Layer
Base layer class.
Inherits From: Module
tf.compat.v1.keras.layers.Layer
tf.compat.v2.keras.layers.Layer
This is the class from which all layers inherit.
A layer is a class implementing common neural networks operations, such as convolution, batch norm, etc. These operations require managing weights, losses, updates, and inter-layer connectivity.
Users will just instantiate a layer and then treat it as a callable.
We recommend that descendants of Layer
implement the following methods:
__init__()
: Save configuration in member variablesbuild()
: Called once from __call__
, when we know the shapes of inputs
and dtype
. Should have the calls to add_weight()
, and then
call the super's build()
(which sets self.built = True
, which is
nice in case the user wants to call build()
manually before the
first __call__
).call()
: Called in __call__
after making sure build()
has been called
once. Should actually perform the logic of applying the layer to the
input tensors (which should be passed in as the first argument).trainable
: Boolean, whether the layer's variables should be trainable.name
: String name of the layer.dtype
: The dtype of the layer's computations and weights (default of
None
means use tf.keras.backend.floatx
in TensorFlow 2, or the type
of the first input in TensorFlow 1).dynamic
: Set this to True
if your layer should only be run eagerly, and
should not be used to generate a static computation graph.
This would be the case for a Tree-RNN or a recursive network,
for example, or generally for any layer that manipulates tensors
using Python control flow. If False
, we assume that the layer can
safely be used to generate a static computation graph.Read-only properties:
name: The name of the layer (string).
dtype: The dtype of the layer's computations and weights. If mixed
precision is used with a tf.keras.mixed_precision.experimental.Policy
,
this is instead just the dtype of the layer's weights, as the computations
are done in a different dtype.
updates: List of update ops of this layer.
losses: List of losses added by this layer.
trainable_weights: List of variables to be included in backprop.
non_trainable_weights: List of variables that should not be
included in backprop.
weights: The concatenation of the lists trainable_weights and
non_trainable_weights (in this order).
trainable
: Whether the layer should be trained (boolean).input_spec
: Optional (list of) InputSpec
object(s) specifying the
constraints on inputs that can be accepted by the layer.Each layer has a dtype, which is typically the dtype of the layer's
computations and variables. A layer's dtype can be queried via the
Layer.dtype
property. The dtype is specified with the dtype
constructor
argument. In TensorFlow 2, the dtype defaults to tf.keras.backend.floatx()
if no dtype is passed. floatx()
itself defaults to "float32". Additionally,
layers will cast their inputs to the layer's dtype in TensorFlow 2. For
example:
x = tf.ones((4, 4, 4, 4), dtype='float64') layer = tf.keras.layers.Conv2D(filters=4, kernel_size=2) print(layer.dtype) # float32 # `layer` casts it's inputs to layer.dtype, which is float32, and does # computations in float32. y = layer(x)
Currently, only tensors in the first argument to the layer's call
method are
casted. For example:
class MyLayer(tf.keras.layers.Layer): # Bug! `b` will not be casted. def call(self, a, b): return a + 1., b + 1. a = tf.constant(1., dtype="float32") b = tf.constant(1., dtype="float32") layer = MyLayer(dtype="float64") x, y = layer(a, b) print(x.dtype) # float64 print(y.dtype) # float32. Not casted since `b` was not passed to first input
It is recommended to accept tensors only in the first argument. This way,
all tensors are casted to the layer's dtype. MyLayer
should therefore be
written as:
class MyLayer(tf.keras.layers.Layer): # Now, all tensor inputs will be casted. def call(self, inputs): a, b = inputs return a + 1., b + 1. a = tf.constant(1., dtype="float32") b = tf.constant(1., dtype="float32") layer = MyLayer(dtype="float64") x, y = layer((a, b)) print(x.dtype) # float64 print(y.dtype) # float64.
In a future minor release, tensors in other arguments may be casted as well.
Currently, other arguments are not automatically casted for technical reasons, but this may change in a future minor release.
A layer subclass can prevent its inputs from being autocasted by passing
autocast=False
to the layer constructor. For example:
class MyLayer(tf.keras.layers.Layer): def __init__(self, **kwargs): kwargs['autocast']=False super(MyLayer, self).__init__(**kwargs) def call(self, inp): return inp x = tf.ones((4, 4, 4, 4), dtype='float64') layer = MyLayer() print(layer.dtype) # float32. y = layer(x) # MyLayer will not cast inputs to it's dtype of float32 print(y.dtype) # float64
If you want to run a Model in float64, you can set floatx to be float64 by
calling tf.keras.backend.set_floatx('float64')
. This will cause all layers
to default to float64 instead of float32:
tf.keras.backend.set_floatx('float64') layer1 = tf.keras.layers.Dense(4) layer2 = tf.keras.layers.Dense(4) x = tf.ones((4, 4)) y = layer2(layer1(x)) # Both layers run in float64
Alternatively, you can pass dtype='float64'
to each individual layer. Note
that if you have any layers which contain other layers as members, you must
ensure each sublayer gets dtype='float64'
passed to it's constructor as
well:
layer1 = tf.keras.layers.Dense(4, dtype='float64') layer2 = tf.keras.layers.Dense(4, dtype='float64') x = tf.ones((4, 4)) y = layer2(layer1(x)) # Both layers run in float64 class NestedLayer(tf.keras.layers.Layer): def __init__(self, **kwargs): super(NestedLayer, self).__init__(**kwargs) self.dense = tf.keras.layers.Dense(4, dtype=kwargs.get('dtype')) def call(self, inp): return self.dense(inp) layer3 = NestedLayer(dtype='float64') z = layer3(x) # layer3's dense layer runs in float64, since NestedLayer # correcty passed it's dtype to it's dense layer
__init__
__init__( trainable=True, name=None, dtype=None, dynamic=False, **kwargs )
activity_regularizer
Optional regularizer function for the output of this layer.
dtype
dynamic
input
Retrieves the input tensor(s) of a layer.
Only applicable if the layer has exactly one input, i.e. if it is connected to one incoming layer.
Input tensor or list of input tensors.
RuntimeError
: If called in Eager mode.AttributeError
: If no inbound nodes are found.input_mask
Retrieves the input mask tensor(s) of a layer.
Only applicable if the layer has exactly one inbound node, i.e. if it is connected to one incoming layer.
Input mask tensor (potentially None) or list of input mask tensors.
AttributeError
: if the layer is connected to
more than one incoming layers.input_shape
Retrieves the input shape(s) of a layer.
Only applicable if the layer has exactly one input, i.e. if it is connected to one incoming layer, or if all inputs have the same shape.
Input shape, as an integer shape tuple (or list of shape tuples, one tuple per input tensor).
AttributeError
: if the layer has no defined input_shape.RuntimeError
: if called in Eager mode.input_spec
losses
Losses which are associated with this Layer
.
Variable regularization tensors are created when this property is accessed,
so it is eager safe: accessing losses
under a tf.GradientTape
will
propagate gradients back to the corresponding variables.
A list of tensors.
metrics
name
Returns the name of this module as passed or determined in the ctor.
NOTE: This is not the same as the self.name_scope.name
which includes
parent module names.
non_trainable_variables
non_trainable_weights
output
Retrieves the output tensor(s) of a layer.
Only applicable if the layer has exactly one output, i.e. if it is connected to one incoming layer.
Output tensor or list of output tensors.
AttributeError
: if the layer is connected to more than one incoming
layers.RuntimeError
: if called in Eager mode.output_mask
Retrieves the output mask tensor(s) of a layer.
Only applicable if the layer has exactly one inbound node, i.e. if it is connected to one incoming layer.
Output mask tensor (potentially None) or list of output mask tensors.
AttributeError
: if the layer is connected to
more than one incoming layers.output_shape
Retrieves the output shape(s) of a layer.
Only applicable if the layer has one output, or if all outputs have the same shape.
Output shape, as an integer shape tuple (or list of shape tuples, one tuple per output tensor).
AttributeError
: if the layer has no defined output shape.RuntimeError
: if called in Eager mode.trainable
trainable_variables
Sequence of variables owned by this module and it's submodules.
Note: this method uses reflection to find variables on the current instance and submodules. For performance reasons you may wish to cache the result of calling this method if you don't expect the return value to change.
A sequence of variables for the current module (sorted by attribute name) followed by variables from all submodules recursively (breadth first).
trainable_weights
updates
variables
Returns the list of all layer variables/weights.
Alias of self.weights
.
A list of variables.
weights
Returns the list of all layer variables/weights.
A list of variables.
__call__
__call__( inputs, *args, **kwargs )
Wraps call
, applying pre- and post-processing steps.
inputs
: input tensor(s).*args
: additional positional arguments to be passed to self.call
.**kwargs
: additional keyword arguments to be passed to self.call
.Output tensor(s).
training
: Boolean scalar tensor of Python boolean indicating
whether the call
is meant for training or inference.mask
: Boolean input mask.call
method takes a mask
argument (as some Keras
layers do), its default value will be set to the mask generated
for inputs
by the previous layer (if input
did come from
a layer that generated a corresponding mask, i.e. if it came from
a Keras layer with masking support.ValueError
: if the layer's call
method returns None (an invalid value).add_loss
add_loss( losses, inputs=None )
Add loss tensor(s), potentially dependent on layer inputs.
Some losses (for instance, activity regularization losses) may be dependent
on the inputs passed when calling a layer. Hence, when reusing the same
layer on different inputs a
and b
, some entries in layer.losses
may
be dependent on a
and some on b
. This method automatically keeps track
of dependencies.
This method can be used inside a subclassed layer or model's call
function, in which case losses
should be a Tensor or list of Tensors.
class MyLayer(tf.keras.layers.Layer): def call(inputs, self): self.add_loss(tf.abs(tf.reduce_mean(inputs)), inputs=True) return inputs
This method can also be called directly on a Functional Model during
construction. In this case, any loss Tensors passed to this Model must
be symbolic and be able to be traced back to the model's Input
s. These
losses become part of the model's topology and are tracked in get_config
.
inputs = tf.keras.Input(shape=(10,)) x = tf.keras.layers.Dense(10)(inputs) outputs = tf.keras.layers.Dense(1)(x) model = tf.keras.Model(inputs, outputs) # Actvity regularization. model.add_loss(tf.abs(tf.reduce_mean(x)))
If this is not the case for your loss (if, for example, your loss references
a Variable
of one of the model's layers), you can wrap your loss in a
zero-argument lambda. These losses are not tracked as part of the model's
topology since they can't be serialized.
inputs = tf.keras.Input(shape=(10,)) x = tf.keras.layers.Dense(10)(inputs) outputs = tf.keras.layers.Dense(1)(x) model = tf.keras.Model(inputs, outputs) # Weight regularization. model.add_loss(lambda: tf.reduce_mean(x.kernel))
The get_losses_for
method allows to retrieve the losses relevant to a
specific set of inputs.
losses
: Loss tensor, or list/tuple of tensors. Rather than tensors, losses
may also be zero-argument callables which create a loss tensor.inputs
: Ignored when executing eagerly. If anything other than None is
passed, it signals the losses are conditional on some of the layer's
inputs, and thus they should only be run where these inputs are
available. This is the case for activity regularization losses, for
instance. If None
is passed, the losses are assumed
to be unconditional, and will apply across all dataflows of the layer
(e.g. weight regularization losses).add_metric
add_metric( value, aggregation=None, name=None )
Adds metric tensor to the layer.
value
: Metric tensor.aggregation
: Sample-wise metric reduction function. If aggregation=None
,
it indicates that the metric tensor provided has been aggregated
already. eg, bin_acc = BinaryAccuracy(name='acc')
followed by
model.add_metric(bin_acc(y_true, y_pred))
. If aggregation='mean', the
given metric tensor will be sample-wise reduced using mean
function.
eg, model.add_metric(tf.reduce_sum(outputs), name='output_mean',
aggregation='mean')
.name
: String metric name.ValueError
: If aggregation
is anything other than None or mean
.add_update
add_update( updates, inputs=None )
Add update op(s), potentially dependent on layer inputs. (deprecated arguments)
Warning: SOME ARGUMENTS ARE DEPRECATED: (inputs)
. They will be removed in a future version.
Instructions for updating:
inputs
is now automatically inferred
Weight updates (for instance, the updates of the moving mean and variance
in a BatchNormalization layer) may be dependent on the inputs passed
when calling a layer. Hence, when reusing the same layer on
different inputs a
and b
, some entries in layer.updates
may be
dependent on a
and some on b
. This method automatically keeps track
of dependencies.
The get_updates_for
method allows to retrieve the updates relevant to a
specific set of inputs.
This call is ignored when eager execution is enabled (in that case, variable updates are run on the fly and thus do not need to be tracked for later execution).
updates
: Update op, or list/tuple of update ops, or zero-arg callable
that returns an update op. A zero-arg callable should be passed in
order to disable running the updates by setting trainable=False
on this Layer, when executing in Eager mode.inputs
: Deprecated, will be automatically inferred.add_weight
add_weight( name=None, shape=None, dtype=None, initializer=None, regularizer=None, trainable=None, constraint=None, partitioner=None, use_resource=None, synchronization=tf.VariableSynchronization.AUTO, aggregation=tf.compat.v1.VariableAggregation.NONE, **kwargs )
Adds a new variable to the layer.
name
: Variable name.shape
: Variable shape. Defaults to scalar if unspecified.dtype
: The type of the variable. Defaults to self.dtype
or float32
.initializer
: Initializer instance (callable).regularizer
: Regularizer instance (callable).trainable
: Boolean, whether the variable should be part of the layer's
"trainable_variables" (e.g. variables, biases)
or "non_trainable_variables" (e.g. BatchNorm mean and variance).
Note that trainable
cannot be True
if synchronization
is set to ON_READ
.constraint
: Constraint instance (callable).partitioner
: Partitioner to be passed to the Trackable
API.use_resource
: Whether to use ResourceVariable
.synchronization
: Indicates when a distributed a variable will be
aggregated. Accepted values are constants defined in the class
tf.VariableSynchronization
. By default the synchronization is set to
AUTO
and the current DistributionStrategy
chooses
when to synchronize. If synchronization
is set to ON_READ
,
trainable
must not be set to True
.aggregation
: Indicates how a distributed variable will be aggregated.
Accepted values are constants defined in the class
tf.VariableAggregation
.**kwargs
: Additional keyword arguments. Accepted values are getter
and
collections
.The created variable. Usually either a Variable
or ResourceVariable
instance. If partitioner
is not None
, a PartitionedVariable
instance is returned.
RuntimeError
: If called with partitioned variable regularization and
eager execution is enabled.ValueError
: When giving unsupported dtype and no initializer or when
trainable has been set to True with synchronization set as ON_READ
.build
build(input_shape)
Creates the variables of the layer (optional, for subclass implementers).
This is a method that implementers of subclasses of Layer
or Model
can override if they need a state-creation step in-between
layer instantiation and layer call.
This is typically used to create the weights of Layer
subclasses.
input_shape
: Instance of TensorShape
, or list of instances of
TensorShape
if the layer expects a list of inputs
(one instance per input).call
call( inputs, **kwargs )
This is where the layer's logic lives.
inputs
: Input tensor, or list/tuple of input tensors.**kwargs
: Additional keyword arguments.A tensor or list/tuple of tensors.
compute_mask
compute_mask( inputs, mask=None )
Computes an output mask tensor.
inputs
: Tensor or list of tensors.mask
: Tensor or list of tensors.None or a tensor (or list of tensors, one per output tensor of the layer).
compute_output_shape
compute_output_shape(input_shape)
Computes the output shape of the layer.
If the layer has not been built, this method will call build
on the
layer. This assumes that the layer will later be used with inputs that
match the input shape provided here.
input_shape
: Shape tuple (tuple of integers)
or list of shape tuples (one per output tensor of the layer).
Shape tuples can include None for free dimensions,
instead of an integer.An input shape tuple.
compute_output_signature
compute_output_signature(input_signature)
Compute the output tensor signature of the layer based on the inputs.
Unlike a TensorShape object, a TensorSpec object contains both shape
and dtype information for a tensor. This method allows layers to provide
output dtype information if it is different from the input dtype.
For any layer that doesn't implement this function,
the framework will fall back to use compute_output_shape
, and will
assume that the output dtype matches the input dtype.
input_signature
: Single TensorSpec or nested structure of TensorSpec
objects, describing a candidate input for the layer.Single TensorSpec or nested structure of TensorSpec objects, describing how the layer would transform the provided input.
TypeError
: If input_signature contains a non-TensorSpec object.count_params
count_params()
Count the total number of scalars composing the weights.
An integer count.
ValueError
: if the layer isn't yet built
(in which case its weights aren't yet defined).from_config
@classmethod from_config( cls, config )
Creates a layer from its config.
This method is the reverse of get_config
,
capable of instantiating the same layer from the config
dictionary. It does not handle layer connectivity
(handled by Network), nor weights (handled by set_weights
).
config
: A Python dictionary, typically the
output of get_config.A layer instance.
get_config
get_config()
Returns the config of the layer.
A layer config is a Python dictionary (serializable) containing the configuration of a layer. The same layer can be reinstantiated later (without its trained weights) from this configuration.
The config of a layer does not include connectivity
information, nor the layer class name. These are handled
by Network
(one layer of abstraction above).
Python dictionary.
get_input_at
get_input_at(node_index)
Retrieves the input tensor(s) of a layer at a given node.
node_index
: Integer, index of the node
from which to retrieve the attribute.
E.g. node_index=0
will correspond to the
first time the layer was called.A tensor (or list of tensors if the layer has multiple inputs).
RuntimeError
: If called in Eager mode.get_input_mask_at
get_input_mask_at(node_index)
Retrieves the input mask tensor(s) of a layer at a given node.
node_index
: Integer, index of the node
from which to retrieve the attribute.
E.g. node_index=0
will correspond to the
first time the layer was called.A mask tensor (or list of tensors if the layer has multiple inputs).
get_input_shape_at
get_input_shape_at(node_index)
Retrieves the input shape(s) of a layer at a given node.
node_index
: Integer, index of the node
from which to retrieve the attribute.
E.g. node_index=0
will correspond to the
first time the layer was called.A shape tuple (or list of shape tuples if the layer has multiple inputs).
RuntimeError
: If called in Eager mode.get_losses_for
get_losses_for(inputs)
Retrieves losses relevant to a specific set of inputs.
inputs
: Input tensor or list/tuple of input tensors.List of loss tensors of the layer that depend on inputs
.
get_output_at
get_output_at(node_index)
Retrieves the output tensor(s) of a layer at a given node.
node_index
: Integer, index of the node
from which to retrieve the attribute.
E.g. node_index=0
will correspond to the
first time the layer was called.A tensor (or list of tensors if the layer has multiple outputs).
RuntimeError
: If called in Eager mode.get_output_mask_at
get_output_mask_at(node_index)
Retrieves the output mask tensor(s) of a layer at a given node.
node_index
: Integer, index of the node
from which to retrieve the attribute.
E.g. node_index=0
will correspond to the
first time the layer was called.A mask tensor (or list of tensors if the layer has multiple outputs).
get_output_shape_at
get_output_shape_at(node_index)
Retrieves the output shape(s) of a layer at a given node.
node_index
: Integer, index of the node
from which to retrieve the attribute.
E.g. node_index=0
will correspond to the
first time the layer was called.A shape tuple (or list of shape tuples if the layer has multiple outputs).
RuntimeError
: If called in Eager mode.get_updates_for
get_updates_for(inputs)
Retrieves updates relevant to a specific set of inputs.
inputs
: Input tensor or list/tuple of input tensors.List of update ops of the layer that depend on inputs
.
get_weights
get_weights()
Returns the current weights of the layer.
Weights values as a list of numpy arrays.
set_weights
set_weights(weights)
Sets the weights of the layer, from Numpy arrays.
weights
: a list of Numpy arrays. The number
of arrays and their shape must match
number of the dimensions of the weights
of the layer (i.e. it should match the
output of get_weights
).ValueError
: If the provided weights list does not match the
layer's specifications.


