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General election: More than 35,000 people to vote by post in Telford and Wrekin
by Mat GrowcottAlmost a third of voters across Telford & Wrekin will vote by post in December's election.
More than 35,000 people across the two constituencies have chosen to use a postal vote ahead of December 12.
And those still interested in voting have until Tuesday to register.
Jonathan Eatough, acting returning officer at Telford & Wrekin Council, said: “It’s really quick and straightforward to apply for a postal vote.
"If you’re away on business, on holiday or just have other commitments that mean you can’t get to your nearest polling station between 7am and 10pm on December 12, there’s no reason you have to miss out on having your say on who represents you.
“There’s nothing to stop anyone in the borough from having their say on December 12.”
Visit gov.uk/register-to-vote to register to vote in the upcoming election.
Paper application forms are available also available from councils on request for anybody without internet access.


WITNESS LIST Business & Commerce Committee May 3, 2001 - 8:00A HB 409 FOR: Risk, Raymond (Tx Construction Association), Austin, TX HB 430 Registering, but not testifying: For: Owen, Robert (Tx Society of CPAs), DeSoto, TX On: Treacy, William (Tx State Board Public Accountancy), Austin, TX HB 471 FOR: Looney, Gary R. (Tx Association of Health Underwriters), San Antonio, TX Parker, Becky (Self), Austin, TX AGAINST: Pollard, Mike (Tx Association of Life and Health Insurers), Austin, TX Registering, but not testifying: For: Glenn, Eric (Humana), Austin, TX Manross, Lee (Tx Association of Health Underwriters), Austin, TX McCandless, Pati (Unicare Life and Health Insurance Co), Austin, TX Tooley, Ken (Tx Association of Insurance and Financial Advisors), Austin, TX Against: Davis, Will D. (Tx Association of Life and Health Insurers), Austin, TX Hill, Holli (Health Insurance Association of America), Austin, TX HB 533 Registering, but not testifying: For: Daly, Richard (Tx Catholic Conference), Austin, TX Lavine, Dick (Center for Public Policy Priorities), Austin, TX Levy, Rick (Tx AFL-CIO), Austin, TX HB 606 FOR: Moy, Julie Graves (Tx Academy of Family Physicians), Austin, TX Registering, but not testifying: For: Banning, Tom (Tx Academy of Family Physicians), Austin, TX Barron, Connie (Tx Medical Association), Austin, TX Gagen, Joe (Tx 5.01(a) Alliance), Austin, TX Oates, John (AETNA), Austin, TX Phipps, Candie (Tx Pediatric Society), Austin, TX Samuels, Marc (Tx Society of Internal Medicine), Austin, TX On: Brodersen, Blake O. (Tx Department of Insurance), Austin, TX HB 688 FOR: Beck, Sister Lauren (Incarnate Word Academy), Houston, TX Nadolney, Carmen D. (Incarnate Word Academy), Houston, TX Registering, but not testifying: For: Bibler, Paul (City of Houston), Houston, TX Daly, Richard (Tx Catholic Conference), Austin, TX Nadolney, Frank E. (Incarnate Word Academy), Houston, TX Schwartz, A. R. (Self), Austin, TX On: Bright, Lou (Tx Alcoholic Beverage Commission), Austin, TX HB 845 FOR: Hunt, Terrell (Self), Houston, TX Zimmerman, Toby (Self), Austin, TX ON: de la Pena, Patricia M. (Tx Department of Insurance), Austin, TX Registering, but not testifying: For: Fuelberg, Curtis (American Jewish Committee), Austin, TX HB 1216 Registering, but not testifying: On: Kuntz, Jr, William H. (Tx Department of Licensing and Regulation), Austin, TX HB 1493 Registering, but not testifying: For: Rudd, Jim (Tx Association of Mortgage Brokers), Austin, TX Stinson, Bill (Tx Association of Realtors), Austin, TX On: Pledger, Jim (Tx Savings and Loan Department), Austin, TX HB 1636 Registering, but not testifying: For: Rudd, Jim (Tx Association of Mortgage Brokers), Austin, TX Sandberg, Eric (Tx Savings and Community Bankers Association), Austin, TX On: Mazur, Jeremy (Sunset Commission), Austin, TX Pledger, Jim (Tx Savings and Loan Department), Austin, TX HB 1684 FOR: DeLeon, Hector (Service Life and Casualty Insurance Co.), Austin, TX Pollard, Mike (Tx Association of Life and Health Insurers), Austin, TX AGAINST: Schneider, Rob (Consumers Union), Austin, TX ON: Durden, David (Tx Department of Insurance), Austin, TX Registering, but not testifying: For: Davis, Will D. (Tx Association of Life and Health Insurers), Austin, TX On: Pettijohn, Leslie (Consumer Credit Commissioner), Austin, TX HB 1703 FOR: Shivers, Marc (Exxon/Mobil), Austin, TX Registering, but not testifying: On: Brady, Kevin (Tx Department of Insurance), Austin, TX HB 1862 FOR: Howell, Bruce F. (Medical Select Management), Dallas, TX Miller, Frederick (Medical Pathways Management Corp.), Ft. Worth, TX AGAINST: Galton, Glenn (Blue Cross and Blue Shield of Tx), Richardson, TX Glenn, Eric (Humana), Austin, TX Keel, Lara Laneri (Tx Association of Business and Chambers of Commerce), Austin, TX Keeling, Dan (Pacificare of Tx), San Antonio, TX Kloster, Jeff (HIAA, and Humana), Austin, TX McCandless, Patricia (Self), Austin, TX Ryder, M.D., Curtis J. (Quantum S. W.), San Antonio, TX Taylor, M.D., William J. (Aetna), Austin, TX Thompson, Jay (TALHI), Austin, TX Treadwell, Janet (HealthSmart Preferred Care), Lubbock, TX Registering, but not testifying: For: Banning, Tom (Tx Academy of Family Physicians), Austin, TX Freeman, Harold (Tx Medical Association), Austin, TX Gonzales, David (Tx Pharmacy Association), Austin, TX Phipps, Candie (Tx Pediatric Society), Austin, TX Against: Davis, Will D. (Tx Association of Life and Health Insurers), Austin, TX Looney, Gary R. (Tx Association of Health Underwriters), San Antonio, TX Manross, Lee (Tx Association of Health Underwriters), Austin, TX McCarty, Tom (Tx Association of Preferred Providers Organization), Austin, TX Nelson, Jim (Golden Rule Insurance Co), Austin, TX Pollard, Mike (Tx Association of Life and Health Insurers), Austin, TX Rummel, Leah (Tx Association of Health Plans), Austin, TX Tooley, Ken (Tx Association of Insurance and Financial Advisors), Austin, TX On: Brodersen, Blake O. (Tx Department of Insurance), Austin, TX HB 1927 Registering, but not testifying: For: Earwood, Herman (Ft. Worth I.S.D.), Ft. Worth, TX On: Kotrla, Claren J. (Tx Department of Health), Austin, TX Wingler, Todd F. (Tx Department of Health), Austin, TX HB 1994 FOR: Fondren, Gene N. (Tx Auto Dealers Association), Austin, TX AGAINST: Schneider, Rob (Consumers Union), Austin, TX Registering, but not testifying: On: Pettijohn, Leslie (Consumer Credit Commissioner), Austin, TX HB 3357 Registering, but not testifying: For: Rubottom, John (Lower Colorado River Authority), Austin, TX SB 1673 FOR: Beauchamp, Jerry (Insurance Agents), San Antonio, TX Boldin, Jim (Self), Austin, TX Gonzalez, Jr, Raymond (Self), San Antonio, TX Howell, Dave (Self), New Braunfels, TX Swift, David (Self), San Antonio, TX AGAINST: Carleton, Kyle (Farmers Insurance Group), Austin, TX Hintz, John W. (State Farm Insurance), Austin, TX Huxel, Bob (Farmers Insurance Group), Austin, TX Norton, Jo Betsy (Allstate Insurance Co), Austin, TX Thompson, Jay (AFACT, Farm Bureau Insurance Group), Austin, TX Registering, but not testifying: For: Ayala, Daniel D. (Self), San Antonio, TX Ayala, Ralph (Self), Jourdanton, TX Liere, Leslie G. (Self), College Station, TX Tooley, Ken (Tx Association of Insurance and Financial Advisors), Austin, TX Against: Alcocer, Merrilyn (Farmers Insurance Group), Hutto, TX Bassett, Jim (Self), Houston, TX Caffey, Cora (Self), Cedar Creek, TX Carr, Mike (Self), Georgetown, TX Caswell, Alan (Self), Round Rock, TX Craig, Tom (Self), Round Rock, TX Galvan, Gerard (Self), Round Rock, TX Grube, Judith G. (Judy Grube Insurance Agency), Austin, TX Hall, Richard (Self), Austin, TX Henson, Darlene (District Manager Dave Vannoy), Leander, TX Miertschin, Diane (Self), Georgetown, TX Norwood, Johnny (Self), Austin, TX Pucci, David (Farmers Insurance), Round Rock, TX Royer, Mark (Farmers Insurance Group), Austin, TX Salazar, Sylvia (Farmers Insurance), Hutto, TX Silguero, Melissa (Self), Austin, TX Steger, Candy (Self), Pflugerville, TX Sturm, Don (Self), Georgetown, TX Vannoy, David Roy (Self), Round Rock, TX Voges, Jessica (Voges Insurance Agency and District Manager), Austin, TX Waugh, Dawn Anne (Self), Round Rock, TX Zamora, Victoria (Self), Austin, TX On: Nesenholtz, Lynda (Tx Department of Insurance), Austin, TX SB 1826 FOR: McKinney, Mike (Centene Corp), Austin, TX AGAINST: McGiffert, Lisa (Consumers Union), Austin, TX Registering, but not testifying: Against: Davis, Helen Kent (Tx Medical Association), Austin, TX


Finding Features¶
Example¶
# features_dict is the dictionary obtained after reading nominal and/or ordinal data
from EBDM import feature_functions
feat_std_entropy = std_entropy(features_dict)
feat_entropy = feature_entropy(feat_std_entropy)
feat_rel = reliability(feat_entropy)
total_rel = total_reliability(feat_rel)
features_dict_weighted = weights(feat_rel, total_rel)
for f in features_dict.keys():
print('name:',f)
print('type:',features_dict[f].feat_type)
print('num_cat:',features_dict[f].num_cat)
print()
for cat in features_dict[f].categories.keys():
print(' index:',features_dict[f].categories[cat].index)
print(' name:',features_dict[f].categories[cat].name)
print()
print()
Output will be
name: You often feel that your life is aimless, with no definite purpose
type: ordinal
num_cat: 5
entropy: 1.4702489763160878
std_entropy: 1.6094379124341003
reliability: 0.9135170514856927
index: 0
name: Strong Disagree
prob: 0.13008130081300814
entropy: 0.26531325309042425
index: 1
name: Disagree
prob: 0.3902439024390244
entropy: 0.3672130124739616
index: 2
name: Neither
prob: 0.21951219512195122
entropy: 0.33285676595884867
index: 3
name: Agree
prob: 0.18699186991869918
entropy: 0.3135274244487411
index: 4
name: Strong Agree
prob: 0.07317073170731707
entropy: 0.19133852034411206
Features Class¶
-
class
features.
