Class yii\elasticsearch\Query
| Inheritance | yii\elasticsearch\Query » yii\base\Component » yii\base\BaseObject |
|---|---|
| Implements | yii\base\Configurable, yii\db\QueryInterface |
| Uses Traits | yii\db\QueryTrait |
| Subclasses | yii\elasticsearch\ActiveQuery |
| Available since version | 2.0 |
| Source Code | https://github.com/yiisoft/yii2-elasticsearch/blob/master/Query.php |
Query represents a query to the search API of elasticsearch.
Query provides a set of methods to facilitate the specification of different parameters of the query. These methods can be chained together.
By calling createCommand(), we can get a yii\elasticsearch\Command instance which can be further used to perform/execute the DB query against a database.
For example,
$query = new Query;
$query->fields('id, name')
->from('myindex', 'users')
->limit(10);
// build and execute the query
$command = $query->createCommand();
$rows = $command->search(); // this way you get the raw output of elasticsearch.
You would normally call $query->search()
instead of creating a command as this method
adds the indexBy()
feature and also removes some inconsistencies from the response.
Query also provides some methods to easier get some parts of the result only:
- one(): returns a single record populated with the first row of data.
- all(): returns all records based on the query results.
- count(): returns the number of records.
- scalar(): returns the value of the first column in the first row of the query result.
- column(): returns the value of the first column in the query result.
- exists(): returns a value indicating whether the query result has data or not.
NOTE: elasticsearch limits the number of records returned to 10 records by default. If you expect to get more records you should specify limit explicitly.
Public Properties
| Property | Type | Description | Defined By |
|---|---|---|---|
| $aggregations | array | List of aggregations to add to this query. | yii\elasticsearch\Query |
| $behaviors | yii\base\Behavior[] | List of behaviors attached to this component | yii\base\Component |
| $emulateExecution | boolean | Whether to emulate the actual query execution, returning empty or false results. | yii\db\QueryTrait |
| $explain | boolean | Enables explanation for each hit on how its score was computed. | yii\elasticsearch\Query |
| $fields | array | The fields being retrieved from the documents. | yii\elasticsearch\Query |
| $filter | array|string | The filter part of this search query. | yii\elasticsearch\Query |
| $highlight | array | The highlight part of this search query. | yii\elasticsearch\Query |
| $index | string|array | The index to retrieve data from. | yii\elasticsearch\Query |
| $indexBy | string|callable | The name of the column by which the query results should be indexed by. | yii\db\QueryTrait |
| $limit | integer|yii\db\ExpressionInterface | Maximum number of records to be returned. | yii\db\QueryTrait |
| $minScore | float | Exclude documents which have a _score less than the minimum specified in min_score | yii\elasticsearch\Query |
| $offset | integer|yii\db\ExpressionInterface | Zero-based offset from where the records are to be returned. | yii\db\QueryTrait |
| $options | array | List of options that will passed to commands created by this query. | yii\elasticsearch\Query |
| $orderBy | array | How to sort the query results. | yii\db\QueryTrait |
| $postFilter | string|array | The post_filter part of the search query for differentially filter search results and aggregations. |
yii\elasticsearch\Query |
| $query | array|string | The query part of this search query. | yii\elasticsearch\Query |
| $source | array | This option controls how the _source field is returned from the documents. |
yii\elasticsearch\Query |
| $stats | array | The 'stats' part of the query. | yii\elasticsearch\Query |
| $suggest | array | List of suggesters to add to this query. | yii\elasticsearch\Query |
| $timeout | integer | A search timeout, bounding the search request to be executed within the specified time value and bail with the hits accumulated up to that point when expired. | yii\elasticsearch\Query |
| $type | string|array | The type to retrieve data from. | yii\elasticsearch\Query |
| $where | string|array|yii\db\ExpressionInterface | Query condition. | yii\db\QueryTrait |
Public Methods
| Method | Description | Defined By |
|---|---|---|
| __call() | Calls the named method which is not a class method. | yii\base\Component |
| __clone() | This method is called after the object is created by cloning an existing one. | yii\base\Component |
| __construct() | Constructor. | yii\base\BaseObject |
| __get() | Returns the value of a component property. | yii\base\Component |
| __isset() | Checks if a property is set, i.e. defined and not null. | yii\base\Component |
| __set() | Sets the value of a component property. | yii\base\Component |
| __unset() | Sets a component property to be null. | yii\base\Component |
| addAgg() | yii\elasticsearch\Query | |
| addAggregate() | Adds an aggregation to this query. Supports nested aggregations. | yii\elasticsearch\Query |
| addAggregation() | yii\elasticsearch\Query | |
| addOptions() | Adds more options, overwriting existing options. | yii\elasticsearch\Query |
| addOrderBy() | Adds additional ORDER BY columns to the query. | yii\db\QueryTrait |
| addSuggester() | Adds a suggester to this query. | yii\elasticsearch\Query |
| all() | Executes the query and returns all results as an array. | yii\elasticsearch\Query |
| andFilterWhere() | Adds an additional WHERE condition to the existing one but ignores empty operands. | yii\db\QueryTrait |
| andWhere() | Adds an additional WHERE condition to the existing one. | yii\db\QueryTrait |
| attachBehavior() | Attaches a behavior to this component. | yii\base\Component |
| attachBehaviors() | Attaches a list of behaviors to the component. | yii\base\Component |
| batch() | Starts a batch query. | yii\elasticsearch\Query |
| behaviors() | Returns a list of behaviors that this component should behave as. | yii\base\Component |
| canGetProperty() | Returns a value indicating whether a property can be read. | yii\base\Component |
| canSetProperty() | Returns a value indicating whether a property can be set. | yii\base\Component |
| className() | Returns the fully qualified name of this class. | yii\base\BaseObject |
| column() | Executes the query and returns the first column of the result. | yii\elasticsearch\Query |
| count() | Returns the number of records. | yii\elasticsearch\Query |
| createCommand() | Creates a DB command that can be used to execute this query. | yii\elasticsearch\Query |
| delete() | Executes the query and deletes all matching documents. | yii\elasticsearch\Query |
| detachBehavior() | Detaches a behavior from the component. | yii\base\Component |
| detachBehaviors() | Detaches all behaviors from the component. | yii\base\Component |
| each() | Starts a batch query and retrieves data row by row. | yii\elasticsearch\Query |
| emulateExecution() | Sets whether to emulate query execution, preventing any interaction with data storage. | yii\db\QueryTrait |
| ensureBehaviors() | Makes sure that the behaviors declared in behaviors() are attached to this component. | yii\base\Component |
| exists() | Returns a value indicating whether the query result contains any row of data. | yii\elasticsearch\Query |
| explain() | Explain for how the score of each document was computer | yii\elasticsearch\Query |
| fields() | Sets the fields to retrieve from the documents. | yii\elasticsearch\Query |
| filter() | Sets the filter part of this search query. | yii\elasticsearch\Query |
| filterWhere() | Sets the WHERE part of the query but ignores empty operands. | yii\db\QueryTrait |
| from() | Sets the index and type to retrieve documents from. | yii\elasticsearch\Query |
| getBehavior() | Returns the named behavior object. | yii\base\Component |
| getBehaviors() | Returns all behaviors attached to this component. | yii\base\Component |
| hasEventHandlers() | Returns a value indicating whether there is any handler attached to the named event. | yii\base\Component |
| hasMethod() | Returns a value indicating whether a method is defined. | yii\base\Component |
| hasProperty() | Returns a value indicating whether a property is defined for this component. | yii\base\Component |
| highlight() | Sets a highlight parameters to retrieve from the documents. | yii\elasticsearch\Query |
| indexBy() | Sets the indexBy() property. | yii\db\QueryTrait |
| init() | Initializes the object. | yii\elasticsearch\Query |
| limit() | Sets the LIMIT part of the query. | yii\db\QueryTrait |
| minScore() | yii\elasticsearch\Query | |
| off() | Detaches an existing event handler from this component. | yii\base\Component |
| offset() | Sets the OFFSET part of the query. | yii\db\QueryTrait |
| on() | Attaches an event handler to an event. | yii\base\Component |
| one() | Executes the query and returns a single row of result. | yii\elasticsearch\Query |
| options() | Sets the options to be passed to the command created by this query. | yii\elasticsearch\Query |
| orFilterWhere() | Adds an additional WHERE condition to the existing one but ignores empty operands. | yii\db\QueryTrait |
| orWhere() | Adds an additional WHERE condition to the existing one. | yii\db\QueryTrait |
| orderBy() | Sets the ORDER BY part of the query. | yii\db\QueryTrait |
| populate() | Converts the raw query results into the format as specified by this query. | yii\elasticsearch\Query |
| postFilter() | Set the post_filter part of the search query. |
yii\elasticsearch\Query |
| query() | Sets the query part of this search query. | yii\elasticsearch\Query |
| scalar() | Returns the query result as a scalar value. | yii\elasticsearch\Query |
| search() | Executes the query and returns the complete search result including e.g. hits, facets, totalCount. | yii\elasticsearch\Query |
| source() | Sets the source filtering, specifying how the _source field of the document should be returned. |
yii\elasticsearch\Query |
| stats() | Adds a 'stats' part to the query. | yii\elasticsearch\Query |
| timeout() | Sets the search timeout. | yii\elasticsearch\Query |
| trigger() | Triggers an event. | yii\base\Component |
| where() | Sets the WHERE part of the query. | yii\db\QueryTrait |
Protected Methods
| Method | Description | Defined By |
|---|---|---|
| filterCondition() | Removes empty operands from the given query condition. | yii\db\QueryTrait |
| isEmpty() | Returns a value indicating whether the give value is "empty". | yii\db\QueryTrait |
| normalizeOrderBy() | Normalizes format of ORDER BY data. | yii\db\QueryTrait |
Property Details
List of aggregations to add to this query.
See also http://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations.html.
Enables explanation for each hit on how its score was computed.
See also https://www.elastic.co/guide/en/elasticsearch/reference/current/search-request-explain.html.
The fields being retrieved from the documents. For example, ['id', 'name']
.
If not set, this option will not be applied to the query and no fields will be returned.
In this case the _source
field will be returned by default which can be configured using source().
Setting this to an empty array will result in no fields being retrieved, which means that only the primaryKey
of a record will be available in the result.
For each field you may also add an array representing a script field. Example:
$query->fields = [
'id',
'name',
'value_times_two' => [
'script' => "doc['my_field_name'].value * 2",
],
'value_times_factor' => [
'script' => "doc['my_field_name'].value * factor",
'params' => [
'factor' => 2.0
],
],
]
Note: Field values are always returned as arrays even if they only have one value.
See also:
The filter part of this search query. This is an array or json string that follows the format of the elasticsearch Query DSL.
The highlight part of this search query. This is an array that allows to highlight search results on one or more fields.
See also http://www.elastic.co/guide/en/elasticsearch/reference/current/search-request-highlighting.html.
The index to retrieve data from. This can be a string representing a single index or a an array of multiple indexes. If this is not set, indexes are being queried.
See also from().
