Preparation time
less than 30 mins
Cooking time
1 to 2 hours
Serves
Serves 8-12
Take the shortcut to cheesecake heaven by using a readymade sponge base.
For the cheesecake, preheat the oven to 180C/350F/Gas 4.
Place the sponge base into the bottom of a 23cm/9in springform, loose-based cake tin.
Place the sugar, lemon juice and zest and cornflour into a bowl and whisk together.
Add the cream cheese and beat well. Crack in the eggs, one at a time, beating well between each addition. Add the vanilla seeds and mix well, then pour in the double cream and whisk until the mixture is smooth. Fold in the strawberries and white chocolate.
Pour the mixture into the cake tin and give the tin a light shake to evenly distribute the mixture.
Wrap the cake tin in a sheet of foil to make it waterproof, then place it into a roasting tin filled to a depth of about 0.5cm/¼in with water. Transfer to the oven and bake for 50 minutes, or until the top is lightly golden-brown and the cheesecake is just set. Remove from the oven and leave to cool in the tin, then keep in the fridge until ready to serve.
For the strawberry sauce, heat a frying pan until hot and place 250g/8oz of the strawberries into the pan. Stir-fry for one minute.
Stir in the lemon juice and icing sugar, to taste.
Pour the mixture into a blender and blend until smooth, then pass through a sieve, pressing with the back of a spoon, to remove all the seeds.
To serve, remove the cheesecake from the fridge, remove from the tin and place a slice onto a serving plate. Top with the sauce and some strawberries.


Monroe County Fair
The First Monroe County Fair was held in 1850 This
article was published in The Spirit of Democracy, Friday, October 26, 1984
Provided by Lena Kahrig Pettit
The Monroe County Fair has been a local attraction for one hundred eighteen
(118) years, which is a long time. The first fair was held in 1850 on the
grounds of the Monroe Academy near Woodsfield--believed to be in the area where
Ohio Street is now located. James R. Morris served as secretary of this fair.
The first fair was listed as a success and an award of $5.00
was made to Jacob Tschappat for the best gallon of grape wine. The names of the
judges were not given, the number of entries in this category were not given,
nor were the qualifications of the judges given.
Wine evidently was rated higher or more rare than oxen. A
pair of oxen, the prize winners, was only awarded a prize of $4.00. Showing
prize oxen were S. P. Jones, Robert Clingen, and Joel Yost.
Peter Witten showed the best stallion, winning $5.00, and
Israel D. Riley exhibited the best mule, being awarded $2.00.
Prizes which were typically awarded one hundred, eighteen
(118) years ago were as follows: Mrs. Robert Clingen received a prize of $1.00
for the best five pounds of butter, Mrs. B. P. Briggs was awarded a prize of
$1.00 for the best cheese, Mrs. F. Koehler was awarded a diploma for the best
wool carpet, and Mrs. M. M. Salisbury was awarded a prize of $1.00 for a pair
of blankets, - - W. R.
Click here for the Short-Cut Table of Contents


## 2018
**47 total posts** have been written on 2018.
There have been *26 different tags* used, the most
used popular being (in order of number of posts):
- *postgresql* (27 posts)
- *planet-postgresql-org* (20 posts)
- *itpug* (16 posts)
- *perl6* (9 posts)
- *git* (4 posts)
- *github* (3 posts)
- *python* (3 posts)
- *pgenv* (3 posts)
- *java* (3 posts)
- *perl5* (3 posts)
- *perl* (2 posts).
The following is overall post ratio on every 2018 month:


This example demonstrates how to use the HTML5 DeviceOrientation API to rotate through the hue values on a blinkM RGBLED module from a mobile device


Mazy Tic-Tac-Toe is a 2-player computer game played on a game board comprising nine tic-tac-toe games consisting of nine cells within a 3x3 big square. Thus, there are 81 cells, arranged in nine 3x3 big square within the board.
The objective of this game is to be the first to win tic-tac-toe game within any big square.
1. The first player may place an "X" in any cell within any big square of the board.
2. The selected cell position within this big square corresponds to the big square where the second player must then place an "O".
3. Thereafter, the two players take turns placing their mark in any unfilled cell within the big square dictated by the cell position marked by the previous player.
a. If a player is sent to a big square in which all the cells are already filled, then the player may next place his mark in any unfilled cell in any other big squares.
b. If you want to interrupt the current game or to start a new game you must press ESC or click "STOP THE GAME" beneath the game board.
c. The game mode "evolution" allows you to workout AI of your computer opponent. Just reach the population number about 300-400 to get the optimal computer AI.


