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generation
- Variable in class com.aerospike.client.policy.
WritePolicy
Expected generation.
generation
- Variable in class com.aerospike.client.
Record
Record modification count.
generation
- Variable in class net.citrusleaf.
CitrusleafClient.ClResult
How many times the record has been modified (including creation) on the server.
GENERATION_ERROR
- Static variable in class com.aerospike.client.
ResultCode
On modifying a record with unexpected generation.
get(Policy, Key)
- Method in class com.aerospike.client.
AerospikeClient
Read entire record for specified key.
get(Policy, Key, String...)
- Method in class com.aerospike.client.
AerospikeClient
Read record header and bins for specified key.
get(Policy, Key[])
- Method in class com.aerospike.client.
AerospikeClient
Read multiple records for specified keys in one batch call.
get(Policy, Key[], String...)
- Method in class com.aerospike.client.
AerospikeClient
Read multiple record headers and bins for specified keys in one batch call.
get(String)
- Static method in class com.aerospike.client.
Operation
Create read bin database operation.
get()
- Static method in class com.aerospike.client.
Operation
Create read all record bins database operation.
get(String)
- Static method in class com.aerospike.client.
Value
Get string or null value instance.
get(byte[])
- Static method in class com.aerospike.client.
Value
Get byte array or null value instance.
get(int)
- Static method in class com.aerospike.client.
Value
Get integer value instance.
get(long)
- Static method in class com.aerospike.client.
Value
Get long value instance.
get(Object)
- Static method in class com.aerospike.client.
Value
Determine value given generic object.
get(Object)
- Method in class net.citrusleaf.
CitrusleafClient
For server nodes configured as "single-bin" only - get record value for specified key, using default namespace, no set name, and default options.
get(String, String, Object, String, CitrusleafClient.ClOptions)
- Method in class net.citrusleaf.
CitrusleafClient
Get bin value for specified key and bin name.
get(String, String, Object, String[], CitrusleafClient.ClOptions)
- Method in class net.citrusleaf.
CitrusleafClient
Get bin name/value pairs for specified key and list of bin names.
get(String, String, Object, Collection<String>, CitrusleafClient.ClOptions)
- Method in class net.citrusleaf.
CitrusleafClient
Get bin name/value pairs for specified key and list of bin names.
get(String, int)
- Static method in class net.citrusleaf.
CitrusleafInfo
Get all the default info from the specified database server node, using host name and port.
get(String, int, String)
- Static method in class net.citrusleaf.
CitrusleafInfo
Get one info value by name from the specified database server node, using host name and port.
get(String, int, String[])
- Static method in class net.citrusleaf.
CitrusleafInfo
Get many info values by name from the specified database server node, using host name and port.
get(InetSocketAddress)
- Static method in class net.citrusleaf.
CitrusleafInfo
Get all the default info from the specified database server node.
get(InetSocketAddress, String)
- Static method in class net.citrusleaf.
CitrusleafInfo
Get one info value by name from the specified database server node.
get(InetSocketAddress, String[])
- Static method in class net.citrusleaf.
CitrusleafInfo
Get many info values by name from the specified database server node.
getAliases()
- Method in class com.aerospike.client.cluster.
Node
Return server node IP address aliases.
getAll(String, String, Object, CitrusleafClient.ClOptions)
- Method in class net.citrusleaf.
CitrusleafClient
Get all bin name/value pairs for specified key.
getAllDigest(String, byte[], CitrusleafClient.ClOptions)
- Method in class net.citrusleaf.
CitrusleafClient
Get all bin name/value pairs for specified key digest.
getAsBlob(Object)
- Static method in class com.aerospike.client.
Value
Get blob or null value instance.
getAsList(List<?>)
- Static method in class com.aerospike.client.
Value
Get list or null value instance.
getAsMap(Map<?, ?>)
- Static method in class com.aerospike.client.
Value
Get map or null value instance.
getAsNull()
- Static method in class com.aerospike.client.
Value
Get null value instance.
getBuffer()
- Method in class com.aerospike.client.
Info
Get response buffer.
getConnection(int)
- Method in class com.aerospike.client.cluster.
Node
Get a socket connection from connection pool to the server node.
getDigest(String, byte[], String, CitrusleafClient.ClOptions)
- Method in class net.citrusleaf.
CitrusleafClient
Get bin value for specified key digest and bin name.
getDigest(String, byte[], Collection<String>, CitrusleafClient.ClOptions)
- Method in class net.citrusleaf.
CitrusleafClient
Get bin name/value pairs for specified key digest and list of bin names.
getHeader(Policy, Key)
- Method in class com.aerospike.client.
AerospikeClient
Read record generation and expiration only for specified key.
getHeader(Policy, Key[])
- Method in class com.aerospike.client.
AerospikeClient
Read multiple record header data for specified keys in one batch call.
getHeader()
- Static method in class com.aerospike.client.
Operation
Create read record header database operation.
getHost()
- Method in class com.aerospike.client.cluster.
Node
Return server node IP address and port.
getKey()
- Method in class com.aerospike.client.query.
RecordSet
Get record's unique identifier.
getLength()
- Method in class com.aerospike.client.
Info
Get response length.
getMessage()
- Method in exception com.aerospike.client.
AerospikeException
getName()
- Method in class com.aerospike.client.cluster.
Node
Return server node name.
getName()
- Method in class com.aerospike.client.
Info.NameValueParser
Get name.
getNameValueParser()
- Method in class com.aerospike.client.
Info
Parse response in name/value pair format:
getNodeNameList()
- Method in class net.citrusleaf.
CitrusleafClient
Return a list of server nodes in the cluster.
getNodeNames()
- Method in class com.aerospike.client.
AerospikeClient
Return list of active server node names in the cluster.
getNodes()
- Method in class com.aerospike.client.
AerospikeClient
Return array of active server nodes in the cluster.
getObject()
- Method in class com.aerospike.client.
Value.BlobValue
getObject()
- Method in class com.aerospike.client.
Value.BytesValue
getObject()
- Method in class com.aerospike.client.
Value
Return original value as an Object.
getObject()
- Method in class com.aerospike.client.
Value.IntegerValue
getObject()
- Method in class com.aerospike.client.
Value.ListValue
getObject()
- Method in class com.aerospike.client.
Value.LongValue
getObject()
- Method in class com.aerospike.client.
Value.MapValue
getObject()
- Method in class com.aerospike.client.
Value.NullValue
getObject()
- Method in class com.aerospike.client.
Value.StringValue
getPriority()
- Method in class net.citrusleaf.
CitrusleafClient.ClScanningOptions
Get server scan priority setting.
getRecord()
- Method in class com.aerospike.client.query.
RecordSet
Get record's header and bin data.
getResultCode()
- Method in exception com.aerospike.client.
AerospikeException
Get integer result code.
getResultString(int)
- Static method in class com.aerospike.client.
ResultCode
Return result code as a string.
getThreadsPerNode()
- Method in class net.citrusleaf.
CitrusleafClient.ClScanningOptions
Get number of client scan threads per node.
getType()
- Method in class com.aerospike.client.
Value.BlobValue
getType()
- Method in class com.aerospike.client.
Value.BytesValue
getType()
- Method in class com.aerospike.client.
Value
Get wire protocol value type.
getType()
- Method in class com.aerospike.client.
Value.IntegerValue
getType()
- Method in class com.aerospike.client.
Value.ListValue
getType()
- Method in class com.aerospike.client.
Value.LongValue
getType()
- Method in class com.aerospike.client.
Value.MapValue
getType()
- Method in class com.aerospike.client.
Value.NullValue
getType()
- Method in class com.aerospike.client.
Value.StringValue
getValue()
- Method in class com.aerospike.client.
Info.NameValueParser
Get value.
getValue(String)
- Method in class com.aerospike.client.
Record
Get bin value given bin name.
getWithTouch(String, String, Object, Collection<String>, int, CitrusleafClient.ClOptions)
- Method in class net.citrusleaf.
CitrusleafClient
Get bin name/value pairs for specified key and list of bin names, and if the record exists, reset record time to expiration.
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Speech
School Reform Minister Nick Gibb speaks to Reform about the changes that have led to more freedom in the education system.
The government’s education reforms over the past 4-and-a-half years have been the most far-reaching for a generation. Our reforms to the curriculum, making it more knowledge-based and academically rigorous - and our focus on raising standards of pupil behaviour in the classroom, enabling teachers to spend more time teaching - are both key elements of this reform.
But today I want to talk about our structural reforms that have delivered professional autonomy. At the centre of these is academisation, making schools free from local authority control. Accompanying this were numerous smaller reforms, designed to pass powers back to teachers and heads - the aim, to let a thousand flowers bloom.
We are now in the enviable position of being able to see which of these flowers have bloomed the brightest. I first became Shadow Schools Minister in 2005, and after 9 years of witnessing some of the most gifted educators in England, I am repeatedly struck by a new vibrancy and excitement in the English education system.
Schools are, with no shadow of a doubt, improving.
As of this summer, the proportion of schools judged ‘good’ or ‘outstanding’ by Ofsted at their most recent inspection reached 80%, compared with 70% in 2012.
Our reforms to GCSEs are helping reverse the decline in the number of pupils taking rigorous academic qualifications. The number of pupils taking challenging EBacc subjects has risen dramatically under this government. In 2010, only 22% of pupils in state-funded schools entered all EBacc subjects. In the most recent academic year, this rose to almost 39%. Over the same period, entries to history or geography have risen from 48% to 65%, and entries to languages from 40% to 50%.
My mother was a primary school teacher, so early years education has always been a key concern for me. I am delighted that the number of 6-year-olds able to decode simple words and pass the phonics screening check at the end of year 1 has increased from 58% in 2012 to 74% in 2014. That’s 102,000 more 6-year-olds on track to be reading more effectively as a direct result of this policy.
The number of persistent truants has fallen from 433,130 in 2009 to 2010, to 300,895 during the last academic year.
Autonomy is not about government directives, committees of experts, quango worthies or national strategies costing hundreds of millions of pounds. It is about associations of like-minded people, bound by a common purpose - academy trusts, teaching school alliances, independent training organisations, charities, social enterprises and online communities. Call it civil society - call it the third sector. It is with these little platoons of idealistic people that the future of our school system lies.
This was why this government launched the free schools programme in 2010. We wanted to provide outlets for idealism - opportunities for dedicated groups of individuals who believed they could improve school provision.
Such groups of individuals have exceeded our expectations. The best academy chains, such as Ark Schools and the Harris Federation, have expanded and replicated their proven success. Ark Schools have opened 3 free schools, with 8 more in development. Likewise, the Harris Federation has opened 8 free schools, with 5 more in development.
And we have seen, much older institutions play a new role in educating our young people. The London Academy of Excellence sixth-form college was established 2-and-a-half years ago by a collection of independent schools including Brighton College, Eton College and Highgate School.
Situated in Newham, the LAE ’s ambition was to channel the brightest pupils from London’s most deprived borough into top universities. 2 years later, its A level results beat those of several well-known public schools. 68 pupils from its first cohort gained places at Russell Group Universities, including 5 at Oxford and Cambridge. This year, more London Academy of Excellence pupils were offered places at Oxbridge than has ever been achieved by the entire borough of Newham in any previous year.
Since 2010, this government has also pioneered university technical colleges, a new type of school geared towards providing technical education for 14- to 18-year-olds. Known as UTCs , they bridge the gap that too often exists between educational provision and the local job market by linking with a nearby university or employer. We now have the Silverstone UTC , Liverpool Life Sciences UTC and UTC Sheffield.
Leading this innovation in vocational education has been Kenneth Baker, a truly inspiring public servant. Now in his ninth decade, Kenneth works tirelessly as chairman of the Baker Dearing Trust and has helped establish 30 UTCs already, with 26 already approved to open.
In the same period, our academies programme has ensured that over 1,200 of the worst-performing schools have been taken over by successful sponsors or headteachers - the majority of which are already leading other schools with a proven track record of academic achievement. We have given the very best heads control over many more schools, with the freedom they need to ensure that the children in their care receive the education they deserve and need.
And they have succeeded. Underperforming schools taken into the academies programme and placed under the leadership of great heads are improving more rapidly than those schools which remain in the hands of local authorities.
This element of the academies programme is a deliberate continuation of an approach begun under the previous government, which we have championed and expanded.
But the government firmly believes that the autonomy previously available to sponsored academies should be available to all schools.
I am delighted that since 2010 more than 3,000 schools - including many of our highest-performing schools - have chosen to become academies. These schools have seized the opportunity to raise standards by using the freedoms we have given them. They can now vary their curriculum, extend the length of their school day and employ the best teachers - regardless of whether they have received formal qualified teacher status.
In each of these cases, parts of civil society - be they teachers, school leaders, employers, philanthropists, universities or parent groups - are empowered to decide how future generations should be educated.
There are now 646 sponsors, 550 chains of 2 schools or more, and 40 chains of at least 10 schools - of these, 9 are responsible for 30 schools or more. All of these rightly compete to raise academic standards for their pupils. And within and between chains, this spirit of competition is accompanied by a culture of collaboration - professionals working together to improve children’s education.
Surveying today’s educational landscape, I derive enormous optimism from other organisations that are being established to support schools. Since Teach First was founded in 2003, 38 social enterprises have been set up by former participants in the programme - all examples of what can be achieved when real autonomy is delivered.
Take one of these - the National Orchestra for All. Founded by Marianna Hay in 2011, the NOFA takes 150 musicians each year from schools in London and the west Midlands and forms a full orchestra, rehearsing throughout the year and giving pupils from these schools the opportunity to play in such venues as the Royal Albert Hall, the Southbank Centre and the Royal Academy of Music.
Similarly, the Brilliant Club was formed in 2011 to bring fruits normally preserved for the more privileged within the reach of the less advantaged. It places postgraduate students in challenging schools to run university-style tutorials for groups of promising pupils. So far, the Brilliant Club has worked with 150 schools around Britain, connecting over 250 doctoral and postdoctoral researchers with 5,000 pupils.
In September this year I had the privilege of attending a ResearchEd conference. These events have brought fresh thinking and new energy to debates about teaching practices in English schools. ResearchEd was founded in 2013 by teachers - not by the government or university education faculties. These teachers, led by Tom Bennett, are determined that what happens in their classrooms should be informed by evidence, not fad.
And Teach First alumni such as Robert Peal, Kris Boulton, Katie Ashford and Joe Kirby are challenging current education orthodoxies. Their passionate iconoclasm, which refuses to accept mistaken and damaging conventional wisdom, is inspirational.
Similarly, the Institute of Ideas - run by Claire Fox - has long been arguing that children deserve a curriculum which is more knowledge-based and rigorous. Its debating competition - Debating Matters - has reinvigorated formal debating in state schools. It was founded in 2002 by a physics teacher from south London called David Perks, today the principal of a free school in east London. Likewise, the debating competition Debate Mate brings 350 undergraduates from top universities to train young debaters in 220 challenging, inner-city schools around England. We are seeing the beginnings of an academic renaissance in our education system.
Autonomy is at the heart of that renaissance. The great liberal politician Lord Beveridge is often invoked as the father of the British welfare state. Less often cited than the 1942 Beveridge report is a report he wrote in 1948 entitled ‘Voluntary Action’. In it, Beveridge specifically warned against monopolistic state provision, in which new ideas and new institutions are quashed instead of nurtured.
Beveridge contrasted a totalitarian state, or a state monopoly, with a free society. He wrote that in a free society, ‘discontented individuals with new ideas can make a new institution to meet their needs. The field is open to experiment and success or failure; secession is the midwife of invention.’
In that passage, Beveridge offered the best-possible articulation of what this government’s school reform agenda has aimed to achieve.
Beveridge was a liberal in the truest sense of the word. He believed that whilst services such as education can be paid for by the state, they should be provided by civil society. Our reforms have unleashed a previously untapped educational idealism within English civil society engaging thousands of groups and individuals, from millionaire carpet salesmen to Premiership football clubs, from high-tech companies to medieval guilds.
As Minister for School Reform, I delight in seeing the fruits of this autonomy in all their vivid abundance. It reaffirms my belief that good government does not improve public services. It enables public services to improve themselves.
Published: 13 November 2014