Features
(name, feat_type)¶ A class used to represent a feature. A feature represents question asked in the questionnaire. … .. attribute:: name
the name of the feature
- type
str
-
feat_type
¶ the type of feature: ordinal or nominal
- Type
str
-
num_cat
¶ the number of categories for a feature in the questionnaire
- Type
int
-
categories
¶ a dictionary with keys as category name and values as objects of Categories class
- Type
dictionary
-
entropy
¶ the entropy of a feature in a particular population, given by entropy of feature = sum(entropy of categories)
- Type
float
-
std_entropy
¶ the standard entropy of a feature given by log(num_cat)
- Type
float
-
reliability
¶ the reliability of a feature given by entropy/ std_entropy
- Type
float
-
weight
¶ the weight of a feature given by reliability/ total_reliability
- Type
float
-
distance
¶ the dictionary of distances between categories of a feature. distance[cat1][cat2] represents distance between cat1 and cat2
- Type
dictionary
-
category_order
¶ the dictionary from category index to category name
- Type
dictionary
Calculating Occurence Probability¶
-
feature_functions.
probability
(df, features)¶ Calculates the occurence probability of all the categories for every feature.
- Parameters
df (panda dataframe) – the dataset of the population
features (dictionary) – a dictionary of features with keys as feature name and values as objects of feature class.
- Returns
features – a dictionary of features with keys as feature name and values as objects of feature class with updated probability values.
- Return type
dictionary
Calculating Entropies¶
-
feature_functions.
entropy
(features)¶ Calculates the entropy of all the categories for every feature.
- Parameters
features (dictionary) – a dictionary of features with keys as feature name and values as objects of feature class.
- Returns
features – a dictionary of features with keys as feature name and values as objects of feature class with updated entropy values.
- Return type
dictionary
-
feature_functions.
std_entropy
(features)¶ Calculates the standard entropy of all the features.
- Parameters
features (dictionary) – a dictionary of features with keys as feature name and values as objects of feature class.
- Returns
features – a dictionary of features with keys as feature name and values as objects of feature class with updated standard entropy values.
- Return type
dictionary
-
feature_functions.
feature_entropy
(features)¶ Calculates the entropy of all the features.
- Parameters
features (dictionary) – a dictionary of features with keys as feature name and values as objects of feature class.
- Returns
features – a dictionary of features with keys as feature name and values as objects of feature class with updated feature entropy values.
- Return type
dictionary
Calculating Reliability¶
-
feature_functions.
reliability
(features)¶ Calculates the reliability of all the features.
- Parameters
features (dictionary) – a dictionary of features with keys as feature name and values as objects of feature class.
- Returns
features – a dictionary of features with keys as feature name and values as objects of feature class with updated reliability values.
- Return type
dictionary
-
feature_functions.
total_reliability
(features)¶ Calculates the total reliability of the features.
- Parameters
features (dictionary) – a dictionary of features with keys as feature name and values as objects of feature class.
- Returns
total_rel – the total reliability of the features
- Return type
float
Calculating Weights¶
-
feature_functions.
weights
(features, total_reliability)¶ Calculates the weights of all the features.
- Parameters
features (dictionary) – a dictionary of features with keys as feature name and values as objects of feature class.
total_reliability (float) – the total reliability of the features
- Returns
features – a dictionary of features with keys as feature name and values as objects of feature class with updated weight values.
- Return type
dictionary


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About
ClusterUI:a web tool for clustering multivariate data
This is an unsupervised learning web tool that clusters microstructures in steel based on their physical properties. You can upload your own data as an Excel or CSV file and get a summary of it under the Upload tab. Different clustering algorithms can be selected under the Cluster tab. You can reduce the dimensionality of the data by selecting Principal Component Analysis (PCA).
This web tool is developed as part of the coursework - Software Engineering, 2019 for the Chair for Functional Materials, Saarland University.
More information on the department can be found on their webpages: https://www.fuwe.uni-saarland.de/


Dem Sen. Brown: 'Some Republicans' Will Vote to Remove Trump | Breitbart
by Ian HanchettOn Friday’s broadcast of HBO’s “Real Time,” Senator Sherrod Brown (D-OH) predicted that some Republicans in Congress will vote to remove President Trump.
Brown said, “[N]ext year, impeachment will be over. There will be some Republicans that vote to remove him, I’ll bet you, by then. Because they’re nervous in their districts.”
Follow Ian Hanchett on Twitter @IanHanchett


1. Introduction
There are a handful of different motion sensors available in modern hardware such as phones.
The motion sensors extends the Generic Sensor API [GENERIC-SENSOR] to expose a class of low-level and fusion sensors. This document explains the relationship between these sensors.
The low-level sensors include:
Multiple new sensors can be created using the data from these above sensors in different ways. These are commonly known as fusion sensors.
2. Security and Privacy Considerations
There are no specific security and privacy considerations beyond those described in the Generic Sensor API [GENERIC-SENSOR].
3. Low-level Sensors
3.1. Accelerometer
A raw accelerometer sensor measures changes in acceleration in 3 different directions, but is affected by gravity. The Accelerometer interface is defined in [ACCELEROMETER] specification.
The Accelerometer sensor is an inertial-frame sensor, this means that when the device is in free fall, the acceleration is 0 m/s2 in the falling direction, and when a device is laying flat on a table, the acceleration in upwards direction will be equal to the Earth gravity, i.e. g ≡ 9.8 m/s2 as it is measuring the force of the table pushing the device upwards.
Accelerometers are less useful by themselves and often take part in other fusion sensors, but they do have some purposes like registering shakes, steps and the like.
Often for such use-cases the developer is interested in the linear acceleration which is the acceleration without the gravity, called gravity compensation (See Linear Acceleration Sensor); or the developer is interested in the isolated gravity, in order to know the gravity vector (see Gravity Sensor), which can be useful for some kinds of sensor fusion like creating a magnetic compass.
For acceleration, you usually care about the big changes and want to avoid noise, like the gravity, thus a high-pass filter can help isolate the linear acceleration and a low-pass filter can help isolate the gravity. A low-pass filter can thus be useful for measuring a tilt. Unfortunately, any high-pass filter or low-pass filter introduces a delay, which may or may not be acceptable.
Notice, as accelerometers report acceleration, you need to integrate to get velocity:
v = ∫a×∂t
And again to get position:
x = ∫v×∂t
An integral creates drift, and a double integral amplifies that:
a = g×sin(θ), x = ½×at2
So position from an accelerometer is very imprecise and not very useful.
3.2. Gyroscope
A gyroscope senses angular velocity, relative to itself, thus it measures its own rotation, using an inertial force called the Coriolis effect. Gyroscopes oscillate at relative high frequency in order to measure this and are thus one of the most power hungry motion sensors. This also means that they can easily be affected by other vibrations, like a vibration (rumble) motor or speaker on the same device. The Gyroscope interface is defined in [GYROSCOPE] specification.
In order to get rotation (angle) from a gyroscope, which senses angular velocity, you need to perform a single integration.
f ≡ frequency
∫cos(2π×ft)) = (1/(2π×f)) × sin(2π×ft)
But be aware that integration turns noise into drift. As we see above, the integration gets a 1/f outside, meaning that high frequency (f) noise disappears with integration, i.e. a noise of frequency will drop by a factor of a 100, but a very low frequency will be amplified, meaning the gyroscope will drift over time.
So in order to do it well you need to do it quickly and as you see below, we multiply with the ∂t, so any error in the reported time difference will manifest itself like the drift above.
θn = θn-1 + ω × ∂t
With ω denoting the angular velocity and θ, the resulting angle.
Most gyroscope sensors perform calibration by applying some sort of drift compensation in hardware for known low frequency caused by adjacent hardware on the device.
3.3. Magnetometer
Magnetometers are magnetic field sensors, which means that without any strong magnetic influence close by, it will sense the Earth’s magnetic field, which more or less points in the direction of North, but not true North. The Magnetometer interface is defined in [MAGNETOMETER] specification.
As said, magnetometers are very sensitive to outside influence, like anything on a table that has been slightly magnetized, and it is even affected by other things inside a device, though the device manufacturer can compensate for this somewhat. In practise though, these sensors work quite well for most common use-cases.
As long as nothing that is magnetized in the surrounding is moving around, the magnetometer readings are stable enough to be used to isolate gravity as mentioned above.
Magnetometer is a 3-axis sensor, which means it gives a 3D vector pointing to the strongest magnetic field. It also means that it does not enforce a specific device orientation in order to work.
In order to tell how the device is being held, though, you need a gravity vector, which as a bare minimum requires an accelerometer in the case of low pass filtering, and additionally a gyroscope if more precise readings are needed. This is called tilt compensation.
The most common use-case for magnetometers are as part of sensor fusion, in order to generate an Orientation Sensor which is stationary to the Earth plane, or a compass, which is basically the former with corrections to the declination depending on geolocation position, such that it points to the true North.
4. High-level Sensors
As mentioned above, each sensor has its own issues, such as noise and drift, and often need some kind of compensation using input from a different sensor. Put another way, one sensor might not be very precise on its own, but the sum of multiple sensory input can be much more stable.
Unfortunately, sensors require power, and the more sensors and the higher the measuring frequency, higher the power consumption. The gyroscope is typically considered more power hungry than the rest, as it needs to vibrate at a certain frequency in order to measure the angular velocity.
For the above reasons, it is always important to consider the minimum set of sensors which solves a task satisfactory. As many devices today can do certain kinds of sensor fusion in hardware, it most often makes sense to use these from a power and performance point of view.
4.1. Common fusion sensors
Below is a list of fusion sensors and what sensors they usually are made up of:
| Sensor type | Underlying physical sensors |
|---|---|
| Relative Orientation Sensor | Accelerometer, Gyroscope, MUST NOT USE Magnetometer |
| Absolute Orientation Sensor | Accelerometer, Magnetometer, AND (when present) Gyroscope |
| Geomagnetic Orientation Sensor | Accelerometer, Magnetometer, MUST NOT USE Gyroscope |
| Gravity Sensor | Accelerometer, Gyroscope |
| Linear Acceleration Sensor | Accelerometer, AND EITHER Gyroscope OR Magnetometer |
4.2. Low and high pass filters
As mentioned earlier, it is possible to remove noise (high or low frequency) using low and high pass filters. As the names say, the filters let low or high frequencies pass and thus cut of, or minimize, the effect of unwanted frequencies.
4.2.1. Low-pass filter
A common way to create a low-pass filter is to only use a percentage of the latest value and take the rest from the existing value. In a way this means that the filter remembers common values and thus smoothens out uncommon values which most often are a result of noise. As it uses a big percentage of the existing value, this solution introduces a delay in registering the actual events.
class LowPassFilterData{ constructor( reading, bias) { Object. assign( this , { x: reading. x, y: reading. y, z: reading. z}); this . bias= bias; } update( reading) { this . x= this . x* this . bias+ reading. x* ( 1 - this . bias); this . y= this . y* this . bias+ reading. y* ( 1 - this . bias); this . z= this . z* this . bias+ reading. z* ( 1 - this . bias); } }; const accl= new Accelerometer({ frequency: 20 }); // Isolate gravity with low-pass filter. const filter= new LowPassFilterData( accl, 0.8 ); accl. onreading= () => { filter. update( accl); // Pass latest values through filter. console. log( `Isolated gravity ( ${ filter. x} , ${ filter. y} , ${ filter. z} )` ); } accl. start();
4.2.2. High-pass filter
High-pass filter works like a low-pass filter, but allows only high frequencies to pass through.
This can be useful to get rid of the drift which builds up over time with gyroscope readings.
class HighPassFilterData{ constructor( reading, cutoffFrequency) { Object. assign( this , { x: reading. x, y: reading. y, z: reading. z}); this . cutoff= cutoffFrequency; this . timestamp= reading. timestamp; } update( reading) { let dt= reading. timestamp- this . timestamp/ 1000 ; this . timestamp= reading. timestamp; for ( let iof [ "x" , "y" , "z" ]) { let alpha= this . cutoff/ ( this . cutoff+ dt); this [ i] = this [ i] + alpha* ( reading[ i] - this [ i]); } } }; const gyro= new Gyroscope({ frequency: 20 }); // Remove drift with a high pass filter. const filter= new HighPassFilterData( gyro, 0.8 ); gyro. onreading= () => { filter. update( gyro); // Pass latest values through filter. console. log( `Steady gyroscope ( ${ filter. x} , ${ filter. y} , ${ filter. z} )` ); } gyro. start();
4.3. Absolute Orientation Sensor
As mentioned before, the Absolute Orientation Sensor, is one of the common use-cases of a magnetometer, and is a sensor representing an orientation stationary (fixed to the magnetic field vector and gravity vector) to the Earth plane. The AbsoluteOrientationSensor interface is defined in [ORIENTATION-SENSOR] specification.
