cvCovEst
: Cross-Validated
Covariance Matrix Estimationvignettes/using_cvCovEst.Rmd
using_cvCovEst.Rmd
When the number of observations in a dataset far exceeds the number of features, the estimator of choice for the covariance matrix is the sample covariance matrix. It is an efficient estimator under minimal regularity assumptions on the data-generating distribution. In high-dimensional regimes, however, this estimator leaves much to be desired: The sample covariance matrix is either singular, numerically unstable, or both, thereby amplifying estimation error.
As high-dimensional data have become widespread, researchers have derived many novel covariance matrix estimators to remediate the sample covariance matrix’s deficiencies. These estimators come in many flavours, though most are constructed by regularizing the sample covariance matrix, or through the estimation of latent factors. A comprehensive review is provided by Fan, Liao, and Liu (2016).
This variety brings with it many challenges. Identifying an “optimal” estimator from among a collection of candidates can prove a daunting task, one whose objectivity is often compromised by the analyst’s decisions. Though data-driven approaches for selecting an optimal estimator from among estimators belonging to certain (limited) classes have been derived, the question of selecting an estimator from among a diverse collection of candidates remains unaddressed.
We therefore offer a general, cross-validation-based framework for covariance matrix estimator selection to tackle just that. The high-dimensional asymptotic optimality of selections are guaranteed based upon extensions of the seminal work of Dudoit and van der Laan (2003), Dudoit and van der Laan (2005), and van der Vaart, Dudoit, and van der Laan (2006) on data-adaptive estimator selection to high-dimensional covariance matrix estimation (Boileau et al. 2021). The interested reader is invited to review theoretical underpinnings of the methodology as described in Boileau et al. (2021).
Let there be a high-dimensional dataset comprising \(n\) realizations of \(i.i.d.\) \(p\)-length random vectors with a possibly nonparametric data-generating distribution. Our goal is to estimate these random vectors’ covariance matrix, which may be accomplished using our general cross-validated estimator selection framework.
Given a library of candidate estimators, a loss function, and a
choice of cross-validation scheme, cvCovEst()
will identify
the asymptotically optimal estimator of the covariance matrix from among
all candidates. It subsequently estimates this parameter using the
selected candidate. An example is provided below. Lists and brief
descriptions of implemented candidate estimators, loss functions, and
cross-validation schemes are provided in the sequel.
## Warning: package 'MASS' was built under R version 4.1.2
## cvCovEst v1.2.0: Cross-Validated Covariance Matrix Estimation
set.seed(1584)
# generate a 50x50 covariance matrix with unit variances and off-diagonal
# elements equal to 0.5
sigma <- matrix(0.5, nrow = 50, ncol = 50) + diag(0.5, nrow = 50)
# sample 50 observations from multivariate normal with mean = 0, var = Sigma
dat <- mvrnorm(n = 50, mu = rep(0, 50), Sigma = sigma)
# run CV-selector
cv_cov_est_out <- cvCovEst(
dat = dat,
estimators = c(
linearShrinkLWEst, denseLinearShrinkEst,
thresholdingEst, poetEst, sampleCovEst
),
estimator_params = list(
thresholdingEst = list(gamma = c(0.2, 0.4)),
poetEst = list(lambda = c(0.1, 0.2), k = c(1L, 2L))
),
cv_loss = cvMatrixFrobeniusLoss,
cv_scheme = "v_fold",
v_folds = 5,
)
# print the table of risk estimates
cv_cov_est_out$risk_df
## # A tibble: 9 × 3
## estimator hyperparameters cv_risk
## <chr> <chr> <dbl>
## 1 linearShrinkLWEst hyperparameters = NA 357.
## 2 poetEst lambda = 0.2, k = 1 369.
## 3 poetEst lambda = 0.2, k = 2 372.
## 4 poetEst lambda = 0.1, k = 2 375.
## 5 poetEst lambda = 0.1, k = 1 376.
## 6 denseLinearShrinkEst hyperparameters = NA 379.
## 7 sampleCovEst hyperparameters = NA 379.
## 8 thresholdingEst gamma = 0.2 384.
## 9 thresholdingEst gamma = 0.4 505.
# print a subset of the selected estimator's estimate
cv_cov_est_out$estimate[1:5, 1:5]
## [,1] [,2] [,3] [,4] [,5]
## [1,] 1.1725637 0.5219385 0.4813226 0.5576840 0.6719526
## [2,] 0.5219385 0.9364171 0.5591108 0.4390799 0.6766744
## [3,] 0.4813226 0.5591108 1.0150440 0.4052703 0.6436765
## [4,] 0.5576840 0.4390799 0.4052703 0.9826984 0.4304168
## [5,] 0.6719526 0.6766744 0.6436765 0.4304168 1.0883278
Covariance matrix estimators implemented in the cvCovEst
package are catalogued in the following table. These estimators are fed
to the cvCovEst()
function through the
estimators
argument as a vector. If these estimators rely
on hyperparameters, then they must be passed to the
estimator_params
as a list. Depending on one’s assumptions
— or lack thereof — about the true covariance matrix, one may choose to
use a subset of these estimators or all of them. Of course, they may
also be used as standalone functions.
| Estimator | Implementation | Description |
|---|---|---|
| Sample covariance matrix | sampleCovEst() |
The sample covariance matrix. |
| Hard thresholding (Bickel and Levina 2008b) | thresholdingEst() |
Applies a hard thresholding operator to the entries of the sample covariance matrix. |
| SCAD thresholding (Rothman, Levina, and Zhu 2009; Fan and Li 2001) | scadEst() |
Applies the SCAD thresholding operator to the entries of the sample covariance matrix. |
| Adaptive LASSO (Rothman, Levina, and Zhu 2009) | adaptiveLassoEst() |
Applies the adaptive LASSO thresholding operator to the entries of the sample covariance matrix. |
| Banding (Bickel and Levina 2008a) | bandingEst() |
Replaces the sample covariance matrix’s off-diagonal bands by zeros. |
| Tapering (Cai, Zhang, and Zhou 2010) | taperingEst() |
Tapers the sample covariance matrix’s off-diagonal bands, eventually replacing them by zeros. |
| Optimal Linear Shrinkage (Ledoit and Wolf 2004) | linearShrinkLWEst() |
Asymptotically optimal shrinkage of the sample covariance matrix towards the identity. |
| Linear Shrinkage (Ledoit and Wolf 2004) | linearShrinkEst() |
Shrinkage of the sample covariance matrix towards the identity, but the shrinkage is controlled by a hyperparameter. |
| Dense Linear Shrinkage (Schäfer and Strimmer 2005) | denseLinearShrinkEst() |
Asymptotically optimal shrinkage of the sample covariance matrix towards a dense matrix whose diagonal elements are the mean of the sample covariance matrix’s diagonal, and whose off-diagonal elements are the mean of the sample covariance matrix’s off-diagonal elements. |
| Nonlinear Shrinkage (Ledoit and Wolf 2018) | nlShrinkLWEst() |
Analytical estimator for the nonlinear shrinkage of the sample covariance matrix. |
| POET (Fan, Liao, and Mincheva 2013) | poetEst() |
An estimator based on latent variable estimation and thresholding. |
| Robust POET (Fan, Liu, and Wang 2018) | robustPoetEst() |
A robust (and more computationally taxing) take on the POET estimator. |
| Spiked Operator Loss Shrinkage (Donoho, Gavish, and Johnstone 2018) | spikedOperatorShrinkEst() |
The asymptotically optimal shrinkage estimator based on the operator loss in a Gaussian spiked covariance model. |
| Spiked Frobenius Loss Shrinkage (Donoho, Gavish, and Johnstone 2018) | spikedFrobeniusShrinkEst() |
The asymptotically optimal shrinkage estimator based on the Frobenius loss in a Gaussian spiked covariance model. |
| Spiked Stein Loss Shrinkage (Donoho, Gavish, and Johnstone 2018) | spikedSteinShrinkEst() |
The asymptotically optimal shrinkage estimator based on the Stein loss in a Gaussian spiked covariance model. |
Note that cvCovEst()
only functions with estimators
native to this package. If you’d like to request a new estimator
implementation, please submit an issue to the
queue.
Given a collection of candidate estimators, cvCovEst()
compares their conditional cross-validated risks to identify the optimal
selection. The loss function used to compute these risks should reflect
both aspects of the data-generating distribution and the goal of the
estimation procedure. This package currently implements three loss
functions:
| Loss | Implementation | Description |
|---|---|---|
| Matrix-based Frobenius | cvMatrixFrobeniusLoss() |
The default, based on the Frobenius norm. Appropriate when the dataset’s features are of similar magnitudes. |
| Variance-scaled matrix-based Frobenius | cvScaledMatrixFrobeniusLoss() |
A scaled version of the matrix-based Frobenius loss, where weights are the inverse of products from the sample covariance matrix’s diagonal. Appropriate when the features of the dataset are of different magnitudes. |
| Observation-based Frobenius | cvFrobeniusLoss() |
Based on the Frobenius norm and the rank-1, observation-level estimates of the sample covariance matrix. Its selections are equivalent to that of the matrix-based Frobenius, though less computationally efficient. However, the optimality results of Boileau et al. (2021) rely on it. |
The choice of loss function is set trough the cv_loss
argument. Like the candidate estimators, cvCovEst()