Please tell me something about yourself, your schooling, your college and the kind of projects you have done during your education.


Hello, my name is Trevor George Wood, and this is my site for Digital Engineering and Fabrication. I am sixteen years old, and I'm from Chippewa Lake, Ohio. I am currently a sophomore at Western Reserve Academy. My favorite subject is Honors Chemistry. During the fall I play football and particapte in my echo "Racism in Sports". In the winter, I play basketball, and in the spring I play AAU basketball. In my free time I like hanging out with my friend Lee. The Migos are the best...


import re
import glob
import numpy as np
import os
import pandas as pd
import multiprocessing
import nltk
import gensim.models.word2vec as w2v
import seaborn as sns
import matplotlib.pyplot as plt
import pprint
import sklearn.manifold
import codecs
%matplotlib inline
book_paths= sorted(glob.glob('data/clean/*.txt'))
print('Found books : ',book_paths)
raw_corpus=u""
for book_path in book_paths:
print('Reading :', book_path)
with codecs.open(book_path,'r',encoding='utf-8') as book_file:
raw_corpus+= book_file.read()
print('corpus is now {0} characters long'.format(len(raw_corpus)))
print()
print(type(raw_corpus),len(raw_corpus),raw_corpus[:500])
##download modules form natural language toolkit nltk
nltk.download('punkt')
nltk.download('stopwords')
#loading the pretrained punkt model to build a tokenizer
tokenizer = nltk.data.load('tokenizers/punkt/english.pickle')
#conerting the raw_corpus into senences
raw_sentences = tokenizer.tokenize(raw_corpus)
#cleaning data a bit--- removing everything that isn't a letter like hyphens and shit
for raw_sentence in raw_sentences:
re.sub("[^a-zA-Z]", " ", raw_sentence)
print(raw_sentences[20:30])
print()
print(type(raw_sentences), len(raw_sentences))
#splitting sentence into a list of words
def sentence_to_wordlist(raw):
clean = re.sub('[^a-zA-Z]'," ",raw)
words = clean.split()
return words
#for each sentence in sentences where each word is tokenized
sentences = []
for raw_sentence in raw_sentences:
if len(raw_sentence) > 0:
sentences.append(sentence_to_wordlist(raw_sentence))
#print an example
print(raw_sentences[100])
print(sentence_to_wordlist(raw_sentences[100]))
#counting tokens
token_count = sum(len(sentence) for sentence in sentences)
print("The book corpus contains {0:,} tokens".format(token_count))
multiprocessing.cpu_count()
# using gensim library to create our model using word2vec
#setting hyperparameters
#for random no. generator
seed = 1
#no. of cores in the computer...multi-core system means faster training of the model
num_cpu= multiprocessing.cpu_count()
#sg-- it defines the training algo -- 2 choices- skip grams(sg=1) and CBOW(continuous bag of words--default(sg=0))
sg=1
#dimensions of feature vectors...
num_features = 300
#minimum word count--- ignore all words with frequency less than min_count
min_freq_count = 3
#sample isthreshold for configuring which higher-frequency words are randomly downsampled;
#default 1e-3,useful range is (0, 1e-5)
downsampling = 1e-3
#context window length---maximum distance between the current and predicted word within a sentence.
context_window_size = 7
# initilising our model
thrones2vec = w2v.Word2Vec(
sg=sg,
seed=seed,
workers=num_cpu,
size=num_features,
min_count=min_freq_count,
window=context_window_size,
sample=downsampling
)
thrones2vec.build_vocab(sentences)
print('the length of our thrones2vec vocabulary is :{0}'.format(len(thrones2vec.vocab)))
#training model
thrones2vec.train(sentences)
if not os.path.exists('trained'):
os.makedirs('trained')
##saving the model for future use
thrones2vec.save(os.path.join('trained','thrones2vec.w2v'))
##loading the saved model
thrones2vec = w2v.Word2Vec.load(os.path.join("trained", "thrones2vec.w2v"))
#initialsing TSNE
tsne = sklearn.manifold.TSNE(n_components= 2, random_state=0)
all_word_vectors_matrix = thrones2vec.syn0
all_word_vectors_matrix.shape
##this checks out as I set my word vectors to have 300 features/dimensions
all_word_vectors_matrix_2d = tsne.fit_transform(all_word_vectors_matrix)
points = pd.DataFrame(
[
(word, coords[0], coords[1])
for word, coords in [
(word, all_word_vectors_matrix_2d[thrones2vec.vocab[word].index])
for word in thrones2vec.vocab
]
],
columns=["word", "x", "y"]
)
points.head(8)
sns.set_context("poster")
from IPython.display import Image
Image('game_of_vectors.png')
points.plot.scatter("x", "y", s=10, figsize=(20, 12))
def plot_region(x_bounds, y_bounds):
slice = points[
(x_bounds[0] <= points.x) &
(points.x <= x_bounds[1]) &
(y_bounds[0] <= points.y) &
(points.y <= y_bounds[1])
]
print(type(slice), slice.shape)
# print(slice)
ax = slice.plot.scatter("x", "y", s=35, figsize=(10, 8))
for i, point in slice.iterrows():
ax.text(point.x + 0.005, point.y + 0.005, point.word, fontsize=11)
plot_region(x_bounds=(5.0, 5.5), y_bounds=(-1.7,-1.0))
def nearest_similarity_cosmul(start1, end1, end2):
similarities = thrones2vec.most_similar_cosmul(
positive=[end2, start1],
negative=[end1]
)
start2 = similarities[0][0]
print("{start1} is related to {end1}, as {start2} is related to {end2}".format(**locals()))
return start2
nearest_similarity_cosmul("Stark", "Winterfell", "Riverrun")
nearest_similarity_cosmul("Jaime", "sword", "wine")
nearest_similarity_cosmul("Arya", "Nymeria", "dragons")
nearest_similarity_cosmul("Winter","Jon","Doom")
thrones2vec.most_similar("Targaryen")
thrones2vec.most_similar("Lannister")
thrones2vec.most_similar('Stark')
thrones2vec.most_similar('Winter')


