login simply because I didn't verify it when I first signed up.


The OHMEC project has a goal to create an open geographical database of historical representation of political boundaries. This demonstration shows a simple rendering of data in the North American arena. A full featured rendering would require tiling from the database indexed with time and geography.
The OHMEC project is being developed in a Github repository. Participation is welcome, see that repo for more information on the state of the project.
A rendering of the current state of the project is reflected at our Website.


{% extends "base.html" %} {% block pageHeader %} Delete Topic: {{topic.topic}} {% endblock %} {% block instructions %} Are you sure that you want to delete this topic? {% endblock %} {% block form %}
{% endblock %} {% block content %} Return to home page {% endblock %}


Python is an interpreted high-level general-purpose programming language. Its design philosophy emphasizes code readability with its use of significant indentation.
 The various dialects of shell scripts are considered to be scripting languages.
C++ is a general-purpose programming language created by Bjarne Stroustrup as an extension of the C programming language, or "C with Classes".


{% extends "layout.html" %} {% block page_title %} GOV.UK prototype kit {% endblock %} {% block content %} {% include "includes/phase_banner_beta.html" %} Request unlock code Enter your email address to get an unlock code. email address Email {% endblock %}
Enter your email address to get an unlock code.


Responsiveness in CI
I not saying that the Responsiveness of the system isn't fit for purpose - but maybe its not.
- we haven't done any testing with real users
- we don't have any devices
- thats been ok to date but Patient recorded forms means it has to actually work properly
- there is an overlap with the other projects that suggests what we do for SmartCare might be useful for CTF and INPDR
Other projects
- I would like to have the compiler create a 2nd version of the form with clean markup for single column layouts - just slapping some more hacked style is never going to work well
- And a clean stylesheet so I can reverse the colours out and give the user options to make the UI work for them
- And present the questions one by one on suitable forms
That would suggest that we style (for example) radio buttons to be resizeable, change colour and remain readable to screen readers
- Bootsrap 3 was released in 2013 and worked finished on it in 2016. I could get a 5 year old plugin to replace the radio buttons and allow them to change colour, but they aren't going to be accessible.
Bootstrap 5 is being released this year
- BootstrapVue does this out of the box
- There is a real chance we are just going to dump more technical debt on put of technical debt and end up supporting poor solutions
This the markup that is most accessible to screen reader - radio buttons wrapped in a fieldset, one label per button and associated with
This is our markup today - orphan label,
Clinical Insight Solutions
WCAG 2.0 has 3 levels of adherence. 'A' is the easiest to pass but even Angular UI and Bootstrap 3 both fail.
We have a challenge with the progressive disclosure fields
Image uploads before saving
Validation is invoked on page loading not Touch
Colours - check colour blind (rag)
Font sizes + Margins - bumping these up could cause issues with the Form layouts and we will see less on screen
Provide better alt tags
Require better format on tables
Useability
Cleaned down interface for Patient Portal which allows us to have a much cleaner and lighter UI tailored for devices likely to be used by Patients.
This should be built from the ground up rather than be version of our standard interface with bits switched off/styled out.
Responsiveness
What our applications do?
CFView resizes down to Tablet size with retracting menu.
Phone app responds to different sizes.
Responsive is difficult
We need to design and plan better before we code
We need to accept that elements are flexible


Gallery
Members
President
Rosemary Ingwersen
11B
Vice-President
Rachel Beattie
11B
Secretary
Mikayla Nicolson
10M
Treasurer
Nate Mitchell
10M
Noor Al-Assafi
10N
Ewan Breakey
10M
Emily Davidson
8M
Bérénice Duchemin
12B
Brodey Hamilton
12N
Giorgia Hinkley
10M
Tamika Hodge
11B
Hannah Hunt
11B
Asha James
8M
William Jones
7S
Rhys Morgans
10M
Sam Nolan
11B
Emily Ruge
10M
Ricky Wang
10M
Members
President
Rosemary Ingwersen
11B
Vice-President
Rachel Beattie
11B
Secretary
Mikayla Nicolson
10M
Treasurer
Nate Mitchell
10M
Noor Al-Assafi
10N
Ewan Breakey
10M
Emily Davidson
8M
Bérénice Duchemin
12B
Brodey Hamilton
12N
Giorgia Hinkley
10M
Tamika Hodge
11B
Hannah Hunt
11B
Asha James
8M
William Jones
7S
Rhys Morgans
10M
Sam Nolan
11B
Emily Ruge
10M
Ricky Wang
10M


