#include <GrMeshInst.h>
Classes | |
| struct | SBoundsInfo |
Public Member Functions | |
| GrMeshInst (UReader &reader, const UFastArray< URef< GrMesh > > &meshArray) | |
| matInfo is an array of materials... one is required for each range in the mesh. | |
| GrMeshInst (UReader &reader, URef< GrMesh > mesh) | |
| GrMeshInst (URef< GrMesh > mesh, const URef< GrMaterial > *matInfo, const MMat4x4 &transform) | |
| ~GrMeshInst () | |
| GrMeshInst * | Clone (bool deep) |
| public methods | |
| void | Cache () |
| caches data for rendering. | |
| void | Evict () |
| void | SetMesh (GrMesh *mesh, const URef< GrMaterial > *matInfo) |
| assignment for the mesh instance data. | |
| void | SetMaterial (unsigned int range, URef< GrMaterial > material) |
| void | SetTransform (const MMat4x4 &transform) |
| unsigned int | GetRangeCount () const |
| accessors | |
| GrMesh * | GetMesh () const |
| GrMaterial * | GetMaterial (unsigned int range) const |
| const MMat4x4 & | GetTransform () const |
| const MMat4x4 & | GetInvTransform () const |
| const MMat3x3 & | GetInvTransposeRot () const |
| const MSphere & | GetBoundingSphere () const |
| spatial information. | |
| const MOBox & | GetOBox () const |
| const MSphere & | GetRangeBoundingSphere (unsigned int range) const |
| const MOBox & | GetRangeOBox (unsigned int range) const |
| void | GetRangePlane (MPlane &plane, MVec3 &pointOnPlane, unsigned int range) const |
| GrSkinInst * | GetSkinInst () const |
| skinning instance data. | |
| void | Save (UWriter &writer) const |
| internal use only. | |
| void | Load (UReader &reader, const UFastArray< URef< GrMesh > > &meshArray) |
| void | Update (unsigned int frameTime) |
| updates deformers and skin (if there are any). | |
| bool | Pick (float &dist, const MRay &ray) const |
| picks against the mesh. | |
| bool | Pick (GrMesh::STriCollision &triHit, const MRay &ray) const |
| void | RenderRange (unsigned int range, unsigned int vertexComponents, unsigned int frameTime) |
| render. | |
| unsigned int | BatchRange (GrStreamingIB &streamingIB, unsigned int range, unsigned int frameTime) |
| note that this is only usable if the transform is identity. |
Definition at line 33 of file GrMeshInst.h.
| GrMeshInst::GrMeshInst | ( | UReader & | reader, | |
| const UFastArray< URef< GrMesh > > & | meshArray | |||
| ) |
matInfo is an array of materials... one is required for each range in the mesh.
class header.
File: GrMeshInst.h Author: Kevin Bray Created: 10-04-04 Copyright © 2004 Bootstrap Studios. All rights reserved. project includes. class GrMeshInst ctor & dtor
Definition at line 43 of file GrMeshInst.cpp.
| GrMeshInst::GrMeshInst | ( | URef< GrMesh > | mesh, | |
| const URef< GrMaterial > * | matInfo, | |||
| const MMat4x4 & | transform | |||
| ) |
make sure everything passed in is okay.
copy the material pointers.
allocate space for bounding volumes.
deformer results.
allocate room for any reflection textures.
get the scale.
make a uniform scale for the bounding volume.
Definition at line 68 of file GrMeshInst.cpp.
| GrMeshInst::~GrMeshInst | ( | ) |
Definition at line 112 of file GrMeshInst.cpp.
| unsigned int GrMeshInst::BatchRange | ( | GrStreamingIB & | streamingIB, | |
| unsigned int | range, | |||
| unsigned int | frameTime | |||
| ) |
note that this is only usable if the transform is identity.
updates each range if needed.
make sure we've been updated.
copy the indices.
return the number of indices in the range we just batched.
Definition at line 522 of file GrMeshInst.cpp.
| void GrMeshInst::Cache | ( | ) |
| GrMeshInst * GrMeshInst::Clone | ( | bool | deep | ) |
public methods
clones a mesh instance. If deep is true, then the mesh and materials are also cloned. Generally, this should be false.
create a new mesh instance.
we need to clone a mesh if it has skinning data associated with it.
return the new mesh instance.
Definition at line 137 of file GrMeshInst.cpp.
| void GrMeshInst::Evict | ( | ) |
Definition at line 166 of file GrMeshInst.cpp.
| const MSphere & GrMeshInst::GetBoundingSphere | ( | ) | const |
| const MMat4x4& GrMeshInst::GetInvTransform | ( | ) | const [inline] |
Definition at line 60 of file GrMeshInst.h.
| const MMat3x3& GrMeshInst::GetInvTransposeRot | ( | ) | const [inline] |
Definition at line 61 of file GrMeshInst.h.
| GrMaterial * GrMeshInst::GetMaterial | ( | unsigned int | range | ) | const |
Definition at line 237 of file GrMeshInst.cpp.
| GrMesh* GrMeshInst::GetMesh | ( | ) | const [inline] |
Definition at line 57 of file GrMeshInst.h.
| const MOBox& GrMeshInst::GetOBox | ( | ) | const [inline] |
Definition at line 65 of file GrMeshInst.h.
| const MSphere & GrMeshInst::GetRangeBoundingSphere | ( | unsigned int | range | ) | const |
| unsigned int GrMeshInst::GetRangeCount | ( | ) | const [inline] |
| const MOBox & GrMeshInst::GetRangeOBox | ( | unsigned int | range | ) | const |
Definition at line 262 of file GrMeshInst.cpp.
get the plane on the mesh.
build a plane and transform it in to world space.
transform the point on the plane into world space.
Definition at line 270 of file GrMeshInst.cpp.
| GrSkinInst* GrMeshInst::GetSkinInst | ( | ) | const [inline] |
| const MMat4x4& GrMeshInst::GetTransform | ( | ) | const [inline] |
Definition at line 59 of file GrMeshInst.h.
| void GrMeshInst::Load | ( | UReader & | reader, | |
| const UFastArray< URef< GrMesh > > & | meshArray | |||
| ) |
clean up.
read the name of the mesh we're bound to. Find the mesh in the mesh list.
the mesh we're linked to wasn't found!
read the range count.
read material data.
read in the current material.
allocate space for bounds.
allocate space for reflections.
read transforms.
initialize the OBB.
Definition at line 342 of file GrMeshInst.cpp.
| bool GrMeshInst::Pick | ( | GrMesh::STriCollision & | triHit, | |
| const MRay & | ray | |||
| ) | const |
if we don't intersect with our obox, then we know we don't intersect with the mesh.
transform the ray into local space.
now perform the pick operation.
simply return if there were no hits.
go through the tri hits and take the closest one to the ray's origin.
calculate the distance between ray hits
take the minimum and store the tri-hit info.
move the hit location into world space.
return true to indicate success.
Definition at line 453 of file GrMeshInst.cpp.
| bool GrMeshInst::Pick | ( | float & | dist, | |
| const MRay & | ray | |||
| ) | const |
picks against the mesh.
try to intersect with the mesh.
calculate the distance and return.
return true to indicate a hit was made.
Definition at line 437 of file GrMeshInst.cpp.
| void GrMeshInst::RenderRange | ( | unsigned int | range, | |
| unsigned int | vertexComponents, | |||
| unsigned int | frameTime | |||
| ) |
render.
updates each range if needed.
make sure we've been updated.
render the mesh.
draw the deformed mesh if one exists.
no deformer, so draw the original mesh.
Definition at line 497 of file GrMeshInst.cpp.
| void GrMeshInst::Save | ( | UWriter & | writer | ) | const |
internal use only.
saving and loading.
save the name of the mesh we're bound to.
save the range count.
save material data.
write the current material.
save transforms.
Definition at line 318 of file GrMeshInst.cpp.
| void GrMeshInst::SetMaterial | ( | unsigned int | range, | |
| URef< GrMaterial > | material | |||
| ) |
Definition at line 209 of file GrMeshInst.cpp.
| void GrMeshInst::SetMesh | ( | GrMesh * | mesh, | |
| const URef< GrMaterial > * | matInfo | |||
| ) |
assignment for the mesh instance data.
testme.
create skin instance data if the mesh is skinned.
copy the material info and assign the new mesh.
allocate room for reflections.
update the bounding volumes.
Definition at line 178 of file GrMeshInst.cpp.
| void GrMeshInst::SetTransform | ( | const MMat4x4 & | transform | ) |
| void GrMeshInst::Update | ( | unsigned int | frameTime | ) |
updates deformers and skin (if there are any).
check to see if we need to perform an update.
update skin and bounds if necessary.
update ranges if necessary.
Definition at line 404 of file GrMeshInst.cpp.


The control/x/while.h
header defines an exponential looping construct which can be parametrically resumed.
#include <chaos/preprocessor/control/x/while.h>
The CHAOS_PP_WHILE_X
macro iterates a state with a user-specified operation while a user-specified predicate expands to 1
.
CHAOS_PP_EXPR
(CHAOS_PP_WHILE_X
(size, pred, op, ...))
The size of the buffer of valid recursion steps maintained by the algorithm.
The predicate that determines whether the loop should continue. This predicate must be either a λ expression or a macro name that refers to a macro with a signature compatible with the following pseudo-signature:
pred(s, state†)
†
The state pseudo-parameter must be either ...
or the number of parameters that corresponds to the number of arguments in the initial state, __VA_ARGS__
.
The operation used to iterate the state. This operation must be either a λ expression or a macro name that refers to a macro with a signature compatible with the following pseudo-signature:
op(s, state†)
†
The state pseudo-parameter must be either ...
or the number of parameters that corresponds to the number of arguments in the initial state, __VA_ARGS__
.
The initial state of the loop.
CHAOS_PP_EXPR
(CHAOS_PP_WHILE_X
(size, pred, op, state))
The size of the buffer of valid recursion steps maintained by the algorithm.
The predicate that determines whether the loop should continue. This predicate must be a macro name that refers to a macro with a signature compatible with the following pseudo-signature:
pred(s, state)
The operation used to iterate the state. This operation must be either a macro name that refers to a macro with a signature compatible with the following pseudo-signature:
op(s, state)
The initial state of the loop.
This macro behaves identically to CHAOS_PP_WHILE
except that the algorithm makes exponential use of the recursion backend and the algorithm itself yields a trampolined deferred expression whenever the number of recursion steps is exhausted.
This allows for parametric resumption.
This algorithm maintains a buffer of size recursion steps available at all times. This guarantees that the predicate and operation have at least size recursion steps available whenever they are invoked.
This macro deduces the current recursion state and invokes CHAOS_PP_WHILE_X_S
.
If the current recursion state is already known, direct use of CHAOS_PP_WHILE_X_S
is more efficient.
This macro may not be used if bypass semantics are in effect.
The CHAOS_PP_WHILE_X_ID
macro indirectly expands to CHAOS_PP_WHILE_X
.
CHAOS_PP_WHILE_X_ID
()
This macro effectively allows CHAOS_PP_WHILE_X
to pass through itself without becoming disabled.
The CHAOS_PP_WHILE_X_
macro expands to a λ expression representing CHAOS_PP_WHILE_X
.
CHAOS_PP_WHILE_X_
This macro is a shorthand form of the following λ binding:
The CHAOS_PP_WHILE_X_S
macro behaves identically to CHAOS_PP_WHILE_X
except that it is parametized by the recursion state.
CHAOS_PP_EXPR_S
(s)(CHAOS_PP_WHILE_X_S
(s, size, pred, op, ...))
The current recursion state.
The size of the buffer of valid recursion steps maintained by the algorithm.
The predicate that determines whether the loop should continue. This predicate must be either a λ expression or a macro name that refers to a macro with a signature compatible with the following pseudo-signature:
pred(s, state†)
†
The state pseudo-parameter must be either ...
or the number of parameters that corresponds to the number of arguments in the initial state, __VA_ARGS__
.
The operation used to iterate the state. This operation must be either a λ expression or a macro name that refers to a macro with a signature compatible with the following pseudo-signature:
op(s, state†)
†
The state pseudo-parameter must be either ...
or the number of parameters that corresponds to the number of arguments in the initial state, __VA_ARGS__
.
The initial state of the loop.
CHAOS_PP_EXPR_S
(s)(CHAOS_PP_WHILE_X_S
(s, size, pred, op, state))
The current recursion state.
The size of the buffer of valid recursion steps maintained by the algorithm.
The predicate that determines whether the loop should continue. This predicate must be a macro name that refers to a macro with a signature compatible with the following pseudo-signature:
pred(s, state)
The operation used to iterate the state. This operation must be either a macro name that refers to a macro with a signature compatible with the following pseudo-signature:
op(s, state)
The initial state of the loop.
This macro may not be used if bypass semantics are in effect.
The CHAOS_PP_WHILE_X_S_ID
macro indirectly expands to CHAOS_PP_WHILE_X_S
.
CHAOS_PP_WHILE_X_S_ID
()
This macro effectively allows CHAOS_PP_WHILE_X_S
to pass through itself without becoming disabled.
The CHAOS_PP_WHILE_X_S_
macro expands to a λ expression representing CHAOS_PP_WHILE_X_S
.
CHAOS_PP_WHILE_X_S_
This macro is a shorthand form of the following λ binding:


They would never do anything like that 🤔🤔🤔😱😱😱😂😂😂 ✌⚔🇺🇸
Show Replies
Hide Replies
Name Hidden·@Private User5 days ago
Ron Rafensberger, brother of Brad Rafensberger speaks Mandarin and works for Huawei. Brad also thanked the CCP for helping him to get elected GA SOS in Mandarin. Can’t make this stuff up...YouTube it
The whole idea that democrats overwhelmingly vote early is a lie to cover up for the massive number of fake ballots.
Should be a massive red wave, anything less is an attempted steal or steal
Are we behind again?
let me guess, Dekalb has decided to drop their votes.
Do you not shut down those machines
What does VEX mean ? Lol
Why the hell is DeKalb County coming in so slow... 👀
They are waiting in that county. Thats where they will cheat the numbers💯🤬🤬
Corruption at it height.
The voter fraud county
Is there a Toilet leaking?
That’s where the cheating will happen.
What numbers are you watching @mitchellvii
Politico is showing 80% with both reds in the lead!
Sorry, not looking good anymore. Maybe Perdue pulls it out, Loeffler is gone. Just my
Opinion based on data.
Never mind bill, never mind. Jesus
Cesspool of a place
Waiting to see how many votes they need.😡
You kind of remind me of Romney but I do appreciate you keeping us up to date very American of you thank you sir
They would never do anything like that 🤔🤔🤔😱😱😱😂😂😂 ✌⚔🇺🇸
Dumbass GOP... thought it was a good idea to cheat Trump! Now look at ya... gotta go learn mandarin just to survive!


Note
Click here to download the full example code
Neural Transfer Using PyTorch¶
Author: Alexis Jacq
Edited by: Winston Herring
Introduction¶
This tutorial explains how to implement the Neural-Style algorithm developed by Leon A. Gatys, Alexander S. Ecker and Matthias Bethge. Neural-Style, or Neural-Transfer, allows you to take an image and reproduce it with a new artistic style. The algorithm takes three images, an input image, a content-image, and a style-image, and changes the input to resemble the content of the content-image and the artistic style of the style-image.
Underlying Principle¶
The principle is simple: we define two distances, one for the content (\(D_C\)) and one for the style (\(D_S\)). \(D_C\) measures how different the content is between two images while \(D_S\) measures how different the style is between two images. Then, we take a third image, the input, and transform it to minimize both its content-distance with the content-image and its style-distance with the style-image. Now we can import the necessary packages and begin the neural transfer.
Importing Packages and Selecting a Device¶
Below is a list of the packages needed to implement the neural transfer.
torch
,torch.nn
,numpy
(indispensables packages for neural networks with PyTorch)torch.optim
(efficient gradient descents)PIL
,PIL.Image
,matplotlib.pyplot
(load and display images)torchvision.transforms
(transform PIL images into tensors)torchvision.models
(train or load pre-trained models)copy
(to deep copy the models; system package)
from __future__ import print_function
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from PIL import Image
import matplotlib.pyplot as plt
import torchvision.transforms as transforms
import torchvision.models as models
import copy
Next, we need to choose which device to run the network on and import the
content and style images. Running the neural transfer algorithm on large
images takes longer and will go much faster when running on a GPU. We can
use torch.cuda.is_available()
to detect if there is a GPU available.
Next, we set the torch.device
for use throughout the tutorial. Also the .to(device)
method is used to move tensors or modules to a desired device.
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
Loading the Images¶
Now we will import the style and content images. The original PIL images have values between 0 and 255, but when transformed into torch tensors, their values are converted to be between 0 and 1. The images also need to be resized to have the same dimensions. An important detail to note is that neural networks from the torch library are trained with tensor values ranging from 0 to 1. If you try to feed the networks with 0 to 255 tensor images, then the activated feature maps will be unable to sense the intended content and style. However, pre-trained networks from the Caffe library are trained with 0 to 255 tensor images.
Note
Here are links to download the images required to run the tutorial:
picasso.jpg and
dancing.jpg.
Download these two images and add them to a directory
with name images
in your current working directory.
# desired size of the output image
imsize = 512 if torch.cuda.is_available() else 128 # use small size if no gpu
loader = transforms.Compose([
transforms.Resize(imsize), # scale imported image
transforms.ToTensor()]) # transform it into a torch tensor
def image_loader(image_name):
image = Image.open(image_name)
# fake batch dimension required to fit network's input dimensions
image = loader(image).unsqueeze(0)
return image.to(device, torch.float)
style_img = image_loader("./data/images/neural-style/picasso.jpg")
content_img = image_loader("./data/images/neural-style/dancing.jpg")
assert style_img.size() == content_img.size(), \
"we need to import style and content images of the same size"
Now, let’s create a function that displays an image by reconverting a
copy of it to PIL format and displaying the copy using
plt.imshow
. We will try displaying the content and style images
to ensure they were imported correctly.
unloader = transforms.ToPILImage() # reconvert into PIL image
plt.ion()
def imshow(tensor, title=None):
image = tensor.cpu().clone() # we clone the tensor to not do changes on it
image = image.squeeze(0) # remove the fake batch dimension
image = unloader(image)
plt.imshow(image)
if title is not None:
plt.title(title)
plt.pause(0.001) # pause a bit so that plots are updated
plt.figure()
imshow(style_img, title='Style Image')
plt.figure()
imshow(content_img, title='Content Image')
Loss Functions¶
Content Loss¶
The content loss is a function that represents a weighted version of the
content distance for an individual layer. The function takes the feature
maps \(F_{XL}\) of a layer \(L\) in a network processing input \(X\) and returns the
weighted content distance \(w_{CL}.D_C^L(X,C)\) between the image \(X\) and the
content image \(C\). The feature maps of the content image(\(F_{CL}\)) must be
known by the function in order to calculate the content distance. We
implement this function as a torch module with a constructor that takes
\(F_{CL}\) as an input. The distance \(\|F_{XL} - F_{CL}\|^2\) is the mean square error
between the two sets of feature maps, and can be computed using nn.MSELoss
.
We will add this content loss module directly after the convolution
layer(s) that are being used to compute the content distance. This way
each time the network is fed an input image the content losses will be
computed at the desired layers and because of auto grad, all the
gradients will be computed. Now, in order to make the content loss layer
transparent we must define a forward
method that computes the content
loss and then returns the layer’s input. The computed loss is saved as a
parameter of the module.
class ContentLoss(nn.Module):
def __init__(self, target,):
super(ContentLoss, self).__init__()
# we 'detach' the target content from the tree used
# to dynamically compute the gradient: this is a stated value,
# not a variable. Otherwise the forward method of the criterion
# will throw an error.
self.target = target.detach()
def forward(self, input):
self.loss = F.mse_loss(input, self.target)
return input
Note
Important detail: although this module is named ContentLoss
, it
is not a true PyTorch Loss function. If you want to define your content
loss as a PyTorch Loss function, you have to create a PyTorch autograd function
to recompute/implement the gradient manually in the backward
method.
Style Loss¶
The style loss module is implemented similarly to the content loss module. It will act as a transparent layer in a network that computes the style loss of that layer. In order to calculate the style loss, we need to compute the gram matrix \(G_{XL}\). A gram matrix is the result of multiplying a given matrix by its transposed matrix. In this application the given matrix is a reshaped version of the feature maps \(F_{XL}\) of a layer \(L\). \(F_{XL}\) is reshaped to form \(\hat{F}_{XL}\), a \(K\)x\(N\) matrix, where \(K\) is the number of feature maps at layer \(L\) and \(N\) is the length of any vectorized feature map \(F_{XL}^k\). For example, the first line of \(\hat{F}_{XL}\) corresponds to the first vectorized feature map \(F_{XL}^1\).
Finally, the gram matrix must be normalized by dividing each element by the total number of elements in the matrix. This normalization is to counteract the fact that \(\hat{F}_{XL}\) matrices with a large \(N\) dimension yield larger values in the Gram matrix. These larger values will cause the first layers (before pooling layers) to have a larger impact during the gradient descent. Style features tend to be in the deeper layers of the network so this normalization step is crucial.
def gram_matrix(input):
a, b, c, d = input.size() # a=batch size(=1)
# b=number of feature maps
# (c,d)=dimensions of a f. map (N=c*d)
features = input.view(a * b, c * d) # resise F_XL into \hat F_XL
G = torch.mm(features, features.t()) # compute the gram product
# we 'normalize' the values of the gram matrix
# by dividing by the number of element in each feature maps.
return G.div(a * b * c * d)
Now the style loss module looks almost exactly like the content loss module. The style distance is also computed using the mean square error between \(G_{XL}\) and \(G_{SL}\).
class StyleLoss(nn.Module):
def __init__(self, target_feature):
super(StyleLoss, self).__init__()
self.target = gram_matrix(target_feature).detach()
def forward(self, input):
G = gram_matrix(input)
self.loss = F.mse_loss(G, self.target)
return input
Importing the Model¶
Now we need to import a pre-trained neural network. We will use a 19 layer VGG network like the one used in the paper.
PyTorch’s implementation of VGG is a module divided into two child
Sequential
modules: features
(containing convolution and pooling layers),
and classifier
(containing fully connected layers). We will use the
features
module because we need the output of the individual
convolution layers to measure content and style loss. Some layers have
different behavior during training than evaluation, so we must set the
network to evaluation mode using .eval()
.
cnn = models.vgg19(pretrained=True).features.to(device).eval()
Additionally, VGG networks are trained on images with each channel normalized by mean=[0.485, 0.456, 0.406] and std=[0.229, 0.224, 0.225]. We will use them to normalize the image before sending it into the network.
cnn_normalization_mean = torch.tensor([0.485, 0.456, 0.406]).to(device)
cnn_normalization_std = torch.tensor([0.229, 0.224, 0.225]).to(device)
# create a module to normalize input image so we can easily put it in a
# nn.Sequential
class Normalization(nn.Module):
def __init__(self, mean, std):
super(Normalization, self).__init__()
# .view the mean and std to make them [C x 1 x 1] so that they can
# directly work with image Tensor of shape [B x C x H x W].
# B is batch size. C is number of channels. H is height and W is width.
self.mean = torch.tensor(mean).view(-1, 1, 1)
self.std = torch.tensor(std).view(-1, 1, 1)
def forward(self, img):
# normalize img
return (img - self.mean) / self.std
A Sequential
module contains an ordered list of child modules. For
instance, vgg19.features
contains a sequence (Conv2d, ReLU, MaxPool2d,
Conv2d, ReLU…) aligned in the right order of depth. We need to add our
content loss and style loss layers immediately after the convolution
layer they are detecting. To do this we must create a new Sequential
module that has content loss and style loss modules correctly inserted.
# desired depth layers to compute style/content losses :
content_layers_default = ['conv_4']
style_layers_default = ['conv_1', 'conv_2', 'conv_3', 'conv_4', 'conv_5']
def get_style_model_and_losses(cnn, normalization_mean, normalization_std,
style_img, content_img,
content_layers=content_layers_default,
style_layers=style_layers_default):
cnn = copy.deepcopy(cnn)
# normalization module
normalization = Normalization(normalization_mean, normalization_std).to(device)
# just in order to have an iterable access to or list of content/syle
# losses
content_losses = []
style_losses = []
# assuming that cnn is a nn.Sequential, so we make a new nn.Sequential
# to put in modules that are supposed to be activated sequentially
model = nn.Sequential(normalization)
i = 0 # increment every time we see a conv
for layer in cnn.children():
if isinstance(layer, nn.Conv2d):
i += 1
name = 'conv_{}'.format(i)
elif isinstance(layer, nn.ReLU):
name = 'relu_{}'.format(i)
# The in-place version doesn't play very nicely with the ContentLoss
# and StyleLoss we insert below. So we replace with out-of-place
# ones here.
layer = nn.ReLU(inplace=False)
elif isinstance(layer, nn.MaxPool2d):
name = 'pool_{}'.format(i)
elif isinstance(layer, nn.BatchNorm2d):
name = 'bn_{}'.format(i)
else:
raise RuntimeError('Unrecognized layer: {}'.format(layer.__class__.__name__))
model.add_module(name, layer)
if name in content_layers:
# add content loss:
target = model(content_img).detach()
content_loss = ContentLoss(target)
model.add_module("content_loss_{}".format(i), content_loss)
content_losses.append(content_loss)
if name in style_layers:
# add style loss:
target_feature = model(style_img).detach()
style_loss = StyleLoss(target_feature)
model.add_module("style_loss_{}".format(i), style_loss)
style_losses.append(style_loss)
# now we trim off the layers after the last content and style losses
for i in range(len(model) - 1, -1, -1):
if isinstance(model[i], ContentLoss) or isinstance(model[i], StyleLoss):
break
model = model[:(i + 1)]
return model, style_losses, content_losses
Next, we select the input image. You can use a copy of the content image or white noise.
input_img = content_img.clone()
# if you want to use white noise instead uncomment the below line:
# input_img = torch.randn(content_img.data.size(), device=device)
# add the original input image to the figure:
plt.figure()
imshow(input_img, title='Input Image')
Gradient Descent¶
As Leon Gatys, the author of the algorithm, suggested here, we will use
L-BFGS algorithm to run our gradient descent. Unlike training a network,
we want to train the input image in order to minimise the content/style
losses. We will create a PyTorch L-BFGS optimizer optim.LBFGS
and pass
our image to it as the tensor to optimize.
def get_input_optimizer(input_img):
# this line to show that input is a parameter that requires a gradient
optimizer = optim.LBFGS([input_img.requires_grad_()])
return optimizer
Finally, we must define a function that performs the neural transfer. For
each iteration of the networks, it is fed an updated input and computes
new losses. We will run the backward
methods of each loss module to
dynamicaly compute their gradients. The optimizer requires a “closure”
function, which reevaluates the module and returns the loss.
We still have one final constraint to address. The network may try to optimize the input with values that exceed the 0 to 1 tensor range for the image. We can address this by correcting the input values to be between 0 to 1 each time the network is run.
def run_style_transfer(cnn, normalization_mean, normalization_std,
content_img, style_img, input_img, num_steps=300,
style_weight=1000000, content_weight=1):
"""Run the style transfer."""
print('Building the style transfer model..')
model, style_losses, content_losses = get_style_model_and_losses(cnn,
normalization_mean, normalization_std, style_img, content_img)
optimizer = get_input_optimizer(input_img)
print('Optimizing..')
run = [0]
while run[0] <= num_steps:
def closure():
# correct the values of updated input image
input_img.data.clamp_(0, 1)
optimizer.zero_grad()
model(input_img)
style_score = 0
content_score = 0
for sl in style_losses:
style_score += sl.loss
for cl in content_losses:
content_score += cl.loss
style_score *= style_weight
content_score *= content_weight
loss = style_score + content_score
loss.backward()
run[0] += 1
if run[0] % 50 == 0:
print("run {}:".format(run))
print('Style Loss : {:4f} Content Loss: {:4f}'.format(
style_score.item(), content_score.item()))
print()
return style_score + content_score
optimizer.step(closure)
# a last correction...
input_img.data.clamp_(0, 1)
return input_img
Finally, we can run the algorithm.
output = run_style_transfer(cnn, cnn_normalization_mean, cnn_normalization_std,
content_img, style_img, input_img)
plt.figure()
imshow(output, title='Output Image')
# sphinx_gallery_thumbnail_number = 4
plt.ioff()
plt.show()
Out:
Building the style transfer model..


