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Kavya S. Kumar
Student at Sahyadri College of engineering and management
India
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51 connections
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Profile Strength:
Beginner


Measures¶
-
graph_tiger.measures.
algebraic_connectivity
(graph)¶ The larger the algebraic connectivity, the more robust the graph. This is due to it’s close connection to edge connectivity, where it serves as a lower bound: 0 < \(u_2\) < node connectivity < edge connectivity. This means that a network with larger algebraic connectivity is harder to disconnect [11,6].
- Parameters
graph – undirected NetworkX graph
- Returns
a float
-
graph_tiger.measures.
average_clustering_coefficient
(graph)¶ The global clustering coefficient is based on the number of triplets of nodes in the graph, and provides an indication of how well nodes tend to cluster together. The larger the average global clustering coefficient, the more robust the graph i.e., more triangles –> better connected –> more robust graph [6].
- Parameters
graph – undirected NetworkX graph
- Returns
a float
-
graph_tiger.measures.
avg_distance
(graph)¶ The average distance between all pairs of nodes in the graph. The smaller the average shortest path distance, the more robust the graph. This can be viewed through the lens of network connectivity i.e., smaller avg. distance –> better connected graph [6].
Undefined for disconnected graphs.
- Parameters
graph – undirected NetworkX graph
- Returns
a float
-
graph_tiger.measures.
avg_edge_betweenness
(graph, k=inf)¶ Similar to vertex betweenness, edge betweenness is defined as the number of shortest paths that pass through an edge e out of the total possible shortest paths. The smaller the average edge betweenness, the more robust the graph. We can view this as the load of the network being better distributed and less dependent on a few edges [6].
- Parameters
graph – undirected NetworkX graph
k – the number of nodes used to approximate betweenness centrality (k=10% of nodes is usually good)
- Returns
a float
-
graph_tiger.measures.
avg_inverse_distance
(graph)¶ The average inverse distance between all pairs of nodes in the graph. The larger the average inverse shortest path distance, the more robust the graph. This can be viewed through the lens of network connectivity i.e., larger average inverse distance –> better connected graph –> more robust graph [6].
Resolves the issue of not working for disconnected graphs in the avg_distance() function.
- Parameters
graph – undirected NetworkX graph
- Returns
a float
-
graph_tiger.measures.
avg_vertex_betweenness
(graph, k=inf)¶ The average vertex betweenness of a graph is the summation of vertex betweenness for every node in the graph. The smaller the average vertex betweenness, the more robust the graph. We can view this as the load of the network being better distributed and less dependent on a few nodes [6].
- Parameters
graph – undirected NetworkX graph
k – the number of nodes used to approximate betweenness centrality (k=10% of nodes is usually good)
- Returns
a float
-
graph_tiger.measures.
diameter
(graph)¶ The diameter of a connected graph is the longest shortest path between all pairs of nodes. The smaller the diameter the more robust the graph i.e., smaller diameter –> better connected graph –> more robust graph [6].
- Parameters
graph – undirected NetworkX graph
- Returns
an integer
-
graph_tiger.measures.
edge_connectivity
(graph)¶ Measures the minimal number of edges that can be removed to disconnect the graph. Larger edge connectivity –> harder to disconnect graph –> more robust graph [8].
- Parameters
graph – undirected NetworkX graph
- Returns
an integer
-
graph_tiger.measures.
effective_resistance
(graph, k=inf)¶ This measure views a graph as an electrical circuit where an edge \((i, j)\) corresponds to a resister of \(r_{ij} = 1\) Ohm and a node i corresponds to a junction. We say the effective graph resistance R is the sum of resistances for all distinct pairs of vertices The smaller the effective resistance, the more robust the graph [6,7,12].
- Parameters
graph – undirected NetworkX graph
- Returns
a float
-
graph_tiger.measures.
generalized_robustness_index
(graph, k=30)¶ This can be considered a fast approximation of spectral scaling. The smaller the value, the more robust the graph. Also helps determine if a graph has many bridges (bad for robustness) [14].
- Parameters
graph – undirected NetworkX graph
- Returns
a float
-
graph_tiger.measures.
get_measures
()¶ Returns a list of strings representing all of the available graph robustness measures
- Returns
list of strings
-
graph_tiger.measures.
largest_connected_component
(graph)¶ This measure provides an indication of a graph’s connectivity by measuring the fraction of nodes contained in the largest connected component. The larger the value, the more robust the graph.
- Parameters
graph – undirected NetworkX graph
- Returns
a float
-
graph_tiger.measures.
natural_connectivity
(graph, k=inf)¶ Natural connectivity has a physical and structural interpretation that is tied to the connectivity properties of a network, identifying alternative pathways in a network through the weighted number of closed walks. The larger the natural connectivity (average eigenvalue of adjacency matrix), the more robust the graph [4].
- Parameters
graph – undirected NetworkX graph
- Returns
a float
-
graph_tiger.measures.
node_connectivity
(graph)¶ Measures the minimal number of vertices that can be removed to disconnect the graph. Larger vertex (node) connectivity –> harder to disconnect graph –> more robust graph [8].
- Parameters
graph – undirected NetworkX graph
- Returns
an integer
-
graph_tiger.measures.
num_spanning_trees
(graph, k=inf)¶ The number of spanning trees T is the number of unique spanning trees that can be found in a graph. The larger the number of spanning trees, the more robust the graph. This can be viewed from the perspective of network connectivity, where a larger set of spanning trees means more alternative pathways in the network [1,6].
- Parameters
graph – undirected NetworkX graph
- Returns
a float
-
graph_tiger.measures.
odd_subgraph_centrality
(i, lam, u)¶ Calculates the number of odd length closed walks that a node participates in [10]. Used in the calculation of spectral scaling and generalized robustness index.
- Parameters
i – node index
lam – largest eigenvalue
u – largest eigenvector
- Returns
a float
-
graph_tiger.measures.
run_measure
(graph, measure, k=inf)¶ Evaluates graph robustness according to a specified measure
- Parameters
graph – undirected NetworkX graph to measure
measure – string containing the robustness measure to evaluate
k – an integer for fast approximation of certain robustness measures. small k = fast, large k = precise
timeout – allows the user to stop running the measure after ‘x’ seconds.
- Returns
a float representing the robustness of the graph, or None if it times out or an error occurs
-
graph_tiger.measures.
spectral_gap
(graph)¶ The difference between the largest and second largest eigenvalues of the adjacency matrix (\(\lambda_1 - \lambda_2\)) is called the spectral gap \(\lambda_d\). The larger the spectral gap, the more robust the graph. Has an advantage over spectral radius since it accounts for undesirable bridges in the network [3,14].
- Parameters
graph – undirected NetworkX graph
- Returns
a float
-
graph_tiger.measures.
spectral_radius
(graph)¶ The largest eigenvalue \(\lambda_1\) of an adjacency matrix A is called the spectral radius. The larger the spectral radius, the more robust the graph. This can be viewed from its close relationship to the “path” or “loop” capacity in a network [5,17].
- Parameters
graph – undirected NetworkX graph
- Returns
a float
-
graph_tiger.measures.
spectral_scaling
(graph, k=inf)¶ Spectral scaling is a combination of the spectral gap and subgraph centrality. Spectral scaling takes into account if a graph has many bridges. The smaller the value, the more robust the graph [9].
- Parameters
graph – undirected NetworkX graph
- Returns
a float


marelac: Tools for Aquatic Sciences
Datasets, constants, conversion factors, and utilities for 'MArine', 'Riverine',
'Estuarine', 'LAcustrine' and 'Coastal' science.
The package contains among others: (1) chemical and
physical constants and datasets, e.g. atomic weights, gas
constants, the earths bathymetry; (2) conversion factors
(e.g. gram to mol to liter, barometric units,
temperature, salinity); (3) physical functions, e.g. to
estimate concentrations of conservative substances, gas
transfer and diffusion coefficients, the Coriolis force
and gravity; (4) thermophysical properties of the
seawater, as from the UNESCO polynomial or from the more
recent derivation based on a Gibbs function.
| Version: |
2.1.9 |
| Depends: |
R (≥ 3.2), shape |
| Imports: |
stats, seacarb |
| Published: |
2018-06-03 |
| Author: |
Karline Soetaert [aut, cre],
Thomas Petzoldt [aut],
Filip Meysman [cph],
Lorenz Meire [cph] |
| Maintainer: |
Karline Soetaert <karline.soetaert at nioz.nl> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
yes |
| CRAN checks: |
marelac results |
Downloads:
Reverse dependencies:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=marelac
to link to this page.