Normalizing Flow Estimator¶
The Normalizing Flow Estimator (NFE) combines a conventional neural network (in our implementation specified as \(estimator\)) with a multi-stage Normalizing Flow [REZENDE2015] for modeling conditional probability distributions \(p(y|x)\). Given a network and a flow, the distribution \(y\) can be specified by having the network output the parameters of the flow given an input \(x\) [TRIPPE2018]. If the normalizing flow is expressive enough, arbitrary conditional distributions can be approximated.
The flows work by transforming a base distribution (in our case a normal distribution) into successively more complex distributions by applying bijectors.
Example of a normal distribution being transformed by two planar flows:
Using the change of variable formula, the resulting probability distribution \(p_1\) for a single flow \(f\) applied to the base distribution \(p_0\) becomes:
Using normalizing flows for density estimation requires that the inverse and the Jacobian determinant of the flow can be calculated quickly.
Given input \(x\), the neural network outputs the parameters \(\theta\) of the flows. The weights and biases \(w\) of the neural network are learned by minimizing the negative logarithm of the likelihood (maximum likelihood) over \(N\) data points for a normalizing flow consisting of \(K\) flows.
Available flows:
-
class
cde.density_estimator.
NormalizingFlowEstimator
(name, ndim_x, ndim_y, flows_type=('affine', 'radial', 'radial', 'radial'), hidden_sizes=(16, 16), hidden_nonlinearity=<function tanh>, n_training_epochs=1000, x_noise_std=None, y_noise_std=None, weight_decay=0.0, weight_normalization=True, data_normalization=True, dropout=0.0, random_seed=None)[source]¶ Normalizing Flow Estimator
- Parameters
name – (str) name space of the network (should be unique in code, otherwise tensorflow namespace collisions may arise)
ndim_x – (int) dimensionality of x variable
ndim_y – (int) dimensionality of y variable
flows_type – (tuple of strings) The chain of individual flows that together make up the full flow. The individual flows can be any of: affine, planar, radial, identity. They will be applied in order going from the base distribution to the transformed distribution.
hidden_sizes – (tuple of int) sizes of the hidden layers of the neural network
hidden_nonlinearity – (tf function) nonlinearity of the hidden layers
n_training_epochs – (int) Number of epochs for training
x_noise_std – (optional) standard deviation of Gaussian noise over the the training data X -> regularization through noise
y_noise_std – (optional) standard deviation of Gaussian noise over the the training data Y -> regularization through noise
weight_decay – (float) the amount of decoupled (http://arxiv.org/abs/1711.05101) weight decay to apply
weight_normalization – (boolean) whether weight normalization shall be used for the neural network
data_normalization – (boolean) whether to normalize the data (X and Y) to exhibit zero-mean and uniform-std
dropout – (float) the probability of switching off nodes during training
random_seed – (optional) seed (int) of the random number generators used
-
cdf
(X, Y)¶ Predicts the conditional cumulative probability p(Y<=y|X=x). Requires the model to be fitted.
- Parameters
X – numpy array to be conditioned on - shape: (n_samples, n_dim_x)
Y – numpy array of y targets - shape: (n_samples, n_dim_y)
- Returns
conditional cumulative probability p(Y<=y|X=x) - numpy array of shape (n_query_samples, )
-
conditional_value_at_risk
(x_cond, alpha=0.01, n_samples=1000000)¶ Computes the Conditional Value-at-Risk (CVaR) / Expected Shortfall of the fitted distribution. Only if ndim_y = 1
- Parameters
x_cond – different x values to condition on - numpy array of shape (n_values, ndim_x)
alpha – quantile percentage of the distribution
- Returns
CVaR values for each x to condition on - numpy array of shape (n_values)
-
covariance
(x_cond, n_samples=1000000)¶ Covariance of the fitted distribution conditioned on x_cond
- Parameters
x_cond – different x values to condition on - numpy array of shape (n_values, ndim_x)
- Returns
Covariances Cov[y|x] corresponding to x_cond - numpy array of shape (n_values, ndim_y, ndim_y)
-
eval_by_cv
(X, Y, n_splits=5, verbose=True)¶ Fits the conditional density model with cross-validation by using the score function of the BaseDensityEstimator for scoring the various splits.
- Parameters
X – numpy array to be conditioned on - shape: (n_samples, n_dim_x)
Y – numpy array of y targets - shape: (n_samples, n_dim_y)
n_splits – number of cross-validation folds (positive integer)
verbose – the verbosity level
-
fit
(X, Y, random_seed=None, verbose=True, eval_set=None, **kwargs)[source]¶ Fit the model with to the provided data
- Parameters
X – numpy array to be conditioned on - shape: (n_samples, n_dim_x)
Y – numpy array of y targets - shape: (n_samples, n_dim_y)
eval_set – (tuple) eval/test dataset - tuple (X_test, Y_test)
verbose – (boolean) controls the verbosity of console output
-
fit_by_cv
(X, Y, n_folds=3, param_grid=None, random_state=None, verbose=True, n_jobs=-1)¶ Fits the conditional density model with hyperparameter search and cross-validation.
Determines the best hyperparameter configuration from a pre-defined set using cross-validation. Thereby, the conditional log-likelihood is used for simulation_eval.
Fits the model with the previously selected hyperparameter configuration
- Parameters
X – numpy array to be conditioned on - shape: (n_samples, n_dim_x)
Y – numpy array of y targets - shape: (n_samples, n_dim_y)
n_folds – number of cross-validation folds (positive integer)
param_grid –
(optional) a dictionary with the hyperparameters of the model as key and and a list of respective parametrizations as value. The hyperparameter search is performed over the cartesian product of the provided lists. Example:
{"n_centers": [20, 50, 100, 200], "center_sampling_method": ["agglomerative", "k_means", "random"], "keep_edges": [True, False] }
random_state – (int) seed used by the random number generator for shuffeling the data
-
get_configuration
(deep=True)¶ Get parameter configuration for this estimator.
- Parameters
deep – boolean, optional If True, will return the parameters for this estimator and contained subobjects that are estimators.
- Returns
params - mapping of string to any Parameter names mapped to their values.
-
get_params
(deep=True)¶ Get parameters for this estimator.
- Parameters
deep (boolean, optional) – If True, will return the parameters for this estimator and contained subobjects that are estimators.
- Returns
params – Parameter names mapped to their values.
- Return type
mapping of string to any
-
get_params_internal
(**tags)¶ Internal method to be implemented which does not perform caching
-
kurtosis
(x_cond, n_samples=1000000)¶ Kurtosis of the fitted distribution conditioned on x_cond
- Parameters
x_cond – different x values to condition on - numpy array of shape (n_values, ndim_x)
- Returns
Kurtosis Kurt[y|x] corresponding to x_cond - numpy array of shape (n_values, ndim_y, ndim_y)
-
log_pdf
(X, Y)¶ Predicts the conditional log-probability log p(y|x). Requires the model to be fitted.
- Parameters
X – numpy array to be conditioned on - shape: (n_samples, n_dim_x)
Y – numpy array of y targets - shape: (n_samples, n_dim_y)
- Returns
onditional log-probability log p(y|x) - numpy array of shape (n_query_samples, )
-
mean_
(x_cond, n_samples=1000000)¶ Mean of the fitted distribution conditioned on x_cond :param x_cond: different x values to condition on - numpy array of shape (n_values, ndim_x)
- Returns
Means E[y|x] corresponding to x_cond - numpy array of shape (n_values, ndim_y)
-
mean_std
(x_cond, n_samples=1000000)¶ - Computes Mean and Covariance of the fitted distribution conditioned on x_cond.
Computationally more efficient than calling mean and covariance computatio separately
- Parameters
x_cond – different x values to condition on - numpy array of shape (n_values, ndim_x)
- Returns
Means E[y|x] and Covariances Cov[y|x]
-
pdf
(X, Y)¶ Predicts the conditional probability p(y|x). Requires the model to be fitted.
- Parameters
X – numpy array to be conditioned on - shape: (n_samples, n_dim_x)
Y – numpy array of y targets - shape: (n_samples, n_dim_y)
- Returns
conditional probability p(y|x) - numpy array of shape (n_query_samples, )
-
plot2d
(x_cond=[0, 1, 2], ylim=(-8, 8), resolution=100, mode='pdf', show=True, prefix='', numpyfig=False)¶ Generates a 3d surface plot of the fitted conditional distribution if x and y are 1-dimensional each
- Parameters
xlim – 2-tuple specifying the x axis limits
ylim – 2-tuple specifying the y axis limits
resolution – integer specifying the resolution of plot
-
plot3d
(xlim=(-5, 5), ylim=(-8, 8), resolution=100, show=False, numpyfig=False)¶ Generates a 3d surface plot of the fitted conditional distribution if x and y are 1-dimensional each
- Parameters
xlim – 2-tuple specifying the x axis limits
ylim – 2-tuple specifying the y axis limits
resolution – integer specifying the resolution of plot
-
predict_density
(X, Y=None, resolution=50)¶ Computes conditional density p(y|x) over a predefined grid of y target values
- Parameters
X – values/vectors to be conditioned on - shape: (n_instances, n_dim_x)
Y – (optional) y values to be evaluated from p(y|x) - if not set, Y will be a grid with with specified resolution
resulution – integer specifying the resolution of simulation_eval grid
- Returns: tuple (P, Y)
P - density p(y|x) - shape (n_instances, resolution**n_dim_y)
Y - grid with with specified resolution - shape (resolution**n_dim_y, n_dim_y) or a copy of Y in case it was provided as argument
-
score
(X, Y)¶ Computes the mean conditional log-likelihood of the provided data (X, Y)
- Parameters
X – numpy array to be conditioned on - shape: (n_query_samples, n_dim_x)
Y – numpy array of y targets - shape: (n_query_samples, n_dim_y)
- Returns
average log likelihood of data
-
set_params
(**params)¶ Set the parameters of this estimator.
The method works on simple estimators as well as on nested objects (such as pipelines). The latter have parameters of the form
<component>__<parameter>
so that it’s possible to update each component of a nested object.- Returns
- Return type
self
-
skewness
(x_cond, n_samples=1000000)¶ Skewness of the fitted distribution conditioned on x_cond
- Parameters
x_cond – different x values to condition on - numpy array of shape (n_values, ndim_x)
- Returns
Skewness Skew[y|x] corresponding to x_cond - numpy array of shape (n_values, ndim_y, ndim_y)
-
std_
(x_cond, n_samples=1000000)¶ Standard deviation of the fitted distribution conditioned on x_cond
- Parameters
x_cond – different x values to condition on - numpy array of shape (n_values, ndim_x)
- Returns
Standard deviations sqrt(Var[y|x]) corresponding to x_cond - numpy array of shape (n_values, ndim_y)
-
tail_risk_measures
(x_cond, alpha=0.01, n_samples=1000000)¶ Computes the Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR)
- Parameters
x_cond – different x values to condition on - numpy array of shape (n_values, ndim_x)
alpha – quantile percentage of the distribution
n_samples – number of samples for monte carlo model_fitting
- Returns
VaR values for each x to condition on - numpy array of shape (n_values)
CVaR values for each x to condition on - numpy array of shape (n_values)
-
value_at_risk
(x_cond, alpha=0.01, n_samples=1000000)¶ Computes the Value-at-Risk (VaR) of the fitted distribution. Only if ndim_y = 1
- Parameters
x_cond – different x values to condition on - numpy array of shape (n_values, ndim_x)
alpha – quantile percentage of the distribution
- Returns
VaR values for each x to condition on - numpy array of shape (n_values)
- REZENDE2015
Rezende, Mohamed (2015). Variational Inference with Normalizing Flows (http://arxiv.org/abs/1505.05770)
- TRIPPE2018
Trippe, Turner (2018). Conditional Density Estimation with Bayesian Normalising Flows (http://arxiv.org/abs/1802.04908)