'Imran Khan-led govt's days are numbered,' warns Pak cleric Fazlur Rehman
alleging that the 'selected' government has offered National Reconciliation Ordinance (NRO) to Khan's sister.
by PTIKarachi: Firebrand cleric-cum-politician Maulana Fazlur Rehman has fired a fresh salvo at Prime Minister Imran Khan, saying the "Gorbachev of Pakistan" was heading a government that has its days numbered.
Speaking at a sit-in in Bannu city in southern Khyber Pakhtunkhwa on Tuesday, the hard-line cleric and leader of the Jamiat Ulema-e-Islam-Fazl (JUI-F) hit out at the prime minister for calling opposition leaders "thieves", alleging that the "selected" government has offered National Reconciliation Ordinance (NRO) to Khan's sister.
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ANDROID API
The ANDROID client API allows mobile applications to send and receive real-time messages via the PushFYI server. The ANDROID API uses WebSocket interface to connect to PushFYI and exchange real-time messages.
The ANDROID API has 3 main functions in addition to 2 helper functions. In this documentation we will examine the API usage and some of the best practices.
init()
The init method allows a mobile client to connect to PushFYI WebSocket gateway to send and receive real-time messages. It is important for a client application to first connect to PushFYI prior to sending or receiving any real-time messages. Hence, this must be the first method that your client application will call in order to use PushFYI real-time transport.
This PushFYI Android init method is invoked after creating pushfyi object constructor ,Which takes listener as an argument to get pushfyi connection states.
API Prototype:
Pushfyi pushfyi = new Pushfyi(appsecret, address, secure);
API Sample Usage:
pushfyi = new Pushfyi("<your appsecret key>",
"<your pushfyi ip address>","<boolean variable for secure/plain text connection>");
pushfyi.init(callback);
Parameter List:
| SN | parameters | note |
|---|---|---|
| 1 | appsecret | This parameter identifies your App when it connects to PushFYI. Since PushFYI can serve real-time messages to many apps simultaneously. This field allows PushFYI to distinguish between Apps, so that real-time messages from one App do not mix up with another App. The value of appsecret parameter is in UUID format. e.g. 123e4567-e89b-12d3-a456-426655440000 |
| 2 | address | URL of your pushfyi instance. e.g. <IP_ADDRESS> |
| 3 | secure | Boolean variable for secure/plain text connection. |
Code Sample:
/**
* create Pushfyi instance
*/
Pushfyi pushfyi= new Pushfyi("<your appsecret key>",
"<your pushfyi ip address>","<boolean variable for secure/plain text connection>");
/**
* initialise Pushfyi
*/
pushfyi.init(new ConnectionListener() {
@Override
public void onConnected() {
Log.i("tag", "connected");
}
@Override
public void onConnectionFail(final PushfyiException pushfyiError) {
mConnectionState.setText("connection failed");
}
}
);
subscribe()
The subscribe method allows a mobile client to register their interest in a given data channel and returns a Channel.Channel is bound with listener to get subscribed data. PushFYI data channels are logical names to which real-time messages are sent and received. Once the connection is established using the init method, your application can make a call to subscribe method to show interest in a specified data channel.
API Prototype:
Channel channel=pushfyi.subscribe("my_data_channel");
channel.bind(callback);
API Sample Usage:
Channel channel=pushfyi.subscribe("my_data_channel");
channel.bind(new SubsciptionEventListener() {
@Override
public void onSubscriptionEvent(String channelName, String data) {
Log.i("tag","subscribed data "+data+" from channel "+channelName);
}
});
Parameter List:
| SN | parameters | note |
|---|---|---|
| 1 | channel | The logical name of the data channel associated with an event. |
| 2 | callback | A callback function to call when the API receives an event with the given data channel. |
Code Sample:
/**
* create Pushfyi instance
*/
Pushfyi pushfyi= new Pushfyi("<your appsecret key>",
"<your pushfyi ip address>","<boolean variable for secure/plain text connection>");
/**
* initialise Pushfyi
*/
pushfyi.init(new ConnectionListener() {
@Override
public void onConnected() {
Log.i("tag", "connected");
}
@Override
public void onConnectionFail(final PushfyiException pushfyiError) {
mConnectionState.setText("connection failed");
}
}
);
Channel channel=pushfyi.subscribe("my_data_channel");
channel.bind(new SubsciptionEventListener() {
@Override
public void onSubscriptionEvent(String channelName, String data) {
Log.i("tag","subscribed data "+data+" from channel "+channelName);
}
});
publish()
The publish method allows a mobile client to publish a real-time message on a given data channel. PushFYI data channels are logical names to which real-time messages are sent and received. Once the connection is established using the init method, your application can make a call to publish method to send a real-time message on the specified data channel.
API Prototype:
pushfyi.publish("my_data_channel", data);
API Sample Usage:
pushfyi.publish("my_data_channel", {name: 'Henry', message: 'Hi, how are you doing?'});
Parameter List:
| SN | parameters | note |
|---|---|---|
| 1 | channel | The logical name of the data channel associated with an event. |
| 2 | params | Data to send in the real-time message. Data is in string format. |
Code Sample:
/**
* create Pushfyi instance
*/
Pushfyi pushfyi= new Pushfyi("<your appsecret key>",
"<your pushfyi ip address>","<boolean variable for secure/plain text connection>");
/**
* initialise Pushfyi
*/
pushfyi.init(new ConnectionListener() {
@Override
public void onConnected() {
Log.i("tag", "connected");
}
@Override
public void onConnectionFail(final PushfyiException pushfyiError) {
mConnectionState.setText("connection failed");
}
}
);
Channel channel=pushfyi.subscribe("my_data_channel");
channel.bind(new SubsciptionEventListener() {
@Override
public void onSubscriptionEvent(String channelName, String data) {
Log.i("tag","subscribed data "+data+" from channel "+channelName);
}
});
JSONObject jsonObject = new JSONObject();
try {
jsonObject.put("name", "Henry");
jsonObject.put("message","How are you doing?");
//publish data on given channel
mPushfyi.publish(channelName, jsonObject.toString());
} catch (JSONException e) {
e.printStackTrace();
}