Kara Locks Horns With Leviathan in New Supergirl Episode 5.07 Promo
by Tudor LeonteThe CW has released a new promo for the upcoming Supergirl Episode 5.07, featuring the clash between Supergirl and Leviathan. The episode will air on November 17. The official synopsis of “Synopsis” reads as follows:
Supergirl (Melissa Benoist) finally learns the truth about Lena (Katie McGrath) while tangling with Leviathan. J’onn J’onnz (David Harewood) makes a discovery about his brother’s whereabouts.
Andi Armaganian directed the episode written by J. Holtham & Katie Rose Rogers.
RELATED – The CW’s Supergirl Season 5 Cast Adds Cara Buono and Mitch Pileggi
Supergirl stars Melissa Benoist (Glee) as Kara Danvers/Supergirl. Mehcad Brooks plays James Olsen, with Chyler Leigh (Grey’s Anatomy) as Alex Danvers, as well as Jeremy Jordan as Winslow ‘Winn’ Schott, and Katie McGrath (Merlin) as Lena Luthor. The show also stars Jess Rath as Brainiac 5, and David Harewood as Hank Henshaw/J’onn J’onnz.
Based on the DC characters created by Jerry Siegel and Joe Shuster, the series boasts executive producers Greg Berlanti, Sarah Schechter, as well as Robert Rovner, and Jessica Queller. Moreover, Berlanti Productions, in association with Warner Bros. Television, produces Supergirl.
Check out the new Supergirl episode 5.07 promo below. Then let us know what you think in the comments section!


| Modifier and Type | Method and Description |
|---|---|
Capabilities |
AbstractAssociator.getCapabilities()
Returns the Capabilities of this associator.
|
Capabilities |
FilteredAssociator.getCapabilities()
Returns default capabilities of the associator.
|
Capabilities |
SingleAssociatorEnhancer.getCapabilities()
Returns default capabilities of the base associator.
|
Capabilities |
FPGrowth.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
Associator.getCapabilities()
Returns the Capabilities of this associator.
|
Capabilities |
Apriori.getCapabilities()
Returns default capabilities of the classifier.
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
OneRAttributeEval.getCapabilities()
Returns the capabilities of this evaluator.
|
Capabilities |
CorrelationAttributeEval.getCapabilities()
Returns the capabilities of this evaluator.
|
Capabilities |
WrapperSubsetEval.getCapabilities()
Returns the capabilities of this evaluator.
|
Capabilities |
ClassifierSubsetEval.getCapabilities()
Returns the capabilities of this evaluator.
|
Capabilities |
ReliefFAttributeEval.getCapabilities()
Returns the capabilities of this evaluator.
|
Capabilities |
CfsSubsetEval.getCapabilities()
Returns the capabilities of this evaluator.
|
Capabilities |
PrincipalComponents.getCapabilities()
Returns the capabilities of this evaluator.
|
Capabilities |
ASEvaluation.getCapabilities()
Returns the capabilities of this evaluator.
|
Capabilities |
SymmetricalUncertAttributeEval.getCapabilities()
Returns the capabilities of this evaluator.
|
Capabilities |
ClassifierAttributeEval.getCapabilities()
Returns the capabilities of this evaluator.
|
Capabilities |
InfoGainAttributeEval.getCapabilities()
Returns the capabilities of this evaluator.
|
Capabilities |
GainRatioAttributeEval.getCapabilities()
Returns the capabilities of this evaluator.
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
MultipleClassifiersCombiner.getCapabilities()
Returns combined capabilities of the base classifiers, i.e., the
capabilities all of them have in common.
|
Capabilities |
AbstractClassifier.getCapabilities()
Returns the Capabilities of this classifier.
|
Capabilities |
Classifier.getCapabilities()
Returns the Capabilities of this classifier.
|
Capabilities |
SingleClassifierEnhancer.getCapabilities()
Returns default capabilities of the base classifier.
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
NaiveBayesMultinomial.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
BayesNet.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
NaiveBayesMultinomialText.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
NaiveBayes.getCapabilities()
Returns default capabilities of the classifier.
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
LinearRegression.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
SimpleLinearRegression.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
SMO.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
VotedPerceptron.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
Logistic.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
SGDText.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
SimpleLogistic.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
SMOreg.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
MultilayerPerceptron.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
GaussianProcesses.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
SGD.getCapabilities()
Returns default capabilities of the classifier.
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
RBFKernel.getCapabilities()
Returns the Capabilities of this kernel.
|
Capabilities |
StringKernel.getCapabilities()
Returns the Capabilities of this kernel.
|
Capabilities |
Puk.getCapabilities()
Returns the Capabilities of this kernel.
|
Capabilities |
PolyKernel.getCapabilities()
Returns the Capabilities of this kernel.
|
Capabilities |
Kernel.getCapabilities()
Returns the Capabilities of this kernel.
|
Capabilities |
PrecomputedKernelMatrixKernel.getCapabilities()
Returns the Capabilities of this kernel.
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
KStar.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
IBk.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
LWL.getCapabilities()
Returns default capabilities of the classifier.
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
KORAomega.getCapabilities() |
Capabilities |
CRplus.getCapabilities() |
Capabilities |
ALVOT.getCapabilities() |
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
ClassificationViaRegression.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
FilteredClassifier.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
IterativeClassifierOptimizer.getCapabilities()
Returns default capabilities of the base classifier.
|
Capabilities |
AdaBoostM1.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
CostSensitiveClassifier.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
CVParameterSelection.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
Vote.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
AttributeSelectedClassifier.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
LogitBoost.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
AdditiveRegression.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
Stacking.getCapabilities()
Returns combined capabilities of the base classifiers, i.e., the
capabilities all of them have in common.
|
Capabilities |
MultiClassClassifier.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
RegressionByDiscretization.getCapabilities()
Returns default capabilities of the classifier.
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
SerializedClassifier.getCapabilities()
Returns default capabilities of the base classifier.
|
Capabilities |
InputMappedClassifier.getCapabilities()
Returns default capabilities of the classifier.
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
JRip.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
OneR.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
ZeroR.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
DecisionTable.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
PART.getCapabilities()
Returns default capabilities of the classifier.
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
HoeffdingTree.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
J48.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
REPTree.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
LMT.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
RandomTree.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
DecisionStump.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
RandomForest.getCapabilities()
Returns default capabilities of the base classifier.
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
ClassifierTree.getCapabilities()
Returns default capabilities of the classifier tree.
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
M5Base.getCapabilities()
Returns default capabilities of the classifier, i.e., of LinearRegression.
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
FilteredClusterer.getCapabilities()
Returns default capabilities of the clusterer.
|
Capabilities |
EM.getCapabilities()
Returns default capabilities of the clusterer (i.e., the ones of
SimpleKMeans).
|
Capabilities |
Cobweb.getCapabilities()
Returns default capabilities of the clusterer.
|
Capabilities |
HierarchicalClusterer.getCapabilities() |
Capabilities |
Clusterer.getCapabilities()
Returns the Capabilities of this clusterer.
|
Capabilities |
FarthestFirst.getCapabilities()
Returns default capabilities of the clusterer.
|
Capabilities |
AbstractClusterer.getCapabilities()
Returns the Capabilities of this clusterer.
|
Capabilities |
Canopy.getCapabilities()
Returns default capabilities of the clusterer.
|
Capabilities |
MakeDensityBasedClusterer.getCapabilities()
Returns default capabilities of the clusterer (i.e., of the wrapper
clusterer).
|
Capabilities |
SimpleKMeans.getCapabilities()
Returns default capabilities of the clusterer.
|
Capabilities |
SingleClustererEnhancer.getCapabilities()
Returns default capabilities of the clusterer.
|
| Modifier and Type | Method and Description |
|---|---|
static Capabilities |
Capabilities.forInstances(Instances data)
returns a Capabilities object specific for this data.
|
static Capabilities |
Capabilities.forInstances(Instances data,
boolean multi)
returns a Capabilities object specific for this data.
|
Capabilities |
Capabilities.getAttributeCapabilities()
returns all attribute capabilities
|
Capabilities |
CapabilitiesHandler.getCapabilities()
Returns the capabilities of this object.
|
Capabilities |
FindWithCapabilities.getCapabilities()
The capabilities to search for.
|
Capabilities |
Capabilities.getClassCapabilities()
returns all class capabilities
|
Capabilities |
MultiInstanceCapabilitiesHandler.getMultiInstanceCapabilities()
Returns the capabilities of this multi-instance classifier for the
relational data (i.e., the bags).
|
Capabilities |
FindWithCapabilities.getNotCapabilities()
The "not to have" capabilities to search for.
|
Capabilities |
Capabilities.getOtherCapabilities()
returns all other capabilities, besides class and attribute related ones
|
| Modifier and Type | Method and Description |
|---|---|
static String |
CapabilitiesUtils.addCapabilities(String title,
Capabilities c)
generates a string from the capabilities, suitable to add to the help
text.
|
void |
Capabilities.and(Capabilities c)
performs an AND conjunction with the capabilities of the given Capabilities
object and updates itself
|
void |
Capabilities.assign(Capabilities c)
retrieves the data from the given Capabilities object
|
static TestInstances |
TestInstances.forCapabilities(Capabilities c)
returns a TestInstances instance setup already for the the given
capabilities.
|
static String |
CapabilitiesUtils.listCapabilities(Capabilities c)
returns a comma-separated list of all the capabilities, excluding interface-based ones.
|
void |
Capabilities.or(Capabilities c)
performs an OR conjunction with the capabilities of the given Capabilities
object and updates itself
|
void |
FindWithCapabilities.setCapabilities(Capabilities c)
Uses the given Capabilities for the search.
|
void |
FindWithCapabilities.setNotCapabilities(Capabilities c)
Uses the given "not to have" Capabilities for the search.
|
boolean |
Capabilities.supports(Capabilities c)
Returns true if the currently set capabilities support at least all of the
capabilities of the given Capabilities object (checks only the enum!)
|
boolean |
Capabilities.supportsMaybe(Capabilities c)
Returns true if the currently set capabilities support (or have a
dependency) at least all of the capabilities of the given Capabilities
object (checks only the enum!)
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
MatlabSaver.getCapabilities()
Returns the Capabilities of this saver.
|
Capabilities |
DatabaseSaver.getCapabilities()
Returns the Capabilities of this saver.
|
Capabilities |
DictionarySaver.getCapabilities()
Returns the Capabilities of this saver.
|
Capabilities |
AbstractSaver.getCapabilities()
Returns the Capabilities of this saver.
|
Capabilities |
JSONSaver.getCapabilities()
Returns the Capabilities of this saver.
|
Capabilities |
ArffSaver.getCapabilities()
Returns the Capabilities of this saver.
|
Capabilities |
CSVSaver.getCapabilities()
Returns the Capabilities of this saver.
|
Capabilities |
SerializedInstancesSaver.getCapabilities()
Returns the Capabilities of this saver.
|
Capabilities |
XRFFSaver.getCapabilities()
Returns the Capabilities of this saver.
|
Capabilities |
LibSVMSaver.getCapabilities()
Returns the Capabilities of this saver.
|
Capabilities |
C45Saver.getCapabilities()
Returns the Capabilities of this saver.
|
Capabilities |
SVMLightSaver.getCapabilities()
Returns the Capabilities of this saver.
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
FilteredNeighbourSearch.getCapabilities()
Returns default capabilities of the classifier.
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
Estimator.getCapabilities()
Returns the Capabilities of this Estimator.
|
Capabilities |
NormalEstimator.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
KernelEstimator.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
DiscreteEstimator.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
PoissonEstimator.getCapabilities()
Returns default capabilities of the classifier.
|
Capabilities |
MahalanobisEstimator.getCapabilities()
Returns default capabilities of the classifier.
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
Filter.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
AllFilter.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
RenameRelation.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
MultiFilter.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
Filter.getCapabilities(Instances data)
Returns the Capabilities of this filter, customized based on the data.
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
NominalToBinary.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
MergeNominalValues.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
AttributeSelection.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
AddClassification.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
ClassConditionalProbabilities.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
ClassOrder.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
Discretize.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
PartitionMembership.getCapabilities()
Returns the Capabilities of this filter.
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
ClassBalancer.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
SpreadSubsample.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
Resample.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
StratifiedRemoveFolds.getCapabilities()
Returns the Capabilities of this filter.
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
Center.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
RandomSubset.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
AddValues.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
ReplaceWithMissingValue.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
NumericToBinary.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
NumericToDate.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
NominalToBinary.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
StringToNominal.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
ReplaceMissingValues.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
NominalToString.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
Reorder.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
AddCluster.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
FirstOrder.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
RandomProjection.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
RemoveType.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
AddNoise.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
Transpose.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
SortLabels.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
Standardize.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
DateToNumeric.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
FixedDictionaryStringToWordVector.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
MergeManyValues.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
MergeTwoValues.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
MathExpression.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
TimeSeriesDelta.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
KernelFilter.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
TimeSeriesTranslate.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
MakeIndicator.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
RenameAttribute.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
MergeInfrequentNominalValues.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
RenameNominalValues.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
PrincipalComponents.getCapabilities()
Returns the capabilities of this evaluator.
|
Capabilities |
ClusterMembership.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
CartesianProduct.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
NumericTransform.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
OrdinalToNumeric.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
ClassAssigner.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
Discretize.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
InterquartileRange.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
AddID.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
SwapValues.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
Add.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
RemoveByName.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
Remove.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
ReplaceMissingWithUserConstant.getCapabilities() |
Capabilities |
Copy.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
ChangeDateFormat.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
NumericToNominal.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
AddUserFields.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
Obfuscate.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
AddExpression.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
NumericCleaner.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
StringToWordVector.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
RemoveUseless.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
Normalize.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
AddCluster.getCapabilities(Instances data)
Returns the Capabilities of this filter, makes sure that the class is never
set (for the clusterer).
|
Capabilities |
ClusterMembership.getCapabilities(Instances data)
Returns the Capabilities of this filter, makes sure that the class is never
set (for the clusterer).
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
RemoveMisclassified.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
SubsetByExpression.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
RemoveWithValues.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
Randomize.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
SparseToNonSparse.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
RemoveFrequentValues.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
Resample.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
RemovePercentage.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
RemoveFolds.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
RemoveDuplicates.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
ReservoirSample.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
RemoveRange.getCapabilities()
Returns the Capabilities of this filter.
|
Capabilities |
NonSparseToSparse.getCapabilities()
Returns the Capabilities of this filter.
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
GenericObjectEditor.CapabilitiesFilterDialog.getCapabilities()
returns the currently selected capabilities.
|
Capabilities |
GenericObjectEditor.getCapabilitiesFilter()
Returns the current Capabilities filter, can be null.
|
Capabilities |
ConverterFileChooser.getCapabilitiesFilter()
returns the capabilities filter for the savers, can be null if all are
listed.
|
| Modifier and Type | Method and Description |
|---|---|
void |
WorkbenchApp.notifyCapabilitiesFilterListeners(Capabilities filter)
Notify filter capabilities listeners of changes
|
void |
GenericObjectEditor.CapabilitiesFilterDialog.setCapabilities(Capabilities value)
sets the initial capabilities.
|
void |
GenericObjectEditor.setCapabilitiesFilter(Capabilities value)
Sets the capabilities to use for filtering.
|
void |
ConverterFileChooser.setCapabilitiesFilter(Capabilities value)
sets the capabilities that the savers must have. use null if all should be
listed.
|
| Modifier and Type | Method and Description |
|---|---|
Capabilities |
Explorer.CapabilitiesFilterChangeEvent.getFilter()
returns the associated Capabilities filter
|
| Modifier and Type | Method and Description |
|---|---|
void |
Explorer.notifyCapabilitiesFilterListener(Capabilities filter)
notifies all the listeners of a change
|
| Constructor and Description |
|---|
CapabilitiesFilterChangeEvent(Object source,
Capabilities filter)
Constructs a GOECapabilitiesFilterChangeEvent object.
|
Copyright © 2018 University of Waikato, Hamilton, NZ. All Rights Reserved.


