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public interface RealVector
Interface defining a real-valued vector with basic algebraic operations.
vector element indexing is 0-based -- e.g., getEntry(0)
returns the first element of the vector.
The various mapXxx
and mapXxxToSelf
methods operate
on vectors element-wise, i.e. they perform the same operation (adding a scalar,
applying a function ...) on each element in turn. The mapXxx
versions create a new vector to hold the result and do not change the instance.
The mapXxxToSelf
versions use the instance itself to store the
results, so the instance is changed by these methods. In both cases, the result
vector is returned by the methods, this allows to use the fluent API
style, like this:
RealVector result = v.mapAddToSelf(3.0).mapTanToSelf().mapSquareToSelf();
Remark on the deprecated mapXxx
and mapXxxToSelf
methods: In
Commons-Math v3.0, the same functionality will be achieved by directly using the
map(UnivariateRealFunction)
and mapToSelf(UnivariateRealFunction)
together with new function objects (not available in v2.2).
| Nested Class Summary | |
|---|---|
static class |
RealVector.Entry
Class representing a modifiable entry in the vector. |
| Method Summary | |
|---|---|
RealVector |
add(double[] v)
Compute the sum of this vector and v . |
RealVector |
add(RealVector v)
Compute the sum of this vector and v . |
RealVector |
append(double d)
Construct a vector by appending a double to this vector. |
RealVector |
append(double[] a)
Construct a vector by appending a double array to this vector. |
RealVector |
append(RealVector v)
Construct a vector by appending a vector to this vector. |
RealVector |
copy()
Returns a (deep) copy of this vector. |
double |
dotProduct(double[] v)
Compute the dot product. |
double |
dotProduct(RealVector v)
Compute the dot product. |
RealVector |
ebeDivide(double[] v)
Element-by-element division. |
RealVector |
ebeDivide(RealVector v)
Element-by-element division. |
RealVector |
ebeMultiply(double[] v)
Element-by-element multiplication. |
RealVector |
ebeMultiply(RealVector v)
Element-by-element multiplication. |
double[] |
getData()
Returns vector entries as a double array. |
int |
getDimension()
Returns the size of the vector. |
double |
getDistance(double[] v)
Distance between two vectors. |
double |
getDistance(RealVector v)
Distance between two vectors. |
double |
getEntry(int index)
Returns the entry in the specified index. |
double |
getL1Distance(double[] v)
Distance between two vectors. |
double |
getL1Distance(RealVector v)
Distance between two vectors. |
double |
getL1Norm()
Returns the L1 norm of the vector. |
double |
getLInfDistance(double[] v)
Distance between two vectors. |
double |
getLInfDistance(RealVector v)
Distance between two vectors. |
double |
getLInfNorm()
Returns the L∞ norm of the vector. |
double |
getNorm()
Returns the L2 norm of the vector. |
RealVector |
getSubVector(int index,
int n)
Get a subvector from consecutive elements. |
boolean |
isInfinite()
Check whether any coordinate of this vector is infinite and none are NaN . |
boolean |
isNaN()
Check whether any coordinate of this vector is NaN . |
Iterator<RealVector.Entry> |
iterator()
Generic dense iterator. |
RealVector |
map(UnivariateRealFunction function)
Acts as if implemented as: |
RealVector |
mapAbs()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapAbsToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapAcos()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapAcosToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapAdd(double d)
Add a value to each entry. |
RealVector |
mapAddToSelf(double d)
Add a value to each entry. |
RealVector |
mapAsin()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapAsinToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapAtan()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapAtanToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapCbrt()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapCbrtToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapCeil()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapCeilToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapCos()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapCosh()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapCoshToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapCosToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapDivide(double d)
Divide each entry. |
RealVector |
mapDivideToSelf(double d)
Divide each entry. |
RealVector |
mapExp()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapExpm1()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapExpm1ToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapExpToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapFloor()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapFloorToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapInv()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapInvToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapLog()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapLog10()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapLog10ToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapLog1p()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapLog1pToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapLogToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapMultiply(double d)
Multiply each entry. |
RealVector |
mapMultiplyToSelf(double d)
Multiply each entry. |
RealVector |
mapPow(double d)
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapPowToSelf(double d)
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapRint()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapRintToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapSignum()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapSignumToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapSin()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapSinh()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapSinhToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapSinToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapSqrt()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapSqrtToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapSubtract(double d)
Subtract a value from each entry. |
RealVector |
mapSubtractToSelf(double d)
Subtract a value from each entry. |
RealVector |
mapTan()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapTanh()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapTanhToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapTanToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapToSelf(UnivariateRealFunction function)
Acts as if it is implemented as: |
RealVector |
mapUlp()
Deprecated. in 2.2 (to be removed in 3.0). |
RealVector |
mapUlpToSelf()
Deprecated. in 2.2 (to be removed in 3.0). |
RealMatrix |
outerProduct(double[] v)
Compute the outer product. |
RealMatrix |
outerProduct(RealVector v)
Compute the outer product. |
RealVector |
projection(double[] v)
Find the orthogonal projection of this vector onto another vector. |
RealVector |
projection(RealVector v)
Find the orthogonal projection of this vector onto another vector. |
void |
set(double value)
Set all elements to a single value. |
void |
setEntry(int index,
double value)
Set a single element. |
void |
setSubVector(int index,
double[] v)
Set a set of consecutive elements. |
void |
setSubVector(int index,
RealVector v)
Set a set of consecutive elements. |
Iterator<RealVector.Entry> |
sparseIterator()
Specialized implementations may choose to not iterate over all dimensions, either because those values are unset, or are equal to defaultValue(), or are small enough to be ignored for the purposes of iteration. |
RealVector |
subtract(double[] v)
Subtract v from this vector. |
RealVector |
subtract(RealVector v)
Subtract v from this vector. |
double[] |
toArray()
Convert the vector to a double array. |
void |
unitize()
Converts this vector into a unit vector. |
RealVector |
unitVector()
Creates a unit vector pointing in the direction of this vector. |
| Method Detail |
|---|
RealVector mapToSelf(UnivariateRealFunction function) throws FunctionEvaluationException
Entry e = null; for(Iteratorit = iterator(); it.hasNext(); e = it.next()) { e.setValue(function.value(e.getValue())); }
function
- Function to apply to each entry.
FunctionEvaluationException
- if the function throws it.RealVector map(UnivariateRealFunction function) throws FunctionEvaluationException
return copy().map(function);
function
- Function to apply to each entry.
FunctionEvaluationException
- if the function throws it.Iterator<RealVector.Entry> iterator()
Iterator<RealVector.Entry> sparseIterator()
iterator()
.
RealVector copy()
RealVector add(RealVector v)
v
.
v
- Vector to be added.
this
+ v
.
DimensionMismatchException
- if v
is not the same size as this vector.RealVector add(double[] v)
v
.
v
- Vector to be added.
this
+ v
.
DimensionMismatchException
- if v
is not the same size as this vector.RealVector subtract(RealVector v)
v
from this vector.
v
- Vector to be subtracted.
this
- v
.
DimensionMismatchException
- if v
is not the same size as this vector.RealVector subtract(double[] v)
v
from this vector.
v
- Vector to be subtracted.
this
- v
.
DimensionMismatchException
- if v
is not the same size as this vector.RealVector mapAdd(double d)
d
- Value to be added to each entry.
this
+ d
.RealVector mapAddToSelf(double d)
d
- Value to be added to each entry.
this
.RealVector mapSubtract(double d)
d
- Value to be subtracted.
this
- d
.RealVector mapSubtractToSelf(double d)
d
- Value to be subtracted.
this
.RealVector mapMultiply(double d)
d
- Multiplication factor.
this
* d
.RealVector mapMultiplyToSelf(double d)
d
- Multiplication factor.
this
.RealVector mapDivide(double d)
d
- Value to divide by.
this
/ d
.RealVector mapDivideToSelf(double d)
d
- Value to divide by.
this
.@Deprecated RealVector mapPow(double d)
d
- Operator value.
@Deprecated RealVector mapPowToSelf(double d)
d
- Operator value.
@Deprecated RealVector mapExp()
Math.exp(double)
function to each entry.
@Deprecated RealVector mapExpToSelf()
Math.exp(double)
operation to each entry.
The instance is changed in-place.
@Deprecated RealVector mapExpm1()
Math.expm1(double)
function to each entry.
@Deprecated RealVector mapExpm1ToSelf()
Math.expm1(double)
function to each entry.
The instance is changed by this method.
@Deprecated RealVector mapLog()
Math.log(double)
function to each entry.
@Deprecated RealVector mapLogToSelf()
Math.log(double)
function to each entry.
The instance is changed by this method.
@Deprecated RealVector mapLog10()
Math.log10(double)
function to each entry.
@Deprecated RealVector mapLog10ToSelf()
Math.log10(double)
function to each entry.
The instance is changed by this method.
@Deprecated RealVector mapLog1p()
Math.log1p(double)
function to each entry.
@Deprecated RealVector mapLog1pToSelf()
Math.log1p(double)
function to each entry.
The instance is changed by this method.
@Deprecated RealVector mapCosh()
Math.cosh(double)
function to each entry.
@Deprecated RealVector mapCoshToSelf()
Math.cosh(double)
function to each entry.
The instance is changed by this method.
@Deprecated RealVector mapSinh()
Math.sinh(double)
function to each entry.
@Deprecated RealVector mapSinhToSelf()
Math.sinh(double)
function to each entry.
The instance is changed by this method.
@Deprecated RealVector mapTanh()
Math.tanh(double)
function to each entry.
@Deprecated RealVector mapTanhToSelf()
Math.tanh(double)
function to each entry.
The instance is changed by this method.
@Deprecated RealVector mapCos()
Math.cos(double)
function to each entry.
@Deprecated RealVector mapCosToSelf()
Math.cos(double)
function to each entry.
The instance is changed by this method.
@Deprecated RealVector mapSin()
Math.sin(double)
function to each entry.
@Deprecated RealVector mapSinToSelf()
Math.sin(double)
function to each entry.
The instance is changed by this method.
@Deprecated RealVector mapTan()
Math.tan(double)
function to each entry.
@Deprecated RealVector mapTanToSelf()
Math.tan(double)
function to each entry.
The instance is changed by this method.
@Deprecated RealVector mapAcos()
Math.acos(double)
function to each entry.
@Deprecated RealVector mapAcosToSelf()
Math.acos(double)
function to each entry.
The instance is changed by this method.
@Deprecated RealVector mapAsin()
Math.asin(double)
function to each entry.
@Deprecated RealVector mapAsinToSelf()
Math.asin(double)
function to each entry.
The instance is changed by this method.
@Deprecated RealVector mapAtan()
Math.atan(double)
function to each entry.
@Deprecated RealVector mapAtanToSelf()
Math.atan(double)
function to each entry.
The instance is changed by this method.
@Deprecated RealVector mapInv()
@Deprecated RealVector mapInvToSelf()
The instance is changed by this method.
@Deprecated RealVector mapAbs()
Math.abs(double)
function to each entry.
@Deprecated RealVector mapAbsToSelf()
Math.abs(double)
function to each entry.
The instance is changed by this method.
@Deprecated RealVector mapSqrt()
Math.sqrt(double)
function to each entry.
@Deprecated RealVector mapSqrtToSelf()
Math.sqrt(double)
function to each entry.
The instance is changed by this method.
@Deprecated RealVector mapCbrt()
Math.cbrt(double)
function to each entry.
@Deprecated RealVector mapCbrtToSelf()
Math.cbrt(double)
function to each entry.
The instance is changed by this method.
@Deprecated RealVector mapCeil()
Math.ceil(double)
function to each entry.
@Deprecated RealVector mapCeilToSelf()
Math.ceil(double)
function to each entry.
The instance is changed by this method.
@Deprecated RealVector mapFloor()
Math.floor(double)
function to each entry.
@Deprecated RealVector mapFloorToSelf()
Math.floor(double)
function to each entry.
The instance is changed by this method.
@Deprecated RealVector mapRint()
Math.rint(double)
function to each entry.
@Deprecated RealVector mapRintToSelf()
Math.rint(double)
function to each entry.
The instance is changed by this method.
@Deprecated RealVector mapSignum()
Math.signum(double)
function to each entry.
@Deprecated RealVector mapSignumToSelf()
Math.signum(double)
function to each entry.
The instance is changed by this method.
@Deprecated RealVector mapUlp()
Math.ulp(double)
function to each entry.
@Deprecated RealVector mapUlpToSelf()
Math.ulp(double)
function to each entry.
The instance is changed by this method.
RealVector ebeMultiply(RealVector v)
v
- vector by which instance elements must be multiplied
DimensionMismatchException
- if v
is not the same size as this vector.RealVector ebeMultiply(double[] v)
v
- vector by which instance elements must be multiplied
DimensionMismatchException
- if v
is not the same size as this vector.RealVector ebeDivide(RealVector v)
v
- vector by which instance elements must be divided
DimensionMismatchException
- if v
is not the same size as this vector.RealVector ebeDivide(double[] v)
v
- vector by which instance elements must be divided
DimensionMismatchException
- if v
is not the same size as this vector.double[] getData()
double dotProduct(RealVector v)
v
- vector with which dot product should be computed
DimensionMismatchException
- if v
is not the same size as this vector.double dotProduct(double[] v)
v
- vector with which dot product should be computed
DimensionMismatchException
- if v
is not the same size as this vector.double getNorm()
The L2 norm is the root of the sum of the squared elements.
getL1Norm()
,
getLInfNorm()
,
getDistance(RealVector)
double getL1Norm()
The L1 norm is the sum of the absolute values of elements.
getNorm()
,
getLInfNorm()
,
getL1Distance(RealVector)
double getLInfNorm()
The L∞ norm is the max of the absolute values of elements.
getNorm()
,
getL1Norm()
,
getLInfDistance(RealVector)
double getDistance(RealVector v)
This method computes the distance consistent with the L2 norm, i.e. the square root of the sum of elements differences, or euclidian distance.
v
- vector to which distance is requested
DimensionMismatchException
- if v
is not the same size as this vector.getL1Distance(RealVector)
,
getLInfDistance(RealVector)
,
getNorm()
double getDistance(double[] v)
This method computes the distance consistent with the L2 norm, i.e. the square root of the sum of elements differences, or euclidian distance.
v
- vector to which distance is requested
DimensionMismatchException
- if v
is not the same size as this vector.getL1Distance(double[])
,
getLInfDistance(double[])
,
getNorm()
double getL1Distance(RealVector v)
This method computes the distance consistent with L1 norm, i.e. the sum of the absolute values of elements differences.
v
- vector to which distance is requested
DimensionMismatchException
- if v
is not the same size as this vector.getDistance(RealVector)
,
getLInfDistance(RealVector)
,
getL1Norm()
double getL1Distance(double[] v)
This method computes the distance consistent with L1 norm, i.e. the sum of the absolute values of elements differences.
v
- vector to which distance is requested
DimensionMismatchException
- if v
is not the same size as this vector.getDistance(double[])
,
getLInfDistance(double[])
,
getL1Norm()
double getLInfDistance(RealVector v)
This method computes the distance consistent with L∞ norm, i.e. the max of the absolute values of elements differences.
v
- vector to which distance is requested
DimensionMismatchException
- if v
is not the same size as this vector.getDistance(RealVector)
,
getL1Distance(RealVector)
,
getLInfNorm()
double getLInfDistance(double[] v)
This method computes the distance consistent with L∞ norm, i.e. the max of the absolute values of elements differences.
v
- vector to which distance is requested
DimensionMismatchException
- if v
is not the same size as this vector.getDistance(double[])
,
getL1Distance(double[])
,
getLInfNorm()
RealVector unitVector()
The instance is not changed by this method.
ArithmeticException
- if the norm is nullvoid unitize()
The instance itself is changed by this method.
ArithmeticException
- if the norm is zero.RealVector projection(RealVector v)
v
- vector onto which instance must be projected
DimensionMismatchException
- if v
is not the same size as this vector.RealVector projection(double[] v)
v
- vector onto which instance must be projected
DimensionMismatchException
- if v
is not the same size as this vector.RealMatrix outerProduct(RealVector v)
v
- vector with which outer product should be computed
DimensionMismatchException
- if v
is not the same size as this vector.RealMatrix outerProduct(double[] v)
v
- vector with which outer product should be computed
DimensionMismatchException
- if v
is not the same size as this vector.double getEntry(int index)
index
- Index location of entry to be fetched.
index
.
OutOfRangeException
- if the index is not valid.setEntry(int, double)
void setEntry(int index, double value)
index
- element index.value
- new value for the element.
OutOfRangeException
- if the index is not valid.getEntry(int)
int getDimension()
RealVector append(RealVector v)
v
- vector to append to this one.
RealVector append(double d)
d
- double to append.
RealVector append(double[] a)
a
- double array to append.
RealVector getSubVector(int index, int n)
index
- index of first element.n
- number of elements to be retrieved.
OutOfRangeException
- if the index is not valid.void setSubVector(int index, RealVector v)
index
- index of first element to be set.v
- vector containing the values to set.
OutOfRangeException
- if the index is not valid.setSubVector(int, double[])
void setSubVector(int index, double[] v)
index
- index of first element to be set.v
- vector containing the values to set.
OutOfRangeException
- if the index is not valid.setSubVector(int, RealVector)
void set(double value)
value
- single value to set for all elementsdouble[] toArray()
The array is independent from vector data, it's elements are copied.
boolean isNaN()
NaN
.
true
if any coordinate of this vector is NaN
,
false
otherwise.boolean isInfinite()
NaN
.
true
if any coordinate of this vector is infinite and
none are NaN
, false
otherwise.
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Dry conditions cause worry about salmon runs, fires
GRANTS PASS, Ore. (AP) - Conditions are dry in southern Oregon.
The Grants Pass Daily Courier reports that with streams running at a trickle, fish biologists are worried about access for spawning salmon. Fire officials have asked the public to avoid outdoor burning until it rains.
Ryan Battleson, biologist for the Oregon Department of Fish and Wildlife in Central Point, said small streams need more water to provide habitat for juvenile coho and steelhead.
No rain is forecast for at least a week. October’s 0.61 inches of rain in Grants Pass, Oregon, was about 25% of average.
The dry conditions have also slowed prescribed burning and slash pile burning at lower elevations.
The fire season ended Oct. 1 but Shelly Hoffer of the Oregon Department of Forestry said the department is still putting out wildfires.
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● Information From here (.pdf) NB! More text ● Information From here(.pdf), Video is HERE . ● Infromation From here (.pdf) ● Wikipedia.org link From here ● Information From here