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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 config.AppConfig @import controllers.routes @import views.forms.components.RadioOption @import views.html.forms.components.input_radiogroup @import models.LiabilityOrder @import models.request.AuthenticatedRequest @import views.html.components.confirm_or_cancel_buttons @import views.html.forms.components.input_text @import models.LiabilityStatus @import views.html.partials.error_summary @import views.html.includes.main @this(main: main) @(form: Form[CorrespondenceApplication])(implicit request: AuthenticatedRequest[_], messages: Messages, appConfig: AppConfig) @main( pageTitle = messages("page.title.create_correspondence.h1") ) { @error_summary(form.errors)


${responses.role}
${responses.name}
Id Number: ${responses.id}
Office number: ${responses.office}
${responses.email}
Another link


Radon
Element Name:
Radon
Latin Name:
Radon
Atomic Number:
86
Atomic Weight:
222.0176 u
Is a:
Noble-Gas
State of the element:
Solid
About:
Radon is a chemical element with the symbol Rn and atomic number 86. It is a radioactive, colorless, odorless, tasteless noble gas. It occurs naturally in minute quantities as an intermediate step in the normal radioactive decay chains through which thorium and uranium slowly decay into lead and various other short-lived radioactive elements; radon itself is the immediate decay product of radium. Its most stable isotope, 222Rn, has a half-life of only 3.8 days, making radon one of the rarest elements since it decays away so quickly.
Electrons
86
Protons
86
Neutrons
136
Discoverer:
Fredrich Ernst Dorn
Discovered in:
1900


CONVERT JSON TO CSV
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bloomedit
Beginning with version 1.4, Elasticsearch no longer enables bloom filters for search. This command is unnecessary if your Elasticsearch version is 1.4 or higher.
Summaryedit
From the Elasticsearch Bloom Filter Posting Format documentation
It can sometime make sense to disable bloom filters. For instance, if you are logging into an index per day, and you have thousands of indices, the bloom filters can take up a sizable amount of memory. For most queries you are only interested in recent indices, so you don’t mind CRUD operations on older indices taking slightly longer.
In these cases you can disable loading of the bloom filter on a per-index basis by updating the index settings
This setting is especially relevant to Logstash and Marvel use-cases. The
bloom
command allows you to disable the bloom filter cache for indices.
Flagsedit
$ curator bloom --help Usage: curator bloom [OPTIONS] COMMAND [ARGS]... Disable bloom filter cache Options: --delay INTEGER Pause *n* seconds after disabling bloom filter cache of an index [default: 0] --help Show this message and exit. Commands: indices Index selection.
This command requires the indices subcommand for index selection.
Exampleedit
Disable the bloom filters (for Elasticsearch versions < 1.4):
curator bloom indices <<index selection parameters>>


We sell the only ten-speed bicycles in the world made entirely of cheese. They get you where you need to go, and you never arrive hungry. Our bikes are 100% biodegradable. And with our new rodent-repelling varnish they last longer than ever!
Our newest model: the Ricotta Racer
The video could not be loaded.
Mixer making the raw material for the new Parmesan Pacer!


Preparation time
overnight
Cooking time
10 to 30 mins
Serves
Serves 2
This authentic recipe requires 48 hours advance prep but is definitely worth the effort. Pair with spicy coleslaw and cornbread for a real taste of the deep south.
For the chicken, dissolve the salt in 1 litre/1¾ pints water. Submerge the chicken in the brine and chill in the fridge for 24 hours.
Remove the chicken from the brine. In a new container, cover the chicken completely with the buttermilk. Chill in the fridge for another 24-48 hours.
For the coleslaw, put the pineapple and cider vinegar in a blender. Blend until smooth, then strain.
Combine all the remaining coleslaw ingredients. Use your hands to massage the salt into the vegetables to break them down slightly. Add the cider mixture and massage a little more. Cover and allow to marinate in the fridge for 24 hours. Taste and season with salt if necessary before serving.
When you are ready to cook, preheat the oven to 220C/200C Fan/Gas 7.
For the cornbread, mix all the dry ingredients in a large bowl. Then mix all of the wet ingredients in a separate bowl or jug. Combine the two and mix until smooth.
Melt the lard in a cast-iron skillet or ovenproof frying pan (alternatively melt the lard in a pan and use it to grease a 20cm/8in cake tin). Add the cornbread batter and bake for 15 minutes, or until a skewer inserted into the centre comes out clean. Spread with butter and honey, to taste.
For the chicken, fill a deep-fat fryer or a large, deep, heavy-bottomed pan two-thirds full with vegetable oil. Heat the oil to 165C. (CAUTION: Hot oil can be dangerous. Do not leave unattended)
Put all the ingredients for the flour dredge in a large plastic food bag and mix. Remove the chicken from the buttermilk, put it in the bag with the flour and shake to coat.
Deep-fry the chicken until golden-brown and cooked through. Place on kitchen roll to drain.
Serve the chicken and coleslaw on plates with the cornbread on the side.


The open source e-mail platform
If you're starting a new organization you can do so by completing this form. You'll be able to invite new users & create mail servers as soon as it has been created.
This is a short name which is used in usernames and the API to identify your organization. It should only contain letters, numbers & hyphens.