At a distance of 24 km from Dandeli, 93 km from Sirsi, 120 km from Karwar and 139 km from Gokarna, Kavala caves are the natural caves located in the heart of Dandeli Wildlife Sanctuary and is one of the popular points of interest in Dandeli.
These caves are formed by volcanic activity ages back and are situated deep with-in the forest. It is believed that these caves have been in existence since the prehistoric times. Currently, the caves are inhabited by numerous snakes and bats. Also known as Limestone Caves or Sidda, these caves are very small in dimension and have a lot of stalagmite formations.
At some places the opening gets smaller and visitors need to crawl through. Visitors need to climb down 375 steps to reach the cave entrance. There is a temple at the entrance of the cave. One has to crawl down 40 feet through winding, narrow tunnels to see the Shivalinga formed naturally. It is 124.3 kilometers from banavasi.
Visiting Timings:-9AM TO 5PM
At a distance of 39 km from Kemmangundi, 47 km from Shimoga, 79 km from Chikmagalur & 9 km from Tarikere, Amruthapura is a village located in Chikmagalur district of the Karnataka which is well known for the famous Amruteshwara Temple.The Amruteshwara Temple is an ancient temple built in 1196 AD by Amruteshwara Dandanayaka, a general of the Hoysala ruler Veera Ballala II.
Ruvari Mallitamma, the well-known Hoysala sculptor and architect is known to have started his career here working on the domed ceilings in the main mantapa. On the porch of the temple is a large stone inscription, a fine example of medieval Kannada poetry.
This temple is situated near the Bhadra Reservoir in Malnad region surrounded by coconut and palm plantations. Dedicated to Lord Shiva, this temple was built using soft clay stone. This medium sized temple showcases excellent craftsmanship of Hoysala architecture. This temple is in the ekakuta style. It is 158.1 kilometers from banavasi.
Visiting Timings:-4:30 AM -10. 30 AM and 4. 00 PM to 6. 00 PM
At a distance of 11 km from Kumta, 22 km from Gokarna, 31 km from Honavar, 59 km from Karwar and 56 km from Murudeshwar, Mirjan Fort is a beautiful fort located in the village of Mirjan on the west coast of the Uttara Kannada district in Karnataka.
The Mirjan Fort has rich history and there are many versions on the origin of the fort. According to one version, the fort was built in 16th century by Chennabhairav Devi, Queen of Gersoppa, a subordinate of Vijayanagar kings. Rani Chennabhairav Devi was also known as the Pepper Queen.
Her reign was one of the longest in the history of female domination in Indian history, from 1552 - 1606. The strong hold of her territory was centered on North and South Kanara districts and south Goa. After the battle of Tallikota in 1565, the territory was attacked by Bijapur Sultans.It is 82.6km from Banavasi.
Visiting Timings:-8AM TO 6PM
At a distance of 23 km from Sirsi, 50 km from Jog Falls, 139 km from Karwar and 111 km from Shimoga, Banavasi, also known as Konkanapura, is an ancient temple town in Uttar Kannada district of Karnataka. It is 24.2 kilometers from banavasi.
Visiting Timings:-6.30am to 8.30pm


Data class to hold one bid entry.
Object with JSON identifier namings. Only the id field is parsed explicitly.
Object to hold common data for the SDK. Not all variables and functions are used right now.
Still left in code.
Data class to hold the SDK configuration.
Helper class to check connection status amd read out connection type.
This code was taken from old sevenonemedia SDK.
Read out the Consent string.
The class uses the proposed identifiers: "IABConsent_CMPPresent" and "IABConsent_ConsentString"
Get the device type. Identifier encoding is taken from Yieldlab API spec.
Please note:
Data class to hold device meta data.
Non valid entries are encoded as null values.
Event to update Geolocation inside the SDK.
Event to update IDFA inside the SDK.
Event to update notify user about a probe request failure.
Event to update notify user about a log event.
Event to update notify user about a probe request success.
Exception for too low API level for using the SDK function.
Used if CompletableFutures are not supported.
Exception for too many adslots provided to API.
Exception for too few adslots provided to API.
Exception for network error events.
Exception for error while parsing response body.
Exception for no Google Play Services available.
Exception for SDK already initialized.
Exception for SDK not initialized.
Base class for all Exception thrown by SDK.
Helper class to get a geolocation.
Uses a fast and lightweight implementation to get the location over the FusedLocationProviderClient API.
Helper class to read out out the IDFA from Google. Also known as Google Advertiser ID.
Using this library: com.google.android.gms:play-services-ads-identifier:17.0.0
Class to hold all data for one network request.
Can not be implemented as data class.
Future variable can not be referenced on lower API levels (!)
Does the HTTP GET request to the backend.
Uses EventBus to communicate back to the SDK user
Helper class to build an URL.
Yieldprobe is implemented as singleton. Using Kotlin language object feature.
All methods are annotated with @JvmStatic so they are easy callable from Java.
Object to hold all URL parameters. Will be references in URLBuilderHelper.
Parameter taken from document "YLSE-011019-0910-34.pdf".