To allow you to visualize the relationships between data and its different visualizations, d3ng allows you to connect individual simple visualizations via user interactions. D3ng uses selections and selection groups to connect different representations of the same data-points. This kind of visual analysis task is known as brushing and linking.
D3ng support 4 different types of possible chart combinations, each employing brushing and linking in a different manner.


News
- We have work ongoing for the next generation WULF. That we have labeled as OT4.0 and it introduces the approved OT2016 style changes.
- Work is starting for Angular 2 support in November.
DRAFT statement in component means that it is not yet ready (under
construction
still). It is possible for you to use such component, but please note that it can change still - a lot
even.
If the draft statement appears in the component header, that whole component is draft. If there are
draft
statements inside the component, then only those sub-parts are draft.
Contact the developers by sending e-mail to: WULF
development team
<EMAIL_ADDRESS>or
WULF user mail list
(nokia-wulf-user@mlist.emea.nsn-intra.net).


11 Keto Dishes, Sides, and Desserts You'll Want to Serve Up This Thanksgiving
by Hajar LarbahThere's almost no getting around a bit of overindulgence on Thanksgiving — but if you're on the keto diet, you don't have to risk knocking yourself out of ketosis. (After all, you worked so hard to get there.) From low-carb stuffing and sugar-free cranberry sauce to veggie-filled mac and cheese and even mashed "potatoes," this menu will help you serve up all your holiday classics while still sticking to your regimen. The best part? We're willing to bet your family and friends won't even notice that your recipes have changed. Settle in — you're going to want to savor every last bite.
1 Easy Herb-Roasted Thanksgiving Turkey
It isn't Thanksgiving without a turkey front and center. This recipe is juicy, flavorful, packed with tons of herbs, and roasted to crispy perfection.
Get the recipe: easy herb-roasted Thanksgiving turkey
2 Cauliflower and Turkey Stuffing
This stuffing is seasoned so perfectly, your family won't even notice it's made with keto-friendly cauliflower instead of carb-y bread.
Get the recipe: cauliflower and turkey stuffing
3 Paleo Gravy
Gravy is a must, and this recipe — made with turkey drippings, stock, and tapioca starch — will only set you back 15 minutes.
Get the recipe: Paleo gravy
4 Sugar-Free Cranberry Sauce
Give your dinner a burst of flavor with this sweet side. All you need are some cranberries, orange zest, and your favorite keto-friendly sweetener.
Get the recipe: sugar-free cranberry sauce
5 Creamy Parmesan Mashed Cauliflower
This recipe for mashed cauliflower is so smooth and cheesy and the perfect low-carb alternative to mashed potatoes.
Get the recipe: creamy parmesan mashed cauliflower
6 Slow-Cooker Green Bean Casserole
Just substitute almond flour for all-purpose flour in this deliciously rich sauce, and go easy on the fried onions. Making them from scratch can help you avoid any unnecessary carbs.
Get the recipe: slow-cooker green bean casserole
7 Sautéed Brussels Sprouts With Mustard and Hazelnuts
This tangy, crunchy take on brussels sprouts will please even the pickiest eaters.
Get the recipe: sautéed brussels sprouts with mustard and hazelnuts
8 Low-Carb Biscuits With Almond Flour
It's hard to believe, but these cheddar and bacon biscuits are only two net grams of carbs per serving. For that, you can thank keto-approved almond flour.
Get the recipe: low-carb biscuits with almond flour
9 Gluten-Free No-Mac and Cheese
This pasta-less recipe is just as irresistible as the classic version. Each serving is just under 400 calories, and thanks to cauliflower and coconut milk, it doesn't pile on the carbs.
Get the recipe: cauliflower mac and cheese
10 Low-Carb Pumpkin Pie
With an almond flour crust and sugar-free filling, this is one dessert you'll be happy to have occupy your fridge for days after Thanksgiving has passed. Top it with whipped cream for an extra delicious bite.
Get the recipe: Paleo low-carb sugar free pumpkin pie
11 Caramel Pecan Cookies
These delicious cookies deliver the same flavor as a traditional pecan pie but with only three grams of net carbs.
Get the recipe: chewy keto pecan cookies