only
supports loss functions implemented in this package. Please submit
suggestions to the issue
queue.
Two cross-validation schemes are currently supported by
cvCovEst()
. Please consider filing an issue in the
queue to request the implementation of another cross-validation
scheme.
| Scheme | Details |
|---|---|
| V-fold | To use V-fold cross-validation, set the cv_scheme
argument in cvCovEst() to "v_fold" , and set
the number of folds through the v_folds argument.
cvCovEst() defaults to 5-fold cross-validation. |
| Monte-Carlo | To perform Monte-Carlo cross-validation, set the
cv_scheme argument to "mc" . Set the proportion
of data to be used in each validation set using the
mc_split argument, and the number of iterations to perform
with the v_folds argument. |
In addition to selecting an optimal estimator, the
cvCovEst
package contains summary and plotting methods
which highlight the statistical properties of the candidate estimators,
and inform the performance of the selection framework. These tools help
build intuition about these estimators’ behavior and allows for the
evaluation of their performance over varying inputs.
The summary()
method for cvCovEst
accepts
an object
argument, a named list
of class
cvCovEst
, a dat_orig
argument, the original
data used to calculate the covariance matrix estimates, and a
summ_fun
argument, a character vector specifying the type
of summary function to use.
These summary functions allow the user to quickly compare the
performance of several classes of estimators and compute other metrics
of interest. The choices of summ_fun
and their outputs are
described below:
| Summary | Implementation | Description |
|---|---|---|
| Empirical Risk by Estimator Class | empRiskByClass |
Returns the minimum, 1st quartile, median, 3rd
quartile, and maximum of the empirical risk associated with each class
of estimator passed to cvCovEst() . |
| Best Performing Estimator by Class | bestInClass |
Returns the specific hyperparameters, if applicable, of the best performing estimator within each class along with additional metrics. |
| Worst Performing Estimator by Class | worstInClass |
Returns the specific hyperparameters, if applicable, of the worst performing estimator within each class along with additional metrics. |
| Empirical Risk by Hyperparameter | hyperRisk |
For estimators that take hyperparameters as arguments, this returns
the hyperparameters associated with the minimum, 1st
quartile, median, 3rd quartile, and maximum of the empirical
risk within each class of estimator. Each class has its own
tibble which are returned as a list . |
When either bestInClass
or worstInClass
is
specified, the additional metrics are the condition number, the sign,
and the sparsity. Sign refers to the estimate’s sign and is one of
positive-definite ("PD"
), positive-semi-definite (“PSD”),
negative-definite (“ND”), negative-semi-definite (“NSD”), or indefinite
(“IND”). If an estimate results in a zero matrix, then the sign is
returned as "NA"
. Sparsity is calculated at the proportion
of total entries in the estimate which are equal to zero.
The plot()
method for cvCovEst
allows users
to visualize three main plot_type
s of the candidate
estimators: covariance heat maps (heatmap
), eigenvalue
plots (eigen
), and the empirical risk (risk
)
as a function of the hyperparameters (for applicable estimator classes).
If users do not specify a plot type, then all three plots are combined
into one figure for the optimal estimator selected by
cvCovEst()
. Users can also achieve this by setting
plot_type = "summary"
.
The heat maps and eigenvalue plots facilitate comparisons both within
and between estimator classes by allowing multiple values to be passed
as estimator
and stat
arguments.
Additional arguments specific to each plot_type
are
outlined below:
| Argument | Description |
|---|---|
| abs_v | If TRUE , then the absolute value of the covariance is
mapped. Otherwise, the signed value is used. |
| Argument | Description |
|---|---|
| leading | If TRUE , then the k leading eigenvalues are displayed.
Otherwise, the k trailing eigenvalues are displayed. |
| k | The number of leading or trailing eigenvalues to plot. |
These two additional arguments only apply to estimators with multiple hyperparameters:
| Argument | Description |
|---|---|
| switch_vars | If TRUE , the hyperparameters used for the x-axis and
factor variables are switched. |
| min_max | If TRUE , only the minimum and maximum values of the
factor hyperparameter will be used. |
To show how the plot and summary methods can be used, data is
simulated from a predetermined covariance matrix following a Toeplitz
structure. The data is then passed to cvCovEst()
along with
a handful of estimators.
set.seed(1584)
toep_sim <- function(p, rho, alpha) {
times <- seq_len(p)
H <- abs(outer(times, times, "-")) + diag(p)
H <- H^-(1 + alpha) * rho
covmat <- H + diag(p) * (1 - rho)
sign_mat <- sapply(
times,
function(i) {
sapply(
times,
function(j) {
(-1)^(abs(i - j))
}
)
}
)
return(covmat * sign_mat)
}
# simulate a 100 x 100 covariance matrix
sim_covmat <- toep_sim(p = 100, rho = 0.6, alpha = 0.3)
# sample 75 observations from multivariate normal mean = 0, var = sim_covmat
sim_dat <- MASS::mvrnorm(n = 100, mu = rep(0, 100), Sigma = sim_covmat)
# run CV-selector
cv_cov_est_sim <- cvCovEst(
dat = sim_dat,
estimators = c(
linearShrinkEst, thresholdingEst, bandingEst, adaptiveLassoEst,
sampleCovEst, taperingEst
),
estimator_params = list(
linearShrinkEst = list(alpha = seq(0.25, 0.75, 0.05)),
thresholdingEst = list(gamma = seq(0.25, 0.75, 0.05)),
bandingEst = list(k = seq(2L, 10L, 2L)),
adaptiveLassoEst = list(lambda = c(0.1, 0.25, 0.5, 0.75, 1), n = seq(1, 5)),
taperingEst = list(k = seq(2L, 10L, 2L))
),
cv_scheme = "v_fold",
v_folds = 5
)
The summary()
method is then used to compare the best
performing estimators in each class:
cv_sum <- summary(cv_cov_est_sim, dat_orig = sim_dat)
cv_sum$bestInClass
## # A tibble: 6 × 6
## estimator hyperparameter cv_risk cond_num sign sparsity
## <chr> <chr> <dbl> <dbl> <chr> <dbl>
## 1 taperingEst k = 6 555. 9.26e 1 PD 0.89
## 2 bandingEst k = 4 557. -1.35e 2 IND 0.91
## 3 adaptiveLassoEst lambda = 0.25, n = 2 570. -3.3 e 1 IND 0.93
## 4 thresholdingEst gamma = 0.35 574. -1.48e 1 IND 0.96
## 5 linearShrinkEst alpha = 0.45 593. 6.65e 0 PD 0
## 6 sampleCovEst hyperparameters = NA 667. 2.14e16 PD 0
In this case, the tapering estimator with k = 6
achieves
the lowest empirical risk. It is also one of the few positive definite
matrices, though its condition number is worse than that of the linear
shrinkage estimator’s estimate. The resulting estimate is also less
sparse than that of the other sparsity-enforcing estimators “best”
estimates.
We can take a closer look at the estimator’s performance based on
other possible hyperparameter values by hashing taperingEst
from the hyperRisk
list.
cv_sum$hyperRisk$taperingEst
## # A tibble: 5 × 3
## hyperparameters cv_risk stat
## <chr> <chr> <chr>
## 1 k = 6 555 min
## 2 k = 6 555 Q1
## 3 k = 6 555 median
## 4 k = 4 558 Q3
## 5 k = 2 572 max
By specifying plot_type = "risk"
, we can see the change
in empirical risk as the value of k
changes. A summary of
the cross-validation scheme and loss function is displayed at the bottom
of all cvCovEst
plot outputs.
plot(cv_cov_est_sim, dat_orig = sim_dat, plot_type = "risk")
We can also examine the matrix structure as the value of
k
changes. Examining the overall sparsity of the resulting
estimator can be useful since, in some cases, the assumption of sparsity
is not warranted. Note that the absolute values of the estimate’s
entries are displayed to emphasize the structural differences between
choices of hyperparameters.
If the signs of the covariances are of interest, they can be
displayed by setting abs_v = FALSE
:
plot(cv_cov_est_sim, dat_orig = sim_dat, plot_type = "heatmap",
stat = c("min", "median", "max"), abs_v = FALSE)
The difference between the optimal estimator selected by
cvCovEst()
and the sample covariance matrix is clear when
displaying their respective heat maps side by side.
plot(cv_cov_est_sim, dat_orig = sim_dat, plot_type = "heatmap",
estimator = c("taperingEst", "sampleCovEst"),
stat = c("min"), abs_v = FALSE)
We may also be interested in the eigenvalues of the various banding
estimators. The distribution of eigenvalues relays information such as
the condition number or the positive-definiteness of the resulting
estimator. As with the other plot types, if the estimator
argument is not specified, the default is to display the optimal
estimator selected by cvCovEst()
.
Specifying multiple values in the estimator
argument
allows us compare the eigenvalues of the other estimator classes as
well.
plot(cv_cov_est_sim, dat_orig = sim_dat, plot_type = "eigen",
stat = c("min", "median", "max"),
estimator = c("taperingEst", "bandingEst", "linearShrinkEst",
"adaptiveLassoEst"))
As previously mentioned, simply calling the plot()
on
the output of cvCovEst()
and providing the original data
will result in a visual summary of the selected estimator.
plot(cv_cov_est_sim, dat_orig = sim_dat)


