Class Base64Codec
Inherited Members
Namespace: Fs.Binary.Codecs.Base64
Assembly: Fs.Binary.Codecs.dll
Syntax
public class Base64Codec : BinaryCodec
Constructors
| Improve this Doc View SourceBase64Codec(Base64Settings)
Declaration
public Base64Codec(Base64Settings settings)
Parameters
| Type | Name | Description |
|---|---|---|
| Base64Settings | settings |
Properties
| Improve this Doc View SourceMinimumInputBuffer
Gets the minimum amount of input data required to ensure that the codec will always make forward progress.
Declaration
public override int MinimumInputBuffer { get; }
Property Value
| Type | Description |
|---|---|
| System.Int32 |
Overrides
| Improve this Doc View SourceMinimumOutputBuffer
Gets the minimum amout of output buffer required to ensure that the codec will always make forward progress.
Declaration
public override int MinimumOutputBuffer { get; }
Property Value
| Type | Description |
|---|---|
| System.Int32 |
Overrides
| Improve this Doc View SourceSettings
Declaration
public Base64Settings Settings { get; }
Property Value
| Type | Description |
|---|---|
| Base64Settings |
Methods
| Improve this Doc View SourceGetByteCount(ReadOnlySpan<Char>)
Calculates the number of bytes produced by decoding the specified sequence of characters.
Declaration
public override int GetByteCount(ReadOnlySpan<char> chars)
Parameters
| Type | Name | Description |
|---|---|---|
| ReadOnlySpan<System.Char> | chars | The sequence of characters to decode. |
Returns
| Type | Description |
|---|---|
| System.Int32 | The number of bytes produced by decoding the specified sequence of characters. |
Overrides
| Improve this Doc View SourceGetBytes(ReadOnlySpan<Char>)
Decodes the specified sequence of characters into an array of bytes.
Declaration
public override byte[] GetBytes(ReadOnlySpan<char> chars)
Parameters
| Type | Name | Description |
|---|---|---|
| ReadOnlySpan<System.Char> | chars | The characters to decode. |
Returns
| Type | Description |
|---|---|
| System.Byte[] | A byte array containing the results of decoding the specified characters. |
Overrides
| Improve this Doc View SourceGetCharCount(ReadOnlySpan<Byte>)
Calculates the number of characters produced by encoding a specified sequence of bytes.
Declaration
public override int GetCharCount(ReadOnlySpan<byte> bytes)
Parameters
| Type | Name | Description |
|---|---|---|
| ReadOnlySpan<System.Byte> | bytes | The sequence of bytes to encode. |
Returns
| Type | Description |
|---|---|
| System.Int32 | The number of characters produced by encoding the sequence of bytes. |
Overrides
| Improve this Doc View SourceGetChars(ReadOnlySpan<Byte>)
Encodes the specified sequence of bytes.
Declaration
public override char[] GetChars(ReadOnlySpan<byte> bytes)
Parameters
| Type | Name | Description |
|---|---|---|
| ReadOnlySpan<System.Byte> | bytes | The sequence of bytes to encode. |
Returns
| Type | Description |
|---|---|
| System.Char[] | A character array containing the results of encoding the sequence of bytes. |
Overrides
| Improve this Doc View SourceGetDecoder()
Obtains a decoder that converts a sequence of encoded characters into a sequence of bytes.
Declaration
public override BinaryDecoder GetDecoder()
Returns
| Type | Description |
|---|---|
| BinaryDecoder | A BinaryDecoder that converts a sequence of characters in to a decoded sequence of byte. |
Overrides
| Improve this Doc View SourceGetEncoder()
Obtains an encoder that converts a sequence of bytes into an encoded sequence of characters.
Declaration
public override BinaryEncoder GetEncoder()
Returns
| Type | Description |
|---|---|
| BinaryEncoder | A BinaryEncoder that converts a sequence of bytes in to an encoded sequence of characters. |
Overrides
| Improve this Doc View SourceGetMaxByteCount(Int32)
Calculates the maximum number of bytes produced by decoding the specified number of characters.
Declaration
public override int GetMaxByteCount(int charCount)
Parameters
| Type | Name | Description |
|---|---|---|
| System.Int32 | charCount | The number of characters to decode. |
Returns
| Type | Description |
|---|---|
| System.Int32 | The maximum number of bytes produced by decoding the specified number of characters. |
Overrides
| Improve this Doc View SourceGetMaxCharCount(Int32)
Calculates the maximum number of characters produced by encoding the specified number of bytes.
Declaration
public override int GetMaxCharCount(int byteCount)
Parameters
| Type | Name | Description |
|---|---|---|
| System.Int32 | byteCount | The number of bytes to encode. |
Returns
| Type | Description |
|---|---|
| System.Int32 | The maximum number of characters produced by encoding the specified number of bytes. |
Overrides
| Improve this Doc View SourceGetString(ReadOnlySpan<Byte>)
Encodes the specified sequence of bytes.
Declaration
public override string GetString(ReadOnlySpan<byte> bytes)
Parameters
| Type | Name | Description |
|---|---|---|
| ReadOnlySpan<System.Byte> | bytes | The sequence of bytes to encode. |
Returns
| Type | Description |
|---|---|
| System.String | A string containing the results of encoding the sequence of bytes. |


Arita Acharjee
Public Relation Officer
"some quote by person goes here .....Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor"
24-10-2020 : started new project24-10-2020 : started new project24-10-2020 : started new project
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24-10-2020 : started new project24-10-2020 : started new project24-10-2020 : started new project
24-10-2020 : started new project24-10-2020 : started new project24-10-2020 : started new project
24-10-2020 : started new project24-10-2020 : started new project24-10-2020 : started new project
Public Relation Officer
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Here we disscus ideas on how to prank and hack lunchb0ne's loner life.
Link to his github right here.


British MPs vote on new speaker after Bercow's departure
LONDON: British MPs began the selection of their new speaker on Monday (Nov 4) to replace John Bercow, who enraged the government but won a global following with his parliamentary rulings on Brexit.
Seven MPs have put themselves forward to replace Bercow, whose shouts of "Order! Order!" have rung out across the House of Commons since June 2009.
READ: UK's Johnson 'sorry' for Brexit delay
Lindsay Hoyle, Bercow's deputy since 2010, is the odds-on favourite to fill his shoes - and won the first round of Monday's voting by a wide margin - but other political heavyweights are also still vying for the job.
After Prime Minister Boris Johnson opened the process on behalf of Queen Elizabeth II, each candidate gave a short pitch before a series of secret ballots began.
Two were eliminated in the first round but voting will continue until a winner secures more than half of votes, and can take their seat in the speaker's raised green chair.
But he or she will not have too long to get comfortable as parliament will be dissolved late Tuesday for the Dec 12 election, after which they will return.
The winning candidate is expected to give up party affiliation and traditionally does not contest general elections.
KEY BREXIT PLAYER
Chosing a new speaker has been an unremarkable event in the past, but Bercow became a key player in the chaotic process of Britain's exit from the European Union.
With the Commons divided over how, when and even if Brexit should happen, he oversaw more than three years of crucial debates that defined the course of Brexit.
His supporters say he has empowered ordinary MPs by granting time for emergency debates and amendments, which had the effect of pressuring or even tying ministers' hands.
But critics accused him of subverting centuries of parliamentary tradition with the aim of frustrating Brexit.
Bercow, who was a Conservative MP before he took on the politically neutral role of speaker, has also been accused of failing to tackle a culture of bullying.
Last week, Johnson paid guarded tribute, likening Bercow's glare to a "trademark Tony Montana scowl", after Al Pacino's character in the 1983 film "Scarface".
Opposition Labour party leader Jeremy Corbyn praised his modernising reforms, which included increasing staff diversity, boosting public access to parliament and switching from traditional robes to suits.
But it was his colourful personality and eccentric performances in parliament that gave him an international profile.
A social media mash-up by German television of footage of Bercow calming rowdy MPs has been seen more than a million times. A Belgian newspaper called him "irreplaceable".
If Johnson succeeds in his goal of winning a majority in the December election - as opinion polls suggest - the next speaker's job could be fairly straightforward as chair of debates.
But if he fails and there is another minority government, the new arrival will have to arbitrate between yet another group of divided MPs.
DEPUTIES JOSTLE FOR PROMOTION
The clear winner in the first round was Hoyle, with 211 out of 562 ballots cast.
He has been a Labour MP for 22 years and was Bercow's deputy from 2010, since when his distinctive Lancashire accent has rung out from the speaker's chair.
The 62-year-old is as unimpressed as his predecessor by the shouting and braying from MPs, once chastising Scottish Nationalists for humming the EU anthem "Ode to Joy" in the chamber.
Hoyle pledged in an interview published in the Sunday Times - in which he introduced his parrot "Boris" - to repair what he claims has become a "toxic parliament".
"I don't want the abuse of each other and I think we have got to close that down quickly and make sure it is a calmer place to be," he said.
Bercow's number two deputy, Eleanor Laing, was in second place with 113 votes.
The 61-year-old Conservative entered parliament in 1997 and previously served as the party's spokeswoman on Scotland.
They were followed by former Church of England vicar and now Labour MP Chris Bryant, Labour MP Harriet Harman, parliament's longest-serving female MP, and another deputy speaker, Labour's Rosie Winterton.