An absolute orientation sensor can be useful for game controls such as a ball-in-a-maze puzzle, or for a head-mounted display where you want to be able to rotate the display and look in all directions.
As the reference frame of an absolute orientation sensor is stationary, it is not useful as a controller for say a driving game on a phone, as it would not allow you to move around, even slightly or slowly, without affecting your driving direction. (See Relative Orientation Sensor).
The orientation vector of the Absolute Orientation Sensor, can be calculated in the following way:
As the Accelerometer is an inertial-frame sensor, the gravity vector will point towards the sky when the device is mostly stationary, and as long as the device is not in free fall, there is enough vector length to project the magnetic field vector onto the ground plane.
Note, this will fail at the magnetic poles as the magnetic field vector will point mostly in the opposite direction as the gravity vector and generally be very unreliable.
By taking the cross product between the the magnetic field vector and gravity vector (see Gravity Sensor), we get a vector which points East on the ground plane, using the right hand rule.
Now if we take the cross product between the gravity vector and the newly found East vector, the resulting vector will point in the northern direction towards the Earth’s magnetic field.
The illustration below represents the case where the device is at rest and y-axis points towards the North. The reading from the Magnetometer is {x: 0, y: 11, z: -16} and Accelerometer reports {x: 0.11, y: 0.07, z: 9.81} acceleration. The uG is a unit vector representing the gravity, uB represents magnetic field vector, uE = uB × uG and points East. The uN = uG × uE points to the northern direction.
That means an Absolute Orientation Sensor is a fusion sensor of the Magnetometer and the Accelerometer, and potentially the Gyroscope for better isolated gravity (see Gravity Sensor).
4.4. Geomagnetic Orientation Sensor
A Geomagnetic Orientation Sensor, is like a Absolute Orientation Sensor, but doesn’t use the Gyroscope which means it uses less power. This also means that it is more sensitive to shakes and movement.
As the main use-case for a Geomagnetic Orientation Sensor is to create a compass, or use compass direction within a mapping application, this is not much of a problem since people usually hold the device steady for these use-cases.
The actual heading (N, S, E, W) can be found by adjusting the rotation vector with the local declination compensation calculated from the current geolocation position.
As the sensor uses the accelerometer to get a more steady heading, like when walking, the rotation vector is projected to the plane perpendicular to the gravity vector (as isolated from the accelerometer) which more or less represents the ground plane. This also means that if you are interested in the actual orientation of the gravity vector, then use the magnetometer directly instead.
4.5. Relative Orientation Sensor
On most sensor hubs, gravity is isolated from the accelerometer using the gyroscope, and the linear acceleration is isolated by removing the isolated gravity, from the accelerometer values.
This avoids the delay which low and high pass filters introduce.
One way of doing this is using a Kalman filter or complementary filter, which leads us to the Relative Orientation Sensor. As a complementary filter yields quite good results and is easy to implement in hardware, this is a common solution.
4.5.1. Complementary filter
A complementary filter can be thought of as a low-pass filter and high-pass filter in one, complementing the gyroscope values with the accelerometer values:
θn = α × (θn-1 + ω × ∂t) + (1.0 - α) × a
With α being the weight constant, a the acceleration from accelerometer, ω the angular velocity from gyroscope and ∂t being the time between measurements.
A common value for α is 0.98, which means that 98% of the weight lays on the gyroscope measurements.
The gyroscope measures angular velocity, so by multiplying with the time difference, we get the change of angle. This change is always calculated relative to the current device position, so we need to use the accelerometer, which includes gravity, to calibrate this to the ground plane.
The values from the accelerometer bring no information about the heading (alpha, the rotation around z), so we don’t include that in our alpha component. On the other hand, the accelerometer (due to gravity) provides information on how the device is held around the x and y axis (beta and gamma).
When there is no or little movement, the vector obtained from the accelerometer reading will contribute more to the (alpha, beta, gamma) angles than the gyroscope.
As values from a steady accelerometer represent the gravity vector, and we don’t include the z component in the alpha, the result of this is that the orientation will just follow the gyroscope and be stable. But as the origin of the heading depends on the device position at start this a device-relative orientation sensor.
const options= { frequency: 50 }; const accl= new Accelerometer( options); const gyro= new Gyroscope( options); let timestamp= null ; let alpha= beta= gamma= 0 ; const bias= 0.98 ; gyro. onreading= () => { let dt= timestamp? ( gyro. timestamp- timestamp) / 1000 : 0 ; timestamp= gyro. timestamp; // Treat the acceleration vector as an orientation vector by normalizing it. // Keep in mind that the if the device is flipped, the vector will just be // pointing in the other direction, so we have no way to know from the // accelerometer data which way the device is oriented. const norm= Math. sqrt( accl. x** 2 + accl. y** 2 + accl. z** 2 ); // As we only can cover half (PI rad) of the full spectrum (2*PI rad) we multiply // the unit vector with values from [-1, 1] with PI/2, covering [-PI/2, PI/2]. const scale= Math. PI/ 2 ; alpha= alpha+ gyro. z* dt; beta= bias* ( beta+ gyro. x* dt) + ( 1.0 - bias) * ( accl. x* scale/ norm); gamma= bias* ( gamma+ gyro. y* dt) + ( 1.0 - bias) * ( accl. y* - scale/ norm); // Do something with Euler angles (alpha, beta, gamma). }; accl. start(); gyro. start();
From the above example, we notice that the alpha represented the initial heading orientation. We also know that this heading might drift over time due to being based on the gyroscope.
In some situations you might want the orientation to drift towards your current position. This can be useful for a controller inside a virtual reality environment, where you want a car to follow the heading of your controller, but you might move and turn around while playing. That would more or less work like driving a real car.
Changing one line in the above accomplishes that.
const zeroBias= 0.02 ; alpha= ( 1 - zeroBias) * ( alpha+ gyro. z* dt);
With the above 2% of the alpha consists of the value 0. Thus, when the device is being held more or less steady, the heading will move towards 0, meaning being adjusted to your current device position and not positioned according to the surroundings.
This example shows how useful manual fusion can be at times.
4.6. Gravity and Linear Acceleration Sensor
The complementary filter used above is quite good at isolating the gravity, and most sensor hubs thus isolate gravity from the accelerometer using the gyroscope, and the linear acceleration is isolated by removing the isolated gravity, from the accelerometer values.
This also means that the Linear Acceleration Sensor and the Gravity Sensor as exposed by most sensor hubs are most likely fusion sensors.
Gravity can also be removed from a linear acceleration sensor using a magnetometer, as the magnetic field vector is more or less stable.
The LinearAccelerationSensor interface and GravitySensor interface are defined in [ACCELEROMETER] specification.
Note, as the gravity changes with the frequency of the movements, i.e., 0 in falling direction in free fall, you can imagine that linear acceleration will be quite imprecise if you are trying to detect a shake, so keep that in mind.
4.7. Use Cases and Requirements
Advanced motion sensor use-cases could have requirements for accurate sensor readings, high sampling rates at which hardware sensor operates, and reading delivery rate that is preferable for particular application.
Motion sensors can be used for variety of advanced use-cases, such as:
-
Virtual and augmented reality HMD tracking [HMDTRACKING]
-
Sensor assisted indoor mapping and navigation [INDOORNAV], [IPIN]
-
Photo and video capture stabilization [ROLLSTABILIZER], [VIDEOSTABILIZER]
-
Games that require high-frequency sampling rates with high accuracy readings.
-
3D scanning [3DSCANNING]
-
Advanced gesture recognition [MEMSGESTURES]
-
Step counting and monitoring of other physical activities [PHYSMON]
The generic requirement for games or UI applications that use motion sensors is to have a new sensor reading per rendered frame. The higher sampling rates in this case, will reduce latency, thus improve user experience.
In case of virtual reality HMD tracking, sensors might run at very high sampling rates (up to several kHz) and minimize motion-to-photon latency by providing latest sensor reading for every rendered frame at refresh rates of 75-120Hz.
Indoor navigation or non-realtime video (image) stabilization applications could benefit from collecting high accuracy sensor readings at high sampling rates (80-100Hz), so that data processing algorithms have enough samples to provide accurate results.


AIMROM's Lead Developer and Founder, an Android Enthusiast.
InfiniteOS's Lead Developer and Founder, an Tech Enthusiast.
Cosmic-OS's Lead Developer and Founder.
halogenOS's and Substratum's Developer.
Maintainer
A Flat, Simple Dark Substratum Theme
“I am no Jedi.” — Ahsoka Tano
A Flat, Simple Light Substratum Theme
“I’ll never turn to the dark side. You’ve failed, your highness. I am a Jedi.” — Luke Skywalker


Installation and Dependencies¶
SPLAT is best forked from the github site https://github.com/aburgasser/splat/,
which is updated on a regular basis. There is a possibility of pip
installation, but this is not working quite yet.
There are two additional steps to complete to get full functionality:
Copy the file
.splat_access
into your home directory - this is your access key if you have priveleged access to unpublished data.Set up your environment variables to find the SPLAT code; this can be done in three ways (in the order of which the code looks for this directory):
- Best: create an environment variable called SPLAT_PATH and set it to the root directory of the SPLAT code (in bsh environment, add the line
export SPLAT_PATH=/Users/adam/projects/splat
to your .bashrc or .bash_profile) - If you use the PYTHONPATH environment variable, add the root directory of the SPLAT code to it (in bsh environment add the line
export PYTHONPATH=/Users/adam/projects/splat:${PYTHONPATH}
to your .bashrc or .bash_profile) - add the root directory of the SPLAT code to your system PATH variable (in bsh environment add the line
export PATH=/Users/adam/projects/splat:${PATH}
to your .bashrc or .bash_profile)
- Best: create an environment variable called SPLAT_PATH and set it to the root directory of the SPLAT code (in bsh environment, add the line
The SPLAT code uses the following external packages that are contained in the Ananconda installation:
The following external packages must be installed separately (using pip):
It also use the following internal (python) packages (no installation should be needed):
- base64
- copy
- csv
- datetime
- division (for Python v2.X)
- glob
- math
- os
- print_function (for Python v2.X)
- random
- re
- shutil
- sys
- string (for Python v2.X)
- time
- warnings
SPLAT has been tested in Python 2.7.X and 3.5.X.
SPLAT has not yet reached v1.0, so bugs are common. Please help us squish them by sending bug reports to<EMAIL_ADDRESS>or start an issue on the github site.


A Complete Mobile App For Your Sports Court Booking Needs And Beyond
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Sports We Have
Search for venues and courts depending on your preferred location
Need players to form a team or just connect, use this feature to find awesome players
Need to book a venue or ground, just go to the Booking section and select your sport
The more you book through our app, and refer it to your friends, the more PS points you earn.
Download the app now by scanning or clicking one of these codes with the phone!
The rise of mobile devices transforms the way we consume information entirely and the world's most elevant channels such as Facebook.
Once you create an account, then you can fully use the app and reap its benefits
Once you create an account, then you can fully use the app and reap its benefits
Once you create an account, then you can fully use the app and reap its benefits
Get working experience to work with this amazing team & in future want to work together for bright future projects and also make deposit to freelancer.
Get working experience to work with this amazing team & in future want to work together for bright future projects and also make deposit to freelancer.
Get working experience to work with this amazing team & in future want to work together for bright future projects and also make deposit to freelancer.