{% extends "base.html" %} {% block body %}
The SUMSARIZER tool helps researchers gain insight into usage of cooking stoves from data collected by SUMS by faster and more accurate transformation of raw temperature readings into cooking events.
“The Stove Use Monitoring System (SUMS) provides information on adoption of new technologies and their effect on cooking habits. SUMS are based on low-cost commercially available temperature loggers coupled with our fit-for-purpose processing software developed with the Kirk Smith Research Group at the University of California-Berkeley. By recording stove temperature, SUMS provides insights into usage patterns, number of meals cooked and time of use.”
The raw data that SUMs collect is not that useful by itself: it must be analyzed to determine when someone is cooking and for how long. This turns out to be difficult to automate and tedious to do by hand.
The SUMSARIZER uses machine learning to turn a small amount of work into a full analysis of a data set.
Researchers upload SUMs data files for a stove study, then the application prompts the labelling of a small subset of the data. The machine learning algorithms learn from this hand-labelled data and label the rest automatically.
The result is an easy-to-use data set of cooking events, ready for insightful analysis.
SUMSARIZER was the brainchild of three Berkeley researchers
The web application was architected and is currently maintained by
The full source for the SUMSARIZER application is available on Github. We welcome pull requests and forks. Let us know how we can help you make use of SUMs.
Please feel free to submit feature requests using Github Issues.
If you have questions, contact the current maintainer: sumsarizer@gmail.com


Hi There!
Welcome to Hungry Hungry Horse
Your goal is to answer at least 8 questions correctly to get your horse to food.
Have Fun!
Start New Game
Hunger Meter


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Compact Living
home for a family of 4 built into a trailer.
buildable area = 8’-7”W x 52’-0”L x 9’-6”H.
3 bedroom, 2 bath, washer/dryer, kitchen, dining, living, 2 offices.
home for a family of 4 built into a trailer.
buildable area = 8’-7”W x 52’-0”L x 9’-6”H.
3 bedroom, 2 bath, washer/dryer, kitchen, dining, living, 2 offices.