Today's Blog
On April 28, Workers’ Memorial Day, at the reported urging of Tyson Foods, President Trump invoked the Defense Production Act (DPA) with the stated goal of keeping meat processing (slaughterhouses) open through the COVID-19 crisis. In doing so, the President is attempting to trample over state decisions intended to improve worker safety while responding to outbreaks of COVID-19 at many slaughterhouses. Click to Read more...
The President made clear in remarks that the primary aim of the order was to insulate the food giant from liability, not ensure the safety of the food supplies or the workers who produce it. Adding insult to injury, this comes as calls to use the DPA to ensure health workers have access to adequate personal protective equipment (PPE) go unheeded. These actions are callous and dangerous. The top COVID-19 hotspots nationwide are all linked to slaughterhouses with active outbreaks, and there are currently 6,500 slaughterhouse workers with COVID infections or exposure across the nation’s 6,200 facilities. Even in this dangerous sector where workers go to work every day knowing that they face high rates of severe injuries and harsh conditions, workers have been staying home, fearing for their lives; some are walking out protesting this order and related commitments to keep plants open at all costs. Forcing plants to stay open without mandating adequate safety measures is not only dangerous, it also undermines the efforts of localities to force companies to look out for the basic safety of workers. Simply put: If companies like Tyson, JBS, and Smithfield are not ready to be responsible for the bare minimum of worker safety, then they are not ready to reopen. Our government has a responsibility to make sure that workers—especially those deemed essential or required to work—are protected.
The Keystone XL tar sands pipeline got knocked down again this week when a federal judge invalidated Nationwide Permit 12, a key water-crossing permit issued by the U.S. Army Corps of Engineers and used by Keystone XL as well as many other pipeline projects. The permit has been routinely used to help pipelines avoid thorough environmental reviews and fast-track their approval process. Click to Read more...
“The Trump administration’s ongoing effort to give out goodies to Big Oil hit another setback,” says NRDC attorney Cecilia Segal. “Whether they like it or not, the Corps cannot skirt foundational environmental laws.” Challenged by a coalition of conservation and landowner groups, including NRDC, Nationwide Permit 12 allowed the Army Corps to avoid fully assessing the impacts of pipelines on local waterways, lands, wildlife, and communities. The court’s ruling now prohibits the agency from using this permit for pipelines nationwide and could block the construction of Keystone XL across hundreds of water crossings. “Projects like the Keystone XL tar sands pipeline will remain stalled as long as the administration keeps trying to illegally fast-track them,” Segal says. TC Energy’s Keystone XL has now been the center of a ping-ponging legal and legislative battle for more than a decade. The proposed pipeline would carry 830 million barrels of tar sands oil per day from Canada to oil refineries on the Gulf Coast. In addition to threatening water, wildlife, and public health along its route, the fossil fuel infrastructure would also lock in more climate-devastating carbon pollution. President Obama agreed the risks were too high and vetoed the project in 2015, but President Trump revived it soon after taking office. His administration has since made numerous attempts to fast-track its approval, and the government of Alberta, Canada, announced just last month that it would invest billions to help the long-delayed project move forward with construction on the U.S.-Canada border as early as this spring. But the latest courtroom win now bolsters the continuing fight by Indigeneous groups, conservationists, and landowners along the pipeline’s route to block its construction.
As hurricane season looms especially large this year, and COVID-19 reveals the deep cracks and fissures in our nation’s response preparedness, North Carolina is gearing up to release its long-awaited plan to bolster climate resilience. The state’s “Climate Risk Assessment and Resilience Plan” is expected to outline a comprehensive strategy to help North Carolina stay ahead of the ever-escalating climate crisis. It can’t come soon enough. Click to Read more...
But publishing a plan does not automatically equate to implementing a plan. The success of North Carolina’s resilience plan will ultimately be determined by the steps Governor Roy Cooper, the legislature, and state’s agencies take to implement the recommendations. That takes leadership and a firm directive from on high that climate resilience is a priority for the state—a mandate that Governor Cooper has fortunately made abundantly clear. When the Governor signed Executive Order 80 in October 2018 he instructed state agencies to integrate climate adaptation and resiliency planning into their policies, programs, and operations, recognizing that the climate crisis touches nearly every aspect of government planning and decision-making. In another major step forward, the Governor called for the state to develop a resilience plan. Eighteen months later, much now hinges on the effectiveness and implementation of that plan. At its core, the resilience plan should feature two bedrock components that future climate efforts can further build upon. Assess the Climate Risks and Prepare for Future Climate Impacts A climate risk assessment should identify vulnerable infrastructure assets, communities that have the most vulnerable housing stock, public safety facilities located in harm’s way and a host of other much-needed information. Such an assessment could be developed by drawing on the recently completed North Carolina Climate Science Report.