An eager purely functional language with records and subtypes. The language has integers, booleans, recursive functions, and immutable records.
The file example.sub defines addition and conjugation of complex numbers.
example.sub


I wanted to share my story for those out there looking to try oxycontin. I am a skinny short girl who started out using marijuana everyday and then in 1999 I got pregnant so I stopped but then I had severe back pain due to being born with spina bifada so my doctor put me on 750mg. vicodin, while I was six months pregnant.
Since I had my first child, in 1999, I then tried oxycontin starting with 10mg. I saw the doctor every three months and each time I went I kept asking for him to raise the dose. Well he would write for more quantity. I was up over 300 pills a month. Then he switched me to 20mg. and then 40mg. I am now at getting 90 pills a month (40mg.) and I have since been pregnant and had another baby only this time she was born addicted (she is fine now) but I have tried 80mg. pills and would like to try the 160mg. pill (I believe that is the highest).
Everytime I run out of my pills I go crazy. I go thru some really bad withdrawls. When I am on my pills, for one thing I do not have any pain and for another I feel like I have so much energy and confidence that I can do anything. When I am not on these pills I lay in bed with deep depression, the coldness and sweats, not eating and thinking of nothing else except what I can get my hands on to help me get over this sick feeling. I have been without oxy's for two weeks before and it still seems like it would take longer to overcome this addiction.
I really need to seek help and I plan on doing so because I have two beautiful children that does not deserve a part time Mother and I would not even call myself a part timer. Hopefully the doctors can come up with something else for my pain other than something addictive. So please take it from someone who has been addicted to this great high but destructive lifestyle to never try oxycontin even for the first time. Granted it does not hit everyone the same way but it is listed as one of the biggest ADDICTIVE drug out there.
Sincerely,
Still Trying To Cope
LIL jo
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


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DOWN IN THE DELTA (Miramax) Starring: Alfre Woodard, Al Freeman Jr., Esther Rolle, Mary Alice, Mpho Koaho, Wesley Snipes. Screenplay: Myron Goble. Producers: Rick Rosenberg, Bob Christiansen, Victor McGauley, Wesley Snipes and Reuben Cannon. Director: Maya Angelou. MPAA Rating: PG-13 (mild profanity, drug use) Running Time: 111 minutes. Reviewed by Scott Renshaw.
DOWN IN THE DELTA, a paean to the importance of family ties, stays such a course of earnestness and muted conflict that it's hard to work up much emotion about the people involved. The story opens in Chicago, where Loretta Sinclair (Alfre Woodard) is responding to the challenges of unemployment and single parenthood -- including an autistic daughter -- with alcohol and drugs. Recognizing a disaster in the making, Loretta's mother (Mary Alice) threatens Loretta with the loss of her kids if she doesn't take son Thomas (Mpho Koaho) and daughter Tracy (Kulani Hansen) to spend the summer at the Sinclair family's Mississippi homestead. There Loretta meets her Uncle Earl (Al Freeman Jr.), a restaurateur caring for his Alzheimer's-stricken wife Annie (the late Esther Rolle) and committed to holding the Sinclairs together.
The first act of DOWN IN THE DELTA gets it off to a rocky start, presenting the inner city background with all the urgency of a generic studio back-lot. Young men hang around cars looking surly, while second unit footage passes buildings that might as well have "The Projects" stamped across them. It's important to the film's themes that the city feel chaotic, a fragmented collection of people from fragmented homes, but it feels false right down to the crack-house apartment where Loretta goes to get high; even the always-reliable Woodard appears adrift in some mediocre TV-drama episode. Director Maya Angelou almost seems afraid of getting her hands dirty, as though the story's more uplifting message will be sullied by showing inner city life at its worst.
DOWN IN THE DELTA gets much stronger when the setting shifts south, and not just because the location feels more genuine. Al Freeman Jr. radiates patriarchal gravity and moral strength as Uncle Earl, his keen eyes providing an added intelligence to every word of wisdom from his lips. He serves as the example of committed family responsibility -- attending to his ill wife where Loretta's husband ran out on his ill daughter, teaching young Thomas about Sinclair ancestors so he'll understand the power of familial love. Screenwriter Myron Goble occasionally pushes too hard on these themes, stumbling over the vague estrangement of Earl's son Will (Wesley Snipes), but Freeman is always there to bring them back into focus. You never doubt for a moment that Earl is the kind of man who can straighten out the lives of others not by lecturing to them, but by showing them the right way.
DOWN IN THE DELTA is the kind of film you'll probably walk out of with a good feeling, even though you may not necessarily have enjoyed it all that much. The key dramatic points prove to be exceedingly tame stuff, adding to the impression that the film is just cruising along on the momentum of its good intentions. Usually films of this kind struggle by becoming too strident; this one struggles by being not nearly strident enough. Freeman alone makes this film worth watching, guiding both viewers and other characters to an understanding of what can be accomplished through a sense of shared responsibility. Still, it should have been easier to be more supportive of a film with as many valuable things to say. DOWN IN THE DELTA's soft-spoken drama is more likely to move you to respectful nods than to social action.
On the Renshaw scale of 0 to 10 delta dawnings: 6.
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Greetings! I am Hanyuan Xiao, a second year PhD student in VGL lab at Institute for Creative Technologies (ICT), an affiliated institution of University of Southern California. My current research lies in interdisciplinary area of Computer Vision and Computer Graphics. I am interested in Augmented Reality (AR) in particular. Please feel free to contact me if you are interested in collaboration!


In this project, you'll use generative adversarial networks to generate new images of faces.
You'll be using two datasets in this project:
Since the celebA dataset is complex and you're doing GANs in a project for the first time, we want you to test your neural network on MNIST before CelebA. Running the GANs on MNIST will allow you to see how well your model trains sooner.
If you're using FloydHub, set data_dir
to "/input" and use the FloydHub data ID "R5KrjnANiKVhLWAkpXhNBe".
data_dir = './data'
# FloydHub - Use with data ID "R5KrjnANiKVhLWAkpXhNBe"
#data_dir = '/input'
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import helper
helper.download_extract('mnist', data_dir)
helper.download_extract('celeba', data_dir)
show_n_images = 25
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
%matplotlib inline
import os
from glob import glob
from matplotlib import pyplot
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'mnist/*.jpg'))[:show_n_images], 28, 28, 'L')
pyplot.imshow(helper.images_square_grid(mnist_images, 'L'), cmap='gray')
The CelebFaces Attributes Dataset (CelebA) dataset contains over 200,000 celebrity images with annotations. Since you're going to be generating faces, you won't need the annotations. You can view the first number of examples by changing show_n_images
.
show_n_images = 25
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'img_align_celeba/*.jpg'))[:show_n_images], 28, 28, 'RGB')
pyplot.imshow(helper.images_square_grid(mnist_images, 'RGB'))
Since the project's main focus is on building the GANs, we'll preprocess the data for you. The values of the MNIST and CelebA dataset will be in the range of -0.5 to 0.5 of 28x28 dimensional images. The CelebA images will be cropped to remove parts of the image that don't include a face, then resized down to 28x28.