Class RootTargetContainerExtensions
Extensions for the IRootTargetContainer interface.
Inherited Members
Namespace: Rezolver
Assembly: Rezolver.dll
Syntax
public static class RootTargetContainerExtensions
Methods
| Improve this Doc View SourceCreateTargetContainerForServiceType(IRootTargetContainer, Type)
Calls GetContainerRegistrationType(Type) to get the correct registration type for the target container
that should own a target that will be registered against the given serviceType
. Once obtained, that type is then
passed to the CreateTargetContainer(Type) to create the correct ITargetContainer for
that container registration type.
This is typically used by 'advanced' target containers which wrap others under potentially any type and which therefore need to reuse the root container's logic for ensuring that registrations are handled correctly.
Declaration
public static ITargetContainer CreateTargetContainerForServiceType(this IRootTargetContainer rootContainer, Type serviceType)
Parameters
| Type | Name | Description |
|---|---|---|
| IRootTargetContainer | rootContainer | |
| Type | serviceType |
Returns
| Type | Description |
|---|---|
| ITargetContainer |
FetchAllCompatibleTargets(IRootTargetContainer, Type)
Fetches all targets from the rootContainer
registered against service types which are
either equal to or compatible with the given serviceType
.
Declaration
public static IEnumerable<ITarget> FetchAllCompatibleTargets(this IRootTargetContainer rootContainer, Type serviceType)
Parameters
| Type | Name | Description |
|---|---|---|
| IRootTargetContainer | rootContainer | The root target container whose targets are to be searched |
| Type | serviceType | The service type for which targets are sought. |
Returns
| Type | Description |
|---|---|
| IEnumerable<ITarget> | An enumerable of targets which match the |
Remarks
This is effectively a covariant version of the FetchAll(Type) function,
and is used by built-in functionality such as automatic enumerable injection (when EnableEnumerableCovariance
is true
) and automatic factory injection Func<TResult>.
Note: the targets are de-duped before being returned, so if one target is registered multiple times against different compatible service types, it will still only appear once in the output enumerable.
RegisterProjection(IRootTargetContainer, Type, Type)
Non-generic version of RegisterProjection<TFrom, TTo>(IRootTargetContainer)
Declaration
public static void RegisterProjection(this IRootTargetContainer targets, Type fromType, Type toType)
Parameters
| Type | Name | Description |
|---|---|---|
| IRootTargetContainer | targets | |
| Type | fromType | The type of the enumerable that provides the source of the projection |
| Type | toType | The type of the enumerable that will be the output of the projection - this type must be able to be created via automatic constructor injection. |
RegisterProjection(IRootTargetContainer, Type, Type, Func<IRootTargetContainer, ITarget, ITarget>)
Non-generic version of RegisterProjection<TFrom, TTo>(IRootTargetContainer, Func<IRootTargetContainer, ITarget, ITarget>)
Declaration
public static void RegisterProjection(this IRootTargetContainer targets, Type fromType, Type toType, Func<IRootTargetContainer, ITarget, ITarget> implementationTargetFactory)
Parameters
| Type | Name | Description |
|---|---|---|
| IRootTargetContainer | targets | |
| Type | fromType | The type of the enumerable that provides the source of the projection |
| Type | toType | The type of the enumerable that will be the output of the projection |
| Func<IRootTargetContainer, ITarget, ITarget> | implementationTargetFactory | A factory callback that will be called once for each target in the input enumerable - the target returned by the factory will then be used to produce the projected element in the output enumerable. |
RegisterProjection(IRootTargetContainer, Type, Type, Func<IRootTargetContainer, ITarget, Type>)
Non-generic version of RegisterProjection<TFrom, TTo>(IRootTargetContainer, Func<IRootTargetContainer, ITarget, Type>)
Declaration
public static void RegisterProjection(this IRootTargetContainer targets, Type fromType, Type toType, Func<IRootTargetContainer, ITarget, Type> implementationTypeSelector)
Parameters
| Type | Name | Description |
|---|---|---|
| IRootTargetContainer | targets | |
| Type | fromType | The type of the enumerable that provides the source of the projection. |
| Type | toType | The type of the enumerable produced by the projection. |
| Func<IRootTargetContainer, ITarget, Type> | implementationTypeSelector | A callback to be invoked for each target in the input enumerable which provides the type that is to be created for the corresponding element in the output enumerable. |
RegisterProjection(IRootTargetContainer, Type, Type, Type)
Non-generic version of RegisterProjection<TFrom, TTo, TImplementation>(IRootTargetContainer)
Declaration
public static void RegisterProjection(this IRootTargetContainer targets, Type fromType, Type toType, Type implementationType)
Parameters
| Type | Name | Description |
|---|---|---|
| IRootTargetContainer | targets | |
| Type | fromType | The type of the enumerable that provides the source of the projection. |
| Type | toType | The type of the enumerable produced by the projection. |
| Type | implementationType | The type to be created for each element in the output enumerable. Must be able to be created via automatic constructor injection. |
RegisterProjection<TFrom, TTo>(IRootTargetContainer)
Registers an enumerable projection that will create an enumerable of type TTo
from elements of an input enumerable of type TFrom
using constructor injection
to create each instance of TTo
.
The same as calling RegisterProjection(IRootTargetContainer, Type, Type, Type) with
TTo
used as the argument to both TTo
and TImplementation
type parameters.
Declaration
public static void RegisterProjection<TFrom, TTo>(this IRootTargetContainer targets)
Parameters
| Type | Name | Description |
|---|---|---|
| IRootTargetContainer | targets |
Type Parameters
| Name | Description |
|---|---|
| TFrom | The type of the enumerable that provides the source of the projection |
| TTo | The type of the enumerable that will be the output of the projection |
RegisterProjection<TFrom, TTo>(IRootTargetContainer, Func<IRootTargetContainer, ITarget, ITarget>)
Registers an enumerable projection that will create an enumerable of type TTo
from elements of an input enumerable of type TFrom
using targets produced by the
implementationTargetFactory
for each input element.
Declaration
public static void RegisterProjection<TFrom, TTo>(this IRootTargetContainer targets, Func<IRootTargetContainer, ITarget, ITarget> implementationTargetFactory)
Parameters
| Type | Name | Description |
|---|---|---|
| IRootTargetContainer | targets | |
| Func<IRootTargetContainer, ITarget, ITarget> | implementationTargetFactory | A factory callback that will be called once for each target in the input enumerable - the target returned by the factory will then be used to produce the projected element in the output enumerable. |
Type Parameters
| Name | Description |
|---|---|
| TFrom | The type of the enumerable that provides the source of the projection |
| TTo | The type of the enumerable that will be the output of the projection |
Remarks
This overload is useful when output elements require more complex injection strategies other than just constructor injection; or perhaps where more advanced constructor injection is required (e.g. perhaps with member injection).
RegisterProjection<TFrom, TTo>(IRootTargetContainer, Func<IRootTargetContainer, ITarget, Type>)
Registers an enumerable projection that create an enumerable of type TTo
from elements of an input enumerable of type TFrom
with the type of each
projected element is determined by the result of the implementationTypeSelector
callback for each input target. The type returned by this callback must be able to be created via
automatic constructor injection.
Declaration
public static void RegisterProjection<TFrom, TTo>(this IRootTargetContainer targets, Func<IRootTargetContainer, ITarget, Type> implementationTypeSelector)
Parameters
| Type | Name | Description |
|---|---|---|
| IRootTargetContainer | targets | |
| Func<IRootTargetContainer, ITarget, Type> | implementationTypeSelector | A callback to be invoked for each target in the input enumerable which provides the type that is to be created for the corresponding element in the output enumerable. |
Type Parameters
| Name | Description |
|---|---|
| TFrom | The type of the enumerable that provides the source of the projection |
| TTo | The type of the enumerable that will be the output of the projection |
Remarks
This overload is useful for creating specialised generics which share the TTo
type
as a base or interface.
RegisterProjection<TFrom, TTo, TImplementation>(IRootTargetContainer)
Registers an enumerable projection that will create an enumerable of type TTo
from elements of an input enumerable of type TFrom
using constructor injection
to create each instance of TImplementation
.
Declaration
public static void RegisterProjection<TFrom, TTo, TImplementation>(this IRootTargetContainer targets)
where TImplementation : TTo
Parameters
| Type | Name | Description |
|---|---|---|
| IRootTargetContainer | targets |
Type Parameters
| Name | Description |
|---|---|
| TFrom | The type of the enumerable that provides the source of the projection |
| TTo | The type of the enumerable that will be the output of the projection |
| TImplementation | The type to be created for each element. |
Remarks
This is like hot-wiring the Linq Select<TSource,TResult>(IEnumerable<TSource>, Func<TSource,TResult>) directly into the container.
Typically each instance of the implementation type TImplementation
will require an
instance of type TFrom
to be passed into its constructor - the framework
takes care of passing the individual elements in for each instance of TImplementation
that it creates.


{{ data.paragraphOne }}
{{ data.paragraphTwo }}
this picture shows the minecraft blocks.
but there are still more blocks to show.
this is a villager.
you can trade with it,but when it dies by a zombie it turns to a zombie.
Insert some of your own paragraph text here.
Insert some of your own paragraph text here.
Insert some of your own paragraph text here.
Insert some of your own paragraph text here.
Insert some of your own paragraph text here.
Insert some of your own paragraph text here.
{{ data.paragraphOne }}
{{ data.paragraphTwo }}
{{ data.paragraphThree }}
{{ data.paragraphFour }}
your couch it is mine
Im a cool paragraph that lives inside of an even cooler modal. Wins
×Your couch. It is mine.
Im a cool paragraph that lives inside of an even cooler modal. Wins
×


{% extends "base.html" %} {% block body %}
I thought you might be interested in this {{ rec.content_type }} on "{{ topic }}" I found...
Published By - {{ rec.author }}
By - {{ rec.author }}
{{ rec.description }}
{{ response }}


Problem loading branch. You may not have
permission to see it, or it may not exist.
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to the branch.
[ Abandon Changes ]
✎✂{{getQuipTime(quip)}}
{{tag.name}}
{{quip.text}}
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The browser is preventing the speech recognition from running.
You may have blocked it from listening to the microphone, or
maybe you need to plug in and turn on your microphone?
You seem to have explicitly denied the page from listening to
the microphone. Check your browser settings to re-enable it.
Speak the quip for {{quipTime}}
[ Stop voice entry ]


@* * 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 config.ConfigDecorator @import controllers.auth.requests.UserRequest @import scala.concurrent.ExecutionContext @import components.{H1, P, Link, Button} @this( main: MainView, h1: H1, p: P, link: Link, button: Button, govukInsetText: GovukInsetText, govukDetails: GovukDetails ) @(year: String, saUtr: SaUtr)(implicit request: UserRequest[_], configDecorator: ConfigDecorator, messages: play.api.i18n.Messages) @insetContent = { @p(Text(messages("label.to_get_your_sa302_calculation")))


The definition of a UART function table that contains the required set of functions to control a specific UART driver implementation. More...
#include <UART.h>
The definition of a UART function table that contains the required set of functions to control a specific UART driver implementation.
| UART_CloseFxn UART_FxnTable_s::closeFxn |
Function to close the specified peripheral
| UART_ControlFxn UART_FxnTable_s::controlFxn |
Function to implementation specific control function
| UART_OpenFxn UART_FxnTable_s::openFxn |
Function to open the specified peripheral
| UART_ReadCancelFxn UART_FxnTable_s::readCancelFxn |
Function to cancel a read from the specified peripheral
| UART_ReadFxn UART_FxnTable_s::readFxn |
Function to read from the specified peripheral
| UART_ReadFxn2 UART_FxnTable_s::readFxn2 |
Function to read from the specified peripheral
| UART_ReadPollingFxn UART_FxnTable_s::readPollingFxn |
Function to read via polling from the specified peripheral
| UART_InitFxn UART_FxnTable_s::uartInitFxn |
Function to initialize the given data object
| UART_WriteCancelFxn UART_FxnTable_s::writeCancelFxn |
Function to cancel a write from the specified peripheral
| UART_WriteFxn UART_FxnTable_s::writeFxn |
Function to write from the specified peripheral
| UART_WriteFxn2 UART_FxnTable_s::writeFxn2 |
Function to write from the specified peripheral
| UART_WritePollingFxn UART_FxnTable_s::writePollingFxn |
Function to write via polling from the specified peripheral


Kanye West’s Religious-Themed Merch is So Ugly People Joke it Turns Them to Atheism
Kanye West has recently declared himself “unquestionably, undoubtedly, the greatest human artist of all time”, but he’s never said anything about his graphic design skills. Some people believe that his newest ‘Jesus is King’ merch is actual blasphemy.
Music fans are still wrapping their minds around Kanye West’s newly-released gospel-themed album, but the similarly devout merchandise has people either up in arms or down in stitches.
On Wednesday, Kanye dropped a set of t-shirts, shorts, crewneck sweaters, sweatpants, hats, and socks. Piety is a recurring motif in all of the pieces, which will run you from $60 to $260.
What’s drawn increased attention to the merch – apart from the usual lamentation about the prices – was the somewhat sloppy graphic design.
 The whole line was apparently designed by AWGE, A$AP Rocky’s creative agency.
The ‘Jesus is King’ merch has come in for a lot of stick online. “This made me even more atheist,” one user wrote.
Another said the clothes looked like “satire merch.”
A number of people jokingly suggested the whole line was made in Microsoft Word.
The wave of criticism then entered the meme territory – and became unstoppable.