About
Work
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Hey I am Mimic
a web developer
These are some of my projects
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Technical Page
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ressume
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html基础界面
Show all >
Let's work together...
How do you take your coffee?
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Call me


Span
The Span
trait represents a  element.
Currently it includes two factories for Span
s that are
based on Cell
. As you read in Fundamentals, Cell
provides a general mechanism for an element's contents to be defined by
a Signal[NodeSeq]
.
The first factory simply takes a Signal[NodeSeq]
and
a returns a Span with Cell
.
val span = Span { for(t <- clock) yield Text("The time is now " + t) }
The second variant takes a binding function Signal
(Signal[NodeSeq=>NodeSeq]
).
This factory returns a binding function (NodeSeq=>NodeSeq
),
that when called will return a Span with Cell
whose content
is defined by applying the input to the returned function to the value
of the Signal
. Perhaps this will become more clear with an
example:

The time is

def innerBindFunc(t: Long): NodeSeq=>NodeSeq = "#span" #> t.toString val innerBindSignal = clock map innerBindFunc val outerBindFunc = "#div *" #> Span(innerBindSignal)
When outerBindFunc
runs, Span
's factory
will be called with innerBindSignal
, a Signal[NodeSeq=>NodeSeq]
.
The factory will return a binding function. Lift will call it with the
contents of the div
. When that happens, the binding
function will create a Signal[NodeSeq]
by calling innerBindSignal.map(bindFunc
=> bindFunc(divContents))
. In other words, it will be the result of
applying your binding function (in the Signal
) to
the NodeSeq
that Lift passes the binding function returned
by Span
— wrapped in a Span
.


Imagemap Test
This was the view outside my window at SunLabs. Click on something.
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I bet theres a lot of blogs out there that start with musings on making the blog. 🤔 This is a nothing-special pelican jinja2 static site getting hosted on GitHub.
Jinja2 templates are really nice and since I'm using them for Flask recently, they seem like a major evolution beyond php for reusing code.
Heres one fun thing to share. A bit of a hack to get Jinja2 to emit UUID4s on the page.
Objective
Ensure browser updates linked stylesheets each time the site is rebuilt, rather than using cached versions.
Strategy
Use Jinja2 to add a random version identifier to the URL of the stylesheet. I saw this trick of adding a random identifyer to the URL over on stackoverflow1 and got it working in the Jinja2 framework this blog is using. Each time the site is built, a random string is added as a GET format variable on the URL and thus the browser is encouraged to reload this new entity. A good and a bad thing to this approach is that the version of the CSS is only updated when the site is rebuilt, not every time the client loads the site. If you need it every time ... better be using flask or javascript to accomplish that. Fortunetly this is exactly the behavior we need for a static site like this.
Code
Where a version string is added to the URL of the style sheet. I wanted to do something like that without this blog since I’ll be editing the style sheet a lot, and I found a way to get UUID4’s into the jinja2. Its kind of a hack because I could only find a way to make filter functions. So thats what I setup first.
pelicanconf.py
from uuid import uuid4
def get_uuid4_string(not_used):
return str(uuid4())
JINJA_FILTERS = {'uuid4':get_uuid4_string}
Now with the filter in place we can put it to work to emit UUID4 strings.
base.html
{# Hack of a jinja2 filter to add uuid4's to links to skirt browser caching #}
<link href="{{ SITEURL }}/theme/static/css/style.css?version={{ 'whatever'|uuid4 }}" rel="stylesheet" />
Result
And if we inspect the html of this page… index.html
we can see it looks okay!
<head>
<title>Hello World - A bioinformatics adventure</title>
<meta charset="UTF-8" />
<link href="/theme/static/css/style.css?version=7921c390-0b9d-4c6b-81a0-6e18fd59683d" rel="stylesheet" />
</head>


| Zone Name | Location Type | Size | Links | |
|---|---|---|---|---|
| Leaderboard | Leaderboard | 728x90 | Stats Edit Code | |
| Super Leaderboard | Super Leaderboard | 970x90 | Stats Edit Code | |
| Cube A | Medium Rectangle | 300x250 | Stats Edit Code | |
| Cube B | Medium Rectangle | 300x250 | Stats Edit Code | |
| Cube C | Medium Rectangle | 300x250 | Stats Edit Code | |
| Mobile Banner | SmartPhone Static Wide Banner | 320x50 | Stats Edit Code | |
| Mobile Footer | SmartPhone Static Wide Banner | 320x50 | Stats Edit Code | |
| Footer | Leaderboard | 728x90 | Stats Edit Code | |


A low-watt bulb in a cheap lampshade illuminated the table top, and anything caught above it, in a cone that had hooked its apex to the tungsten filament. Smoke stratified the air, moving barely. Outside this cone nothing existed except as a suggestion. Four people sat, perhaps. there were the hints of featureless walls. There may have been a door.
1.
The first leaned forward into the light: first his cheeks, then his mean forehead and chin were visible. Each of the spines on his unshaven chin was a "V" composed of one grey and one black needle. His skin was almost as colourless as his beard under the glare.
He looked at his three companions and adversaries who did not seem to exist, one at a time. Realistically it could not help his decision, as they had no faces visible to be read, poker or otherwise. Still it hardened his resolve into a choice. He indicated this choice by moving rapidly back into obscurity, save his fretting hand which scooped up two chips of identical colour. They were launched haphazardly into a bowl, to lie upon a rainbow of other chips. "See five, raise five," was heard across the table, and the hand disappeared.
2.
With one fluid unaccelerated movement, the second swung himself forward. His eyes were rectangular and slitted, like a pillbox seen edge-on, and looked through glasses that matched their shape, only larger. The two of them looked steadily forward from his flat, expressionless face.
"See your ten," he clipped. Lips as angular as his eyes cut and chopped the words into shape. Manicured digits appeared and handled a single chip, of a different colour to the two sitting on top of the pile. This chip was apparently worth ten alone, and was almost placed rather than thrown, along with its cousins, in the centre of the table. As the hand receded, this gentleman's head glided back out of sight.
3.
The fat, beery face of a third player appeared. It glistened in the light, showing its curves in a sheen of sweat.  He blew out air which confused the smoke.
Cards appeared in one hand, flashing bright red backs as if to attract other cards. Depending on the individual, the combined stereoscopy of the human eyes can stretch to some one hundred and fifty degrees from left to right. True focus can only be obtained within a few degrees of the eyes' axis of vision, but is often not necessary to recognise exaggerated artistic features, such as the scowl of a knave as distinct from the curves of a queen. Suspecting this he bent his cards into an arc that subtended a similar fovea's worth of degrees.
A second hand reached over to a whisky glass on the table. The whisky glass was present all the time. Like the pot and the table and the stakes, it had its own existence. It was steady even as the liquid inside rocked from side to side: it steadied and the fat man swung around it in space. His fat, hairy fingers clung tightly to it, and his rubbery lips inhaled a short draught of its contents. Blinking, seeing the table for the first time, the face retreated even as the hand flung the cards outwards and slammed the glass down. "Fold," called the retreating lips and they vanished.
4.
From the direction of where the fourth player might have been sitting there came a high-voiced grunt. It was difficult to tell whether the grunt emanated from features expressing humour, resignation or any other emotion. The grunt itself was bleached as it passed over the lit table. A few fingers slipped over the chips at that side of the table, and disappeared. Half a second later a pale, delicate hand sliced through the light and a chip, worth precisely ten in whatever units they were using and of a similar colour to the second man's most recent bet, appeared by prestidigitation and with a clink in the pot.
"See ten," said a voice in a similar tone to the earlier grunt, and perhaps the voice came from the final chip, sitting with finality on the top of the pile. It was that little disc of plastic that spoke in a clear voice to two of the three pitch-black edges of the table.
"What do you have?"


As is mentioned in Sec. A.4, the beta limit study on JET tokamak shows that the maximal βt obtained is proportional to Ip∕aBt0. This means the maximal plasmas pressure obtained is proportional to Ip∕a, i.e.,
|
| (538) |
The total plasma energy is given by E ≈⟨p⟩2πRπa2, where R is the major radius of the device. Using Eq. (538), we obtain
|
| (539) |
Since fusion power is proportional to the plasma energy, the above relation indicates, to obtain larger fusion power, we need bigger tokamaks with larger plasma current.
The reason why larger plasma current is desired can also be appreciated by examining an empirical scaling of the the energy conﬁnement time τE given by
|
| (540) |
which is proportional to I2.
Another fundamental reason for building larger tokamaks is that the energy conﬁnement time τE ∼ a2∕χ increases with the machine size, where χ is the heat diﬀusitivity. In addition, the heat diﬀusitivity χ decreases with increasing machine size if the diﬀusitivity satisﬁes the gyro-Bohm scaling, which is given by
|
| (541) |
which is inverse proportional to the machine size a. However, if the diﬀusitivity satisﬁes the Bohm scaling, which is given by
|
| (542) |
then, the diﬀusitivity is independent of the machine size. The Bohm diﬀusitivity χB is a∕ρs times larger than the gyro-Bohm diﬀusitivity χGB, where ρs is the gyro-radius. Heat diﬀusitivity scaling in the low conﬁnement operation (L mode) in present-day tokamaks is observed to be Bohm or worse than Bohm.


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{% extends 'about/base.html' %} {% load staticfiles %} {% block title %}Core Values{% endblock title %} {% block values_active %}active{% endblock values_active %} {% block extrahead %} {% endblock extrahead %} {% block about_content %}
We believe learning is fundamental to human flourishing, and strive to support educational opportunities on every front, both with the tools we create, and in how we create them. When faced with a choice between optimal efficiency or a chance to learn something new, we will choose to learn, to grow, and to better ourselves. We teach each other and actively learn from one another, and are willing to take on challenges for which we may not feel quite ready.
If you can address a problem now, don't wait. Waiting for a problem to resolve itself will only create additional problems along the way. Whether it's the slow and uneven spread of global Internet, or a problem that has been brewing with a coworker, we recognize the compounding effects of inequality, conflict, and suffering, and aim to resolve problems at their root.
"If you want to go fast, go alone. If you want to go far, go together." Important problems cannot be solved by a knight in shining armour made of silver bullets, but instead require a community of diverse voices and skills collaborating and supporting one another. Just as the tools we create are only ever part of the solution to global inequality of educational access and achievement, we are made stronger by our partnerships and collaborations, and our efforts are magnified.
The beauty of knowledge is that its value is not diminished, but rather made even greater, by sharing it as broadly as possible. When others remix, repurpose, and build upon what has been shared, cascading value is created for the global community. And when someone leverages that knowledge to make the world a better place, we all benefit. High costs and restrictive copyrights erect barriers to learning and growth, and thereby slow the spread of equal learning opportunities for all.
Enabling equal access for all requires proactively designing solutions that are able to meet a wide diversity of needs and contexts, sensitive to technology, culture, and user ability. It's easy to design something that fulfills your own needs; the big challenge is in building something that is intuitive, effective, and high-performance across a wide range of users and devices. If we can build for the lowest common denominator without sacrificing quality, then everybody can benefit from the tools we're creating.
Every person, community, or country knows its own needs and values best, and our role is to collaborate in supporting mutual self-fulfilment, not to dictate solutions. Similarly, within our own organization we aim to empower each other and support one another's goals and self-actualization, while collaborating toward common goals. We work to give voice to others, not create an echo chamber.
We strive to improve the happiness of the world, and believe we can be happy doing it.  We think that joyfully creating tools for a troubled world can make the world more joyful, both in our work and the user's enjoyment.