|
Simbody
3.5
|
A primitive useful for computations involving a single bicubic Bezier patch. More...
Public Member Functions | |
| BicubicBezierPatch_ () | |
| Construct an uninitialized patch; control points will be garbage. More... | |
| BicubicBezierPatch_ (const Mat< 4, 4, Vec3P > &controlPoints) | |
| Construct a bicubic Bezier patch using the given control points B. More... | |
| Vec3P | evalP (RealP u, RealP w) const |
| Evaluate a point P(u,w) on this patch given values for the parameters u and w in [0,1]. More... | |
| void | evalP1 (RealP u, RealP w, Vec3P &Pu, Vec3P &Pw) const |
| Evaluate the tangents Pu=dP/du, Pw=dP/dw on this patch given values for the parameters u and w in [0,1]. More... | |
| void | evalP2 (RealP u, RealP w, Vec3P &Puu, Vec3P &Puw, Vec3P &Pww) const |
| Evaluate the second derivatives Puu=d2P/du2, Pww=d2P/dw2, and cross derivative Puw=Pwu=d2P/dudw on this patch given values for the parameters u and w in [0,1]. More... | |
| void | evalP3 (RealP u, RealP w, Vec3P &Puuu, Vec3P &Puuw, Vec3P &Puww, Vec3P &Pwww) const |
| Evaluate the third derivatives Puuu=d3P/du3, Pwww=d3P/dw3, and cross derivatives Puuw=Pwuu=Puwu=d3P/du2dw and Puww=Pwwu=Pwuw=d3P/dudw2 on this patch given values for the parameters u and w in [0,1]. More... | |
| const Mat< 4, 4, Vec3P > & | getControlPoints () const |
| Return a reference to the Bezier control points B that are stored in this object. More... | |
| Mat< 4, 4, Vec3P > & | updControlPoints () |
| Return a writable reference to the Bezier control points B that are stored in this object. More... | |
| Mat< 4, 4, Vec3P > | calcAlgebraicCoefficients () const |
| Calculate the algebraic coefficients A from the stored Bezier control points. More... | |
| Mat< 4, 4, Vec3P > | calcHermiteCoefficients () const |
| Calculate the Hermite coefficients H from the stored Bezier control points. More... | |
| CubicBezierCurve_< P > | getBoundaryCurveU0 () const |
| Return the u=0 boundary curve as a Bezier curve segment. More... | |
| CubicBezierCurve_< P > | getBoundaryCurveU1 () const |
| Return the u=1 boundary curve as a Bezier curve segment. More... | |
| CubicBezierCurve_< P > | getBoundaryCurveW0 () const |
| Return the w=0 boundary curve as a Bezier curve segment. More... | |
| CubicBezierCurve_< P > | getBoundaryCurveW1 () const |
| Return the w=1 boundary curve as a Bezier curve segment. More... | |
| CubicBezierCurve_< P > | calcIsoCurveU (RealP u0) const |
| Given a particular value u0 for patch coordinate u, create a cubic Bezier curve segment P(w)=P(u0,w) for the isoparametric curve along the patch at fixed u=u0. More... | |
| CubicBezierCurve_< P > | calcIsoCurveW (RealP w0) const |
| Given a particular value w0 for patch coordinate w, create a cubic Bezier curve segment P(u)=P(u,w0) for the isoparametric curve along the patch at fixed w=w0. More... | |
| void | splitU (RealP u, BicubicBezierPatch_< P > &patch0, BicubicBezierPatch_< P > &patch1) const |
| Split this patch into two along the u direction, along an isoparametric curve of constant u=t such that 0 < t < 1. More... | |
| void | splitW (RealP w, BicubicBezierPatch_< P > &patch0, BicubicBezierPatch_< P > &patch1) const |
| Split this patch into two along the w direction, along an isoparametric curve of constant w=t such that 0 < t < 1. More... | |
| void | split (RealP u, RealP w, BicubicBezierPatch_< P > &patch00, BicubicBezierPatch_< P > &patch01, BicubicBezierPatch_< P > &patch10, BicubicBezierPatch_< P > &patch11) const |
| Split this patch into four subpatches at a particular parametric point (u,w) such that 0 < u,w < 1, with each resulting subpatch covering part of the original parametric domain in each direction. More... | |
| Geo::Sphere_< P > | calcBoundingSphere () const |
| Return a sphere that surrounds the entire patch in the 0<= u,w <=1 range. More... | |
| Geo::AlignedBox_< P > | calcAxisAlignedBoundingBox () const |
| Return an axis-aligned bounding box (AABB) that surrounds the entire patch segment in the 0<= u,w <=1 range. More... | |
| Geo::OrientedBox_< P > | calcOrientedBoundingBox () const |
| Return an oriented bounding box (OBB) that surrounds the entire curve segment in the 0<= u,w <=1 range. More... | |
Static Public Member Functions | |
Utility methods | |
These static methods work with given control points. | |
| static Vec3P | evalPUsingB (const Mat< 4, 4, Vec3P > &B, RealP u, RealP w) |
| Given Bezier control points B and values for the curve parameters u and w in [0..1], return the point P(u,w)=Fb(u)*B*~Fb(w) at that location, where Fb is a vector of Bezier basis functions. More... | |
| static void | evalP1UsingB (const Mat< 4, 4, Vec3P > &B, RealP u, RealP w, Vec3P &Pu, Vec3P &Pw) |
| Given Bezier control points B and values for the curve parameters u and w in [0..1], return the tangents Pu(u,w)=dFb(u)*B*~Fb(w) and Pw(u,w)=Fb(u)*B*~dFb(w) at that location. More... | |
| static void | evalP2UsingB (const Mat< 4, 4, Vec3P > &B, RealP u, RealP w, Vec3P &Puu, Vec3P &Puw, Vec3P &Pww) |
| Given Bezier control points B and values for the curve parameters u and w in [0..1], return the second derivatives Puu(u,w)=d2Fb(u)*B*~Fb(w), Puw(u,w)=dFb(u)*B*~dFb(w) and Pww(u,w)=Fb(u)*B*~d2Fb(w) at that location. More... | |
| static void | evalP3UsingB (const Mat< 4, 4, Vec3P > &B, RealP u, RealP w, Vec3P &Puuu, Vec3P &Puuw, Vec3P &Puww, Vec3P &Pwww) |
| Given Bezier control points B and values for the curve parameters u and w in [0..1], return the third derivatives Puuu(u,w)=d3Fb(u)*B*~Fb(w), Puuw(u,w)=d2Fb(u)*B*~dFb(w), Puww(u,w)=dFb(u)*B*~d2Fb(w) and Pwww(u,w)=Fb(u)*B*~d3Fb(w) at that location. More... | |
| static CubicBezierCurve_< P > | calcIsoCurveU (const Mat< 4, 4, Vec3P > &B, RealP u0) |
| Given a particular value u0 for patch coordinate u, create a cubic Bezier curve segment P(w)=P(u0,w) for the isoparametric curve along the patch at fixed u=u0. More... | |
| static CubicBezierCurve_< P > | calcIsoCurveW (const Mat< 4, 4, Vec3P > &B, RealP w0) |
| Given a particular value w0 for patch coordinate w, create a cubic Bezier curve segment P(u)=P(u,w0) for the isoparametric curve along the patch at fixed w=w0. More... | |
| static Mat< 4, 4, Vec3P > | calcAFromB (const Mat< 4, 4, Vec3P > &B) |
| Given the Bezier control points B, return the equivalent vector algebraic coefficients A. More... | |
| static Mat< 4, 4, Vec3P > | calcBFromA (const Mat< 4, 4, Vec3P > &A) |
| Given the vector algebraic coefficients A, return the equivalent Bezier control points B. More... | |
| static Mat< 4, 4, Vec3P > | calcHFromB (const Mat< 4, 4, Vec3P > &B) |
| Given the Bezier control points B, return the equivalent vector Hermite coefficients H. More... | |
| static Mat< 4, 4, Vec3P > | calcBFromH (const Mat< 4, 4, Vec3P > &H) |
| Given the vector Hermite coefficients H, return the equivalent Bezier control points B. More... | |
A primitive useful for computations involving a single bicubic Bezier patch.
Note that a bicubic Bezier spline surface would not necessarily be composed of these, but could use the static methods here for patch computations.
The primary reference for this implementation is the book "Geometric Modeling, 3rd ed." by Michael E. Mortenson, Industrial Press 2006, chapter 8. We follow Mortenson's notation here (with some name changes) and equation numbers are from the text. See CubicHermiteCurve_ and BicubicHermitePatch_ comments for introductory material; here we add the Bezier description to the algebraic and Hermite (geometric) forms described there.
We use B for Bezier control points (rather than P), and H for Hermite coefficients (rather than B). We call the Bezier basis matrix Mb (same as Mortenson) but call the Hermite basis matrix Mh (rather than Mf).
The 16 control points are laid out like this, matching Mortenson, with the Hermite coefficient matrix for comparison:
[ b11 b12 b13 b14 ] u=0 [ h00 h01 w00 w01 ] u=dp/du B = [ b21 b22 b23 b24 ] . H = [ h10 h11 w10 w11 ] w=dp/dw [ b31 b32 b33 b34 ] . [ u00 u01 t00 t01 ] t=d2p/dudw [ b41 b42 b43 b44 ] u=1 [ u10 u11 t10 t11 ] ("twist") w=0 . . w=1
We store those in a 4x4 hypermatrix; subtract one from each control point index to get the matrix indices (sorry).
To convert between Bezier and Hermite or algebraic forms, use
A = Mb B ~Mb (although Mb is symmetric so ~Mb=Mb) H = (Mh^-1 Mb) B ~(Mh^-1 Mb) B = (Mb^-1 Mh) H ~(Mb^-1 Mh)
where the parenthesized (very simple) matrices are given explicitly in the Theory section for CubicBezierCurve_. The results are:
[ b11 b14 3(b12-b11) 3(b14-b13) ] H = [ b41 b44 3(b42-b41) 3(b44-b43) ] [ 3(b21-b11) 3(b24-b14) 9(b22-b21-{b12-b11}) 9({b24-b14}+b13-b23) ] [ 3(b41-b31) 3(b44-b34) 9({b42-b41}+b31-b32) 9({b44-b34}+b33-b43) ]
The braces in the twist terms mark common subexpressions, so the conversion from Bezier to Hermite takes 3x28=84 flops (all entries are 3-vectors).
[ h00 h00+w00/3 h01-w01/3 h01 ] B = [h00+u00/3 {h00+u00/3}+w00/3+t00/9 {h01+u01/3}-w01/3-t01/9 h01+u01/3 ] [h10-u10/3 {h10-u10/3}+w10/3-t10/9 {h11-u11/3}-w11/3+t11/9 h11-u11/3 ] [ h10 h10+w10/3 h11-w11/3 h11 ]
Exploiting the common subexpressions in braces, conversion from Hermite to Bezier takes 3x32=96 flops.
|
inline |
Construct an uninitialized patch; control points will be garbage.
|
inlineexplicit |
Construct a bicubic Bezier patch using the given control points B.
See the class documentation for how this matrix is defined. If instead you have algebraic or Hermite coefficients, you can first convert them to Bezier control points with the calcBFromA() or calcHFromA() provided here.
|
inline |
Evaluate a point P(u,w) on this patch given values for the parameters u and w in [0,1].
Values outside this range are permitted but do not lie on the patch. Cost is 123 flops.
|
inline |
Evaluate the tangents Pu=dP/du, Pw=dP/dw on this patch given values for the parameters u and w in [0,1].
Values outside this range are permitted but do not lie on the curve segment. Cost is 248 flops.
|
inline |
Evaluate the second derivatives Puu=d2P/du2, Pww=d2P/dw2, and cross derivative Puw=Pwu=d2P/dudw on this patch given values for the parameters u and w in [0,1].
Values outside this range are permitted but do not lie on the curve segment. Cost is 363 flops.
|
inline |
Evaluate the third derivatives Puuu=d3P/du3, Pwww=d3P/dw3, and cross derivatives Puuw=Pwuu=Puwu=d3P/du2dw and Puww=Pwwu=Pwuw=d3P/dudw2 on this patch given values for the parameters u and w in [0,1].
Cost is 468 flops. All higher derivatives of a cubic patch are zero.
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inline |
Return a reference to the Bezier control points B that are stored in this object.
See the documentation for this class to see how the returned matrix of control points is defined.
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inline |
Return a writable reference to the Bezier control points B that are stored in this object.
See the documentation for this class to see how the returned matrix of control points is defined.
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inline |
Calculate the algebraic coefficients A from the stored Bezier control points.
See the documentation for BicubicHermitePatch_ to see how the returned matrix of coefficients is defined. Cost is 240 flops.
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inline |
Calculate the Hermite coefficients H from the stored Bezier control points.
See the documentation for this class to see how the returned matrix of coefficients is defined. Cost is 84 flops.
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inline |
Return the u=0 boundary curve as a Bezier curve segment.
The control points are just the first row of the patch control points B so no computation is required.
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inline |
Return the u=1 boundary curve as a Bezier curve segment.
The control points are just the last row of the patch control points B so no computation is required.
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inline |
Return the w=0 boundary curve as a Bezier curve segment.
The control points are just the first column of the patch control points B so no computation is required.
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inline |
Return the w=1 boundary curve as a Bezier curve segment.
The control points are just the last column of the patch control points B so no computation is required.
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inline |
Given a particular value u0 for patch coordinate u, create a cubic Bezier curve segment P(w)=P(u0,w) for the isoparametric curve along the patch at fixed u=u0.
Cost is 93 flops.
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inline |
Given a particular value w0 for patch coordinate w, create a cubic Bezier curve segment P(u)=P(u,w0) for the isoparametric curve along the patch at fixed w=w0.
Cost is 93 flops.
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inline |
Split this patch into two along the u direction, along an isoparametric curve of constant u=t such that 0 < t < 1.
On return, patch0 coincides with the u=0..t subpatch, and patch1 coincides with the u=t..1 subpatch. Each of the new patches is reparameterized so that its u parameter goes from 0 to 1, and the w direction remains parameterized as before. This method is only allowed for tol <= t <= 1-tol where tol is the default tolerance for this precision.
| [in] | u | The u parameter of splitting isoparametric curve (tol <= u <= 1-tol). |
| [out] | patch0 | Subpatch covering domain [0..u,0..1] (contains 0,0 corner). |
| [out] | patch1 | Subpatch covering domain [u..1,0..1] (contains 1,1 corner). |
Cost is 180 flops, or 120 flops if u=1/2.
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inline |
Split this patch into two along the w direction, along an isoparametric curve of constant w=t such that 0 < t < 1.
On return, patch0 coincides with the w=0..t subpatch, and patch1 coincides with the w=t..1 subpatch. Each of the new patches is reparameterized so that its w parameter goes from 0 to 1, and the u direction remains parameterized as before. This method is only allowed for tol <= t <= 1-tol where tol is the default tolerance for this precision.
| [in] | w | The w parameter of splitting isoparametric curve (tol <= w <= 1-tol). |
| [out] | patch0 | Subpatch covering domain [0..1,0..w] (contains 0,0 corner). |
| [out] | patch1 | Subpatch covering domain [0..1,w..1] (contains 1,1 corner). |
Cost is 180 flops, or 120 flops if w=1/2.
|
inline |
Split this patch into four subpatches at a particular parametric point (u,w) such that 0 < u,w < 1, with each resulting subpatch covering part of the original parametric domain in each direction.
The subpatches are reparametrized to have [0..1,0..1] domains. This method is only allowed for tol <= u,w <= 1-tol where tol is the default tolerance for this precision.
| [in] | u | The u parameter of the splitting point (tol <= u <= 1-tol). |
| [in] | w | The w parameter of the splitting point (tol <= w <= 1-tol). |
| [out] | patch00 | Subpatch covering domain [0..u,0..w] (contains 0,0 corner). |
| [out] | patch01 | Subpatch covering domain [0..u,w..1] (contains 0,1 corner). |
| [out] | patch10 | Subpatch covering domain [u..1,0..w] (contains 1,0 corner). |
| [out] | patch11 | Subpatch covering domain [u..1,w..1] (contains 1,1 corner). |
Cost is 360, 420, or 540 flops depending on whether both, one, or neither parameter is 1/2.
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inline |
Return a sphere that surrounds the entire patch in the 0<= u,w <=1 range.
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inline |
Return an axis-aligned bounding box (AABB) that surrounds the entire patch segment in the 0<= u,w <=1 range.
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inline |
Return an oriented bounding box (OBB) that surrounds the entire curve segment in the 0<= u,w <=1 range.
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inlinestatic |
Given Bezier control points B and values for the curve parameters u and w in [0..1], return the point P(u,w)=Fb(u)*B*~Fb(w) at that location, where Fb is a vector of Bezier basis functions.
Cost is 3x35+18=123 flops.
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inlinestatic |
Given Bezier control points B and values for the curve parameters u and w in [0..1], return the tangents Pu(u,w)=dFb(u)*B*~Fb(w) and Pw(u,w)=Fb(u)*B*~dFb(w) at that location.
Cost is 3x70+38=248 flops.
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inlinestatic |
Given Bezier control points B and values for the curve parameters u and w in [0..1], return the second derivatives Puu(u,w)=d2Fb(u)*B*~Fb(w), Puw(u,w)=dFb(u)*B*~dFb(w) and Pww(u,w)=Fb(u)*B*~d2Fb(w) at that location.
Cost is 3x105+48=363 flops.
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inlinestatic |
Given Bezier control points B and values for the curve parameters u and w in [0..1], return the third derivatives Puuu(u,w)=d3Fb(u)*B*~Fb(w), Puuw(u,w)=d2Fb(u)*B*~dFb(w), Puww(u,w)=dFb(u)*B*~d2Fb(w) and Pwww(u,w)=Fb(u)*B*~d3Fb(w) at that location.
Cost is 3x140+48=468 flops.
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inlinestatic |
Given a particular value u0 for patch coordinate u, create a cubic Bezier curve segment P(w)=P(u0,w) for the isoparametric curve along the patch at fixed u=u0.
Cost is 3x28+9=93 flops.
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inlinestatic |
Given a particular value w0 for patch coordinate w, create a cubic Bezier curve segment P(u)=P(u,w0) for the isoparametric curve along the patch at fixed w=w0.
Cost is 3x28+9=93 flops.
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inlinestatic |
Given the Bezier control points B, return the equivalent vector algebraic coefficients A.
All coefficients are 3-vectors. Cost is 3x80=240 flops.
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inlinestatic |
Given the vector algebraic coefficients A, return the equivalent Bezier control points B.
All coefficients are 3-vectors. Cost is 3x72=216 flops.
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inlinestatic |
Given the Bezier control points B, return the equivalent vector Hermite coefficients H.
All coefficients are 3-vectors. Cost is 3x28=84 flops.
|
inlinestatic |
Given the vector Hermite coefficients H, return the equivalent Bezier control points B.
All coefficients are 3-vectors. Cost is 3x32=96 flops.