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Sprites
and Movie Clips..................................................................................................................................... 1
Sprites and Movie Clips Contents............................................................................................................. 1
Sprites and Movie Clips.................................................................................................................................... 2
Sprite Names.......................................................................................................................................................... 2
DefineSprite........................................................................................................................................................... 3
QuickTimeä Movies............................................................................................................................................ 4
A sprite corresponds to a ‘movie clip’ in the Flash user-interface. It is a Macromedia Flash (SWF) movie contained within a Macromedia Flash (SWF) movie, and supports many of the features of a regular Flash movie, including:
· Most of the control tags that can be used in the main movie.
· A timeline that can stop, start and play independently of the main movie.
· A streaming sound track that is automatically mixed with the main sound track.
A sprite object is defined with a DefineSprite tag. It consists of a character ID, a frame count, and a series of control tags. Definition tags (such as DefineShape) are not allowed in the DefineSprite tag. All the characters referred to by control tags in the sprite must be defined outside the sprite, and before the DefineSprite tag.
Once defined, a sprite is displayed with a PlaceObject2 tag in the main movie. The transform (specified in PlaceObject) is concatenated with the transforms of objects placed inside the sprite. These objects behave like ‘children’ of the sprite, so when the sprite is moved, the objects inside the sprite move also. Similarly, when the sprite is scaled or rotated, the child objects are also scaled or rotated. A sprite object stops playing automatically when it is removed from the display list.
When a sprite is placed on the display list, it can be given a name with the PlaceObject2 tag. This name corresponds to the instance name in the Macromedia Flash user-interface. It is used to identify the sprite so the main movie (or other sprites) can perform actions inside the sprite. This is achieved with the SetTarget action (called ‘Tell Target’ in the Flash user-interface)
For example, say a sprite object was placed in the main movie with the name “spinner”. The main movie can send this sprite to the first frame in its timeline with the following action sequence:
1. SetTarget “spinner”
2. GotoFrame zero
3. SetTarget “” (empty string)
4. End of actions. (Action code = 0)
Note: All actions following SetTarget “spinner” apply to the spinner object until SetTarget “”, which sets the action context back to the main movie.
Macromedia Flash (SWF) supports placing sprites within sprites, which can lead to complex hierarchies objects. To handle this complexity Macromedia Flash (SWF) uses a naming convention similar to that used by file systems to identify sprites.
For example, the following outline shows four sprites defined within the main movie:
MainMovie.swf
SpriteA (name: Jack)
SpriteA1 (name: Bert)
SpriteA2 (name: Ernie)
SpriteB (name: Jill)
The following SetTarget paths identify the sprites above:
· /Jack targets SpriteA from the main movie.
·
../ targets the main
movie from SpriteA
· /Jack/Bert targets SpriteA1 from any other sprite or the main movie.
· Bert targets SpriteA1 from SpriteA.
· ../Ernie targets SpriteA2 from SpriteA1
· ../../Jill targets SpriteB from SpriteA1
The DefineSprite tag defines a sprite character. It consists of a character ID and a frame count, followed by a series of control tags. The sprite is terminated with an End tag.
Definition tags (such as DefineShape) are not allowed in the DefineSprite tag. All the characters referred to by control tags in the sprite must be defined in the main body of the file before the sprite is defined.
(See class FDTSprite in the Macromedia Flash File Format (SWF) SDK)
|
DefineSprite |
||
|
Field |
Type |
Comment |
|
Header |
RECORDHEADER |
Tag ID = 39 |
|
Sprite ID |
UI16 |
ID of sprite |
|
FrameCount |
UI16 |
Number of frames in Sprite. |
|
ControlTags |
TAG[one or more] |
A series of tags |
The valid tags within a DefineSprite tag are as follows:
· DoAction
· End
A QuickTime movie is defined with the DefineMovie tag. It is defined using an external reference to a file or URL. A movie character can be placed on the Display List like any other character.
|
DefineMovie |
||
|
Field |
Type |
Comment |
|
Header |
RECORDHEADER |
Tag ID = 38 |
|
MovieID |
UI16 |
ID of Movie |
|
MovieName |
Filename or URL of the
movie. |