Sylvanian Families Marlowe Tuxedo Cat Baby Carry Case
Cat baby Olive Marlow is the youngest member of the Tuxedo cat family - so called because of their distinctive black and white colouring! Olive loves to play in the nursery on her little see-saw, perfect for when her best friend comes to tea!


A passionate Developer having experience in Web Development and wants to develop sustainable and scalable social and technical systems to create impact in our society.
I’m a young Kenyan visionary in tech currently
a software development student in Moringa School.
I’m passionate about understanding and communicating the connection between tech and humans; we are tech and tech is us.
As a young African female in tech, I believe in working towards a more educated and innovative Africa
I want to be a part of the team that ensures that the future generation of African leaders in various industries have the skills and resources
they need to revolutionize the continent for the better.
This is why i became part of Moringa community.
The journey of a thousand miles begins with a ("Hello World!);
I LOVE ATTENDING SOCIAL EVENTS WHEN I AM NOT STARING AT MY TERMINAL!
I Also read a book once in a while.
Fullname: Felista Gatwiri Kiriinya Birth Date: November 15, 2001 State of Origin: Kenya Occupation: Student, Frontend Developer Address: 1506,Nanyuki<EMAIL_ADDRESS>I would love to hear from you, you can contact me by filling the form below. I am always ready to reply and give assistance where needed. Thanks!


Dimension Meetup runs on the blockchain and is a blockchain integrated platform that integrates blockchain games, blockchain activities, blockchain ticketing and user-generated content.The Dimension Meetup code is fully open source, developed for community developers, and motivated by the notarization economy.
Dimension Meetup's existing Earth module combines gameplay and openness. The future development direction is determined by community consensus.
In the Earth module, we divide the land by level, such as the earth, continents, countries, cities, landmarks, etc.These game assets are NFT(Non-Fungible Token), unique and chain-ready.Dimension Meetup will combine different levels of land to achieve different ways of playing.
In the map module, users can upload the landmarks autonomously. The landmarks are recorded on the blockchain and become user assets. The coinju provides a rich gameplay, giving users the greatest freedom to create space. Users can buy and sell landmarks, define the attributes of landmarks, hold events on landmarks, and earn income.
Users can become managers of the region by buying and selling land passes (eg, National Pass). Then they have the right to manage activities in their area.
Not yet open, please look forward to
In order to prevent users from uploading spam, we are now leaving the landmark review to the core players of the coinju community, which will be fully open to the community in the future.
We have opened two rounds of national trading games, and we are about to update our smart contracts. We will launch the third round of internal testing on December 14, 2018. The gameplay is as follows:
The third round of testing opened 249 countries, the starting price of Token in each country was 0.1 EON, and each purchase made the country's price increase by 35%.The amount of the next purchase will be returned to the previous player's principal and the value added will be distributed as follows:
Mortgage EON at the Dimension Meetup "Token -> Bonuspool " , you can get the dividend of the current project income in real time. The dividend will be distributed according to the proportion of mortgage EON
The third round of testing increased the countdown function, from 30 days to 0. Every EON flow into the smart contract for the purchase of land, the countdown increased by 1 minute. The countdown was 0 when the last purchased player won the total prize pool.
The token for Dimension Meetup is “EON”. The holder can share the profit of the Dimension Meetup and participate in the decentralized autonomy of the platform through token mortgage.In addition, EON is also an application token, players can use EON to purchase game assets. How to get EON


Jitsi Meet Desktop app
You may need to click
Open Jitsi Meet
in the dialog shown by the browser.
Don’t have Jitsi Meet installed?
Download Now
Use the web app instead
Life is more fun when you use the Jitsi Meet Electron app
Download the app
Use the web app instead


Nov. 21 (UPI) -- The cast of Frozen including Kristen Bell, Idina Menzel, Josh Gad and Jonathan Groff performed the Disney musical on a busy Los Angeles intersection with James Corden on The Late Late Show.
The segment, which aired on Wednesday, was Corden's latest installment of Crosswalk the Musical.
The group donned costumes, used props and were joined by backup dancers in order to perform in front of unsuspecting drivers songs from Frozen and Frozen II, which hits theaters on Friday.
Bell, Menzel and the others would put on the show in different parts during every red light. Corden would then have to rush everyone off the street every time the light turned green.
The late night host also competed with Menzel for the role of Elsa, who the Broadway star voices in the film. Corden was regulated to dressing up as a snowflake after Menzel displayed her singing ability.
Menzel last performed "Let It Go" while standing on top of a car.
Bell and Menzel were recently honored with stars on the Hollywood Walk of Fame simultaneously.
Kristen Bell, Idina Menzel attend 'Frozen II' premiere in LA


At BenchMark Valley Behavioural group home, we strive to attain the delivery of the highest quality of healthcare services to our residents in a harmonious and comfortable atmosphere
We are here to offer you help and support in every step of your recovery
By supporting each client and family in identifying anf building their resources and strenght, we empower them to approach the future with renewed optimism and a stronger sense of possibilities for creating a new and different story for their lives.
"I have learned an incredible amount about myself and how I am, as well as about my illness. I feel it
is now my time to move on with my life. I will take with me the toold and coping mechanism that will help
me conquer my illness."
-Former Patient
“ Though no one can go back and make a brand new start, anyone can start from now and make a brand new ending. ”
Recovery here at Benchmark involves a team work effort between the Client, Family Members or other support parties and BenchMark Valley as a whole. To make this a sucess we need every cliet to go through three main steps to ensure full recovery.
We would love to show you our home. Simply Contact us or make a booking with us to schedule a tour of our facilities or request Information.