--- author: Andre Charland categories: app date: '2011-04-28 23:27:29' link: http://blogs.nitobi.com/andre/index.php/2011/04/28/phonegap-presentation-at-under-the-radar-17/ permalink: /2011/04/28/phonegap-presentation-at-under-the-radar-17/ slug: phonegap-presentation-at-under-the-radar-17 status: publish title: 'PhoneGap Presentation at Under The Radar #17!' type: post format: html ---
I just finished my talk at Under The Radar down in Mountain View. The 6min format was intense and I'm glad I did…good to sharpen the presentation skills once in a while.
Here's the video:
And here's a video of the Q & A:
And finally here's my slides: (please note the mullet business model on slide 14)
View more presentations from AndreCharland.
And boy the Deal Maker Media crew our fast getting these videos and blogs out almost instantly.


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Vegan alternative to a cheesey classicMac and Cheese
Serves 4 peopleDairy mac and cheese
Ingredients:
2 tbsp butter
350g pasta
350g pasta
1 garlic glove
3 tbsp plain flour
500 ml milk
250g cheddar
50g parmesan
Method:
Heat oven to 200C/fan 180C/gas 6
Boil the pasta for 2 minutes less than stated on the pack and drain.
Melt the butter in a saucepan, and add the garlic for a minute before adding the flour and continue to stir
Cook for 2 minutes then gradually whisk in the milk until the sauce it lump-free. Simmer for 5 minutes, whisking the whole time until thickened.
Take off the heat and stir in the cheddar and 25g of the parmesan.
Stir in the pasta and tip into an ovenproof dish, then scatter over the rest of the parmesan and place in the oven for 20 minutes until crisp and golden.
Makes 4 burgersVegan Mac and Cheese
Ingredients:
160g raw cashews
200g carrots, peeled and cut into 1cm cubes
700g potatoes, peeled and cut into 1cm cubes
60ml olive oil
40g nutritional yeast
1 Juice of a Lemon
4 garlic cloves, peeled and roughly chopped
1 tbsp Dijon mustard
1 tbsp white wine vinegar
1 tsp cayenne pepper
400g pasta
3 tbsp panko breadcrumbs
Method:
The night before, soak the cashew nuts in water and leave overnight.
Heat the oven to 180C/160C fan/gas 4.
Cook the macaroni for 1 minute less than stated on the packaging
Steam the carrots and potatoes together for 5 mins, until completely softened.
In the food processor, add the drained cashews, carrots, potatoes and the oil, then blitz to break down the nuts.
Then add the rest of the ingredients – apart from the macaroni, breadcrumbs and the remaining oil – then blitz again until the mixture is smooth and season well. Add a splash of water and just a drizzle of olive oil if it looks too stiff, then set aside.
Stir the macaroni through the sauce and transfer to an ovenproof dish. Scatter the breadcrumbs over the top and bake for 20-25 minutes, until hot and crispy.