You'll build the components necessary to build a GANs by implementing the following functions below:
model_inputs
discriminator
generator
model_loss
model_opt
train
This will check to make sure you have the correct version of TensorFlow and access to a GPU
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
from distutils.version import LooseVersion
import warnings
import tensorflow as tf
# Check TensorFlow Version
assert LooseVersion(tf.__version__) >= LooseVersion('1.0'), 'Please use TensorFlow version 1.0 or newer. You are using {}'.format(tf.__version__)
print('TensorFlow Version: {}'.format(tf.__version__))
# Check for a GPU
if not tf.test.gpu_device_name():
warnings.warn('No GPU found. Please use a GPU to train your neural network.')
else:
print('Default GPU Device: {}'.format(tf.test.gpu_device_name()))
Implement the model_inputs
function to create TF Placeholders for the Neural Network. It should create the following placeholders:
image_width
, image_height
, and image_channels
.z_dim
.Return the placeholders in the following the tuple (tensor of real input images, tensor of z data)
import problem_unittests as tests
def model_inputs(image_width, image_height, image_channels, z_dim):
"""
Create the model inputs
:param image_width: The input image width
:param image_height: The input image height
:param image_channels: The number of image channels
:param z_dim: The dimension of Z
:return: Tuple of (tensor of real input images, tensor of z data, learning rate)
"""
inputs_real = tf.placeholder(tf.float32, (None, image_width, image_height, image_channels), name='input_real')
inputs_z = tf.placeholder(tf.float32, (None, z_dim), name='input_z')
learning_rate = tf.placeholder(tf.float32, None, name='learning_rate')
return inputs_real, inputs_z, learning_rate
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_inputs(model_inputs)
Implement discriminator
to create a discriminator neural network that discriminates on images
. This function should be able to reuse the variabes in the neural network. Use tf.variable_scope
with a scope name of "discriminator" to allow the variables to be reused. The function should return a tuple of (tensor output of the generator, tensor logits of the generator).
def leaky_relu(x, alpha=0.2, name='leaky_relu'):
return tf.maximum(x, alpha * x, name=name)
def discriminator(images, reuse=False):
"""
Create the discriminator network
:param image: Tensor of input image(s)
:param reuse: Boolean if the weights should be reused
:return: Tuple of (tensor output of the discriminator, tensor logits of the discriminator)
"""
alpha = 0.2
with tf.variable_scope('discriminator', reuse=reuse):
# Input layer is 32x32x3
x1 = tf.layers.conv2d(images, 64, 5, strides=2, padding='same', kernel_initializer=tf.contrib.layers.xavier_initializer())
relu1 = leaky_relu(x1)
# 16x16x64
x2 = tf.layers.conv2d(relu1, 128, 5, strides=2, padding='same', kernel_initializer=tf.contrib.layers.xavier_initializer())
bn2 = tf.layers.batch_normalization(x2, training=True)
relu2 = leaky_relu(bn2)
# 8x8x128
x3 = tf.layers.conv2d(relu2, 256, 5, strides=2, padding='same', kernel_initializer=tf.contrib.layers.xavier_initializer())
bn3 = tf.layers.batch_normalization(x3, training=True)
relu3 = leaky_relu(bn3)
relu3 = tf.nn.dropout(relu3, keep_prob=0.8)
# 4x4x256
# Flatten it
flat = tf.reshape(relu3, (-1, 4*4*256))
logits = tf.layers.dense(flat, 1)
out = tf.sigmoid(logits)
return out, logits
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_discriminator(discriminator, tf)
Implement generator
to generate an image using z
. This function should be able to reuse the variabes in the neural network. Use tf.variable_scope
with a scope name of "generator" to allow the variables to be reused. The function should return the generated 28 x 28 x out_channel_dim
images.
def generator(z, out_channel_dim, is_train=True):
"""
Create the generator network
:param z: Input z
:param out_channel_dim: The number of channels in the output image
:param is_train: Boolean if generator is being used for training
:return: The tensor output of the generator
"""
alpha = 0.2
with tf.variable_scope('generator', reuse=not is_train):
# First fully connected layer
x1 = tf.layers.dense(z, 2*2*512)
# Reshape it to start the convolutional stack
x1 = tf.reshape(x1, (-1, 2, 2, 512))
x1 = tf.layers.batch_normalization(x1, training=is_train)
x1 = leaky_relu(x1)
# 2x2x512 now
x2 = tf.layers.conv2d_transpose(x1, 256, 5, strides=2, padding='valid')
x2 = tf.layers.batch_normalization(x2, training=is_train)
x2 = leaky_relu(x2)
# 7x7x256 now
x3 = tf.layers.conv2d_transpose(x2, 128, 5, strides=2, padding='same')
x3 = tf.layers.batch_normalization(x3, training=is_train)
x3 = leaky_relu(x3)
# 14x14x128 now
# Output layer
logits = tf.layers.conv2d_transpose(x3, out_channel_dim, 5, strides=2, padding='same')
# 28x28x3 now
out = tf.tanh(logits)
return out
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_generator(generator, tf)
Implement model_loss
to build the GANs for training and calculate the loss. The function should return a tuple of (discriminator loss, generator loss). Use the following functions you implemented:
discriminator(images, reuse=False)
generator(z, out_channel_dim, is_train=True)
def model_loss(input_real, input_z, out_channel_dim):
"""
Get the loss for the discriminator and generator
:param input_real: Images from the real dataset
:param input_z: Z input
:param out_channel_dim: The number of channels in the output image
:return: A tuple of (discriminator loss, generator loss)
"""
alpha = 0.2
smooth = 0.1
g_model = generator(input_z, out_channel_dim, is_train=True)
d_model_real, d_logits_real = discriminator(input_real, reuse=False)
d_model_fake, d_logits_fake = discriminator(g_model, reuse=True)
d_loss_real = tf.reduce_mean(
tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_real, labels=tf.ones_like(d_model_real) * (1 - smooth)))
d_loss_fake = tf.reduce_mean(
tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake, labels=tf.zeros_like(d_model_fake)))
g_loss = tf.reduce_mean(
tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake, labels=tf.ones_like(d_model_fake)* (1 - smooth)))
d_loss = d_loss_real + d_loss_fake
return d_loss, g_loss
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_loss(model_loss)
Implement model_opt
to create the optimization operations for the GANs. Use tf.trainable_variables
to get all the trainable variables. Filter the variables with names that are in the discriminator and generator scope names. The function should return a tuple of (discriminator training operation, generator training operation).
def model_opt(d_loss, g_loss, learning_rate, beta1):
"""
Get optimization operations
:param d_loss: Discriminator loss Tensor
:param g_loss: Generator loss Tensor
:param learning_rate: Learning Rate Placeholder
:param beta1: The exponential decay rate for the 1st moment in the optimizer
:return: A tuple of (discriminator training operation, generator training operation)
"""
# Get weights and bias to update
t_vars = tf.trainable_variables()
d_vars = [var for var in t_vars if var.name.startswith('discriminator')]
g_vars = [var for var in t_vars if var.name.startswith('generator')]
# Optimize
with tf.control_dependencies(tf.get_collection(tf.GraphKeys.UPDATE_OPS)):
d_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(d_loss, var_list=d_vars)
g_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(g_loss, var_list=g_vars)
return d_train_opt, g_train_opt
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_opt(model_opt, tf)
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import numpy as np
def show_generator_output(sess, n_images, input_z, out_channel_dim, image_mode):
"""
Show example output for the generator
:param sess: TensorFlow session
:param n_images: Number of Images to display
:param input_z: Input Z Tensor
:param out_channel_dim: The number of channels in the output image
:param image_mode: The mode to use for images ("RGB" or "L")
"""
cmap = None if image_mode == 'RGB' else 'gray'
z_dim = input_z.get_shape().as_list()[-1]
example_z = np.random.uniform(-1, 1, size=[n_images, z_dim])
samples = sess.run(
generator(input_z, out_channel_dim, False),
feed_dict={input_z: example_z})
images_grid = helper.images_square_grid(samples, image_mode)
pyplot.imshow(images_grid, cmap=cmap)
pyplot.show()
Implement train
to build and train the GANs. Use the following functions you implemented:
model_inputs(image_width, image_height, image_channels, z_dim)
model_loss(input_real, input_z, out_channel_dim)
model_opt(d_loss, g_loss, learning_rate, beta1)
Use the show_generator_output
to show generator
output while you train. Running show_generator_output
for every batch will drastically increase training time and increase the size of the notebook. It's recommended to print the generator
output every 100 batches.
def train(epoch_count, batch_size, z_dim, learning_rate, beta1, get_batches, data_shape, data_image_mode):
"""
Train the GAN
:param epoch_count: Number of epochs
:param batch_size: Batch Size
:param z_dim: Z dimension
:param learning_rate: Learning Rate
:param beta1: The exponential decay rate for the 1st moment in the optimizer
:param get_batches: Function to get batches
:param data_shape: Shape of the data
:param data_image_mode: The image mode to use for images ("RGB" or "L")
"""
input_real, input_z, learn_rate = model_inputs(data_shape[1], data_shape[2], data_shape[3], z_dim)
d_loss, g_loss = model_loss(input_real, input_z, data_shape[3])
d_opt, g_opt = model_opt(d_loss, g_loss, learning_rate, beta1)
losses = []
steps = 0
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
for epoch_i in range(epoch_count):
for batch_images in get_batches(batch_size):
steps += 1
batch_images = batch_images.reshape(batch_size, data_shape[1], data_shape[2], data_shape[3])
batch_images = batch_images*2
# Sample random noise for G
batch_z = np.random.uniform(-1, 1, size=(batch_size, z_dim))
# Run optimizers
_ = sess.run(d_opt, feed_dict={input_real: batch_images, input_z: batch_z, learn_rate:learning_rate })
_ = sess.run(g_opt, feed_dict={input_real: batch_images, input_z: batch_z, learn_rate:learning_rate})
_ = sess.run(g_opt, feed_dict={input_real: batch_images, input_z: batch_z, learn_rate:learning_rate})
if steps % 10 == 0:
# At the end of each epoch, get the losses and print them out
train_loss_d = d_loss.eval({input_z: batch_z, input_real: batch_images})
train_loss_g = g_loss.eval({input_z: batch_z})
print("Epoch {}/{}...".format(epoch_i+1, epoch_count, steps),
"Discriminator Loss: {:.4f}...".format(train_loss_d),
"Generator Loss: {:.4f}".format(train_loss_g))
# Save losses to view after training
losses.append((train_loss_d, train_loss_g))
if steps % 100 == 0:
show_generator_output(sess, 25, input_z, data_shape[3], data_image_mode)
Test your GANs architecture on MNIST. After 2 epochs, the GANs should be able to generate images that look like handwritten digits. Make sure the loss of the generator is lower than the loss of the discriminator or close to 0.
batch_size = 64
z_dim = 100
learning_rate = 0.0002
beta1 = 0.5
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 2
mnist_dataset = helper.Dataset('mnist', glob(os.path.join(data_dir, 'mnist/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, mnist_dataset.get_batches,
mnist_dataset.shape, mnist_dataset.image_mode)
Run your GANs on CelebA. It will take around 20 minutes on the average GPU to run one epoch. You can run the whole epoch or stop when it starts to generate realistic faces.
batch_size = 64
z_dim = 100
learning_rate = 0.0002
beta1 = 0.5
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1
celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
celeba_dataset.shape, celeba_dataset.image_mode)
When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as "dlnd_face_generation.ipynb" and save it as a HTML file under "File" -> "Download as". Include the "helper.py" and "problem_unittests.py" files in your submission.


I am a hands-on software engineering leader with over a decade of experience in Python, asynchronous programming and many years of experience doing continuous delivery, DevOps and SRE.
15+ years of experience in building large Python applications. 14+ years of building horizontally scalable software for SaaS.
Using my skills and experience to help out the communities dear to me, whether that be Internet, networking or audio/video.
I have fun playing golf, thinking and playing my way around challenging courses. I have played at Pebble Beach, Torrey Pines, Manele, Plantation course, The Belfry and many others around the world.