Exclude documents which have a _score less than the minimum specified in min_score
See also http://www.elastic.co/guide/en/elasticsearch/reference/current/search-request-min-score.html.
List of options that will passed to commands created by this query.
See also yii\elasticsearch\Command::$options.
The post_filter
part of the search query for differentially filter search results and aggregations.
See also https://www.elastic.co/guide/en/elasticsearch/guide/current/_post_filter.html.
The query part of this search query. This is an array or json string that follows the format of the elasticsearch Query DSL.
This option controls how the _source
field is returned from the documents. For example, ['id', 'name']
means that only the id
and name
field should be returned from _source
.
If not set, it means retrieving the full _source
field unless fields() are specified.
Setting this option to false
will disable return of the _source
field, this means that only the primaryKey
of a record will be available in the result.
See also:
The 'stats' part of the query. An array of groups to maintain a statistics aggregation for.
See also http://www.elastic.co/guide/en/elasticsearch/reference/current/search.html#stats-groups.
List of suggesters to add to this query.
See also http://www.elastic.co/guide/en/elasticsearch/reference/current/search-suggesters.html.
A search timeout, bounding the search request to be executed within the specified time value and bail with the hits accumulated up to that point when expired. Defaults to no timeout.
See also:
The type to retrieve data from. This can be a string representing a single type or a an array of multiple types. If this is not set, all types are being queried.
See also from().
Method Details
| public $this addAgg ( $name, $type, $options ) | ||
| $name | string | The name of the aggregation |
| $type | string | The aggregation type. e.g. |
| $options | string|array | The configuration options for this aggregation. Can be an array or a json string. |
| return | $this | The query object itself |
|---|
Adds an aggregation to this query. Supports nested aggregations.
See also https://www.elastic.co/guide/en/elasticsearch/reference/2.3/search-aggregations.html.
| public $this addAggregate ( $name, $options ) | ||
| $name | string | The name of the aggregation |
| $options | string|array | The configuration options for this aggregation. Can be an array or a json string. |
| return | $this | The query object itself |
|---|
| public $this addAggregation ( $name, $type, $options ) | ||
| $name | string | The name of the aggregation |
| $type | string | The aggregation type. e.g. |
| $options | string|array | The configuration options for this aggregation. Can be an array or a json string. |
| return | $this | The query object itself |
|---|
Adds more options, overwriting existing options.
See also options().
| public $this addOptions ( $options ) | ||
| $options | array | The options to be added. |
| return | $this | The query object itself |
|---|---|---|
| throws | yii\base\InvalidParamException | if $options is not an array |
Adds a suggester to this query.
See also http://www.elastic.co/guide/en/elasticsearch/reference/current/search-suggesters.html.
| public $this addSuggester ( $name, $definition ) | ||
| $name | string | The name of the suggester |
| $definition | string|array | The configuration options for this suggester. Can be an array or a json string. |
| return | $this | The query object itself |
|---|
Executes the query and returns all results as an array.
| public array all ( $db = null ) | ||
| $db | yii\elasticsearch\Connection | The database connection used to execute the query.
If this parameter is not given, the |
| return | array | The query results. If the query results in nothing, an empty array will be returned. |
|---|
Starts a batch query.
A batch query supports fetching data in batches, which can keep the memory usage under a limit. This method will return a yii\elasticsearch\BatchQueryResult object which implements the Iterator interface and can be traversed to retrieve the data in batches.
For example,
$query = (new Query)->from('user');
foreach ($query->batch() as $rows) {
// $rows is an array of 10 or fewer rows from user table
}
Batch size is determined by the limit
setting (note that in scan mode batch limit is per shard).
| public yii\elasticsearch\BatchQueryResult batch ( $scrollWindow = '1m', $db = null ) | ||
| $scrollWindow | string | How long Elasticsearch should keep the search context alive, in time units |
| $db | yii\elasticsearch\Connection | The database connection. If not set, the |
| return | yii\elasticsearch\BatchQueryResult | The batch query result. It implements the Iterator interface and can be traversed to retrieve the data in batches. |
|---|
Executes the query and returns the first column of the result.
| public array column ( $field, $db = null ) | ||
| $field | string | The field to query over |
| $db | yii\elasticsearch\Connection | The database connection used to execute the query.
If this parameter is not given, the |
| return | array | The first column of the query result. An empty array is returned if the query results in nothing. |
|---|
Returns the number of records.
| public integer count ( $q = '*', $db = null ) | ||
| $q | string | The COUNT expression. This parameter is ignored by this implementation. |
| $db | yii\elasticsearch\Connection | The database connection used to execute the query.
If this parameter is not given, the |
| return | integer | Number of records |
|---|
Creates a DB command that can be used to execute this query.
| public yii\elasticsearch\Command createCommand ( $db = null ) | ||
| $db | yii\elasticsearch\Connection | The database connection used to execute the query.
If this parameter is not given, the |
| return | yii\elasticsearch\Command | The created DB command instance. |
|---|
Executes the query and deletes all matching documents.
Everything except query and filter will be ignored.
| public array delete ( $db = null, $options = [] ) | ||
| $db | yii\elasticsearch\Connection | The database connection used to execute the query.
If this parameter is not given, the |
| $options | array | The options given with this query. |
| return | array | The query results. |
|---|
Starts a batch query and retrieves data row by row.
This method is similar to batch() except that in each iteration of the result, only one row of data is returned. For example,
$query = (new Query)->from('user');
foreach ($query->each() as $row) {
}
| public yii\elasticsearch\BatchQueryResult each ( $scrollWindow = '1m', $db = null ) | ||
| $scrollWindow | string | How long Elasticsearch should keep the search context alive, in time units |
| $db | yii\elasticsearch\Connection | The database connection. If not set, the |
| return | yii\elasticsearch\BatchQueryResult | The batch query result. It implements the Iterator interface and can be traversed to retrieve the data in batches. |
|---|
Returns a value indicating whether the query result contains any row of data.
| public boolean exists ( $db = null ) | ||
| $db | yii\elasticsearch\Connection | The database connection used to execute the query.
If this parameter is not given, the |
| return | boolean | Whether the query result contains any row of data. |
|---|
Explain for how the score of each document was computer
See also $explain.
| public $this explain ( $explain ) | ||
| $explain |
Sets the fields to retrieve from the documents.
See also http://www.elastic.co/guide/en/elasticsearch/reference/current/search-request-fields.html.
| public $this fields ( $fields ) | ||
| $fields | array | The fields to be selected. |
| return | $this | The query object itself |
|---|
Sets the filter part of this search query.
| public $this filter ( $filter ) | ||
| $filter | string | |
| return | $this | The query object itself |
|---|
Sets the index and type to retrieve documents from.
| public $this from ( $index, $type = null ) | ||
| $index | string|array | The index to retrieve data from. This can be a string representing a single index
or a an array of multiple indexes. If this is |
| $type | string|array | The type to retrieve data from. This can be a string representing a single type
or a an array of multiple types. If this is |
| return | $this | The query object itself |
|---|
Sets a highlight parameters to retrieve from the documents.
See also http://www.elastic.co/guide/en/elasticsearch/reference/current/search-request-highlighting.html.
| public $this highlight ( $highlight ) | ||
| $highlight | array | Array of parameters to highlight results. |
| return | $this | The query object itself |
|---|
Initializes the object.
This method is invoked at the end of the constructor after the object is initialized with the given configuration.
| public void init ( ) |
See also http://www.elastic.co/guide/en/elasticsearch/reference/current/search-request-min-score.html.
| public static minScore ( $minScore ) | ||
| $minScore | float | Exclude documents which have a |
| return | static | The query object itself |
|---|
Executes the query and returns a single row of result.
| public array|boolean one ( $db = null ) | ||
| $db | yii\elasticsearch\Connection | The database connection used to execute the query.
If this parameter is not given, the |
| return | array|boolean | The first row (in terms of an array) of the query result. False is returned if the query results in nothing. |
|---|
Sets the options to be passed to the command created by this query.
See also yii\elasticsearch\Command::$options.
| public $this options ( $options ) | ||
| $options | array | The options to be set. |
| return | $this | The query object itself |
|---|---|---|
| throws | yii\base\InvalidParamException | if $options is not an array |
Converts the raw query results into the format as specified by this query.
This method is internally used to convert the data fetched from database into the format as required by this query.
| public array populate ( $rows ) | ||
| $rows | array | The raw query result from database |
| return | array | The converted query result |
|---|
Set the post_filter
part of the search query.
See also $postFilter.
| public $this postFilter ( $filter ) | ||
| $filter | string|array | |
| return | $this | The query object itself |
|---|
Sets the query part of this search query.
| public $this query ( $query ) | ||
| $query | string|array | |
| return | $this | The query object itself |
|---|
Returns the query result as a scalar value.
The value returned will be the specified field in the first document of the query results.
| public string scalar ( $field, $db = null ) | ||
| $field | string | Name of the attribute to select |
| $db | yii\elasticsearch\Connection | The database connection used to execute the query.
If this parameter is not given, the |
| return | string | The value of the specified attribute in the first record of the query result. Null is returned if the query result is empty or the field does not exist. |
|---|
Executes the query and returns the complete search result including e.g. hits, facets, totalCount.
| public array search ( $db = null, $options = [] ) | ||
| $db | yii\elasticsearch\Connection | The database connection used to execute the query.
If this parameter is not given, the |
| $options | array | The options given with this query. Possible options are: |
| return | array | The query results. |
|---|
Sets the source filtering, specifying how the _source
field of the document should be returned.
See also http://www.elastic.co/guide/en/elasticsearch/reference/current/search-request-source-filtering.html.
| public $this source ( $source ) | ||
| $source | array | The source patterns to be selected. |
| return | $this | The query object itself |
|---|
Adds a 'stats' part to the query.
See also http://www.elastic.co/guide/en/elasticsearch/reference/current/search.html#stats-groups.
| public $this stats ( $groups ) | ||
| $groups | array | An array of groups to maintain a statistics aggregation for. |
| return | $this | The query object itself |
|---|
Sets the search timeout.
| public $this timeout ( $timeout ) | ||
| $timeout | integer | A search timeout, bounding the search request to be executed within the specified time value and bail with the hits accumulated up to that point when expired. Defaults to no timeout. |
| return | $this | The query object itself |
|---|