|
Scientific Fortran Tools (SciFT)
1.2
|
The StringRealHistogramPairList class is a template class that provides linked lists. It stores a list of values and provides iterator-based access as well as insertions and removals. StringRealHistogramPairList features both STL-style iterators and Java-style iterators. For developers who already know STL, have the advantage of familiarity. More...
Public Member Functions | |
| generic | init => initList |
| generic | assignment => copyList |
| procedure | initlist |
| procedure | copylist |
| final | destroylist |
| procedure | str |
| procedure | show |
| procedure | tofstream |
| generic | size => ssize |
| procedure | isempty |
| generic | append => appendValue, appendFArray |
| procedure | prepend |
| procedure | insert |
| generic | erase => eraseFromPtr, eraseFromPos |
| procedure | erasefromptr |
| procedure | erasefrompos |
| procedure | eraseallexcept |
| procedure | eraseallexceptfirst |
| procedure | eraseallexceptlast |
| procedure | clear |
| generic | at => atFromPtr, atFromPos |
| generic | replace => replaceFromPtr, replaceFromPos |
| procedure | ptr |
Public Attributes | |
| integer | nitems = 0 |
| class(stringrealhistogrampairlistiterator), pointer | begin => null() |
| class(stringrealhistogrampairlistiterator), pointer | end => null() |
Private Member Functions | |
| procedure, private | ssize |
| procedure, private | appendvalue |
| procedure, private | appendfarray |
| procedure, private | atfromptr |
| procedure, private | atfrompos |
| procedure, private | replacefromptr |
| procedure, private | replacefrompos |
The StringRealHistogramPairList class is a template class that provides linked lists. It stores a list of values and provides iterator-based access as well as insertions and removals. StringRealHistogramPairList features both STL-style iterators and Java-style iterators. For developers who already know STL, have the advantage of familiarity.
Here's an example of a List that stores integers ...
{.c}
... and a StringRealHistogramPairList that stores Atom values:
{.c}
Finally, you can use the first one thus:
{.f90}
Definition at line 171 of file StringRealHistogramPairList.f90.
| generic stringrealhistogrampairlist::stringrealhistogrampairlist::append | ( | ) |
Definition at line 190 of file StringRealHistogramPairList.f90.
|
private |
Definition at line 192 of file StringRealHistogramPairList.f90.
|
private |
Definition at line 191 of file StringRealHistogramPairList.f90.
| generic stringrealhistogrampairlist::stringrealhistogrampairlist::assignment | ( | ) |
Definition at line 178 of file StringRealHistogramPairList.f90.
| generic stringrealhistogrampairlist::stringrealhistogrampairlist::at | ( | ) |
Definition at line 202 of file StringRealHistogramPairList.f90.
|
private |
Definition at line 204 of file StringRealHistogramPairList.f90.
|
private |
Definition at line 203 of file StringRealHistogramPairList.f90.
| procedure stringrealhistogrampairlist::stringrealhistogrampairlist::clear | ( | ) |
Definition at line 201 of file StringRealHistogramPairList.f90.
| procedure stringrealhistogrampairlist::stringrealhistogrampairlist::copylist | ( | ) |
Definition at line 181 of file StringRealHistogramPairList.f90.
|
final |
Definition at line 182 of file StringRealHistogramPairList.f90.
| generic stringrealhistogrampairlist::stringrealhistogrampairlist::erase | ( | ) |
Definition at line 195 of file StringRealHistogramPairList.f90.
| procedure stringrealhistogrampairlist::stringrealhistogrampairlist::eraseallexcept | ( | ) |
Definition at line 198 of file StringRealHistogramPairList.f90.
| procedure stringrealhistogrampairlist::stringrealhistogrampairlist::eraseallexceptfirst | ( | ) |
Definition at line 199 of file StringRealHistogramPairList.f90.
| procedure stringrealhistogrampairlist::stringrealhistogrampairlist::eraseallexceptlast | ( | ) |
Definition at line 200 of file StringRealHistogramPairList.f90.
| procedure stringrealhistogrampairlist::stringrealhistogrampairlist::erasefrompos | ( | ) |
Definition at line 197 of file StringRealHistogramPairList.f90.
| procedure stringrealhistogrampairlist::stringrealhistogrampairlist::erasefromptr | ( | ) |
Definition at line 196 of file StringRealHistogramPairList.f90.
| generic stringrealhistogrampairlist::stringrealhistogrampairlist::init | ( | ) |
Definition at line 177 of file StringRealHistogramPairList.f90.
| procedure stringrealhistogrampairlist::stringrealhistogrampairlist::initlist | ( | ) |
Definition at line 180 of file StringRealHistogramPairList.f90.
| procedure stringrealhistogrampairlist::stringrealhistogrampairlist::insert | ( | ) |
Definition at line 194 of file StringRealHistogramPairList.f90.
| procedure stringrealhistogrampairlist::stringrealhistogrampairlist::isempty | ( | ) |
Definition at line 189 of file StringRealHistogramPairList.f90.
| procedure stringrealhistogrampairlist::stringrealhistogrampairlist::prepend | ( | ) |
Definition at line 193 of file StringRealHistogramPairList.f90.
| procedure stringrealhistogrampairlist::stringrealhistogrampairlist::ptr | ( | ) |
Definition at line 208 of file StringRealHistogramPairList.f90.
| generic stringrealhistogrampairlist::stringrealhistogrampairlist::replace | ( | ) |
Definition at line 205 of file StringRealHistogramPairList.f90.
|
private |
Definition at line 207 of file StringRealHistogramPairList.f90.
|
private |
Definition at line 206 of file StringRealHistogramPairList.f90.
| procedure stringrealhistogrampairlist::stringrealhistogrampairlist::show | ( | ) |
Definition at line 184 of file StringRealHistogramPairList.f90.
| generic stringrealhistogrampairlist::stringrealhistogrampairlist::size | ( | ) |
Definition at line 187 of file StringRealHistogramPairList.f90.
|
private |
Definition at line 188 of file StringRealHistogramPairList.f90.
| procedure stringrealhistogrampairlist::stringrealhistogrampairlist::str | ( | ) |
Definition at line 183 of file StringRealHistogramPairList.f90.
| procedure stringrealhistogrampairlist::stringrealhistogrampairlist::tofstream | ( | ) |
Definition at line 186 of file StringRealHistogramPairList.f90.
| class(stringrealhistogrampairlistiterator), pointer stringrealhistogrampairlist::stringrealhistogrampairlist::begin => null() |
Definition at line 173 of file StringRealHistogramPairList.f90.
| class(stringrealhistogrampairlistiterator), pointer stringrealhistogrampairlist::stringrealhistogrampairlist::end => null() |
Definition at line 174 of file StringRealHistogramPairList.f90.
| integer stringrealhistogrampairlist::stringrealhistogrampairlist::nitems = 0 |
Definition at line 172 of file StringRealHistogramPairList.f90.


2018
|
Caitie Oder
|
Pratik Vaidya
|
Ryan Brush
|
Kevin Shekleton
|
Jared Moore
|
Joe Geris, Jennifer Lambert, Andie Young
|
Chris Fagyal, Carl Chesser
|
Kyle Harper
|
Jerrod Carpenter
|
Lindsey Bromberg
|
Isabella Kuzava, Carl Chesser
|
Bryan Baugher
|
Matt Anderson
|
Jody Butts
2017
|
Isabella Kuzava, Carl Chesser
|
Ryan Brush
|
Lauren Bock
|
Rebecca Green, Amber Wilks
|
Arvindo Kinny
|
Dennis Patterson
|
Isabella Kuzava and Ian Kottman
|
Will Gorman
|
Michelle Brush and Vinay Koduri
|
Bryan Baugher
|
Denisse Osorio de Large
|
Isabella Kuzava and Shahzad Zafar
|
Lindsay Ullyot
|
Lindsay Ullyot
|
Seth Claybrook, Bradley Scott
|
Mike Rzepka
|
Dennis Patterson, Jenni Syed
|
Lindsay Ullyot
|
Bryan Baugher
|
Sundeep Paruvu
|
Isabella Kuzava and Carl Chesser
2013
|
Kevin Shekleton
|
Frank Rydzewski
|
Chris Finn
|
Kevin Shekleton and Frank Rydzewski
|
Michelle Brush
|
Carl Chesser
|
Ryan Brush
|
Cerner Engineering
|
Paul Conklin
|
Cerner Engineering
|
Cerner Engineering
|
Jonny Wright
|
Ryan Brush
|
Cerner Engineering
|
Charlie Huggard
|
Ryan Brush


My name is Kyly Vass and this is my glorious HCI project page. I am currently working full stack software development Ingenu where we are creating the internet of things while and studying computer science at the Jacobs School of Engineering at UC San Diego.
My favorite, check out the video for details...
Time Clock is a java application that helps employees track their hours at their workstation. Time Clock runs in the background tracking the amount of time the user has been idle.
This is a project I worked on last year with Ranjit Jhala and his team. LiquidHaskell is a static verifier for Haskell, based on Liquid Types.
Provides a simple way to incorporate and customize your Gravatar profile.
 Pretty simple but it came out nice.
This is a script that I used throughout all my programming classes last year at UCSD and will most likely continue to use. It is easy to change to fit most of my testing needs.


Google was founded by Larry Page and Sergey Brin while they were Ph.D. students at Stanford University.


LeBlanc first appeared in a 1987 Heinz Tomato Ketchup commercial. In 1988, he starred in the television drama TV 101 for one season. In 1991, he had a recurring role on the hit Fox sitcom, Married... with Children. He played Vinnie Verducci, the son of one of the friends of the protagonist, Al Bundy and the boyfriend of Al's daughter, Kelly. He went on to star in two short-lived spin-offs of Married... with Children, Top of the Heap in 1991 and Vinnie and Bobby in 1992.
He appeared in two of Jon Bon Jovi's music videos: "Miracle", from the Young Guns II soundtrack in 1990, and "Say It Isn't So" in 2000. He also appeared in Alanis Morissette's single "Walk Away" in 1991, the last seconds of Tom Petty and the Heartbreakers "Into the Great Wide Open" in which he is seen getting a tattoo, and in Bob Seger's "Night Moves" in 1994
1994–2006: Breakthrough role as Joey Tribbiani
LeBlanc found success in the role of Joey Tribbiani on Friends, and went on to play this character for 12 years — 10 seasons of Friends and two seasons of Joey. Friends was successful and LeBlanc, along with his co-stars, gained wide recognition among viewers. For his performance, LeBlanc received three Primetime Emmy Award nominations, three Golden Globe award nominations, and one Screen Actors Guild Award. During this time he also appeared in the films Lookin' Italian (1994), Ed (1996), Lost in Space (1998), Charlie's Angels (2000), and its sequel, Charlie's Angels: Full Throttle