Summary. The purpose of this document is to test LaTeX math in DocOnce with various output formats. Most LaTeX math constructions are renedered correctly by MathJax in plain HTML, but some combinations of constructions may fail. Unfortunately, only a subset of what works in html MathJax also works in sphinx MathJax. The same is true for markdown MathJax expresions (e.g., Jupyter notebooks). Tests and examples are provided to illustrate what may go wrong.
The recommendation for writing math that translates to MathJax in
html, sphinx, and markdown is to stick to the environments \[
... \]
, equation
, equation*
, align
, align*
, alignat
, and
alignat*
only. Test the math with sphinx output; if it works in that
format, it should work elsewhere too.
The current version of the document is translated from DocOnce source to the format html.
We can get an inline equation
$u(t)=e^{-at}$
rendered as \( u(t)=e^{-at} \).
An equation with number,
!bt
\begin{equation} u(t)=e^{-at} label{eq1a}\end{equation}
!et
looks like $$ \begin{equation} u(t)=e^{-at} \label{eq1a}\end{equation} $$ Maybe this multi-line version is what we actually prefer to write:
!bt
\begin{equation}
u(t)=e^{-at}
label{eq1b}
\end{equation}
!et
The result is the same:
$$
\begin{equation}
u(t)=e^{-at} \label{eq1b}
\end{equation}
$$
We can refer to this equation through its label eq1b
: \eqref{eq1b}.
MathJax has historically had some problems with rendering many LaTeX
math environments, but the align*
and align
environments have
always worked.
!bt
\begin{align*}
u(t)&=e^{-at}\\
v(t) - 1 &= \frac{du}{dt}
\end{align*}
!et
Result: $$ \begin{align*} u(t)&=e^{-at}\\ v(t) - 1 &= \frac{du}{dt} \end{align*} $$
Here, we use align
with user-prescribed labels:
!bt
\begin{align}
u(t)&=e^{-at}
label{eq2b}\\
v(t) - 1 &= \frac{du}{dt}
label{eq3b}
\end{align}
!et
Result: $$ \begin{align} u(t)&=e^{-at} \label{eq2b}\\ v(t) - 1 &= \frac{du}{dt} \label{eq3b} \end{align} $$ We can refer to the last equations as the system \eqref{eq2b}-\eqref{eq3b}.
In LaTeX, equations within an align
environment is automatically
given numbers. To ensure that an html document with MathJax gets the
same equation numbers as its latex/pdflatex companion, DocOnce
generates labels in equations where there is no label prescribed. For
example,
!bt
\begin{align}
u(t)&=e^{-at}
\\
v(t) - 1 &= \frac{du}{dt}
\end{align}
!et
is edited to something like
!bt
\begin{align}
u(t)&=e^{-at}
label{_auto5}\\
v(t) - 1 &= \frac{du}{dt}
label{_auto6}
\end{align}
!et
and the output gets the two equation numbered. $$ \begin{align} u(t)&=e^{-at} \label{_auto1}\\ v(t) - 1 &= \frac{du}{dt} \label{_auto2} \end{align} $$
The align
environment can be used with two &
alignment characters, e.g.,
!bt
\begin{align}
\frac{\partial u}{\partial t} &= \nabla^2 u, & x\in (0,L),
\ t\in (0,T]\\
u(0,t) &= u_0(x), & x\in [0,L]
\end{align}
!et
The result in html becomes $$ \begin{align} \frac{\partial u}{\partial t} &= \nabla^2 u, & x\in (0,L), \ t\in (0,T] \label{_auto3}\\ u(0,t) &= u_0(x), & x\in [0,L] \label{_auto4} \end{align} $$
A better solution is usually to use an alignat
environment:
!bt
\begin{alignat}{2}
\frac{\partial u}{\partial t} &= \nabla^2 u, & x\in (0,L),
\ t\in (0,T]\\
u(0,t) &= u_0(x), & x\in [0,L]
\end{alignat}
!et
with the rendered result $$ \begin{alignat}{2} \frac{\partial u}{\partial t} &= \nabla^2 u, & x\in (0,L), \ t\in (0,T]\\ u(0,t) &= u_0(x), & x\in [0,L] \end{alignat} $$
Let us try the old eqnarray*
environment.
!bt
\begin{eqnarray*}
u(t)&=& e^{-at}\\
v(t) - 1 &=& \frac{du}{dt}
\end{eqnarray*}
!et
which results in $$ \begin{eqnarray*} u(t)&=& e^{-at}\\ v(t) - 1 &=& \frac{du}{dt} \end{eqnarray*} $$
Here we use eqnarray
with labels:
!bt
\begin{eqnarray}
u(t)&=& e^{-at}
label{eq2c}\\
v(t) - 1 &=& \frac{du}{dt}
label{eq3c}
\end{eqnarray}
!et
which results in $$ \begin{eqnarray} u(t)&=& e^{-at} \label{eq2c}\\ v(t) - 1 &=& \frac{du}{dt} \label{eq3c} \end{eqnarray} $$ Can we refer to the last equations as the system \eqref{eq2c}-\eqref{eq3c} in the html format?
multiline
environment with label and number The LaTeX code
!bt
\begin{multline}
\int_a^b f(x)dx = \sum_{j=0}^{n} \frac{1}{2} h(f(a+jh) +
f(a+(j+1)h)) \\
=\frac{h}{2}f(a) + \frac{h}{2}f(b) + \sum_{j=1}^n f(a+jh)
label{multiline:eq1}
\end{multline}
!et
gets rendered as $$ \begin{multline} \int_a^b f(x)dx = \sum_{j=0}^{n} \frac{1}{2} h(f(a+jh) + f(a+(j+1)h)) \\ =\frac{h}{2}f(a) + \frac{h}{2}f(b) + \sum_{j=1}^n f(a+jh) \label{multiline:eq1} \end{multline} $$ and we can hopefully refer to the Trapezoidal rule as the formula \eqref{multiline:eq1}.
Although align
can be used to split too long equations, a more obvious
command is split
:
!bt
\begin{equation}
\begin{split}
\int_a^b f(x)dx = \sum_{j=0}^{n} \frac{1}{2} h(f(a+jh) +
f(a+(j+1)h)) \\
=\frac{h}{2}f(a) + \frac{h}{2}f(b) + \sum_{j=1}^n f(a+jh)
\end{split}
\end{equation}
!et
The result becomes $$ \begin{equation} \begin{split} \int_a^b f(x)dx = \sum_{j=0}^{n} \frac{1}{2} h(f(a+jh) + f(a+(j+1)h)) \\ =\frac{h}{2}f(a) + \frac{h}{2}f(b) + \sum_{j=1}^n f(a+jh) \end{split} \label{_auto5} \end{equation} $$
First we use the plain old pmb package for bold math. The formula
!bt
\[ \frac{\partial\u}{\partial t} +
\u\cdot\nabla\u = \nu\nabla^2\u -
\frac{1}{\varrho}\nabla p,\]
!et
and the inline expression $\nabla\u (\x)\cdot\normalvec$
(with suitable newcommands using pmb)
get rendered as
$$ \frac{\partial\u}{\partial t} +
\u\cdot\nabla\u = \nu\nabla^2\u -
\frac{1}{\varrho}\nabla p,$$
and \( \nabla\u (\x)\cdot\normalvec \).
Somewhat nicer fonts may appear with the more modern \bm
command:
!bt
\[ \frac{\partial\ubm}{\partial t} +
\ubm\cdot\nabla\ubm = \nu\nabla^2\ubm -
\frac{1}{\varrho}\nabla p,\]
!et
(backslash ubm
is a newcommand for bold math \( u \)), for which we get
$$ \frac{\partial\ubm}{\partial t} +
\ubm\cdot\nabla\ubm = \nu\nabla^2\ubm -
\frac{1}{\varrho}\nabla p.$$
Moreover,
$\nabla\boldsymbol{u}(\boldsymbol{x})\cdot\boldsymbol{n}$
becomes \( \nabla\boldsymbol{u}(\boldsymbol{x})\cdot\boldsymbol{n} \).
Note: for the html format, \bm
was substituted by DocOnce
to \boldsymbol
.
Finally, we collect some problematic formulas in MathJax. They all work fine in LaTeX. Most of them look fine in html too, but some fail in sphinx, ipynb, or markdown.
The LaTeX code
!bt
\[ {\color{blue}\frac{\partial\u}{\partial t}} +
\nabla\cdot\nabla\u = \nu\nabla^2\u -
\frac{1}{\varrho}\nabla p,\]
!et
results in $$ {\color{blue}\frac{\partial\u}{\partial t}} + \nabla\cdot\nabla\u = \nu\nabla^2\u - \frac{1}{\varrho}\nabla p,$$
Sometimes one must be extra careful with the LaTeX syntax to get sphinx MathJax to render a formula correctly. Consider the combination of a bar over a bold math symbol:
!bt
\[ \bar\f = f_c^{-1}\f,\]
!et
which for html output results in $$ \bar\f = f_c^{-1}\f.$$
With sphinx, this formula is not rendered. However, using curly braces for the bar,
!bt
\[ \bar{\f} = f_c^{-1}\f,\]
!et
makes the output correct also for sphinx: $$ \bar{\f} = f_c^{-1}\f,$$
Here is an align
environment with a label and the pmatrix
environment for matrices and vectors in LaTeX.
!bt
\begin{align}
\begin{pmatrix}
G_2 + G_3 & -G_3 & -G_2 & 0 \\
-G_3 & G_3 + G_4 & 0 & -G_4 \\
-G_2 & 0 & G_1 + G_2 & 0 \\
0 & -G_4 & 0 & G_4
\end{pmatrix}
&=
\begin{pmatrix}
v_1 \\
v_2 \\
v_3 \\
v_4
\end{pmatrix}
+ \cdots
label{mymatrixeq}\\
\begin{pmatrix}
C_5 + C_6 & -C_6 & 0 & 0 \\
-C_6 & C_6 & 0 & 0 \\
0 & 0 & 0 & 0 \\
0 & 0 & 0 & 0
\end{pmatrix}
\frac{d}{dt} &=
\begin{pmatrix}
v_1 \\
v_2 \\
v_3 \\
v_4
\end{pmatrix} =
\begin{pmatrix}
0 \\
0 \\
0 \\
-i_0
\end{pmatrix}
\end{align}
!et
which becomes $$ \begin{align} \begin{pmatrix} G_2 + G_3 & -G_3 & -G_2 & 0 \\ -G_3 & G_3 + G_4 & 0 & -G_4 \\ -G_2 & 0 & G_1 + G_2 & 0 \\ 0 & -G_4 & 0 & G_4 \end{pmatrix} &= \begin{pmatrix} v_1 \\ v_2 \\ v_3 \\ v_4 \end{pmatrix} + \cdots \label{mymatrixeq}\\ \begin{pmatrix} C_5 + C_6 & -C_6 & 0 & 0 \\ -C_6 & C_6 & 0 & 0 \\ 0 & 0 & 0 & 0 \\ 0 & 0 & 0 & 0 \end{pmatrix} \frac{d}{dt} &= \begin{pmatrix} v_1 \\ v_2 \\ v_3 \\ v_4 \end{pmatrix} = \begin{pmatrix} 0 \\ 0 \\ 0 \\ -i_0 \end{pmatrix} \end{align}$$
The same matrices without labels in an align*
environment:
!bt
\begin{align*}
\begin{pmatrix}
G_2 + G_3 & -G_3 & -G_2 & 0 \\
-G_3 & G_3 + G_4 & 0 & -G_4 \\
-G_2 & 0 & G_1 + G_2 & 0 \\
0 & -G_4 & 0 & G_4
\end{pmatrix}
&=
\begin{pmatrix}
v_1 \\
v_2 \\
v_3 \\
v_4
\end{pmatrix}
+ \cdots \\
\begin{pmatrix}
C_5 + C_6 & -C_6 & 0 & 0 \\
-C_6 & C_6 & 0 & 0 \\
0 & 0 & 0 & 0 \\
0 & 0 & 0 & 0
\end{pmatrix}
\frac{d}{dt} &=
\begin{pmatrix}
v_1 \\
v_2 \\
v_3 \\
v_4
\end{pmatrix} =
\begin{pmatrix}
0 \\
0 \\
0 \\
-i_0
\end{pmatrix}
\end{align*}
!et
The rendered result becomes $$ \begin{align*} \begin{pmatrix} G_2 + G_3 & -G_3 & -G_2 & 0 \\ -G_3 & G_3 + G_4 & 0 & -G_4 \\ -G_2 & 0 & G_1 + G_2 & 0 \\ 0 & -G_4 & 0 & G_4 \end{pmatrix} &= \begin{pmatrix} v_1 \\ v_2 \\ v_3 \\ v_4 \end{pmatrix} + \cdots \\ \begin{pmatrix} C_5 + C_6 & -C_6 & 0 & 0 \\ -C_6 & C_6 & 0 & 0 \\ 0 & 0 & 0 & 0 \\ 0 & 0 & 0 & 0 \end{pmatrix} \frac{d}{dt} &= \begin{pmatrix} v_1 \\ v_2 \\ v_3 \\ v_4 \end{pmatrix} = \begin{pmatrix} 0 \\ 0 \\ 0 \\ -i_0 \end{pmatrix} \end{align*} $$