Quick Installation¶
Use this guide if you are an expert Python user and aware of Python virtual environment and package management. For a detailed and clean installation guide, see the Detailed Installation section.
Prerequisites¶
NEORL is tested on python3 (3.5-3.7)
with the development headers.
Note
NEORL supports tensorflow
versions from 1.8.0 to 1.14.0, we do not support tensorflow >= 2.0. Please, make sure to uninstall tensorflow
if already installed on your environment or have a proper version. If tensorflow
does not exist, NEORL will automatically install tensorflow-1.14.0
for most stability.
Ubuntu Prerequisites¶
sudo apt-get update && sudo apt-get install cmake python3-dev
Mac OS X Prerequisites¶
NEORL is not tested yet on Mac OS, the Mac OS NEORL is currently under development.
Windows 10 Prerequisites¶
To install NEORL on Windows, it is recommended to install Anaconda3 on the machine first to have some pre-installed packages, then open “Anaconda Prompt” as an administrator and use the instructions below for Install using pip.
Note
You can access Anaconda3 archives for all OS installers from this page https://repo.anaconda.com/archive/
Note
We typically recommend creating a new virtual environment for NEORL to avoid version conflicts and compatibility issues with other projects.
conda create --name neorl python=3.7
conda activate neorl
Install using pip¶
For both Ubuntu and Windows, you can install NEORL via pip
pip install neorl --extra-index-url https://test.pypi.org/simple


--- layout: page title: 3 High Poly Objects navlink: false permalink: /3D/3D2_3_objects/ ---
These are 3 objects I modeled and textured for a school assignment (at Digital Arts and Entertainment) as a way to learn subdivision surface modeling as well as procedural texturing. I spent around 4 weeks working this project.
Objects modeled:
Tools used:
(Click on the images to see higher resolution versions)


|
Panda3D
|
This class is used as a namespace to group several global properties of Panda. More...
Public Member Functions | |
| addSystem (str system) | |
| Intended for use by each subsystem to register itself at startup. More... | |
| int | getNumSystems () |
| Returns the number of Panda subsystems that have registered themselves. More... | |
| str | getSystem (int n) |
| Returns the nth Panda subsystem that has registered itself. More... | |
| list | getSystems () |
| str | getSystemTag (str system, str tag) |
| Returns the value associated with the indicated tag for the given system. More... | |
| bool | hasSystem (str system) |
| Returns true if the current version of Panda claims to have the indicated subsystem installed, false otherwise. More... | |
| bool | heapTrim (int pad) |
| Attempts to release memory back to the system, if possible. More... | |
| output (Ostream out) | |
| setSystemTag (str system, str tag, str value) | |
| Intended for use by each subsystem to register its set of capabilities at startup. More... | |
| write (Ostream out) | |
Static Public Member Functions | |
| static str | getBuildDate () |
| Returns a string representing the date and time at which this version of Panda (or at least dtool) was compiled, if available. More... | |
| static TypeHandle | getClassType () |
| static str | getCompiler () |
| Returns a string representing the compiler that was used to generate this version of Panda, if it is available, or "unknown" if it is not. More... | |
| static str | getDistributor () |
| Returns the string defined by the distributor of this version of Panda, or "homebuilt" if this version was built directly from the sources by the end- user. More... | |
| static str | getGitCommit () |
| Returns a string representing the git commit hash that this source tree is based on, or the empty string if it has not been specified at build time. More... | |
| static PandaSystem | getGlobalPtr () |
| Returns the global PandaSystem object. More... | |
| static int | getMajorVersion () |
| Returns the major version number of the current version of Panda. More... | |
| static int | getMemoryAlignment () |
| Returns the memory alignment that Panda's allocators are using. More... | |
| static int | getMinorVersion () |
| Returns the minor version number of the current version of Panda. More... | |
| static str | getP3dCoreapiVersionString () |
| Returns the current version of Panda's Core API, expressed as a string of dot-delimited integers. More... | |
| static str | getPackageHostUrl () |
| Returns the URL of the download server that provides the Panda3D distributable package currently running. More... | |
| static str | getPackageVersionString () |
| Returns the version of the Panda3D distributable package that provides this build of Panda. More... | |
| static str | getPlatform () |
| Returns a string representing the runtime platform that we are currently running on. More... | |
| static int | getSequenceVersion () |
| Returns the sequence version number of the current version of Panda. More... | |
| static str | getVersionString () |
| Returns the current version of Panda, expressed as a string, e.g. More... | |
| static bool | isOfficialVersion () |
| Returns true if current version of Panda claims to be an "official" version, that is, one that was compiled by an official distributor of Panda using a specific version of the panda source tree. More... | |
Public Attributes | |
| String | build_date |
| Returns a string representing the date and time at which this version of Panda (or at least dtool) was compiled, if available. More... | |
| String | compiler |
| Returns a string representing the compiler that was used to generate this version of Panda, if it is available, or "unknown" if it is not. More... | |
| String | distributor |
| Returns the string defined by the distributor of this version of Panda, or "homebuilt" if this version was built directly from the sources by the end- user. More... | |
| String | git_commit |
| Returns a string representing the git commit hash that this source tree is based on, or the empty string if it has not been specified at build time. More... | |
| int | major_version |
| Returns the major version number of the current version of Panda. More... | |
| int | memory_alignment |
| Returns the memory alignment that Panda's allocators are using. More... | |
| int | minor_version |
| Returns the minor version number of the current version of Panda. More... | |
| bool | official_version |
| Returns true if current version of Panda claims to be an "official" version, that is, one that was compiled by an official distributor of Panda using a specific version of the panda source tree. More... | |
| String | platform |
| Returns a string representing the runtime platform that we are currently running on. More... | |
| int | sequence_version |
| Returns the sequence version number of the current version of Panda. More... | |
| String | systems [] |
| Returns the nth Panda subsystem that has registered itself. More... | |
| String | version_string |
| Returns the current version of Panda, expressed as a string, e.g. More... | |
This class is used as a namespace to group several global properties of Panda.
Application developers can use this class to query the runtime version or capabilities of the current Panda environment.
| addSystem | ( | str | system | ) |
Intended for use by each subsystem to register itself at startup.
|
static |
Returns a string representing the date and time at which this version of Panda (or at least dtool) was compiled, if available.
|
static |
|
static |
Returns a string representing the compiler that was used to generate this version of Panda, if it is available, or "unknown" if it is not.
|
static |
Returns the string defined by the distributor of this version of Panda, or "homebuilt" if this version was built directly from the sources by the end- user.
This is a completely arbitrary string.
|
static |
Returns a string representing the git commit hash that this source tree is based on, or the empty string if it has not been specified at build time.
|
static |
Returns the global PandaSystem object.
|
static |
Returns the major version number of the current version of Panda.
This is the first number of the dotted triple returned by get_version_string(). It changes very rarely.
|
static |
Returns the memory alignment that Panda's allocators are using.
|
static |
Returns the minor version number of the current version of Panda.
This is the second number of the dotted triple returned by get_version_string(). It changes with each release that introduces new features.
| int getNumSystems | ( | ) |
Returns the number of Panda subsystems that have registered themselves.
This can be used with get_system() to iterate through the entire list of available Panda subsystems.
|
static |
Returns the current version of Panda's Core API, expressed as a string of dot-delimited integers.
There are usually four integers in this version, but this is not guaranteed.
The Core API is used during the runtime (plugin) environment only. This may be the empty string if the current version of Panda is not built to provide a particular Core API, which will be the normal case in a development SDK. However, you should not use this method to determine whether you are running in a runtime environment or not.
|
static |
Returns the URL of the download server that provides the Panda3D distributable package currently running.
This can be used, along with the get_package_version_string(), to uniquely identify the running version of Panda among distributable Panda versions.
See get_package_version_string() for more information.
This string is set explicitly at compilation time. Normally, it should be set to a nonempty string only when building a Panda3D package for distribution.
|
static |
Returns the version of the Panda3D distributable package that provides this build of Panda.
When the currently-executing version of Panda was loaded from a distributable package, such as via the browser plugin, then this string will be nonempty and will contain the corresponding version string. You can build applications that use this particular version of Panda by requesting it in the pdef file, using "panda3d", this version string, and the download host provided by get_package_host_url().
If this string is empty, then the currently-executing Panda was built independently, and is not part of a distributable package.
This string is set explicitly at compilation time. Normally, it should be set to a nonempty string only when building a Panda3D package for distribution.
|
static |
Returns a string representing the runtime platform that we are currently running on.
This will be something like "win32" or "osx_i386" or "linux_amd64".
|
static |
Returns the sequence version number of the current version of Panda.
This is the third number of the dotted triple returned by get_version_string(). It changes with bugfix updates and very minor feature updates.
| str getSystem | ( | int | n | ) |
Returns the nth Panda subsystem that has registered itself.
This list will be sorted in alphabetical order.
| list getSystems | ( | ) |
| str getSystemTag | ( | str | system, |
| str | tag | ||
| ) |
Returns the value associated with the indicated tag for the given system.
This provides a standard way to query each subsystem's advertised capabilities. The set of tags and values are per-system and implementation-defined.
The return value is the empty string if the indicated system is undefined or if does not define the indicated tag.
|
static |
Returns the current version of Panda, expressed as a string, e.g.
"1.0.0". The string will end in the letter "c" if this build does not represent an official version.
| bool hasSystem | ( | str | system | ) |
Returns true if the current version of Panda claims to have the indicated subsystem installed, false otherwise.
The set of available subsystems is implementation defined.
| bool heapTrim | ( | int | pad | ) |
Attempts to release memory back to the system, if possible.
The pad argument is the minimum amount of unused memory to keep in the heap (against future allocations). Any memory above that may be released to the system, reducing the memory size of this process. There is no guarantee that any memory may be released.
Returns true if any memory was actually released, false otherwise.
|
static |
Returns true if current version of Panda claims to be an "official" version, that is, one that was compiled by an official distributor of Panda using a specific version of the panda source tree.
If this is true, there will not be a "c" at the end of the version string returned by get_version_string().
Note that we must take the distributor's word for it here.
| output | ( | Ostream | out | ) |
| setSystemTag | ( | str | system, |
| str | tag, | ||
| str | value | ||
| ) |
Intended for use by each subsystem to register its set of capabilities at startup.
| write | ( | Ostream | out | ) |
| String build_date |
Returns a string representing the date and time at which this version of Panda (or at least dtool) was compiled, if available.
| String compiler |
Returns a string representing the compiler that was used to generate this version of Panda, if it is available, or "unknown" if it is not.
| String distributor |
Returns the string defined by the distributor of this version of Panda, or "homebuilt" if this version was built directly from the sources by the end- user.
This is a completely arbitrary string.
| String git_commit |
Returns a string representing the git commit hash that this source tree is based on, or the empty string if it has not been specified at build time.
| int major_version |
Returns the major version number of the current version of Panda.
This is the first number of the dotted triple returned by get_version_string(). It changes very rarely.
| int memory_alignment |
Returns the memory alignment that Panda's allocators are using.
| int minor_version |
Returns the minor version number of the current version of Panda.
This is the second number of the dotted triple returned by get_version_string(). It changes with each release that introduces new features.
| bool official_version |
Returns true if current version of Panda claims to be an "official" version, that is, one that was compiled by an official distributor of Panda using a specific version of the panda source tree.
If this is true, there will not be a "c" at the end of the version string returned by get_version_string().
Note that we must take the distributor's word for it here.
| String platform |
Returns a string representing the runtime platform that we are currently running on.
This will be something like "win32" or "osx_i386" or "linux_amd64".
| int sequence_version |
Returns the sequence version number of the current version of Panda.
This is the third number of the dotted triple returned by get_version_string(). It changes with bugfix updates and very minor feature updates.
| String systems[] |
Returns the nth Panda subsystem that has registered itself.
This list will be sorted in alphabetical order.
| String version_string |
Returns the current version of Panda, expressed as a string, e.g.
"1.0.0". The string will end in the letter "c" if this build does not represent an official version.