{{hostname}}.local API
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Compressed Macintosh resource data, as stored in resources with the "compressed" attribute.
Resource decompression is not documented by Apple. It is mostly used internally in System 7, some of Apple's own applications (such as ResEdit), and also by some third-party applications. Later versions of Classic Mac OS make less use of resource compression, but still support it fully for backwards compatibility. Carbon in Mac OS X no longer supports resource compression in any way.
The data of all compressed resources starts with a common header,
followed by the compressed data.
The data is decompressed using code in a 'dcmp'
resource.
Some decompressors used by Apple are included in the System file,
but applications can also include custom decompressors.
The header of the compressed data indicates the ID of the 'dcmp'
resource used to decompress the data,
along with some parameters for the decompressor.
This page hosts a formal specification of Compressed Macintosh resource using Kaitai Struct. This specification can be automatically translated into a variety of programming languages to get a parsing library.
<?php
// This is a generated file! Please edit source .ksy file and use kaitai-struct-compiler to rebuild
/**
* Compressed Macintosh resource data,
* as stored in resources with the "compressed" attribute.
*
* Resource decompression is not documented by Apple.
* It is mostly used internally in System 7,
* some of Apple's own applications (such as ResEdit),
* and also by some third-party applications.
* Later versions of Classic Mac OS make less use of resource compression,
* but still support it fully for backwards compatibility.
* Carbon in Mac OS X no longer supports resource compression in any way.
*
* The data of all compressed resources starts with a common header,
* followed by the compressed data.
* The data is decompressed using code in a `'dcmp'` resource.
* Some decompressors used by Apple are included in the System file,
* but applications can also include custom decompressors.
* The header of the compressed data indicates the ID of the `'dcmp'` resource used to decompress the data,
* along with some parameters for the decompressor.
*/
namespace {
class CompressedResource extends \Kaitai\Struct\Struct {
public function __construct(\Kaitai\Struct\Stream $_io, \Kaitai\Struct\Struct $_parent = null, \CompressedResource $_root = null) {
parent::__construct($_io, $_parent, $_root);
$this->_read();
}
private function _read() {
$this->_m_header = new \CompressedResource\Header($this->_io, $this, $this->_root);
$this->_m_compressedData = $this->_io->readBytesFull();
}
protected $_m_header;
protected $_m_compressedData;
/**
* The header of the compressed data.
*/
public function header() { return $this->_m_header; }
/**
* The compressed resource data.
*
* The format of this data is completely dependent on the decompressor and its parameters,
* as specified in the header.
* For details about the compressed data formats implemented by Apple's decompressors,
* see the specs in the resource_compression subdirectory.
*/
public function compressedData() { return $this->_m_compressedData; }
}
}
/**
* Compressed resource data header,
* as stored at the start of all compressed resources.
*/
namespace CompressedResource {
class Header extends \Kaitai\Struct\Struct {
public function __construct(\Kaitai\Struct\Stream $_io, \CompressedResource $_parent = null, \CompressedResource $_root = null) {
parent::__construct($_io, $_parent, $_root);
$this->_read();
}
private function _read() {
$this->_m_commonPart = new \CompressedResource\Header\CommonPart($this->_io, $this, $this->_root);
$this->_m__raw_typeSpecificPartRawWithIo = $this->_io->readBytes(($this->commonPart()->lenHeader() - 12));
$_io__raw_typeSpecificPartRawWithIo = new \Kaitai\Struct\Stream($this->_m__raw_typeSpecificPartRawWithIo);
$this->_m_typeSpecificPartRawWithIo = new \BytesWithIo($_io__raw_typeSpecificPartRawWithIo);
}
protected $_m_typeSpecificPartRaw;
/**
* The type-specific part of the header,
* as a raw byte array.
*/
public function typeSpecificPartRaw() {
if ($this->_m_typeSpecificPartRaw !== null)
return $this->_m_typeSpecificPartRaw;
$this->_m_typeSpecificPartRaw = $this->typeSpecificPartRawWithIo()->data();
return $this->_m_typeSpecificPartRaw;
}
protected $_m_typeSpecificPart;
/**
* The type-specific part of the header,
* parsed according to the type from the common part.
*/
public function typeSpecificPart() {
if ($this->_m_typeSpecificPart !== null)
return $this->_m_typeSpecificPart;
$io = $this->typeSpecificPartRawWithIo()->_io();
$_pos = $io->pos();
$io->seek(0);
switch ($this->commonPart()->headerType()) {
case 8:
$this->_m_typeSpecificPart = new \CompressedResource\Header\TypeSpecificPartType8($io, $this, $this->_root);
break;
case 9:
$this->_m_typeSpecificPart = new \CompressedResource\Header\TypeSpecificPartType9($io, $this, $this->_root);
break;
}
$io->seek($_pos);
return $this->_m_typeSpecificPart;
}
protected $_m_commonPart;
protected $_m_typeSpecificPartRawWithIo;
protected $_m__raw_typeSpecificPartRawWithIo;
/**
* The common part of the header.
* Among other things,
* this part contains the header type,
* which determines the format of the data in the type-specific part of the header.
*/
public function commonPart() { return $this->_m_commonPart; }
/**
* Use `type_specific_part_raw` instead,
* unless you need access to this field's `_io`.
*/
public function typeSpecificPartRawWithIo() { return $this->_m_typeSpecificPartRawWithIo; }
public function _raw_typeSpecificPartRawWithIo() { return $this->_m__raw_typeSpecificPartRawWithIo; }
}
}
/**
* The common part of a compressed resource data header.
* The format of this part is the same for all compressed resources.
*/
namespace CompressedResource\Header {
class CommonPart extends \Kaitai\Struct\Struct {
public function __construct(\Kaitai\Struct\Stream $_io, \CompressedResource\Header $_parent = null, \CompressedResource $_root = null) {
parent::__construct($_io, $_parent, $_root);
$this->_read();
}
private function _read() {
$this->_m_magic = $this->_io->readBytes(4);
if (!($this->magic() == "\xA8\x9F\x65\x72")) {
throw new \Kaitai\Struct\Error\ValidationNotEqualError("\xA8\x9F\x65\x72", $this->magic(), $this->_io(), "/types/header/types/common_part/seq/0");
}
$this->_m_lenHeader = $this->_io->readU2be();
if (!($this->lenHeader() == 18)) {
throw new \Kaitai\Struct\Error\ValidationNotEqualError(18, $this->lenHeader(), $this->_io(), "/types/header/types/common_part/seq/1");
}
$this->_m_headerType = $this->_io->readU1();
$this->_m_unknown = $this->_io->readU1();
if (!($this->unknown() == 1)) {
throw new \Kaitai\Struct\Error\ValidationNotEqualError(1, $this->unknown(), $this->_io(), "/types/header/types/common_part/seq/3");
}
$this->_m_lenDecompressed = $this->_io->readU4be();
}
protected $_m_magic;
protected $_m_lenHeader;
protected $_m_headerType;
protected $_m_unknown;
protected $_m_lenDecompressed;
/**
* The signature of all compressed resource data.
*
* When interpreted as MacRoman, this byte sequence decodes to `®üer`.
*/
public function magic() { return $this->_m_magic; }
/**
* The byte length of the entire header (common and type-specific parts).
*
* The meaning of this field is mostly a guess,
* as all known header types result in a total length of `0x12`.
*/
public function lenHeader() { return $this->_m_lenHeader; }
/**
* Type of the header.
* This determines the format of the data in the type-specific part of the header.
*
* The only known header type values are `8` and `9`.
*
* Every known decompressor is only compatible with one of the header types
* (but every header type is used by more than one decompressor).
* Apple's decompressors with IDs 0 and 1 use header type 8,
* and those with IDs 2 and 3 use header type 9.
*/
public function headerType() { return $this->_m_headerType; }
/**
* The meaning of this field is not known.
* It has the value `0x01` in all known compressed resources.
*/
public function unknown() { return $this->_m_unknown; }
/**
* The byte length of the data after decompression.
*/
public function lenDecompressed() { return $this->_m_lenDecompressed; }
}
}
/**
* The type-specific part of a compressed resource header with header type `8`.
*/
namespace CompressedResource\Header {
class TypeSpecificPartType8 extends \Kaitai\Struct\Struct {
public function __construct(\Kaitai\Struct\Stream $_io, \CompressedResource\Header $_parent = null, \CompressedResource $_root = null) {
parent::__construct($_io, $_parent, $_root);
$this->_read();
}
private function _read() {
$this->_m_workingBufferFractionalSize = $this->_io->readU1();
$this->_m_expansionBufferSize = $this->_io->readU1();
$this->_m_decompressorId = $this->_io->readS2be();
$this->_m_reserved = $this->_io->readU2be();
if (!($this->reserved() == 0)) {
throw new \Kaitai\Struct\Error\ValidationNotEqualError(0, $this->reserved(), $this->_io(), "/types/header/types/type_specific_part_type_8/seq/3");
}
}
protected $_m_workingBufferFractionalSize;
protected $_m_expansionBufferSize;
protected $_m_decompressorId;
protected $_m_reserved;
/**
* The ratio of the compressed data size to the uncompressed data size,
* times 256.
*
* This parameter affects the amount of memory allocated by the Resource Manager during decompression,
* but does not have a direct effect on the decompressor
* (except that it will misbehave if insufficient memory is provided).
* Alternative decompressors that decompress resources into a separate buffer rather than in-place can generally ignore this parameter.
*/
public function workingBufferFractionalSize() { return $this->_m_workingBufferFractionalSize; }
/**
* The maximum number of bytes that the compressed data might "grow" during decompression.
*
* This parameter affects the amount of memory allocated by the Resource Manager during decompression,
* but does not have a direct effect on the decompressor
* (except that it will misbehave if insufficient memory is provided).
* Alternative decompressors that decompress resources into a separate buffer rather than in-place can generally ignore this parameter.
*/
public function expansionBufferSize() { return $this->_m_expansionBufferSize; }
/**
* The ID of the `'dcmp'` resource that should be used to decompress this resource.
*/
public function decompressorId() { return $this->_m_decompressorId; }
/**
* The meaning of this field is not known.
* It has the value `0` in all known compressed resources,
* so it is most likely reserved.
*/
public function reserved() { return $this->_m_reserved; }
}
}
/**
* The type-specific part of a compressed resource header with header type `9`.
*/
namespace CompressedResource\Header {
class TypeSpecificPartType9 extends \Kaitai\Struct\Struct {
public function __construct(\Kaitai\Struct\Stream $_io, \CompressedResource\Header $_parent = null, \CompressedResource $_root = null) {
parent::__construct($_io, $_parent, $_root);
$this->_read();
}
private function _read() {
$this->_m_decompressorId = $this->_io->readS2be();
$this->_m__raw_decompressorSpecificParametersWithIo = $this->_io->readBytes(4);
$_io__raw_decompressorSpecificParametersWithIo = new \Kaitai\Struct\Stream($this->_m__raw_decompressorSpecificParametersWithIo);
$this->_m_decompressorSpecificParametersWithIo = new \BytesWithIo($_io__raw_decompressorSpecificParametersWithIo);
}
protected $_m_decompressorSpecificParameters;
/**
* Decompressor-specific parameters.
* The exact structure and meaning of this field is different for each decompressor.
*
* This field always has the same length,
* but decompressors don't always use the entirety of the field,
* so depending on the decompressor some parts of this field may be meaningless.
*/
public function decompressorSpecificParameters() {
if ($this->_m_decompressorSpecificParameters !== null)
return $this->_m_decompressorSpecificParameters;
$this->_m_decompressorSpecificParameters = $this->decompressorSpecificParametersWithIo()->data();
return $this->_m_decompressorSpecificParameters;
}
protected $_m_decompressorId;
protected $_m_decompressorSpecificParametersWithIo;
protected $_m__raw_decompressorSpecificParametersWithIo;
/**
* The ID of the `'dcmp'` resource that should be used to decompress this resource.
*/
public function decompressorId() { return $this->_m_decompressorId; }
/**
* Use `decompressor_specific_parameters` instead,
* unless you need access to this field's `_io`.
*/
public function decompressorSpecificParametersWithIo() { return $this->_m_decompressorSpecificParametersWithIo; }
public function _raw_decompressorSpecificParametersWithIo() { return $this->_m__raw_decompressorSpecificParametersWithIo; }
}
}