Draw a polygon using the draw tools.
Calculate area of selected features
Edit Polygon(s)
Lock Polygon(s)
Calculate intersect of layer polygons


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|
dynamic_graph_manager
|
This class has for purpose to manage the different processes during run time. More...
#include <dynamic_graph_manager.hh>
Public Member Functions | |
| DynamicGraphManager () | |
| DynamicGraphManager, constructor of the class. | |
| virtual | ~DynamicGraphManager () |
| DynamicGraphManager, destructor of the class. | |
| void | initialize (YAML::Node param) |
| initialize the basic variables | |
| void | run () |
| run() splits the process in the dynamic_graph process and the hadware_communication process. More... | |
| void | wait_start_dynamic_graph () |
| wait_start_dynamic_graph put the current thread to sleep until the user start the dynamic graph | |
| void | wait_stop_dynamic_graph () |
| wait_stop_dynamic_graph put the current thread to sleep until the user stop the dynamic graph | |
| void | wait_stop_hardware_communication () |
| wait_stop_hardware_communication put the current thread to sleep until the user stop the hardware communication. More... | |
| void | initialize_dynamic_graph_process () |
| initialize_dynamic_graph_process instanciates all variables related to the dynamic_graph and user interface. | |
| void | run_python_command (std::ostream &file, const std::string &command) |
| run_python_command More... | |
| void | python_prologue () |
| python_prologue get the pointer of the device in the the python interpretor. | |
| virtual void | run_dynamic_graph_process () |
| run_dynamic_graph_process spawns the real time thread and becomes a ros spinner (thread in charge of the ros::service callbacks). More... | |
| virtual void | run_hardware_communication_process () |
| run_hardware_communication_process spawns the real time thread. More... | |
| virtual void | run_single_process () |
| run_single_process spawns the real time thread. More... | |
| virtual void | initialize_hardware_communication_process () |
| initialize_hardware_communication_process instanciate all variables related to the hardware communication. More... | |
| virtual void | get_sensors_to_map (VectorDGMap &) |
| get_sensors_to_map is the fonction that get the motor command from a map and that uses the drivers to send these command to the robot. More... | |
| virtual void | set_motor_controls_from_map (const VectorDGMap &) |
| set_motor_controls_from_map is the fonction that get the motor command from a map and that uses the drivers to send these command to the robot. More... | |
| virtual void | compute_safety_controls () |
| compute_safety_controls computes safety controls very fast in case the dynamic graph is taking to much computation time or has crashed. | |
| void | stop_dynamic_graph () |
| stop_dynamic_graph stop the DynamicGraph. More... | |
| void | start_dynamic_graph () |
| start_dynamic_graph start the DynamicGraph. More... | |
| bool | is_dynamic_graph_stopped () |
| get the status of the dynamic graph (is running or not) More... | |
| void | stop_hardware_communication () |
| stop_hardware_communication stops the hardware communication. More... | |
| void | start_hardware_communication () |
| start_hardware_communication starts the hardware communication. More... | |
| bool | is_hardware_communication_stopped () |
| get the status of the hardware communication (is running or not). More... | |
| pid_t | pid_dynamic_graph_process () |
| pid_dynamic_graph_process is an accessor on the pid of the process More... | |
| pid_t | pid_hardware_communication_process () |
| pid_hardware_communication_process is an accessor on the pid of the process More... | |
| Device & | device () |
| device is a getter method on the Device internal pointer. More... | |
| bool | has_dynamic_graph_process_died () |
| has_dynamic_graph_process_died check if the process of the DynamicGraph has died or not. More... | |
| virtual bool | is_in_safety_mode () |
| is_in_safety_mode check if the dynamic graph is still alive and sending commands at a descent frequency. More... | |
Static Public Attributes | |
| static const std::string | dg_ros_node_name_ = "dynamic_graph" |
| dg_ros_node_name_ this is the ros node name of the dynamic graph process | |
| static const std::string | hw_com_ros_node_name_ |
| hw_com_ros_node_name_ this is the ros node name of the harware communication process More... | |
| static const std::string | shared_memory_name_ = "DGM_ShM" |
| shared_memory_name is the name of the shared memory segment to be used | |
| static const std::string | sensors_map_name_ = "sensors_map" |
| sensors_map_name is the name of the sensor map inside the shared memory segment | |
| static const std::string | motor_controls_map_name_ |
| motor_controls_map_name is the name of the motor controls map inside the shared memory segment More... | |
| static const std::string | cond_var_name_ = "cond_var" |
| cond_var_sensors_name_ is the name of the condition variable in the shared memory | |
Protected Member Functions | |
| void | add_user_command (std::function< void(void)> func) |
| Method inherited. More... | |
Protected Attributes | |
| ros::ServiceServer | ros_service_start_dg_ |
| ros_service_start_dg_ allows to start the dynamic graph on call. More... | |
| ros::ServiceServer | ros_service_stop_dg_ |
| ros_service_stop_dg_ allows to stop the dynamic graph on call. More... | |
| std::atomic< bool > | is_dynamic_graph_stopped_ |
| is_dynamic_graph_stopped_ is the flag reflecting the state of the dynamic graph. More... | |
| std::atomic< bool > | is_hardware_communication_stopped_ |
| is_hardware_communication_stopped_ is the flag reflecting the state of the hardware communication thread. More... | |
| std::unique_ptr< dynamic_graph::RosPythonInterpreter > | ros_python_interpreter_ |
| ros_python_interpreter_ptr_ is a ROS wrapper around a python interpreter. | |
| std::unique_ptr< real_time_tools::RealTimeThread > | thread_dynamic_graph_ |
| thread_dynamic_graph_ is the real time thread that runs the dynamic graph. | |
| std::unique_ptr< real_time_tools::RealTimeThread > | thread_hardware_communication_ |
| thread_hardware_communication_ is the real thread that communicate with the hardware. | |
| pid_t | pid_dynamic_graph_process_ |
| pid_dynamic_graph_process_ is the pid of the DynamicGraph process. More... | |
| pid_t | pid_hardware_communication_process_ |
| pid_hardware_communication_process_ is the pid of the hardware communication process. More... | |
| std::unique_ptr< Device > | device_ |
| device_ is the DynamicGraph device that manages the computation of the graph. | |
| VectorDGMap | sensors_map_ |
| sensors_map_ is a map of dynamicgraph::Vector. More... | |
| VectorDGMap | motor_controls_map_ |
| motor_controls_map_ is a map of dynamicgraph::Vector. More... | |
| std::unique_ptr< shared_memory::LockedConditionVariable > | cond_var_ |
| cond_var_sensors_ this condition variable allow the computation of the dynamic graph just after the acquisition of the sensors | |
| bool | has_been_waken_by_dg_ |
| has_been_waken_by_dg_ is a flag that indicates if the hardware communication process has been awaken by the dynamic_graph process or not. | |
| unsigned | missed_control_count_ |
| missed_control_count_ is counting the number of iteration when the dynamic_graph failed to provide data. | |
| unsigned | max_missed_control_ |
| max_missed_control_ if the missed_control_count_ reach the value of max_missed_control_ then we switch to safety mode. | |
| clock::duration | control_period_ |
| control_period_ this is the control period in nanoseconds. | |
| clock::time_point | hw_time_loop_before_sleep_ |
| hw_time_loop_before_sleep_ is the time measurement just before the hardware communication loop goes to sleep. | |
| clock::time_point | hw_time_loop_after_sleep_ |
| hw_time_loop_after_sleep_ is the time measurement just after the hardware communication loop goes to sleep. | |
| clock::duration | hw_meas_sleep_time_ |
| hw_measured_sleep_time_ is the time during which the hardware communication process actually slept. | |
| clock::duration | hw_ref_sleep_time_ |
| hw_ref_sleep_time_ is the time during which the hardware communication process is supposed to sleep. | |
| clock::duration | hw_meas_active_time_ |
| hw_meas_active_time_ is the time during which the hardware communication process is supposed to sleep. | |
| bool | is_real_robot_ |
| is_real_robot this boolean is a parameter to indicate if yes or no we are in simulation or in a real robot mode. | |
| std::string | dg_active_timer_file_ |
| dg_active_timer_file_ this is the path to the file that will contain the computation time of each of the dynamic graph complete execution. | |
| std::string | dg_sleep_timer_file_ |
| dg_sleep_timer_file_ this is the path to the file that will contain the sleep duration of the dynamic graph thread. | |
| std::string | dg_timer_file_ |
| dg_timer_file_ this is the path to the file that will contain the time of the dynamic graph loop. | |
| std::string | hwc_active_timer_file_ |
| hwc_active_timer_file_ this is the path to the file that will contain the computation time of each active period of the hardware communication loop. | |
| std::string | hwc_sleep_timer_file_ |
| hwc_sleep_timer_file_ this is the path to the file that will contain the sleeping time of the hardware communication loop. | |
| std::string | hwc_timer_file_ |
| hwc_timer_file_ this is the path to the file that will contain the computation time of each of the hardware communication complete execution. | |
| std::string | log_dir_ |
| log_folder_ is the folder where all the data of the current experiment will be saved. | |
| std::string | python_log_file_ |
| This file will contain the python interpreter output. | |
| std::string | app_dir_ |
| This is the application directory in the home directory. | |
| real_time_tools::Timer | dg_active_timer_ |
| dg_active_timer_ is the timer measuring the computation time of the dynamic graph loop. | |
| real_time_tools::Timer | dg_sleep_timer_ |
| dg_sleep_timer_ is the timer measuring the time during which the dynamic graph loop sleeps. | |
| real_time_tools::Timer | dg_timer_ |
| dg_timer_ is the timer measuring the duration time of the dynamic graph loop. | |
| real_time_tools::Timer | hwc_active_timer_ |
| hwc_active_timer is measuring the active time of the hardware communication loop | |
| real_time_tools::Timer | hwc_sleep_timer_ |
| hwc_sleep_timer is measuring the sleeping time of the hardware communication loop | |
| real_time_tools::Timer | hwc_timer_ |
| hwc_timer is measuring the time of the hardware communication loop | |
| unsigned | memory_buffer_timers_ |
| memory_buffer_timers_ is the size of the memory buffers for the real_time_tools timers. | |
| real_time_tools::Spinner | hwc_spinner_ |
| This class allows us to time the real time thread for the hardware communication. | |
| double | hwc_predicted_sleeping_time_ |
| This corresponds to the predicted sleeping time for the hardware communication process. More... | |
| double | maximum_time_for_user_cmd_ |
| This the duration during which a user command can be executed. | |
| std::deque< std::function< void(void)> > | user_commands_ |
| This is the list of the user commands. | |
| std::deque< ros::ServiceServer > | ros_user_commands_ |
| Attribute shared with the daughter class. More... | |
| double | control_period_sec_ |
| control_period_sec_ this is the control period in Seconds (S.I. More... | |
| YAML::Node | params_ |
| params_ is the pool of parameters in a yaml tree | |
| std::mutex | hwc_mutex_ |
Private Member Functions | |
| bool | start_dynamic_graph (std_srvs::Empty::Request &, std_srvs::Empty::Response &) |
| Method NOT inherited. More... | |
| bool | stop_dynamic_graph (std_srvs::Empty::Request &, std_srvs::Empty::Response &) |
| stop_dg is the callback method of the ROS service stop dynamic graph More... | |
| void | start_ros_service (ros::NodeHandle &ros_node_handle) |
| start_ros_service is the method that advertise the different ros services. | |
| void * | dynamic_graph_real_time_loop () |
| dynamic_graph_real_time_loop is the method used to execute the dynamic graph. | |
| void * | hardware_communication_real_time_loop () |
| hardware_communication_real_time_loop is the method that communicate with the hardware and send the commands (torque, position, current, ...) | |
| void * | single_process_real_time_loop () |
| single_process_real_time_loop is the method that performs the control but in one single process. More... | |
Static Private Member Functions | |
| static void * | dynamic_graph_real_time_loop_helper (void *context) |
| dynamic_graph_real_time_loop_helper is a static member allowing to use the posix pthread_create. More... | |
| static void * | hardware_communication_real_time_loop_helper (void *context) |
| dynamic_graph_real_time_loop_helper is a static member allowing to use the posix pthread_create. More... | |
| static void * | single_process_real_time_loop_helper (void *context) |
| dynamic_graph_real_time_loop_helper is a static member allowing to use the posix pthread_create. More... | |
This class has for purpose to manage the different processes during run time.
The main tasks are:
|
protected |
|
inline |
device is a getter method on the Device internal pointer.
|
inlinestaticprivate |
dynamic_graph_real_time_loop_helper is a static member allowing to use the posix pthread_create.
| context | is the DynamicGraphManager that spawned the thread. |
|
inlinevirtual |
get_sensors_to_map is the fonction that get the motor command from a map and that uses the drivers to send these command to the robot.
Each robot must have a different implementation of this function. WARNING, this function needs to be overloaded using the actual drivers of the robot.
Reimplemented in dynamic_graph_manager::SimpleDGM.
|
inlinestaticprivate |
dynamic_graph_real_time_loop_helper is a static member allowing to use the posix pthread_create.
| context | is the DynamicGraphManager that spawned the thread. |
| bool DynamicGraphManager::has_dynamic_graph_process_died | ( | ) |
has_dynamic_graph_process_died check if the process of the DynamicGraph has died or not.
|
inlinevirtual |
initialize_hardware_communication_process instanciate all variables related to the hardware communication.
In addition it spawns the real time thread. WARNING, this function needs to be overloaded using the actual drivers of the robot.
Reimplemented in dynamic_graph_manager::SimpleDGM.
|
inline |
get the status of the dynamic graph (is running or not)
|
inline |
get the status of the hardware communication (is running or not).
|
inlinevirtual |
is_in_safety_mode check if the dynamic graph is still alive and sending commands at a descent frequency.
Reimplemented in dynamic_graph_manager::SimpleDGM.
|
inline |
pid_dynamic_graph_process is an accessor on the pid of the process
|
inline |
pid_hardware_communication_process is an accessor on the pid of the process
| void DynamicGraphManager::run | ( | ) |
run() splits the process in the dynamic_graph process and the hadware_communication process.
It initialize them and run them. WARNING this a NONE blocking function. One can spin endlessly using the ROS: ros::waitForShutdown(), for example.
|
virtual |
run_dynamic_graph_process spawns the real time thread and becomes a ros spinner (thread in charge of the ros::service callbacks).
This function is virtual has it might differ from os to os.
|
virtual |
run_hardware_communication_process spawns the real time thread.
WARNING this function is not blocking. Function to block are available like ros::waitForShutdown() for example. This function is virtual has it might differ from os to os.
| void DynamicGraphManager::run_python_command | ( | std::ostream & | file, |
| const std::string & | command | ||
| ) |
run_python_command
| file | is the logging file to log the entry |
| command | is the python command itself |
|
virtual |
run_single_process spawns the real time thread.
WARNING this function is not blocking. Function to block are available like ros::waitForShutdown() for example. This function is virtual has it might differ from os to os.
|
inlinevirtual |
set_motor_controls_from_map is the fonction that get the motor command from a map and that uses the drivers to send these command to the robot.
Each robot must have a different implementation of this function. WARNING, this function needs to be overloaded using the actual drivers of the robot.
Reimplemented in dynamic_graph_manager::SimpleDGM.
|
private |
single_process_real_time_loop is the method that performs the control but in one single process.
(torque, position, current, ...)
|
inlinestaticprivate |
dynamic_graph_real_time_loop_helper is a static member allowing to use the posix pthread_create.
| context | is the DynamicGraphManager that spawned the thread. |
|
inline |
start_dynamic_graph start the DynamicGraph.
;)
|
inlineprivate |
Method NOT inherited.
start_dg is the callback method of the ROS service start dynamic graph.
|
inline |
start_hardware_communication starts the hardware communication.
;)
|
inline |
stop_dynamic_graph stop the DynamicGraph.
;)
|
inlineprivate |
stop_dg is the callback method of the ROS service stop dynamic graph
|
inline |
stop_hardware_communication stops the hardware communication.
;)
| void DynamicGraphManager::wait_stop_hardware_communication | ( | ) |
wait_stop_hardware_communication put the current thread to sleep until the user stop the hardware communication.
&& hw_com_ros_node.ok()
|
protected |
control_period_sec_ this is the control period in Seconds (S.I.
units) for computation.
|
static |
hw_com_ros_node_name_ this is the ros node name of the harware communication process
|
protected |
This corresponds to the predicted sleeping time for the hardware communication process.
If this time is bigger than a certain threshold then user commands to the hardware can be sent.
|
protected |
is_dynamic_graph_stopped_ is the flag reflecting the state of the dynamic graph.
|
protected |
is_hardware_communication_stopped_ is the flag reflecting the state of the hardware communication thread.
|
protected |
motor_controls_map_ is a map of dynamicgraph::Vector.
They represent all the controls to be sent to the robot.
|
static |
motor_controls_map_name is the name of the motor controls map inside the shared memory segment
|
protected |
pid_dynamic_graph_process_ is the pid of the DynamicGraph process.
It is initialized to 0 and set during the DynamicGraphManager::run method
|
protected |
pid_hardware_communication_process_ is the pid of the hardware communication process.
It is initialized to 0 and set during the DynamicGraphManager::run method
|
protected |
ros_service_start_dg_ allows to start the dynamic graph on call.
It simply sets a flags that is used to wait the user call. Only used in the dynamic_graph process.
|
protected |
ros_service_stop_dg_ allows to stop the dynamic graph on call.
It simply sets a flags that stop the main real time the control loop. Only used in the dynamic_graph process.
|
protected |
Attribute shared with the daughter class.
This is the list of the ros user commands. The class inheriting from this one can add services for the hardware communication process.
|
protected |
sensors_map_ is a map of dynamicgraph::Vector.
They represent all the sensors data measured on the robot.