--- title: Inception-ResNet v2 model, with weights trained on ImageNet type: docs repo: https://github.com/rstudio/keras menu: main: name: Inception-ResNet v2 model, with weights trained on ImageNet - keras parent: keras-reference aliases: - /reference/keras/application_inception_resnet_v2.html - /keras/reference/application_inception_resnet_v2.html - /guide/keras/reference/application_inception_resnet_v2.html - /tools/tools/keras/reference/application_inception_resnet_v2.html - /installation/keras/reference/application_inception_resnet_v2.html - /tutorials/keras/reference/application_inception_resnet_v2.html - /guide/tools/keras/reference/application_inception_resnet_v2.html - /deploy/keras/reference/application_inception_resnet_v2.html - /tools/keras/reference/application_inception_resnet_v2.html - /tutorials/tools/keras/reference/application_inception_resnet_v2.html ---
Inception-ResNet v2 model, with weights trained on ImageNet
application_inception_resnet_v2(
include_top = TRUE,
weights = "imagenet",
input_tensor = NULL,
input_shape = NULL,
pooling = NULL,
classes = 1000
)
inception_resnet_v2_preprocess_input(x)
| include_top | whether to include the fully-connected layer at the top of the network. |
| weights |
|
| input_tensor | optional Keras tensor to use as image input for the model. |
| input_shape | optional shape list, only to be specified if |
| pooling | Optional pooling mode for feature extraction when
|
| classes | optional number of classes to classify images into, only to be
specified if |
| x | Input tensor for preprocessing |
A Keras model instance.
Do note that the input image format for this model is different than for the VGG16 and ResNet models (299x299 instead of 224x224).
The inception_resnet_v2_preprocess_input()
function should be used for image
preprocessing.
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning(http://arxiv.org/abs/1512.00567)