44
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Welcome
Complete Name
Email Address
I´m not Robot
Enter
Travel Music
Hear, Sing, Dancing
and Communicates
Enjoy your music and dancing with your life


+++ title = "Rio de Janeiro" lat = -22.904324 lon = -43.209915 +++
Does Rio really need a description? It's so famous — I hardly think so. Beautiful beaches, beautiful weather, and beautiful people. Surf, sand, and parties every night. Amidst it all, the extreme violence and poverty of the favelas. And looking over the entire city, Christ the Redeemer — now one of the new seven wonders of the world. Rio is my grand finale end to South America, and what better place could there be, to finish up and to relax for a bit?


{% extends "base_site.html" %} {% load admin_static %} {% block title %} OQMD {% endblock %} {% block content_title %}
The OQMD is a database DFT calculated thermodynamic and structural properties. We are providing this online interface for convenient, small scale access; however for more powerful utilization we recommend downloading the entire database and the API for interfacing with it, detailed in the link below.
The OQMD was created in Chris Wolverton's group at Northwestern University.


Business Control Manager at a Fortune 50 company with a focus on Compliance / Operational Risk. Recent Graudate of Full-Stack Development BootCcamp with the University of Penn. I strive to provide support and help obtain deeper insight by asking the simple questions. Tell me more about your concerns and problems, and let’s figure out the solutions together! Please contact me for a conversation. Thank you!
ResumeFeel free to browse any code through my Github Account or directly through the pictures below. See more at my LinkedIn Profile.
GitHub Account LinkedIn ProfileReady to start your next project with a fresh perspective? Give me a call or send me an email and I will get back to you as soon as possible!


*** User 2017-04-18 14:17:32.603 ***
14:17:32.603 [info] Disabling blocking sync...
*** User 2017-04-18 14:17:32.607 ***
14:17:32.607 [info] Configured peer_service_manager partisan_default_peer_service_manager on node 'node-1@MBPdeAnneFrance'
*** User 2017-04-18 14:17:34.060 ***
14:17:34.059 [info] Enabling membership...
*** User 2017-04-18 14:17:34.061 ***
14:17:34.061 [info] Disabling blocking sync...
*** User 2017-04-18 14:17:34.065 ***
14:17:34.065 [info] Configured peer_service_manager partisan_default_peer_service_manager on node 'node-2@MBPdeAnneFrance'
*** User 2017-04-18 14:17:35.522 ***
14:17:35.522 [info] Enabling membership...
*** User 2017-04-18 14:17:35.523 ***
14:17:35.523 [info] Disabling blocking sync...
*** User 2017-04-18 14:17:35.528 ***
14:17:35.528 [info] Configured peer_service_manager partisan_default_peer_service_manager on node 'node-3@MBPdeAnneFrance'
*** User 2017-04-18 14:17:35.766 ***
Joining node: 'node-3@MBPdeAnneFrance' to runner@MBPdeAnneFrance at port 50232
*** User 2017-04-18 14:17:35.766 ***
Joining issued: 'node-3@MBPdeAnneFrance' to runner@MBPdeAnneFrance at port 50232
*** User 2017-04-18 14:17:35.766 ***
Joining node: 'node-2@MBPdeAnneFrance' to runner@MBPdeAnneFrance at port 50217
*** User 2017-04-18 14:17:35.767 ***
Joining issued: 'node-2@MBPdeAnneFrance' to runner@MBPdeAnneFrance at port 50217
*** User 2017-04-18 14:17:35.767 ***
Joining node: 'node-1@MBPdeAnneFrance' to runner@MBPdeAnneFrance at port 50206
*** User 2017-04-18 14:17:35.768 ***
Joining issued: 'node-1@MBPdeAnneFrance' to runner@MBPdeAnneFrance at port 50206
*** User 2017-04-18 14:17:35.829 ***
Waiting for join to complete with manager: partisan_default_peer_service_manager
*** User 2017-04-18 14:17:35.830 ***
Finished.
*** CT 2017-04-18 14:17:35.830 *** COVER INFO
Adding nodes to cover test: [runner@MBPdeAnneFrance]
*** CT 2017-04-18 14:17:35.839 *** COVER INFO
Successfully added nodes to cover test: []
*** User 2017-04-18 14:17:43.863 ***
Case finished: filter_test
*** User 2017-04-18 14:17:50.905 ***
14:17:50.904 [info] Application lasp exited with reason: stopped
*** User 2017-04-18 14:17:50.905 ***
14:17:50.905 [info] Application partisan exited with reason: stopped
=== Ended at 2017-04-18 14:17:50
=== successfully completed test case
=== Returned value: ok
Test run history
| Top level test index