--- layout: default title: About ---
stuyCTF is an online jeopardy-style Capture the Flag competition where the objective is to solve problems to obtain "flags." Featuring problems that range from Binary and Web Exploitations to Reverse Engineering, Forensics, and Reconnaissance, stuyCTF is the ultimate high school CTF competition to get both new and veteran competitors excited about computer science and security. It serves as an excellent hands-on experience that is both rewarding and fun! For more information about the general idea of CTFs and this competition, please refer to our FAQ page.
Each team consists of 1-5 students who will work together to solve challenges. The final rankings will be decided on the basis of whichever team obtains the most points, where ties are settled in favor of the team that obtained the points first.
The competition begins on Saturday, April 11, 2015 at 10 AM and ends on Monday, April 20, 2015 at 10 PM. Both times are in EST.
Because this is the first year that we are hosting a CTF, we do not have any sponsors and have limited prizes. However, if you would like to sponsor, we would be happy to talk about how we can include your company!
Fun, educational experience, and bragging rights :D
This CTF was made by Danny Qiu, Chesley Tan, Ethan Cheng, Yicheng Wang, and Daniel Zabari, with moral support by Ishraq Bhuiyan and Richard Zhan.
If you have any questions, concerns, comments or just want to get in touch, please contact us at<EMAIL_ADDRESS>and we will respond as soon as possible.


fsn1
or nbg1-dc3
To obtain list of locations, you can use following curl command:
curl -H "Authorization: Bearer $API_TOKEN" https://api.hetzner.cloud/v1/locationsAPI documentation To obtain list of datacenters, you can use following curl command:
curl -H "Authorization: Bearer $API_TOKEN" https://api.hetzner.cloud/v1/datacentersAPI documentation


This Todo-App helps a user to generate a list of items/ tasks to be carried out, filter through, and delete list items from the log.
The app also gives the flexibility of marking each Todo Items as either active or completed, and display/filter corresponding Todo Items based on all, active or completed Todo list.
It also has a feature that clears all completed Todos from the list array.
The architecture of the application was built using plain JavaScript which is commonly referred to as Vanilla JavaScript.
The Todo App is built using the Model - View - Controller Architecture design.
The MVC pattern is a software design pattern commonly used for developing user interfaces that divides the related program logic into three interconnected elements. This pattern is used to separate application's concerns.
Model, View and the Controller are separate entities. The Controller serves as the intermidiary between the Model and the View, thereby making it the only entity that can interact with the both. See the picture below for more information.
The Todo App is made up of the following structure, which are:
Bug which not allows adding new todos to the list (simple typo bug).
bug:
Controller.prototype.adddItem
Solved:
Controller.prototype.addItem
Bug which may leads to potential conflict between duplicate IDs
bug:
for (var i = 0; i < 6; i++) {
newId +=charset.charAt(Math.floor(Math.random() * charset.length));
}
Solved:
var isUnique = false;
while (!isUnique){
for (var i = 0; i < 6; i++) {
newId +=charset.charAt(Math.floor(Math.random() * charset.length));
}
isUnique=true;
for(var i = 0; i < todos.length; i++){
if (todos[i].id == newId){
isUnique = false;
}
}
}
Missing id in input tag for toggle-all label which prevent toggle all todos to work properly.
Bug:
Fixed:
Console log displayed message when user delete todo (unnessesary code and console log).
items.forEach(function(item) {
if (item.id === id) {
console.log("Element with ID: " + id + " has been removed.");
})
});
The piece of code above was removed
The test for the project was written using Jasmine. Jasmine is a JavaScript Open Source Testing Framework.
Tests carried out in the Todo App are as follows:
Frame Rate: The main metric for measuring the performance of any animation is frames per second (FPS). Optimum User experience is achieved when animations run at 60 FPS.
First Contentful Paint: The First Contentful Paint (FCP) metric measures the time from when the page starts loading to when any part of the page's content is rendered on the screen. For this metric, "content" refers to text, images (including background images), svg elements, or non-white canvas elements.
Largest Contentful Paint: The (LCP) metric reports the render time of the largest image or text block visible within the viewport. A good user experience within the first 2.5 seconds when the page started to load.
Waterfall: This gives insight into the sorts of things the browser is doing as it runs your site or app.
Call Tree: The Call Tree tells which JavaScript functions the browser spent the most time in. By analyzing its results, one can find bottlenecks in one's code - places where the browser is spending a disproportionately large amount of time.
Flame Chart: The Flame Chart shows you the state of the JavaScript stack for your code at every millisecond during the performance profile.
| S/N | Pros | Cons |
|---|---|---|
| 1 | Short loading time | The functionality is limited |
| 2 | Low memory usage | Only local storage is used to store data |
| 3 | Short time of performing functionalities | - |
| 4 | Simple design | - |
| S/N | Pros | Cons |
|---|---|---|
| 1 | Ability to sort tasks | Long loading time |
| 2 | Ability to print list | High memory usage |
| 3 | User can create multiple list | Google ads significantly extend loading time |
| 4 | User can create categories | - |


---
layout: post
title: The correct way to read a text file in Python
date: '2013-11-22T02:02:00.001-08:00'
author: Gert Lombard
tags:
- python
modified_time: '2013-11-22T02:02:41.805-08:00'
blogger_id: tag:blogger.com,1999:blog-1583243090910089198.post-5406013279184113865
blogger_orig_url: http://www.lombard.me/2013/11/the-correct-way-to-read-text-file-in.html
---
When you search for examples of reading a file on the web, most examples you see show:
with open('file') as f:
text = f.read()
with open('file') as f:
for line in f:
yield line


home
projects
♥ gallery
♥ studio
sophia lin
i am sophia lin. i like to create new projects including my most recent collection of decorated eggs!
about me
sophia lin is awesome


|
BiriBiriBeat
An Arduboy Otoge/Rhythm Game
|
#include <rhythm_manager.h>
Public Attributes | |
| uint16_t | greats |
| uint16_t | goods |
| uint16_t | misses |
| uint16_t | combo |
| uint16_t | max_combo |
| uint32_t | total_score |
Definition at line 68 of file rhythm_manager.h.
| uint16_t scoreboard_t::combo |
Definition at line 73 of file rhythm_manager.h.
| uint16_t scoreboard_t::goods |
Definition at line 71 of file rhythm_manager.h.
| uint16_t scoreboard_t::greats |
Definition at line 70 of file rhythm_manager.h.
| uint16_t scoreboard_t::max_combo |
Definition at line 74 of file rhythm_manager.h.
| uint16_t scoreboard_t::misses |
Definition at line 72 of file rhythm_manager.h.
| uint32_t scoreboard_t::total_score |
Definition at line 75 of file rhythm_manager.h.


Saltwater, Freshwater
Various Breeds
Various Breeds, Exotic Varieties
Lizards, Turtles, Snakes
Exotic Varieties


--- layout: default group: "navigation" title: Executives permalink: /executives/ order: 2 ---
Our talented executive board consists of the eight dedicated community members listed below.
{% for exec in site.data.executives %} {% include exec_member.html exec=exec%} {% endfor %}


JavaScript Loup
Using JavaScript in Reduce in Looping Constructs
January 16, 2015
I'll have to admit, working in JavaScript after working in Ruby feels vulnerable. It's not just the syntax differs enough to give one pause before attempting to solve a problem. It's that the tools that come with Ruby, namely in the Enumerable class, are not available. The methods I've come to rely on or even think in, such as select, map, cycle or inject are not in the toolbox anymore. Let's step back and talk about looping in as a general technique in both JavaScript and Ruby. From there, we'll compare looping over collections. Even though we cannot get to all the methods in Ruby, we'll show that the JavaScript method of reduce can become a middle step to each of those particular methods.
Looping
Let's say we wanted to determine the average temperature for 2014. We'd have a large set of datapoints of the high temperature for each day across the globe. Now hopefully these would be compared to a set of datapoint taken from the same geographical locations. In Ruby and JavaScript, we'd keep those datapoints in a collection such as an Array. To take the average of the temperature in Ruby, we'd do something like this:
Notice that we don't have a 'for each' with an obvious iterator here. Instead we have an Enumerator method of reduce with the + symbol passed to it. We understand that there's an accumulator behind all of this. When we get to the last member of the collection we end up with the summed value. How does the typical approach look in JavaScript?
Let's talk about our gut reaction here to this section of JavaScript code. It's doing the same thing as the reduce statement above. However, notice a few extra rules of the road. First, we have to declare the variables and the function with the keyword var in JavaScript. Not so in Ruby. Next, we end the line with a semi-colon. Ruby instead recognizes the end of the line. Lastly, JavaScript requires the console.log() object and method in order to see something. We are used to using 'p' or 'print' or 'puts' in Ruby to hear back from our code. JavaScript requires console.log(show-me-something).
JavaScript Reduce
Let's consider the use of the reduce funcion as a gateway to re-writing all of these loops without the for i++ technique. Here's an alternative to the sum method above.
We still visit every member of our collection. We rely on our total variable set to an initial value of 0 and then end up with our final value. In other words, we've reduced our entire collection to a single value. In fact, many of our other useful missing Enumerable functions in Ruby can be thought of (and even re-written) using the reduce method in JavaScript. Max, Min are obvious examples. Map, collect and select can be thougt of as returning something new as a result of visting the collection. Check out Aldo's blog at AirPair on the JavaScript reduce function and map.


General election: Child killers to be locked up for life under Tory plans for tougher sentences
Courts currently hand out life sentences but most murderers do not serve the rest of their lives in prison. Instead they are eligible for parole at the end of the minimum tariff set by a sentencing judge
by Ben Glaze, https://www.facebook.com/MirrorPoliticsChild killers will be locked up for life under plans outlined by the Government.
The Tories pledged to end the system which sees murderers of youngsters become eligible for parole after they have served the minimum tariff set by a sentencing judge.
While courts are duty-bound to set mandatory life terms, most murderers do not serve the rest of their lives behind bars.
However, under the shake up planned by Boris Johnson , adults who commit pre-meditated child murder will remain in jail until they die, with no chance of release.
Justice Secretary Robert Buckland, a former crown court judge, said: “There can be no more sickening injustice than that of heartbroken parents watching the killer of their child walk free.
“That’s why under a Conservative majority Government the law will be rewritten to be absolutely clear: any murderer who denies a young, innocent child the right to life surrenders their own right to liberty.
“They do so permanently, and they do so without exception.
“There is nothing we can do to take away the pain of the families of murdered children so we must do everything in our power not to compound it.”