本书是epub格式。
1.1 Surrounded by Mysteries
1.2 The Social Behavior of H2O
1.3 The Enigma of Interfacial Water
2.1 A Fourth Phase of Water?
2.2 Batteries Made from Water
2.3 Charging the Water Battery
2.4 Water: The Engine of Nature
3.1 A Universal Attractor
3.2 Brown’s Dance: Energy-Driven Movements
3.3 Heat and Temperature: Throwing New Light on Thermal Darkness
3.4 Osmosis and Diffusion: They Don’t Just Happen
4.1 The Power of Protonated Water
4.2 Droplets and Bubbles: Siblings in the Water Family
4.3 Birth of a Bubble: A Passage to Maturity
4.4 Clouds from Coffee: The Remarkable Nature of Evaporation
4.5 Water Trampolines: Layering at the Water’s Surface
4.6 Warming up to Ice
5.1 The Secret Rules of Nature


HKBU JOUR2106 Data Visualisation for News is calling for external mentors to work with the students on course projects.
The Mentorship Program brings small groups of 4 to 6 students together with one mentor to do a final project. The final delivery of course project is a functioning website with interactive storytelling or data visualization. Mentors we invited are experienced professionals/ senior executives in different industries who have a desire to help young people by sharing their knowledge and skills.
As a mentor, you are expected to bring your topic or areas of interest, and it would be even better if you could provide students with some raw data sets for analysis and visualization. After groups assigned, a kick-off meeting will be soonly arranged in which mentors could have brainstorming session with your students to come up with an appropriate topic and approach for the group project. Mentors will provide background knowledge, general advice and feedback to students, guide the students through the process of the whole project.
The course mainly focuses on data visualisation although it covers basic data analytics and data journalism workflow just to be self-contained. Among many visualisation techniques and tools, this course focuses on the web stack, because most content are distributed via (mobile) web-based technology at present. More detailed course information could be reached at: https://hkbu-jour2106.github.io/
Being a mentor is rewarding. You not only have fun with the students but also work with the dedicated teaching team to introduce latest web-based visualisation technology into your project. Having access to our talent pool way before summer can also ensure you an advantageous position if you are looking for new team members.
The tentative program timeline is as follows:
If you or your group is interested, please email<EMAIL_ADDRESS>(Or any other channels you prefer). We'll be in touch to work out a mentoring plan with you. We are interested to know the following information:
Q: What is the expected time for mentors to commit to this program?
A: The program spans 5-6 weeks. Mentors are expected to commit 1-2 hours per week discussing with the students, either offline or online, to guide them through the practical problem that we pick together.
Q: What is the copyright of any outcome?
A: The outcome will be shared authorship between students and mentors. By default, Copyright is CC 3.0 Attribution and the final product will be open source. Any referred prior works/ cited data sets remain their original
license. Detailed arrangements can be discussed subject to the mutual agreement between mentors and students.
Q: How do you protect my data and ensure it is not leaked outside the project?
A: We teach the students proper ways to handle the data set and keep on reminding them about copyright & privacy issue of raw data set. Besides, student groups can also sign an NDA with the mentor to make sure the dataset
is only used for this course project and by this project group only.
Q: What if I don't have a dataset or my organisation does not allow me to work with external collaborators on current projects?
A: You are still welcome to be the mentor if interested! As long as you can help advise the project working process or help criticise the milestones, your input will be valuable to the student groups.
We are also ready to answer anything you'd like to know. Just shoot us an email to kick off.