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Interface for HIR alias analysis. All future alias analysis classes will implement this interface.
The query interfaces mayAlias, mustAlais, and getAliasGroupFor
all deal with lvalues. An lvalue is an HIR node that is
associated with an object, and its operator code
(see {Link coins.ir.hir.HIR#getOperator}) is one
of HIR.OP_VAR
, HIR.OP_SUBS
,
HIR.OP_QUAL
, HIR.OP_ARROW
,
HIR.OP_CONTENTS
, and HIR.OP_UNDECAY
.
HIR nodes with the operator code HIR.OP_SUBS or HIR.OP_QUAL,
however, are lvalue only when their first child
(specified by {Link coins.ir.hir.SubscriptedExp#getArrayExp}
and {Link coins.ir.hir.Exp#getQualifierExp}, respectively)
is lvalue. To see if an Exp node is lvalue, the isLvalue
method may be used.
| Field Summary | |
static java.lang.String |
CATEGORY_NAME
The category name of the alias analysis package. |
| Method Summary | |
AliasGroup |
getAliasGroupFor(Exp pExp)
Returns the set of lvalue nodes that are possibly aliased ( mayAlias ) to the specified argument. |
boolean |
isLvalue(Exp pExp)
Returns true if the specified argument is considered lvalue in this alias analysis. |
boolean |
mayAlias(Exp pExp,
Exp pExp0)
Returns true if the two arguments may
refer to an overlapping area in memory. |
boolean |
mustAlias(Exp pExp,
Exp pExp0)
Returns true if the two arguments
definitely refer to an overlapping area in memory. |
void |
prepareForAliasAnalHir(SubpDefinition pSubpDef)
Performs alias analysis for the given argument. |
void |
printAliasPairs(SubpDefinition pSubpDef)
Prints out alias pairs in IoRoot.printOut object. |
| Field Detail |
public static final java.lang.String CATEGORY_NAME
Alias
". Used in debug-tracing.
| Method Detail |
public void prepareForAliasAnalHir(SubpDefinition pSubpDef)
Performs alias analysis for the given argument. After calling this method, the alias analysis object (object that implements this interface) is ready to accept the queries (mayAlias etc.) for the specified argument.
For intraprocedural analyses only (so far).
pSubpDef
- the SubpDefinition
instance
nodes belonging to which are to be analyzed for aliasing.public boolean isLvalue(Exp pExp)
public boolean mayAlias(Exp pExp, Exp pExp0)
true
if the two arguments may
refer to an overlapping area in memory. The two arguments
both must be contained in the SubpDefinition
which was analyzed most recently by this analysis instance.
pExp
- lvalue node to check for aliasing.pExp0
- lvalue node to check for aliasing.
java.lang.IllegalArgumentException
- if either of the arguments
is not lvalue.public boolean mustAlias(Exp pExp, Exp pExp0)
true
if the two arguments
definitely refer to an overlapping area in memory.
The two arguments both must be contained in the
SubpDefinition
which was analyzed most
recently by this analysis instance.
pExp
- lvalue node to check for aliasing.pExp0
- lvalue node to check for aliasing.
java.lang.IllegalArgumentException
- if either of the
arguments is not lvalue.public AliasGroup getAliasGroupFor(Exp pExp)
mayAlias
) to the specified argument.
The argument must be contained in the
SubpDefinition
which was analyzed most recently
by this analysis instance.
pExp
- lvalue node to check for aliasing.
java.lang.IllegalArgumentException
- if the argument
is not lvalue.
See #mayAliaspublic void printAliasPairs(SubpDefinition pSubpDef)
IoRoot.printOut
object.
For debugging.
pSubpDef
- the SubpDefinition
object for
which alias pairs will be printed.
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Memory management of http passthrough service has been improved. This will avoid out of memory issues which can be caused with high number connections.