---
layout: definitions
---
For $v_1, \dots, v_n\in\mathbb{R}^n$, let the determinant of $v_1, \dots, v_n$ be defined as the signed volume of a parallelpiped formed with $v_1, \dots, v_n$ ie. $\text{det}(v_1, \dots, v_n)=\text{signed volume of }P(v_1, \dots, v_n)$, where
$P(v_1, \dots, v_n)=\{\alpha_1 v_1 + \dots + \alpha_n v_n: \alpha_1\in [0, 1]\}$. The convension is that for $v_1$ to $v_2$ where we go clockwise, the volume is positive and negative volume otherwise.
For a matrix $A\in M_n(P_n)$ with columns $v_1, \dots, v_n\in\mathbb{R}^n$, we define $\text{det} A=\text{det}(v_1, \dots, v_n)$
Concepts
In two dimension, two vectors can determine a parallelogram. In general for $n$ dimensions, $n$ vectors can determine a parallelpiped.
For the determinant, we are interested in the volume of the parallelpiped.
There are four basic properties of a determinant we want to cover.
-
The determinant detects linear independence. That is, the determinant of a set is nonzero if and only if the set is linearly independent
-
Antisymmetry. That is, $\text{det}(v_1, \dots, v_n)=-\text{det}(v_n, \dots, v_1)$
-
Multilinearity. That is, if we fix all variables except the first, we can express the determinant as a sum of two separate determinants with each of the first terms and so $\text{det}(v_1+v_1', \dots, v_n)=\text{det}(v_1, \dots, v_n)+\text{det}(v_1', \dots, v_n)$.
-
Normalized. That is, for unit vectors $e_1$, we have $\text{det}(e_1, \dots, e_n)=1$
For calculating the determinant, let
$$\begin{align*}
A=\begin{bmatrix}a_1 & 0 & \dots & 0 \\
0 & a_2 & \dots & 0 \\
\vdots & \vdots &\ddots & \vdots \\
0 & 0 & \dots & a_n
\end{bmatrix}.
\end{align*}$$
Then
$$\begin{align*}
\text{det}(A)&=a_1\begin{bmatrix}1 & 0 & \dots & 0 \\ 0 & a_2 & \dots & 0 \\
\vdots & \vdots & \ddots & \vdots \\
0 & 0 & \dots & a_n\end{bmatrix}\\
&=a_1a_2\begin{bmatrix}1 & 0 & \dots & 0\\
0 & 1 & \dots & 0 \\
\vdots & \vdots &\ddots & \vdots \\
0 & 0 & \dots & a_n
\end{bmatrix}\\
&=a_1\dots a_n\begin{bmatrix}1 & 0 & \dots & 0 \\
0 & 1 & \dots & 0\\
\vdots & \vdots & \ddots & \vdots \\
0 & 0 & \dots & 1 \end{bmatrix}
\end{align*}$$
Note that for an upper triangular matrix if $a_{ii}=0$ for some $i$, then $A$ is not invertible, so $\text{det }A=0$
Recall that for elementary column operations, if we multiple one column by $\alpha$, then the determinant gets multiplied by $\alpha$. If we swap two columns, the determinant gets multiplied by $-1$, and adding scalar multiples of columns does not affect the determinant. Using this, we can create a formula to calculate the determinant.
Another method to calculate determinants is using
cofactor expansion.
Used In
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Hypothesis
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Results
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Diego borrowed money at a 15% interest rate for 5 years, compounded daily. If they had to pay back $3000, how much did they borrow originally?


Air Canada faces online backlash over new booking system
by BNN BloombergAir Canada has a new booking system, and some of its customers aren’t happy with it.
As of Friday morning, some customers were still reporting issues on social media with booking flights or modifying existing reservations following a migration to a new system on Tuesday.
In a tweet early Friday, Air Canada said “the situation is being monitored closely” and assured the issues would be fixed.
The airline warned customers last Monday they would not be able to make or modify reservations as of 8 p.m. until the middle of the next day while the migration to the new system was taking place. But customers were reporting issues throughout the week.
On its website last Tuesday, Air Canada said it’s “business as usual” with the new reservation system in place. However, the airline did acknowledge it was experiencing some technical issues related to the migration on Friday.
“As with any IT project of this magnitude and complexity, some temporary issues are inevitable and we are working hard to resolve these as quickly as possible,” a spokesperson for Air Canada said in an emailed statement to BNN Bloomberg.
“In a relatively small number of cases, some customers are unfortunately encountering technical issues and, at times, longer call center wait times, Overall, however, the new system is functioning as expected”
The airline added it has continued to operate its schedule normally despite the issues with its booking system.


Box Modifiers
There's a couple of classes that help you add certain styles like borders to block elements, rounded edges and shadows in various directions.
Borders
border
The border class adds a very light border to your elements.
There are classes that add a border to a specific side. Notice that because of the Right To Left support, what you might be used to calling left is now start and what was formerly known as right is now called end.
There is also a set of classes that deletes the borders from a specific side. It assumes that these sides have already been assigned borders.
You can add more than one of these classes to add or delete specific borders to different sides.
Contextual Borders
border-{COL}
- COL:
primary
secondary
success
danger
warning
info
light
dark
white
- COL:
Border Width
border-{NUM}
- NUM:
1
2
3
4
5
- NUM:
There are a few sizes for borders from 1 to 5 pixels. By the way, border-1
happens to be the same size as just border. You can also combine these with the contextual colors or sizes, but they will affect all of the borders in the current element.
Border Radius
top
end
bottom
start
circle
pill
Radius Sizes
rounded-{NUM}
- NUM:
0
1
2
3
- NUM:
If you want a little better control over the roundness of the edges you can use these sizes right here. rounded-0
is the same as not adding rounded
, rounded-1
is slightly smaller roundness than just using the rounded
class and rounded-3
is slightly bigger.
Shadows
shadow{-SIZ}
- SIZ:
none
sm
lg
- SIZ:
There are four shadow classes. You can just use the shadown keyword or add a modifier.
The none keyword is an override and we can use it to turn the shadow off an existing element.
There is a small shadown and a large shadow. The regular shadow is in between these.


The Federation of Children’s Book Groups (FCBG) are celebrating National Non-Fiction November this month. They’ve worked with bookseller Marilyn Brocklehurst and adult and child FCGB members to compile a leaflet of 100 brilliant non-fiction books for children and young people (PDF).
We have listed a selection of these books you can borrow from Suffolk libraries, covering the topics of the natural world, animals, science and geography. We also have a list of books on history, English and general knowledge.
The Natural World
Dianna Hutts Aston and Sylvia Long - A Rock is Lively
This book introduces children to the beauty and science of rocks with beautiful illustrations and a picture of poetic language and straight facts.
Christiane Dorion and Beverley Young - How We Make Stuff: the story behind our everyday things
This book uses pop-ups, pull-tabs and booklets to explain to children how we use Earth’s natural resources to make everyday items such as clothing, mobile phones, paper and food. It aims to answer many of the questions children ask, and teaches them about sustainable living in an engaging way; for example, there is a pull-flap refrigerator door behind which are the six types of plastic containers we use, and a pull-tab showing what happens to plastics that are not recycled.
Joanna Readman and Ley Honor Roberts - The World Came To My Place Today
In a similar vein, in this book, George’s grandpa comes to look after him and his sister for the day, bearing a globe. He explains how everything they use - for example, chocolate, rubber, cereal and wood - comes from plants all over the world.
Tracey Turner - Lost… in the Jungle of Doom
A choose-your-own-story adventure where the reader has to survive the dangers of the Amazon Rainforest by paying attention to facts and information in order to choose the right path. Defeat ferocious jaguars, terrifying black caiman and deadly dehydration to make it out alive.
Alice James, Emily Bone and Briony May Smith - The Usborne Outdoor Book
The weather may have turned, but there are still plenty of reasons to get outside and enjoy the outdoors, be it in the form of the woods, the local park, or the back garden. This book guides children in what they can do and find by ponds, rivers and the sea, in the woods, and in different weather conditions.
Animals
Jess French and Jonathan Woodward - Fluttering Minibeast Adventures
Vet and Cbeebies presenter Jess French encourages children to go moth searching, pond searching and butterfly feeding with lots of pictures in vibrant colours. She explains how caterpillars change into beautiful butterflies, where to find baby dragonflies and how to identify bugs.
 Your child can get a real sense of their size, as all the bugs in the book are presented at their actual size. They can also learn about the biggest swarms and colonies, the deadliest bugs, and the bugs that are best at camouflage.
Camilla de la Bédoyère and Mel Howells - Would You Rather… dine with a dung beetle or lunch with a maggot?
Continuing the bug theme, this book reveals the revolting eating habits of bugs and gives readers choices of what they would prefer to eat, where they would rather live, and what super senses they would rather have.
Owen Davey - Mad About Monkeys
If your child prefers their wildlife on the larger side, they can learn about the differences and similarities of many different types of monkeys from this book. They can find out about monkey intelligence, behaviour and movement and where they live. The stylish illustrations and semi-irreverent tone mean that adults can also enjoy this book.
Nicola Davies and Luciano Lozano - I Don’t Like Snakes
Like many people, the little girl in this book doesn’t like slithery, slimy, scaly snakes. Over the course of the book she learns several facts about snakes from her snake-loving family. She comes to change her mind - and perhaps your snake-fearing child will, too!
Science
Katie Daynes and Christine Pym - What Makes it Rain?
Young children can lift the flaps in this book to find out not only what makes it rain, but how rainbows appear, why lightning flashes, where wind comes from and why it is colder in winter. They can also find surprising facts and weather forecasting tips.
Jason Chin - Gravity
Using captivating paintings and few words, this book succeeds in teaching young readers how gravity stops objects from floating out of our hands, keeps our feet on the ground, and stops everything from rising up into space.
Louie Stowell, Roger Simó, Adam Larkum and Jamie Ball - The Usborne Official Astronaut's Handbook
This book, which features a foreword from ESA astronaut Tim Peake, the first British astronaut to embark on a mission to the International Space Station, teaches children about the training astronauts undertake, how they travel into space, and what they do there.
Catherine Barr, Steve Williams and Amy Husband - The Story of Life: a first book about evolution
This book takes young children from the first living cell, to jellyfish and worms, to fish with bendy necks which drag themselves out of the water into swampy forests, to dinosaurs, to hairy mammals who stand on two legs. The story includes dramatic events such as ice ages and volcanic eruptions. Subtle humour adds to the entertainment.
Geography
Aleksandra Mizielińska and Daniel Mizieliński - Maps
Lavishly-drawn illustrations of maps featuring borders, cities, rivers, peaks, places of historical and cultural interest, eminent personalities, iconic animals and plants, cultural events and much more.
Anita Ganeri and Mike Phillips - Horrible Geography: Wicked World Tour
In typical Horrible style, with this book children can take a grisly whistle-stop tour around the globe, taking in perishing poles, desperate deserts, stormy weather and earth-shattering earthquakes.
David J. Smith - If The World Were A Village
This book helps young readers wrap their minds around the huge numbers that make up the world by shrinking them to fit a village of just 100 people. For example, of the 100, 22 can speak a Chinese dialect, just 9 can speak English, and 17 cannot read or write. By learning about these, as well as the variations in the village’s religions, education and standard of living, children can gain an increased awareness of the world around them.
Mick Webb - The Book of Languages: speak your way around the world
If your child wants to learn a language but isn’t sure which one, this book features basic vocabulary and short dialogues in a variety of different tongues, as well as facts about where different languages are spoken, and information on Morse code, sign language and whale song.
William Grill - Shackleton’s Journey
A unique illustrated narrative of Ernest Shackleton’s landmark 1914 expedition across the Antarctic from pole to pole. Readers can learn about the crew members, dogs, the ship Endurance, equipment, maps, and everything that happened on the expedition.