|
AssetTrackerRK
|
Class to hold a location value. More...
#include <TinyGPS++.h>
Public Member Functions | |
| bool | isValid () const |
| Returns true if the data is valid. More... | |
| bool | isUpdated () const |
| Returns true if the value has been updated since last read. More... | |
| uint32_t | age () const |
| Returns the age of the value in milliseconds. More... | |
| const RawDegrees & | rawLat () |
| Returns the raw latitude. More... | |
| const RawDegrees & | rawLng () |
| Returns the raw longitude. More... | |
| double | lat () |
| Returns the latitude in degrees as a signed double floating point value. More... | |
| double | lng () |
| Returns the longitude in degrees as a signed double floating point value. More... | |
| void | invalidate () |
| Sets the valid flag to false (marks data as invalid) More... | |
| TinyGPSLocation () | |
| Constructor. | |
Friends | |
| class | TinyGPSPlus |
Class to hold a location value.
|
inline |
Returns the age of the value in milliseconds.
If the value is not valid, then ULONG_MAX is returned.
You might check to see if age is < 10000 to make sure the value has been retrieved in the last 10 seconds, for example.
|
inline |
Sets the valid flag to false (marks data as invalid)
This is used internally when we get a valid GPS sentence that does not have a fix. It can be checked by using the isValid() method.
|
inline |
Returns true if the value has been updated since last read.
The updated flag is set to false after reading data (lag, lng, rawLat, rawLng) and is set to true when a valid location is received from the GPS.
|
inline |
Returns true if the data is valid.
The valid flag will be false if the GPS loses its fix, but will not be invalidated if the GPS stops returning data. If that is a possibility, you should also check the age.
| double TinyGPSLocation::lat | ( | ) |
Returns the latitude in degrees as a signed double floating point value.
Positive values are for north latitude. Negative values are for south latitude. Valid values are 0 <= lat() < 360.0
This method is not const because it clears the updated flag.
| double TinyGPSLocation::lng | ( | ) |
Returns the longitude in degrees as a signed double floating point value.
Positive values are for west longitude. Negative values are for east longitude. Valid values are 0 <= lng() < 360.0
This method is not const because it clears the updated flag.
|
inline |
Returns the raw latitude.
The raw latitude separates out the whole part (in degrees), billionths of a degree, and sign, instead of using a double floating point number.
This method is not const because it clears the updated flag.
|
inline |
Returns the raw longitude.
The raw latitude separates out the whole part (in degrees), billionths of a degree, and sign, instead of using a double floating point number.
This method is not const because it clears the updated flag.


Welcome to SeemsRelevant, a site about coding, technology, life and other cool stuff.
Everything here is a work in progress, and new features will be added periodically as my schedule and personal life allow. I hope you find something useful here!


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Vertical/Default Form with Fieldsets and Legends (React)
Please fill in the fields:
First Name:
Hint: Maximum 10 characters
Error: First Name is required
Last Name:
Hint: Maximum 10 characters
Error: Last Name is required
Please fill in your address details:
City:
Hint: Maximum 10 characters
Error: City is required
Address:
Hint: Maximum 10 characters
Error: Address is required
Submit
Clear
Horizontal Form with Fieldsets and Legends (React)
Please fill in the fields:
First Name:
Hint: Maximum 10 characters
Error: First Name is required
Last Name:
Hint: Maximum 10 characters
Error: Last Name is required
Please fill in your address details:
City:
Hint: Maximum 10 characters
Error: City is required
Address:
Hint: Maximum 10 characters
Error: Address is required
Submit
Clear


We want every .initialize-me item to have color changed to blue by js - no matter how and when item with this class is added
You can even add item with .initialize-me class via browser inspector - proper js will be executed on it just when you finish edition.
This elem has .wrong-class and will not be initialized.
Sub element
This class has .initialize-me class so it will be initialized.
Sub element
This should be bold, if there is a div in front of it.
This item wont be initialised because it is outside the target element that is being observed.