"""The Window class.
This class is the main graphical content of any window. With
[Dialog](dialog.md), chances are you won't need anything else as a
container for your windows.
The Window class contains the controls of your window, as user-defined
methods prefixed with `on`.. It can also contain data models and controls
of the contained widgets (graphical elements) in this window. Optionally,
it can contain the window layout, though it's recommended to place this
layout in a separate [file](../layout/file.md).
"""
import asyncio
import inspect
from pathlib import Path
import sys
from typing import Type, Union
from bui.control.exceptions import StopControl
from bui.layout.parser import BUILayoutParser
from bui.tasks import cancel_all, run_remaining
from bui.widget.base import Widget
from bui import widget as wg
class MetaWindow(type):
"""
Metaclass for the window class.
It only traces the layout attribute for debugging purposes.
"""
_marks = {}
def __prepare__(name, bases, **kwargs):
namespace = {
"mark": MetaWindow.mark
}
# If one of the bases has a `close` method, put it in the namespace
for base in bases:
close = getattr(base, "close", None)
if close:
namespace["close"] = close
namespace["stop_control"] = base.stop_control
break
return namespace
@staticmethod
def mark(layout: str) -> str:
"""Mark layout in the window."""
frame = sys._getframe().f_back
file = frame.f_globals["__file__"]
line = frame.f_lineno
line = line - len(layout.splitlines())
qualname = frame.f_locals["__qualname__"]
MetaWindow._marks[qualname] = (file, line)
return layout
class Window(Widget, metaclass=MetaWindow):
"""
The Window main class.
Instanciating it (with `Window()`) will attempt to create and return an
object of a specific GUI toolkit. This object will inherit from `Window`
and will have the exact same methods and attributes. You should remain
blessfully ignorant of the real class you use. BUI is designed in such
a way that you can ignore how it does its magic for a particular
GUI toolkit, except if you're coding for such a toolkit.
Class attributes:
layout (str, optional): the optional window layout, if it is not
defined in a separate [file](../layout/file.md). It is
recommended to not use this class attribute, but you still
can do so, if you have your reasons.
bui (str, optional): the path leading to the `.bui` file
containing your layout. By default, this is in the same
folder and has the same name as the Python file containing
your Window class, except it has the `.bui` extension. If
you use this naming convention, you don't have to override
the `bui` class attribute. Otherwise, give it a relative
or absolute path: absolute paths consider their root to be
the user directory when the Python application started
(which might not be the same as the directory in which
your Python file is contained).
[Controls]../control/overview.md] are defined as methods on this
class. By convention, their name starts with `on_`, like `on_focus` or
`on_quit`. You can also watch for widget controls (execute a method
when a button is pressed, for instance). In this case, you can create
`on_{control verb}_{control ID}` like `on_click_button`. BUI will
attempt to connect `on*` methods with controls and will tell you if
it fails, or has a doubt.
"""
widget = "window"
class_name = "Window"
default_controls = {
"close": "The window is ready to be closed",
"init": "The window is ready to be displayed",
"press": "The user presses a key anywhere in the window",
"release": "The user releases a key anywhere in the window",
"right_click": "The user right clicks in the window",
"type": "The user types a character anywhere in the window",
}
_debug_controls = False
# Can be overrideen by subclasses
layout = ""
bui = ""
# Class attributes, to be overridden by instance attributes
parsed_layout = None
def __init__(self, leaf):
super().__init__(leaf)
self.control_methods = {}
self.title = leaf.title
self.width = leaf.width
self.height = leaf.height
self._ids = {}
def __getitem__(self, item):
try:
return self._ids[item]
except KeyError:
raise KeyError(f"{item!r} isn't a known or valid "
"widget identifier") from None
@property
def usable_surface(self):
"""
Return the screen size that can be used, in pixels.
This size is returned in a tuple: (width, height), so that
(x, y) follow the exact same pattern. Both components are integers.
Note that this is the screen surface being "free", that is,
not counting the taskbar on some operating systems, since
we cannot draw on that. Therefore, the usable surface tends
to be somewhat narrower than the screen resolution.
"""
return self.specific.usable_surface
@classmethod
def parse_layout(cls, Window, tag_name="window"):
"""
Determine where the layout is and try to parse it, return a window.
Raises:
ValueError: the layout couldn't be parsed.
"""
if cls.layout:
layout = cls.layout
# Try to find the first line and the proper file,
# since the layout is defined in code
qualname = cls.__qualname__
file, line = MetaWindow._marks.get(qualname, ("__unknown__", 0))
parser = BUILayoutParser(file, line)
else:
bui = cls.bui
if not bui:
filename = Path(inspect.getsourcefile(cls))
bui = f"{filename.stem}.bui"
with open(bui, 'r', encoding="utf-8") as file:
layout = file.read()
parser = BUILayoutParser(bui)
parser.feed(layout)
parsed_layout = parser.layout
window_leaf = parsed_layout.get(tag_name)
if window_leaf is None:
raise ValueError("the specified layout doesn't contain a <window> description")
# Creates all the leafs
from bui.widget import WIDGETS
widgets = []
ids = {}
for leaf in parsed_layout.flat:
leaf.complete()
if not leaf.has_widget:
continue
elif leaf is window_leaf:
Generic = Window
else:
Generic = WIDGETS[leaf.tag_name]
widget = Generic(leaf)
leaf.widget = widget
widget.create_specific()
widgets.append(widget)
if leaf is window_leaf:
window = widget
widget_id = getattr(widget, "id", None)
if widget_id:
ids[widget_id] = widget
window._ids = ids
# Call the `_init` method on all generic widgets
if window._debug_controls:
print(" Binding control methods...")
for widget in widgets:
widget._bind_controls(window)
widget._init()
window.parsed_layout = parsed_layout
for widget in widgets:
widget._process_control("init")
return window
async def sleep(self, seconds):
"""
Asynchronous sleep during the specified number of seconds.
This method should ONLY be called in an asynchronous control method.
It is a shortcut to `asyncio.sleep`.
Args:
seconds (int or float): the number of seconds to wait.
"""
await asyncio.sleep(seconds)
def _init(self):
"""Private method to initialize the generic and specific window."""
self.specific._init()
def _start(self, loop):
"""
Start the window, watch events and allow async loop.
Args:
loop (AsyncLoop): the asynchronous event loop (see asyncio).
"""
self.specific.show()
return self.specific._start(loop)
def _stop(self):
"""Stop the window toolkit."""
cancel_all()
self._process_control("close")
run_remaining()
self.close()
def close(self):
"""Close this window."""
self.specific.close()
def stop_control(self):
"""Stop the control, and the control method that called it."""
raise StopControl()
def pop_dialog(self, dialog: Union[str, Type['wg.dialog.Dialog']]
) -> 'wg.dialog.Dialog':
"""
Pop up a dialog, blocks until the dialog has been closed.
Args:
dialog (str or Dialog): the dialog layout (as a str) or the
Dialog class to instantiate from.
Returns:
dialog (Dialog): the dialog object.
"""
from bui.widget.dialog import Dialog
if isinstance(dialog, str):
class NewDialog(Dialog):
layout = mark(dialog)
dialog = NewDialog
assert issubclass(dialog, wg.dialog.Dialog)
dialog.window = self
dialog_obj = dialog.parse_layout(dialog, tag_name="dialog")
self.specific.pop_dialog(dialog_obj.specific)
return dialog_obj
def pop_menu(self, context_id: str):
"""
Pop a context menu, blocks until the menu is closed.
Args:
context_id (str): the registered ID of the context menu.
"""
context = self[context_id]
self.specific.pop_menu(context.specific)
def open_window(self, window: "Window", child=False):
"""
Open a new window.
Args:
window (Window): the window class.
child (bool): if True, the new window will be a child of the
current window (closing self will close the new window).
"""
window = window.parse_layout(window)
self.specific.open_window(window.specific, child=child)
return window
def handle_close(self, control):
"""The window closes."""
pass