This package contains classes used to store JPA mapping information about mapped classes and properties.


The art of research
Noam Shomron includes antiques and his own paintings of wildlife in the decor for his genomics lab.
by Virginia GewinIn my genomics lab, I’ve posted nine life-sized paintings that I did of zebras, tigers and penguins, among other images. I’ve also sprinkled around some pieces of antique scientific equipment, such as a Soviet Union-era manual centrifuge and salvaged microscopes from a bygone time.
I specifically and intentionally selected every detail of the lab’s decor. I chose animals as the theme because they provide a universal connection. One day a person can feel like a tiger, and another day more like a puppy dog. And, when someone is repeating experiments over and over, I think they can identify with a parrot. I drew a penguin when someone had to work in the cold room all day to keep proteins stable.
I have more paintings than wall space, so sometimes I switch some out to see who is paying attention. I hope they help to create a welcoming environment for lab members who are largely local and from diverse religious backgrounds, who include Jews, Muslims and Christians. And international colleagues also come for short stays.
I study the roles of RNA and DNA in human diseases, including in mental disorders and breast cancer. But the antique equipment reminds us that we have much to learn from yesterday’s scientists. There is such a rush to publish new findings, but if people conduct a detailed literature search, they are likely to find that a similar experiment has already been run. Life is so fast these days, I want my students to stop and think about the proper way to conduct science rather than simply try to speed through experiments as fast as they can.
I’ve worked in labs that had a cold, sterile appearance. I didn’t want that for mine. It must be a place of comfort — physically as well as mentally. I want my students to love entering a space in which they are motivated to do their best work and where they feel supported. My door is always open. I bring cookies or chocolate into a corner of my office, so that people will stop by and I can ask them how they are.
Nature 575, 408 (2019)
doi: 10.1038/d41586-019-03460-0