The wearing of the poppy
Sir, – In her sketch (“Is enthusiasm for wearing the poppy starting to wilt?”, November 16th) Miriam Lord takes a swipe what she calls poppy mania across the water. She then continues to have a pop at Senators Frankie Feighan and Neale Richmond for wearing the emblem here. It takes courage for both to do this and they are quite entitled to remember the Irish war dead.
There was a time here during the violent IRA campaign when poppies could not be sold or even worn in this Republic. I might recall one occasion in the same Senate . After the 1987 horrendous act when IRA murdered mostly elderly people in the Enniskillen massacre, Senator John Robb wore a poppy in the senate and offered to the then Cathaoirleach Senator Sean Fallon, Fianna Fáil. The latter graciously accepted it and placed it on his lapel. Might I suggest that the redoubtable Miriam Lord might find other things to poke fun at. – Yours, etc,
BRENDAN CAFFERTY,
Ballina, Co Mayo.


---
layout: def
---
$\mathbb{P}_k=\ket{a_k}\bra{a_k}$ is the projection onto the $k^{\text{th}}$ eigenstate.
Notations
Coming soon
Concepts
If we sum over a complete set of states, then
$$\begin{align*}
\sum_{k}^{n}\ket{a_k}\bra{a_k}=1
\end{align*}$$
The probability of measuring the state $\ket{a_n}$ can also be written $\text{Prob}(\ket{a_n})=|c_n|^2=\braket{\psi|\mathbb{P}_n|\psi}$


Reason required*
atleast 3 characters
Account Number:
{{bankdata.bank_account_no}}
Branch :
{{bankdata.bank_branch}}
Bank Name :
{{bankdata.bank_name}}
City :
{{bankdata.bank_city}}
IFSC Code:
{{bankdata.bank_ifsc_code}}
Is Active:
{{bankdata.is_active}}
Is active:


MAKE YOUR PIZZA
Size of pizza
Big
Small
Medium
Type of crust
Crispy
Stuff
Gluten-free
Topping
Chicken
Pineapple
Cheese
How many pizzas
Order
Checkout
size:
topping:
crust:
total:
Location:


{{ $has_ad := .Get "show_ad" }} {{ if (or (eq $has_ad true) (eq $has_ad "")) }}
This screencast only scratches the surface. Subscribe to my new screencast series on Go web apps to dive deeper.
Check out the example code on GitHub and keep on rockin', Gophers!


class RegisterSetInitialisationException : Exception
Thrown when a RegisterSet cannot be initialised.
This could be due to invalid configuration or some other error.
message
- A message accompanying the exception.
RegisterSetInitialisationException(message: String)
Thrown when a RegisterSet cannot be initialised. |


{% extends "private/base.htm" %} {% block result %}
The password you entered was not recognised. If this is a new password and would like to save it to your account, we need you to enter any of your other passwords in order to confirm your identity.


Please note that the testcases will have to be extracted before the coverage report will display.
The contents of the zip file should be extracted into a folder with the same name as the zip file but without the extension. For example, RIMDemo-testCases.zip should be extracted into a folder called RIMDemo-testCases. This should be the default behaviour for standard Windows® tools.
Windows is a registered trademark of Microsoft Corporation in the United States and/or other countries.