Domains¶
Get domain¶
To retrieve a specific domain, you will need the domain’s id, not its domain name:
$domain = $service->domain('{domainId}');
If you are having trouble remembering or accessing the domain ID, you can do a domain list search for your domain and then access its ID.
List domains¶
These calls provide a list of all DNS domains manageable by a given account. The resulting list is flat, and does not break the domains down hierarchically by subdomain. All representative domains are included in the list, even if a domain is conceptually a subdomain of another domain in the list.
$domains = $service->domainList();
# Return detailed information for each domain
$domains = $service->domainList(true);
Filter parameters¶
You can filter the search by using the name parameter in a key/value array supplied as a method argument. For example, to retrieve domains named foo.com, along with any subdomains like bar.foo.com:
$hoolaDomains = $service->domainList(array(
'name' => 'foo.com'
));
Filter criteria may consist of:
- Any letter (A-Za-z)
- Numbers (0-9)
- Hyphen (“-”)
- 1 to 63 characters
Filter criteria should not include any of the following characters:
‘ + , | ! ” £ $ % & / ( ) = ? ^ * ç ° § ; : _ > ] [ @ à, é, ò
Finding a domain ID¶
Once you have a list of domains, to retrieve a domain’s ID:
foreach ($domains as $domain) {
$id = $domain->id;
}
List domain changes¶
This call shows all changes to the specified domain since the specified date/time. To list all available changes for a domain for the current day:
$changes = $domain->changes();
For more granular control, you can manually define the since parameter like so:
$since = date('c', strtotime('last week'));
$changes = $domain->changes($since);
Once you have a set of changes, you can iterate over them like so:
foreach ($changes->changes as $change) {
printf("Domain: %s\nAction: %s\nTarget: %s", $change->domain, $change->action, $change->targetType);
foreach ($change->changeDetails as $detail) {
printf("Details: %s was changed from %s to %s", $detail->field, $detail->oldValue, $detail->newValue);
}
}
Create domain¶
The first thing you will need to do is instantiate a new object and set the primary A record for the DNS domain, like so:
// get empty object
$domain = $service->domain();
// add A record
$aRecord = $domain->record(array(
'type' => 'A',
'name' => 'example.com',
'data' => '<IP_ADDRESS>',
'ttl' => 3600
));
$domain->addRecord($aRecord);
You also have the option of adding more types of DNS records such as CNAME, MX and NS records. This step is completely optional and depends on your requirements:
// add CNAME record
$cRecord = $domain->record(array(
'type' => 'CNAME',
'name' => 'www.example.com',
'data' => 'example.com',
'ttl' => 3600
));
$domain->addRecord($cRecord);
// add MX record
$mxRecord = $domain->record(array(
'type' => 'MX',
'data' => 'mail.example.com',
'name' => 'example.com',
'ttl' => 3600,
'priority' => 5
));
$domain->addRecord($mxRecord);
// add NS record
$nsRecord = $domain->record(array(
'type' => 'NS',
'data' => 'dns1.stabletransit.com',
'name' => 'example.com',
'ttl' => 5400
));
$domain->addRecord($nsRecord);
You can also add sub-domains to your new DNS domain. Again, this is completely optional:
$subdomain = $domain->subdomain(array(
'emailAddress' =><EMAIL_ADDRESS>'name' => 'dev.example.com',
'comment' => 'Dev portal'
));
$domain->addSubdomain($subdomain);
Once you’ve finished configuring how your DNS domain will work, you’re ready to specify the essential details and send it to the API for creation:
$domain->create(array(
'emailAddress' =><EMAIL_ADDRESS>'ttl' => 3600,
'name' => 'example.com',
'comment' => 'Optional comment'
));
Clone domain¶
This call will duplicate an existing domain under a new name. By default, all records and, optionally, subdomains are duplicated as well.
The method signature you will need to use is:
- cloneDomain($newDomainName[, $subdomains[, $comments[, $email[, $records]]]])¶
Clone a domain
Parameters: - $newDomainName (string) – The name of the new domain entry
- $subdomains (bool) – Set to true to clone all the subdomains for this domain
- $comments (bool) – Set to true to replace occurrences of the reference domain name with the new domain name in comments on the cloned (new) domain.
- $email (bool) – Set to true to replace occurrences of the reference domain name with the new domain name in data fields (of records) on the cloned (new) domain. Does not affect NS records.
- $records (bool) – Set to true to replace occurrences of the reference domain name with the new domain name in data fields (of records) on the cloned (new) domain. Does not affect NS records.
For example:
$asyncResponse = $domain->cloneDomain('new-name.com', true, false, true, false);
Export domain¶
This call provides access to the BIND (Berkeley Internet Name Domain) 9 for the requested domain. This call is for a single domain only, and as such, does not traverse up or down the domain hierarchy for details:
$asyncResponse = $domain->export();
$body = $asyncResponse->waitFor('COMPLETED');
echo $body['contents'];
Import domain¶
This operation will create a new DNS domain according to a BIND (Berkeley Internet Name Domain) 9 formatted value.
In order for the BIND value to be considered valid, it needs to adhere to the following rules:
Each record starts on a new line and on the first column. If a record will not fit on one line, use the BIND_9 line continuation convention where you put a left parenthesis and continue the one record on the next line and put a right parenthesis when the record ends. For example:
example2.net. 3600 IN SOA dns1.stabletransit.com<EMAIL_ADDRESS>1308874739 3600 3600 3600 3600)
The attribute values of a record must be separated by a single blank or tab. No other white space characters.
If there are any NS records, the data field should not be dns1.stabletransit.com or dns2.stabletransit.com. They will result in “duplicate record” errors.
For example:
$bind9Data = <<<EOT
example.net. 3600 IN SOA dns1.stabletransit.com<EMAIL_ADDRESS>1308874739 3600 3600 3600 3600
example.net. 86400 IN A <IP_ADDRESS>
example.net. 3600 IN MX 5 mail2.example.net.
www.example.net. 5400 IN CNAME example.net.
EOT;
$asyncResponse = $service->import($bind9Data);
Modify domain¶
Only the TTL, email address and comment attributes of a domain can be modified. Records cannot be added, modified, or removed through this API operation - you will need to use the add records, modify records or remove records operations respectively.
$domain->update(array(
'ttl' => ($domain->ttl + 100),
'emailAddress' =><EMAIL_ADDRESS>));
Delete domain¶
$domain->delete();


Woman Flies 500 Miles To Lose Virginity To Polyamorous Couple
by Emma RosemurgeyA woman has told how she travelled more than 500 miles to lose her virginity to a 42-year-old man and his girlfriend – and now they all live together as a ‘throuple’.
Advertisements
Gabrielle Reese met Jacob Boswell and Megan Muirhead on a sugar daddy website at the tender age of 18.
Now 21, Gabrielle has spent the last three years living with the couple in Salt Lake City, Utah, where she admits that although they’re happy together, jealousy is a big threat in their relationship.
Advertisements
The three of them spoke online for three months before Gabrielle, from Idaho, travelled to visit the couple, where she lost her virginity ‘that first weekend’.
‘I did lose my virginity that first weekend,’ Gabrielle recalled. ‘We never really discussed that as the plan, but we were all interested and open to the idea.’
The 21-year-old continued:
The whole thing was exciting and new. We all clicked very fast and there was a lot of chemistry – we were all involved that first night.
There were definitely positives. Jacob and Megan are both older, while I had no experience.
Losing my virginity to a guy and a girl, being bisexual, I got to experience all aspects of my sexuality, too. Girls are soft, delicate and nurturing, while men are more dominant.
I’d never thought that much about how I would lose my virginity, but I guess it wasn’t what I predicted. I don’t have any regrets though – we’re still here three years later.
The graphic designer admitted she’s ‘always liked older guys’ and even warned her parents that she planned to marry someone their age.
Advertisements
This interest, she says, stopped her from forming any romantic relationships with boys her own age growing up.
So, after turning 18, she joined a sugar daddy website, and in October 2016, she found Jacob and Megan and agreed to meet them a few days before her 19th birthday.
Gabrielle says she was honest with her parents, Don, 46, and Kathea, 44, but they weren’t happy about it.
Advertisements
She said:
My family knew but they weren’t too happy. But I was very, very honest.
Growing up, I’d warned my parents I wanted to marry someone their age, but I think they thought I was joking.
I’ve always known I liked older guys – and girls too – so when I saw on Jacob’s website profile that he had a girlfriend, too, he checked all the boxes.
But I told my parents I was flying from Idaho to Utah for a first date with a couple I’d only Facetimed once before, so I do understand why they were concerned.
When she first arrived in Utah, Gabrielle spent time with Jacob before moving on to become a ‘trouple’ that night and the next day.
She recalled:
Megan had work, so Jacob and I went to their house and hung out, watching TV and got dinner.
It was all very normal and that’s what we did when Megan finished work too.
After spending our first night together Megan told me she loved me and she wanted me to move in – I was like, ‘Who knows?’
That first night I lost my virginity and yeah. I was nervous about the whole experience – but in a good way. The nerves were definitely worth it.
I knew that I wanted to do it. I don’t think I could have had a better experience for my first time – it was so intimate and perfect.
Upon her return to Idaho, Gabrielle found herself constantly messaging Megan and Jacob, which has becoming increasingly romantic. So, she asked them if they had been serious about their offer to move her in.
‘They said they were 100 per cent up for me moving in,’ Gabrielle said. ‘A month later that’s just what I did.’
The 21-year-old continued:
I’d never been in a relationship before, let alone moved states for two people – one of whom was in his 40s and the other a girl.
This was my first ever relationship, I was moving in after meeting them once, and being invited straight into a shared bedroom – it was a huge adjustment.
It did feel weird at times, but I think anyone’s first relationship does, and at the same time, somehow it just worked.
Although the threesome enjoy a happy relationship, Gabrielle is conscious of people poking fun of their relationship and assuming it’s purely sexual.
She said:
I’ve never had anyone say anything negative to my face, but you can see it in their faces as soon as they find out.
People tend to sexualise it and ask a lot of invasive questions that they would not ask anyone else.
They ask how it works and whether we are happy – like they have a right to know.
But with any relationship there’s problems and the only difference is we have one extra person.
An extra person requires extra passion, extra patience and extra compassion – of course we have ups and downs.
Gabrielle cites jealousy as being the main threat to their harmonious relationship:
There’s definitely been jealously throughout the relationship – it ebbs and flows. It’s not a feeling I want to have, so it’s something we work on as a triad.
It’s hard not to get those feelings when the other two are going on a date and you’re not invited, but you learn to accept it and let it flow.
Once you come to realise it isn’t all about who likes who more – it’s about timing – it gets easier.
For example, Megan works a lot at the moment, so Jacob and I see a lot more of each other. So, if he’s had a stressful day and needs to work it out we’ll deal with that solo in the bedroom.
But we have a healthy sex life together. One month we have sex five times a week, another month it will be once a week.
I’m totally happy being with Jacob and Megan sexually for the rest of my life – I don’t care about anyone else.
Gabrielle is even keen to have children with the pair later down the line, and says although there’s no legal way for them all to marry, ‘a ceremony would be nice at some point’.
Fortunately, Gabrielle’s parents have now come to accept their relationship, explaining:
I think they’re just happy I didn’t get kidnapped or locked in a basement after that first weekend.
While being poly works for the triad, Jacob has revealed he gets more of a reaction about the age gap than about being poly.
Jacob, who is 24 years older than Gabrielle and 15 years old than Megan, said:
When people hear I have two girlfriends they always go, ‘Well done,’ but when they hear about the age gap they imply it’s not ok, as if I am cradle snatching.
It’s very demeaning, as Gabrielle is smart, brilliant and intelligent – she doesn’t need saving. Give her some credit, please.
It’s not been as direct as saying, ‘You’re a monster.’ It’s more subtle, like, why would someone my age want to date someone Gabrielle’s age. It’s simple – she’s hot.
Emma Rosemurgey is an NCTJ trained Journalist who started her career by producing The Royal Rosemurgey newspaper in 2004, which kept her family up to date with the goings on of her sleepy north east village. She graduated from the University of Central Lancashire in Preston and started her career in regional newspapers before joining Tyla (formerly Pretty 52) in 2017, and progressing onto UNILAD in 2019.


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Use with pleasure! Make your first order above 15,000 tenge
and get a new year's gift from our store for any choice!


Sorry to see you go! HabitLab has been uninstalled
Thanks for trying HabitLab! We'd appreciate your feedback so we can make it better! Why are you uninstalling?
Here are some possible reasons for uninstalling and how to fix them:
Disabling Annoying Interventions
You can disable interventions on the Settings page, which you can access by clicking the icon in the Chrome toolbar and clicking "Settings".
You can also disable the current intervention by clicking the icon in the Chrome toolbar and clicking "Disable Intervention".
Temporarily Disabling All Interventions
You can disable HabitLab for the rest of the day by clicking the icon in the Chrome toolbar and checking "Disable HabitLab Today".
No Interventions Are Shown
Go to the Settings page and make sure that you have enabled that site on your goals list. You can go to the Settings page by clicking the icon in the Chrome toolbar and clicking "Settings".