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Descriptive Inorganic Chemistry 6e
作者：
Geoff Rayner-Canham
&
Tina Overton
分类：
化学 - 无机化学
出版商：W. H. Freeman & Company
语言：英语
百度盘下载
提取码是：xhjy
书籍目录
The Electronic Structure of the Atom: A Review
The Structure of the Periodic Table
Covalent Bonding and Molecular Spectroscopy
Metallic Bonding and Alloys
Ionic Bonding and Solid State Structures
Why Compounds Exist—Inorganic Thermodynamics
Solvent Systems and Acid-Base Behavior
Oxidation and Reduction
Periodic Patterns
Hydrogen
The Group 1 Elements: The Alkali Metals
The Group 2 Elements: The Alkaline Earth Metals
The Group 13 Elements
The Group 14 Elements
The Group 15 Elements: The Pnictogens
The Group 16 Elements: The Chalcogens
The Group 17 Elements: The Halogens
The Group 18 Elements: The Noble Gases
Transition Metal Complexes
The 3d Transition Metals
The 4d and 5d Transition Metals
The Group 12 Elements
Organometallic Chemistry
The Rare Earth, Actinoid, and Postactinoid Elements
书籍简介
本书pdf是
文字版
，
彩图版
，书签良好。
The Electronic Structure of the Atom: A Review
The Structure of the Periodic Table
Covalent Bonding and Molecular Spectroscopy
Metallic Bonding and Alloys
Ionic Bonding and Solid State Structures
Why Compounds Exist—Inorganic Thermodynamics
Solvent Systems and Acid-Base Behavior
Oxidation and Reduction
Periodic Patterns
Hydrogen
The Group 1 Elements: The Alkali Metals
The Group 2 Elements: The Alkaline Earth Metals
The Group 13 Elements
The Group 14 Elements
The Group 15 Elements: The Pnictogens
The Group 16 Elements: The Chalcogens
The Group 17 Elements: The Halogens
The Group 18 Elements: The Noble Gases
Transition Metal Complexes
The 3d Transition Metals
The 4d and 5d Transition Metals
The Group 12 Elements
Organometallic Chemistry
The Rare Earth, Actinoid, and Postactinoid Elements


As the sea level rose, every street became a canal. Every skyscraper an island. For the residents of one apartment building in Madison Square, however, New York in the year 2140 is far from a drowned city.
There is the market trader, who finds opportunities where others find trouble. There is the detective, whose work will never disappear - along with the lawyer's, of course.
There is the internet star, beloved by millions for her airship adventures, and the building's manager, quietly respected for his attention to detail. Then there are two boys who don't live there, but have no other home - and who are motr important to its future than anyone might imagine.
Lastly there are the coders, temporary residents on the roof, whose disappearance triggers a sequence of events that threatens the ecistence of all - and even the long-hidden foundations on which the city rests.
"Whoever writes the code creates the value."


The Expanding Text Area is a TextArea that shrinks and grows automatically based on the text within the area. It uses the technique discussed in Expanding Text Areas Made Elegant.
ExpandingTextArea.java


Masters thesis submitted in 2017.
Developed a set of Houdini Digital Assets to provide the user with additional control when performing melting simulations. The user is able to specify multiple heat zones that impact the temperature and viscosity for those regions. This results in an art-directed approach to performing melting simulations.
Tools used: Houdini, VEX


9
1 Wisdom has built her own house;
she has carved seven pillars out of rocks.
2 She has prepared her animals to serve for dinner; she has mixed her wine;
and she has set her table.
3 She has sent out invitations with her maids and she calls out
from the highest point of the city:
4 "Let those who are untaught come in here!"
she says to those who have no sense.
5 "Come, eat my food,
and drink the wine I have mixed.
6 Leave your untaught ways behind, and live;
walk in the way of understanding.
7 Whoever corrects a mocker invites abuse,
and whoever reproves a wicked person will be hurt.
8 Do not reprove a mocker, or he will hate you;
reprove a wise man, and he will love you.
9 Give instructions to a wise man, and he will become wiser still;
teach a righteous man, and he will increase in learning.
10 The fear of Yahweh is the beginning of wisdom,
and the knowledge of the Holy One is understanding.
11 For through me your days will be multiplied,
and years added to your life.
12 If you are wise, you are wise for yourself,
but if you mock, you will carry it alone."
13 A foolish woman is noisy—
she is untaught and she knows nothing.
14 She sits at the door of her house,
on a seat in the highest places of the town.
15 She is calling out to those who pass by,
to people walking straight on their way.
16 "Let those who are untaught come in here!"
she says to those who have no sense.
17 "Stolen waters are sweet,
and bread eaten in secret is pleasant."
18 But he does not know that the dead are there,
that her guests are in the depths of sheol.


flixel.addons.plugin.taskManager.AntTask
type
class
Constructor
new
(Obj :
Dynamic
, Func :
Dynamic
, ?Args :
Array
<
Dynamic
>, ?IgnoreCycle :
Bool
, ?Instant :
Bool
, ?Next :
AntTask
)
Creates a new AntTask
Instance Variables
args
:
Array
<
Dynamic
>
An array of arguments that can be passed to the task-method.
func
:
Dynamic
Method-task to be executed
ignoreCycle
:
Bool
If true then the task will be deleted from the manager immediately after execution.
instant
:
Bool
If true the task will be completed right after it's first call
next
:
AntTask
Pointer to the next task.
obj
:
Dynamic
An object to call func from
Instance Methods
dispose
() :
Void
Destroys the list.


Basics of the Web
World Wide Web
The world wide web is a collection of HTML documents that was invented in the 1990s and now emcompasses around 30 billion pages.
All sorts of files can be found on the web, such as HTML (hypertext markup language), images, videos, and music.
You to the server:
The user (you) accesses a browser which makes requests of a server via the internet. The requests use HTTP, the main protocol of the web. The browser then displays the files found on the web.
HTML is the heart of the web. It includes text content, mark-up, references to other documents and links to other pages.
HTML documents are made of HTML elements. When writing HTML, we tell browsers the type of each element by using HTML tags.
All whitespace in HTML is converted to a single space.
HTML elements are either inline or block. Block elements form an "invisible box" around the content inside of them.


Tegan Alexander Kissane
Democrat
My current occupation is Director of Stakeholder Communications for the City and County of Denver, Denver International Airport.
I have an Undergraduate Degree from the University of Kentucky with Majoring in Communications and Minor's in Sociology and Political Science with a Master's Degree in Public Policy from the University of Denver.
80207
I have not donated to any campaigns or political organizations within the last 5 years (since November 10, 2015). However, I have been an active member of the Democratic Party and have worked in local, state, and federal politics for many years.
Since November 10, 2015, I have been involved with the Colorado Blueflower Board.
I have extensive experience organizing and advocating on behalf of mission-based groups both in Colorado and across the country. I am a Denver native having grown up in Denver and have a deep connection to my community. I understand the varying interests of each neighborhood in the city and the specific challenges that exist within them. I am also very familiar with the various regions that comprise Colorado having worked on many statewide campaigns.
I feel that it is our civic responsibility to participate in the political process. I have a diverse background which would serve as a voice for those who may not always have a seat at the table. The redistricting process is a fundamental component of ensuring fair and equal representation at the ballot box. I would represent the interests of Coloradans with an unbiased, pragmatic approach, working to create districts that are properly representative of the communities they speak for.
With an undergraduate degree in communications, I am an excellent public speaker and would represent the organization’s priorities and positions with poise and thoughtfulness. I am comfortable working with elected officials and subject matter experts, in collaboration with stakeholders from across the political spectrum, to achieve common goals. I have the ability to promote team-building leadership, a commitment to multicultural awareness, gender sensitivity, and racial and socioeconomic appreciation. I have the skillset to make informed, and objective judgements to cultivate meaningful connections with any group of people, irrespective of political affiliation.
Adept in strategic planning and financial management, and possessing a graduate degree in Public Policy, I have the know how to inform and assist the decision-making process utilizing data-driven metrics. This approach allows me to excel as a thought partner, working to identify opportunities for process improvement and programmatic advancements while maintaining the highest level of professionalism and collegiality. I have the skillset to design and implement value-based strategies across organizations, a passion for public service, and a desire to contribute my talents to enable legacy projects for future generations.
Female