WITNESS LIST Human Services Committee January 29, 2004-10:00A CPS On: Kromrei, Liz (TX Dept. of Protective and Regulatory Services) HHSC On: Berndt, Trey (Health and Human Services Commission) Hawkins, Albert (Health and Human Services Commission)


General Zoltan Interface FunctionsExamples of the calling sequences for initialization, load-balancing, and data migration are included in the Initialization, Load-Balancing, and Migration sections, respectively, of the Examples of Library Usage.
Load-Balancing Interface Functions
Functions for Augmenting a Decomposition
Migration Interface Functions
Graph Coloring Functions
Graph Ordering Functions
Note: Robust error handling in parallel has not yet been achieved
in Zoltan. When a processor returns from Zoltan due to an error condition,
other processors do not necessarily return the same condition. In
fact, other processors may not know that the original processor has returned
from Zoltan, and may wait indefinitely in a communication routine (e.g.,
waiting for a message from the original processor that is not sent due
to the error condition). The parallel error-handling capabilities
of Zoltan will be improved in future releases.
| C and Fortran | C++ | |
|---|---|---|
| Partitioning and migration functions example: perform partitioning example: assign a point to a part |
Zoltan_LB_function() Zoltan_LB_Partition() Zoltan_LB_Point_Assign() |
Zoltan::function() Zoltan::LB_Partition() Zoltan::LB_Point_Assign() |
| Unstructured communication example: perform communication |
Zoltan_Comm_function Zoltan_Comm_Do() |
Zoltan_Comm::function Zoltan_Comm::Do() |
| Distributed data example: find objects in a remote process |
Zoltan_DD_function Zoltan_DD_Find() |
Zoltan_DD::function Zoltan_DD::Find() |
| Timers example: print timing results |
Zoltan_Timer_function Zoltan_Timer_Print() |
Zoltan_Timer::function Zoltan_Timer::Print() |
In particular, the C++ Zoltan class represents a load balancing instance and the methods that operate on it. The method name is identical to the part of the C and Fortran function name that indicates the function performed.  Their method names are derived similarly.


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Akan names come from a traditional naming system for people from countries such as Togo, Ivory Coast and Ghana.
A child’s name is determined by factors surrounding his or her birth.
For example, the day of their birth or the manner in which they were born may determine which name they get irrespective of their gender.
These Akan names signify the day one is born.
According to Akan tradition, each child is born with a name associated to their soul.
Would you love to know your Akan name, and the day you were born??
please insert your Birthday and gender and lets play..


Cornell University ChemE Car is a project team in which students of all majors work together to build several model cars purely powered and stopped by chemical reactions. After months of design, construction and careful calibrations, we compete each spring at the AIChE Northeast Regional Conference, where if successful, we move on to the National Conference the following fall. If you have any questions about the team, including media inquiries and applications, feel free to contact us at<EMAIL_ADDRESS>Cornell University ChemE Car is a student-run project team of approximately fifty members. Since it started in 2004, the team has won first place in the AIChE Regional and National Conferences several times, with the team most recently obtaining their fourth national title (an all-time record) at the 2015 AIChE National Conference.
ChemE Car is one of several stellar opportunities Cornell students have to apply the theoretical principles they learn in class to real-life situations. All members work in smaller sub-teams to design and execute a specific aspect of the vehicle. Following months of design, construction, and calibration, all these parts are put together to make the final car. The goal of each car is to carry a certain load over a given distance. Because the constraints (distance to travel, load to carry) are declared during the competition, our cars are designed to be quite flexible.
You can read more about our extensive history here.
Our members are split into power teams, support teams, and administrative teams. The power teams include Battery, Fuel Cell, Pressure, Biological Systems, and Thermo-Electric Generation; they are responsible for designing a new mechanism to power the car each year. To build the chassis, set up the electronics, and design a stopping mechanism, we have three support teams: Mechanical, Electronics, and Potions. Finally, to make sure everything between the teams and outside of the team runs smoothly, ChemE Car has Safety and Business teams in addition to a senior and junior standing captains, and a treasurer. Members are assigned to a specific sub-team during recruitment, but as our members know, there is no such thing as strictly being a sub-team member: due to the nature of our goal, each member will have to work with several sub-teams. Some of our members even belong to multiple sub-teams.
11/8/15 - ChemE Car's Battery Car, Drifter, sucessfully placed 1st at AIChE Nationals competitions, winning our 4th title.
9/18/15 - ChemE Car is proud to announce that our Battery Car, Drifter is going to Salt Lake City, UT for our Nationals competition.
8/27/15 - ChemE Car is now recruiting for the Fall Semester! Applications are due September 10th at 11:59 PM!
3/11/15 - Regionals are over! Battery came in 1st and Fuel Cell came in 3rd!
2/25/15 - Calibrations for Regionals are underway!
2/18/15 - ChemE Car welcomes our newest members for the spring semester.
Cornell University ChemE Car is a student-run project team of approximately fifty members with the goal to build model cars entirely operated by chemical reactions. Since it started in 2004, the team has won first place in the AIChE Regional and National Conferences several times, and is currently preparing for the Northeast Regional Conference that will be held in the coming spring.
ChemE Car is one of several stellar opportunities Cornell students have to apply the theoretical principles they learn in class to real-life situations. All members work in smaller sub-teams to design and execute a specific aspect of the car. Following months of design, construction, and calibration, all these parts are put together to make the final car. The goal of each car is to carry a certain load over a given distance. Because the constraints (distance to travel, load to carry) are declared during the competition, our cars are designed to be quite flexible.
You can read more about our sponsorship program here.


Diane Rehm on Education Reform
Today during my plan period I happened to see a tweet from @ThalesDream about today’s Diane Rehm Show being focused on charter schools and education reform. I like the show and I feel like most of the time, it is balanced and includes many experts and good commentary.
Not today.
I was (I hope) one of the public teachers across the country that was trying to call in and e mail about the current state of education and the true effect charters and vouchers are having on education in America. It was heartbreaking to hear an unbalanced, one-sided explanation of charter schools in American education. I’ve tried to break my thoughts down into three parts.
- Charter schools are not the solution to the American education problems. Charters are being heralded as the golden bullet for education with stories of soaring test scores and student achievement. Let me say that there are good charter schools out there. There are schools that are using innovative methods to teach every child and to teach those children that need different challenges to learn. I am not against the idea. What really irks me is that charters are never put in a bad light. There are stories of schools that raise scores on tests by kicking the low-performers out. Artificially raising grades is a disservice to students and parents and is probably the lowest form of education, if you ask me. If you are funded by public funds, you must be public! Test scores cannot be the basis for admittance and retention. Charters were designed to give different opportunities…but not for limited times.
- Teachers do not have absolute job security with no evaluation process. With the changing economy, I hear this more and more, and it made me extremely sad to hear it again this morning with no rebuttal. I am evaluated every year. It isn’t a union thing. If I am not performing my job as required, I will be fired. Teachers are under just as much pressure to perform to the best of their ability as much as the next guy. There are limited situations where teachers “are completely safe, even though they are terrible.” But, that is a very narrow window in the public education system. States are evaluating teachers in a variety of ways, one of which (unfortunately) is leaning more and more on student test scores. We are evaluated. We do not have absolute security.
- Education and corporations are not the same and cannot be treated the same. Education management has been shifting more and more toward a corporate model under the guise of “no-nonsense management” to improve schools. The problem is that corporate goals and education goals are on opposite ends of the spectrum. Corporations deliver products for profits. Education is trying to produce learners that are independent and dynamic. If we begin to produce products that think, talk, and work the same, our society is going to be even farther behind globally than we already are. Schools need good management but from professionals that are educators. Not former CEO’s that took their companies to the Fortune 500 level. The goals are different and until that is realized, education will continue to struggle.
I know this is more of a rant, but I was really concerned about the discussion.
The author being interviewed, Steven Brill, has spent time in schools as an observer…not a teacher. Without proper perspective, education will continue to be skewed.
You can go listen to the segment
here. I really encourage you to
send an e mail to Diane about the episode and your thoughts as a teacher. This is an issue teachers need to speak up on in order to show that we are here working our hardest to continue to provide students with a quality, dynamic, and meaningful education.
Written on
August
16th,
2011
by
Brian Bennett
Categorized in:
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---
layout: portal
category: reject
tags: reject
id: 113
imgurl: https://lh4.ggpht.com/qAO-mm18YmQ8pVai0ejqoBMQU0ivpJGZpfETED8TOQ3Su6gviV5yf3eOEqk9rBeW6g1-Zrbe5bPBcJLQ-P7dKg
portalname: 天使
sentdate: Thu Apr 16 17:39:18 JST 2015
title: 113 - 天使
---
From: Ingress Operations<EMAIL_ADDRESS>Date: 2015-04-16 13:44 GMT+09:00
Subject: Ingress Portal Rejected: 天使
To: **
Thank you for your Portal submission. However, this Portal candidate does not meet the criteria required for approval.
Please refer to New Portal Submission criteria at our Help Center for further information.