An interface to 'GNU gretl': running 'gretl' scripts from, estimating econometric models with backward passing of model results, opening 'gretl' data files (.gdt). 'gretl' can be downloaded from <http://gretl.sourceforge.net>. This package could make life on introductory/intermediate econometrics courses much easier: full battery of the required regression diagnostics, including White's heteroskedasticity test, restricted ols estimation, advanced weak instrument test after iv estimation, very convenient dealing with lagged variables in models, standard case treatment in unit root tests, vector auto- regressions, and vector error correction models. Datasets for 8 popular econometrics textbooks can be installed into 'gretl' from its server. All datasets can be easily imported using this package.
| Version: | 0.2.2 |
| Depends: | R (≥ 3.4.0) |
| Imports: | compiler, lubridate, png, xml2 |
| Published: | 2018-03-18 |
| Author: | Oleh Komashko |
| Maintainer: | Oleh Komashko <oleg_komashko at ukr.net> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| SystemRequirements: | gretl (>= 2017c), gretlcli |
| Materials: | README NEWS |
| CRAN checks: | Rgretl results |
| Reference manual: | Rgretl.pdf |
| Package source: | Rgretl_0.2.2.tar.gz |
| Windows binaries: | r-devel: Rgretl_0.2.2.zip, r-release: Rgretl_0.2.2.zip, r-oldrel: Rgretl_0.2.2.zip |
| OS X binaries: | r-release: Rgretl_0.2.2.tgz, r-oldrel: Rgretl_0.1.6.tgz |
| Old sources: | Rgretl archive |
Please use the canonical form https://CRAN.R-project.org/package=Rgretl to link to this page.


#822 p_sion
passion
pension
percussion
persuasion
perversion
possession
precession
precision
pretension
procession
profession
profusion
progression
propulsion
protrusion
provision