Get working experience to work with this amazing team & in future want to work together for bright future projects and also make deposit to freelancer.
Get working experience to work with this amazing team & in future want to work together for bright future projects and also make deposit to freelancer.
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About Me
Selected Projects
Resume
Blog
Do Good
Developer and ex-finance nerd. Kind of quirky.
Loves: Building things, animals, creative, spreadsheets.


This is an open field west of a white house, with a boarded front door.
[[NORTH->North of House]]
[[SOUTH->South of House]]
[[WEST->Forest]]You are facing the north side of a white house. There is no door here, and all the windows are barred.
[[WEST->West of House]]
[[EAST->East of House]]
[[NORTH->Forest]]
You are facing the south side of a white house. There is no door here, and all the windows are barred.
[[WEST->West of House]]
[[EAST->East of House]]
[[SOUTH->Forest]]This is a forest, with trees in all directions around you.
[[NORTH->Sunlit Forest]]
[[EAST->Forest]]
[[SOUTH->Forest]]
[[WEST->Forest]]You are behind the white house. A path leads into the forest to the east. In one corner of the house there is a small window which is slightly ajar.
[[NORTH->North of House]]
[[SOUTH->South of House]]
[[EAST->Sunlit Forest]]
[[WEST->Kitchen]]
[[ENTER->Kitchen]]This is a dimly lit forest, with large trees all around. One particularly large tree with some low branches stands here.
[[NORTH->Forest]]
[[SOUTH->Forest]]
[[EAST->Forest]]
[[WEST->East of House]]
[[UP->Tree]]You are in the kitchen of the white house. A table seems to have been used recently for the preparation of food. A passage leads to the west and a dark staircase can be seen leading upward. A dark chimney leads down and to the east is a small window which is open.
[[EAST->East of House]]You are about 10 feet above the ground nestled among some large branches. The nearest branch above you is above your reach. Beside you on the branch is a small bird's nest.
[[DOWN->Sunlit Forest]]


<EMAIL_ADDRESS>Class: Rogue Hacker
Level: 19
Armor Type: Graphic T
Key Stats: Initiative, Creativity
Alignment: Chaotic Good
Quests:
BackStory:
<EMAIL_ADDRESS>Class: Noble-Techie
Level: 19
Armor Type: Jorts
Key Stats: Constitution, Willpower
Alignment: Lawful Good
Quests:
BackStory:


OUTDATED
I wrote this back when I was 16, the drivers for the intel graphics for broadwell and up can now be installed via ports/pkg on the STABLE release of FreeBSD.
Here is my first blog showing my personal experience of getting FreeBSD working on a my Thinkpad T450s in hopes that it will serve someone else.
Before we get started on the actual installation and configuration process, some useful notes to consider that can differ on your personal machine;
My hardware inventory on this T450s, consists of:
- Processor: Intel(R) i5-5300U @ 2.3 GHz with 2 cores and 4 threads.
- Memory: 12 GB DDR4, 4 GB soldered, 8 GB soketed.
- Graphics: Intel(R) HD 5500 (Broadwell GT2)
- Driver(s): i915kms, drm. see here.
- Storage: 128 GB HITACHI(R) SSD.
- Display: 1600x900 TN built in Thinkpad display and a 3648x1152 Samsung(R) VGA monitor.
- Wireless: Intel Dual Band Wireless AC 7265
- Driver(s): if_iwm, iwm7265fw, iwm7265Dfw. see here.
- Battery: 1 default 86+ lenovo battery, 3 cell 54 Wh and 1 internal 3 cell 54 Wh
This page assumes you have the base system of FreeBSD 11.0-RELEASE installed on your machine, if you do not see here.
I will also be assuming you are using the same model of thinkpad as me, a thinkpad T450s if you havent caught on. similar models may have a very similar process if not the same.
This guide will be taking care of these major things:
- Getting the iwm wireless driver working.
- Getting the intel DRM graphics stack working.
- Installing and Configuring Xorg.
- Configuring audio.
- Configuring synaptics trackpad driver.
- Fine tuning of the FreeBSD kernel.
Since you will need a internet connection to take care of any task obviously the first step is getting WI-FI to work. This step can vary wildly in success, my T450s came with a special snowflake of a realtek chip that isn’t even supported by the FreeBSD rtwn driver.  Specifically the one listed in the hardware inventory, which I was able to get working pretty easily.
In order to get this chip working you need the iwm driver either compiled into your kernel or loaded as a kernel module. It is not included by default.
The iwm driver supports the following wireless cards:
- Intel Dual Band Wireless AC 3160
- Intel Dual Band Wireless AC 3165
- Intel Dual Band Wireless AC 7260
- Intel Dual Band Wireless AC 7265
- Intel Dual Band Wireless AC 8260
This is easily accessible documentation about this driver and how to get it working here, but I wanted to keep everything in one place so i listed it here as well.
Since we are going to compile the kernel twice anyway lets just take the easy route and just load it as a module. To do this let’s open /boot/loader.conf with a text editor, the default preinstalled editor is ee.
Add the following lines:
if_iwm_load="YES"
Depending on which wireless card you specifically have, you will also need to add 1 of the following depending on your model of wireless card:
iwm3160fw_load="YES"
iwm7260fw_load="YES"
iwm7265fw_load="YES"
iwm8000Cfw_load="YES"
If you are unsure and too lazy to check simply add all of them, no harm in it besides being less minimalistic For my chip it was the 7265 firmware.
Adding the driver alone will not get you a active internet connection. You must also get the driver to use DHCP in order to get you a ip address. Add the following to /etc/rc.conf:
ifconfig_iwm0="DHCP"
iwm0 can change depending on what wireless card you are using. for example if you were using the rtwn driver instead, it would be:
ifconfig_rtwn0="DHCP"
Okay now reboot, you will notice you still cannot ping google. Obviously you need to add a network first. First make sure your wlan0 interface is even loaded. run:
ifconfig | grep wlan
If you see something similar to:
wlan0: flags=8843<UP,BROADCAST,RUNNING,SIMPLEX,MULTICAST> metric 0 mtu 1500
Then all is fine, if you don’t see that you can attempt to attach the device with:
ifconfig wlan create wlandev iwm0
Again, iwm0 is a variable, in case you are using a different driver other then iwm.
If you see that the device has attached then you have successfully gotten your wireless card functional.
If you see a error that looks something like:
SOIFCONFIG: Device not configured
Then you might have made a typo in /boot/loader.conf or you have the wrong driver loaded altogether.
Assuming you now are able to run the scan command mentioned earlier, take your ssid as shown in the can results and the password of the network and create a new file named wpa_supplicant.conf in /etc/. The ultimate path of it should be /etc/wpa_supplicant.conf. Then put your network info inside this file, to do this follow:
First create/open the file with:
ee /etc/wpa_supplicant.conf
How for your network info:
network={
ssid="your network name goes here"
psk="your password goes here"
}
Now restart the network daemon in order to achieve net access:
service netif restart
Now test your connection:
ping <IP_ADDRESS>
If you get packets pack from google then we can move onto the next step, if you don’t the friendly people in #freebsd on the irc network irc.freenode.net, will gladly help.
Next quick step is just making sure that the pkg binary tree is working, to do this run:
pkg update
As root. If you would like to use the ports tree instead run:
portsnap fetch && portsnap extract
Next we will be getting the intel HD 5500 graphics card functional, this will be a far longer and more complicated step then what we just did, but not impossible.
Lets get started on getting the Intel HD 5500 graphics chip fully working.
Just like the wireless card the Intel HD 5500 graphics chip does not work out-of-the-box in the base system.
The driver for the intel HD 5500 graphics chip among others is called i915. Unlike iwm, you need to recompile the whole base system.
To do this, first you need to download the source tree of drm-next graphics stack. You can find documentation for this here.
But i’m going to put it here in order to keep everything in one place, of course. First, install llvm40:
pkg install llvm40
Or via ports:
cd /usr/ports/devel/llvm40/ && make clean install
Now download the drm-next source tree:
git clone https://github.com/FreeBSDDesktop/freebsd-base-graphics.git -b drm-next
NOTE When I installed drm-next branch on a 12.0-CURRENT install it resulted in a nightmare of a kernel panic, make sure you are using 11.0-RELEASE which i had success with.
When the branch is done cloning, go into the directory:
cd FreeBSDDesktop/freebsd-base-graphics
Normally I would say this is a good chance to strip unused drivers from the kernel config in order to:
- Use less memory on boot
- Decrease the time taken to boot past the bios
If this is your first time doing this then I will suggest you do not do this now in order to turn down the chance of getting a kernel panic afterwards, so for now we will be conservative with our drivers.
If you wish to do this now anyway, well here.
How long this part will take will vary depending on what hardware you are using in terms of CPU mainly. (# of cores, # of threads, clock speed, cache.)
Lets say if you are using the intel i5 5300U, it has 2 cores and 4 threads. To utilise all cores and all threads to make these commands as fast as possible the following would apply:
Run as root.
make -j4 buildworld -s
In this step you are making the “world” of your installation, the userspace. As you can see -j4 represents that im using 4 cores, or 2 cores and 4 threads. If you have 8 cores and 16 threads or 16 cores and 16 threads it would both be -j16.
You can find the docs for this procedure in the drm-next wiki here.
Now build the kernel:
make -j4 buildkernel -s
Now install the kernel.
```markdown sudo make -j4 installkernel -s


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Component PHP
Edit (pull request)This component will install the PHP on the host server.
Used version for this tutorial : PHP
This installation is based on Ubuntu distribution with apt-get command.
Definition
PHP is the programming language of the LAMP stack, it’s a server-side scripting. On this page, we just explain the recipe of this component. Below, the header of the php-type :
Properties
The PHP recipe is not so complicated, it has only three properties. The first property is the version, like for Apache recipe, it’s just to be mentioned. The two other properties are booleans to install the PHP Apache 2 module or the PHP MySQL module.
| Property | Usage | Comment |
|---|---|---|
| version | Mention the php version | Constant version in our example (v5) |
Lifecycle and related scripts
PHP inherite from the tosca base type tosca.nodes.SoftwareComponent
| Operation | Usage | Comment |
|---|---|---|
| create | Executed script to install PHP on the Compute | Through apt-get on ubuntu image |


--- layout: default title: Arindam Paul ---
Since graduating with my PhD in Computer Science from Northwestern University in 2019, I have been working in the Enterprise Data Science & ML Research as a Data & Applied Scientist at American Family Insurance. My research interests include machine learning, deep learning, computational informatics and natural language processing.
During my PhD, I worked at CUCIS group on applications of machine and deep learning for accelerating scientific discovery in the fields of cheminformatics, materials informatics and manufacturing technology.
I also completed my M.S. in Computer Science from Northwestern University in 2014. During my M.S., I have worked on internet privacy at the Northwestern Networks Group led by Prof. Kuzmanovic, and studied anonymity in social media at the Northwestern Social Media Lab directed by Prof. Birnholtz.
Prior to that, I completed my M.Eng. in Software Systems and B.Eng. in Chemical Engineering (with a minor in Computer Science) from BITS Pilani, India.