Task 1: Numbers
Write a script that prints all the numbers from 1 to N.
"N" number:
Print
Task 2: Numbers not divisible
Write a script that prints all the numbers from 1 to N, that are not divisible by 3 and 7 at the same time.
"N" number:
Print
Task 3: Min/Max of sequence
Write a script that finds the max and min number from a sequence of numbers(divide them using a space).
Numbers:
Find
Task 4: Lexicographically smallest
Write a script that finds the lexicographically smallest and largest property in document, window and navigator objects.
Find
Result Task 1:
Result Task 2:
Result Task 3:


.prettydiffrc file
Purpose of this file
This file allows users to save option configurations for the Pretty Diff tool. The file is run automatically when Pretty Diff is run as a Node.js application using its Node interface file, api/node-local.js.
Order of operations
Pretty Diff accepts options in various different ways. The first thing Pretty Diff looks for is if options are passed directly to the application, which can occur from another application or directly from the command line. The .prettdiffrc file is evaluated only after externally supplied options are evaluated. Each option has a default type and value that is applied if no other value is supplied. Finally, Pretty Diff accepts an option comment from the source file as the final and most dominate means of defining option values. This order of operations allows Pretty Diff to interpret options in the .prettydiffrc file conditionally in regards to certain other options.
Supported formats
The primary supported format is JSON. Simply supply JSON data containing the options to change and their intended values.
If the file is not JSON format the Pretty Diff's Node interface will evaluate the file as a JavaScript application using the supplied format. This is a more complex approach, but allows users to define options conditionally. This can be helpful if users wish to define one set of options a given language and another set of options for a different language, mode, or other combination of features.
File location
Pretty Diff will attempt to search for the file in two locations. The primary location is the current local directory of the executing application or user's command prompt. If Pretty Diff is installed both locally and globally the local configuration has dominance provided the command prompt is at that location.
If the .prettydiffrc file is not available at the user's locally active directory the application's local directory is searched.


{header_style# } {header_scripts# }
I'm sorry, but this XMPP client application won't work without JavaScript.
Perhaps you would like to try one of these clients:
More clients...


{% extends "base.html" %} {% block title %}Codenamer AI{% endblock %} {% block content %}
Instructions
Enter space-separated words into word categories or use randomly generated words. Hints may have common root parts with the given words.
Hint quality feedback
I am collecting data to fine-tune the system. You can vote on the matches in the lower form: Mark all the words you think you would match hearing that hint (including enemy and killer words). Select just "BAD" if the hint is completely unusable. A row with no marks (not even "BAD") will be ignored. You may add a new hint you find missing (and its matches) to the first line.
Entering a nick may help me with the data analysis, but is optional. I promise not to publish the nicks. I will publish the collected words and matches, anonymized, most likely under Creative Commons licence.
For a more efficient way to generate matching data, see here.
Source at [github]


| Overview |
Module |
Use |
Devguide |
Index |
:: com :: sun :: star :: form ::
|
| module runtime |
- Description
- collects functionality needed during a form's runtime, e.g.
when it is active and interacts with the user.
|
| Services |
| FormController |
specifies a component controlling the interaction between the user and multiple
form controls belonging to a single form.
|
| FormOperations |
encapsulates operations on a database form which has a UI representation,
and is interacting with the user.
|
| Structs |
| FeatureState |
encapsulates the state of a FormFeature
|
| FilterEvent |
is an event fired by a filter controller, when the filter managed by the controller changes.
|
Top of Page
Copyright © 2013, The Apache Software Foundation, Licensed under the Apache License, Version 2.0. Apache, the Apache feather logo, Apache OpenOffice and OpenOffice.org are trademarks of The Apache Software Foundation. Other names may be trademarks of their respective owners.


prepare_regression_table.Rd
Builds a regression table based on a set of user-specified models or a single model and a partitioning variable.
prepare_regression_table( df, dvs, idvs, feffects = rep("", length(dvs)), clusters = rep("", length(dvs)), models = rep("auto", length(dvs)), byvar = "", format = "html" )
| df | Data frame containing the data to estimate the models on. |
|---|---|
| dvs | A character vector containing the variable names for the dependent variable(s). |
| idvs | A character vector or a a list of character vectors containing the variable names of the independent variables. |
| feffects | A character vector or a a list of character vectors containing the variable names of the fixed effects. |
| clusters | A character vector or a a list of character vectors containing the variable names of the cluster variables. |
| models | A character vector indicating the model types to be estimated ('ols', 'logit', or 'auto') |
| byvar | A factorial variable to estimate the model on (only possible if only one model is being estimated). |
| format | A character scalar that is passed on |
A list containing two items
A list containing the model results and by values if appropriate
The output of stargazer
containing the table
This is a wrapper function calling the stargazer package. For numeric
dependent variables the models are estimated using lm
for models without and plm
for models with fixed
effects. Binary dependent variable models are estimated using
glm
(with family = binomial(link="logit")
).
You can override this behavior by specifying the model with the
models
parameter. Multinomial logit models are not supported.
Clustered standard errors are estimated using plm
's robust
covariance matrix estimators for OLS and
cluster.vcov
for logit models.
Only up to two dimensions are supported for fixed effects and standard
error clusters need to be also present as fixed effects.


my stack
As I come from a maker culture, influenced by friends who code better than they speak and consider it rude if a person is not respecting the system of machines they own /1 1/ One can draw parallels with Indian professional practices. I wish to remember વિશ્વકર્મા. Every year on વિશ્વકર્મા જયંતી, all the craftsmen, all the engineers, all the ironsmiths, all the carpenters, all the masons, and everyone is even remotely associated with making, engineering, fabricating or even operating machines, workship their machines. I find this practice similar to that
While some have critiqued that a practice of describing their workplace is a way of showing off geekiness, I acknowledge that. I understant that. But then, some show muscles, some show books, some show their love towards their hard earned machines. I agree that this flaunt also turns highly specific and turns into bragging, I am aware of such system descriptions on websites. I also hear that it is a way to show your understanding your machine and that tells a lot about you. So, I will not only describe my systems, but also tell reasons about my choices.
Thinkpad fangirling…
Ever since I came to know about thinkpads from a very good friend, I have not purchased any other machine. I currently own an refurbished /2 2/ I have been buying and encouraging people to buy refurbished thinkpads since 2016 now. The reason they are available in the refurbished market is because of their build quality. Everything is modular and one can just make a new thinkpad by combining several thinkpads. It also reduces the electronic waste at an individual level. Needs are met, laptops run for a good 6-7 years without creating any troubles at a desirable speeds (my E431 running Ubuntu has boot time comparable to a macbook, thanks to FOSS contributors). X1 Carbon (6th generation) with 8GB RAM and practically useable 128GB SSD. I use this when I am working away from my station. It is lightweight pretty mobile. The only limitation I find with X1 is its lack of modularity, everything is soldered. And things are not replaceable like in the X2x0 series. But for the time being, I am all good.
My work station is a thinkpad E431 customised with 1GB of NVidia GEforce 7040 GPU (working on replacing it with a 4GB GPU, suggestions?) juiced up with 12GB RAM, a 256 GB SSD, and a 1TB HDD. The display is extended by ACER Nitro 144Hz Gaming monitor and a Perixx Periboard 512 Ergonomic keyboard. Apart from Ubuntu, the machine hosts Windows 10 through the optical drive for doing qualitative analysis at times.
Workflow
As a design researcher, I use qualitative and quantitative methods. To maintain a coherence in references across devices and OSes, I used to use Zotero, but now I use Mendeley. I am planning to switch back to Zotero with digital Ocean and Zot files to overcome the 300 MB storage limit. Thanks to Matthias for suggesting this. For notes, and memos, writings, I used to use Notion, but now I use VS Code + Foam Bubble. Thanks to Rohit and Rishabh for suggesting it. I have an LaTeXware running on my machine, but I use Overleaf for most of the typesetting and editing of papers.
Everybody has a habit of annotating papers while they read. I find Okular a good pdf reader when it comes to annotations. I use that as a default pdf reader along with some cloud syncing service like dropbox, mendeley, and digial ocean for different purposes. To extract annotations from different pdf files, I use a python script that extracts and arranges them neatly in a .csv or a .txt or an .md file which makes life a lot easier when you’re using .md based note taking tools like notion or foam bubble.
Reading and everyday tasks
Pen and Paper, although they are THE mode of thinking, I try to reduce my paper usage wherever I can. I used to own a kindle, but the major limitation I found was that I somehow cannot remember things on a kindle. I need information anchored to a page number and fluidity does not help my reading practice. To sort that, I use okular with Golden Dict and wordNet.
I use GS connect Gnome shell implementation of KDE connect configured to send select notifications to my unity desktop. This reduced my anxiety and allows me to work distraction free. Also, it helps in transferring files over TCP/IP and controlling media while watching movies.
Clothes around keyboards are to protect them from dust. I love my keyboards (perixx and thinkpad keyboards), I love dustiness of Mumbai and Gujarat as well /3 3/ Makes drinking water more satisfying . To love both, I have to use these clothes to protect my beloved peripherals.


Tyler Tafoya, Callan Fisher, Emily Randall, Andrew Krodinger
RideSki
Rides to ski resorts
Anyone who wants to go to the mountains
Anyone that meets certain criteria. I.e. good driving record, etc.
Driver name, Location, Departure/Return time, destination, route, cost, available seats
Boulder
Base rate per ski resort, affected by miles, surge pricing, and minutes
80%


{% extends "base.html" %} {% block page_title %}Mozilla Jobs — Error{% endblock %} {% block site_css %} {{ super() }} {{ css('careers') }} {% endblock %} {% block site_ie8 %} {{ super() }} {{ css('careers-ie8') }} {% endblock %} {% block content %} Sorry, but something went wrong! Sorry, but something went wrong on our end and we couldn't process your request. You can reload the page to try again, or check out all the listings for all careers at Mozilla. {% endblock %}
Sorry, but something went wrong on our end and we couldn't process your request. You can reload the page to try again, or check out all the listings for all careers at Mozilla.


This is designed to test onlytopic.in.map=true. If this file was generated from src/ then the test fails, and the generated content will not match this file.


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