Posted on Sep 1, 2017 at 12:00 PM
Teradata has been in the data managment business for quiet some time now,their platform is made up of Teradata Data Warehouse,Database,set of analytic tools and Big Data. In this blog we would focus on Analytical functions and OLAP,we will try and cover things beyond the SUM ,COUNT,MAX,MIN and other commonly used functions.
Application programmers,administrators and end users are the principal audience for this blog.Other technical personnel responsible for designing, maintaining, and using Teradata Database might also find this manual to be useful.A lot of content has been sourced form db books and Teradata manuals.
ABS:
Computes the absolute value of an argument.
SELECT ABS(5-10);
5
This comes handy when we need to apply business rules, and are have to eliminate negative values.
FLOOR:
Returns the following values: the next largest integer that is equal to or less than arg. The input argument arg in case of exact number.CEILING Returns the smallest integer that is not less than the input argument.
SELECT CEILING(10.455);
11
SELECT FLOOR(6.5);
6
Dealing with Nulls:
In this example, you can test the Salary column for null.
SELECT empno, ZEROIFNULL(salary)
FROM employee ;
All NULL values in the salary field will be relaced by 0 in the result-set.
DATE MANIPULATIONS:
Adding DAY/MONTH/YEAR TO A DATE
SELECT DATE '2017-10-28' + INTERVAL '1' DAY;
29/10/2017
SELECT DATE '2017-10-28' + INTERVAL '1' MONTH;
28/11/2017
SELECT DATE '2017-10-28' + INTERVAL '1' YEAR;
28/10/2018
CASE EXPRESSION:
We have an example that shows how using a CASE expression can result in significantly enhanced performance by eliminating multiple passes over the data. Without using CASE, you would have to perform multiple queries for each region and then consolidate the answers to the individual queries in a final report.
SELECT item_number, SUM(CASE
WHEN Class_desc='JUICE'
THEN xsa_saved_nws
ELSE 0
END) AS JUICE,
SUM(CASE
WHEN Class_desc='SNACKS'
THEN xsa_saved_nws
ELSE 0
END) AS SNACKS,
SUM(CASE
WHEN Class_desc LIKE 'LIQUID MILK'
THEN xsa_saved_nws
ELSE 0
END)
AS MILK, MILK/SUM(xsa_saved),
SUM(xsa_saved)
FROM db.store_data_set
WHERE item_number IN ('P20000511','P10069661','P10370319','P10370320','P10370381')
GROUP BY item_number;
CASE IN PARTITIONING:
Here is an example that uses CASE_N and the value of the totalorders column to define the partition to which a row is assigned:
CREATE TABLE orders
(storeid INTEGER NOT NULL
,productid INTEGER NOT NULL
,orderdate DATE FORMAT 'yyyy-mm-dd' NOT NULL
,totalorders INTEGER)
PRIMARY INDEX (storeid, productid)
PARTITION BY CASE_N(totalorders < 100, totalorders < 1000,
NO CASE, UNKNOWN);
In the example, CASE_N specifies four partitions to which a row can be assigned, based on the
value of the totalorders column.
includes approximately 40 predefined data mining functions in SQL based on the Teradata SQL-specific functions. For example, the Teradata Warehouse Miner FREQ function uses the Teradata SQL-specific functions RANK,CSUM and QUALIFY to determine frequencies.
DENSE_RANK:
Calculates the number of proceeding distinct values, plus one. If multiple rows have equal values, they all get the same rank, but there are no gaps. Each change in data value causes the ranking number to be incremented by one. Its not implemented in Teradata (probably because of performance reasons), but can be rewritten. For example in normal Ranking operation if two items have same marks, they both would be given the same Rank, say 1.Now the next item would be given Rank 3 in regular ranking operation. In Dense Rank this item would be given Rank 2.
SELECT
item_number,
sales,
DENSE_RANK() OVER (PARTITION BY offer_number ORDER BY sales) as DNS_RNK
FROM
DB.ntnl_fcasts
order by DNS_RNK;
item_number |sales| DNS_RNK
P20001828 |0.222| 1
P20001828 |0.222| 1
P10069349 |0.418| 2
P10069349 |0.418| 2
P10069349 |0.764| 3
P10069349 |0.764| 3
P10069349 |0.818| 4
P10069349 |0.818| 4
P10069349 |0.866| 5
In Rank this item would not be given Rank 2 & 3.
SELECT
item_number,
sales,
RANK() OVER (PARTITION BY offer_number ORDER BY sales) as DNS_RNK
FROM
DB.ntnl_fcasts
order by RNK;
item_number sales RNK
P20001828 5 1
P20001828 5 1
P20001828 5 1
P20001828 6 4
P10069349 6 4
P10069349 12 7
CSUM:
This command uses the first parameter as the column containing a numeric value to sum. This value will be added to the previous data values and provide a running or cumulative answer.
SELECT
DEPT,
WEEK_START_DATE,
ZONE_NUMBER,
COUNTRY_CODE,
EXP_WEEKLY_SALES,
CSUM(EXP_WEEKLY_SALES,DEPT) CUSUM
FROM DB.BASE_WEEKLY
WHERE ZONE_NUMBER= 8046 AND WEEK_START_DATE='2017-08-14';
MAVG:
This command uses the first parameter as the column containing a numeric value to average. The second parameter used by the MAVG is the width number. It represents the number of rows included in the summation. Valid values are from 1 to 4096.


Psalms 20:7
Some trust in chariots, and some in horses: but we will remember the name of the LORD our God.


Compassion
The times in my life where I've been happiest and the most satisfied, the value of compassion comes to mind.
Compassion means so much to me because it connects me to every human being whether they be a stranger or close friend or family. Compassion allows me to remove focus from myself and tap into another person's emotional state.
When I am being compassionate I can recognize that a person may be reacting to me with anger out of fear or desperation -- not necessarily because pf something I did or said. In turn, I feel most understood when someone can direct that same compassion my way and see all of my flaws and weaknesses without judgment. This compassion allows me to share and break down any walls that I build up to protect myself. There is real growth in compassion. It is the thing I find most connects me to other people.
I would say that I most definitely strive to live up to this value daily so I'd rate myself a 5.
The last topic someone asked for my advice on was a friend wanting to make a career change who was worried that they might be making the wrong decision. I told them to go for it. It's better to try and fail than not try and have regrets.


| Table 1 |
Yield potentials for double-maize cropping systems (two maiz ... |
| Table 2 |
Grain yield, yield potential, and the grain yield expressed ... |
| Table 3 |
Precipitation, irrigation, evapotranspiration (ET), water us ... |
| Table 4 |
Precipitation, irrigation, evapotranspiration (ET), and net ... |


| Title | Priority | User | Created | Completed | |
|---|---|---|---|---|---|
| @(h (elide-string (todo-title obj) 40 #:honor-word-boundaries #t)) | @(format-priority (todo-priority obj)) | @(user-username (todo-user-obj obj)) | @(~t (todo-created-at obj) "MM/dd/yy HH:mm") | @(if (todo-completed-at obj) (~t (todo-completed-at obj) "MM/dd/yy HH:mm") "") | @(define user (webctx-user ctx)) @(when (may? user 'edit obj) @`{ Edit }) @(when (may? user 'delete obj) @`{ Delete }) |


"But Chuck, you work at a startup,
this can never work at my large Enterprise!?!?!"
Don't worry, this talk was "forged" in the fires of the Enterprise and field tested in my new role at a startup.
First one should be easy...
That you’ll learn at least one thing that’ll make your development cycle faster.
The 'rough' definition: “A test that you run to make sure that everything is setup and ready for development”
“Just get some kind of output”
Venkat Subramaniam (@venkat_s)
A fast feedback cycle is the most valuable thing a developer can influence
Can you automate it?
Examples: Clink/ConsoleZ, DosKey, shortcuts
"...but Chuck, I don't have time to write unit tests
I have deadlines I have to meet right Meow!"
Define the context with whoever you're working with
Be explicit
The 3 stages of control/influence


We have variety of destinations just for you
We have numerous tropical destinations to suit your needs such
But popularity makes the difference right? How about our numerous popular world-wide travel destinations?
INTRODUCING


{% load staticfiles %}
Looking for the title of a data series in FRED's database.
Search »
Looking to graph a series from FRED's database.
Graph »
© Volkoff Industries 2014


JiBX/WS is a framework for creating fast, simple web services.
It is built upon the JiBX data binding framework. It provides the same advantages of flexibility and performance for web services as the base JiBX project does for ordinary XML data binding.
JiBX treats both Java classes and XML schema as first class objects, and uses a separate binding definition to specify the mapping between them. This allows JiBX/WS services, and clients, to be developed in either a "code-first" or "schema-first" manner. If using a "code-first" approach, the JiBX BindGen tool allows you to create customized bindings and XML schema. If using "schema-first", the JiBX CodeGen tool will generate customized Java code and bindings. The binding definition can also be hand-crafted.
JiBX/WS is designed from the start to support document/literal (doc/lit) web services rather than the older rpc/encoded (rpc/enc) style. This is an important distinction - the rpc/enc approach allows developers to easily expose simple method calls as web services, but creates problems for interoperability, especially with more complex data structures. Because of these problems, rpc/enc has been effectively deprecated by recommendations such as the Web Services Interoperability Organization's Basic Profile (WS-I BP), and replaced by the doc/lit approach.
The doc/lit approach to web services focuses on the actual XML data being exchanged. Rather than model method calls with parameters encoded in XML, the doc/lit approach uses W3C XML Schema definitions to fix the XML data formats. It's up to the participants in a web services interaction to process the XML payload of doc/lit SOAP messages in whatever manner is appropriate to their needs.
This focus on the XML formats is what allows JiBX/WS to apply the power of JiBX data binding to doc/lit web services. JiBX is designed to support fast and flexible conversions between XML and Java objects. With doc/lit web services the contents of SOAP messages are just XML document fragments, which can be converted to and from Java objects using JiBX just the same as any other XML. All that's needed to support this is a framework that handles the SOAP wrappers and actual transport, which is what JiBX/WS provides.
In benchmark tests to date JiBX/WS performs 1.3 to 2.5 times faster than the Apache Axis2 implementation for doc/lit web services. With the XBIS encoding, JiBX/WS is even faster over the wire than RMI! You can view the details of some performance tests in Dennis's presentation on The World's Fastest Web Services. There's also a condensed 10-minute YouTube of this talk.
JiBX/WS is an update to, and replacement for, the JibxSoap project, which is in use by a number of organizations.
| Module Name | Primary Developer | Status |
|---|---|---|
| jibxws (svn) | Nigel Charman | 0.9 beta release June 21, 2009 |


| Interface | Description |
|---|---|
| ParcelChannel |
References a channel that can transmit a parcel to multiple receivers, all registered using this channel.
|
| ParcelInterface |
Represents a point of contact for each
ParcelRegistry . |
| ParcelReceiver |
When you have a parcel or signal to be transmitted to another part of the application,
you first need to find the
ParcelReceiver intended for handling the parcel. |
| ParcelSender | |
| ParcelSerializer<ParcelObject> |
Interface for implementing an object serializer.
|
| Class | Description |
|---|---|
| DefaultParcelReceiver | |
| EntryParcel | |
| Parcel | |
| Parcel.Factory |
Used to serialize an Object to a
Parcel and vice-versa,
as well as, deserialize from bytes, e.g., file or network. |
| ParcelCarrier |
Defines a carrier containing data and signals to be transmitted over network, IPC, and by reference.
|
| ParcelCarrier.Serializer | |
| ParcelChecker | |
| ParcelLoader | |
| ParcelRegistry |
Not Finished!
|
| Enum | Description |
|---|---|
| ParcelCarrier.ResultCode |
Allows for the sending and reply of very basic rudimentary signals.
|
| ParcelChecker.CheckerFlag | |
| ParcelChecker.ValueFlag | |
| ParcelChecker.ValueType | |
| ParcelLoader.Type |
| Annotation Type | Description |
|---|---|
| Parcelable |