Literatura
Knjige
-
Julijan Šribar, Boris Motik. Demistificirani C++. Zagreb: Element, 2001.
-
Mary Campione, Kathy Walrath, Alison Huml. The Java Tutorial: a short course on the basics. Boston: Addison-Wesley, 2000.
Internet izvori
-
"What Is a Class?." Oracle. https://docs.oracle.com/javase/tutorial/java/concepts/class.html (preuzeto studeni 24, 2018).
-
"Where are your objects stored in C++?." Well House Consultants LTD. Zadnje uređeno siječanj 1, 2010. http://www.wellho.net/mouth/2578_Where-are-your-objects-stored-in-C-.html (preuzeto studeni 24, 2018).
-
pramodbablad. "Difference Between Class Variables And Instance Variables In Java." Java Concept Of The Day. Zadnje uređeno srpanj 24, 2016. https://javaconceptoftheday.com/class-variables-and-instance-variables-in-java/ (preuzeto studeni 24, 2018).
-
"Static methods vs Instance methods in Java." GeeksforGeeks. https://www.geeksforgeeks.org/static-methods-vs-instance-methods-java/ (preuzeto studeni 24, 2018).
-
"Class-based vs prototype-based languages." Weekly Web Wisdom. Zadnje uređeno rujan 13, 2017. https://weeklywebwisdom.com/2017/09/13/class-based-vs-prototype-based-languages/ (preuzeto studeni 24, 2018).
-
"Public, Protected and Private Inheritance in C++ Programming." Programiz. https://www.programiz.com/cpp-programming/public-protected-private-inheritance (preuzeto studeni 24, 2018).
-
"Abstract Methods and Classes." Oracle. https://docs.oracle.com/javase/tutorial/java/IandI/abstract.html (preuzeto studeni 24, 2018).
-
"What Is an Interface?." Oracle. https://docs.oracle.com/javase/tutorial/java/concepts/interface.html (preuzeto studeni 24, 2018).
-
Andrei Milea. "Multiple Inheritance in C++." Cprogramming. https://www.cprogramming.com/tutorial/multiple_inheritance.html (preuzeto studeni 24, 2018).
-
"A Brief History of Object-Oriented Programming." Min H. Kao Department of Electrical Engineering and Computer Science. https://web.eecs.utk.edu/~huangj/CS302S04/notes/oo-intro.html (preuzeto studeni 24, 2018).


Survey Form
FreeCodeCamp - Survey Form Project
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SVG draggable elements example
This examples ilustrates 4 thumbs: a static green thumb,
and 3 thumbs that can be moved based on mouse movement or touch gestures.
The dark red thumb can be moved only on vertical, meanwhile the dark orange
can be moved only on horizontal.


NOTE: This test shows FileUploader successfully being created in TabContainers, BUT
there is a serious limitation in the Flash version for Firefox and Safari. When a node in those browsers is hidden
(or essentially repainted which can mean other style applications) the SWF is reloaded. This means that if you browse
for a file but don't upload upload it, change the tab and return, the files will no longer be in the FileUploader.
This problem can be seen when tabbing between Tab 1 and Tab 2 and observing the console logs and you will see the
SWF reinitializes. This problem does not exist in Internet Explorer. The HTML version of the Uploader should also
work fine.
This test also shows work around for the problem. View source of this test and see that in Tab 3, the FileUploader
is in a separate div floating over the TabContainer. When Tab #3 is shown and hidden, the div is moved off and on screen.


This is your bookshelf! You can save books you might want to read here and promote them to the book club survey. You can vote for books in the next bookclub in the survey here: Survey
It looks like you dont have any books on your bookshelf, you can add some by searching for them here: Booksearch


Work Samples
Java: Object-Oriented Programming
Below is a program written in Java that counts the occurences of each character in a document.
My First Website Project
Below is my first website implementing html and css. The instructor provided the content for students to embed within HTML and style with CSS.
Pong
Below is a project that utilizes Python, event handling, and a graphical user interface (GUI) to recreate Pong.


During the early 80's major cities like Montreal, Toronto, Hamilton, Calgary and Vancouver played roles in the popularity of Vespas courtesy of The Who's film Quadrophenia.
There were different groups that rode Vespas from Mods, skinheads, uni and of course scooter boys (Canada's version). There were many rallies in Southern Ontario, specifically Niagara Falls, and all parts in between as well as Mod nights in Toronto, Montreal and Vancouver.
It's the enthusiasm of Vespa lovers/owners that make this community thrive. Whether it's a slick paint scheme, modded out scoots, go-fast scoots or bog standard it's the rider that makes it their own.
Toronto, Montreal, Calgary and Halifax have clubs that continue to hold rallies as well as Vancouver, with their mild winters allowing year-round scootering. As the scooter culture grew across the nation, local clubs quickly formed to better meet the needs of their local scootering community.
Founded by Rinaldo Piaggio in 1884, Piaggio initially produced locomotives and railway carriages.
Piaggio is commissioned by the Italian government to supply their air force with bomber aircraft.
Aeronautical engineer, Corradinio D’Ascanio sold the design he was working on for an inexpensive scooter to Piaggio
called the Vespa.Vespas were shipped to North America via navy ships when sailors were posted and/or docked in Italy. They ended up in cities across Canada.
Mods were smart dressers with the latest Italian suits and shoes. Some started buying Vespas to be able to get around to Mod clubs and events.
Sears brought in a few Vespas in 1952 as a test of the market. These sold so well that Sears decided to begin full scale sales. The Sears Vespas were dubbed the "Super Cruisaire Allstate" and were sold from 1952 to 1967. The last year of sales in 1966-67 the Allstate was simply called the "Sears" scooter.
The Mod Revival came about with the release of The Who’s film Quadrophenia set in the heyday of the Mod scene in England 1964-65.
Piaggio leaves the North American market due to strict American emission laws. Closing some shops across Canada and the USA.
A UK scooter magazine started publishing in the early 80’s, called Scooter Scene with ads for scooter shops that sold parts internationally.
Vancouver and Toronto were the major cities with the larger populations of Vespa owners were keeping the Vespa spirit alive.
The Canadian Scooter Corp was created and started opening up shops across Canada
. These shops sold various models which were quieter and automatic.There are many Vespa dealers across Canada and small businesses that maintain and restore Vespas. It's important to our Vespa community to support these local shops.
$25 CAD
$5 CAD
$15 CAD
Size: 8" Colour: Blue
$5 CAD
Size: 3.5" Colour: Black
$2 CAD
$25 CAD
Member's Only Item. Size: 26" x 8"
$20 CAD
Size fits all.
Exchange ideas, attend rallies, share opinions on various Vespa models, their parts, accessories and join a community of like minded Vespa riders.
The Vespa Club of Canada is a non-profit club and proud to be a member in good standing with Vespa World Club (previously known as the Federation International des Vespa Clubs or F.I.V.).
You will recieve a membership card, club patch, club decal and discounts to Vespa-friendly shops and parts suppliers across Canada.
As a memmber you can attend the Vespa World Club’s annual event Vespa World Days under the Vespa Club of Canada banner*. Various cities host this event and they are as follows: St. Tropez France 2016; Celle Germany 2017; Belfast Ireland 2018 (TBC)
Simply click the button below. Your membership renewal notices will be billed annually.
$21 CAD
* Event registration is payable by the member but the VCOC does the registration.


School Construction Grants
Values shown as currency representing total statewide allocation of School Construction grants for a given year.
Year
—
Grant Amount
—


Thermo MSF Viewer
This program is able to parse and display the information found in msf files created by Thermo's Proteome
Discoverer (v1.2 and v1.3).
- Protein list: Upper left side of the screen This list displays all the proteins found in the loaded msf files. If a protein is clicked
the peptides linked to the protein are displayed in the peptide table.
- A->Z: Sort alphabetically This button will sort the proteins in the protein list alphabetically
- 1->20: Sort by peptide count This button will sort the proteins in the protein list by the number of peptides linked to the protein
- Show all: Restore protein/peptide selection This button will deselect the selected peptide and protein. All the peptides found in the msf files are shown in the peptide table.
- Peptide Table: This table shows information for every identified spectrum. If a peptide is selected the MS, MS/MS, quantification spectra are shown (if requested, see below). Also the selected peptide is annotated in the protein coverage panel. If a
peptide can be linked to multiple proteins these different proteins will be indicated in the "Matching protein(s)" protein list.
- Peptide Confidence Level: Three check boxes show the confidence levels used to display the peptides in the peptide table. This confidence level is given by Proteome Discoverer.
- Peptide Spectrum Match: Three radio buttons show which PSM are shown in the peptide table. These can either by only highest scoring, only lowest scoring or all.
- Load Spectrum: Four check boxes indicate which spectra should be shown when a peptide in the peptide table is selected.
- Start Rover: If quantitative information can be found in the used msf files the "Start Rover" button is visible. When pressed this
button start the Rover program and loads the data from the used msf files. Rover is a program to validate and analyze quantified proteins in the context of the experiment
and in the context of the protein inference problem.
- Chromatogram: The peptides linked to the selected protein are displayed on the chromatogram with vertical bars. The selected protein is colored in red. Peptides found in the same lc-run as the selected protein are shown in blue.
The other peptides (not from the same lc-run) are indicated in green.
- Protein Coverage: The protein sequence of the selected protein is given in the protein coverage panel. The peptides found are indicated in black whereas the unidentified sequence is colored in light gray. The selected peptide (from the peptide table) has a blue background.


What means "Hi" on Russian. Also simple title font test :p
I am new translator and I am happy to become part of BBlog team. Hope that my work will be helpful.
As a player of BF3 I use Battlelog and BBlog is awesome addition to it and translate it into Russinan help BBlog became better.
So, as title said: Hi!
Meaurk
Global Moderator
In order to go further in the same trend: Hallo :-)


We Have Free Templates for Everyone
Our website templates are created with inspiration, checked for quality and originality and meticulously sliced and coded. What´s more, they´re absolutely free! You can do a lot with them. You can modify them. You can use them to design websites for clients, so long as you agree with the Terms of Use. You can even remove all our links if you want to.
We Have More Templates for You
Looking for more templates? Just browse through all our Free Website Templates and find what you´re looking for. But if you don´t find any website template you can use, you can try our Free Web Design service and tell us all about it. Maybe you´re looking for something different, something special. And we love the challenge of doing something different and something special.
Be Part of Our Community
If you´re experiencing issues and concerns about this website template, join the discussion on our forum and meet other people in the community who share the same interests with you.
Template details
Design version 11
Code version 3
Website Template details, discussion and updates for this Custom Shirt Web Template.
Website Template design by Free Website Templates.
Please feel free to remove some or all the text and links of this page and replace it with your own About content.


Rock - Paper - Scissors
Scores
User
Machine
Game: {{$index+1}}
User:
{{item.user}}
Machine:
{{item.machine}}


XMP Toolkit error, associates an error code with a descriptive error string. More...
#include <XMP_Const.h>
Public Member Functions | |
| XMP_Error (XMP_Int32 _id, XMP_StringPtr _errMsg) | |
| Constructor for an XMP_Error. More... | |
| XMP_Int32 | GetID () const |
| Retrieves the numeric code from an XMP_Error. More... | |
| XMP_StringPtr | GetErrMsg () const |
| Retrieves the descriptive string from an XMP_Error. More... | |
| XMP_Bool | IsNotified () const |
| Retrieves the information whether particular error is notified or not. More... | |
| void | SetNotified () |
| Sets the notification status for an error. More... | |
Private Attributes | |
| XMP_Int32 | id |
Exception code. See constants kXMPErr_Unknown and following. More... | |
| XMP_StringPtr | errMsg |
| XMP_Bool | notified |
| Variable to store whether this particular error is notified to user or not. More... | |
XMP Toolkit error, associates an error code with a descriptive error string.
Definition at line 1314 of file XMP_Const.h.
|
inline |
Constructor for an XMP_Error.
| _id | The numeric code. |
| _errMsg | The descriptive string, for debugging use only. It must not be shown to users in a final product. It is written for developers, not users, and never localized. |
Definition at line 1323 of file XMP_Const.h.
|
inline |
|
inline |
Retrieves the numeric code from an XMP_Error.
Definition at line 1326 of file XMP_Const.h.
|
inline |
Retrieves the information whether particular error is notified or not.
Definition at line 1332 of file XMP_Const.h.
|
inline |
Sets the notification status for an error.
Definition at line 1335 of file XMP_Const.h.
|
private |
Descriptive string, for debugging use only. It must not be shown to users in a final product. It is written for developers, not users, and never localized.
Definition at line 1342 of file XMP_Const.h.
|
private |
Exception code. See constants kXMPErr_Unknown
and following.
Definition at line 1335 of file XMP_Const.h.
|
private |
Variable to store whether this particular error is notified to user or not.
Definition at line 1344 of file XMP_Const.h.