demo index
»
monosynth with delay
A simple, 1 octave, monophonic synthesizer, that you can play with the keyboard with added 5 stage delay effect
Press the following keys to play the monosynth:
W E T Y U A S D F G H J K


This page will show how to start a blog, get information on how to troubleshoot slowness, how to tell if a device is on the network, which software is preferred for dictation and instructions on how to use different PACS systems The main content will have a FAQ container as well as directions and images of using different PACS systems and troubleshooting different parts of the Enterprise Architecture


WITNESS LIST Subcommittee on Higher Education Committee October 18, 2004 - 1:00P Creation of Higher Education Enhancement Districts FOR: Ball, Jim Public Relations Consultant (Self) Eastland, William M. (Bill) Tax Accounting (On behalf of UT Arlington), Arlington, TX Warren, Joshua Student (Self), Arlington, TX ON: Calvert, Stanton C. (Texas A&M University System), Austin, TX Collins, Steve Interim Vice Chancellor & Gen. Counsel (UT System), Austin, TX Flack, Teri E. Deputy Commissioner (Texas Higher Education Coordinating Board), Austin, TX Morton, Jack Vice Chancellor (University of North Texas System), Austin, TX Pankratz, Terry Vice President-Business & Admin. (Texas A&M Commerce-Keith McFarland), Commerce, TX Smith, Roland Vice President of Business Affairs (Stephen F. Austin State University), Nacogdoches, TX Urbanovsky, Lamar Chancellor (Texas State University System), Austin, TX


Getting Cray / On Fleek
By using :target
and ~
we can do some pretty ridiculous things without touching Javascript. In this pen, we are using :target
to trigger different state-related styles.
At the top of this pen, there are
elements. Their only purpose is being used as targets.

...
Using their :target
state, we can then select and style anything else on the page.
Moving the main content area over -300%
to reveal this fourth section.
#s4:target ~ main {
left: -300%;
}
Changing the background color and image:
#s4:target ~ #background {
background-image: url(http://lorempixel.com/g/400/150/city/4/);
background-color: #265273;
}
Changing the progress bar width:
#s4:target ~ #progress {
width: 50%;
}
Styling the fourth thumbnail as active:
#s4:target ~ .thumbs li:nth-child(4) a {
opacity: 1;
width: 80px;
height: 60px;
box-shadow: 0px 0px 0px 1px rgba(255, 255, 255, 0.1);
}
Showing the appropriate previous link and making it say the right thing:
#s4:target ~ .prevnext li[class*="p4"] {
display: block;
float: left;
}
#s4:target ~ .prevnext li[class*="p4"] a:after {
content: "Prev";
}
Showing the appropriate next link and making it say the right thing:
#s4:target ~ .prevnext li[class*="n4"] {
display: block;
float: right;
}
#s4:target ~ .prevnext li[class*="n4"] a:after {
content: "Next";
}


#assign documentation="active">
Getting started
Trouble shooting
Logging
DDL generation
DB Migration
Testing
Configuration
Transactions
Mapping
Query
L2 Cache
Persisting
Kotlin
Features
ElasticSearch
History
Event listening
Soft delete
Draftable
JSON in DB
JSON
Who auditing
Change log
Read auditing
Tuning
Monitoring
Tooling
Upgrading
Architecture
JPA comparison
Hibernate comparison
Persistence context
Load context
Funding
Funding & Sponsorship


Some console application may provide the syntax that just carries only one option. For example, gacutil.exe provides a syntax that just have a /? option, which may provide detailed help information on the program. Actually there are many console applications that will have such kind of syntax defined, some application defines the syntax for providing the help screen, some for displaying the system status and others may use it to print the version number of the application. No matter how the application behaves, we call such kind of syntax an Exact contract in ACF.
Take catool.exe as an example, it has the following syntaxes (or option contracts) that are of the type of Exact.
| catool.exe
/version|/ver|/v catool.exe /help|/h|/v |
The first one is for displaying the version information of the application, and the second is for displaying the help screen.


Polymorphism and HOFs are the Secret Sauce
Refactor arbitrary repeated code patterns …
… into precisely specified and reusable functions
EXERCISE: Iteration
Write a function that squares a list of Int
squares :: [Int] -> [Int]
= ??? squares ns
When you are done you should see
>>> squares [1,2,3,4,5]
1,4,9,16,25] [
Pattern: Iteration
Next, lets write a function that converts a String
to uppercase.
>>> shout "hello"
"HELLO"
Recall that in Haskell, a String
is just a [Char]
.
shout :: [Char] -> [Char]
= ??? shout
Hoogle to see how to transform an individual Char
Iteration
Common strategy: iteratively transform each element of input list
Like humans and monkeys, shout
and squares
share 93% of their DNA
Super common computation pattern!
Abstract Iteration “Pattern” into Function
Remember D.R.Y. (Don’t repeat yourself)
Step 1 Rename all variables to remove accidental differences
-- rename 'squares' to 'foo'
= []
foo [] :xs) = (x * x) : foo xs
foo (x
-- rename 'shout' to 'foo'
= []
foo [] :xs) = (toUpper x) : foo xs foo (x
Step 2 Identify what is different
In
squares
we transformx
tox * x
In
shout
we transformx
toData.Char.toUpper x
Step 3 Make differences a parameter
- Make transform a parameter
f
= []
foo f [] :xs) = (f x) : foo f xs foo f (x
Done We have bottled the computation pattern as foo
(aka map
)
map f [] = []
map f (x:xs) = (f x) : map f xs
map
bottles the common pattern of iteratively transforming a list:
QUIZ
What is the type of map
?
map :: ???
map f [] = []
map f (x:xs) = (f x) : map f xs
A. (Int -> Int) -> [Int] -> [Int]
B. (a -> a) -> [a] -> [a]
C. [a] -> [b]
D. (a -> b) -> [a] -> [b]
E. (a -> b) -> [a] -> [a]
The type precisely describes map
>>> :type map
map :: (a -> b) -> [a] -> [b]
That is, map
takes two inputs
- a transformer of type
a -> b
- a list of values
[a]
and it returns as output
- a list of values
[b]
that can only come by applying f
to each element of the input list.
Reusing the Pattern
Lets reuse the pattern by instantiating the transformer
shout
-- OLD with recursion
shout :: [Char] -> [Char]
= []
shout [] :xs) = Char.toUpper x : shout xs
shout (x
-- NEW with map
shout :: [Char] -> [Char]
= map (???) xs shout xs
squares
-- OLD with recursion
squares :: [Int] -> [Int]
= []
squares [] :xs) = (x * x) : squares xs
squares (x
-- NEW with map
squares :: [Int] -> [Int]
= map (???) xs squares xs
EXERCISE
Suppose I have the following type
type Score = (Int, Int) -- pair of scores for Hw0, Hw1
Use map
to write a function
total :: [Score] -> [Int]
= map (???) xs total xs
such that
>>> total [(10, 20), (15, 5), (21, 22), (14, 16)]
30, 20, 43, 30] [
The Case of the Missing Parameter
Note that we can write shout
like this
shout :: [Char] -> [Char]
= map Char.toUpper shout
Huh. No parameters? Can someone explain?
The Case of the Missing Parameter
In Haskell, the following all mean the same thing
Suppose we define a function
add :: Int -> Int -> Int
= x + y add x y
Now the following all mean the same thing
= add x y
plus x y = add x
plus x = add plus
Why? equational reasoning! In general
= e x
foo x
-- is equivalent to
= e foo
as long as x
doesn’t appear in e
.
Thus, to save some typing, we omit the extra parameter.
Pattern: Reduction
Computation patterns are everywhere lets revisit our old sumList
sumList :: [Int] -> Int
= 0
sumList [] :xs) = x + sumList xs sumList (x
Next, a function that concatenates the String
s in a list
catList :: [String] -> String
= ""
catList [] :xs) = x ++ (catList xs) catList (x
Lets spot the pattern!
Step 1 Rename
= 0
foo [] :xs) = x + foo xs
foo (x
= ""
foo [] :xs) = x ++ foo xs foo (x
Step 2 Identify what is different
???
???
Step 3 Make differences a parameter
= ???
foo p1 p2 [] :xs) = ??? foo p1 p2 (x
EXERCISE: Reduction/Folding
This pattern is commonly called reducing or folding
foldr :: (a -> b -> b) -> b -> [a] -> b
foldr op base [] = base
foldr op base (x:xs) = op x (foldr op base xs)
Can you figure out how sumList
and catList
are just instances of foldr
?
sumList :: [Int] -> Int
= foldr (?op) (?base) xs
sumList xs
catList :: [String] -> String
= foldr (?op) (?base) xs catList xs
Executing foldr
To develop some intuition about foldr
lets “run” it a few times by hand.
foldr op b (a1:a2:a3:a4:[])
==>
`op` (foldr op b (a2:a3:a4:[]))
a1 ==>
`op` (a2 `op` (foldr op b (a3:a4:[])))
a1 ==>
`op` (a2 `op` (a3 `op` (foldr op b (a4:[]))))
a1 ==>
`op` (a2 `op` (a3 `op` (a4 `op` foldr op b [])))
a1 ==>
`op` (a2 `op` (a3 `op` (a4 `op` b))) a1
Look how it mirrors the structure of lists!
(:)
is replaced byop
[]
is replaced bybase
So
foldr (+) 0 (x1:x2:x3:x4:[])
==> x1 + (x2 + (x3 + (x4 + 0))
Typing foldr
foldr :: (a -> b -> b) -> b -> [a] -> b
foldr op base [] = base
foldr op base (x:xs) = op x (foldr op base xs)
foldr
takes as input
- a reducer function of type
a -> b -> b
- a base value of type
b
- a list of values to reduce
[a]
and returns as output
- a reduced value
b
QUIZ
Recall the function to compute the len
of a list
len :: [a] -> Int
= 0
len [] :xs) = 1 + len xs len (x
Which of these is a valid implementation of Len
A. len = foldr (\n -> n + 1) 0
B. len = foldr (\n m -> n + m) 0
C. len = foldr (\_ n -> n + 1) 0
D. len = foldr (\x xs -> 1 + len xs) 0
E. All of the above
The Missing Parameter Revisited
We wrote foldr
as
foldr :: (a -> b -> b) -> b -> [a] -> b
foldr op base [] = base
foldr op base (x:xs) = op x (foldr op base xs)
but can also write this
foldr :: (a -> b -> b) -> b -> [a] -> b
foldr op base = go
where
= base
go [] :xs) = op x (go xs) go (x
Can someone explain where the xs
went missing ?
Trees
Recall the Tree a
type from last time
data Tree a
= Leaf
| Node a (Tree a) (Tree a)
For example here’s a tree
tree2 :: Tree Int
= Node 2 Leaf Leaf
tree2
tree3 :: Tree Int
= Node 3 Leaf Leaf
tree3
tree123 :: Tree Int
= Node 1 tree2 tree3 tree123
Some Functions on Trees
Lets write a function to compute the height
of a tree
height :: Tree a -> Int
Leaf = 0
height Node x l r) = 1 + max (height l) (height l) height (
Here’s another to sum the leaves of a tree:
sumTree :: Tree Int -> Int
Leaf = ???
sumTree Node x l r) = ??? sumTree (
Gathers all the elements that occur as leaves of the tree:
toList :: Tree a -> [a]
Leaf = ???
toList Node x l r) = ??? toList (
Lets give it a whirl
>>> height tree123
2
>>> sumTree tree123
6
>>> toList tree123
1,2,3] [
Pattern: Tree Fold
Can you spot the pattern? Those three functions are almost the same!
Step 1: Rename to maximize similarity
-- height
Leaf = 0
foo Node x l r) = 1 + max (foo l) (foo l)
foo (
-- sumTree
Leaf = 0
foo Node x l r) = foo l + foo r
foo (
-- toList
Leaf = []
foo Node x l r) = x : foo l ++ foo r foo (
Step 2: Identify the differences
- ???
- ???
Step 3 Make differences a parameter
Leaf = ???
foo p1 p2 Node x l r) = ??? foo p1 p2 (
Pattern: Folding on Trees
Leaf = b
tFold op b Node x l r) = op x (tFold op b l) (tFold op b r) tFold op b (
Lets try to work out the type of tFold
!
tFold :: t_op -> t_b -> Tree a -> t_out
QUIZ
Suppose that t :: Tree Int
.