Puppet Class: php::composer::auto_update
- Defined in:
- manifests/composer/auto_update.pp
Overview
Install composer package manager
=== Parameters
[max_age] Defines number of days after which Composer should be updated
[source] Holds URL to the Composer source file
[path] Holds path to the Composer executable
[proxy_type] proxy server type (none|http|https|ftp)
[proxy_server] specify a proxy server, with port number if needed. ie: https://example.com:8080.
=== Examples
include php::composer::auto_update class { "php::composer::auto_update": "max_age" => 90 }
28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 |
# File 'manifests/composer/auto_update.pp', line 28
class php::composer::auto_update (
$max_age,
$source,
$path,
$proxy_type = undef,
$proxy_server = undef,
) {
if $caller_module_name != $module_name {
warning('php::composer::auto_update is private')
}
if $proxy_type and $proxy_server {
$env = [ 'HOME=/root', "${proxy_type}_proxy=${proxy_server}" ]
} else {
$env = [ 'HOME=/root' ]
}
exec { 'update composer':
command => "${path} --no-interaction --quiet self-update",
environment => $env,
onlyif => "test `find '${path}' -mtime +${max_age}`",
path => [ '/bin/', '/sbin/' , '/usr/bin/', '/usr/sbin/', '/usr/local/bin', '/usr/local/sbin' ],
require => [File[$path], Class['::php::cli']],
}
}
|


The 37 new bands that have been announced for Download Festival 2020
Organisers have revealed new additions to the line-up
by Hayley WatsonA huge number of bands have been announced for next year’s Download Festival.
Download Festival 2020 will see KISS, Iron Maiden and System of a Down headline the rock festival.
Now, organisers have revealed the second run of bands for the festival – with a whopping 37 new acts in total.
Joining the headliners will be Danish rockers Volbeat, American metalcore legends Killswitch Engage, and Japanese kawaii metal band Babymetal.
The festival takes place at the 'spiritual home of rock' of Donington Park in Leicestershire.
Commenting on the announcement, Volbeat said: "We are very excited to return to Donington Park once again to rock with all of our friends in the UK alongside so many great bands. See you in June!"
Jesse Leach from Killswitch Engage added: "We are honoured and excited to play the mighty Download festival once again! We are ready to kick out our new songs and play the old anthems as well!"
While SU-METAL from Babymetal said: "The crowd at Download Festival always welcomes us with a lot of energy so I can’t wait to perform there again! We hope to bring even more power and energy so please look forward to our performance!"
The three-day festival takes between 12 and 14 June 2020, and tickets are now on sale at the official Download website .
View the full list of acts that have been added to the line-up below.
The 37 acts added to the Download Festival line-up
Airbourne
Babymetal
Baroness
Blackout Problems
Bleed From Within
Blues Pills
Bokassa
British Lion
Bush
Cellar Door Moon Crow
Chelsea Grin
Dead Label
Dead Posey
Dying Fetus
Electric Wizard
Killswitch Engage
Lit
Lotus Eater
Marianas Trench
Obituary
Periphery
P.O.D.
Powerwolf
Pup
Puppy
Skillet
Stone Broken
Theory
The Last Internationale
The Pretty Reckless
The Wildhearts
Tiny Moving Parts
Uncured
Volbeat
Wargasm
Wayward Sons
Wednesday 13


1 write to M3PWorkflowLoadedForExecutionEvent
System.Management.Automation (1)
utils\tracing\TracingGen.cs (1)
197
M3PWorkflowLoadedForExecutionEvent
= new EventDescriptor(0xb024, 0x1, 0x11, 0x5, 0x14, 0x6, (long)0x4000000000000200);
1 reference to M3PWorkflowLoadedForExecutionEvent
System.Management.Automation (1)
utils\tracing\TracingGen.cs (1)
844
WriteEvent(
M3PWorkflowLoadedForExecutionEvent
, workflowId);


| Trees | Indices | Toggle frames |
|---|
An immutable string of glyphs that can be rendered quickly.
This class is ideal for quickly rendering single or multi-line strings of text that use the same font. To wrap text using a glyph string, call get_break_index to find the optimal breakpoint for each line, the repeatedly call draw for each breakpoint.
Deprecated: Use pyglet.text.layout classes.
|
__init__(self,
text,
glyphs,
x=0,
y=0)
Create a glyph string.
|
|
| int |
get_break_index(self,
from_index,
width)
Find a breakpoint within the text for a given width.
|
| float |
get_subwidth(self,
from_index,
to_index)
Return the width of a slice of this string.
|
|
draw(self,
from_index=0,
to_index=None)
Draw a region of the glyph string.
|
Create a glyph string.
The text string is used to determine valid breakpoints; all glyphs must have already been determined using pyglet.font.base.Font.get_glyphs. The string will be positioned with the baseline of the left-most glyph at the given coordinates.
Find a breakpoint within the text for a given width.
Returns a valid breakpoint after from_index
so that the text
between from_index
and the breakpoint fits within width
pixels.
This method uses precomputed cumulative glyph widths to give quick answer, and so is much faster than pyglet.font.base.Font.get_glyphs_for_width.
from_index
if there is no valid breakpoint.Draw a region of the glyph string.
Assumes texture state is enabled. To enable the texture state:
from pyglet.gl import * glEnable(GL_TEXTURE_2D)
| Trees | Indices | Toggle frames |
|---|
| Generated by Epydoc 3.0beta1 on Sun Mar 22 20:15:39 2009 | http://epydoc.sourceforge.net |