There are currently three web APIs that can be used for cross-tab communication: Local Storage, Broadcast Channels and Shared Workers.
In many of these tests, Shared Workers outperformes the other APIs by at least one order of magnitude. Unfortunately, not all major browsers support the API. Therefore, any public-facing cross-tab communication framework should probably dynamically degrade from the better API to at least Local Storage since it enjoys much wider support in browsers.
These tests has been written in ECMAScript 5.1 in order to be compatible with contemporary browsers. Currently, only Firefox version 38 supports all three web APIs.


gratum.etl
Interfaces
Openable
Classes
AfterStep
Condition
Duration
FileOpenable
LoadStatistic
Pipeline
Rejection
Step
Enums
RejectionCategory


The Atlantic Current: Mapping the Virgins of Guadalupe and Remedios
La Cerollera, Teruel
Verified
The Church of los Remedios was built in the baroque style in the 18th century by architect Antonio Moreno. During the Civil War, all altarpieces were destroyed.
Works cited
- “La Cerollera” Bajo Aragon.
- “LA IGLESIA PARROQUIAL DE NUESTRA SEÑORA DEL REMEDIO” Fundación Quílez Llisterri.
- “Historia” La Cerollera
Cite this article
Katherine Dau. "La Cerollera, Teruel." The Atlantic Current: Mapping the Virgins of Guadalupe and Remedios. . https://dauk19.wludci.info/atlanticcurrent/article/2019-02-06-la-cerollera-teruel/


Trials to begin on new cancer treatment
Clinical trials on a new treatment expected to improve the survival rates for sufferers of lung and ovarian cancer will begin soon in South Australia.
Recruiting patients for the trials will start in early 2020 thanks to a partnership between AusHealth and researchers at the Royal Adelaide Hospital.
RAH Cancer Clinical Trials Unit chief Michael Brown says the treatment uses antibody technology and has the potential to change the way solid cancers are fought.
"The test uses antibodies that carry a low dose of radiation and target a specific protein that is created by dying or dead cancer cells," Professor Brown said.
"The radiation signal is picked up on a scan, so we can see in patients who have received chemotherapy just how well the chemotherapy is killing the cancer cells.
"Our trial aims to test how well the antibodies can target specific cancer cells to deliver low-dose radiation."
Professor Brown said the new method, the result of a decade-long research effort, might transfer to other cancers.
"In the first instance we are trialling the test on lung and ovarian cancer patients receiving chemotherapy, but we believe this approach has the potential to boost the effectiveness of other cancer treatments," he said.
South Australian Health Minister Stephen Wade said the $33 million investment in the local research was the largest commercial deal for Adelaide developed medical technology in 20 years.
"This partnership, driven by AusHealth, links RAH researchers with pharmaceutical investors, and will help to fast track bringing this important technology to patients," Mr Wade said.


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To make sure that you keep using git random smoothly, you may generate a token and add it below to override the Rate Limit imposed by Github


What's next? You can use<EMAIL_ADDRESS>to write to all of your representatives at once. Or send individual emails:
{% include 'www/partials/your_reps.html' with user=user %}Tips for emailing Congress {% if msg %}next time{% endif %}
{% include 'www/partials/faq_tips.html' %}


--- layout: post title: Using Eclipse WTP with Maven's eclipse:eclipse Goal date: 2011-11-01 05:45:52.000000000 -07:00 type: post parent_id: '0' published: true password: '' status: publish categories: [] tags: - download - eclipse - jpa - maven - Programming - wtp meta: _edit_last: '1' tmac_last_id: '166390219044700160' _jetpack_related_posts_cache: a:1:{s:32:"8f6677c9d6b0f903e98ad32ec61f8deb";a:2:{s:7:"expires";i:1542953334;s:7:"payload";a:3:{i:0;a:1:{s:2:"id";i:695;}i:1;a:1:{s:2:"id";i:724;}i:2;a:1:{s:2:"id";i:946;}}}} author: login: Philihp email<EMAIL_ADDRESS>display_name: Philihp first_name: '' last_name: '' ---
If you use Maven's "eclipse:eclipse" goal to generate a project descriptor for eclipse, by default you're just going to get a plain Java project. You'll have to add in the Dynamic Web facet in order to tell Eclipse that you can deploy this project in a web container. The easy way around this is to configure the maven-eclipse-plugin in the pom.xml file like this:
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-eclipse-plugin</artifactId>
<version>2.8</version>
<configuration>
<wtpContextName>some/url/context</wtpContextName>
<wtpversion>1.5</wtpversion>
</configuration>
</plugin>
Also, I like to download sources and Javadoc, which makes navigating in Eclipse a lot easier. This can be done like this.
<plugin>
...
<configuration>
<downloadSources>true</downloadSources>
<downloadJavadocs>true</downloadJavadocs>
</configuration>
</plugin>
Supposing you also want your project to have JPA facets, or other additional project facets you could also add them in like this
<plugin>
...
<configuration>
<additionalProjectFacets>
<jpt.jpa>2.0</jpt.jpa>
</additionalProjectFacets>
</configuration>
</plugin>
And all of these can be combined to do this
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-eclipse-plugin</artifactId>
<version>2.8</version>
<configuration>
<wtpContextName>list</wtpContextName>
<wtpversion>1.5</wtpversion>
<downloadSources>true</downloadSources>
<downloadJavadocs>true</downloadJavadocs>
<additionalProjectFacets>
<jpt.jpa>2.0</jpt.jpa>
</additionalProjectFacets>
</configuration>
</plugin>


🍽 ARBI JHOL 🍽
Shallow fried Arbi & Lotus seeds cooked in ginger tomato gravy is a delicious and healthy gravy recipe that is a must try. Make this popular dish from Uttar Pradesh and serve with roti or phulka for dinner.
Ingredients
- 10 Colocasia root (Arbi) , chopped into discs
- 15 Phool Makhana (Lotus Seeds)
- 2 Tomato , chopped
- 1 inch Ginger , garted Sunflower Oil , to cook
- 2 Green Chillies , chopped
- 1 teaspoon Cumin seeds (Jeera)
- 1 pinch Asafoetida (hing)
- 1 tsp Red Chilli powder
- 1 tsp Coriander Powder
- 1/4 tsp cumin powder
- 1/2 tsp Turmeric Powder
- 1/2 tsp Garam masala Powder
Directions
- To begin making Arbi Jhol Recipe - Colocasia & Lotus Seeds Sabzi, wash, peel and cut colocasia roots into discs of uniform thickness (uniformity will help in even cooking).
 Keep aside.
- In the same pan, roast lotus seeds till crisp. Keep aside
- In a mixer, grind tomato, green chilli and ginger and take out in a bowl.
- Heat a kadai with a little ghee/oil. Once the oil is hot, add cumin seeds and let it sizzle. Add hing to the oil and once the hing releases its aromas add the tomato puree with chilli and ginger.
- Add salt and saute till you feel that the puree is cooked well and it starts coming together.
- Next, add dry roasted colocasia, salt to taste, and about a cup of water. Mix well, simmer and close the lid and cook for 5-6 minutes.
- When you feel that the colocasia/arbi is almost cooked, add roasted lotus seeds . Simmer and bring to boil for 2-3 minutes such that the taste is seeped in well into both arbi and lotus seeds.
- Finally add garam masala, and crushed kasoori methi to the Arbi Jhol. Mix well and switch off. Garnish Arbi Jhol with chopped coriander leaves and serve.
Serve Arbi Jhol Recipe with Pudina Tawa Paratha, Baingan Ka Chokha Recipe, steamed rice and Dal Tadka Recipe Flavored with Lemon and Coriander.