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BREAKING Late Late Show legend Gay Byrne dies aged 85 after long illness
The Irish broadcasting legend has sadly passed away following a battle with illness - his family have announced in a statement
by Vicki Newman, https://www.mirror.co.uk/authors/vicki-newman/Irish broadcasting legend Gay Byrne has died at the age of 85.
The former Late Late Show host had been ill for some time.
His sad passing was announced in a family statement.
It said: "It is with sadness that Kathleen, Crona and Suzy wish to announce that their beloved Gay has died peacefully at home today, surrounded by his family.
"We wish to thank everybody for their love and support during Gay's illness. Particularly the wonderful teams in the Mater Hospital, St Francis Hospice and the Irish Cancer Society."
Gay hosted the Late Late Show in Ireland for 37 years and had a career spanning six decades.
We'll be bringing you the latest updates on this breaking celebrity news story.
For the latest news and breaking news visit Mirror.co.uk/3am .
Get all the big headlines, pictures, analysis, opinion and video on the stories that matter to you.
Follow us on Twitter @DailyMirror - the official Daily Mirror & Mirror Online Twitter account - real news in real time.
We're also on Facebook /dailymirror - your news, features, videos and pictures throughout the day from the Daily Mirror, Sunday Mirror and Mirror Online.


What sort of SIP phone configuration would you like to perform?
Created configuration file for a brand new phone and assign to an employee.
Reconfigure an existing phone and assign to a different employee.


Lagrange is a minimalist Jekyll theme for running a personal blog or site for free through Github Pages, or on your own server. Everything that you will ever need to know about this Jekyll theme is included in the README below, which you can also find in the demo site.
Compatible with GitHub Pages.
Support for Jekyll’s built-in Sass/SCSS preprocessor and data files for making customizing easier.
Google Analytics support.
Commenting support powered by Disqus.
Optimized for search engines.
LaTeX support through MathJax.
Lagrange is a Jekyll theme that was built to be 100% compatible with GitHub Pages. If you are unfamiliar with GitHub Pages, you can check out their documentation for more information. Jonathan McGlone’s guide on creating and hosting a personal site on GitHub is also a good resource.
Jekyll is a simple, blog-aware, static site generator for personal, project, or organization sites. Basically, Jekyll takes your page content along with template files and produces a complete website. For more information, visit the official Jekyll site for their documentation. Codecademy also offers a great course on how to deploy a Jekyll site for complete beginners.
 Everything can be done through the GitHub code editor, with minimal knowledge of how to use Jekyll or the command line. All you have to do is add your posts to the _posts
directory and edit the _config.yml
file to change the site settings. With some rudimentary knowledge of HTML and CSS, you can even modify the site to your liking. This can all be done through the GitHub code editor, which acts like a content management system (CMS).
To start using Jekyll right away with GitHub Pages, fork the Lagrange repository on GitHub. From there, you can rename your repository to ‘USERNAME.github.io’, where ‘USERNAME’ is your GitHub username, and edit the settings.yml
file in the _data
folder to your liking. Ensure that you have a branch named gh-pages
. Your website should be ready immediately at ‘http://USERNAME.github.io’. Note: if you are hosting several sites under the same GitHub username, then you will have to use Project Pages instead of User Pages - just change the repository name to something other than ‘http://USERNAME.github.io’.
Head over to the _posts
directory to view all the posts that are currently on the website, and to see examples of what post files generally look like. You can simply just duplicate the template post and start adding your own content.
For a full local installation of Lagrange, download your own copy of Lagrange and unzip it into it’s own directory. From there, open up your favorite command line tool, enter bundle install
, and then enter jekyll serve
. Your site should be up and running locally at http://localhost:4000.
If you are familiar with Jekyll, then the Lagrange directory structure shouldn’t be too difficult to navigate. The following some highlights of the differences you might notice between the default directory structure. More information on what these folders and files do can be found in the Jekyll documentation site.
Lagrange/
├── _data # Data files
| └── settings.yml # Theme settings and custom text
├── _includes # Theme includes
├── _layouts # Theme layouts (see below for details)
├── _posts # Where all your posts will go
├── assets # Style sheets and images are found here
| ├── css # Style sheets go here
| | └── main.css # Main CSS file
| | └── syntax.css # Style sheet for code syntax highlighting
| └── img # Images go here
├── menu # Menu pages
├── _config.yml # Site build settings
├── Gemfile # Ruby Gemfile for managing Jekyll plugins
├── index.md # Home page
├── LICENSE.md # License for this theme
├── README.md # Includes all of the documentation for this theme
└── rss-feed.xml # Generates RSS 2.0 file which Jekyll points to
To completely start from scratch, simply delete all the files in the _posts
, assets/img
, and menu
folder, and add your own content. You may also replace the README.md
file with your own README. Everything in the _data
folder and _config.yml
file can be edited to suit your needs. You may also change the favicon.ico
file to your own favicon.
Visit the the demo site to find sample posts that show what different types of text formatting look like. You can find these posts in the _posts
folder, which show what the best practices for setting up your own site are.
To change site build settings, edit the _config.yml
file found in the root of your repository, which you can tweak however you like. More information on configuration settings and plugins can be found on the Jekyll documentation site. This is also where you will be able to customize the title, description, and the author/owner of your site.
If you are hosting your site on GitHub Pages, then committing a change to the _config.yml
file will force a rebuild of your site with Jekyll. Any changes made should be viewable soon after. If you are hosting your site locally, then you must run jekyll serve
again for the changes to take place.
In the settings.yml
file found in the _data
folder, you will be able to customize your site settings, such as setting Disqus comments, Google Analytics, what shows up in your menu, and social media information.
The menu pages are found in the menu
folder in the root directory, and can be added to your menu in the settings.yml
file.
You will find example posts in your _posts
directory. Go ahead and edit any post and re-build the site to see your changes. You can rebuild the site in many different ways, but the most common way is to run jekyll serve
, which launches a web server and auto-regenerates your site when a file is updated.
To add new posts, simply add a file in the _posts
directory that follows the convention of YYYY-MM-DD-name-of-post.md
and includes the necessary front matter. Take a look at any sample post to get an idea about how it works. If you already have a website built with Jekyll, simply copy over your posts to migrate to Lagrange.
There are two main layout options that are included with Lagrange: post and page. Layouts are specified through the YAML front block matter. Any file that contains a YAML front block matter will be processed by Jekyll. For example:
---
layout: post
title: "Example Post"
---
Examples of what posts looks like can be found in the _posts
directory, which includes this post you are reading right now. Posts are the basic blog post layout, which includes a header image, post content, author name, date published, social media sharing links, and related posts.
Pages are essentially the post layout without any of the extra features of the posts layout. An example of what pages look like can be found at the About and Contacts.
In addition to the two main layout options above, there are also custom layouts that have been created for the home page and the archives page. These are simply just page layouts with some Liquid template code. Check out the index.html
file in the root directory for what the code looks like.
The recommended YAML front block is:
---
layout:
title:
author:
categories:
tags: []
image:
---
layout
specifies which layout to use, title
is the page or post title, categories
can be used to better organize your posts, tags
are used when generating related posts based on the topic of the post, and image
specifies which images to use. Have a look at some posts in the _posts
directory to see how these variables are set.
Lagrange was designed to be a minimalist theme in order for the focus to remain on your content. For example, links are signified mainly through an underline text-decoration, in order to maximize the perceived affordance of clickability (I originally just wanted to make the links a darker shade of grey).
Lagrange supports comments at the end of posts through Disqus. In order to activate Disqus commenting, set disqus.comments
to true in the _data/settings.yml
file. If you do not have a Disqus account already, you will have to set one up, and create a profile for your website. You will be given a disqus_shortname
that will be used to generate the appropriate comments sections for your site. More information on how to set up Disqus.
It is possible to track your site statistics through Google Analytics. Similar to Disqus, you will have to create an account for Google Analytics, and enter the correct Google ID for your site under google-ID
in the settings.yml
file. More information on how to set up Google Analytics.
Atom is supported by default through jekyll-feed. With jekyll-feed, you can set configuration variables such as ‘title’, ‘description’, and ‘author’, in the _config.yml
file.
RSS 2.0 is also supported through RSS auto-discovery. The rss-feed.xml
file (based on the template found at jekyll-rss-feeds) that the feed path points to when using RSS 2.0 is automatically generated based on the appropriate configuration variables found in _data/settings.yml
.
To use RSS 2.0, ensure the following is done:
Uncomment the last two lines in the _config.yml
file.
In _data/settings.yml
, under ‘social’, comment out the rss-square that points to feed.xml
, and uncomment the rss-square that points to rss-feed.xml
.
In _includes/head.html
, comment out <link type="application/atom+xml" rel="alternate" href="http://localhost:4000/feed.xml" title="Walter Bircher" />
and uncomment the line under the RSS 2.0 comment.
All social media icons are courtesy of Font Awesome. You can change which icons appear, as well as the account that they link to, in the settings.yml
file in the _data
folder.
Lagrange comes out of the box with MathJax, which allows you to display mathematical equations in your posts through the use of LaTeX.
Lagrange provides syntax highlighting through fenced code blocks. Syntax highlighting allows you to display source code in different colors and fonts depending on what programming language is being displayed. You can find the full list of supported programming languages here. Another option is to embed your code through Gist.
As always, Jekyll offers support for GitHub Flavored Markdown, which allows you to format your posts using the Markdown syntax. Examples of these text formatting features can be seen below. You can find this post in the _posts
directory as well as the README.md
file.
Check out the Jekyll docs for more info on how to get the most out of Jekyll. File all bugs/feature requests at Jekyll’s GitHub repo. If you have questions, you can ask them on Jekyll Talk.
If you would like to make a feature request, or report a bug or typo in the documentation, then please submit a GitHub issue. If you would like to make a contribution, then feel free to submit a pull request - as a bonus, I will credit all contributors below! If this is your first pull request, it may be helpful to read up on the GitHub Flow first.
Lagrange has been designed as a base for users to customize and fit to their own unique needs. Please keep this in mind when requesting features and/or submitting pull requests. Some examples of changes that I would love to see are things that would make the site easier to use, or better ways of doing things. Please avoid changes that do not benefit the majority of users.
This theme is completely free and open source software. You may use it however you want, as it is distributed under the MIT License. If you are having any problems, any questions or suggestions, feel free to tweet at me, or file a GitHub issue.
Open sourced under the MIT license.
Written on October 10th, 2015 by Paul Le


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GraphSense is a cryptocurrency analytics research platform, developed under the leadership of the Austrian Institute of Technology, with funding from the Austrian Research Promotion Agency's KIRAS program (Project VIRTCRIME) and the European Union's Horizon 2020 research innovation program (Project TITANIUM).
GraphSense is provided as Open Source software, under the terms of the MIT license. It can be downloaded free of charge for self-hosting from our GitHub repository.
The Austrian Institute of Technology offers free access to a hosted version of the software at demo.graphsense.info in the spirit of open source and as an act of collegiality. Please refer to our Terms and Conditions of Use for information.
This service is hosted at the
AIT Austrian Institute of Technology GmbH
Giefinggasse 4
1210 Vienna
Austria
Contact the AIT Data Protection Officer via dpo@ait.ac.at