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PULP FICTION A film review by Raymond Johnston Copyright 1994 Raymond Johnston
Dir: Quentin Tarentino Starring: John Travolta, Samuel L. Jackson, Uma Thurman, Christopher Walken, Tim Roth, Eric Stoltz, Amanda Plummer, Roseanne Arquette, Harvey Keitel and Bruce Willis.  From Orson Welles to Spike Lee and John Singleton, this has held true. Quentin Tarentino, who came out of nowhere to write and direct RESERVOIR DOGS has broken that rule with PULP FICTION. It shows no signs of being the work of a young man struggling with too many ideas. Instead it is the polished work of an accomplished film maker.
As the title suggests, the film is about the world of gangsters and gamblers that populated the cheap paperback fiction of the thirties, forties and fifties, updated to a somewhat nebulous modern time. Just as SHORT CUTS interweaved various highbrow story threads into one somewhat convoluted and far reaching story, PULP FICTION takes themes from Cornell Woolrich and Raymond Chandler, mixes them with Seventies' TV and Fifties' movies into intertwining stories of deals gone wrong and criminals searching for some bigger meaning to it all.
Surprisingly enough, John Travolta, considered by many to be a has-been, or a one-hit wonder turns in the performance of his career. As the hapless hitman who figures into all the story threads he holds the film together. Between jobs he rattles on constantly to his cohort Samuel L. Jackson about the glories of life in Amsterdam and eroticism of foot massages. Jackson tends more towards quoting TV shows and Blaxploitaion movies. Travolta and Jackson encounter the rest of the all star cast, most of whom really just have glorified cameos in their own little story segments.
The various story segments each reflect different elements of pulp fiction genres- fixed fights, double crossed deals, dance contests, narcotics, weird perversions, and mob hits. Each story is really an homage to a famous crime film, THE KILLERS , THE SET-UP and KISS ME DEADLY, to name just a couple. Even samurai films get a slight nod. The stories quickly swings from surreal to absurd to profound, and no story is without its share of media savvy humor. Almost all the characters seem obsessed with the media. Hitman Travolta points out the difference between a Marilyn Monroe look alike and a Mamie van Doren look alike. Jackson quotes the "Kung Fu" series.
Tarantino's ear for dialogue and eye for sight gags is priceless. The little throw away lines and obtuse arguments that the characters constantly get into are what make this sometimes ultra-violent film worthwhile. Just when you peg a scene as being routine, some odd comic mishap sends the plot off in another direction. Tarentino also uses an odd non-linear narrative structure that leaves some important unanswered questions, and then fills in the gaps by returning to some plot threads, sort of like Kubrik's structure in THE KILLING, but not quite as rigorous. This structure works by keeping the pace steady and building some suspense.
While the film is, at close to two and a half hours, never boring and a great success, it has a few minor faults. A bizarre S& M scene doesn't really match the offhandedly flip tone of the rest of the film. Another is that some of the highly hyped actors in the film have little more than a cameo. Uma Thurman is really just in two scenes, Harvey Keitel in one, and Chris Walken has just a few lines. And while Tarentino scores big as both writer and director, he scores much less an actor. With actors of the caliber of Chris Walken doing bits, Tarentino just doesn't hold up in his acting scene.
Those minor quibbles aside, it is easy to see why PULP FICTION won the Palm d'or at Cannes. It delivers on the potential that the low-budget RESERVOIR DOGS promised.
.
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QuantumBit Design
Naturally Inspired Craft
contact
Greetings! First of all, thank you for visiting my website, and for taking the time to get to know a little about me and my work. My background is of a humble one. I come from a small town in the foothills of California. I was always a builder growing up- whether it be legos, helping my family with home construction projects, creating custom battle scenarios in Starcraft, or any and all art projects, I was always interested in seeing my creations come to life. It was not until recently that I started "going pro," by taking on a house flip, and building a website for my water company.
The water website, www.thvmwc.com was my fist major success with web development. The feeling I got from discovering front-end development was indescribable. It was more of a revelation that there was a world with unlimited resources, where creativity and imagination are the only constraints to building complex tools that actually could have a profound impact. It became apparent that a career working with the web was a way to make a measurable difference in the world. Needless to say, I was hooked. Now that I have the spark, I am moving forward with my career into web development to see just how big this new world is!
So, besides the fact that atomic physics is an incredibly fascinating field of science, and quantum computing is just around the corner, what interests me greatly about the subject is how mysterious sub-atomic mechanisms are. Quantum physics is still emerging each passing day, and the more we find out, the more obscure it seems to become. Despite it's perceived intangibility though, it is worth remembering that these tiny particles comprise literally all matter around us. Being from the mountains, I see a lot of value in the natural world, and have grown up with an understanding of our place in nature. When I was thinking of a theme for the portfolio, I wanted something that reflected this personality- a blending of the streamlined, manufactured look of tech, with the vast, breathtaking design of our own natural world.
If you have a comment on how this theme can be improved upon, and rest assured, it will be, please contact me.


All Classes
-
Class Summary Class Description AudioPanel AudioPanel is the entity that displays the volume controls at the bottom of the screen.Bark The object representing the players bark "attack".Bone The Bone class is the entity needed to be collected in order to progress to the next level.BoneListener BoneListener is the object responsible for managing collisions withBone
objects.BreakablePlatform BreakablePlatform template for creating obstacles that can be removed with a bark.CollisionHandler CollisionHandler is the object responsible for managing most of the collisions between objects.Controller The controller object takes keyboard inputs and outputs interprets them as actions that the player character can take.ControlPanel ControlPanel is the entity that displays the control bar and health of the player at the top of the screen.Game Main runnable class of the program.GameLevel GameLevel is the template for the level classes.LevelDebug LevelOne LevelThree LevelTwo MyView MyView is an entity used to display images in the background and foreground.NullLevel Platform The Platform entity is one that the player can stand on.Player The Player object is the main entity in the game, and the one used by the player in the gamePlayerScore PlayerScore is an entity used to display the players score without having it constantly updating every frame.SaveReader SaveReader reads save files and returns a player to the start of their chosen level.SaveWriter Save writer writes level data to a file.Spike The Spike class is an object that when collided with causes damage.TennisBall The tennis ball is an object that when collided with increases score.Tracker Tracker is an entity used to follow the movements of a body in the x-axis.