The Game Awards 2019 Nominee List Revealed as Voting Opens
by SillicurIt is that time of the year again when we reflect back on a year of awesome gaming and what better way to do it than to vote for your favourite games, developers, esports teams and much more. That’s what The Game Awards hosted and produced by Geoff Keighley is all about. The Game Awards 2019 will take place on 12 December 2019 (13 December at 03:30 for South Africans) and now, the voting has opened and the nominee list for The Game Awards 2019 have been revealed.
RELATED: Detroit: Become Human PC Release Date and Details Revealed
There are 29 categories to vote in over on the official website and you can register and cast your vote for your favourites from The Game Awards 2019 nominee list by heading on over to this link. Death Stranding leads the way, being nominated in nine categories, including GOTY, which isn’t all that surprising since we gave it a 10/10 in our review. Remedy’s Control, which we gave a 9.2/10 in our review, has been nominated in eight categories.
The Game Awards 2019 nominee list was picked by “a jury of 80 media and influencer outlets” and the choices, for the most part, look very solid, with a possible exception in the esports player of the year category where there is no player from OG, a team that made esports history this year.
Check out The Game Awards 2019 nominee list below and don’t forget to vote for your favourite in each category. Scroll down to the bottom of the article if you don’t like reading to watch the video announcement.
Game of the Year
- Control (Remedy/505 Games)
- Death Stranding (Kojima Productions/SIE)
- Super Smash Bros. Ultimate (Bandai-Namco/Sora/Nintendo)
- Resident Evil 2 (Capcom/Capcom)
- Sekiro: Shadows Die Twice (From Software/Activision)
- The Outer Worlds (Obsidian/Private Division)
Best Game Direction
- Control (Remedy/505 Games)
- Death Stranding (Kojima Productions/SIE)
- Resident Evil 2 (Capcom/Capcom)
- Sekiro: Shadows Die Twice (From Software/Activision)
- Outer Wilds (Mobius Digital/Annapurna)
Best Narrative
- A Plague Tale: Innocence (Asobo/Focus Home)
- Control (Remedy/505)
- Death Stranding (Kojima Productions/SIE)
- Disco Elysium (ZA/UM)
- The Outer Worlds (Obsidian/Private Division)
Best Art Direction
- Control (Remedy/505)
- Death Stranding (Kojima Productions/SIE)
- Gris (Nomada Studio/Devolver)
- Sayonara Wild Hearts (Simogo/Annapurna)
- Sekiro: Shadows Die Twice (From Software/Activision)
- The Legend of Zelda: Link’s Awakening (Grezzo/Nintendo)
Best Score/Music
- Cadence of Hyrule (Brace Yourself Games/Nintendo)
- Death Stranding (Kojima Productions/SIE)
- Devil May Cry 5 (Capcom)
- Kingdom Hearts III (Square Enix)
- Sayonara Wild Hearts (Simogo/Annapurna)
Best Audio Design
- Call of Duty: Modern Warfare (Infinity Ward/Activision)
- Control (Remedy/505)
- Death Stranding (Kojima Productions/SIE)
- Gears 5 (The Coalition/Xbox Game Studios)
- Resident Evil 2 (Capcom)
- Sekiro: Shadows Die Twice (From Software/Activision)
Best Performance
- Ashly Burch as Parvati Holcomb, The Outer Worlds
- Courtney Hope as Jesse Faden, Control
- Laura Bailey as Kait Diaz, Gears 5
- Mads Mikkelsen as Cliff, Death Stranding
- Matthew Porretta as Dr. Casper Darling, Control
- Norman Reedus as Sam Porter Bridges, Death Stranding
Games for Impact
- Concrete Genie (Pixelopus/SIE)
- Gris (Nomada Studio/Devolver)
- Kind Words (Popcannibal)
- Life is Strange 2 (Dontnod/Square Enix)
- Sea of Solitude (Jo-Mei Games/EA)
Best Ongoing Game
- Apex Legends (Respawn)
- Destiny 2 (Bungie)
- Final Fantasy XIV (Square Enix)
- Fortnite (Epic Games)
- Tom Clancy’s Rainbow Six Siege (Ubisoft Montreal/Ubisoft)
Best Independent Game
- Baba Is You (Hempuli)
- Disco Elysium (ZA/UM)
- Katana ZERO (Askiisoft/Devoler)
- Outer Wilds (Mobius Digital/Annapurna)
- Untitled Goose Game (House House/Panic)
Best Mobile Game
- Call of Duty: Mobile (TiMi Studios/Activision)
- GRINDSTONE (Capybara Games)
- Sayonara Wild Hearts (Simogo/Annapurna)
- Sky: Children of Light (Thatgamecompany)
- What the Golf? (Tribland)
Best Community Support
- Apex Legends (Respawn/EA)
- Destiny 2 (Bungie)
- Final Fantasy XIV (Square Enix)
- Fortnite (Epic Games)
- Tom Clancy’s Rainbow Six Siege (Ubisoft Montreal/Ubisoft)
Best VR/AR Game
- Asgard’s Wrath (Sanzaru Games/Oculus Studios)
- Blood & Truth (SIE London Studio/SIE)
- Beat Saber (Beat Games)
- No Man’s Sky (Hello Games)
- Trover Saves the Universe (Squanch Games)
Best Action Game
- Apex Legends (Respawn/EA)
- Astral Chain (Platinum Games/Nintendo)
- Call of Duty: Modern Warfare (Infinity Ward/Activision)
- Devil May Cry 5 (Capcom/Capcom)
- Gears 5 (The Coalition/Xbox Game Studios)
- Metro Exodus (4A Games/Deep Silver)
Best Action/Adventure Game
- Borderlands 3 (Gearbox/2K)
- Control (Remedy/505 Games)
- Death Stranding (Kojima Productions/SIE)
- Resident Evil 2 (Capcom)
- The Legend of Zelda: Link’s Awakening (Grezzo/Nintendo)
- Sekiro: Shadows Die Twice (From Software/Activision)
Best RPG
- Disco Elysium (ZA/UM)
- Final Fantasy XIV (Square Enix)
- Kingdom Hearts III (Square Enix)
- Monster Hunter World: Iceborne (Capcom)
- The Outer Worlds (Obsidian/Private Division)
Best Fighting Game
- Dead or Alive 6 (Team Ninja/Koei Tecmo)
- Jump Force (Spike Chunsoft/Bandai Namco)
- Mortal Kombat 11 (NetherRealm/WBIE)
- Samurai Showdown (SNK/Athlon)
- Super Smash Bros. Ultimate (Bandai Namco/Sora/Nintendo)
Best Family Game
- Luigi’s Mansion 3 (Next Level Games/Nintendo)
- Ring Fit Adventure (Nintendo EPD/Nintendo)
- Super Mario Maker 2 (Nintendo EPD/Nintendo)
- Super Smash Bros. Ultimate (Bandai Namco/Sora/Nintendo)
- Yoshi’s Crafted World (Good-Feel/Nintendo)
Best Strategy Game
- Age of Wonders: Planetfall (Triumph Studios/Paradox)
- Anno 1800 (Blue Byte/Ubisoft)
- Fire Emblem: Three Houses (Intelligent Systems/Koei Tecmo/Nintendo)
- Total War: Three Kingdoms (Creative Assembly/Sega)
- Tropico 6 (Limbic Entertainment/Kalypso Media)
- Wargroove (Chucklefish)
Best Sports/Racing Game
- Crash Team Racing Nitro-Fueled (Beenox/Activision)
- DiRT Rally 2.0 (Codemasters)
- eFootball Pro Evolution Soccer 2020 (PES Productions/Konami)
- F1 2019 (Codemasters)
- FIFA 20 (EA Sports)
Best Multiplayer Game
- Apex Legends (Respawn/EA)
- Borderlands 3 (Gearbox/2K)
- Call of Duty: Modern Warfare (Infinity Ward/Activision)
- Tetris 99 (Arika/Nintendo)
- Tom Clancy’s The Division 2 (Massive Entertainment/Ubisoft)
Fresh Indie Game Presented by Subway
- ZA/UM for Disco Elysium
- Nomada Studio for Gris
- DeadToast Entertainment for My Friend Pedro
- Mobius Digital for Outer Wilds
- Mega Crit for Slay the Spire
- House House for Untitled Goose Game
Content Creator of the Year
- Courage – Jack Dunlop
- Dr. Lupo – Benjamin Lupo
- Ewok – Soleil Wheeler
- Grefg – David Martínez
- Shroud – Michael Grzesiek
Best Esports Game
- Counter-Strike: Global Offensive (Valve)
- DOTA2 (Valve)
- Fortnite (Epic Games)
- League of Legends (Riot Games)
- Overwatch (Blizzard)
Best Esports Player
- Kyle ‘Bugha’ Giersdorf (Immortals, Fortnite)
- Lee ‘Faker’ Sang-hyeok (SK Telecom, League of Legends)
- Luka ‘Perkz’ Perkovic (G2 Esports, League of Legends)
- Oleksandr ‘S1mple’ Kostyliev (Natus Vincere, CSGO)
- Jay ‘Sinatraa’ Won (SF Shock, Overwatch)
Best Esports Team
- Astralis (CS:GO)
- G2 Esports (LOL)
- OG (DOTA2)
- San Francisco Shock (OWL)
- Team Liquid (CS:GO)
Best Esports Event
- 2019 Overwatch League Grand Finals
- EVO 2019
- Fortnite World Cup
- IEM Katowice 2019
- League of Legends World Championship 2019
- The International 2019
Best Esports Coach
- Eric ‘adreN’ Hoag (Team Liquid, CS:GO)
- Nu-ri ‘Cain’ Jang (Team Liquid, LOL)
- Fabian ‘GrabbZ’ Lohmann (G2 Esports, LOL)
- Kim ‘Kkoma’ Jeong-gyun (SK Telecom T1, LOL)
- Titouan ‘Sockshka’ Merloz (OG, DOTA2)
- Danny ‘Zonic’ Sørensen (Astralis, CSGO)
Best Esports Host
- Eefje “Sjokz” Depoortere
- Alex “Machine” Richardson
- Paul “Redeye” Chaloner
- Alex “Goldenboy” Mendez
- Duan “Candice” Yu-Shuang
Check out The Game Awards 2019 nominee announcements below in a 10-minute video from Geoff Keighley then tell us what your GOTY is in the comment section.


10.4.d delete action using at attribute
|
| open |
../../Chapt10/10.4/10.4.d.xhtml |
&nsp; |
Opens the form |
| waitForModelReady |
|
|
|
| verifyTitle |
10.4.d delete action using at attribute |
|
Makes sure this is the right form |
| verifyElementPresent |
xpath=/html/body/xforms:model/xforms:action[@ev:event='xforms-ready']/xforms:delete[@nodeset="instance('instance_2')/number_list/number" and @at="1"] |
|
Checks that delete is in the form |
| verifyElementPresent |
xpath=/html/body/xforms:model/xforms:action[@ev:event='xforms-ready']/xforms:delete[@nodeset="number_list[3]/number" and @at="-2"] |
|
Checks that delete is in the form |
| verifyElementPresent |
xpath=/html/body/xforms:model/xforms:action[@ev:event='xforms-ready']/xforms:delete[6] |
|
Checks that delete is in the form |
| verifyText |
xpath=/html/body/xforms:group[3]/xforms:repeat |
1*2 |
Checks that output is in the form |
| verifyText |
xpath=/html/body/xforms:group[4]/xforms:repeat |
4*6 |
Checks that output is in the form |
| verifyText |
xpath=/html/body/xforms:group[5]/xforms:repeat |
8*9 |
Checks that output is in the form |
| verifyText |
xpath=/html/body/xforms:group[6]/xforms:repeat |
10*11 |
Checks that output is in the form |
| verifyText |
xpath=/html/body/xforms:group[7]/xforms:repeat |
13*14 |
Checks that output is in the form |
| verifyText |
xpath=/html/body/xforms:group[8]/xforms:repeat |
17 |
Checks that output is in the form |


{% extends "home/home_base.html" %} {% block trust_active %}active{% endblock %} {% block home_content %}
We understand that. So, before to bet any amount of bitcoin, what about access the game in test mode? During the game you will find further instructions on how to proceed and will have access to proof information. This can be proftable for both of us: you can take a better look on how things works and we can check for bugs during your staying.


Cabinet approves two-year moratorium on spectrum payments for telcos
by PTINEW DELHI: Providing relief to telecom companies, the Union Cabinet on Wednesday approved a moratorium of two years for spectrum payments, sources said.
The move to defer payments for 2020-21 and 2021-22 will give Rs 42,000 crore relief to Bharti Airtel, Vodafone Idea and Reliance Jio, they said.
The move was approved by the Union Cabinet headed by Prime Minister Narendra Modi.