QuizDrum
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Guest {{.U.GetId}}
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Edit Quiz Properties.
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{{range .Q.GetQuestions}}
{{.GetTitle}}
{{.GetHtmlBody}}
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{{end}}
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Quiz Name
{{.Q.GetHtmlDescription}}
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Update Quiz Properties
delete
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undo
Undo Delete
Title
Body
Short Text Answer
Long Text Answer
Integer Answer
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Approximate Decimal Point Answer
For multiple choice questions only, set the options:
Option 1:
❌
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❌
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{% extends "base_generic.html" %} {% block title %}
Welcome to the Accounts of Fairy Maids, a webapp developed by Robert Melikyan!
The database has the following record counts:
You have visited this page {{ num_visits }}{% if num_visits == 1 %} time{% else %} times{% endif %}.
{% endblock %}


Just like you did for poker, you also want to know those days where you realized a positive return for roulette.
selection_vector
, this time to see if you made profit with roulette for different days.roulette_winning_days
. This vector thus contains the positive winnings of roulette_vector
.
# Poker and roulette winnings from Monday to Friday:
poker_vector <- c(140, -50, 20, -120, 240)
roulette_vector <- c(-24, -50, 100, -350, 10)
days_vector <- c("Monday", "Tuesday", "Wednesday", "Thursday", "Friday")
names(poker_vector) <- days_vector
names(roulette_vector) <- days_vector
# Which days did you make money on roulette?
selection_vector <-
# Select from roulette_vector these days
roulette_winning_days <-
# Poker and roulette winnings from Monday to Friday:
poker_vector <- c(140, -50, 20, -120, 240)
roulette_vector <- c(-24, -50, 100, -350, 10)
days_vector <- c("Monday", "Tuesday", "Wednesday", "Thursday", "Friday")
names(poker_vector) <- days_vector
names(roulette_vector) <- days_vector
# Which days did you make money on roulette?
selection_vector <- roulette_vector > 0
# Select from roulette_vector these days
roulette_winning_days <- roulette_vector[selection_vector]
msg = "Do not change anything about the definition and naming of `poker_vector` and `roulette_vector`."
test_object("days_vector", undefined_msg = msg, incorrect_msg = msg)
test_object("poker_vector", eq_condition = "equal", undefined_msg = msg, incorrect_msg = msg)
test_object("roulette_vector", eq_condition = "equal", undefined_msg = msg, incorrect_msg = msg)
test_object("selection_vector",
incorrect_msg = "It looks like `selection_vector` does not contain the correct result. Use `roulette_vector > 0`.")
test_object("roulette_winning_days",
incorrect_msg = "It looks like `roulette_winning_days` does not contain the correct result. Use `roulette_vector[selection_vector]`.")
success_msg("Great! This exercise concludes the chapter on vectors. The next chapter will introduce you to the two-dimensional version of vectors: matrices.")
Once you've correctly calculated selection_vector
, you can again use roulette_vector[selection_vector]
to select the positive results from roulette_vector
.


Reasons why Chelsea are considering a move for Wilfried Zaha
by Simon PhillipsChelsea have been linked to making a move for Crystal Palace striker Wilfried Zaha for some time now and most major UK media outlets are reporting it, including this one from The Telegraph.
The most common reaction from Chelsea supporters appears to be negative regarding the possibility of Zaha joining them. Many are against the move and feel there are better options.
I will begin this by saying that I agree with that sentiment, there are better options, and I like any Chelsea fan, have preferred targets such as Jadon Sancho for example for the wing positions.
However, the purpose of this article is to play devils advocate a little and discuss the thinking behind a potential move for Zaha by the club themselves, and I have come up with the following reasons.
- He wants to leave and is more than a realistic buy in January, Palace want Batshuayi.
It isn’t always going to be easy to sign players in January. You have less time, and the demanded fees are usually higher. But with that said, Zaha is desperate to leave Palace and his agent has already been laying down the foundations for a January move away.
His price might not necessarily be the cheapest, but Chelsea could decide to offer Michy Batshuayi as part of any deal. He had a good loan spell there, isn’t getting first team football at Chelsea, and could decide to leave in January.
Lets be honest, Chelsea need reinforcements in January.
2. Chelsea would look at him AS WELL as another winger (Sancho).
He wouldn’t be signed instead of their main winger pursuit, he would be signed as well as. If it was instead of, then I wouldn’t even be trying to look for the positives and I’d shut it down right away.
However, because he can play anywhere across the front three, essentially he will be coming in to backup Tammy Abraham in the striker position, and provide competition for the winger spaces.
Chelsea look set to lose Olivier Giroud, Michy Batshuayi, Pedro, and Willian all by the summer at the latest, some could even be January. So Zaha comes in and replaces one of the strikers, and one of the wingers collectively.
So if you think about Chelsea moving forward, they would have Callum Hudson-Odoi, Christian Pulisic, Jadon Sancho (hypothetically) and Wilfried Zaha (hypothetically) as the wing options, and Tammy Abraham, Wilfried Zaha, plus perhaps one other as the striker options.
So it doesn’t block any other players development, neither does it stop Chelsea signing other world class talents.
3. Not every player we sign will be world class, they can’t all play regularly.
There is this odd trail of thought that Chelsea need to sign only world class players from now on. Whilst I agree they certainly need to add 3 or 4 quality players, someone like Zaha as competition and to fill the squad may not be as bad as some make out.
4. He has Premier League experience and has only been playing in a defensive system.
Having PL experience goes a LONG way in this league. But also, I think Zaha is being under rated be some. He is heavily relied on by Palace as their main attacking threat in a very defensive system.
It is only natural that you will get more out of his ability if he is alongside better players and playing in an attack minded system.
5. He actually does have some quality.
Zaha is one of those rare players who has the ability to change a game by himself. He has pace, is strong, can dribble, shoot, decent on the ball, and is direct.
Yes he might have shown inconsistency over time, but I genuinely feel that could be different around better players.
This isn’t me saying go all out and sign him no matter what. I’m saying that for the right price in January, with Batshuayi as a makeweight, he could certainly improve our attacking options and give Abraham a decent backup option.
More Stories about News Now
Transfer Window Woes
December 6, 2019 14:29
Poll Results: These Chelsea fans select their preferred backup striker and most valued midfielder
November 28, 2019 15:50
Likely Giroud departure means it’s make or break time for Batshuayi at Chelsea
November 21, 2019 15:57


| Class | Description |
|---|---|
| Buyer |
Allows merchant to pass buyer related information in the invoice object.
|
| Invoice |
The type Invoice.
|
| InvoiceBuyerProvidedInfo |
Information collected from the buyer during the process of paying an invoice.
|
| InvoiceEventToken |
The type Invoice event token.
|
| InvoiceItemizedDetails |
The type Invoice itemized details.
|
| InvoiceStatus |
The type Invoice status.
|
| InvoiceTransaction |
Initially empty when the invoice is created.
|
| InvoiceUniversalCodes |
Object containing wallet-specific URLs for payment protocol.
|
| MinerFees |
The total amount of fees that the purchaser will pay to cover BitPay's UTXO sweep cost for an invoice.
|
| MinerFeesItem |
The type Miner fees item.
|
| Refund |
Fully paid invoices can be refunded via the merchant's authorization to issue a refund,
while underpaid and overpaid invoices are automatically executed by BitPay to issue the underpayment
or overpayment amount to the customer.
|
| RefundInfo |
The type Refund info.
|
| RefundStatus |
The type Refund status.
|
| RefundWebhook |
The type Refund webhook.
|
| Shopper |
The type Shopper.
|
| SupportedTransactionCurrencies |
The currencies that may be used to pay this invoice.
|
| SupportedTransactionCurrency |
The currency that may be used to pay this invoice.
|
Copyright © 2023 BitPay. All rights reserved.