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mlpack
1.0.12
|
A Gaussian Mixture Model (GMM). More...
Public Member Functions | |
| GMM () | |
| Create an empty Gaussian Mixture Model, with zero gaussians. More... | |
| GMM (const size_t gaussians, const size_t dimensionality) | |
| Create a GMM with the given number of Gaussians, each of which have the specified dimensionality. More... | |
| GMM (const size_t gaussians, const size_t dimensionality, FittingType &fitter) | |
| Create a GMM with the given number of Gaussians, each of which have the specified dimensionality. More... | |
| GMM (const std::vector< arma::vec > &means, const std::vector< arma::mat > &covariances, const arma::vec &weights) | |
| Create a GMM with the given means, covariances, and weights. More... | |
| GMM (const std::vector< arma::vec > &means, const std::vector< arma::mat > &covariances, const arma::vec &weights, FittingType &fitter) | |
| Create a GMM with the given means, covariances, and weights, and use the given initialized FittingType class. More... | |
| template<typename OtherFittingType > | |
| GMM (const GMM< OtherFittingType > &other) | |
| Copy constructor for GMMs which use different fitting types. More... | |
| GMM (const GMM &other) | |
| Copy constructor for GMMs using the same fitting type. More... | |
| void | Classify (const arma::mat &observations, arma::Col< size_t > &labels) const |
| Classify the given observations as being from an individual component in this GMM. More... | |
| const std::vector< arma::mat > & | Covariances () const |
| Return a const reference to the vector of covariance matrices (sigma). More... | |
| std::vector< arma::mat > & | Covariances () |
| Return a reference to the vector of covariance matrices (sigma). More... | |
| size_t | Dimensionality () const |
| Return the dimensionality of the model. More... | |
| size_t & | Dimensionality () |
| Modify the dimensionality of the model. More... | |
| double | Estimate (const arma::mat &observations, const size_t trials=1, const bool useExistingModel=false) |
| Estimate the probability distribution directly from the given observations, using the given algorithm in the FittingType class to fit the data. More... | |
| double | Estimate (const arma::mat &observations, const arma::vec &probabilities, const size_t trials=1, const bool useExistingModel=false) |
| Estimate the probability distribution directly from the given observations, taking into account the probability of each observation actually being from this distribution, and using the given algorithm in the FittingType class to fit the data. More... | |
| const FittingType & | Fitter () const |
| Return a const reference to the fitting type. More... | |
| FittingType & | Fitter () |
| Return a reference to the fitting type. More... | |
| size_t | Gaussians () const |
| Return the number of gaussians in the model. More... | |
| size_t & | Gaussians () |
| Modify the number of gaussians in the model. More... | |
| void | Load (const std::string &filename) |
| Load a GMM from an XML file. More... | |
| const std::vector< arma::vec > & | Means () const |
| Return a const reference to the vector of means (mu). More... | |
| std::vector< arma::vec > & | Means () |
| Return a reference to the vector of means (mu). More... | |
| template<typename OtherFittingType > | |
| GMM & | operator= (const GMM< OtherFittingType > &other) |
| Copy operator for GMMs which use different fitting types. More... | |
| GMM & | operator= (const GMM &other) |
| Copy operator for GMMs which use the same fitting type. More... | |
| double | Probability (const arma::vec &observation) const |
| Return the probability that the given observation came from this distribution. More... | |
| double | Probability (const arma::vec &observation, const size_t component) const |
| Return the probability that the given observation came from the given Gaussian component in this distribution. More... | |
| arma::vec | Random () const |
| Return a randomly generated observation according to the probability distribution defined by this object. More... | |
| void | Save (const std::string &filename) const |
| Save a GMM to an XML file. More... | |
| std::string | ToString () const |
| Returns a string representation of this object. More... | |
| const arma::vec & | Weights () const |
| Return a const reference to the a priori weights of each Gaussian. More... | |
| arma::vec & | Weights () |
| Return a reference to the a priori weights of each Gaussian. More... | |
Private Member Functions | |
| double | LogLikelihood (const arma::mat &dataPoints, const std::vector< arma::vec > &means, const std::vector< arma::mat > &covars, const arma::vec &weights) const |
| This function computes the loglikelihood of the given model. More... | |
Private Attributes | |
| std::vector< arma::mat > | covariances |
| Vector of covariances; one for each Gaussian. More... | |
| size_t | dimensionality |
| The dimensionality of the model. More... | |
| FittingType & | fitter |
| Reference to the fitting object we should use. More... | |
| size_t | gaussians |
| The number of Gaussians in the model. More... | |
| FittingType | localFitter |
| Locally-stored fitting object; in case the user did not pass one. More... | |
| std::vector< arma::vec > | means |
| Vector of means; one for each Gaussian. More... | |
| arma::vec | weights |
| Vector of a priori weights for each Gaussian. More... | |
A Gaussian Mixture Model (GMM).
This class uses maximum likelihood loss functions to estimate the parameters of the GMM on a given dataset via the given fitting mechanism, defined by the FittingType template parameter. The GMM can be trained using normal data, or data with probabilities of being from this GMM (see GMM::Estimate() for more information).
The FittingType template class must provide a way for the GMM to train on data. It must provide the following two functions:
These functions should produce a trained GMM from the given observations and probabilities. These may modify the size of the model (by increasing the size of the mean and covariance vectors as well as the weight vectors), but the method should expect that these vectors are already set to the size of the GMM as specified in the constructor.
For a sample implementation, see the EMFit class; this class uses the EM algorithm to train a GMM, and is the default fitting type.
The GMM, once trained, can be used to generate random points from the distribution and estimate the probability of points being from the distribution. The parameters of the GMM can be obtained through the accessors and mutators.
Example use:
|
inline |
Create an empty Gaussian Mixture Model, with zero gaussians.
Definition at line 99 of file gmm.hpp.
References mlpack::Log::Debug.
| mlpack::gmm::GMM< FittingType >::GMM | ( | const size_t | gaussians, |
| const size_t | dimensionality | ||
| ) |
| mlpack::gmm::GMM< FittingType >::GMM | ( | const size_t | gaussians, |
| const size_t | dimensionality, | ||
| FittingType & | fitter | ||
| ) |
Create a GMM with the given number of Gaussians, each of which have the specified dimensionality.
Also, pass in an initialized FittingType class; this is useful in cases where the FittingType class needs to store some state.
| gaussians | Number of Gaussians in this GMM. |
| dimensionality | Dimensionality of each Gaussian. |
| fitter | Initialized fitting mechanism. |
|
inline |
|
inline |
Create a GMM with the given means, covariances, and weights, and use the given initialized FittingType class.
This is useful in cases where the FittingType class needs to store some state.
| means | Means of the model. |
| covariances | Covariances of the model. |
| weights | Weights of the model. |
| mlpack::gmm::GMM< FittingType >::GMM | ( | const GMM< OtherFittingType > & | other | ) |
Copy constructor for GMMs which use different fitting types.
| mlpack::gmm::GMM< FittingType >::GMM | ( | const GMM< FittingType > & | other | ) |
Copy constructor for GMMs using the same fitting type.
This also copies the fitter.
| void mlpack::gmm::GMM< FittingType >::Classify | ( | const arma::mat & | observations, |
| arma::Col< size_t > & | labels | ||
| ) | const |
Classify the given observations as being from an individual component in this GMM.
The resultant classifications are stored in the 'labels' object, and each label will be between 0 and (Gaussians() - 1). Supposing that a point was classified with label 2, and that our GMM object was called 'gmm', one could access the relevant Gaussian distribution as follows:
| observations | List of observations to classify. |
| labels | Object which will be filled with labels. |
|
inline |
Return a const reference to the vector of covariance matrices (sigma).
Definition at line 230 of file gmm.hpp.
References mlpack::gmm::GMM< FittingType >::covariances.
|
inline |
Return a reference to the vector of covariance matrices (sigma).
Definition at line 232 of file gmm.hpp.
References mlpack::gmm::GMM< FittingType >::covariances.
|
inline |
Return the dimensionality of the model.
Definition at line 219 of file gmm.hpp.
References mlpack::gmm::GMM< FittingType >::dimensionality.
|
inline |
Modify the dimensionality of the model.
Careful! You will have to update each mean and covariance matrix yourself.
Definition at line 222 of file gmm.hpp.
References mlpack::gmm::GMM< FittingType >::dimensionality.
| double mlpack::gmm::GMM< FittingType >::Estimate | ( | const arma::mat & | observations, |
| const size_t | trials = 1 , |
||
| const bool | useExistingModel = false |
||
| ) |
Estimate the probability distribution directly from the given observations, using the given algorithm in the FittingType class to fit the data.
The fitting will be performed 'trials' times; from these trials, the model with the greatest log-likelihood will be selected. By default, only one trial is performed. The log-likelihood of the best fitting is returned.
Optionally, the existing model can be used as an initial model for the estimation by setting 'useExistingModel' to true. If the fitting procedure is deterministic after the initial position is given, then 'trials' should be set to 1.
| FittingType | The type of fitting method which should be used (EMFit<> is suggested). |
| observations | Observations of the model. |
| trials | Number of trials to perform; the model in these trials with the greatest log-likelihood will be selected. |
| useExistingModel | If true, the existing model is used as an initial model for the estimation. |
| double mlpack::gmm::GMM< FittingType >::Estimate | ( | const arma::mat & | observations, |
| const arma::vec & | probabilities, | ||
| const size_t | trials = 1 , |
||
| const bool | useExistingModel = false |
||
| ) |
Estimate the probability distribution directly from the given observations, taking into account the probability of each observation actually being from this distribution, and using the given algorithm in the FittingType class to fit the data.
The fitting will be performed 'trials' times; from these trials, the model with the greatest log-likelihood will be selected. By default, only one trial is performed. The log-likelihood of the best fitting is returned.
Optionally, the existing model can be used as an initial model for the estimation by setting 'useExistingModel' to true. If the fitting procedure is deterministic after the initial position is given, then 'trials' should be set to 1.
| observations | Observations of the model. |
| probabilities | Probability of each observation being from this distribution. |
| trials | Number of trials to perform; the model in these trials with the greatest log-likelihood will be selected. |
| useExistingModel | If true, the existing model is used as an initial model for the estimation. |
|
inline |
Return a const reference to the fitting type.
Definition at line 240 of file gmm.hpp.
References mlpack::gmm::GMM< FittingType >::fitter.
|
inline |
Return a reference to the fitting type.
Definition at line 242 of file gmm.hpp.
References mlpack::gmm::GMM< FittingType >::fitter.
|
inline |
Return the number of gaussians in the model.
Definition at line 213 of file gmm.hpp.
References mlpack::gmm::GMM< FittingType >::gaussians.
|
inline |
Modify the number of gaussians in the model.
Careful! You will have to resize the means, covariances, and weights yourself.
Definition at line 216 of file gmm.hpp.
References mlpack::gmm::GMM< FittingType >::gaussians.
| void mlpack::gmm::GMM< FittingType >::Load | ( | const std::string & | filename | ) |
|
private |
This function computes the loglikelihood of the given model.
This function is used by GMM::Estimate().
| dataPoints | Observations to calculate the likelihood for. |
| means | Means of the given mixture model. |
| covars | Covariances of the given mixture model. |
| weights | Weights of the given mixture model. |
|
inline |
Return a const reference to the vector of means (mu).
Definition at line 225 of file gmm.hpp.
References mlpack::gmm::GMM< FittingType >::means.
|
inline |
Return a reference to the vector of means (mu).
Definition at line 227 of file gmm.hpp.
References mlpack::gmm::GMM< FittingType >::means.
| GMM& mlpack::gmm::GMM< FittingType >::operator= | ( | const GMM< OtherFittingType > & | other | ) |
Copy operator for GMMs which use different fitting types.
| GMM& mlpack::gmm::GMM< FittingType >::operator= | ( | const GMM< FittingType > & | other | ) |
Copy operator for GMMs which use the same fitting type.
This also copies the fitter.
| double mlpack::gmm::GMM< FittingType >::Probability | ( | const arma::vec & | observation | ) | const |
Return the probability that the given observation came from this distribution.
| observation | Observation to evaluate the probability of. |
| double mlpack::gmm::GMM< FittingType >::Probability | ( | const arma::vec & | observation, |
| const size_t | component | ||
| ) | const |
Return the probability that the given observation came from the given Gaussian component in this distribution.
| observation | Observation to evaluate the probability of. |
| component | Index of the component of the GMM to be considered. |
| arma::vec mlpack::gmm::GMM< FittingType >::Random | ( | ) | const |
Return a randomly generated observation according to the probability distribution defined by this object.
| void mlpack::gmm::GMM< FittingType >::Save | ( | const std::string & | filename | ) | const |
Save a GMM to an XML file.
| filename | Name of XML file to write to. |
| std::string mlpack::gmm::GMM< FittingType >::ToString | ( | ) | const |
Returns a string representation of this object.
|
inline |
Return a const reference to the a priori weights of each Gaussian.
Definition at line 235 of file gmm.hpp.
References mlpack::gmm::GMM< FittingType >::weights.
|
inline |
Return a reference to the a priori weights of each Gaussian.
Definition at line 237 of file gmm.hpp.
References mlpack::gmm::GMM< FittingType >::weights.
|
private |
Vector of covariances; one for each Gaussian.
Definition at line 91 of file gmm.hpp.
Referenced by mlpack::gmm::GMM< FittingType >::Covariances().
|
private |
The dimensionality of the model.
Definition at line 87 of file gmm.hpp.
Referenced by mlpack::gmm::GMM< FittingType >::Dimensionality().
|
private |
Reference to the fitting object we should use.
Definition at line 368 of file gmm.hpp.
Referenced by mlpack::gmm::GMM< FittingType >::Fitter().
|
private |
The number of Gaussians in the model.
Definition at line 85 of file gmm.hpp.
Referenced by mlpack::gmm::GMM< FittingType >::Gaussians().
|
private |
|
private |
Vector of means; one for each Gaussian.
Definition at line 89 of file gmm.hpp.
Referenced by mlpack::gmm::GMM< FittingType >::Means().
|
private |
Vector of a priori weights for each Gaussian.
Definition at line 93 of file gmm.hpp.
Referenced by mlpack::gmm::GMM< FittingType >::Weights().