I read an article recently by Educause Review and I wonder if your able to pick up on what I did. Before reading ahead, take a minute and read through their article. It's a good take on the state of affairs in education as it relates to edtech...
Ok class, pencils down. Now; Who can tell me what is wrong with the following argument?
What, the, actually F is that!? So let me get this straight. Education is important as a social good, it's something that generally speaking still isn't completely driven by a pure profit motive. It's situated somewhere between socialist utopia (Everyone has access maaaan ) and capitalist utopia (Everyone competes and knowledge is part of that competition). And you address concerns of "Weeellll it seems like these technology vendors have no real foundation in education / instructional principles" with the equivalent of the "meh" emoji followed by a hands up in the air? I read this article and went off on a total drill down rant on twitter (unfortunately against someone who's an edtech provider and he wasn't the target it just sorta happened that way). They for once, finally, omg finally identify the problem: That edtech producers don't work in Education and have almost no clue wtf they are doing other then making something shiny. There is little to no research behind what they do. AND THEY ARE PURELY PROFIT DRIVEN .  This false narrative is what perpetuates the cycles of us training people, them leaving and immediately forming companies with knowledge of our problem space and then selling us into insane contracts for things that aren't actually hitting the mark.
Instructure, all the rage with C levels becasue they adopted Twitter Boostrap and React in a world driven by home-made solutions, did just that. A bunch of students said "blackboard sucks" and threw something together rather quickly which is superior to it. Think for a second then... why can't we collectively do the same? NO!
If you want to stop edtech driving us around collectively and being part of the techno-centric worldview that forces education to be more about money then learning, then you've gotta defeat this narrative. I view our team and those we collaborate with as being among the first to plant that flag in the ground. We are educators, trainers, designers, technologists, students, learners, and administrators all working together with a singular purpose to solve this problem. We are going to deliver solutions that are not profit motive driven, that are more open, more accessible, have research backing , and are ultimately better then anything you will see produced external to education.
Watch us! This is just a small glimpse of what we have coming to all systems near you..


This is a paragraph. Simple paragraph tags for content
Ensure we dont get into a bad habit of using tags for styling your elements
Simple anchor tag embedded within a paragraph tag. Anchors link out to files or urls on the web Really random worm website


We will utilize the OpenAPI/ Swagger standard in order to produce our API documentation.
By using the OpenAPI standard, we can automatically produce robust API documentation and even generate an SDK and NPM module for interacting with/ consuming our API.
The goal of this project is to eventually open source all of the code and create a public API, however, for now we will continue to use an authenticated API while prototyping.
For more information on our documentation, you can visit our GitHub Repo.


PASS's Programs
Click on one of the links to your right to get started and learn more about these programs and annual events that PASS puts on.
Click on one of the links to your right to get started and learn more about these programs and annual events that PASS puts on.
| General Meetings | Meetings open to the public occur 2-4 times per semester, with the final meeting being facilitated by our interns |
| Mixers | Social events where new first year and transfer students can meet the upperclassmen |
| Study Halls/Jams | Held every Sunday to provide a room for folks to study or acquire resource materials. Study jams are held at 89 Dwinelle from 9am-9pm. Also, during dead week, the multicultural community center (mcc) is transformed into a study space from 11AM until 12AM. |
| Biyuti Meetings | biyuti meetings are generally held twice a month on tuesdays |
| PASOC | During the Fall, PASOC is a weekly, 2 unit course P/NP (AAADS 98). During the Spring, PASOC takes the form of multiple workshops catering to Spring admits. |
| Retreats | Multiple retreats are held for the various programs put on by PASS, some of these include a retreat for General Members held in the Spring semester as well as a Gender and Sexuality Awareness component retreat |


THANK YOU FOR PURCHASE!
If you are theme developer and you want to include our plugin with your theme for sale on Themeforest (or other marketplace) you can do this if you purchased one EXTENDED theme license for every theme where you include plugin. If you will not follow this rule your themes will be DMCA rejected.
If you are regular user you need to purchase one REGULAR license for every site that use this plugin.
You just purchased one of our amazing WordPress plugins and we
hope that you will enjoy with this purchase!
To help us with plugin FREE for you updates with new cool staff and new features please take 1 minute to leave stars rating for this plugin on CodeCanyon:
- Go to CodeCanyon login and navigate to your account
- Click Downloads link and you will see your
purchases list
- Click stars around our plugin to leave stars
rating:
- Thanks! This little thing will help us to release new plugin updates and new cool staff for you quickly and for FREE!
ULTIMATE WORDPRESS PLUGINS SERIES
We are working hard to develop more interesting WordPress and WooCommerce plugins in our Ultimate collection. Check some of our items from Ultimate WordPress plugins collection.
Hosting RECOMENDATION
We recommend you to use Bluehost hosting to host your sites based on our themes and plugins.
This hosting have a lot of different tariff plans starting from $3.95 per month, all plans include a lot of FREE bonuses and unlimited possibilities:
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The most important and great thing that with Bluehost you can install your OpenCart, WordPress or Magento website in just 5 minutes and 1-2 clicks! That allow you to not spend money for installation services and install different scripts yourself automatically, without any software knowledge! This is why we can recommend Bluehost for all our customers again.
Installation
You must have WPBakery Page Builder plugin installed to use our plugin. Our plugin add Timeline/Roadmap element to WPBakery Page Builder elements list.
Unzip ZIP file that you download after purchase on CodeCanyon. The following files and folders will be in the unzipped file:
- mgroadmaptimeline.zip (Packed plugin file for install)
- mgroadmaptimeline folder - plugin for manual FTP upload
- Documentation (This file)
Plugin can be uploaded in two ways:
- FTP upload: Using your FTP program, upload the non-zipped mgroadmaptimeline folder into the /wp-content/plugins/ folder on your server.
- WordPress upload: Navigate to Plugins > Add New > Upload plugin. Go to browse, and select the zipped mgroadmaptimeline.zip file. Hit Install Now and the plugin will be uploaded and installed.
Once the plugin is uploaded, you need to install and activate it. Go to Plugins and activate Ultimate RoadMap Timeline plugin.
If you need detailed help installing Wordpress plugin see the link here : http://codex.wordpress.org/Managing_Plugins
CREATING TIMELINE/ROADMAP ELEMENTS
You can create unlimited timelines with unlimited elements everywhere on your content area on site (pages, posts, custom post types, etc).
- Go to page where you want to create your timeline and enable
backend or frontend WPBakery Page Builder edit mode (we will use
backend mode as example in this Documentation).
- Click + to add new page builder element and select MGT
Timeline element from list:
- You will see Timeline element options dialog where you can configure all element options for your timeline event - check next documentation section for available options help.
- Set options that you like and click Save changes.
- Add all other timeline elements and Publish your page.
- You can add Timeline elements inside any rows or columns, but make sure your column have enough width to fit timeline elements nicely.
Timeline/ROADMAP element options
- Timeline item title - your event title (for ex. "Store opening").
- Title color - text color for your title if
you want to override default color.
- Timeline item text - your event description. You can use HTML and third party shortcodes here, insert images or videos. If you want to add video use its embeding code (for ex. for Youtube) in Text mode for content editor.
- Timeline image - image for your event. Use if you want to add image after text or instead of text.
- Timeline date year - Year for your event date. You can add full date or any text here to display it with large text.
- Timeline date month - Month for your event date. You can add any text here (for ex. "Q1-Q4") or leave it empty.
- Year text color - text color for your year if you want to override default color.
- Month text color - text color for your month if you want to override default color.
- Text block style - change background appearance for your timeline item text element.
- Text block border style - change corners style for your timeline item text element.
- Text color - text color for your timeline item text element if you want to override default color.
- Text background color - text background color for your timeline item text element if you want to override default color. If you selected bordered or double bordered text block style (#9) property text background color will change border color (not background).
- Timeline vertical line position - This is important option for your timeline layout. If you adding first (top) timeline element you must choose "Bottom" line position here. If you adding last (bottom) timeline element here you must choose "Top" line position here. If you adding middle element - use "Both" option value here.
- Date position - you should alternate this value for your timeline elements to display it at left, right, left, right, etc. So for example your odd elements will have "Left" here, your even elements will have "Right" here.
- Timeline vertical line color - vertical line color for this timeline element if you want to override default color.
- Pointer style - style for your element pointer (line from element text block to vertical line).
- Timeline element link url - add url to your element title and icon if you wish.
- Open link in new tab - used for Timeline element url link.
- Disable icon - use this option to disable icon and show just small bullet for this element in vertical line.
- Timeline icon library and icon - choose icon that you want to use from available. This option will be ignored if you disabled icon.
- Icon size - Change icon size (note: this does not change icon background size). You does not need to input "px" here, input just integer value, for ex. 32. This option will be ignored if you disabled icon.
- Icon color - icon color for your month if you want to override default color. This option will be ignored if you disabled icon.
- Icon background color - change icon background color. This option will work even if you disabled icon (you will change small bullet background color).
- Timeline Icon Border style - change border style for icon box. This option will work even if you disabled icon (you will change small bullet border style).
- Add mouse hover shadow effect - use to add mouse hover animation for icon or bullet.
- CSS Animation - on scroll appear animation for your timeline element.
TROUBLESHOOTING
This plugin will work fine with any well-coded WordPress themes that works well with WPBakery Page Builder plugin. If you see missing or broken styles, incorrect layouts for Timeline elements this means your theme override our plugin styles in incorrect way and you need to contact theme developer for help (he need to modify theme styles to not override our plugin styles).
Translations
This plugin is translation ready and WPML plugin compatible and this mean you can easy adapt it to your language or use it multilanguage. You can translate plugin manualy with WPML or LocoTranslate plugins.
Manual theme translation
We included POT files for translation with theme:
- /wp-plugins/mgroadmaptimeline/languages/ - main plugin translations
Read
this section on Wordpress website about WP translations.
Translation with LOCO TRANSLATE PLUGIN
If you installed and activated LocoTranslate Translation Manager you can translate plugin with it:
- Install and activate LocoTranslate
- Go to Loco Translate > Manage translations
- Click New language near our plugin in list
- Translate all plugin strings in admin panel
Support AND UPDATES
We offer free support and updates for our items.
Use any of this options to subscribe to theme/plugins updates releases notifications:
- Like our page on Facebook
- Plus our page on Google+
- Follow us on Twitter
If you have any questions about this plugin you should:
- Check WordPress Plugins section in our FAQ page
- If you don't find answer submit support question in our support system
- If you need customization service or WP/Theme setup check our customization services page.
Please don't ask support questions in Codecanyon comments, email, skype, facebook or twitter - questions in this places will never be answered.