CSS Wishlist
Features:
• Static scrolling header.
• Links with borders that show up on mouseover.
• Images with descriptions that popup on mouseover.
• Looping transparent gif over content.
Features:
• Animated background image (Javascript?)
• Expanding nav menu in mobile format.
• Text formatting- overall design has fun campy 50's sci-fi
vibe while still feeling modern. Probably individual elements
with clean simple background- minimal clutter.
• Note: Not very responsive. Also has loading
screens- I found myself exiting the page in impatience.
Responsiveness > fancy JS elements!
Other features/bugfixes planned:
- Dropdown menu for blogs link instead of standalone page
- Spacing adjusted in header (scale appropriately with media queries)
- Header background made opaque
- About page added
- Fix link hover effect on header links- currently on hover they move slightly
- Add dates on blogs in top right corner


|
JavaTM 2 Platform Standard Ed. 5.0 |
|||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
public interface StateFactory
This interface represents a factory for obtaining the state of an object for binding.
The JNDI framework allows for object implementations to be loaded in dynamically via object factories. For example, when looking up a printer bound in the name space, if the print service binds printer names to References, the printer Reference could be used to create a printer object, so that the caller of lookup can directly operate on the printer object after the lookup.
An ObjectFactory is responsible for creating objects of a specific type. In the above example, you may have a PrinterObjectFactory for creating Printer objects.
For the reverse process, when an object is bound into the namespace, JNDI provides state factories. Continuing with the printer example, suppose the printer object is updated and rebound:
The service provider for ctx uses a state factory to obtain the state of printer for binding into its namespace. A state factory for the Printer type object might return a more compact object for storage in the naming system.ctx.rebind("inky", printer);
A state factory must implement the StateFactory interface. In addition, the factory class must be public and must have a public constructor that accepts no parameters.
The getStateToBind() method of a state factory may be invoked multiple times, possibly using different parameters. The implementation is thread-safe.
StateFactory is intended for use with service providers that implement only the Context interface. DirStateFactory is intended for use with service providers that implement the DirContext interface.
NamingManager.getStateToBind(java.lang.Object, javax.naming.Name, javax.naming.Context, java.util.Hashtable, ?>)
,
DirectoryManager.getStateToBind(java.lang.Object, javax.naming.Name, javax.naming.Context, java.util.Hashtable, ?>, javax.naming.directory.Attributes)
,
ObjectFactory
,
DirStateFactory
| Method Summary | |
|---|---|
Object |
getStateToBind(Object obj,
Name name,
Context nameCtx,
Hashtable<?,?> environment)
Retrieves the state of an object for binding. |
| Method Detail |
|---|
Object getStateToBind(Object obj, Name name, Context nameCtx, Hashtable<?,?> environment) throws NamingException
NamingManager.getStateToBind() successively loads in state factories and invokes this method on them until one produces a non-null answer. DirectoryManager.getStateToBind() successively loads in state factories. If a factory implements DirStateFactory, then DirectoryManager invokes DirStateFactory.getStateToBind(); otherwise it invokes StateFactory.getStateToBind().
When an exception is thrown by a factory, the exception is passed on to the caller of NamingManager.getStateToBind() and DirectoryManager.getStateToBind(). The search for other factories that may produce a non-null answer is halted. A factory should only throw an exception if it is sure that it is the only intended factory and that no other factories should be tried. If this factory cannot create an object using the arguments supplied, it should return null.
The name
and nameCtx
parameters may
optionally be used to specify the name of the object being created.
See the description of "Name and Context Parameters" in
ObjectFactory.getObjectInstance()
for details.
If a factory uses nameCtx
it should synchronize its use
against concurrent access, since context implementations are not
guaranteed to be thread-safe.
The name and environment parameters are owned by the caller. The implementation will not modify these objects or keep references to them, although it may keep references to clones or copies.
obj
- A non-null object whose state is to be retrieved.name
- The name of this object relative to nameCtx
,
or null if no name is specified.nameCtx
- The context relative to which the name
parameter is specified, or null if name
is
relative to the default initial context.environment
- The possibly null environment to
be used in the creation of the object's state.
NamingException
- if this factory encountered an exception
while attempting to get the object's state, and no other factories are
to be tried.NamingManager.getStateToBind(java.lang.Object, javax.naming.Name, javax.naming.Context, java.util.Hashtable, ?>)
,
DirectoryManager.getStateToBind(java.lang.Object, javax.naming.Name, javax.naming.Context, java.util.Hashtable, ?>, javax.naming.directory.Attributes)
|
JavaTM 2 Platform Standard Ed. 5.0 |
|||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
Copyright © 2004, 2010 Oracle and/or its affiliates. All rights reserved. Use is subject to license terms. Also see the documentation redistribution policy.


Toggle navigation
Brand
Link
(current)
Circle
Start
End
addPt
Dropdown
Action
Another action
Something else here
Separated link
One more separated link


FOOLS RUSH IN A film review by Walter Frith Copyright 1997 Walter Frith
I don't care how many times a certain premise has been exploited in Hollywood because there are some stories that find a way to reach you by just being well made films. 'Fools Rush In' isn't necessarily well made in a lot of areas but it is a heartfelt romantic adventure with the right doses of comedy and drama mixed together.
Matthew Perry and Salma Hayek are two strangers from wildly different backgrounds who have a one night stand and she shows up three months later to tell him that she's pregnant! After rushing into marriage a lot of things such as religion, living arrangements and dealing with the in-laws are to be sorted out as things begin to unfold in the life of this young couple who have many hurdles to overcome.
I laughed in all the right places and felt sentimental at other times and this is a movie that remains faithful to its central characterizations but does fail to develop its supporting players who could have added a lot of zest to the story.
One of the problems I encountered with 'Fools Rush In' was the tempo with which the story unfolded. It basically tells you everything up front in the first half hour, makes its point but then seems to get lazy before redeeming itself later on. It is an uneven and slightly aloof movie which is pleasant enough and is unquestionably a great date movie. It's one of those movies that in many ways has to be accepted for what it is because extreme criticism of a good natured film can be pushing the boundaries of escapism and 'Fools Rush In' is acceptable escapism.
OUT OF 5> * * * 1/2
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


public
or
protected
visible methods.
In general, checked exceptions used in Calimero should extend the base exception
KNXException
.
Unchecked exceptions only:
Since a method might throw any type of runtime exception, even those not
specified here, there is no Calimero specific base exception for this.
Nevertheless, internal error states and failures originating from Calimero itself
should be signaled through Calimero specific exceptions if possible.


FechaDeCreacion: 2018-01-10T16:29:25.344Z
EpisodiosDondeAparece: ['https://rickandmortyapi.com/api/episode/11', 'https://rickandmortyapi.com/api/episode/16', 'https://rickandmortyapi.com/api/episode/21']
NumeroEpisodiosDondeAparece: ['11', '16', '21']
Genero: Male
Id_Personaje: 331
Imagen: https://rickandmortyapi.com/api/character/avatar/331.jpeg
Location_Name: Planet Squanch
Location_URL: https://rickandmortyapi.com/api/location/35
Nombre: Squanchy
Origen_Name: Planet Squanch
Origen_URL: https://rickandmortyapi.com/api/location/35
Especie: Alien
Status: unknown
Tipo: Cat-like creature
URL: https://rickandmortyapi.com/api/character/331


Premier League table: Liverpool maintain leadership with 8 points over Leicester City
- Premier League table after matchday 16 shows Liverpool are runaway leaders of the table
- The Reds have opened an eight points lead over Leicester City who are second on the table
- Man United have risen to fifth on the table after back to back wins over Spurs and Man City
Liverpool cruised to a 3-0 victory over Bournemouth at Dean Court as they remain unbeaten in the Premier League this campaign.
A goal each from Alex Oxlade-Chamberlain, Naby Keita, and Mohamed Salah ensured Jurgen Klopp's men ran off with maximum after matchday 16.
And they sit at the summit of the table with 46 points - eight points better than the second-placed team, Leicester City after the same number of matches.
PAY ATTENTION: Become a member of the leading sports Facebook group 'Naija Football Fan Zone'
The Merseyside outfit is now looking like they will finally win their first Premier League title after close to three decades.
Ndidi makes big statement about Leicester City's title challenge with Liverpool
Brendan Rodgers' side are the surprise team of the season as no one gave them the chance to be where they are at this point.
The Foxes currently second on the log with 38 points after their 4-1 win over West Ham United last weekend.
Having won the title for the first time in 2015, the King Power Stadium outfit looks like they can contend the title as they are six points better than defending champions Manchester City.
Manchester United climbed to fifth position after their famous victory over Pep Guardiola's Man City at the Etihad Stadium on Saturday.
READ ALSO: NAIJ.com upgrades to Legit.ng
Their back-to-back victories over the citizens and Tottenham pushed them within the Europa League qualification stage - only if they can maintain or better their performances this term.
Southampton, Norwich City, and Watford are at the bottom of the table with 15, 11 and 9 points respectively.
Legit.ng earlier reported that Liverpool defeated Bournemouth 3-0 in last weekend's Premier League clash.
Mohamed Salah, Naby Keita and Oxlade-Chamberlain scored the goals that powered the Reds to victory after regulation period.
They are now eight points ahead of Leicester City and 14 points better than defending champions Man City.
Abu Azeez: Meet the only Nigerian rated among top 50 beach soccer players worldwide | Legit TV