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| DOSE: |
1 capsl |
oral |
2C-I |
(capsule) |
This story begins with numerous people, but only M, G & myself were taking 2C-I this night. I had gotten 3 capsules from J earlier in the week, and we had been anticipating this trip for a few days before we met up at around 4:30 on July 4th.
5:00PM - We were sitting around the garage, M was already pretty loaded on Southern Comfort, G was possibly stoned but I wasn't questioning, and I was sober, having just shown up after a dinner date. There were supposed to be fireworks in town at the Memorial Field, so we decided to take the 2C-I & then immediately travel the 10 minutes into town to avoid driving while tripping. [REGARDLESS, DO NOT DRIVE AFTER INGESTING ANYTHING THAT MAKES YOU TRIP.]
[Erowid Note: Driving while intoxicated or tripping is dangerous and irresponsible because it endangers other people. Don't do it!]
M & I took my car, and G took his truck, we parked on separate side streets and walked to meet each other, then walked to the field. On the way to the field, M claimed to already be tripping, stating repeatedly that he felt that he was skiing, not walking, but I wasn't so sure it was plausible, since we had only taken it approximately 30 minutes prior to this.
It's raining like all hell, and we're just getting soaked out in the rain, so we walk to the field & sit in the small pavilion where there are a few people hanging out, younger than us, and not really friends, but recognized. They almost immediately catch on to what we're doing when I begin to cough & whine about not wanting to throw up. They start almost leering at us, so we decide to start walking again.
We're walking around the field, police crawling all over the place, starting to feel it slightly, when we run into a few friends that had been at the carnival, and had won a few stuffed animals. This is where I realize that I have begun tripping. The animals they have won are LUDICROUSLY brightly colored. They are unreal to me, and they hurt my eyes, but I can't stop looking at them. I'm slightly squeamish in their presence and we cut our conversation with them short, and walk over to a small gazebo to smoke a cigarette.
There are young kids in the gazebo, also trying to get out of the rain. M wanders off while G and I smoke our cigarettes, and suddenly one of the kids starts making animal noises. G & I, tripping now, begin uncontrollably laughing, and follow M into the middle of a field toward the road.
When we get onto the road, G starts throwing up as he walks, which makes me cough and want to vomit as well. I try to push the thought from my head and concentrate mainly on not getting hit by a car, as we're now tripping fairly hard. My feet don't want to work, they feel heavy, and my vision is fuzzy, amplified by water on my glasses which is bending and moving.
I'm starting to get dizzy and G and I have some type of verbal diarhea as we blather on to ourselves about the pavement moving and how unstable we are and how the rain feels on our faces. We head back to the small pavilion, the kids we didn't want to be around were still there, so we sit on the other side. M starts talking about how he doesn't feel well, his pupils are as large as dinner plates. I whine about how I wish I could just throw up and get it over with, and take a drag of G's Midnight Special unfiltered cigarette, nearly puking but only managing to gag and make myself miserable.
We decide to go watch Transformers at our local theatre. We sit outside of the theatre for awhile, smoking cigarettes, trying not to puke, and watching the cars drive by. We watch the streelights reflecting off of the wet road, it looks shimmery, and it's rippling and moving with dots of light in it, and at times it looks oily to me. Water droplets start collecting on my glasses, and I enjoy looking at the blinking multi-colored lights above us, looking straight into them, eyes and pupils wide, looking at the patterns within the light caught on the water on my lenses, multiple circles and spectrums of light trapped within them.
We're cold and we decide to go back to my car. We blast the heat and watch the windows fog up, and I draw squiggly things on the windows and laugh. The rain drops melt and move down the windshield in odd patterns, and though the windshield is completely fogged up, I explain how it's defogging, but it's morphing and changing like the edge of a river, ebbing and flowing.
We finally walk back to the other part of town, and actually enter the theatre a few minutes into the movie, and don't bother actually finding seats. We sit in the back up against the wall on the side. We stare at the ceiling, and the squares shift and bend and blend together, the light coming off of the screen changing the colors of them. The movie has some extremely intense visual effects for me, certain parts when they are in the desert the sand seems to be moving off of the screen, the computerized colorful parts of the movie where they intercept hack signals are alive and beautiful. I spend most of the movie either giggling uncontrollably, or with my mouth agape, in awe of all the colors and movement.
At some point during the movie, G gets popcorn. I immediately start eating handfuls of it, then I pause, with about 4 pieces in my hand, and feel it melting into my palm. Alarmed, I quickly try to eat it, and it feels almost like I'm drinking it, though it still has the correct texture, it's warm and strange in my mouth.
We wander back outside for a cigarette at some point, and a friend of mine from high school literally rolls out a car at the curb, and begins taking pictures with a Polaroid camera. I'm not exactly sure if this happened, but I explain to him how beautiful everything looks, and how alive and wonderful everything is, and how life is happening RIGHT NOW. He's wearing special edition 'seafoam green' Nikes, and G and I get entranced by them, the color is so just beautiful and vibrant against the sidewalk.
Back into the theatre, back to the movie.
When the movie is over, we immediately jump up, and we are the first people out the door. I notice G is still wearing his sunglasses, because when we stumble out of the door into the hallway, there are 20-30 people waiting to get into the theatre, and I hear an older gentleman say, 'Cool man, he wears his sunglasses at night.'  Everyone's faces are leering at me and they feel so close, someone touches my hand and I jump back slightly, then plow through the crowd, looking down at the pattern of the carpet, smiling to myself.
9:45PM- When we essentially fall out of the building, we are met with a curious feeling. It's no longer raining hard, but we are tripping hard. There is a heavy fog from the rain and the temperature changes. We find out the fireworks have been cancelled, and it seems like everyone is evacuating town. We walk toward where everyone is leaving, the lights are extremely intense, and I comment that I feel like we're in the movie, and that at any moment a car is going to get up and start jogging down the street. The fog is strange and mutating into strange shapes as we wander around town, hearing strange banging noises from people's backyards as they set off their own fireworks, feeling as though we're in a war zone. There is garbage from the parade earlier in the day, littering the street, vomit [or imaginary vomit] all over the place, the streetlights casting a strange Nightmare on Elm Street feeling.
After awhile we decide we're coming down, and we decide to drive back to the garage [BAD IDEA, BAD IDEA]
[Erowid Note: Driving while intoxicated or tripping is dangerous and irresponsible because it endangers other people. Don't do it!]
12:30PM- When we finally made it there, we have a conversation mainly stating, 'I have no idea how I got here safely.' It was very upsetting to me, so I waited about an hour or so before I actually left, and was actually sober.
All in all, definitely doing this again, I have tripped on it twice so far and haven't really had anything terrible happen. As long as I have G as an anchor we can kind of babysit ourselves safely.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Each and every DNS resource record carries an explicit TTL that
specifies how long the information may be cached. In most situations,
Squid has access to the TTL values and doesn't store
DNS answers longer than allowed. This is certainly true when you use
Squid's internal DNS implementation, which is
enabled by default. However, if you elect to use the (external)
dnsserver processes, Squid may not receive TTL
values for DNS answers. In this case, successful DNS answers are
cached for the amount of time specified by this directive. |
Syntax
|
positive_dns_ttl time-specification
| |
Default
|
positive_dns_ttl 6 hours
| |
Example
|
positive_dns_ttl 1 hour
| |
Related
|
negative_dns_ttl
|
|


Trump says trade deal with China coming along well
WASHINGTON (Reuters) - President Donald Trump said on Friday that talks on a trade agreement with China were coming along well, echoing comments by U.S. and Chinese officials of progress on an initial deal.


See: Description
| Class | Description |
|---|---|
| AbstractInsnNode |
A node that represents a bytecode instruction.
|
| AnnotationNode |
A node that represents an annotationn.
|
| ClassNode |
A node that represents a class.
|
| FieldInsnNode |
A node that represents a field instruction.
|
| FieldNode |
A node that represents a field.
|
| FrameNode |
A node that represents a stack map frame.
|
| IincInsnNode |
A node that represents an IINC instruction.
|
| InnerClassNode |
A node that represents an inner class.
|
| InsnList |
A doubly linked list of
AbstractInsnNode objects. |
| InsnNode |
A node that represents a zero operand instruction.
|
| IntInsnNode |
A node that represents an instruction with a single int operand.
|
| InvokeDynamicInsnNode |
A node that represents an invokedynamic instruction.
|
| JumpInsnNode |
A node that represents a jump instruction.
|
| LabelNode |
An
AbstractInsnNode that encapsulates a Label . |
| LdcInsnNode |
A node that represents an LDC instruction.
|
| LineNumberNode |
A node that represents a line number declaration.
|
| LocalVariableAnnotationNode |
A node that represents a type annotation on a local or resource variable.
|
| LocalVariableNode |
A node that represents a local variable declaration.
|
| LookupSwitchInsnNode |
A node that represents a LOOKUPSWITCH instruction.
|
| MethodInsnNode |
A node that represents a method instruction.
|
| MethodNode |
A node that represents a method.
|
| MultiANewArrayInsnNode |
A node that represents a MULTIANEWARRAY instruction.
|
| ParameterNode |
A node that represents a parameter access and name.
|
| TableSwitchInsnNode |
A node that represents a TABLESWITCH instruction.
|
| TryCatchBlockNode |
A node that represents a try catch block.
|
| TypeAnnotationNode |
A node that represents a type annotationn.
|
| TypeInsnNode |
A node that represents a type instruction.
|
| VarInsnNode |
A node that represents a local variable instruction.
|
Provides an ASM visitor that constructs a tree representation of the classes it visits. This class adapter can be useful to implement "complex" class manipulation operations, i.e., operations that would be very hard to implement without using a tree representation (such as optimizing the number of local variables used by a method).
However, this class adapter has a cost: it makes ASM bigger and slower. Indeed it requires more than twenty new classes, and multiplies the time needed to transform a class by almost two (it is almost two times faster to read, "modify" and write a class with a ClassVisitor than with a ClassNode). This is why this package is bundled in an optional asm-tree.jar library that is separated from (but requires) the asm.jar library, which contains the core ASM framework. This is also why it is recommended not to use this class adapter when it is possible.
The root class is the ClassNode, that can be created from existing bytecode. For example:
ClassReader cr = new ClassReader(source); ClassNode cn = new ClassNode(); cr.accept(cn, true);
Now the content of ClassNode can be modified and then serialized back into bytecode:
ClassWriter cw = new ClassWriter(true); cn.accept(cw);
Using a simple ClassVisitor it is possible to create MethodNode instances per-method. In this example MethodNode is acting as a buffer that is flushed out at visitEnd() call:
ClassReader cr = new ClassReader(source); ClassWriter cw = new ClassWriter(); ClassVisitor cv = new ClassVisitor(cw) { public MethodVisitor visitMethod(int access, String name, String desc, String signature, String[] exceptions) { final MethodVisitor mv = super.visitMethod(access, name, desc, signature, exceptions); MethodNode mn = new MethodNode(access, name, desc, signature, exceptions) { public void visitEnd() { // transform or analyze method code using tree API accept(mv); } }; } }; cr.accept(cv, true);
Several strategies can be used to construct method code from scratch. The first option is to create a MethodNode, and then create XxxInsnNode instances and add them to the instructions list:
MethodNode m = new MethodNode(...); m.instructions.add(new VarInsnNode(ALOAD, 0)); ...
Alternatively, you can use the fact that MethodNode is a MethodVisitor, and use that to create the XxxInsnNode and add them to the instructions list through the standard MethodVisitor methods:
MethodNode m = new MethodNode(...); m.visitVarInsn(ALOAD, 0); ...
If you cannot generate all the instructions in sequential order, i.e. if you need to save some pointer in the instruction list and then insert instructions at that place after other instructions have been generated, you can use InsnList methods insert() and insertBefore() to insert instructions at a saved pointer.
MethodNode m = new MethodNode(...); m.visitVarInsn(ALOAD, 0); AbstractInsnNode ptr = m.instructions.getLast(); m.visitVarInsn(ALOAD, 1); // inserts an instruction between ALOAD 0 and ALOAD 1 m.instructions.insert(ptr, new VarInsnNode(ALOAD, 0)); ...
If you need to insert instructions while iterating over an existing instruction list, you can also use several strategies. The first one is to use a ListIterator over the instruction list:
ListIterator it = m.instructions.iterator(); while (it.hasNext()) { AbstractInsnNode n = (AbstractInsnNode) it.next(); if (...) { it.add(new VarInsnNode(ALOAD, 0)); } }
It is also possible to convert an instruction list into an array and iterate trough array elements:
AbstractInsnNode[] insns = m.instructions.toArray(); for(int i = 0; i<insns.length; i++) { AbstractInsnNode n = insns[i]; if (...) { m.instructions.insert(n, new VarInsnNode(ALOAD, 0)); } }
If you want to insert these instructions through the MethodVisitor methods, you can use another instance of MethodNode as a MethodVisitor and then insert instructions collected by that instance into the instruction list. For example:
AbstractInsnNode[] insns = m.instructions.toArray(); for(int i = 0; i<insns.length; i++) { AbstractInsnNode n = insns[i]; if (...) { MethodNode mn = new MethodNode(); mn.visitVarInsn(ALOAD, 0); mn.visitVarInsn(ALOAD, 1); m.instructions.insert(n, mn.instructions); } }