---
order: 11
title: Dark Eldar
name: Kabal of Pain’s Way Dark Eldar
introduction:
|
forces:
- dark-eldar
using_the_army_list:
|
Kabal of Pain’s Way Dark Eldar formations come in two types: _kabals_ and _partisans_. Each kabal you include in the army allows you to field any two partisan formations. Although you can only take a partisans formation if you first take a kabal, they are treated as separate independent formations during a battle and do not have to move around together.
In addition, formations may be given upgrades. Which upgrades a formation may be given are listed in the Upgrades column. Upgrades are added to the formation and are not a separate formation. Each upgrade that is taken adds to the cost of the formation, as shown on the upgrade chart. Note that you may never exceed more than eight infantry units in a formation.
Dark Eldar armies may be supported by Dark Eldar Aircraft, Spacecraft and Other Horror formations. A maximum of up to a third of the points available to the army may be spent on these formations.
Finally, Dark Eldar Individuals includes special characters, formations and objective options. Each individual may only be taken once by the army. The rules for using each individual are listed in the Notes column.
special_rules_text:
|
The _Hit & Run Tactics_ rule (see [_Hit & Run Tactics_](#dark-eldar-hit-and-run-tactics)) and _Fleet of Foot_ rule (see [_Fleet of Foot_](#fleet-of-foot)) apply to all Dark Eldar formations. Additionally, certain units and weapons have special abilities described in _Dark Eldar Technology_ (see [_Dark Eldar Technology_](#dark-eldar-technology)).
special_rules:
- kabal-of-pains-way-epic-tournament-special-rules
- dark-eldar-transport
- kashnarak
---
Kabal of Pain’s Way Dark Eldar armies have a strategy rating of 3. Dark Eldar Kabals, Tormentor and Executor formations have an initiative rating of 1+. All other formations have an initiative rating of 2+.
Dark Eldar Individuals
(Up to one of each type of individual may be taken per army.)
Type
Notes
Cost
0–1 Archon
Replace one Dracon character with an Archon. The Archon must be placed in the Kabal Coterie formation if there is one in the army.
+50 points
0–1 Kashnarak
In the Strategy Phase of any turn place the Kashnarak within 5cm of a Webway Portal, it behaves according to the Kashnarak rule (see Kashnarak).
+50 points
0–1 Webway Portal
At the start of the game nominate one objective on your half of the table as a Webway Portal before setting up spacecraft and garrisons. The objective functions both as a Webway Portal and as an objective for the rules purposes. It may not be destroyed. Only formations consisting completely of infantry units, light vehicle units or armoured vehicles units with the Walker ability may use the Webway Portal to enter play.
+50 points
Dark Eldar Kabals
(Each formation may never exceed more than eight infantry units.)
Formation
Units
Upgrades
Cost
0–1 Kabal Coterie
Four Incubi, one with a Dracon character, plus transport


var
type that can be replaced with an explicit type.
Example:
var str = "Hello";
After the quick-fix is applied:
String str = "Hello";
var
keyword appeared in Java 10.
This inspection can help to downgrade for backward compatibility with earlier Java versions.


Methods
Public Instance methods
Write to a file atomically. Useful for situations where you don‘t want other processes or threads to see half-written files.
File.atomic_write("important.file") do |file| file.write("hello") end
If your temp directory is not on the same filesystem as the file you‘re trying to write, you can provide a different temporary directory.
File.atomic_write("/data/something.important", "/data/tmp") do |f| file.write("hello") end
[ show source ]
# File vendor/rails/activesupport/lib/active_support/core_ext/file/atomic.rb, line 18 18: def atomic_write(file_name, temp_dir = Dir.tmpdir) 19: require 'tempfile' unless defined?(Tempfile) 20: 21: temp_file = Tempfile.new(basename(file_name), temp_dir) 22: yield temp_file 23: temp_file.close 24: 25: begin 26: # Get original file permissions 27: old_stat = stat(file_name) 28: rescue Errno::ENOENT 29: # No old permissions, write a temp file to determine the defaults 30: check_name = join(dirname(file_name), ".permissions_check.#{Thread.current.object_id}.#{Process.pid}.#{rand(1000000)}") 31: open(check_name, "w") { } 32: old_stat = stat(check_name) 33: unlink(check_name) 34: end 35: 36: # Overwrite original file with temp file 37: rename(temp_file.path, file_name) 38: 39: # Set correct permissions on new file 40: chown(old_stat.uid, old_stat.gid, file_name) 41: chmod(old_stat.mode, file_name) 42: end


Steelers Bench Mason Rudolph for Devlin Hodges, New QB Immediately Throws Touchdown (VIDEO)
by Darrelle LincolnMason Rudolph is having a rough few weeks.
During the Steelers last game against the Browns, he got his helmet snatched off and hit over the head with it and would receive a $50K fine from the league.
On Sunday, he got benched for playing badly and his back-up in Devlin Hodges showed what he had almost immediately as he tossed a 79-yard TD.
Rudolph was 8-16 for 85 yards, no touchdowns, and an interception as Pittsburgh mustered just three points in the first half against a winless Bengals team.


This helps us keep your information secure.


| Home | About Us | Cinemas |
About Us
Bangalore has joined the band of cities that boast of high tech modern theatres for total entertainment pleasure. The newest Malls all house the best theatres that one would expreince in New York or Los Angeles.
One of the popular means of entertainment in Bangalore comprises of the numerous movie theaters and multiplexes dotting the city. Infact, Bangalore was one of the first cities where the concept of multiplexes was introduced. Most of the movie theaters in Bangalore have restaurants situated nearby, thus offering the complete entertainment package for the entire day.


Project Sicarius
Check out more games on my website!
Source Code
Have Windows? You can download and play the Windows build from
here
.


{% assign image = object.featured_image_path | prepend: site.image_url | remove: 'uploads/' | append: '?w=400' %} {% assign collection = site.collections | where: 'label', object.collection | first %}
' | remove: '


"EPHRAIM", WOOD OF a forest in which a fatal battle was fought between the army of David and that of Absalom, who was killed there (2 Samuel 18:6, 8). It lay on the east of Jordan, not far from Mahanaim, and was some part of the great forest of Gilead.
"EPHRAIM", WOOD OF a forest in which a fatal battle was fought between the army of David and that of Absalom, who was killed there (2 Samuel 18:6, 8). It lay on the east of Jordan, not far from Mahanaim, and was some part of the great forest of Gilead.


This page provides a minimal guide on how to use the RapidLib. It shows how to build and use simple machine learning objects, in just a few steps.
First, to install RapidLib you need to include it in your HTML page using the HTML <script> tag.
// Just include this script tag inside your HTML page
<script src="RapidLib.js"></script>
Now you have the RapidLib module available on the Javascript global scope.
To load RapidLib into a variable, you use RapidLib(). That variable will give you access to the Machine Learning objects that RapidLib provides.
var rapidLib = RapidLib();
var myRegression = new rapidLib.Regression();
var myClassification = new rapidLib.Classification();
var mySeriesClassification = new rapidLib.SeriesClassification();
RapidLib provides constructors to three main objects: Regression, Classification and SeriesClassification.
You can use each one of these objects to apply a specific Machine Learning task.
To apply a Machine Learning task such as training a regression model, you need data and a data structure that holds it—this is usually called a data set.
The Regression and Classification objects expect a certain structure from a data set object, as you can see in the example below.
var myData = [
{
input: [48],
output: [130.81]
},
{
input: [54],
output: [185.00]
},
{
input: [60],
output: [261.63]
},
{
input: [66],
output: [369.994]
},
{
input: [72],
output: [523.25]
}
];
Note:
myData is implemented as a Javascript Array containing examples that are implemented as Javascript objects.
Both input and output are implemented as Javascript Arrays, although the examples in myData match one input to one output.
You need to make sure that the number of inputs and outputs remain constant for the data sets of a specific Machine Learning object.
myRegression.train(myData);
var newInput = [64];
var freqHz = myRegression.run(newInput);
The next code snippet shows a simple but complete example of applying the RapidLib for a machine learning task.
<!DOCTYPE html>
<html>
<head> </head>
<body> </body>
<script src="RapidLib.js"> </script>
<script>
var rapidLib = RapidLib();
//Create a machine learning object for regression
var midiToFrequencyRegression = new rapidLib.Regression();
//Create a Javascript object to hold your training data
var myData = [
{
input: [48],
output: [130.81]
},
{
input: [54],
output: [185.00]
},
{
input: [60],
output: [261.63]
},
{
input: [66],
output: [369.994]
},
{
input: [72],
output: [523.25]
}
];
//Train a machine learning model with the data
midiToFrequencyRegression.train(myData);
//Run the trained model with a new input
var newInput = [64];
var freqHz = midiToFrequencyRegression.run(newInput);
console.log(freqHz); // 333.713
</script>
</html>
Note that, in this example, the variable named midiToFrequencyRegression keeps the regression object.
The model that trained with myData data set is a function that converts MIDI values to Frequency values.


Everyone knows the fact that MEMBERSHIP websites are the WAY to build FANS & Create recurring income but the issue is that proper membership platform will cost you a car payment & your kidney!
When you invest for MemberConnect Reseller, You are giving YOURSELF an oppurtunity to resell MemberConnect or Give it to your clients as a bonus... Do Whatever you like as long as it doesn't kill another human being! You keep 100% of the income generate from the sales & Your Customers are YOURS!


Frequently Asked Questions
?
What is QIPR?
The Quality Improvement Project Registry (QIPR) for UF Health quality improvement projects.
?
Are there differences between Quality Improvement and Research?
Yes, there are several important distinctions between quality improvement/quality assurance and research. To read more about these differences, visit the IRB’s webpage: QA/QI vs Research
?
Why should I use QIPR?
- Share your QI projects, learn from others, and see current improvement projects to connect and collaborate
- Apply credit to New Innovations (for Residents and Magnet only)
- Access to BMJ Quality website to manage projects and facilitate QI publications and presentations
- Access to Quality Department experts and data resources
?
What do I need to get started?
- Search QIPR to learn about existing quality improvement projects
- Make sure you have a mentor for your project if you are a resident/trainee/student
- Complete QI project charter
?
Do I need IRB approval?
Most QI projects do not require IRB approval if they meet QI criteria. If the project does not meet QI criteria, the IRB will need to review the project. QIPR will help to determine if the project meets QI criteria.
?
How can I get help?
- Visit the Quality Improvement Resources and Education website
- Call us<PHONE_NUMBER>


80s Theme Song Survey!
How many of these theme songs do you know? Is there a correlation between the number of theme songs you know and where you were born or where you've spent most of your time? Let's find out. :-)
How many of these theme songs do you know? Is there a correlation between the number of theme songs you know and where you were born or where you've spent most of your time? Let's find out. :-)


{% extends "free_software.html" %} {% block logo %} {% endblock %} {% block software %}
Slack is a group communication platform built around chat channels. (You can join Code for America's Slack at slack.codeforamerica.org if you want to learn more!) Slack typically only offers one nonprofit plan per organization, but some brigades have had success applying for their own nonprofit plan. Your mileage may vary.
Slack offers a generous free tier to anyone that includes support for unlimited users with a fixed quota of storage space for messages and files. When you hit the limit, old messages and files are automatically deleted.
{% endblock %}