--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/contrapose.html ---
@Patrick Massot I have a feature request.
I would like to do contrapose foo with bar
. Because now the hypothesis name just gets reused, but this can create severe semantic dissonance.
H_nonzero : y ≠ 0 ⊢ ⇑l q ≠ 0
contrapose! H_nonzero
H_nonzero : ⇑l q = 0 ⊢ y = 0
I just do intro bar, apply foo
which I think is shorter! I didn't know about contrapose
But it sounds good for beginners.
I just used contrapose
for the first time today in the sensitivity proof. It's suprisingly useful, especially the !
variant that fixes double negations.
https://github.com/leanprover-community/mathlib/pull/1302
Right, with !
it is really powerful. It fixes double negations, but also changes \not \exists
into \forall
and vice versa.
And it does this recursively
(This feature is also available standalone, as push_neg
)
Once again: kudos to @Patrick Massot
@Rob Lewis does #1302 also clear the old hypothesis?
Because that would make sense, I think. Otherwise you end up with a hypothesis that is the negation of the goal. Pretty useless, as long as Lean is consistent :wink:
Yes, it reverts the old hypothesis, contraposes the goal, then introduces the new hypothesis with the new name.
Awesome!
Sometimes contrapose
fails because I'm not in classical mode. What do people think of enhancing contrapose
so that it invokes classical
automatically in such cases?
Indeed this tactic doesn't make much sense in anon-classical context. It could start with classical.
Well, sometimes it works... If you're doing fake proof by contradiction.
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


Before Change
with tf.compat.v1.name_scope(metric.name,
"normalized_discounted_cumulative_gain",
(labels, predictions, weights)):
return metric.compute(labels, predictions, weights)
class _DCGMetric(_RankingMetric):
Implements discounted cumulative gain (DCG).
After Change
with tf.compat.v1.name_scope(metric.name,
"normalized_discounted_cumulative_gain",
(labels, predictions, weights)):
per_list_ndcg, per_list_weights = metric.compute(labels, predictions,
weights)
return tf.compat.v1.metrics.mean(per_list_ndcg, per_list_weights)
class _DCGMetric(_RankingMetric):


|
Platinum_Genetic_Algorithm_Doc
|
#include <ctime>
#include <cstdlib>
#include <algorithm>
#include <fstream>
#include <sstream>
#include <iostream>
#include <vector>
#include "../includes/Genetic_Algorithm.h"
#include "../includes/Circuit_Simulator.h"
Functions | |
| bool | Check_Convergence (double expected_performance, double performance, double tol, int steps, int max_steps) |
| void | find_max_min (double *performance_list, int num_parents, int &max_index, int &min_index) |
| void | select_parent (int &tgt_parent_index_1, int &tgt_parent_index_2, double *distribution, int num_parents) |
| bool | RollingDice (double crossover_rate) |
| void | mutation (int *circuit_vector, double gene_change_rate) |
| void | swapping_parent (int **all_parents, int **new_all_parents, int num_parents, int length) |
| void | run_genetic_algorithm (int **all_parents, int **new_all_parents, double *performance_list, double *distribution, int num_parents, int num_units, int max_steps, double gene_change_rate, double crossover_rate) |
| bool Check_Convergence | ( | double | expected_performance, |
| double | performance, | ||
| double | tol, | ||
| int | steps, | ||
| int | max_steps | ||
| ) |
Function to check wthether the genetic algorithm has found a vector close to the exepected performance. Returns true when the vector has converged.
expected_performance: This is the performance expected from the unit's vector
performance: This is to calculate performance
tol: This is the accepted tolerance
steps: Number of steps that has been done while checking for performance
max_steps: Maximum steps to be done.
| void find_max_min | ( | double * | performance_list, |
| int | num_parents, | ||
| int & | max_index, | ||
| int & | min_index | ||
| ) |
Function to find the maximum and minimum values from the performance list as well as their indices.
performance_list: List of performance values.
num_parents: Total number of parents.
max_index: Maximum index in the list.
min_index: Maximum index in the list.
| void mutation | ( | int * | circuit_vector, |
| double | gene_change_rate | ||
| ) |
Function to perform mutation.
circuit_vector: a circuit vector
gene_change_rate: rate at which mutations are introduced (recommended values < 1%).
| bool RollingDice | ( | double | crossover_rate | ) |
Function to decide whether a vector will crossover. Returns true if a vector will crossover and false if it won't.
crossover_rate: probability of crossing over selected parents(a recommended range between 0.8 and 1).
| void run_genetic_algorithm | ( | int ** | all_parents, |
| int ** | new_all_parents, | ||
| double * | performance_list, | ||
| double * | distribution, | ||
| int | num_parents, | ||
| int | num_units, | ||
| int | max_steps, | ||
| double | gene_change_rate, | ||
| double | crossover_rate | ||
| ) |
Main function to run genetic algorithm.
all_parents: all vectors of previous parents.
new_all_parents: all vectors of new parents.
performance_list: list of performance values.
distribution: number to represent the likelihood of a vector showing up as a parent based on its performance
num_parents: total number of parent vectors.
num_units: total number of units in the circuit.
max_steps: Maximum steps to be done.
gene_change_rate: rate at which mutations are introduced (recommended values < 1%).
crossover_rate: probability of crossing over selected parents(a recommended range between 0.8 and 1).
| void select_parent | ( | int & | tgt_parent_index_1, |
| int & | tgt_parent_index_2, | ||
| double * | distribution, | ||
| int | num_parents | ||
| ) |
Function to choose two parents from a number of parents to produce children depending on the distribution values.
tgt_parent_index_1: first target parent index
tgt_parent_index_2: second target parent index
distribution: number to represent the likelihood of a vector showing up as a parent based on its performance
| void swapping_parent | ( | int ** | all_parents, |
| int ** | new_all_parents, | ||
| int | num_parents, | ||
| int | length | ||
| ) |
Function to swap old and new parents.
all_parents: all vectors of previous parents.
new_all_parents: all vectors of new parents.
num_parents: total number of parent vectors.
length: length of the parent vectors.


Look: Mouse
Shoot: Left Mouse
Up/Down Arrow: Change sensitivity (training only)
I: Invert Y (pitch) sensitivity
Move: WASD (or arrows)
Run: SHIFT
Jump: SPACE
Reset score banner: R


Fayemi attends Fayose son’s wedding in Lagos
by Agency ReportEkiti State Governor, Dr Kayode Fayemi, on Saturday joined other well wishers to celebrate with the family of the immediate past governor of the state, Ayodele Fayose, whose son, Tomiwa, got married.
The event drew many important persons to the Haven Event Centre, Ikeja, Lagos
The event saw the duo burying their political differences to savour the moment.


Pick a date from calander:
Event Details:
* click top of the details to edit
© 2020 Copyright : Pasindu Nawodya


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@* * Copyright 2023 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import include._ @import forms2._ @import config.{ ApplicationConfig} @import utils.Strings._ @import views.html.helper.CSRF @import models.status.{Renewal, ReadyForRenewal, RenewalSubmitted} @( canSubmit: Boolean, renewal: Renewal, renewalSectionCompleted: Boolean = false )(implicit messages: Messages, request: Request[_])
@{(renewalSectionCompleted, canSubmit) match { case(true, false) => Messages("renewal.progress.complete.sections.incomplete") case(true, true) => Messages("renewal.progress.ready.to.submit.intro") case(false, _) => Messages("renewal.progress.submit.intro") }}
@if(renewalSectionCompleted){ @if(canSubmit) { }@anchor( attrHref = controllers.renewal.routes.SummaryController.get.url, linkText = Messages("renewal.progress.edit"), id=Some("renewal-progress-edit") )
} else {@{renewal match { case _:RenewalSubmitted => { anchor( attrHref = controllers.renewal.routes.SummaryController.get.url, linkText = Messages("renewal.progress.continue"), attrRole = true, id=Some("renewal-progress-continue") ) } case _ => { anchor( attrHref = controllers.renewal.routes.WhatYouNeedController.get.url, linkText = Messages("renewal.progress.continue"), attrRole = true, id=Some("renewal-progress-continue") ) } }}
}


{% extends "layout.html" %} {% block page_title %} GOV.UK prototype kit {% endblock %} {% block content %} Enter card details Card number Accepted credit and debit card types Expiry date For example, 07/17 Month Year Name on card Card security code The last 3 digits on the back of the card Billing address This is the address associated with the card Country United Kindom Country 1 Country 2 Building number or name, and street Town or city Postcode Email We'll send your payment confirmation here Cancel payment Payment summary Government service Total amount: £{{data['amount-paid']}} {% endblock %}
Accepted credit and debit card types
This is the address associated with the card
Cancel payment
Government service
£{{data['amount-paid']}}


This example uses the ammo.js physics library, that is a direct port of the Bullet physics engine. You can find the basic API documentation of the Bullet engine here.
This example explores the ConvexObjectBreaker class, that can be used to subdivide a convex Geometry object into pieces.
Open in a new tab


This is a story told from your character's point of view who is Riley. She is a 16 year old girl who gets sucked in into an apocalyptic world, where her ( or technically your ) morals and good sense of character is tested. She also meet survivors on the way so good luck.
Story By Adam Zaman Website by Adnaan Rahman Coding by Khen Dasal, Adnaan Rahman and Michael Sorohan