menu
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|
Adbase
Adinf C++ base library V2
|
#include <Logging.hpp>
Classes | |
| class | SourceFile |
Public Types | |
| enum | LogLevel { TRACE, DEBUG, INFO, WARN, ERROR, FATAL, NUM_LOG_LEVELS } |
| typedef std::function< void(const char *msg, size_t len)> | OutputFunc |
| typedef std::function< void()> | FlushFunc |
Public Member Functions | |
| Logger (SourceFile file, int line) | |
| Logger (SourceFile file, int line, LogLevel level) | |
| Logger (SourceFile file, int line, LogLevel level, const char *func) | |
| Logger (SourceFile file, int line, bool toAbort) | |
| ~Logger () | |
| LogStream & | stream () |
Static Public Member Functions | |
| static LogLevel | logLevel () |
| static void | setLogLevel (LogLevel level) |
| static void | setOutput (const OutputFunc &func) |
| static void | setFlush (const FlushFunc &func) |
| static void | setTimeZone (const TimeZone &tz) |
Definition at line 20 of file Logging.hpp.
| typedef std::function<void ()> adbase::Logger::FlushFunc |
Definition at line 76 of file Logging.hpp.
| typedef std::function<void (const char* msg, size_t len)> adbase::Logger::OutputFunc |
Definition at line 75 of file Logging.hpp.
| Enumerator | |
|---|---|
| TRACE | |
| DEBUG | |
| INFO | |
| WARN | |
| ERROR | |
| FATAL | |
| NUM_LOG_LEVELS |
Definition at line 22 of file Logging.hpp.
| adbase::Logger::Logger | ( | SourceFile | file, |
| int | line | ||
| ) |
Definition at line 127 of file Logging.cpp.
Referenced by adbase::CheckNotNull().
| adbase::Logger::Logger | ( | SourceFile | file, |
| int | line, | ||
| LogLevel | level | ||
| ) |
Definition at line 136 of file Logging.cpp.
| adbase::Logger::Logger | ( | SourceFile | file, |
| int | line, | ||
| LogLevel | level, | ||
| const char * | func | ||
| ) |
Definition at line 131 of file Logging.cpp.
| adbase::Logger::Logger | ( | SourceFile | file, |
| int | line, | ||
| bool | toAbort | ||
| ) |
Definition at line 140 of file Logging.cpp.
| adbase::Logger::~Logger | ( | ) |
Definition at line 144 of file Logging.cpp.
References adbase::detail::FixedBuffer< SIZE >::data(), FATAL, adbase::gFlush, adbase::gOutput, adbase::detail::FixedBuffer< SIZE >::length(), and stream().
|
static |
Definition at line 162 of file Logging.cpp.
|
static |
Definition at line 154 of file Logging.cpp.
Referenced by stream().
|
static |
Definition at line 158 of file Logging.cpp.
|
static |
Definition at line 166 of file Logging.cpp.
|
inline |
Definition at line 68 of file Logging.hpp.
References logLevel(), and setLogLevel().
Referenced by ~Logger().


To run queries
1 Determine the scope of the modules you want to run queries on:
• the current project
• a selection of files or projects from the Browser
• one or more groups selected from the Group Manager
2 From the Input From list, select the scope you want to run queries on:
• Current Scope
• Browser Selection
• Group Selection
3 Determine the scope of the queries that you want to run:
• a single query
• a selection of queries from a single filter set
• a selection of queries from several or all filter sets
• the entire body of queries (all filter sets)
Note: You can optionally modify the weight of individual queries by entering a new number in the Weight box. Adjusting the weight of individual queries affects the total quality score. For more information, see Caliper Sessions and Weights.
4 Do one of the following:
• Click Run All.
• Click Run Selected.
A window appears, displaying Caliper progress against each selected file. At any time, you can click Cancel in this window to end the Caliper analysis.


This is my first webpage. its a demonstar
Hi hi im 18 years old this year. My hobbies are reading
Another paragraph.


Find Your Relative Steem Power Ranking
Search
@{{ranking.account}}:
{{ranking.rank}}
Backend by SteemData
Developed by @gutzofter
gutzofter@alephchain.com


Example Voting System dapp
Save
Example
Approve vote:
0
Approve
Against votes:
0
Against
Abstence votes:
0
Abstence


With Appfast responsive landing page template, you can showcase your next creative & amazing apps!
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Explain to you how all this mistaken idea of denouncing pleasure and praising pain was born and I will give you completed.
The master-builder of human happines no one rejects, dislikes avoids pleasure itself, because it is very pursue pleasure.
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Deleting Entries from a File List
Selected from the Action button menu in the file list dialog.
Selected file list entries that do not refer to files are deleted without confirmation. If only one file is selected, you will be asked for confirmation for that file; if more than one file is selected, the following dialog will be displayed:
This allows you to control confirmation of deletion of each file and whether the associated entries in the file directory are erased as well.
The default settings for this dialog can be changed using Settings Moderate.


Taeyeon takes #1 on November 9th 'Show! Music Core'!
by germainejTaeyeon took #1 on the November 9th episode of 'Show! Music Core'!
On the latest episode, Taeyeon's "Spark" was up against AKMU's "How Can I Love the Heartbreak, You're the One I Love" and MC Mong's "Fame". MC Mong came in 3rd, AKMU came in 2nd, and the Girls' Generation took 1st with 9,740 points, which marked her second music show win with "Spark". Congratulations to Taeyeon!
Check out the performances posted by MBC below.


I studied computer science in France, my native country, I got a bachelor and a master/engineer degrees in IT.
After graduating, I moved to Paris where I worked for 5 years in a service company for multiple big clients mostly with Java. I worked on high-traffic back-end applications and also websites with HTML/CSS.
Later, I wanted to be closer to clients and improve my expertise in development. I went to a smaller service company where I had the opportunity of developing a unique skill-set with Javascript, front-end frameworks and mobile apps.
Then I decided to take a big step and move to Vancouver, a city I visited a few years ago and I really liked. I am now working on client facing and E-commerce websites with Meteor and Grails.


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{% call macros.panel("info", "Step 3 - pick some features") %}
Mailu comes with multiple base features, including a specific admin interface, Web email clients (webmails), antispam, antivirus, etc. If you wish to disable some of these features, you are free to do so.
Emails will be available through IMAP and POP3. You may also enable a Web email client. These do add some complexity but provide an easier way of accessing messages for beginner users.
Email filtering is a really important features. You can still disable it, which will prevent Mailu from doing spam filtering, virus filtering, and from applying white and blacklists that you may configure in the admin interface. You may also disable the antivirus if required (it does use aroung 1GB of ram).