assigned
by None at 2020-08-12 19:15:04.labeled
by None at 2020-08-12 19:15:11.closed
by None at 2020-08-12 20:30:37.labeled
by None at 2020-08-12 20:31:17.assigned
by None at 2020-08-12 20:31:17.closed
by None at 2020-08-12 20:31:20.closed
by None at 2020-08-12 20:31:34.closed
by None at 2020-08-12 20:31:45.mentioned
by None at 2020-08-12 00:11:42.labeled
by James R. Griffin III at 2020-08-12 13:23:58.labeled
by James R. Griffin III at 2020-08-12 13:26:42.labeled
by James R. Griffin III at 2020-08-12 19:43:03.labeled
by James R. Griffin III at 2020-08-12 19:43:03.assigned
by James R. Griffin III at 2020-08-12 19:43:03.The following errors were identified:
ARK: NO ARK FOR: Neptune’s Trident: Sea Power, Order, and the Evolution of Maritime Strategy
ARK: NO ARK FOR: Medicine without Borders: Ṭibb and the Asbab Tradition in Mughal and Colonial India
ARK: NO ARK FOR: When the South Matters: Imagination of Chu and Classicization of Chuci (Verses of Chu)
ARK: NO ARK FOR: Hyperborean Baroque: David Klocker Ehrenstrahl (1628-98) and the Rhetoric of Style
ARK: NO ARK FOR: Essays on Empirical Corporate Finance
ARK: NO ARK FOR: Application of Optogenetics Towards Control of Microbial Chemical Production and in Vivo Protein-Protein Interactions
ARK: NO ARK FOR: On the Models of the Fluid-Polymer Systems
ARK: NO ARK FOR: The Politics of Immigration under Authoritarianism
ARK: NO ARK FOR: Ships of State: Global Shipping, the Emergency Fleet Corporation, and the Business of American Government, 1870-1930
ARK: NO ARK FOR: Fragment Coupling Protocols Via Metallaphotocatalysis
ARK: NO ARK FOR: Electrochemical Reduction of Carbon Dioxide on Zinc Antimonide and Developing of Catalytic Conductance for Benchmarking Electrocatalysts
ARK: NO ARK FOR: World Observation: Ito Chuta and the Making of Architectural Knowledge in Modern Japan, Volume I
ARK: NO ARK FOR: Trustguard: A Model for Practical Trust in Real Systems
I could manually find the following Items from the MARC records:
For many of the Items, I could not find the original SFTP upload. However, imports for the following items seem to have failed:
The MARC records have been updated with the ARKs for the missing Items and newly-imported Items. These will be submitted for upload into Voyager later today.
https://github.com/pulibrary/dspace-development/issues/149 was created in order to ensure that DRDS members can progress with this without requesting assistance from @pmgreen
mentioned
by Peter Green at 2020-08-12 19:44:07.subscribed
by Peter Green at 2020-08-12 19:44:07.@kelea99 this is an indexing problem on the pulfa side. However, the issue is that the MC279 file is not valid and causing the indexing process to fail. The solution is to validate the EAD data before checking files into SVN. This is the responsibility of the Mudd technical services staff.
Thank you, @sdellis ! Writing to #PULFA channel now. standby
nevermind! you got it! thanks so much, @sdellis !
mentioned
by Kim Leaman at 2020-08-12 16:33:31.subscribed
by Kim Leaman at 2020-08-12 16:33:31.mentioned
by Shaun Ellis at 2020-08-12 16:55:17.subscribed
by Shaun Ellis at 2020-08-12 16:55:17.mentioned
by Shaun Ellis at 2020-08-12 16:56:22.subscribed
by Shaun Ellis at 2020-08-12 16:56:22.referenced
by Trey Pendragon at 2020-08-12 17:23:56.closed
by None at 2020-08-12 17:56:44.referenced
by None at 2020-08-12 17:56:45.referenced
by None at 2020-08-12 17:56:44.merged
by None at 2020-08-12 17:56:44.closed
by None at 2020-08-12 17:56:44.head_ref_deleted
by None at 2020-08-12 17:56:45.Attempting to generate the pyramidal tiff now. This might be our biggest scroll - we'll see how it goes.
For now I generated the pyramidal manually. The final fix will be #3940. The command to do this is the following:
resource_id = "4eae2e8a-5fd5-4792-bdea-8e2085465687"
change_set_persister = ::ChangeSetPersister.new(metadata_adapter: Valkyrie::MetadataAdapter.find(:indexing_persister), storage_adapter: Valkyrie::StorageAdapter.find(:pyramidal_derivatives))
VIPSDerivativeService.new(id: resource_id, storage_adapter: storage_adapter).create_derivatives
resource = change_set_persister.query_service.find_by(id: resource_id)
resource.processing_status = "processed"
change_set_persister.metadata_adapter.persister.save(resource: resource)
mentioned
by Trey Pendragon at 2020-08-12 17:48:33.subscribed
by Trey Pendragon at 2020-08-12 17:48:34.closed
by Trey Pendragon at 2020-08-12 18:20:31.assigned
by Cliff Wulfman at 2020-08-12 19:22:38.Closed in preference for #4181
closed
by Trey Pendragon at 2020-08-12 19:37:16.The automatic completer turned out to be more complicated than I expected. Priorities have shifted a bit, so I'm putting this back into Ready and moving to a high priority ticket.
unassigned
by Trey Pendragon at 2020-08-12 19:37:57.IngestMETSJob is written to process a combined METS/MODS document that was generated by @jpstroop.
Doesn't show up here https://drive.google.com/drive/u/1/search?q=IsPartOf%20parent:1vM0mkt62UeRICyc45SlRnt9LgHxMnK-j
I'm assuming the short answer is to write some new code to handle the actual METS/MODS we have.
Or update the METS files to have the expected IsPartOf
div? The files we ingested most of the PUDL content from had StructMaps that started like this:
<mets:structMap TYPE="RelatedObjects">
<mets:div DMDID="q6wwb r7db1" ID="e4lns" LABEL="Default">
<mets:div CONTENTIDS="pudl0001" TYPE="IsPartOf"/>
Also, I do have METS files with IsPartOf
divs for most of PUDL, but I strongly suspect these are the collections that have already been ingested:
pudl0001, pudl0002, pudl0003, pudl0004, pudl0006, pudl0007, pudl0008, pudl0009, pudl0011, pudl0013, pudl0014, pudl0016, pudl0017, pudl0021, pudl0022, pudl0023, pudl0024, pudl0027, pudl0028, pudl0032, pudl0036, pudl0038, pudl0044, pudl0045, pudl0046, pudl0053, pudl0058, pudl0059, pudl0063, pudl0064, pudl0067, pudl0069, pudl0070, pudl0071, pudl0072, pudl0073, pudl0074, pudl0075, pudl0076, pudl0077, pudl0079, pudl0081, pudl0085, pudl0087, pudl0090, pudl0091, pudl0094, pudl0100, pudl0102, pudl0104, pudl0105, pudl0106, pudl0107, pudl0112, pudl0114, pudl0115, pudl0116, pudl0117, pudl0118, pudl0120, pudl0122, pudl0123, pudl0124, pudl0125, pudl0126, pudl0127, pudl0129, pudl0132, pudl0134, pudl0135, pudl0137, pudl0139
IngestMETSJob was created quite some time ago to ingest some hybrid METS/MODS @jpstroop created for (some) PUDL collections. Based on discussion with @hackmastera and @tpendragon , I'll modify ingestephemeramods to handle the GNIB MODS.
I don't think I ever 'compiled' pudl0066 (I really hope I can forget these numbers someday). The METS that are used to ingest into Figgy have just a slightly different flavor (don't ask me what now) from the PUDL MODS, and there's some ancient code on a branch of PUDL that should be able to make the METS that you need:
https://github.com/pulibrary/pudl_mets_compiler/tree/plum_migration
I can fire up my old dev machine in the next few days and see if it just works; not sure why it would be different from any other collection.
No worries, @jpstroop. I met with @tpendragon and @hackmastera this afternoon, and I've now got it well in hand!
mentioned
by Esmé Cowles at 2020-08-12 18:02:27.subscribed
by Esmé Cowles at 2020-08-12 18:02:27.mentioned
by Jon Stroop at 2020-08-12 18:02:27.subscribed
by Jon Stroop at 2020-08-12 18:02:28.closed
by Cliff Wulfman at 2020-08-12 19:17:23.mentioned
by None at 2020-08-12 19:17:23.subscribed
by None at 2020-08-12 19:17:23.mentioned
by Jon Stroop at 2020-08-12 19:17:23.subscribed
by Jon Stroop at 2020-08-12 19:17:23.mentioned
by Trey Pendragon at 2020-08-12 19:17:23.subscribed
by Trey Pendragon at 2020-08-12 19:17:23.reopened
by Jon Stroop at 2020-08-12 21:26:30.mentioned
by None at 2020-08-12 21:29:32.subscribed
by None at 2020-08-12 21:29:32.mentioned
by Jon Stroop at 2020-08-12 21:29:32.subscribed
by Jon Stroop at 2020-08-12 21:29:32.mentioned
by Trey Pendragon at 2020-08-12 21:29:32.subscribed
by Trey Pendragon at 2020-08-12 21:29:32.labeled
by Trey Pendragon at 2020-08-12 19:36:45.renamed
by Trey Pendragon at 2020-08-12 19:39:34.assigned
by Trey Pendragon at 2020-08-12 22:35:10.Links given in #1895 may be helpful.
The availability code gets very complex as soon as one starts to follow all the paths. Even if ultimately we want to refactor functionality out to marc_liberation, getting this code converted out of coffeescript and covered by tests will be a useful step in that process.
assigned
by None at 2020-08-12 14:46:02.closed
by Christina Chortaria at 2020-08-12 20:16:56.Coverage remained the same at 96.512% when pulling 7020e8e28b2437b4edbcaacf1c903cc4e2341734 on 2176-cdl-link into 5d1f2bc6609503f6400f9830027f015606ff3c4d on master.
@hackmastera the only thing is that the page will load and then the javascript will hide the button. But we can improve this later.
review_requested
by Christina Chortaria at 2020-08-12 15:32:59.mentioned
by None at 2020-08-12 20:06:16.subscribed
by None at 2020-08-12 20:06:16.deployed
by Trey Pendragon at 2020-08-12 20:07:41.referenced
by Christina Chortaria at 2020-08-12 20:16:56.merged
by Christina Chortaria at 2020-08-12 20:16:56.closed
by Christina Chortaria at 2020-08-12 20:16:56.labeled
by None at 2020-08-12 13:07:51.added_to_project
by None at 2020-08-12 13:08:41.labeled
by None at 2020-08-12 13:10:13.labeled
by None at 2020-08-12 13:10:33.labeled
by None at 2020-08-12 13:13:23.labeled
by None at 2020-08-12 13:16:28.labeled
by None at 2020-08-12 13:19:37.labeled
by None at 2020-08-12 13:20:55.labeled
by None at 2020-08-12 13:37:52.added_to_project
by None at 2020-08-12 13:38:06.labeled
by None at 2020-08-12 13:38:20.added_to_project
by None at 2020-08-12 13:38:28.labeled
by None at 2020-08-12 13:15:34.labeled
by None at 2020-08-12 13:40:02.labeled
by None at 2020-08-12 13:15:34.labeled
by None at 2020-08-12 13:40:08.labeled
by None at 2020-08-12 13:40:15.labeled
by None at 2020-08-12 13:40:27.labeled
by None at 2020-08-12 13:40:43.labeled
by None at 2020-08-12 13:41:37.labeled
by None at 2020-08-12 13:41:54.labeled
by None at 2020-08-12 13:43:06.labeled
by None at 2020-08-12 13:43:33.labeled
by None at 2020-08-12 13:43:50.labeled
by None at 2020-08-12 13:44:13.labeled
by None at 2020-08-12 13:45:25.labeled
by None at 2020-08-12 13:45:32.@kelea99 There is not currently a way to do this but it could be implemented.
@hackmastera , @kelynch and I were having a conversation about collections creation in figgy and I think question indirectly relates. It might be a good idea for a few of us, and @tpendragon as lead for figgy to talk about potential best practices / uses for each before something like this is considered? Id hate to waste your time.
unlabeled
by None at 2020-08-12 13:24:58.labeled
by None at 2020-08-12 13:24:58.mentioned
by Kim Leaman at 2020-08-12 13:25:06.subscribed
by Kim Leaman at 2020-08-12 13:25:06.renamed
by None at 2020-08-12 13:26:07.mentioned
by None at 2020-08-12 14:05:10.subscribed
by None at 2020-08-12 14:05:10.mentioned
by Trey Pendragon at 2020-08-12 14:05:10.subscribed
by Trey Pendragon at 2020-08-12 14:05:10.mentioned
by Kate Lynch at 2020-08-12 14:05:10.subscribed
by Kate Lynch at 2020-08-12 14:05:10.This seems like a different issue from #285. That one is a general feedback form as in the header on the catalog; this one is specific to a given record. What email address should this one submit to @kelea99 ?
@hackmastera it depends on the item and I would really like to hear your thoughts. I see a couple of ways this can go--one is a bit of a pain, but more direct. the other seems like it would be programmatically easier (but I do not know)? 1. (Easier?): the correction suggestion goes to the exhibition owner(s). 2. The Correction Suggestion, depending on what the item/correction is, would be triaged:
The metadata is incorrect in the DPUL/Figgy/Online Catalog record:
Any corrections requests for MARC/catalog records may be sent to<EMAIL_ADDRESS>Any corrections requests for EAD/Finding Aids: click on “suggest a correction” within the finding aid component itself or wherever that form is sent to ( would Kevin know this?)
Any corrections requests for ephemeral items would go to the Selector who works with the ephemeral collection (examples include Gabrielle/Fernando for LAE, Thomas/Anna for Soviet, Ellen for SAE, etc.)
If an item is described in an exhibition in DPUL incorrectly (in a curators note, or text within and exhibition, for example) - Contact Kim Leaman<EMAIL_ADDRESS>/ Slack: Kelea) and/or the exhibition curator listed in the left hand column on the “About” pages within the exhibit.
If the wrong metadata is associated with an item in Figgy and/or DPUL. - Contact Kim Leaman<EMAIL_ADDRESS>/ Slack: Kelea), and provide a link to the item in figgy/DPUL.
If the images are oriented incorrectly in the viewer, pages are askew and/or missing in Figgy/DPUL. - Contact Kim Leaman<EMAIL_ADDRESS>/ Slack: Kelea) or Roel Munoz<EMAIL_ADDRESS>/ Slack: Roel) and provide a link to the figgy/online catalog/DPUL URL, along with a description as to what is wrong with the images.
@kelea99 Either way works and it seems like a discussion to have with the exhibition owners. Option 1 we would do by pulling the email addresses from the exhibit record. Option 2 we would do by sending them all to a single / central email address (probably a metadata-oriented libguides email address?); and then the person monitoring that address would follow the workflow you lay out. We would just need to know what the email address is to send to.
@hackmastera I like the idea of option two, just to ensure the request gets through to the right people. OK, so we would need to have an said metadata-oriented libguides email address set up and go from there. I am happy to monitor that address as the primary point person, but it would be a good idea to have more folks than just me on that email/listserv (whatever it may be called in libguides). @kevinreiss Im assuming you are the person to talk to regarding setting an email like this up?
Sorry I said libguides but I meant libanswers.
renamed
by None at 2020-08-12 13:27:17.renamed
by None at 2020-08-12 13:28:45.mentioned
by Kim Leaman at 2020-08-12 13:33:19.subscribed
by Kim Leaman at 2020-08-12 13:33:19.mentioned
by None at 2020-08-12 13:57:01.subscribed
by None at 2020-08-12 13:57:01.mentioned
by Kim Leaman at 2020-08-12 14:29:05.subscribed
by Kim Leaman at 2020-08-12 14:29:05.mentioned
by Kevin Reiss at 2020-08-12 14:32:30.subscribed
by Kevin Reiss at 2020-08-12 14:32:30.mentioned
by None at 2020-08-12 14:32:30.subscribed
by None at 2020-08-12 14:32:30.I don't see the link in figgy @tpendragon. Here is the figgy record: https://figgy.princeton.edu/catalog/a538af11-8d21-4be7-aaa0-40c1e9514d89.
The click-throughs to the catalog are working but the link presented in the catalog gives a 404, which seems like another issue. Do we know where this program is?
@hackmastera I should have been clearer. The link is in the JSON-LD which gets synced to DPUL. See "electronic_locations": https://figgy.princeton.edu/catalog/a538af11-8d21-4be7-aaa0-40c1e9514d89.jsonld
@tpendragon thanks. So it's still giving a 404; have these been moved but not updated in voyager? @kelea99?
mentioned
by Trey Pendragon at 2020-08-12 13:06:01.subscribed
by Trey Pendragon at 2020-08-12 13:06:01.renamed
by None at 2020-08-12 13:06:47.mentioned
by None at 2020-08-12 17:10:30.subscribed
by None at 2020-08-12 17:10:30.mentioned
by Trey Pendragon at 2020-08-12 17:59:31.subscribed
by Trey Pendragon at 2020-08-12 17:59:31.mentioned
by Kim Leaman at 2020-08-12 17:59:32.subscribed
by Kim Leaman at 2020-08-12 17:59:32.referenced
by Francis Kayiwa at 2020-08-12 16:37:30.merged
by Francis Kayiwa at 2020-08-12 16:37:31.closed
by Francis Kayiwa at 2020-08-12 16:37:31.head_ref_deleted
by Francis Kayiwa at 2020-08-12 16:37:46.closed
by Francis Kayiwa at 2020-08-12 16:38:07.closed
by Francis Kayiwa at 2020-08-12 16:38:28.referenced
by James R. Griffin III at 2020-08-12 16:52:57.merged
by James R. Griffin III at 2020-08-12 16:52:57.closed
by James R. Griffin III at 2020-08-12 16:52:57.head_ref_deleted
by James R. Griffin III at 2020-08-12 16:53:01.closed
by Francis Kayiwa at 2020-08-12 16:53:59.review_requested
by Francis Kayiwa at 2020-08-12 17:21:15.referenced
by James R. Griffin III at 2020-08-12 17:45:06.merged
by James R. Griffin III at 2020-08-12 17:45:06.closed
by James R. Griffin III at 2020-08-12 17:45:06.head_ref_deleted
by James R. Griffin III at 2020-08-12 17:45:10.renamed
by Christina Chortaria at 2020-08-12 17:53:13.@christinach what are the keys and where can I find the desired values?
You can find them in the last pass in the Shared ITIMS
@hackmastera ^
So it looks like these are:
The orangelight
role depends on the blacklight-app
role which depends on rails-app
which runs the task that sets up the env. Everything looks set up correctly to me. I'm going to run it.
The problem is that it's pulling from roles/pulibrary.orangelight/vars/main.yml
. This file has a really high precedence and can't be overridden by playbook or groupvars. defaults/main.yml
is the place to put defaults for a role, unless we never expect it to change from playbook to playbook (an example from @kayiwa in slack was "upstream repo keys"). Otherwise we should keep settings in groupvars files.
assigned
by None at 2020-08-12 13:34:59.mentioned
by Christina Chortaria at 2020-08-12 14:41:29.subscribed
by Christina Chortaria at 2020-08-12 14:41:29.mentioned
by None at 2020-08-12 17:39:38.subscribed
by None at 2020-08-12 17:39:38.mentioned
by Francis Kayiwa at 2020-08-12 20:17:52.subscribed
by Francis Kayiwa at 2020-08-12 20:17:52.referenced
by None at 2020-08-12 20:50:28.referenced
by James R. Griffin III at 2020-08-12 20:49:49.merged
by James R. Griffin III at 2020-08-12 20:49:49.closed
by James R. Griffin III at 2020-08-12 20:49:50.head_ref_deleted
by James R. Griffin III at 2020-08-12 20:49:54.referenced
by Francis Kayiwa at 2020-08-12 17:20:38.closed
by Francis Kayiwa at 2020-08-12 21:10:08.closed
by Francis Kayiwa at 2020-08-12 23:45:01.closed
by Francis Kayiwa at 2020-08-12 23:45:27.unassigned
by Shaun Ellis at 2020-08-12 13:44:43.closed
by Eliot Jordan at 2020-08-12 16:27:07.referenced
by Eliot Jordan at 2020-08-12 16:27:07.merged
by Eliot Jordan at 2020-08-12 16:27:07.closed
by Eliot Jordan at 2020-08-12 16:27:07.head_ref_deleted
by Eliot Jordan at 2020-08-12 16:27:10.labeled
by None at 2020-08-12 20:04:52.labeled
by None at 2020-08-12 20:04:52.The commits need to be squashed for this, but I believe that this should be ready for review following this.
I am not certain why https://app.circleci.com/pipelines/github/pulibrary/pulfalight/604/workflows/35416731-b30e-426d-bf8e-f7de41c5fe89/jobs/1281 is occurring, and I cannot reproduce this locally.
I have tried a new git clone
on my own local development environment, and still cannot reproduce these CI errors.
The releases of arclight-6020c4ef4f65
and blacklight-7.2.0
are identical between my local and the CI environments.
head_ref_force_pushed
by James R. Griffin III at 2020-08-12 13:55:24.head_ref_force_pushed
by James R. Griffin III at 2020-08-12 14:03:11.head_ref_force_pushed
by James R. Griffin III at 2020-08-12 15:09:01.head_ref_force_pushed
by James R. Griffin III at 2020-08-12 18:23:14.head_ref_force_pushed
by James R. Griffin III at 2020-08-12 19:11:56.labeled
by None at 2020-08-12 21:30:44.milestoned
by None at 2020-08-12 21:30:44.mentioned
by Shaun Ellis at 2020-08-12 21:30:44.subscribed
by Shaun Ellis at 2020-08-12 21:30:44.