Its me Thanga (preferred to call) having 5.8 years of experience in Big data engineering and building data lake solutions. Implemented multiple data engineering project across many domains such as Retail, Market Research and Healthcare. Built data lake using AWS stack (S3, Kinesis, Lambda, Redshift). Having deep knowledge on Hadoop, Spark, Flume, Hive, NiFi, Kafka, Solr, ELK (Elasticsearch, Logstash, Kibana), MongoDB, Neo4j. Acquired programming knowledge in Python, SQL, Java and Scala. Having hands-on dirty data to curated data. Having good understanding on NLP and having experience in deployment.
As a senior data engineer building data lake for our retail customers using AWS stack providing curated data to data science team based on their use case requirements. Also handing all Research and Development projects with 5-8 team members. Giving my knowledge to junior data engineers by providing trainings
Third eye is a Face Recognition based solution to monitor Footfall in malls and airports. It is capable of finding face demographic information's like Gender, Age group and Emotions for the people entering the premises. Crime prevention, vehicle classification and license plate recognition and authorizing the staffs.
Involves combing the sales data of all shopping centres across the country into data lake and to see the trends and the direction in which the Retail industry is going. How is the growth of Retail industry in India? How is the trend in next 6 months? Is it upwards or downwards or flat? If so, at what rate? How is a category [Ex: Fashion] is performing in a market [Ex: Mumbai]?
OData 360° makes it easy to choose a best location to open a store and to identify potential area around it. It is based on the geo spatial concepts and advanced statistics which can make effective analysis on customer demographics, social economic, trading and competitors’ factors and will help in analyzing the proper catchment areas. Draw flexible and actionable market boundaries for area up to the level of 5 sq.km. Prioritize the market based on the consumer demography, customer spent pattern, city’s sales potential to perform the catchment analysis and to know the competitor’s presence
Planning and Route Optimization is to create a travel schedule for auditors to visit nearby stores based on the Auditor Location. It includes to find the actual distance and best path to travel. And provide real-time routing.
Match and Merge Algorithm enables GSD (Global Store Data) to accept data from multiple data sources and perform matching in such a way that only one golden copy of the store in retained. Performs the matching across various attributes and gives match score for all the matches displayed. Perform both exact and inexact matches based on the threshold defined by the users. Also provide results with less relevance to the actual query
The purpose of project is to create application which can detect plagiarism in the assignments submitted by students through online. This involved extraction of text content form .DOC, DOCX and PDF using Apache Tika and load it into Hadoop .Using MapReduce processing engine we create N-Grams and using Jaccard co-efficient to check similarity between the documents. And the reporting has been done in Qlikview.
The purpose of project is to create application which can pull streaming Twitter data into Bigdata environment HDFS and Elasticsearch. The dashboard has been visualize using Kibana. Then named entity extraction done using spark and stored in Neo4j as a batch. Using Neo4j data an interactive network Visualization has been developed using Vis.js.
The purpose of project is to create near real time log analytics application for analyzing huge logs of web applications servers and IIS servers of leading investment banking firm. The application will provide real time insight for different server metrics which will help manage their IT infrastructure in better fashion by detecting major bottlenecks. This involves real time data ingestion of web server logs into Elasticsearch and HDFS using Flume
In the Insurance Company claims are submitted, out of which few claims can be fraud. Job involves gathering requirements and setting up a design for dataflow. Creating ETL mappings and loading data into the database for report generation. The idea of the work is to find the fraudulent claims and analyze the factors which normally makes a claim a fraudulent claim like high claim amount, number of parts damaged etc.


The History Of Coffee
In the Ethiopian highlands, where the legend of Kaldi, the goatherd, originated, coffee trees grow today as they have for centuries. Though we will never know with certainty, there probably is some truth to the Kaldi legend.
It is said that he discovered coffee after noticing that his goats, upon eating berries from a certain tree, became so spirited that they did not want to sleep at night.
Kaldi dutifully reported his findings to the abbot of the local monastery who made a drink with the berries and discovered that it kept him alert for the long hours of evening prayer. Soon the abbot had shared his discovery with the other monks at the monastery, and ever so slowly knowledge of the energizing effects of the berries began to spread. As word moved east and coffee reached the Arabian peninsula, it began a journey which would spread its reputation across the globe.
 Whether it is Asia or Africa, Central or South America, the islands of the Caribbean or Pacific, all can trace their heritage to the trees in the ancient coffee forests on the Ethiopian plateau. coffeegatheringThe Arabian Peninsula
The Arabs were the first, not only to cultivate coffee but also to begin its trade. By the fifteenth century, coffee was being grown in the Yemeni district of Arabia and by the sixteenth century it was known in Persia, Egypt, Syria and Turkey.
The history Coffee was not only drunk in homes but also in the many public coffee houses -- called qahveh khaneh -- which began to appear in cities across the Near East. The popularity of the coffee houses was unequaled and people frequented them for all kinds of social activity. Not only did they drink coffee and engage in conversation, but they also listened to music, watched performers, played chess and kept current on the news of the day. In fact, they quickly became such an important center for the exchange of information that the coffee houses were often referred to as 'Schools of the Wise.'
With thousands of pilgrims visiting the holy city of Mecca each year from all over the world, word of the 'wine of Araby' as the drink was often called, was beginning to spread far beyond Arabia. In an effort to maintain its complete monopoly in the early coffee trade, the Arabians continued to closely guard their coffee production.
Coffee Comes to Europe (pic)
European travellers to the Near East brought back stories of the unusual dark black beverage. By the 17th century, coffee had made its way to Europe and was becoming popular across the continent. Opponents were overly cautious, calling the beverage the 'bitter invention of Satan.' With the coming of coffee to Venice in 1615, the local clergy condemned it. The controversy was so great that Pope Clement VIII was asked to intervene. Before making a decision however, he decided to taste the beverage for himself. He found the drink so satisfying that he gave it Papal approval.
coffeecomestovienna1Despite such controversy, in the major cities of England, Austria, France, Germany and Holland, coffee houses were quickly becoming centers of social activity and communication. In England 'penny universities' sprang up, so called because for the price of a penny one could purchase a cup of coffee and engage in stimulating conversation. By the mid-17th century, there were over 300 coffee houses in London, many of which attracted patrons with common interests, such as merchants, shippers, brokers and artists.
Many businesses grew out of these specialized coffee houses. Lloyd's of London, for example, came into existence at the Edward Lloyd's Coffee House. The New World
In the mid-1600's, coffee was brought to New Amsterdam, a location later called New York by the British. (pic)
Though coffee houses rapidly began to appear, tea continued to be the favored drink in the New World until 1773 when the colonists revolted against a heavy tax on tea imposed by King George. The revolt, known as the Boston Tea Party, would forever change the American drinking preference to coffee.
Plantations Around the World (pic)
As demand for the beverage continued to spread, there was tense competition to cultivate coffee outside of Arabia. Though the Arabs tried hard to maintain their monopoly, the Dutch finally succeeded, in the latter half of the 17th century, to obtain some seedlings. Their first attempts to plant them in India failed but they were successful with their efforts in Batavia, on the island of Java in what is now Indonesia. The plants thrived and soon the Dutch had a productive and growing trade in coffee. They soon expanded the cultivation of coffee trees to the islands of Sumatra and Celebes.
The Dutch did a curious thing, however. In 1714, the Mayor of Amsterdam presented a gift of a young coffee plant to King Louis XIV of France. The King ordered it to be planted in the Royal Botanical Garden in Paris. In 1723, a young naval officer, Gabriel de Clieu obtained a seedling from the King's plant.  Once planted, the seedling thrived and is credited with the spread of over 18 million coffee trees on the island of Martinique in the next 50 years. It was also the stock from which coffee trees throughout the Caribbean, South and Central America originated.
Coffee is said to have come to Brazil in the hands of Francisco de Mello Palheta who was sent by the emperor to French Guiana for the purpose of obtaining coffee seedlings. But the French were not willing to share and Palheta was unsuccessful. However, he was said to have been so handsomely engaging that the French Governor's wife was captivated. As a going-away gift, she presented him with a large bouquet of flowers. Buried inside he found enough coffee seeds to begin what is today a billion-dollar industry.
In only 100 years, coffee had established itself as a commodity crop throughout the world. Missionaries and travellers, traders and colonists continued to carry coffee seeds to new lands and coffee trees were planted worldwide. Plantations were established in magnificent tropical forests and on rugged mountain highlands. Some crops flourished, while others were short-lived. New nation's were established on coffee economies. Fortunes were made and lost. And by the end of the 18th century, coffee had become one of the world's most profitable export crops.


--- layout: page title: JSON Schema permalink: / ---
JSON Schema is a vocabulary that allows you to annotate and validate JSON documents.
The JSON document being validated or described we call the instance, and the document containing the description is called the schema.
The most basic schema is a blank JSON object, which constrains nothing, allows anything, and describes nothing:
{}
You can apply constraints on an instance by adding validation keywords to the schema. For instance, the "type" keyword can be used to restrict an instance to an object, array, string, number, boolean, or null:
{"type": "string"}
JSON Schema is hypermedia ready, and ideal for annotating your existing JSON-based HTTP API. JSON Schema documents are identified by URIs, which can be used in HTTP Link headers, and inside JSON Schema documents to allow recursive definitions.
Interested? Check out:
Questions? Feeling helpful? Get involved on:


Awesome application, its a must use.
I always hated going in line and waiting for a long time, this site saves me.
11/10
If you ever want to buy for your family after work, i can just order and pick it up later.
Super epic awesome yeeeeh!!