{% extends 'layouts/main.html' %} {% block title %}NutroMonkey{% endblock %} {% block content %} Nutromonkey Your daily nutrition tracker
Your daily nutrition tracker
{{ additional_info.replace(';', ', ') }}
Show Less
Nutritional information is based on the data provided by USDA.


|
Open-Source Isotopics
|
Public Member Functions | |
| def | __init__ (self, input_path) |
| def | file (self) |
| def | cells (self) |
| def | cell_id_list (self) |
| def | cell_list (self) |
| def | cell_dict (self) |
| def | mode (self) |
| def | MC_input_path (self) |
| def | lib (self) |
Public Attributes | |
| input_path | |
input reads, stores and process the input data in the input file provided by the user
| def onix.input.Input.cell_id_list | ( | self | ) |
| def onix.input.Input.cells | ( | self | ) |
| def onix.input.Input.lib | ( | self | ) |
| def onix.input.Input.mode | ( | self | ) |


|
|||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
Object org.apache.spark.mllib.evaluation.MulticlassMetrics
public class MulticlassMetrics
::Experimental:: Evaluator for multiclass classification.
param: predictionAndLabels an RDD of (prediction, label) pairs.
| Constructor Summary | |
|---|---|
MulticlassMetrics(RDD<scala.Tuple2<Object,Object>> predictionAndLabels)
|
| Method Summary | |
|---|---|
Matrix |
confusionMatrix()
Returns confusion matrix: predicted classes are in columns, they are ordered by class label ascending, as in "labels" |
double |
falsePositiveRate(double label)
Returns false positive rate for a given label (category) |
double |
fMeasure()
Returns f-measure (equals to precision and recall because precision equals recall) |
double |
fMeasure(double label)
Returns f1-measure for a given label (category) |
double |
fMeasure(double label,
double beta)
Returns f-measure for a given label (category) |
double[] |
labels()
Returns the sequence of labels in ascending order |
double |
precision()
Returns precision |
double |
precision(double label)
Returns precision for a given label (category) |
double |
recall()
Returns recall (equals to precision for multiclass classifier because sum of all false positives is equal to sum of all false negatives) |
double |
recall(double label)
Returns recall for a given label (category) |
double |
truePositiveRate(double label)
Returns true positive rate for a given label (category) |
double |
weightedFalsePositiveRate()
Returns weighted false positive rate |
double |
weightedFMeasure()
Returns weighted averaged f1-measure |
double |
weightedFMeasure(double beta)
Returns weighted averaged f-measure |
double |
weightedPrecision()
Returns weighted averaged precision |
double |
weightedRecall()
Returns weighted averaged recall (equals to precision, recall and f-measure) |
double |
weightedTruePositiveRate()
Returns weighted true positive rate (equals to precision, recall and f-measure) |
| Methods inherited from class Object |
|---|
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
|---|
public MulticlassMetrics(RDD<scala.Tuple2<Object,Object>> predictionAndLabels)
| Method Detail |
|---|
public Matrix confusionMatrix()
public double truePositiveRate(double label)
label
- the label.
public double falsePositiveRate(double label)
label
- the label.
public double precision(double label)
label
- the label.
public double recall(double label)
label
- the label.
public double fMeasure(double label, double beta)
label
- the label.beta
- the beta parameter.
public double fMeasure(double label)
label
- the label.
public double precision()
public double recall()
public double fMeasure()
public double weightedTruePositiveRate()
public double weightedFalsePositiveRate()
public double weightedRecall()
public double weightedPrecision()
public double weightedFMeasure(double beta)
beta
- the beta parameter.
public double weightedFMeasure()
public double[] labels()
|
|||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |


Hugo Ortega's journey from dishwasher to renowned chef
Hugo Ortega's name is well-known in Houston. He's the executive chef and co-owner at four top local restaurants - Hugo's, Backstreet Café, Xochi and Caracol.
Last year, he won Best Chef of the Southwest at the prestigious James Beard Awards. But he never forgets his roots.
Growing up in rural Mexico, he herded 300 goats and learned to grind corn for masa. Ortega credits his grandmother with being the primary influence on his traditional Mexican cuisine.


Direction
Home
Examples
Tutorial
Reference
Source code
Index
Enumeration members
Down
Left
Right
Up
Enumeration members
Down
•
Down
: = “DOWN”
Left
•
Left
: = “LEFT”
Right
•
Right
: = “RIGHT”
Up
•
Up
: = “UP”


Taiwan starts military exercises days after Chinese aircraft carrier sails by
F-16 jets simulate enemy attack
by Matthew StrongA Taiwanese F-16. (CNA photo)
TAIPEI (Taiwan News) – The military launched a new series of exercises Tuesday (November 19), just two days after China sent its first domestically built aircraft carrier through the Taiwan Strait.
The
The drills, named “Lien Hsiang” (聯翔), were directed against an air attack and would involve F-16 fighter jets from a base in Hualien County pretending to be enemy aircraft, the Ministry of National Defense said.
Army, Navy, Air Force and missile units would cooperate in testing their joined response to the simulated attack, according to a report by the Central News Agency.
Chief of the General Staff Shen Yi-ming (沈一鳴), who hails from the Air Force, represented President Tsai Ing-wen (蔡英文) at the special command center to oversee the developments in Tuesday’s military drills, according to the CNA.


CONTACT
Mobile number
6XXXXXXXXXX
<EMAIL_ADDRESS>Residence
LoknathPur Ganj Road DalsinghSarai
Samastipur
State:Bihar
SKILLS
ABOUT ME
My self Satyam kumar completed my Bachelor Engineering with Computer Science and Education (Information Security) with an overall CGPA of 7.00 . I am highly organised ,diplomatic and dedicated engineer. I have excellent communication skills enabling me to effectively communicate with the people in a better way. I am currently looking for an opportunity to utilise my technical skills in a challenging working environment and become a valuable asset to the organisation that I work for.
WORK EXPERIENCE
programming language
Chandigarh University
2019/2023Since i am from enginnering background and i also love to do programming , so i believe that every programming language is important in each and every field ,i have a good command in c++ and java also learn python and c i also love to learn new technology .
Lead web developer
Chandigarh University
2019/2023I started web devloping in my 3rd semester and i am very much comfortable in HTML/CSS/Javascript . I am expert in front-end but i started learning backend to become a full stack developer.I am in that position that i can build my website in an effective manner.
UI/UX designer
Chandigarh University
2019/2023I don't have much experience in UI/UX designe but i have some knowledge regarding it that help me to design our personal website and also the designing part.
Web application penetration tester
......
2021/-I had knowledge in web application penetration testing and also test the website to explore the vulnerabilities and also provide to solution to the security expert to how to patch them..
EDUCATION
ST.Xavier's public school(Bihar)
2004/2016Schooling upto 10th standard
CGPA-10.0
Sri Chaitanya Techno school (Visakhapatnam)
2017/2019Schooling upto 12th standard
CGPA-7.3
Chandigarh University
2019/2023BE CSE(IS)
CGPA-7.5
PROJECTS
Notepad
2020In this project we are designing a basic notepad which is beginner friendly with the help of java swings and file handling concepts.This project contains all actions of notepad wth less memory consumption so it will also work on any version of windows and operating system.The unique feature is that it is most precisable and also have an attractive background color
Data Shield
2021This is the project based on AES encryption, In this project .we are emplementing AES encryption by usig pycrypt aes module of python we are implementing AES module. We are taking file location and key by user and location of encrypted file the we pass the argument to the pycryptaes module then it will return the file in encrypted format. For decrypting we are using same module but before decrypting it we must have to calculate the size of the encrypted file and after pass the information to pycrypt aes module your file is decrypted if you wrongly it conver file into some other format.
Dummy Swiggy app
2020This is a project which is build using HTML/CSS . With the help of this project anyone can order any kind of food which is as same as Swiggy.The unique feature of this project is that it looks as exactly as swiggy.
CERTIFICATIONS
Ethical Hacking(Internshala)
2021In this certifications i learnt about the protection of web application from various types of attacks and how to secure them from various types of OWASP and also learnt how to be a security expert.
Get Connected English 0521 cga(Cisco)
2021In this certifications we learnt about the basics computer knowledge,Directories and files,The Internet and Exploring the human network.
Cybersecurity Essentials English 0421 cga
2021In this certifications we learnt about A World of Experts and Criminals,The Cybersecurity cube,Cybersecurity Threats, Vulnerabilities, and Attacks,The Art of Protecting Secrets,The Art of Ensuring Integrity,Protecting a Cybersecurity Domain
CCNAv7 - Bridging English 0221 cga
2021In this certifications we learnt about Switching, Routing, and Wireless Essentials (SRWE) Bridging Content,Enterprise Networking, Security, and Automation (ENSA) Bridging Content,
Web Devlopement Masterclass(Udemy)
2021In this certifications we learnt how to make website using HTML,CSS,Javascript,JSON,JQuery and how to deploy it.
Introduction to Cybersecurity
2019In this certifications we learnt about The need of Cybersecurity,Attacks,concepts and techniques,Protecting your data and privacy,Protecting your organisations.


Sounds easy for a second but then the fact people are pretty complicated settles in and you're left feeling a bit overwhelmed. That's the feeling I'm having as I write this-- I'm very familiar with my own site but figuring out what information people are really interested in is a bit of a challenge. For this reason, this description will be broken down into 2 sections, the first dealing with all of the conceptual things like basic organization structure, look, and feel while section 2 will deal with the notable bits of tech wich make this whole site go.
The goal of this site was to show people what I am capable of in regards to my profession which bounces between graphic designer, web developer, and web designer depending on client needs. For that reason, the site was pretty easy to break down into smaller, common sense areas of focus.
Musicians always seem to have the most fun with what represents them visually-- T-shirts, posters, album covers, and of course, websites. I wanted to have a bit of that fun while still acknowledging my non-musical profession and keeping things pretty sharp and intuitive to use.
With a general direction in mind, it was off to the internet to see if any musicians had put together something which
Quick post on the nav: https://jsfiddle.net/0d3cjzbq/


Information and Communication Technology
is a central engine to driving Rwanda’s transformation to a knowledge based economy,
a fact Rwanda has acknowledged by allocating a budget to ICT
– as a percentage of its GDP,
– that is at par with OECD countries.
Rwanda continues to be one of the fastest growing African countries in ICT and there are several
avenues for growth for the ICT sector
– from e-commerce and e-services, mobile technologies,
applications development and automation to becoming a regional center
for the training of top quality ICT professionals and research.
A rofeature-pict ICT industry can create wealth, jobs and entrepreneurs.
| Jackson<EMAIL_ADDRESS>| Likes | Action |
|---|---|---|
| Computer Tech in Rwanda is raising up keep it up! |
34 |


Allow/Deny
Use first the Allowed Cidr's to check if a destination is allowed. If an IP
is not allowed, reject it. If it is allowed, check if it is not denied.
When using the Denied first, check if an IP is denied; if not, allow it. If it is denied, check
if it is allowed.