Components
Buttons
To make a button, just use the BUTTON tag. Add one of the standard classes (primary, success, warning, danger, info) to alter the button styles.
<button>Default</button>
<button class="primary">Primary</button>
<button class="success">Success</button>
<button class="warning">Warning</button>
<button class="danger">Danger</button>
<button class="info">Info</button>
You also can use the .button class where you want to make a non-button element to look like a button. You also can combine any of the standard style classes in conjunction with the button class in order to modify the button styles.
Default
Default
Success
Warning
Danger
Info
Input Buttons
<input type="button">
and
<input type="submit">
elements
also should work, but generally should be avoided
as they're not really semantic, don't support icons
and hard to style.
Element Groups
Whenever you need to create a group of elements, such as pills, and such, please use the .group class on the grouping element.

<button>One</button>
<button class="primary">Two</button>
<button>Three</button>
<button>Four</button>

You also can group input fields and select boxes with buttons.

<input type="search" placeholder="Search">
<button class="primary">Go</button>

Navigation
Navigation in the case of pain.less.css should be a combination of the NAV and the A elements. Like so.

One
Two
Three

The actual look of the nav element is contextual. For example if you put the NAV element within the BODY > HEADER element (or add the .bar class to it), it will look like the navbar in the header.

Cheezburgerz!

Home
Cheez
Blog

.... the rest of the page markup

If you put the NAV component structure in the ASIDE element in on of the sidebars, or add the .list class to it, you'll end up with a vertical navigation list.

Home
Cheez
Blog


|
My Project
|
A light-weight emulator to calculate switch targets from switch variables. More...
#include <jumptable.hh>
Public Member Functions | |
| EmulateFunction (Funcdata *f) | |
| Constructor. More... | |
| void | setLoadCollect (bool val) |
| Set whether we collect LOAD information. | |
| virtual void | setExecuteAddress (const Address &addr) |
| Set the address of the next instruction to emulate. | |
| virtual uintb | getVarnodeValue (Varnode *vn) const |
| Given a specific Varnode, retrieve the current value for it from the machine state. More... | |
| virtual void | setVarnodeValue (Varnode *vn, uintb val) |
| Given a specific Varnode, set the given value for it in the current machine state. More... | |
| uintb | emulatePath (uintb val, const PathMeld &pathMeld, PcodeOp *startop, Varnode *startvn) |
| Execute from a given starting point and value to the common end-point of the path set. More... | |
| void | collectLoadPoints (vector< LoadTable > &res) const |
| Recover any LOAD table descriptions. More... | |
| Public Member Functions inherited from EmulatePcodeOp | |
| EmulatePcodeOp (Architecture *g) | |
| Constructor. More... | |
| void | setCurrentOp (PcodeOp *op) |
| Establish the current PcodeOp being emulated. More... | |
| virtual Address | getExecuteAddress (void) const |
| Get the address of the current instruction being executed. | |
| Public Member Functions inherited from Emulate | |
| Emulate (void) | |
| generic emulator constructor | |
| void | setHalt (bool val) |
| Set the halt state of the emulator. More... | |
| bool | getHalt (void) const |
| Get the halt state of the emulator. More... | |
| void | executeCurrentOp (void) |
| Do a single pcode op step. More... | |
Additional Inherited Members | |
| Protected Member Functions inherited from EmulatePcodeOp | |
| virtual uintb | getLoadImageValue (AddrSpace *spc, uintb offset, int4 sz) const |
| Pull a value from the load-image given a specific address. More... | |
| virtual void | executeUnary (void) |
| Execute a unary arithmetic/logical operation. | |
| virtual void | executeBinary (void) |
| Execute a binary arithmetic/logical operation. | |
| virtual void | executeStore (void) |
| Standard behavior for a p-code STORE. | |
| virtual bool | executeCbranch (void) |
| Check if the conditional of a CBRANCH is true. More... | |
| virtual void | executeMultiequal (void) |
| Standard behavior for a MULTIEQUAL (phi-node) | |
| virtual void | executeIndirect (void) |
| Standard behavior for an INDIRECT op. | |
| virtual void | executeSegmentOp (void) |
| Behavior for a SEGMENTOP. | |
| virtual void | executeCpoolRef (void) |
| Standard behavior for a CPOOLREF (constant pool reference) op. | |
| virtual void | executeNew (void) |
| Standard behavior for (low-level) NEW op. | |
| Protected Attributes inherited from EmulatePcodeOp | |
| Architecture * | glb |
| The underlying Architecture for the program being emulated. | |
| PcodeOp * | currentOp |
| Current PcodeOp being executed. | |
| PcodeOp * | lastOp |
| Last PcodeOp that was executed. | |
| Protected Attributes inherited from Emulate | |
| bool | emu_halted |
| Set to true if the emulator is halted. | |
| OpBehavior * | currentBehave |
| Behavior of the next op to execute. | |
A light-weight emulator to calculate switch targets from switch variables.
We assume we only have to store memory state for individual Varnodes and that dynamic LOADs are resolved from the LoadImage. BRANCH and CBRANCH emulation will fail, there can only be one execution path, although there can be multiple data-flow paths.
| EmulateFunction::EmulateFunction | ( | Funcdata * | f | ) |
| f | is the function to emulate within |
| void EmulateFunction::collectLoadPoints | ( | vector< LoadTable > & | res | ) | const |
Recover any LOAD table descriptions.
Pass back any LOAD records collected during emulation. The individual records are sorted and collapsed into concise table descriptions.
| res | will hold any resulting table descriptions |
| uintb EmulateFunction::emulatePath | ( | uintb | val, |
| const PathMeld & | pathMeld, | ||
| PcodeOp * | startop, | ||
| Varnode * | startvn | ||
| ) |
Execute from a given starting point and value to the common end-point of the path set.
Flow the given value through all paths in the path container to produce the single output value.
| val | is the starting value |
| pathMeld | is the set of paths to execute |
| startop | is the starting PcodeOp within the path set |
| startvn | is the Varnode holding the starting value |
|
virtual |
Given a specific Varnode, retrieve the current value for it from the machine state.
This is the placeholder internal operation for obtaining a Varnode value during emulation. The value is loaded using the Varnode as the address and storage size.
| vn | is the specific Varnode |
Implements EmulatePcodeOp.
|
virtual |
Given a specific Varnode, set the given value for it in the current machine state.
This is the placeholder internal operation for setting a Varnode value during emulation. The value is stored using the Varnode as the address and storage size.
| vn | is the specific Varnode |
| val | is the constant value to store |
Implements EmulatePcodeOp.


Lecture 15: Programming review session¶
Common data types in python: lists, strings, dictionaries, ints, floats, boolean values, tuples¶
string¶
s = '40'
r = '20'
print r + s
int¶
s = 40
r = 20
print r + s
float¶
s = 40.0
r = 20.0
print r + s
boolean values: True or False¶
s = True
r = False
print s or r
print s and r
print 42 == 42
print 4 > 5
c = True
print (42 >= 41) and ('A' == 'a' or c)
Loops and conditionals¶
Loops¶
for
loops are much more commonly used in python then while
loops (although this isn’t necessarily true in other languages). for
loops allow you to iterate over several steps of code to perform the same operation multiple times, usually with a different value for one or a few variables. For example, what does this code do:
for c in 'ACCGATTGACC':
print c.lower(),
c
in this case is a variable name that gets set to each entry in the string in turn. All code in the indented block will be executed before c
gets assigned to the next value.
Sometimes you need to do the same thing some specified number of times with no different variable settings (which differs from the previous example where we’re doing the same thing multiple times with a different value of c
each time). To do this in python, you would typically use the range
function, which when called as:
range(n)
returns a list of numbers from 0 to n-1: [0, 1, 2, ..., n-1]
. For example, to randomly reorder the positions in a given DNA sequence 25 times and print the resulting sequences, you could do the following:
sequence = 'ACCGAGGACCATACATTA'
for i in range(25):
shuffle(sequence)
print ''.join(sequence)
Note that we don’t actually use the value assigned to the variable i
ever: we just use that in combination with range to iterate 25 times.
Conditional statements¶
Conditional statements allow you to apply some steps under certain conditions, such as when two values are equal, and apply some other steps in cases where those certain conditions are not met. The if/elif/else
statements are used for conditionally executing some code in python. For example, describe line-by-line what this code does:
sequence = 'ACCTAGGCAT'
result = []
for base in sequence:
if base == 'T':
result.append('U')
elif base == 'A' or base == 'C' or base == 'G':
result.append(base)
else:
print "Unknown base (%s). Cannot complete." % base
exit()
print ''.join(result)
Functions in python¶
def complement_sequence(seq,complements={'A':'T','C':'G','T':'A','G':'C'}):
result = []
for base in seq:
result.append(complements[base])
return ''.join(result)
my_seq = 'ACCGATTAGCCA'
complement_sequence(my_seq)
my_seq_comp = complement_sequence(my_seq)
my_seq_comp_non_default = complement_sequence(my_seq,{'A':'t','C':'g','T':'a','G':'c'})


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