Realbricks : Lets Change the world
Real estate is property made up of land and the buildings on it, as well as the natural resources of the land including uncultivated flora and fauna, farmed crops and livestock, water, and any additional mineral deposits.
Real estate is a tangible asset and a type of real property. Real property examples include land, buildings and other improvements, plus the rights of use and enjoyment of that land and all its improvements. Renters and leaseholders may have rights to inhabit land or buildings that are considered a part of their estate, but these rights themselves are not, strictly speaking, considered real estate.
Real property is not the same thing and should not to be confused with personal property. Personal property includes intangible assets like investments, along with tangible assets such as furniture and fixtures like a dishwasher. Also, even renters may claim parts of a home as personal property, provided you bought and installed the property with the lessor's permission.
Although the media often refers to the "real estate market," real property examples can be grouped into three broad categories based on its use.
Residential real estate includes undeveloped land, houses, condominiums, and townhouses. The structures may be single-family or multi-family dwellings and may be owner-occupied or rental properties.
Commercial real estate includes nonresidential structures such as office buildings, warehouses, and retail buildings. These buildings may be free-standing or in shopping malls.
Industrial real estate includes factories, business parks, mines, and farms. These properties are usually larger in size and locations may include access to transportation hubs such as rail lines and harbors.
Homeownership, also known as owner-occupancy, is the most common type of real estate investment in the United States. According to the National Multifamily Housing Council (NMHC), roughly two-thirds of residents own their home. Often, these owners have financed the purchase by taking out a mortgage loan, in which the property acts as collateral for the debt.
Individuals shopping for home mortgages to help them realize the dream of property ownership are faced with a variety of options. Mortgages can charge either fixed-rate or variable-rate interest. Fixed-rate mortgages generally have higher interest rates than variable-rate mortgages, which can make them more expensive in the short run. Fixed-rate loans cost more in the short term because they are protected from future interest rate increases.
 Balloon loans are mortgages that don't fully amortize—reduce to zero—over time. Instead, the borrower pays interest for a set period, five years for example, and then must pay the remainder of the loan in a balloon payment at the end of the term.
Also, mortgages can come with heavy costs that include transaction fees and taxes. These additional expenses are often rolled into the loan. Once potential homeowners have proven their eligibility and secured a mortgage from a bank or other lender, they must complete additional steps to make sure the property is legally for sale and in good condition.
Commercial real estate is used for commerce and includes anything from strip malls and free-standing restaurants to office buildings and skyscrapers. It is often distinguished from industrial real estate, which is practical space used in the manufacturing of products.
Buying or leasing real estate for commercial purposes is very different from buying a home or even buying residential real estate. Commercial leases are generally longer than residential leases. Commercial real estate returns are based on their profitability per square foot, unlike structures intended to be private residences.
Moreover, lenders may require a larger down payment on a mortgage for commercial real estate then what is required for a residence.
One can invest in real estate directly by buying actual properties or parcels of land; or indirectly, by buying shares in publicly traded real estate investment trusts (REITs) or mortgage-backed securities (MBS). Investing directly in real estate results in profits—or losses—through two avenues, which haven't changed in centuries: Revenue from rent or leases, and appreciation of the real estate's value.
Unlike other investments, real estate is dramatically affected by its surroundings and immediate geographic area. Hence the well-known real-estate maxim "location, location, location." Except for a severe national recession or depression, residential real estate values, in particular, are affected primarily by local factors. Such factors include the area's employment rate, the local economy, crime rates, transportation facilities, quality of schools, municipal services, and property taxes.
Offers steady income
Offers capital appreciation
Diversifies portfolio
Can be bought with leverage
Is usually illiquid
Influenced by highly local factors
Requires big initial capital outlay
May require active management, expertise
There are key differences in residential and commercial real estate investments. On the one hand, residential real estate is usually less expensive and smaller than commercial real estate, and so it is more affordable for the small investor.
On the other hand, commercial real estate is often more valuable per square foot, and its leases are longer, which theoretically ensures a more predictable income stream. With greater revenue comes greater responsibility. Commercial rental real estate is more heavily regulated than residential real estate, and these regulations can differ not only from country to country and state by state but also by county and city. Even within cities, zoning regulations add a layer of unwanted complexity to commercial real estate investments.
There is also an increased risk of tenant turnover in commercial rental agreements. If the lessee's business model is bad, their product is unattractive, or they are poor managers, they might declare bankruptcy. The business failure can abruptly stop expensive real estate from generating revenue.
Moreover, just as property can appreciate, it can also depreciate. Once-hot retail locations have been known to decay into rotten shopping centers and dead malls.
Appreciation is achieved through different means, but the increase in a property’s value isn't realized until the owner sells it the property. Another way to realize profit would be to refinance the mortgage. Raw and undeveloped land, like the territory right outside a city’s borders, offers the biggest potential for construction, enhancement, and profit. Appreciation can also come from discovering valuable materials or natural resources on a plot of land, like striking oil. Also, a rise in the market values of the area around the land you own.
As a neighborhood grows and develops, property values tend to climb. The gentrification of urban neighborhoods in some American cities over the last few decades has often resulted in a dramatic increase in real estate prices. Scarcity can also play a role in the value of real estate holdings. If a lot is the last of its size or kind in a prestigious area—or one where such lots rarely become available—it gains in marketability.
Income from real estate comes in many forms. The biggest generator is the rent paid on land already developed into residential or commercial properties. However, companies will also pay royalties for natural resource discoveries on raw land. Also, they may pay to build structures on it, like cell towers or pipelines.
Income can also come from indirect real estate investments. In a REIT, the owner of multiple properties sells shares to investors and passes along rental income in the form of distributions. Similarly, in an MBS, the interest and principal payments from a pool of mortgages are collected and passed through to investors.
Both REITs and MBS investment products trade like stocks, with real estate acting as their underlying security. So, they may offer capital appreciation is the shares gain in market value.
Mortgage-backed securities got a lot of bad press from the role they played in the mortgage meltdown that triggered a global financial crisis in 2007. However, they are still in existence and traded. The most accessible way for the average investor to buy into these products is via exchange-traded funds (ETFs). Like all investments, these products do carry a degree of risk. However, they may also offer portfolio diversification. Investors must investigate the holdings to ensure the funds specialize in investment-grade MBS, not the subprime variety that figured in the crisis.
As of April 2019, the top-performing vehicles of this type include:
Realbricks : Lets Change the world


Pybtex is a drop-in replacement for BibTeX written in Python. You can start using it right now by simply typing pybtex where you would have typed bibtex.
Please note that the correct spelling is just Pybtex, without any camel-casing, which we considered too annoying to type.
We also suggest reading the Friendly Manual, although it is still incomplete.
Oh! Is it really BibTeX-compatible?
Yes, it really is, most of the time.
BibTeX styles work fine with Pybtex, although there are still some minor issues. Nevertheless, we are going to achieve 100% compatibility before releasing version 1.0.
If something does not work for you, just let us know.
But why should I use it instead of BibTeX?
You probably should not if you ask. But still, Pybtex has Unicode inside. It supports BibTeXML and YAML. It can write HTML and plain text. It is extensible and fun to hack. It comes with a free database conversion utility. And designing new bibliography styles is no more a pain with Pybtex' brand new pythonic style API.
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Hmm nice. Wrap it up, I'll take it! Where is the download link?
The tarballs thay are available from the PyPI page. That said, the most stable and feature complete and well documented version of Pybtex is known to be the Bazaar trunk.
To get the very latest Pybtex from the trunk:
bzr branch lp:pybtex
To run the tests (need nose):
cd pybtex python setup.py egg_info # or python setup.py develop python setup.py nosetests
Pybtex can be also installed with Easy Install:
easy_install pybtex
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Have fun!