WordNet is a semantic lexicon for the English language that computational linguists and cognitive scientists use extensively. For example, WordNet was a key component in IBM’s Jeopardy-playing Watson computer system. WordNet groups words into sets of synonyms called synsets. For example, { AND circuit, AND gate } is a synset that represent a logical gate that fires only when all of its inputs fire. WordNet also describes semantic relationships between synsets. One such relationship is the is-a relationship, which connects a hyponym (more specific synset) to a hypernym (more general synset). For example, the synset { gate, logic gate } is a hypernym of { AND circuit, AND gate } because an AND gate is a kind of logic gate.
The WordNet digraph. Your first task is to build the WordNet digraph: each vertex v is an integer that represents a synset, and each directed edge v→w represents that w is a hypernym of v. The WordNet digraph is a rooted DAG: it is acyclic and has one vertex—the root—that is an ancestor of every other vertex. However, it is not necessarily a tree because a synset can have more than one hypernym. A small subgraph of the WordNet digraph appears below.
The WordNet input file formats. We now describe the two data files that you will use to create the WordNet digraph. The files are in comma-separated values (CSV) format: each line contains a sequence of fields, separated by commas.
For example, line 36 means that the synset {
AND_circuit
, AND_gate
}
has an id number of 36 and its gloss is
a circuit in a computer that fires only when all of its inputs fire
.
The individual nouns that constitute a synset are separated by spaces.
If a noun contains more than one word, the underscore character connects
the words (and not the space character).
For example, line 36 means that synset 36 (
AND_circuit AND_Gate
)
has 42338 (gate logic_gate
) as its only hypernym. Line 34 means that
synset 34 (AIDS acquired_immune_deficiency_syndrome
) has two hypernyms:
47569 (immunodeficiency
) and 48084 (infectious_disease
).
WordNet data type.
Implement an immutable data type WordNet
with the following API:
Corner cases. Throw anpublic class WordNet { // constructor takes the name of the two input files public WordNet(String synsets, String hypernyms) // returns all WordNet nouns public Iterable<String> nouns() // is the word a WordNet noun? public boolean isNoun(String word) // distance between nounA and nounB (defined below) public int distance(String nounA, String nounB) // a synset (second field of synsets.txt) that is the common ancestor of nounA and nounB // in a shortest ancestral path (defined below) public String sap(String nounA, String nounB) // do unit testing of this class public static void main(String[] args) }
IllegalArgumentException
in the following situations:
null
distance()
or sap()
is not a WordNet noun.
Performance requirements.
Your data type should use space linear in the input size
(size of synsets and hypernyms files).
The constructor should take time linearithmic (or better) in the input size.
The method isNoun()
should run in time logarithmic (or better) in
the number of nouns.
The methods distance()
and sap()
should run in time linear in the
size of the WordNet digraph.
For the analysis, assume that the number of nouns per synset
is bounded by a constant.
Shortest ancestral path. An ancestral path between two vertices v and w in a digraph is a directed path from v to a common ancestor x, together with a directed path from w to the same ancestor x. A shortest ancestral path is an ancestral path of minimum total length. We refer to the common ancestor in a shortest ancestral path as a shortest common ancestor. Note also that an ancestral path is a path, but not a directed path.
We generalize the notion of shortest common ancestor to subsets of vertices. A shortest ancestral path of two subsets of vertices A and B is a shortest ancestral path over all pairs of vertices v and w, with v in A and w in B. The figure (digraph25.txt) below shows an example in which, for two subsets, red and blue, we have computed several (but not all) ancestral paths, including the shortest one.
SAP data type.
Implement an immutable data type SAP
with the following API:
public class SAP { // constructor takes a digraph (not necessarily a DAG) public SAP(Digraph G) // length of shortest ancestral path between v and w; -1 if no such path public int length(int v, int w) // a common ancestor of v and w that participates in a shortest ancestral path; -1 if no such path public int ancestor(int v, int w) // length of shortest ancestral path between any vertex in v and any vertex in w; -1 if no such path public int length(Iterable<Integer> v, Iterable<Integer> w) // a common ancestor that participates in shortest ancestral path; -1 if no such path public int ancestor(Iterable<Integer> v, Iterable<Integer> w) // do unit testing of this class public static void main(String[] args) }
Corner cases.
Throw an IllegalArgumentException
in the following situations:
null
null
item
Performance requirements. All methods (and the constructor) should take time at most proportional to E + V in the worst case, where E and V are the number of edges and vertices in the digraph, respectively. Your data type should use space proportional to E + V.
Test client. The following test client takes the name of a digraph input file as as a command-line argument, constructs the digraph, reads in vertex pairs from standard input, and prints out the length of the shortest ancestral path between the two vertices and a common ancestor that participates in that path:
Here is a sample execution:public static void main(String[] args) { In in = new In(args[0]); Digraph G = new Digraph(in); SAP sap = new SAP(G); while (!StdIn.isEmpty()) { int v = StdIn.readInt(); int w = StdIn.readInt(); int length = sap.length(v, w); int ancestor = sap.ancestor(v, w); StdOut.printf("length = %d, ancestor = %d\n", length, ancestor); } }
% cat digraph1.txt % java-algs4 SAP digraph1.txt 13 3 11 11 length = 4, ancestor = 1 7 3 8 3 9 12 3 1 length = 3, ancestor = 5 4 1 5 1 7 2 9 5 length = 4, ancestor = 0 10 5 11 10 1 6 12 10 length = -1, ancestor = -1 1 0 2 0
Measuring the semantic relatedness of two nouns. Semantic relatedness refers to the degree to which two concepts are related. Measuring semantic relatedness is a challenging problem. For example, you consider George W. Bush and John F. Kennedy (two U.S. presidents) to be more closely related than George W. Bush and chimpanzee (two primates). It might not be clear whether George W. Bush and Eric Arthur Blair are more related than two arbitrary people. However, both George W. Bush and Eric Arthur Blair (a.k.a. George Orwell) are famous communicators and, therefore, closely related.
We define the semantic relatedness of two WordNet nouns x and y as follows:
This is the notion of distance that you will use to implement the
distance()
and sap()
methods in the WordNet
data type.
Outcast detection. Given a list of WordNet nouns x1, x2, ..., xn, which noun is the least related to the others? To identify an outcast, compute the sum of the distances between each noun and every other one:
di = distance(xi, x1) + distance(xi, x2) + ... + distance(xi, xn)and return a noun xt for which dt is maximum. Note that distance(xi, xi) = 0, so it will not contribute to the sum.
Implement an immutable data type Outcast
with the following API:
Assume that argument topublic class Outcast { public Outcast(WordNet wordnet) // constructor takes a WordNet object public String outcast(String[] nouns) // given an array of WordNet nouns, return an outcast public static void main(String[] args) // see test client below }
outcast()
contains only valid wordnet
nouns (and that it contains at least two such nouns).
The following test client takes from the command line the name of a synset file, the name of a hypernym file, followed by the names of outcast files, and prints out an outcast in each file:
Here is a sample execution:public static void main(String[] args) { WordNet wordnet = new WordNet(args[0], args[1]); Outcast outcast = new Outcast(wordnet); for (int t = 2; t < args.length; t++) { In in = new In(args[t]); String[] nouns = in.readAllStrings(); StdOut.println(args[t] + ": " + outcast.outcast(nouns)); } }
% cat outcast5.txt horse zebra cat bear table % cat outcast8.txt water soda bed orange_juice milk apple_juice tea coffee % cat outcast11.txt apple pear peach banana lime lemon blueberry strawberry mango watermelon potato % java-algs4 Outcast synsets.txt hypernyms.txt outcast5.txt outcast8.txt outcast11.txt outcast5.txt: table outcast8.txt: bed outcast11.txt: potato
Analysis of running time (optional). Analyze the effectiveness of your approach to this problem by giving estimates of its time requirements.
length()
and ancestor()
methods
in SAP
as a function of the number of
vertices V and the number of edges E in the digraph.
Web submission.
Submit a .zip file containing
WordNet.java
, SAP.java
, Outcast.java
,
any other supporting files (excluding algs4.jar
).
You may not call any library functions except those in
java.lang
, java.util
, and algs4.jar
.