- iAStar - Interface in com.example.sulemaia.Interface
-
Public interface to control de implementation of the methods for A* algorithm.
- ibEdit - Variable in class com.example.sulemaia.Adapter.CharacterSelectorAdapter.Item
-
- ibInfo - Variable in class com.example.sulemaia.Adapter.CharacterSelectorAdapter.Item
-
- iCharacterSelected - Interface in com.example.sulemaia.Interface
-
Interface to coordinate the character selected options.
- icon - Variable in class com.example.sulemaia.Model.CharacterItem
-
- iconPos - Variable in class com.example.sulemaia.Dialog.CustomCharacterEditorDialog
-
- iconSelected - Variable in class com.example.sulemaia.Adapter.DialogCharacterEditorAdapter
-
- iconSelected(int) - Method in class com.example.sulemaia.Dialog.CustomCharacterEditorDialog
-
We instantiate the basic parts of the view whenever a character icon is selected.
- iconSelected(int) - Method in interface com.example.sulemaia.Interface.iDialogCharacterIconSelected
-
Process the selected icon to show the corresponding dialog, after checking everything
is correct and possible, based on a position.
- iDialogCharacterIconSelected - Interface in com.example.sulemaia.Interface
-
Interface implementation for the dialog character icon.
- iFirstTheBest - Interface in com.example.sulemaia.Interface
-
Public interface to control de implementation of the methods for First Best algorithm.
- iIconSelected - Variable in class com.example.sulemaia.Adapter.DialogCharacterEditorAdapter
-
- images - Variable in class com.example.sulemaia.Activity.Tutorial
-
- iMethods - Variable in class com.example.sulemaia.Thread.ResolverAStarThread
-
- iMethods - Variable in class com.example.sulemaia.Thread.ResolverFirstBestThread
-
- iMethods - Variable in class com.example.sulemaia.Thread.ResolverUniformCostThread
-
- inAstar(HeuristicPathTree.Node) - Method in class com.example.sulemaia.Model.HeuristicPathTree
-
- INCONSISTENT_ID_QUANTITY - Static variable in class com.example.sulemaia.Helper.Parser
-
- initialItem - Variable in class com.example.sulemaia.Activity.MainActivity
-
- initialNameField - Variable in class com.example.sulemaia.Activity.CharacterSelector
-
- initialX - Variable in class com.example.sulemaia.Activity.CharacterSelector
-
- initialX - Variable in class com.example.sulemaia.Activity.GameScreen
-
- initialX - Variable in class com.example.sulemaia.Fragment.AStar
-
- initialX - Variable in class com.example.sulemaia.Fragment.FirstBest
-
- initialX - Variable in class com.example.sulemaia.Fragment.UniformCost
-
- initialY - Variable in class com.example.sulemaia.Activity.CharacterSelector
-
- initialY - Variable in class com.example.sulemaia.Activity.GameScreen
-
- initialY - Variable in class com.example.sulemaia.Fragment.AStar
-
- initialY - Variable in class com.example.sulemaia.Fragment.FirstBest
-
- initialY - Variable in class com.example.sulemaia.Fragment.UniformCost
-
- initTreeAndColors() - Method in class com.example.sulemaia.Activity.GameScreen
-
We create the graphic tree with the first node (which is obviously the
initial coordinate of the character), process the invalid nodes, and paint
the adjacent tiles with the corresponding color.
- inOrderFirst(HeuristicPathTree.Node) - Method in class com.example.sulemaia.Model.HeuristicPathTree
-
Algorithm to obtain the tree in an Inorder organization, to make sure it will
be displayed correctly.
- intent - Variable in class com.example.sulemaia.Activity.ExpansionDetails
-
- intent - Variable in class com.example.sulemaia.Activity.SearchAlgorithms
-
- inUniformCost(HeuristicPathTree.Node) - Method in class com.example.sulemaia.Model.HeuristicPathTree
-
- INVALID_FILE_CONTENT - Static variable in class com.example.sulemaia.Helper.Parser
-
- isAccessible() - Method in class com.example.sulemaia.Model.HeuristicPathTree.Node
-
Check if a node is accessible by the character.
- isAccessible() - Method in class com.example.sulemaia.Model.PathManualTree.Node
-
Method to check if a certain tile (node) is accessible by the character.
- iSelected - Variable in class com.example.sulemaia.Adapter.CharacterSelectorAdapter
-
- isEndingState() - Method in class com.example.sulemaia.Activity.ExpansionDetails.ButtonActions
-
We can proceed once the last order state is implemented by the user.