facilitating the explanatory use of a unifying theory (for example, evolutionary
theory in the case of biology). But even on the broadest understanding
of ‘theory’, no warranted unifying theory regulates the scientific explanation
of any significant range of social phenomena. This distinctive disunity
of the social sciences, along with the distinctive nature of social questions,
sustains a different way of assessing classifications as marking genuine
distinguishing properties, a form of taxonomic assessment in which moral
evaluations and political contexts are directly relevant. I will
show how such assessment should proceed in the judgment of the social scientific
standing of classifications by ethnicity and nationality. Appealing
to connections in natural science between classification, communication
and interests in change, I will argue that the inherently political nature
of social scientific taxonomy is not a barrier to objectivity. Rather,
traditional questions about the boundary between facts and values become
questions of the rational social division of labor in social inquiry.
“Race: Biological Reality or Social Construct?”
Robin Andreasen, University of Wisconsin, Madison
Abstract:
Race was once thought to be a real biological kind. Today, however,
the dominant view is that biological races don’t exist. Theorists
are now debating the question of the social reality, or lack thereof, of
race. I challenge the trend to reject the biological objectivity
of race by arguing that cladism—a branch of systematic biology that individuates
taxa solely by appeal to common ancestry—in conjunction with current work
in human evolution, provides a new way to define race biologically.
I then show how to reconcile the proposed biological conception with current
social scientific theories about the nature of human racial categories.
Specifically, I argue that social scientific conceptions of race and the
cladistic concept are complementary; they should not be interpreted as
in competition.
“Local Realism and Global Arguments”
Harold Kincaid, University of Alabama at Birmingham
Abstract:
The paper looks at realism issues in the social sciences taken as debates
whether basic predicates of kind terms in the social sciences should be
taken realistically, i.e. as picking out mind-independent entities.
The first half looks at various general conceptual arguments given to show
that social kinds should not be taken realistically. These arguments
include (1) claims that the best explanation of poor empirical progress
in the social sciences is that they lack natural kinds, (2) arguments based
on the idea that social kinds don’t have the right relation to the physical,
(3) doubts based on the lack of any clear fact/value distinction in the
social science, and (4) arguments pointing to apparent multiplicity of
competing ways to dividing up the social world. I argue that none
of these considerations establishes that social predicates do not refer.
At most, they provide important clues to potential obstacles. The
second half of the paper then goes on to argue that the interesting issues
are not ones that can be decided independently of substantive issues in
the social sciences themselves and that therefore trying to decide realism
issues in a global fashion for all social science is misguided. I
thus look in detail at some basic categories in economics—in particular,
the productive/nonproductive distinction which goes to the heart of the
discipline—as a way of identifying some of the various kinds of general
empirical considerations that are at issue in deciding when social kinds
should be taken realistically and when they should not. Crucial issues
involve whether we can produce well-confirmed causal explanations, and
I try to show how that is possible with social kinds despite the doubts
that have been raised about them.
Symposium: The Structure of Scientific Theories Thirty Years On
Organizers: Steven French, Leeds University, and
Nick Huggett, University of Illinois at Chicago
Chair: TBA
“Understanding Scientific Theories: An Assessment of Developments, 1969?1998”
Frederick Suppe, University of Maryland
Abstract
The positivistic Received View construed scientific theories syntactically
as axiomatic calculi where theoretical terms were given a partial interpretation
via correspondence rules connecting them to observation statements.
This view came under increasing attack in the 1960s, and its death can
be dated March 26, 1969, when Carl G. Hempel opened the Illinois Symposium
on Theories with an address repudiating the Received View and proposing
an alternative analysis. This paper will assess what, with hindsight,
seem the most important defects in the Received View; survey the main proposed
successor analyses to the Received View—semantic reworkings of the Received
View, various versions of the Semantic Conception of Theories. and the
Structuralist Analysis of Theories; evaluate how well they avoid those
defects; examine what new problems they face and where the most promising
require further development or leave unanswered questions; and explore
implications of recent work on models for understanding theories.
“Theories, Models and Structures: Thirty Years On”
Steven French, University of Leeds, and
Newton da Costa, University of Sao Paulo,
Abstract
In The Structure of Scientific Theories, Suppe put forward the Semantic
Approach as a “... promising alternative to the linguistic formulation
approaches of the Received View and Weltanschauungen analyses.” This
approach has since entered the “mainstream” of philosophy of science through
the work of van Fraassen, Giere and Suppe himself. Our aim in this
paper is to survey the developments of the past thirty years from the perspective
of Suppes’ set-theoretic analysis and to suggest how recent work might
overcome a series of objections to the Semantic Approach.
“The Emergence of Feminist Philosophy of Science”
Helen E. Longino, University of Minnesota
Abstract
This paper will describe the emergence of feminist concerns in philosophy
of science. Feminist philosophers and scientists have been concerned
with explicitly sexist or androcentric aspects of scientific research programs
and with the metaphoric gendering of various aspects of scientific practice
and content In the effort to identify and understand these features
of the sciences, feminist scholars have advanced theses about the role
of social values in scientific research, about the character of experiment,
about evidential relations, and about science and power. In this
they have made common cause with scholars in social and cultural studies
of science, but with important differences. This paper will articulate
the relationship of the work of feminists to other changes in philosophy
of science in the last thirty years.
“Local Philosophies of Science”
Nick Huggett, University of Illinois in Chicago
Abstract
One of the central characteristics of the received view was its tendency
to treat questions in the philosophy of science as “global”: what is the
nature of scientific theories? What are the units of significance
in science? What is an explanation? And so on. Even problems
in specific sciences were typically approaches (for instance, by Reichenbach)
with answers to the global questions in mind. Much contemporary work
still seeks global answers, but there is also a widespread opinion that
science has no essence, and that philosophical work should be concentrated
on “local” questions that arise within sciences, independently of general
theories about the nature of science. This idea can be particularly
identified, for instance, in the work of Nancy Cartwright, Arthur Fine,
and Ian Hacking, as well as in contemporary philosophy of individual sciences.
This paper will discuss the “no essence” view, and evaluate the prospects
for “local” philosophical research programs.
“The Legacy of ‘Weltanschauungen’ Approaches in Philosophy of Science”
Alison Wylie, University of Western Ontario
Abstract:
When Suppe mapped the emerging terrain of post-positivist philosophy
of science in 1968, what he called “Weltanschauungen” approaches figured
prominently. As a loosely articulated family of views about science
these require that, in various senses and to varying degrees, the language
and logic of science, the knowledge it produces, its preferred forms of
practice and even its defining epistemic ideals must be contextualized.
The central question that divides the advocates of such approaches is,
what constitutes “context”: is it restricted to the theoretical, conceptual
assumptions that inform inquiry (aspects of context internal to science),
or does it extend to various of the (external) human, social conditions
that make possible the scientific enterprise?
In the intervening thirty years, “Weltanschauungen” approaches have
proven to be the dominant legacy of the demise of positivism in science
studies outside philosophy, and they have generated intense debate about
the goals and strategies appropriate to philosophical studies of science.
This is an important juncture at which to assess the implications of these
developments for philosophy of science. Increasingly, even the most
uncompromising constructivists acknowledge that sociologically reductive
accounts of science are inadequate, while a growing number of philosophers
recognize the need to broaden the scope of their contextualizing arguments.
Although this rapprochement has been tentative and uneven, it has given
rise to a fundamental reassessment of the traditional opposition between
epistemic and social categories of analysis that is evident in recent philosophical
work in a number of areas. I will focus here on arguments for rethinking
objectivist ideals that recognize their pragmatic, socio-historic contingency.
One central problem here, which feminist philosophers of science have taken
particular initiative in addressing, is to explain how it is that the features
of context typically seen as contaminants of scientific inquiry can serve
as a source of critical insight that enhances the integrity, credibility
and, indeed, the objectivity of scientific inquiry.
Symposium: Recent Advances in the Logic of Decision: A symposium in Honor of Richard Jeffrey.
Organizer: Allan Franklin, University of Colorado
Chair: Brian Skyrms, University of California, Irvine
Why We Still Need the Logic of Decision
James Joyce, University of Michigan
Abstract
Richard Jeffrey’s classic The Logic of Decision (LOD) defends a version
of expected utility theory that requires agents to strive to secure evidence
of desirable outcomes. As many philosophers have argued, Jeffrey’s
system fails as an account of rational choice because it is unable to properly
distinguish the causal properties of acts from their merely evidential
features. Only an appropriately “causal” utility theory can do the
work of a true “logic of decision.” This notwithstanding, Jeffrey’s
system has two desirable traits that its causal competitors lack.
Ethan Bolker’s elegant representation theorem provides LOD with a theoretical
foundation superior to that of any other utility theory. In addition,
LOD assigns utilities to actions in a manner that does not depend on the
way their consequences happen to be individuated. These advantages
are so significant, in my view, that we should reject any decision theory
that does not use Jeffrey’s system as its underlying account of value.
All value, I claim, is news value seen from an appropriate epistemic perspective,
with different perspectives being appropriate for the evaluation of an
agent’s actions and for the evaluation of events that lie outside her control.
The upshot of this is that causal decision theorists must employ Jeffrey’s
theory in order to properly formulate their own. I will show how
this can be done consistently. This dependence of causal decision
theory on the system of LOD may seem to present a problem, however, since
LOD is often compared unfavorably with other versions of decision theory
because it cannot, except in recherché cases, extract unique probability/utility
representations from facts about preferences (given a zero and unit for
measuring utility). Fortunately, this shortcoming is not a serious
one. Three points need to be made: First, all theories that
claim to deliver unique representations resort to technical tricks of dubious
merit. Second, reflection on the notion of expected utility theory
suggests that unique representations should not be extractable from facts
about preferences alone, but only from facts about preferences and beliefs.
Third, unique representability can be obtained in LOD if we supplement
the Jeffrey/Bolker axioms governing rational preference with independent
constraints on rational (comparative) belief. This last point turns
out to have significant theoretical implications because it lets us generalize
Bolker’s representation theorem so that it can be used as a foundation
for a wide range of decision theories, causal decision theory among them.
Title: TBA
Ethan Bolker, University of Massachusetts, Boston
Abstract:
To be supplied
“Conditionals and the Logic of Decision”
Richard Bradley, London School of Economics
Abstract
Rational decision making is typically guided by practical reasoning
of a hypothetical kind: the sort of reasoning an agent engages in when
she supposes that she will perform some or other action under some or other
set of conditions and then considers the consequences of her doing so under
just these conditions. In reasoning hypothetically agents show
that they can take rational attitudes to the possibilities falling within
the scope of their hypotheses: that they can believe that if they jump
out the window then they will hurt themselves, can desire that if it snows
tomorrow that school will be cancelled and can prefer that if beef is for
dinner that it be of French rather than British origin.
In this paper, I extend Richard Jeffrey’s logic of decision by incorporation
of conditionals as objects of agents’ attitudes. (A genuine augmentation
is involved because I take conditionals to be non-propositional).
In the extended logic, probabilities of conditionals equal their conditional
probabilities (in accordance with Adams’ famous thesis) and the desirabilities
of conditionals are weighted averages of the desirabilities of the mutually
exclusive consequences consistent with their truth, where the weights are
provided by the probabilities of the antecedently presupposed conditions.
In similar fashion, Bolker’s axioms are augmented to define the conditions
satisfied by rational preferences for conditionals (roughly, a conditional
a->b is preferable to another conditional c->d iff it is preferable to
learn that b is the case if a is, than to learn that d is the case if c
is). Unlike in the Jeffrey-Bolker system, the assumption that these
conditions are satisfied by an agent’s preferences suffices for them to
determine a unique representation of her degrees of belief and, up to a
choice of scale, of her degrees of desire (consistent with the extended
logic of decision). This shows, I suggest, that to obtain a complete and
precise description of a decision-maker’s state of mind it is necessary
to identify the attitudes she takes to the kinds of possibilities expressed
by conditionals.
"Subjective Thoughts on Subjective Probability:
What did Dick Jeffrey know and when did he know it? and a Mathematician's
Request for Help from the Philosophers"
Ethan Bolker, Department of Mathematics and Computer Science University
of Massachusetts, Boston
Abstract
In this talk I provide some views of contemporary decision theory from
my perspective as a professional mathematician, an amateur philosopher,
and Dick Jeffrey's friend. I'll discuss what Dick and I learned from each
other in Princeton in 1963, and what I've learned since as a decision theory
observer. In my speculations on the usefulness of that theory I finesse
the well studied question "what is probability?" but will address the question
"what is random?", with further thoughts on whether TCMITS will believe
the answer. I conclude with my own interpretation of Jeffrey's radical
probabilism.
Commentator:
Richard Jeffrey, Princeton University


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