What does tFold (\x y z -> y + z) 1 t
return?
a. 0
b. the largest element in the tree t
c. the height of the tree t
d. the number-of-leaves of the tree t
e. type error
EXERCISE
Write a function to compute the largest element in a tree or 0
if tree is empty or all negative.
treeMax :: Tree Int -> Int
= tFold f b t
treeMax t where
= ???
f = ??? b
Map over Trees
We can also write a tmap
equivalent of map
for Tree
s
treeMap :: (a -> b) -> Tree a -> Tree b
Leaf x) = Leaf (f x)
treeMap f (Node l r) = Node (treeMap f l) (treeMap f r) treeMap f (
which gives
>>> treeMap (\n -> n * n) tree123 -- square all elements of tree
Node 1 (Node 4 Leaf Leaf) (Node 9 Leaf Leaf)
EXERCISE
Recursion is HARD TO READ do we really have to use it ?
Lets rewrite treeMap
using tFold
!
treeMap :: (a -> b) -> Tree a -> Tree b
= tFold op base t
treeMap f t where
= ???
op = ??? base
When you are done, we should get
>>> animals = Node "cow" (Node "piglet" Leaf Leaf) (Leaf "hippo" Leaf Leaf)
>>> treeMap reverse animals
Node "woc" (Node "telgip" Leaf Leaf) (Leaf "oppih" Leaf Leaf)
Examples: foldDir
data Dir a
= Fil a -- ^ A single file named `a`
| Sub a [Dir a] -- ^ A sub-directory name `a` with contents `[Dir a]`
data DirElem a
= SubDir a -- ^ A single Sub-Directory named `a`
| File a -- ^ A single File named `a`
foldDir :: ([a] -> r -> DirElem a -> r) -> r -> Dir a -> r
= go [] r0 dir
foldDir f r0 dir where
Fil a) = f stk r (File a)
go stk r (Sub a ds) = L.foldl' (go stk') r' ds
go stk r (where
= f stk r (SubDir a)
r' = a:stk stk'
foldDir
takes as input
an accumulator
f
of type[a] -> r -> DirElem a -> r
takes as input the path
[a]
, the current resultr
, the nextDirElem [a]
and returns as output the new result
r
an initial value of the result
r0
anddirectory to fold over
dir
And returns the result of running the accumulator over the whole dir
.
Examples: Spotting Patterns In The “Real” World
These patterns in “toy” functions appear regularly in “real” code
Start with beginner’s version riddled with explicit recursion.
Spot the patterns and eliminate recursion using HOFs.
Finally refactor the code to “swizzle” and “unswizzle” without duplication.
Try it yourself
- Rewrite the code that swizzles
Char
to use theMap k v
type inData.Map
Which is more readable? HOFs or Recursion
At first, recursive versions of shout
and squares
are easier to follow
fold
takes a bit of getting used to!
With practice, the higher-order versions become easier
only have to understand specific operations
recursion is lower-level & have to see “loop” structure
worse, potential for making silly off-by-one errors
Indeed, HOFs were the basis of map/reduce
and the big-data revolution
Can parallelize and distribute computation patterns just once
Reuse across hundreds or thousands of instances!


This package provides regression methods to quantify the relation between two measurement methods. In particular it addresses regression problems with errors in both variables and without repeated measurements. The package provides implementations of Deming regression, weighted Deming regression, and Passing-Bablok regression following the CLSI EP09-A3 recommendations for analytical method comparison and bias estimation using patient samples.
| Version: | 1.2.1 |
| Depends: | R (≥ 3.0.0), methods |
| Suggests: | RUnit, XML |
| Published: | 2014-02-12 |
| Author: | Ekaterina Manuilova Andre Schuetzenmeister Fabian Model |
| Maintainer: | Fabian Model <fabian.model at roche.com> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | yes |
| CRAN checks: | mcr results |
| Reference manual: | mcr.pdf |
| Package source: | mcr_1.2.1.tar.gz |
| Windows binaries: | r-devel: mcr_1.2.1.zip, r-release: mcr_1.2.1.zip, r-oldrel: mcr_1.2.1.zip |
| OS X binaries: | r-release: mcr_1.2.1.tgz, r-oldrel: mcr_1.2.1.tgz |
| Old sources: | mcr archive |
Please use the canonical form https://CRAN.R-project.org/package=mcr to link to this page.


ExternalAPI
of the JavaMelody monitoring
This page lists links to the external API of JavaMelody, including how to get the monitoring data in a XML or JSON format over http.
For that, the XStream and XPP3 dependencies are needed in your webapp.
See Documentation.
Warning: The XML and JSON formats are dependent on the internal structure of data in JavaMelody.
By using this XML/JSON format, you are coupled on this specific internal structure, which may change anytime without notice.
JSON format
Statistics
Current requests
System information
XML format
Statistics
Current requests
System information
PNG and last value
JMX value


I learn to code, I code to learn. It is my passion. My everyday.
I'm a software engineering student from Montreal.


Welcome
Hello! My name is Jacob, but known online as Reyzerbit.  When coming up with an online name for gaming and software freelancing, that popped into my head and I decided to go with it.
This webpage is meant to be the center of my online presence. Through this website, you can contact me, request commissions for freelance software jobs, and donate to help me keep developing!
As of right now, I am a junior at BYU Provo, studying as a
CompSci major. I'm married to the love of my life, Felicity, and am also an avid gamer.
I am fluent in Java and C++, with some experience in C#, HTML, and CSS. I am very willing and comfortable with learning new languages however, and am currently looking to expand my repertoire.
If you would like me to join your team or project, feel free to shoot me a message. I love working on cross-platform applications, Minecraft mods and plugins, and creatign websites, and will willingly join any projects associated with those themes.


Methods
encryptedDataExport(passPhrase) → {String}
encryptedDataExport returns a string which represents the encrypted
data of a task.
Parameters:
| Name | Type | Description |
|---|---|---|
passPhrase |
String | A passphrase used for encryption. |
Returns:
A string that is an encrypted version of the task.
- Type
- String
encryptedDataImport(encryptedData, passPhrase)
encryptedDataImport sets the state of the task object from
the encrypted input string.
Parameters:
| Name | Type | Description |
|---|---|---|
encryptedData |
String | The encrypted data. |
passPhrase |
String | The passphrase |
getActivityLog() → {String}
getActivityLog is the "getter" method for getting the activity log
Returns:
The activity log.
- Type
- String
getCompletion() → {Number}
getCompletion is the "getter" method for getting the
completion value.
Returns:
The completion value.
- Type
- Number
getEffort() → {Number}
getEffort is the "getter" method for getting effort
Returns:
The task's effort level.
- Type
- Number
getImportance() → {Number}
getImportance is the "getter" function for a task's importance.
Returns:
The task's importance.
- Type
- Number
getName() → {String}
getName is the "getter" function for a Task's name.
Returns:
The task's name.
- Type
- String
getUrgency() → {Number}
getUrgency is the "getter" function for a task's urgency
Returns:
The task's urgency.
- Type
- Number
setActivityLog(ActivityLog)
setActivityLog is a "setter" method to set the activity log
Parameters:
| Name | Type | Description |
|---|---|---|
ActivityLog |
String | The log to be set. |
setCompletion(Completion)
setCompletion is the "setter" method for setting the completion value.
Parameters:
| Name | Type | Description |
|---|---|---|
Completion |
Number | The completion value. An error object will be thrown if the incoming parameter is null, is NaN, is less than zero, or greater than one hundred. |
setEffort(Effort_in)
setEffort is the "setter" method for setting a task's effort
Parameters:
| Name | Type | Description |
|---|---|---|
Effort_in |
Number | The value to be set. An error object will be thrown if the incoming parameter is null, is NaN, is less than zero, or greater than one hundred. |
setImportance(The)
setImportance is the "setter" function for a task's importance.
Parameters:
| Name | Type | Description |
|---|---|---|
The |
Number | task's importance. An error object will be thrown if the incoming parameter is null, is NaN, is less than zero, or greater than one hundred. |
setName(The)
setName is a "setter" function for a Task's name.
Parameters:
| Name | Type | Description |
|---|---|---|
The |
String | task's name. |
setUrgency(The)
setUrgency is the "setter" function for a Task's urgency.
Parameters:
| Name | Type | Description |
|---|---|---|
The |
Number | task's urgency. An error object will be thrown if the incoming parameter is null, is NaN, is less than zero, or greater than one hundred. |


CVS tool documents: Index
If you are participating in a development project on this site, you must use CVS as the versioning control tool for project source files. This the first in a series of three tool documents covering information and commands pertinent to using CVS.
If you do have cvs login access for a project hosted on this site, first you must set the cvsroot to access the project's source code repository. In your shell or terminal client, type:
:pserver:yourlogin@cvs.projectname.domain.com:/home/main_cvs_dir
substituting your login and project information.
If you are only working on one project at a time, you only have to set cvsroot the first time you log in to CVS.
If you are participating in more than one project and need to access CVS repositories located on different servers, you need to set the cvsroot for each login session access the correct project's source repository.
If you do not have a specific cvs login but wish to look at an open source project's source repository, you may still be able to log in to cvs as "anonymous" by typing:
:pserver:anoncvs@cvs.projectname.domain.com:/home/main_cvs_dir
More about accessing a CVS repository
To log in to CVS, use the following command:
cvs login
Enter your user password when prompted. This should be the same password associated with your user account on this site.
To get a "working copy" of the latest source files, you must check out the source files, a process which copies the files onto your system. First create a directory on your local machine by typing:
mkdir my_working_dir (the directory name of your choosing)
cd my_working_dir
Then, to check out or copy source file from the repository into your newly created local directory, type:
cvs checkout project_name
This top-level module would contain the entire source code tree (that is, the top level directory and any subdirectories) for that part of the project. There is a fairly common module structure for project CVS repositories initially. As the project grows, the project's source "tree" also grows as subdirectories are added to various modules.
To obtain the source code for a particular module called "module-name" within the project named "project_name", specify:
cvs checkout module_name/project_name
More about checking out a working copy of project files
Anyone with cvs read permission can view individual file histories to track revision information by typing:
cvs log filename
The result is a display of the file's revision information, starting with the most current revision, and includes such information as the log message, status, working revision number, and repository revision number.
More about file revision numbers
To see the particulars of a file's modifications between two revisions, after obtaining file revision numbering information from the "cvs log" command's output, type:
cvs diff -r revision_# -r revision_#
The entire file contents display with lines from both versions where differences occur marked by revision number.