fun setOnDismissListener(listener: (() -> Unit)?): Unit
Sets a listener that is called when this popup window is dismissed.
listener - Listener that is called when this popup window is dismissed.
listener


ASP MVC Actions
Actions
- HttpGets should be idempotent. "Postback" actions aren't, so add [HttpPost] to Edits
- Use [ActionName("Illegal-Name")] to override names (non C# names, or methods that are the same except for HttpGet/Post).
[ActionName("Person-Detail")]
public ActionResult Details(int id) - To make searches bookmarkable, use the Html.BeginForm overload:
@using (Html.BeginForm("Index", "Categories", FormMethod.Get)) { - Arguments are automatically bound to RouteData.Values["x"], Request.QueryString["y"] and/or Request.Form["z"]
public ActionResult Edit(int id = 0)
{
var isValid = ModelState.IsValid; //false if id="a"
Action Results
- return View(category); //ViewResult
- return RedirectToAction("Index"); //RedirectResult
- return HttpNotFound();
- return Json(category); //Json. Yes, that's all.
- return Content("Hello world"); //plain text
//returning a date or int is automatically a ContentResult - Mark non-http public methods as [NoAction] as otherwise they'd be a ContentResult
- return PartialView(category<EMAIL_ADDRESS>To return simple values (such as an int) add [NoAction] attribute.
Post-Redirect-Get pattern
HttpPost actions usually redirect, with a RedirectToAction (or RedirectToRoute)
return RedirectToAction("Edit", new { id });
return RedirectToRoute(new {controller = "Person", action = "Edit", id});
To pass data across, use TempData["x"] = x.
ModelState.Remove("HasBeenPosted"); //so the model value isn't overridden
model.HasBeenPosted = true;
Partial Actions
An Html.Partial can just call a partial view/user control; Html.Action (and Html.RenderAction) calls a controller which in turn calls a partial view. In other words, Html.Action allows the view to do processing- the view calls a controller to call a view.
<div>@Html.Action("CategorySummary", "Category", Model)</div>
In CategoryController. Mark as [ChildActionOnly] if required. ControllerContext.IsChildAction can detect if within an Action.
[ChildActionOnly]
public ActionResult CategorySummary(CategoryModel category)
{
//(ControllerContext.IsChildAction)
return PartialView(category);
}
If you use dependency injection, you'll get the error A single instance of controller 'Web.Controllers.MyController' cannot be used to handle multiple requests. If a custom controller factory is in use, make sure that it creates a new instance of the controller for each request.. The DI container is supplying the same instance per request (request-scoped).
Change the DI configuration to be scoped per call- eg StructureMap is For<MyController>().AlwaysUnique();
Action Filters
| [OutputCache] | Duration, VaryByParams etc |
| [Authorize] | Any authenticated user - specifics with Users = "", Roles = "" |
| [AllowAnonymous] | MVC 4: whitelist for logon actions when you have a global [Authorize] |
| [ValidateAntiForgeryToken] | In conjunction with Html.AntiForgeryToken() |
| [HandleError] | Error trapping, It goes to the default Shared/Errors.cshtml.
|
HandleErrors in GlobalFilters
public static void RegisterGlobalFilters(GlobalFilterCollection filters)
{
//multiple filters are applied with ascending Order (default = -1)
//database errors
filters.Add(new HandleErrorAttribute
{
ExceptionType = typeof(System.Data.Common.DbException),
View = "DatabaseError", //-> Shared/DatabaseError.cshtml
Order = 1
});
//generic errors (default order is -1)
filters.Add(new HandleErrorAttribute { Order = 2 });
}
protected void Application_Start()
{
AreaRegistration.RegisterAllAreas();
RegisterGlobalFilters(GlobalFilters.Filters);
RegisterRoutes(RouteTable.Routes);
}
Error views have no controller. The model is @model System.Web.Mvc.HandleErrorInfo
Action Input Binding
You can still access Request.Form, or accept a FormCollection, but AspMVC's DefaultModelBinder is quite good at mapping the HttpPosted fields (and Route data) into simple model classes.
You can use simple arguments (which can have defaults), with UpdateModel (or TryUpdateModel) - which can take an interface (as well as inclusions/ exclusions).
[HttpPost]
public ActionResult Edit(int categoryId, string categoryName)
{
var category = new CategoryModel();
UpdateModel(category, new[] { "CategoryName", "CategoryId" });
...Or...
[HttpPost]
public ActionResult Edit(CategoryModel category)
BindAttribute
This applies to the individual parameters - or to your model class.
[HttpPost]
public ActionResult Edit(
[Bind(Include = "CategoryName,CategoryId")]
CategoryModel category)
Custom ModelBinders
- In MVC 1-2, you could add an IModelBinder via ModelBinders.Binders.Add(x)
- IModelBinder.BindModel(ControllerContext controllerContext,
ModelBindingContext bindingContext)
You can access Request.Form or bindingContext.ValueProvider.GetValue - You can inherit from the DefaultModelBinder and override CreateModel to create your models from a repository/IoC
- In MVC3, there is an IModelBinderProvider.GetBinder(type) which can be added to ModelBinderProviders.BinderProviders.Add(x).


Glifada is situated about 5 miles south of Athens and is the site of a proposed large marina development together with a comprehensive shore-side infrastructure. Currently this does not appear to have happened quite as planned.
For full details on clearing into our out of Greece see Greek Formalities.
There are a series of yacht basins here. The largest and most northerly is no. 4 and this is probably the only one where any space might be found. The other 3 are principally private.
In marina no. 4 (Glyphada), berth stern-to where there is space. The moorings are tailed back to the quay. There is good all-round shelter.
It may also be possible to berth at the Olympic Sailing Centre, about 2 miles north of Glifadha. There are basic facilities here.
Last updated August 2009.


One of the most frequently asked questions about the CS-script
is a question about running the script engine on PocketPC.
Unfortunately Compact Framework (CF) is not ready yet for
running dynamically loaded/compiled managed code.
The reason for this is that CF does not have implementation of
the
C# ICodeCompiler. Another words the following code would not compile:
ICodeCompiler compiler = (new CSharpCodeProvider()).CreateCompiler();
If, in any
future version of
CF, Microsoft includes the CSharpCodeProvider implementation the
CS-Script will work on such platform.
Starting from version 1.3 CS-Script supports
pluggable custom compilers.
It means that if you have third-party implementation of the
CLR
compiler that can work on CF it can be used instead of
Microsoft
compiler and CS-Script engine will be able to run C# scripts under CF.
Basically you need any workable C# compiler either managed or native
that would work on CF.
I have tried to resolve the
problem by isolating the compiler from full
version of .NET Framework and bringing it on CF but did not
succeeded. Also I was trying to use third-party compilers (after all it
does not matter what software does the conversion C#->IL).
The
Pocket
C# compiler
looked promising but I could not get it working. Even despite the fact that I have
seen some reports dated 2004 that it actually did work.
However CS-Script provides some very limited support for CF. It
comes in a form of
cfbuild.cs
script, which allows building a CF compatible managed executable from
any appropriate the C# script.
You can compile the "Hello-World" script (
hello.cs) into executable for
WinCE5.0 with the following command:
//cscs cfbuild hello
This is the content of the
hello.cs:
using System;
using System.Windows.Forms;
class Script
{
static public void Main(string[] args)
{
MessageBox.Show("Just a test!");
}
} |
The produced executable can be run on the MS Device emulator or real
PocketPC.
MS Device emulator:
PocketPC:
You can also use
cfbuild.cs
to install/uninstall the shell extensions for building CF based
executables from the scripts:
//cscs cfbuild /i
Note: when you execute
cfbuild.cs
for the first time you will be asked to specify the location of the CF
installed on your PC. You have to do it only once (
cfbuild.cs will
remember CF location for the next sessions.
See Also
Alternative
Compilers


This scenario demonstrates how to use IMbnPinManager/IMbnPin APIs to get current pin state and if pin is locked then how to unlock it.
Enter required PIN to unlock device:


I am now testing the work flow to see how the phonetic fonts are rendered and check unicode compliance.
- /θɪs ɪs eɪ pɐʉst wɪθ ə fɔˈnɛtɪk ˈkɔmpɐʉnənt/
- This is a post with a phonetic componant
Diacritics
- Diacritics are often a problem
- pʰɜt̪o
- Rə̄
- Su̺ 1
All of the diacritics seem to render correctly 2. I will check them along the way.
Below I will embed an audio file from soundcloud.
In the future this will include a relavent phonetic example rather than this example - but in the meantime enjoy! :).