This section contains information for developers. It contains the following parts: one about customization, accessing runtime information, and one about how the source code for OIOSAML.java itself is structured.
Pages protected by SPFilter can access information about the authenticated user and the associated SAML assertion in a number of ways. In all cases, the SAML information is contained in a dk.itst.oiosaml.sp.UserAssertion object. Generally, only types from dk.itst.oiosaml.sp should be used from the application itself. Using types outside this package (including subpackages) is not supported or recommended. Instances of UserAssertion can be retrieved using these methods:
If IsPassive is set (using a property in oiosaml-sp.properties), the UserAssertion will not be valid. This can be checked with assertion.isAuthenticated(). If this method returns false, the user has not been authenticated, and should be treated as an anonymous user. To force a login, redirect the user to saml/login.
When developing a new application, it might be an issue to get a connection to a real IdP, and it might also disturb any automated integration tests. To overcome this, the filter has a special developer mode where it will not issue any redirects. Instead, it will create a dummy-assertion with configurable user and attributes.
To enable developer mode, simply set oiosaml-sp.develmode=true in oiosaml-sp.properties. It is not necessary to go through the configuration process when using this mode, so simply create the file and set the property.
For the developer mode to work, it is necessary to configure one or more users. Do this by setting oiosaml-sp.develmode.users to a comma-separated list of usernames. If only one is specified, this user will be selected automatically, otherwise a simple page will be shown where the user can be chosen.
Attributes can be defined for each user by setting oiosaml-sp.develmode.<username>.<attributename>=attributevalue.
Remember that if attribute names contain ;, it must be escaped using \.
Warning: When developer mode is enabled, no checks for valid assertions are made whatsoever!
Some times it is desirable to force a user to login again even if the user already had a valid authentication session. This can be accomplished by adding the query string parameter "forceAuthn=True" to the query string when requesting a page.
Attribute Query must be performed programatically. How to use Attribute Query is described in in the Attribute Query guide.
A number parts of OIOSAML.java can be directly: the the page used for sending POST requests when authenticating a user, the error page, and other advanced parts. In the demo, the post page is called postlogin.jsp, and contains a simple POST form.
The default page does not submit the form automatically using Javascript, it just builds a basic form which the user must submit. A new page can use the following request attributes to build the form (using ServletRequest.getAttribute()):
All of the values are correctly encoded, so they should be inserted into the form without further processing.
The customized page must be accessible as a servlet in the local web application. The path to the servlet must be configured in oiosaml-sp.properties (see the configuration section for more information about configuring OIOSAML.java) using the property POSTDispatchPath.
The error page is used whenever SAML processing fails. Like the login page, it is a servlet, which can be configured using a property. The page receives two objects in the request:
By default, the error page is rendered from an internal template.
When assertions are received, they are automatically validated according to the OIOSAML specification. The validation code can be controlled by implementing the dk.itst.oiosaml.sp.model.validation.AssertionValidator interface and injecting the class into the system using a configuration property.
If the user does not have an active session (due to for example timeout) and makes a POST request to a protected page, the POST request will normally be lost after the SSO process has completed. However, OIOSAML.java captures information about the last request made and replays it after the user had been authenticated. For GET requests, this results in a 302 redirect. For POST requests, a HTML page is displayed with a form containing the original form data.
By default, the form is a very simple page which displays all form fields and asks the user to either submit the request or cancel it. However, it is possible to customize the page. The mechanism is the same as when customizing the error page. Set the property called oiosaml-sp.repost to point to a local servlet path. This servlet must then display a form for reposting the request. The servlet received two attributes in the request: "request" and "home". The request attribute contains a dk.itst.oiosaml.sp.service.session.Request object with all the information about the original request (all parameter names and values have been html encoded). The home attribute contains the address for the default home page, in case the user wants to cancel the request.
See the clustering guide.
It is possible to receive a notification when a user has been authenticated by the SAML filter. To do this, implement the interface dk.itst.oiosaml.sp.AuthenticationHandler. This interface has one method, userAuthenticated, which is called when an assertion has been validated without errors.
Authentication handlers can be used to do further authentication or lookups, which should not be performed on every request.
The userAuthenticated method returns either true or false. If false is returned, processing is aborted, and the user will not be authenticated by the filter, which means that no objects are added to the session.
See the separate section on logging.
The source code consists of an Eclipse project with Java source code, unit tests, documentation, jar file dependencies, the demo files, and build files. Gant is used for building the project, and the target 'build_everything' will perform a full build. Gant will need to be installed in order to build the project
Dependencies are managed through Ivy. This means that dependencies are described in ivy.xml and downloaded automatically when the project is built.
No code generation is used, so the Eclipse project can be imported to Eclipse without any changes, and should be able to compile and run.
Unit tests are located in test/ and are baed on Junit4. The tests can be run with either ant using the target 'test' or from Eclipse. To run the tests from Eclipse, simply right-click on the test folder and select Run As -> JUnit Test.
Packages in use:
Configuration is done through Apache commons-configuration. The main config file is src/config.xml, which loads two config files: src/oiosaml-common.properties and ${oiosaml-j.home}/oiosaml-sp.properties. The common properties file contain properties which have default values, and which do not normally need to be changed. These properties can be overwritten in oiosaml-sp.properties.
It is possible to access configuration through dk.itst.oiosaml.configuration.BRSConfiguration.getSystemConfiguration().
Only one servlet is used in OIOSAML.java, dk.itst.oiosaml.sp.service.DispatcherServlet. This servlet dispatches to a number of SAMLHandlers which act as protocol endpoints. DispatcherServlet has a static configuration of which urls are mapped to which handlers.
Resources can be protected with a filter: dk.itst.oiosaml.sp.service.SPFilter. This filter checks if requests have a valid session. If so, a UserAssertion is placed in UserAssertionHolder, which is a ThreadLocal. If the request does not contain an authenticated session, the filter delegates to a BindingHandler, which either issues a HTTP Redirect or displays a POST form, depending on the SAML binding in use. The BindingHandlers are responsible for issuing AuthnRequests.
Responses to AuthnRequests are received by SAMLAssertionConsumer, which validates the Response and registers the assertion in the user's session.
In some scenarios, it might be preferable to run without the SPFilter, but instead handle user checking manually. In that case, the logic from SPFilter must be duplicated. This is quite simple: SPFilter handles three tasks:
If SPFilter is disabled, it is also necessary to start cleanup tasks manually. The tasks in question are the CRLChecker and LoggedInHandler#scheduleCleanupTasks().


ARE SO SPECIAL ARE OUR AREAS OF ACTIVITY
It is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout. The point of using Lorem Ipsum is that it has a more-or-less normal distribution of letters, as opposed to using ‘Content here, content here’, making it look like readable English.
→It is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout. The point of using Lorem Ipsum is that it has a more-or-less normal distribution of letters, as opposed to using ‘Content here, content here’, making it look like readable English.
→It is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout. The point of using Lorem Ipsum is that it has a more-or-less normal distribution of letters, as opposed to using ‘Content here, content here’, making it look like readable English.
→It is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout. The point of using Lorem Ipsum is that it has a more-or-less normal distribution of letters, as opposed to using ‘Content here, content here’, making it look like readable English.
→


To have a project revised or added to this Atlas, learn more about NEMO, or ask questions about this site, please find and contact your local NEMO program here.
Or, contact the National NEMO Network coordinator at david.dickson@uconn.edu.


@import views.html.personal.personal @* * Call the `main` template with two arguments. The first * argument is a `String` with the title of the page, the second * argument is an `Html` object containing the body of the page. *@ @personal{
With supporting text below as a natural lead-in to additional content.
Go somewhere


“I've spent so much time Googling fun things to do in London, so I'm very happy to have found TailorMade. A TailorMade day in London is the perfect day for me! ”
Tina Gogna, Evening Standard“What would I do without the TailorMade girls?! They are the first place I turn to find the coolest things to do in London. ”
Joe Wu, Time Out London“New to London and don't know where to start? Contact TailorMade. Highly recommended! ”
The Londonist


28 April 1999
Disease Outbreak Reported
The outbreak of meningococcal meningitis that started in Northern Darfur State in early December 1998 has spread to 18 out of 26 states. From the beginning of the epidemic up to 22 April more than 16,000 cases, of which nearly 1,000 died, have been notified. The epidemic is expected to last until the end of June-July, depending on the geographical location of the states affected.
Since the start of the epidemic 7,6 million people have been vaccinated. The vaccination campaigns, as well as other epidemic control measures are being implemented through a national task force chaired by the Federal Ministry of Health. This task force includes the members of the International Coordinating Group on Vaccine Provision for Epidemic Meningitis Control (ICG), namely the IFRC, MSF, UNICEF and WHO.
Current work includes strengthening of the surveillance system and training for health care and laboratory workers in order to improve the detection and management of cases. Health education messages have also been widely distributed.
The task force estimated that a further 4,5 million people need to be vaccinated during the next three weeks and stressed the need for availability of medicines for treatment of the patients at peripheral health centres. The ICG is requesting an additional US$ 2.1 million from the international community with a view to meeting these needs immediately.
For further details please contact IFRC (Dr. Sandblad, phone: 41 22 730 44 07, e-mail: [email protected]), MSF (Dr. Varaine, phone: 33 1 40 21 29 35, e-mail: [email protected]), UNICEF (Dr. S. Goings, phone: 234 1 269 02 76(280), e-mail: [email protected]), WHO (Dr. Santamaria, phone: 41 22 7912725, e-mail:. [email protected])


Effect with probability
Through this effect we can choose the execution of two effects depending on a probability rate, hundred-base. Therefore, we can define random behaviours on the adventures.
Create an effect with probability:
- Select the effect: Select the effect on the creation effects panel. Press OK.
- Creation effect panel: afterwards an edition panel will appear: In the first place we must choose the probability to execute the first effect (hundred-base). Afterwards we choose the two related effects.


array imap_get_quotaroot ( resource $imap_stream , string $quota_root )
Retrieve the quota settings per user. The limit value represents the total amount of space allowed for this user's total mailbox usage. The usage value represents the user's current total mailbox capacity.
Returns an array of integer values pertaining to the specified user mailbox. All values contain a key based upon the resource name, and a corresponding array with the usage and limit values within. This function will return FALSE in the case of call failure, and an array of information about the connection upon an un-parsable response from the server.


Carnell-Rettgers Family History
Spanish American War Veterans
Frederick H Rettgers
(
fold3
)
1873 - 1944
Company A,
4th Regiment, Pennsylvania Volunteers
Also
(
Roster
- See Richards, Fred)
Entered Service: 9 May 1898
Honorable Discharge: 16 Nov 1898
Pvt


Basic
Locked Title
Offsets
Basic Usage
Video will always fill all possible space within parent div. No cropping will ever occur.


Temperature dependent evolution of lattice parameters, measured on a single‐crystal (top; standard derivations are smaller than the symbols) and DSC (bottom) measurement of K 2[Fe 2O 3(OH) 2]. The absolute value of the enthalpy is nearly the same for both transitions (Δ H≈8.7 J/g).


Binary words
Define a type representing fixed-length sequences of binary values
(binary_word: nat->Set) and define the concatenation function for
this type.
Remark
Try first do do this exercise without using Coq's library Vectors, then compare your solution with the facilities provided by this library.
Solution
Look at this file


--- layout: rustwasm title: wasm_bindgen::JsValue description: wasm_bindgen::JsValue keyword: wasm_bindgen::JsValue, wasm_bindgen JsValue ---
A representation of an object owned by JavaScript generated by wasm-bindgen.
Cargo.toml
[package]
name = "web_sys_console"
version = "0.1.0"
authors = ["www.webassemblyman.com"]
edition = "2019"
[lib]
crate-type = ["cdylib"]
[dependencies]
wasm-bindgen = "0.2.50"


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OrderedInserter
An OrderedInserter is a mechanism for efficiently populating a RangeRunStorage. Values and runs are pushed into it in order, and when the OrderedInserter is committed, the data is written into the underlying RangeRunStorage.
value_type
RangeRunStorage<S>::value_type
The value type of the underlying RangeRunStorage.
run_type
RangeRunStorage<S>::run_type
The run type of the underlying RangeRunStorage.
| Name | Expression | Type | Semantics |
|---|---|---|---|
SetAt |
boost::range_run_storage::set_at(o, r, v) |
void |
Adds a run r with value v. This operation is amortized O(1). The offset of the run r must be greater than or equal to the end-offset of any run added previously. |
Commit |
boost::range_run_storage::commit(o) |
void |
Writes all the runs and values into the underlying series. The complexity is O(N) in the worst case. |
| Copyright © 2006 Eric Niebler |