Finding out what you and others did
More about diffs and options
More CVS help: Contributing your changes
Back to main Help index


public class Object
extends java.lang.Object
implements java.lang.Cloneable
| Modifier and Type | Class and Description |
|---|---|
static interface |
Object.ObjectClass
This interface defines the available object classes as defined by PKCS#11: DATA, CERTIFICATE,
PUBLIC_KEY, PRIVATE_KEY, SECRET_KEY, HW_FEATURE, DOMAIN_PARAMETERS or VENDOR_DEFINED.
|
static interface |
Object.VendorDefinedObjectBuilder
If an application uses vendor defined objects, it must implement this interface and install
such an object handler using setVendorDefinedObjectBuilder.
|
| Modifier and Type | Field and Description |
|---|---|
protected java.util.Hashtable |
attributeTable_
Contains all attribute objects an object posesses.
|
protected ObjectClassAttribute |
objectClass_
The class type of this object.
|
protected static java.util.Hashtable |
objectClassNames_
A table holding string representations for all known key types.
|
protected long |
objectHandle_
The object handle as given from the PKCS#11 driver.
|
protected static Object.VendorDefinedObjectBuilder |
vendorObjectBuilder_
The currently set vendor defined object builder, or null.
|
| Modifier | Constructor and Description |
|---|---|
|
Object()
The default constructor.
|
protected |
Object(Session session,
long objectHandle)
The subclasses that are used to create objects by reading the attributes from the token should
call this super-constructor first.
|
| Modifier and Type | Method and Description |
|---|---|
protected void |
allocateAttributes()
Allocates the attribute objects for this class and adds them to the attribute table.
|
java.lang.Object |
clone()
Create a (deep) clone of this object.
|
boolean |
equals(java.lang.Object otherObject)
Compares all member variables of this object with the other object.
|
Attribute |
getAttribute(long attribute)
Gets the attribute.
|
java.util.Hashtable |
getAttributeTable()
Return the table that contains all attributes of this object.
|
protected static void |
getAttributeValue(Session session,
long objectHandle,
Attribute attribute)
This method reads the attribute specified by
attribute from the token using the
given session . |
protected static void |
getAttributeValues(Session session,
long objectHandle,
Attribute[] attributes)
This method reads the attributes in a similar way as
getAttributeValue(iaik.pkcs.pkcs11.Session, long, iaik.pkcs.pkcs11.objects.Attribute) , but a complete
array at once. |
static Object |
getInstance(Session session,
long objectHandle)
The object creation mechanism of ObjectAccess uses this method to create an instance of an
PKCS#11 object.
|
LongAttribute |
getObjectClass()
Gets the object class attribute of the PKCS#11 object.
|
static java.lang.String |
getObjectClassName(java.lang.Long objectClass)
Get the given object class as string.
|
long |
getObjectHandle()
Gets the object handle of the underlying PKCS#11 object on the token.
|
java.util.Vector |
getSetAttributes()
This method returns the PKCS#11 attributes of this object.
|
static CK_ATTRIBUTE[] |
getSetAttributes(Object object)
This method returns the PKCS#11 attributes of an object.
|
protected static Object |
getUnknownObject(Session session,
long objectHandle)
Try to create an object which has no or an unkown object class attribute.
|
static Object.VendorDefinedObjectBuilder |
getVendorDefinedObjectBuilder()
Get the currently set vendor-defined object builder.
|
int |
hashCode()
The overriding of this method should ensure that the objects of this class work correctly in a
hashtable.
|
void |
putAttribute(long attribute,
java.lang.Object value)
Allows for putting attributes into the table without knowing the
Attribute at
compile-time. |
protected static void |
putAttributesInTable(Object object)
Put all attributes of the given object into the attributes table of this object.
|
void |
readAttributes(Session session)
Read the values of the attributes of this object from the token.
|
void |
removeAttribute(long attribute)
Removes the attribute.
|
void |
setObjectHandle(long objectHandle)
Sets the object handle of the underlying PKCS#11 object on the token.
|
static void |
setVendorDefinedObjectBuilder(Object.VendorDefinedObjectBuilder builder)
Set a vendor-defined object builder that should be called to create an instance of an
vendor-defined PKCS#11 object; i.e.
|
java.lang.String |
toString()
This method returns a string representation of the current object.
|
java.lang.String |
toString(boolean newline,
boolean withName,
java.lang.String indent)
This method returns a string representation of the current object.
|
protected static Object.VendorDefinedObjectBuilder vendorObjectBuilder_
protected static java.util.Hashtable objectClassNames_
protected java.util.Hashtable attributeTable_
protected ObjectClassAttribute objectClass_
protected long objectHandle_
public Object()
protected Object(Session session, long objectHandle) throws TokenException
session
- The session to use for reading attributes. This session must have the appropriate
rights; i.e. it must be a user-session, if it is a private object.objectHandle
- The object handle as given from the PKCS#111 module.TokenException
- If getting the attributes failed.public static Object getInstance(Session session, long objectHandle) throws TokenException
session
- The session to use for reading attributes. This session must have the appropriate
rights; i.e. it must be a user-session, if it is a private object.objectHandle
- The object handle as given from the PKCS#111 module.TokenException
- If getting the attributes failed.protected static Object getUnknownObject(Session session, long objectHandle) throws TokenException
Object
.session
- The session to use.objectHandle
- The handle of the objectTokenException
- If no object could be created.public static void setVendorDefinedObjectBuilder(Object.VendorDefinedObjectBuilder builder)
builder
- The vendor-defined object builder. Null to clear any previously installed
vendor-defined builder.public static java.lang.String getObjectClassName(java.lang.Long objectClass)
objectClass
- The object class to get as string.public static Object.VendorDefinedObjectBuilder getVendorDefinedObjectBuilder()
protected static void putAttributesInTable(Object object)
object
- The object to handle.protected void allocateAttributes()
public java.lang.Object clone()
clone
in class java.lang.Object
public boolean equals(java.lang.Object otherObject)
equals
in class java.lang.Object
otherObject
- The other object to compare to.public java.util.Hashtable getAttributeTable()
public void putAttribute(long attribute, java.lang.Object value) throws UnsupportedAttributeException
Attribute
at
compile-time.attribute
- the attribute identifier as a long
valuevalue
- the valueUnsupportedAttributeException
- the specified attribute identifier is not available for this Object
instance.java.lang.ClassCastException
- the given value type is not valid for this Attribute
instance.public Attribute getAttribute(long attribute)
attribute
- the attribute identifier as a long
valuepublic void removeAttribute(long attribute)
attribute
- the attribute identifier as a long
valuepublic long getObjectHandle()
public void setObjectHandle(long objectHandle)
objectHandle
- The object handle of the corresponding PKCS#11 object.public LongAttribute getObjectClass()
public java.util.Vector getSetAttributes()
public int hashCode()
hashCode
in class java.lang.Object
public void readAttributes(Session session) throws TokenException
session
- The session handle to use for reading attributes. This session must have the
appropriate rights; i.e. it must be a user-session, if it is a private object.TokenException
- If getting the attributes failed.public java.lang.String toString()
toString
in class java.lang.Object
public java.lang.String toString(boolean newline, boolean withName, java.lang.String indent)
newline
- true if the output should start in a new linewithName
- true if the type of the attribute should be returned tooindent
- the indent to be usedpublic static CK_ATTRIBUTE[] getSetAttributes(Object object) throws PKCS11Exception
object
- The iaik.pkcs.pkcs11.object.Object object to get the attributes from.PKCS11Exception
- If setting the attribute values.protected static void getAttributeValue(Session session, long objectHandle, Attribute attribute) throws PKCS11Exception
attribute
from the token using the
given session
. The object from which to read the attribute is specified using the
objectHandle
. The attribute
will contain the results. If the attempt
to read the attribute returns CKR_ATTRIBUTE_TYPE_INVALID
, this will be indicated
by setting Attribute.setPresent(boolean)
to false
. It
CKR_ATTRIBUTE_SENSITIVE is returned, the attribute object is marked as present (by callign
Attribute.setPresent(boolean)
with true
), and in addition as sensitive by
calling Attribute.setSensitive(boolean)
with true
.session
- The session to use for reading the attribute.objectHandle
- The handle of the object which contains the attribute.attribute
- The object specifying the attribute type (see Attribute.getType()
) and
receiving the attribute value (see Attribute.setCkAttribute(CK_ATTRIBUTE)
).PKCS11Exception
- If getting the attribute failed.protected static void getAttributeValues(Session session, long objectHandle, Attribute[] attributes) throws PKCS11Exception
getAttributeValue(iaik.pkcs.pkcs11.Session, long, iaik.pkcs.pkcs11.objects.Attribute)
, but a complete
array at once. This can lead to performance improvements. If reading all attributes at once
fails, it tries to read each attributes individually.session
- The session to use for reading the attributes.objectHandle
- The handle of the object which contains the attributes.attributes
- The objects specifying the attribute types (see Attribute.getType()
) and
receiving the attribute values (see Attribute.setCkAttribute(CK_ATTRIBUTE)
).PKCS11Exception
- If getting the attributes failed.
IAIK JavaSecurity Website http://jce.iaik.tugraz.at/
IAIK at Graz University of Technology, Austria, Europe
Copyright 2001-2004, IAIK, Graz University of Technology, Inffeldgasse 16a, 8010 Graz, Austria. All Rights Reserved.
version 1.4


Class Derivatives<T>
Keeps track of derivatives
Implements
Inherited Members
Namespace: SpiceSharpBehavioral.Parsers
Assembly: SpiceSharpBehavioral.dll
Syntax
public abstract class Derivatives<T> : IEquatable<Derivatives<T>>
Type Parameters
| Name | Description |
|---|---|
| T |
Constructors
Derivatives()
Initializes a new instance of the Derivatives<T> class.
Declaration
public Derivatives()
Derivatives(Int32)
Initializes a new instance of the Derivatives<T> class.
Declaration
public Derivatives(int capacity)
Parameters
| Type | Name | Description |
|---|---|---|
| System.Int32 | capacity | The capacity. |
Properties
Count
Gets the number of derivatives.
Declaration
public int Count { get; }
Property Value
| Type | Description |
|---|---|
| System.Int32 | The count. |
FudgeFactor
Gets or sets the fudge factor for numerical edge-cases.
Declaration
public static double FudgeFactor { get; set; }
Property Value
| Type | Description |
|---|---|
| System.Double | The fudge factor. |
Remarks
One should not be able to divide by 0, or raise 0 to a negative power. However, the simulator may not know this, so we introduce a fudge factor to remove this. If the exact solution is expected, use 0 as the fudge factor.
Item[Int32]
Gets or sets the derivative at the specified index.
Declaration
public T this[int index] { get; set; }
Parameters
| Type | Name | Description |
|---|---|---|
| System.Int32 | index | The index. |
Property Value
| Type | Description |
|---|---|
| T | The System.Linq.Expressions.Expression. |
Methods
Add(Derivatives<T>)
Add derivatives.
Declaration
public abstract Derivatives<T> Add(Derivatives<T> b)
Parameters
| Type | Name | Description |
|---|---|---|
| Derivatives<T> | b | The other operand. |
Returns
| Type | Description |
|---|---|
| Derivatives<T> | The sum. |
And(Derivatives<T>)
And the derivatives.
Declaration
public abstract Derivatives<T> And(Derivatives<T> b)
Parameters
| Type | Name | Description |
|---|---|---|
| Derivatives<T> | b | The other operand. |
Returns
| Type | Description |
|---|---|
| Derivatives<T> | The derivatives. |
Divide(Derivatives<T>)
Divide derivatives.
Declaration
public abstract Derivatives<T> Divide(Derivatives<T> b)
Parameters
| Type | Name | Description |
|---|---|---|
| Derivatives<T> | b | The other operand. |
Returns
| Type | Description |
|---|---|
| Derivatives<T> | The divided result. |
Equal(Derivatives<T>)
Check for equality.
Declaration
public abstract Derivatives<T> Equal(Derivatives<T> b)
Parameters
| Type | Name | Description |
|---|---|---|
| Derivatives<T> | b | The other operand. |
Returns
| Type | Description |
|---|---|
| Derivatives<T> | A value representing true if equal. |
Equals(Derivatives<T>)
Check equality.
Declaration
public bool Equals(Derivatives<T> obj)
Parameters
| Type | Name | Description |
|---|---|---|
| Derivatives<T> | obj | The other object. |
Returns
| Type | Description |
|---|---|
| System.Boolean |
Equals(Object)
Check equality.
Declaration
public override bool Equals(object obj)
Parameters
| Type | Name | Description |
|---|---|---|
| System.Object | obj | The other object. |
Returns
| Type | Description |
|---|---|
| System.Boolean |
Overrides
GetHashCode()
Gets a hash code
Declaration
public override int GetHashCode()
Returns
| Type | Description |
|---|---|
| System.Int32 |
Overrides
GreaterOrEqual(Derivatives<T>)
Check greater or equal.
Declaration
public abstract Derivatives<T> GreaterOrEqual(Derivatives<T> b)
Parameters
| Type | Name | Description |
|---|---|---|
| Derivatives<T> | b | The operand. |
Returns
| Type | Description |
|---|---|
| Derivatives<T> | A value representing true if this is greater or equal. |
GreaterThan(Derivatives<T>)
Check greater than.