Contact Us for More Detailed Information
General Points of Contact
Emergencies: Call 911 or call us at<PHONE_NUMBER> (toll free, 24 hours a day, every day of the year)
General Phone:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
General Email<EMAIL_ADDRESS>Sales Hours: 8 a.m. to 4:30 p.m. Monday through Friday, except holidays
General Manager: Greg Cohen
Mailing Address:
NY Solar
2288 Flatbush Road
Kingston, NY 12401
Other Contact Info
Career Inquires<EMAIL_ADDRESS>Resellers: resellers@nysolar.com


TV Simulator '99
Version 0.6.1
Zach Hall, 2017
Credits
Prevue reference software, information, and Curday.dat by AriX, other Prevue Guide forum members.
New Prevue Fonts by rudyvalencia
90's Commercials Vol. 244 by 80sCommercialVault


QWebEngineFullScreenRequest Class
The QWebEngineFullScreenRequest class enables accepting or rejecting requests for entering and exiting the fullscreen mode. More...
| Header: | #include <QWebEngineFullScreenRequest> |
| qmake: | QT += webenginewidgets |
| Since: | Qt 5.6 |
Properties
Public Functions
Detailed Description
The QWebEngineFullScreenRequest class enables accepting or rejecting requests for entering and exiting the fullscreen mode.
To allow elements such as videos to be shown in the fullscreen mode, applications must set QWebEngineSettings::FullScreenSupportEnabled and connect to QWebEnginePage::fullScreenRequested, which takes a QWebEngineFullScreenRequest instance as an argument.
If an element of a web page requests to be shown in the fullscreen mode, QWebEnginePage::fullScreenRequested will be emitted with an QWebEngineFullScreenRequest instance as an argument where toggleOn() returns true
. The signal handler needs to then either call accept() or reject().
If the request to enter the fullscreen mode is accepted, the element requesting fullscreen mode will fill the viewport, but it is up to the application to make the view fullscreen or to move the page to a view that is in the fullscreen mode.
Likewise, a QWebEnginePage::fullScreenRequested will be emitted when the user wants to leave the full screen mode (that is, through the QWebEnginePage::ExitFullScreen context menu action). In this case, toggleOn() will return false
, and the signal handler again needs to accept() or reject() the request. If it is accepted, the applicaton needs to make sure that the global window state is restored.
Property Documentation
origin : const QUrl
This property holds the URL to be opened in the fullscreen mode.
Access functions:
| const QUrl & | origin() const |
toggleOn : const bool
This property holds whether the web page has issued a request to enter fullscreen mode.
Access functions:
| bool | toggleOn() const |
Member Function Documentation
void QWebEngineFullScreenRequest::accept()
Accepts the request to enter or exit the fullscreen mode.
const QUrl &QWebEngineFullScreenRequest::origin() const
Returns the URL to be opened in the fullscreen mode.
Note: Getter function for property origin.
void QWebEngineFullScreenRequest::reject()
Rejects a request to enter or exit the fullscreen mode.
bool QWebEngineFullScreenRequest::toggleOn() const
Returns true
if the web page has issued a request to enter the fullscreen mode, otherwise returns false
.
Note: Getter function for property toggleOn.


---
sort_order: 70
tei_id: rdx_b5j2m.p.idm190929952
annotation_count: 0
images:
small-thumbnail: http://readux.library.emory.edu/books/emory:b5j2m/pages/emory:p75qk/mini-thumbnail/
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title: Page 70
number: 70
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{% raw %}66 MRS. H. BEECHER STOWE's " UNCLE TOM."{% endraw %}
{% raw %}poultry, corn, whisky, and other articles which were to{% endraw %}
{% raw %}be sold as we dropped down the river, wherever they{% endraw %}
{% raw %}could be disposed of to the greatest advantage. It{% endraw %}
{% raw %}was a common trading-voyage to New Orleans, the{% endraw %}
{% raw %}interest of which consisted not in the incidents that{% endraw %}
{% raw %}occurred, not in storms, shipwreck, or external{% endraw %}
{% raw %}disaster of any sort; but in the storm of passions{% endraw %}
{% raw %}contending within me, and the imminent risk of the{% endraw %}
{% raw %}shipwreck of my soul, which was impending over{% endraw %}
{% raw %}me nearly the whole period of the voyage. One{% endraw %}
{% raw %}circumstance, only, I will mention, illustrating, as{% endraw %}
{% raw %}other events in my life have often done, the counsel{% endraw %}
{% raw %}of the Saviour, " He that will be chief among you,{% endraw %}
{% raw %}let him be your servant."{% endraw %}
{% raw %}We were all bound to take our turn at the helm,{% endraw %}
{% raw %}sometimes under direction of the captain, and some¬{% endraw %}
{% raw %}times on our own responsibility, as he could not be{% endraw %}
{% raw %}always awake. In the daytime there was less diffi¬{% endraw %}
{% raw %}culty than at night, when it required some one who{% endraw %}
{% raw %}knew how to avoid sandbars and snags in the river ;{% endraw %}
{% raw %}the captain was the only person on board who had{% endraw %}
{% raw %}this knowledge. But whether by day or by night,{% endraw %}
{% raw %}as I was the only negro in the boat, I was compelled{% endraw %}
{% raw %}to stand at least three turns at the helm to any other{% endraw %}
{% raw %}person's one; so that, from being much with the{% endraw %}
{% raw %}captain, and frequently thrown upon my own exer¬{% endraw %}
{% raw %}tions, I learned the art of steering and managing{% endraw %}
{% raw %}the boat far better than the rest. I watched the{% endraw %}
{% raw %}manoeuvres necessary to shoot by a "sawyer," to{% endraw %}
{% raw %}land on a bank, avoid a snag, or a steamboat, in the{% endraw %}
{% raw %}rapid current of the Mississippi, till I could do it as{% endraw %}
{% raw %}well as the captain. After a while, he was attacked{% endraw %}


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Guide: Best Upcoming PS4 RPGs
Worlds worth visiting
by Liam CroftRole-playing games cast a wide umbrella over the video game industry -- making for a genre that contains some of the very best titles of all time. No matter whether it comes from the east or the west, every experience brings with it something to call its own. The PlayStation 4 has seen some of the greatest RPGs over the past couple of years, including the likes of The Witcher 3: Wild Hunt and Persona 5, but what's next? What can we look forward to when it comes to creating a character and setting off into an entirely new world in the future? These are the best upcoming PS4 RPGs.
Final Fantasy VII Remake (PS4)
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Profile Publisher: Square Enix / Developer: Square Enix Release Date: 3rd Mar 2020 (USA) / 3rd Mar 2020 (UK/EU) |
We start with a showstopper. Five years in the making, Final Fantasy VII Remake finally arrives on PlayStation 4 in March 2020. Bringing with it the first part of the classic story, an all-new combat system ditches the original's turn-based nature alongside stunning visuals and an expanded Midgar that is sure to delight fans across the globe. This is the big one, and we can't wait to get our hands on it.
Nioh 2 (PS4)
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Profile Publisher: Koei Tecmo / Developer: Team Ninja Release Date: 13th Mar 2020 (USA) / 13th Mar 2020 (UK/EU) |
Nioh 2 is the Souls-like to beat at the moment after a recent beta proved its worth in combat, style, variation, and deep RPG mechanics. This has more skill trees than you can shake a stick at, while a deep suite of character creation options seemingly allows you to create a Samurai to your tastes. It may be a dark horse when you take into account what's releasing around it, but Nioh 2 is surely set to impress those that give it a shot.
Cyberpunk 2077 (PS4)
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Profile Publisher: CD Projekt Red / Developer: CD Projekt Red Release Date: 16th Apr 2020 (USA) / 16th Apr 2020 (UK/EU) |
The masters of the role-playing genre are back. After developing one of the best RPGs ever made in The Witcher 3: Wild Hunt and capitalizing on that launch with two rounds of incredible DLC, CD Projekt Red is back with one of 2020's most anticipated games. Cyberpunk 2077 has the potential to be one of the PS4's crowning achievements as various slices of gameplay and impressive trailers have proven its potential. If the Polish developer can back all of that up come April, then we're all in for a rather special ride.
Trials of Mana (PS4)
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Profile Publisher: Square Enix / Developer: Square Enix Release Date: 24th Apr 2020 (USA) / 24th Apr 2020 (UK/EU) |
Trials of Mana is a remake of the 1995 Seiken Densetsu 3 -- a classic RPG that never made its way out of Japan. It's the sequel to Secret of Mana, which we're sure you've all heard of before. Just forget about that awful PS4 re-release, okay? Anyway, Trials of Mana brings the experience into the modern age with 4K visuals and an updated battle system. Not too much more is known about it, but with the experience hitting PS4 in late April, we don't have too long to wait.
Marvel's Avengers (PS4)
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Profile Publisher: Square Enix / Developer: Crystal Dynamics Release Date: 15th May 2020 (USA) / 15th May 2020 (UK/EU) |
While it'll still be classed as an RPG overall, Marvel's Avengers will be an experience focused much more on the loot than its levelling up system. Of course, there will be one, but this is a title from Crystal Dynamics that's set to emulate Destiny more than anything else. With pieces of armour to collect, new weapons and mods to equip, and cosmetic skins to acquire, you'll be blasting your way to max level before you know it. Then the endgame begins -- one we're definitely interested in checking out in May 2020.
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Jeff gave his previously announced, invited talk at Stanford yesterday and the video is available here.
Congrats, Jeff!
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