Rails7에서 tailwind-css인스톨 방법
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rails joins 메소드의 특징에 대해 알아보자
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일본의 풋살매칭 시스템
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[사투리]저가베,주그메라는 말의 정체
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ruby 우주선 연산자(<=>)란?
Posted by negabaro kim on December 25, 2022
rails constantize메소드란
Posted by negabaro kim on December 25, 2022
2022년 지름신강림 회고
Posted by negabaro on December 18, 2022
rails model에서의 scope이란
Posted by negabaro kim on May 27, 2021
rails default scope은 웬만하면 쓰지말자
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flutter state_notifier란?
Posted by negabaro kim on May 23, 2021
Dart collection패키지란?
Posted by negabaro kim on May 7, 2021
Firebase Custom Token이란?
Posted by negabaro kim on May 3, 2021
firebase_id_token gem에 대해 알아보자.
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Firebase Web API Key란?
Posted by negabaro kim on May 2, 2021


Phi Phi Islands
The Phi Phi Islands are an island group in Thailand, between the large island of Phuket and the west Strait of Malacca coast of the mainland. The islands are administratively part of Krabi province. Ko Phi Phi Don ("ko" (Thai: เกาะ) meaning "island" in the Thai language) is the largest island of the group, and is the most populated island of the group, although the beaches of the second largest island, Ko Phi Phi Lee (or "Ko Phi Phi Leh"), are visited by many people as well. The rest of the islands in the group, including Bida Nok, Bida Noi, and Bamboo Island (Ko Mai Phai), are not much more than large limestone rocks jutting out of the sea. The Islands are reachable by speedboats or Long-tail boats most often from Krabi Town or from various piers in Phuket Province.
Phi Phi Don was initially populated by Muslim fishermen during the late-1940s, and later became a coconut plantation. The Thai population of Phi Phi Don remains more than 80% Muslim. The actual population however, if counting laborers, especially from the north-east, is much more Buddhist these days. The population is between 2,000 and 3,000 people (2013).
The islands came to worldwide prominence when Ko Phi Phi Leh was used as a location for the 2000 British-American film The Beach. This attracted criticism, with claims that the film company had damaged the island's environment, since the producers bulldozed beach areas and planted palm trees to make it resemble description in the book, an accusation the film's makers contest. An increase in tourism was attributed to the film's release, which resulted in increases in waste on the Islands, and more developments in and around the Phi Phi Don Village. Phi Phi Lee also houses the "Viking Cave", where there is a thriving industry harvesting edible bird's nest.
Ko Phi Phi was devastated by the Indian Ocean tsunami of December 2004, when nearly all of the island's infrastructure was destroyed. As of 2010 most, but not all, of this has been restored.
In Wikipedia. Retrieved January 24, 2018, from https://en.wikipedia.org/wiki/Bora_Bora


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--- layout: post status: publish published: true title: WWF Persistence Service author: display_name: Tomas Restrepo login: tomasr email<EMAIL_ADDRESS>url: http://winterdom.com/ author_login: tomasr author_email<EMAIL_ADDRESS>author_url: http://winterdom.com/ wordpress_id: 239 wordpress_url: http://winterdom.com/2005/10/wwfpersistenceservice date: '2005-10-05 16:17:13 +0000' date_gmt: '2005-10-05 16:17:13 +0000' categories: - WinFX - Workflow tags: [] comments: [] ---
Jesus Rodriguez has a cool article on the WWF Persistence Service. It's pretty interesting to read about these basic services provided by the WWF runtime.
Reading this, two questions come to mind which don't seem to be directly addressed in the article:
All of these questions seem, to me, quite interesting because they help highlight just exactly what runtime guarantees the WWF runtime can actually make regarding the state of the workflow instances and it's reliability and recoverability, and just how much a work will developers working with just WWF have to do to help the core runtime provide a robust environment for running certain kinds of business flows (particularly if they are long running, which almost all real workflows are, in my short experience).


--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/ctrl-space.20in.20VS.20Code.html ---
Just learnt this:
import data.list.basic #check list.length_zero -- ctrl-space suggests "list.length_eq_zero" open list #check list.length_zero -- ctrl-space suggests nothing
I have seen ctrl-space not giving me as many results as I was hoping for, but I'd not realised that this was a possible issue.
I find this really annoying.
Often I open nat
, but I still want to make sure I get a nat
lemma, and not the corresponding group version, but that is difficult with this behaviour.
Would you mind opening an issue at leanprover-community/lean? This is something that would have to be changed in C++.
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{% extends 'admin/base.html' %} {% block title %}Transportation{% endblock %} {% block nav_transport %}active{% endblock nav_transport %} {% block content %}
No Transportation Added
This transportation will be removed from database.


All Form elements based on Bootstrap 3. Check out form elements page for more demos
You can use any icon gliph from fontawesome or custom iconmoon icon font.
You also can use icon effects with any input size (normal, large, small)
You can combine date and time pick inputs with any input icon elements and input size (normal, large, small)


See: Description
| Interface | Description |
|---|---|
| ExpandedVariable |
Identifies a variable to be expanded into the
sql string rather than representing a placeholder.
|
| GroovyResultSet |
Represents an extent of objects
|
| InOutParameter | |
| InParameter |
A typed parameter to pass to a query
|
| OutParameter |
A parameter to be returned from a CallableStatement.
|
| ResultSetOutParameter |
A ResultSet out parameter.
|
| Class | Description |
|---|---|
| BatchingPreparedStatementWrapper |
Class which delegates to a PreparedStatement but keeps track of
a batch count size.
|
| BatchingStatementWrapper |
Class which delegates to a Statement but keeps track of a batch count size.
|
| DataSet |
An enhancement of Groovy's Sql class providing support for accessing
and querying databases using POGO fields and operators rather than
JDBC-level API calls and RDBMS column names.
|
| GroovyResultSetExtension |
GroovyResultSetExtension implements additional logic for ResultSet.
|
| GroovyResultSetProxy |
GroovyResultSetProxy is used to create a proxy for GroovyResultSet.
|
| GroovyRowResult |
Represents an extent of objects.
|
| ResultSetMetaDataWrapper |
This class defines a wrapper for accessing a specific column in
ResultSetMetaData . |
| Sql |
A facade over Java's normal JDBC APIs providing greatly simplified
resource management and result set handling.
|
| SqlOrderByVisitor | |
| SqlWhereVisitor | |
| SqlWithParams |
Groovy helper classes for working with SQL data as Groovy objects


Wish
Problem settings:
Warning: The participant {{mail}} just modified his/her wish. Please reload the page.
Assignation:
help page


array_for_each(fn, a1, @rest...)
The function fn
is applied to each element of the arrays a1, ...
. Fn
must accept
as many arguments as there are arrays. The arrays must be of the same length.
Return void.
array_for_each(^(x, y) showln(x * y), #[1, 2, 3], #[4, 5, 6])
//-> 4
10
18


PROJECTS
AnimeDict
AnimeDict - August 2018 to Current
React-Native mobile application to find information about Anime and Manga
Performs API requests to the Jikan REST-ful API (https://jikan.docs.apiary.io)
Shows information based on name, genre or type(Anime or Manga)
Invoice-Me
Invoice-Me - June 2018 to August 2018
Ruby on rails web application to create and manage invoices
Performs authentication through user registration and login
Uses bootstrap web framework for design
SKILLS
HTML/CSS
JavaScript
Bootstrap
React
Python
Ruby
Ruby on Rails
C#
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MySQL
PostgreSQL
Spanish
Windows
Linux
Bash
PowerShell
Node.js
XML
Postman
Wireshark


An ode to Olivia
By Salma
Olivia is fun to play with.


Bridge collapses in southwest France; 1 dead, 1 missing
by Associated PressPARIS (AP) — Authorities say a bridge has collapsed in rural southwest France, killing a 15-year-old girl and leaving at least one person missing.
Toulouse prosecutor Dominique Alzeari said the girl’s mother was rescued by witnesses after several vehicles, including hers, fell into the Tarn River on Monday morning near the village of Mirepoix-sur-Tarn.
He said rescuers were still searching for a truck driver whose vehicle also fell in the river. He said five people were injured in the collapse, including two firefighters at the scene.
Prime Minister Edouard Philippe, on a visit to Senegal, deplored the “tragic accident.” The bridge had been renovated in 2003 and its last safety check was in 2017.
An investigation into the cause of the collapse has been opened.
Associated Press


Drag Drop Example 8. Provide fruit model by calling provideModel (read from DOM)
Custom logic may be used to store and retrieve models using DragOptions.provideModel handler.
In this example, model for draggable element is not bound and element's ID attribute is used to retrieve draggable element's
model.


[1]
we had booked 2 main reasons we chose this hotel.
[2]
the bathtub was that 1 we had booked 2 main reasons we chose this hotel.