Declaration
public abstract Derivatives<T> GreaterThan(Derivatives<T> b)
Parameters
| Type | Name | Description |
|---|---|---|
| Derivatives<T> | b | The other operand. |
Returns
| Type | Description |
|---|---|
| Derivatives<T> | A value representing true if this is greater. |
IfThenElse(Derivatives<T>, Derivatives<T>)
Conditional derivatives.
Declaration
public abstract Derivatives<T> IfThenElse(Derivatives<T> iftrue, Derivatives<T> iffalse)
Parameters
| Type | Name | Description |
|---|---|---|
| Derivatives<T> | iftrue | Argument if true. |
| Derivatives<T> | iffalse | Argument if false. |
Returns
| Type | Description |
|---|---|
| Derivatives<T> | The derivatives. |
LessOrEqual(Derivatives<T>)
Check less or equal.
Declaration
public abstract Derivatives<T> LessOrEqual(Derivatives<T> b)
Parameters
| Type | Name | Description |
|---|---|---|
| Derivatives<T> | b | The other operand. |
Returns
| Type | Description |
|---|---|
| Derivatives<T> | A value representing true if this is less or equal. |
LessThan(Derivatives<T>)
Check less than.
Declaration
public abstract Derivatives<T> LessThan(Derivatives<T> b)
Parameters
| Type | Name | Description |
|---|---|---|
| Derivatives<T> | b | The other operand. |
Returns
| Type | Description |
|---|---|
| Derivatives<T> | A value representing true if this is less. |
Modulo(Derivatives<T>)
Modulo operation on derivatives.
Declaration
public abstract Derivatives<T> Modulo(Derivatives<T> b)
Parameters
| Type | Name | Description |
|---|---|---|
| Derivatives<T> | b | The other operand. |
Returns
| Type | Description |
|---|---|
| Derivatives<T> | The remainder of the division. |
Multiply(Derivatives<T>)
Multiply derivatives.
Declaration
public abstract Derivatives<T> Multiply(Derivatives<T> b)
Parameters
| Type | Name | Description |
|---|---|---|
| Derivatives<T> | b | The other operand. |
Returns
| Type | Description |
|---|---|
| Derivatives<T> | The multiplied result. |
Negate()
Negate the derivatives.
Declaration
public abstract Derivatives<T> Negate()
Returns
| Type | Description |
|---|---|
| Derivatives<T> | The derivatives. |
Not()
Not (binary) the derivatives.
Declaration
public abstract Derivatives<T> Not()
Returns
| Type | Description |
|---|---|
| Derivatives<T> | The derivatives. |
NotEqual(Derivatives<T>)
Check for inequality.
Declaration
public abstract Derivatives<T> NotEqual(Derivatives<T> b)
Parameters
| Type | Name | Description |
|---|---|---|
| Derivatives<T> | b | The other operand. |
Returns
| Type | Description |
|---|---|
| Derivatives<T> | A value representing true if not equal. |
Or(Derivatives<T>)
Or the derivatives.
Declaration
public abstract Derivatives<T> Or(Derivatives<T> b)
Parameters
| Type | Name | Description |
|---|---|---|
| Derivatives<T> | b | The other operand. |
Returns
| Type | Description |
|---|---|
| Derivatives<T> | The derivatives. |
Pow(Derivatives<T>)
Raises the derivatives to a power.
Declaration
public abstract Derivatives<T> Pow(Derivatives<T> exponent)
Parameters
| Type | Name | Description |
|---|---|---|
| Derivatives<T> | exponent | The exponent. |
Returns
| Type | Description |
|---|---|
| Derivatives<T> | The raised power. |
Subtract(Derivatives<T>)
Subtract derivatives.
Declaration
public abstract Derivatives<T> Subtract(Derivatives<T> b)
Parameters
| Type | Name | Description |
|---|---|---|
| Derivatives<T> | b | The other operand. |
Returns
| Type | Description |
|---|---|
| Derivatives<T> | The difference. |
ToString()
Convert to a string
Declaration
public override string ToString()
Returns
| Type | Description |
|---|---|
| System.String |


{% extends 'main_page.html' %} {% block body %}
A database is present. These are your available collections:


About
Events
Twitter
Mastodon
GitHub
Meetup.com
Upcoming Meetups
MadPy Social: Great Dane Hilldale
— 2023-09-14
Past Meetups
Dashboards with Live Updates for Real-Time Analytics
— 2023-08-10
Lightning Talks
— 2023-07-13
Workshop: Interactive Plots Using Plotly and Streamlit
— 2023-06-08
For Your Eyes Only: An Introduction to Cryptography with Python
— 2023-05-11
Serving ML Models at Scale with FastAPI
— 2023-04-13
Code Cleanup
— 2023-03-09
Serving ML Models at Scale with FastAPI [postponed -- weather]
— 2023-02-09
Lightning Talks
— 2023-01-12
pytest: It's What's For Testing
— 2022-12-08
Clean Code and Test Driven Development: A Primer
— 2022-11-10
Blue Moon Gathering
— 2022-10-13
Capital Brewery Gathering
— 2022-09-15
Olbrich Biergarten Gathering
— 2022-08-11
pytest: It's What's For Testing [postponed -- obviously]
— 2020-03-12
A Deep Dive into Django 3.0
— 2020-02-06
Interactive Visualizations with Python
— 2020-01-09
Lightning talks from the machine learning hackathon
— 2019-12-12
Machine Learning Hackathon
— 2019-11-14
Choosing the right data file format for numerical computing
— 2019-10-10
Accelerating Numerical Python with Numba
— 2019-09-12
The Python Data Model
— 2019-08-08
Lightning talks on hobby projects
— 2019-07-11


[viewBag] title = "Social Media Marketing" url = "/social-media-marketing" layout = "staticPage" is_hidden = 0 navigation_hidden = 0 robot_index = "index" robot_follow = "follow" localeUrl[ru] = "/social-media-marketing" ==
Social Media Marketing


| ActivationConfigPropertyOverride |
|
| AnnotationDeployer |
|
| AnnotationDeployer.DiscoverAnnotatedBeans |
|
| AnnotationDeployer.FieldMember |
Implementation of Member for java.lang.reflect.Field
Used for injection targets that are annotated fields
|
| AnnotationDeployer.FilledMember |
|
| AnnotationDeployer.MethodMember |
Implementation of Member for java.lang.reflect.Method
Used for injection targets that are annotated methods
|
| AnnotationDeployer.ProcessAnnotatedBeans |
|
| AnnotationDeployer.ProcessAnnotatedBeans.AccessTimeoutHandler |
|
| AnnotationDeployer.ProcessAnnotatedBeans.LockHandler |
|
| AnnotationDeployer.ProcessAnnotatedBeans.TransactionAttributeHandler |
|
| AnnotationDeployer.ProvidedJAXRSApplication |
|
| AppContextConfigDeployer |
|
| ApplicationComposerDeployer |
|
| ApplicationProperties |
TODO Check for app.properties
|
| ApplyOpenejbJar |
|
| AppModule |
|
| AppValidator |
|
| AutoConfig |
|
| AutoDeployer |
|
| BaseConvertDefinitions |
|
| BeanProperties |
|
| BuiltInEnvironmentEntries |
|
| Cipher |
|
| CleanEnvEntries |
|
| ClearEmptyMappedName |
|
| ClientModule |
|
| CompManagedBean |
|
| ConfigurableClasspathArchive |
|
| ConfigurableClasspathArchive.FakeModule |
|
| ConfigurationDeployer |
|
| ConfigurationFactory |
|
| ConfigurationFactory.Chain |
|
| ConfigurationFactory.ProxyBeanClassUpdate |
|
| ConfigUtils |
|
| ConnectorModule |
|
| ContainerUtils |
|
| ContextRef |
|
| ConvertDataSourceDefinitions |
|
| ConvertJMSConnectionFactoryDefinitions |
|
| ConvertJMSDestinationDefinitions |
|
| Deploy |
Deploy EJB beans
|
| DeploymentLoader |
|
| DeploymentLoader.ExternalConfiguration |
|
| DeploymentModule.ID |
|
| DeploymentsResolver |
|
| DeploymentsResolver.ClasspathSearcher |
|
| EffectiveTomEEXml |
Will dump properties once resolved.
|
| EjbJarInfoBuilder |
|
| EjbModule |
Class is to remain "dumb" and should not have deployment logic added to it.
|
| EmptyEjbJar |
|
| EnvEntriesPropertiesDeployer |
Read in all the properties for an app's META-INF/env-entries.properties file
and create tags for each in the component's enc.
|
| FinderFactory |
|
| FinderFactory.DebugArchive |
|
| FinderFactory.DoLoadClassesArchive |
|
| FinderFactory.ModuleLimitedFinder |
|
| FinderFactory.OpenEJBAnnotationFinder |
|
| GeneratedClientModules |
This class encompasses a little technique that saves lots of architecture rework.
|
| GeneratedClientModules.Add |
Add the auto-generated and linked ClientModule from each EjbModule
|
| GeneratedClientModules.Prune |
Clean up any that didn't turn out to have any actual ejb clients
|
| GeronimoMappedName |
|
| InitEjbDeployments |
|
| JndiEncInfoBuilder |
|
| JPAPropertyConverter |
|
| JPAPropertyConverter.Pair |
|
| LegacyProcessor |
|
| LinkBuiltInTypes |
|
| MappedNameBuilder |
|
| MBeanDeployer |
|
| MergeWebappJndiContext |
In a webapp all ejbs will share the JNDI namespace of the servlets
This means no private namespace for each EJB.
|
| Module |
|
| ModuleProperties |
|
| NewLoaderLogic |
|
| NewLoaderLogic.OptimizedExclusionFilter |
|
| OpenEjb2Conversion |
|
| OpenEJBDeploymentManager |
|
| OpenEJBDeploymentManager.DeploymentStatusImpl |
|
| OpenEJBDeploymentManager.TargetImpl |
|
| OpenEJBDeploymentManager.TargetModuleIDImpl |
|
| OutputGeneratedDescriptors |
|
| PersistenceContextAnnFactory |
|
| PersistenceModule |
|
| PersistenceUnitLinkResolver |
|
| PojoConfiguration |
|
| QuickJarsTxtParser |
|
| QuickServerXmlParser |
|
| ReadDescriptors |
|
| ReadDescriptors.StringSource |
|
| ReadDescriptors.UrlSource |
|
| RemoteServer |
NOTE: Do not add inner or anonymous classes or a dependency without updating ExecMojo
|
| RemoteServer.CleanUpThread |
|
| ReportValidationResults |
|
| ResourcesModule |
|
| ScanUtil |
|
| ScanUtil.ScanHandler |
|
| ServiceUtils |
|
| ServiceUtils.ProviderInfo |
|
| SunConversion |
|
| SystemAppInfo |
|
| SystemApps |
Avoids the needs to scan the classpath to load system applications that are used
for deploy tools and other command line tooling.
|
| SystemPropertiesOverride |
Anything starting with "openejb" or "tomee" trumps other properties
so "openejb.foo" always beats "foo"
|
| SystemProperty |
|
| TldScanner |
TLD file urls cached on a per classloader basis.
|
| Undeploy |
UnDeploy EJB beans
|
| ValidateModules |
|
| ValidationContext |
|
| VmDeploymentFactory |
|
| VmDeploymentManager |
|
| VmDeploymentManager.DeploymentStatusImpl |
|
| VmDeploymentManager.TargetImpl |
|
| VmDeploymentManager.TargetModuleIDImpl |
|
| WebappAggregatedArchive |
|
| WebappAggregatedArchive.ScanXmlSaverFilter |
|
| WebModule |
|
| WlsConversion |
|
| WsDeployer |
|