- isFinal - Variable in class com.example.sulemaia.Activity.FieldInformation
-
- isFinal - Variable in class com.example.sulemaia.Model.GameLandItem
-
- isFinal() - Method in class com.example.sulemaia.Model.GameLandItem
-
Check if the land is final.
- isFinal(int, int) - Method in class com.example.sulemaia.Model.HeuristicPathTree.Node
-
Check if the actual node is the final node.
- isFinal - Variable in class com.example.sulemaia.Model.LandItem
-
- isFinal() - Method in class com.example.sulemaia.Model.LandItem
-
Check if a certain tile is the final one, designated by the user.
- isGameFinish() - Method in class com.example.sulemaia.Activity.GameScreen
-
We check if the actual coordinate in which the character is right now,
is the same as the final tile, so the game would be finished.
- isInitial - Variable in class com.example.sulemaia.Activity.FieldInformation
-
- isInitial - Variable in class com.example.sulemaia.Model.GameLandItem
-
- isInitial() - Method in class com.example.sulemaia.Model.GameLandItem
-
Check if the land is initial.
- isInitial - Variable in class com.example.sulemaia.Model.LandItem
-
- isInitial() - Method in class com.example.sulemaia.Model.LandItem
-
Check if the tile was designated as initial by the user.
- isPathFound - Variable in class com.example.sulemaia.Thread.ResolverUniformCostThread
-
- isPathFounded - Variable in class com.example.sulemaia.Thread.ResolverAStarThread
-
- isPathFounded - Variable in class com.example.sulemaia.Thread.ResolverFirstBestThread
-
- isPermissionGranted() - Method in class com.example.sulemaia.Activity.MainActivity.ButtonActions
-
Check if the reading of archives permission is granted.
- isValidStringInFile(String) - Static method in class com.example.sulemaia.Helper.Parser
-
We receive a whole document (whichever the user chooses, so be careful with this;
it means this can load anything, like photos or documents, but is only intended
to load incredibly light txt files that go along the project specifications.
- item - Variable in class com.example.sulemaia.Activity.CharacterEditor
-
- Item(View) - Constructor for class com.example.sulemaia.Adapter.CharacterEditorAdapter.Item
-
Item view of selected character.
- item - Variable in class com.example.sulemaia.Adapter.CharacterSelectorAdapter.ButtonActions
-
- Item(View) - Constructor for class com.example.sulemaia.Adapter.CharacterSelectorAdapter.Item
-
Implementation of the item view, that cant be null.
- Item(View) - Constructor for class com.example.sulemaia.Adapter.DialogCharacterEditorAdapter.Item
-
Constructor of the item view, that cant be null.
- item - Variable in class com.example.sulemaia.Adapter.DialogCharacterInformationAdapter
-
- Item(View) - Constructor for class com.example.sulemaia.Adapter.DialogCharacterInformationAdapter.Item
-
Constructor of the itemview, that cant be null.
- Item(View) - Constructor for class com.example.sulemaia.Adapter.MainActivityAdapter.Item
-
On the item creation take action.
- iUniformCost - Interface in com.example.sulemaia.Interface
-
Public interface to control de implementation of the methods for Uniform Cost algorithm.
- ivFieldColor - Variable in class com.example.sulemaia.Activity.FieldInformation
-
- ivImage - Variable in class com.example.sulemaia.Activity.CharacterEditor
-


JavaScript Broughlike Tutorial
This is a tutorial about writing a broughlike (a small roguelike game similar to
868-HACK or
Cinco Paus) from scratch in JavaScript.
Check out the
Introduction to see why I created this and how it differs from other tutorials.
Try it out
Here's the
completed game.
Controls are lowercase
wasd for move/attack and number keys for spells.
Table of Contents
What to do if you get stuck
The
github project contains completed versions of all stages, so you can check your results as you go along. Open the
index.html in each completed stage in your browser to test out the behavior at that stage.
Getting help
If you have any questions or anything is unclear, please reach out on our
discord server.
You can also email me directly if you prefer:
jeremiah.reid@gmail.com


NewYorkButton
public final class NewYorkButton : UIButton
A button for the NewYorkAlert.
-
Styles to apply to buttons in the NewYorkAlert.
See moreDeclaration
Swift
public enum Style
-
A Boolean value indicating whether the control draws a highlight. Highlight animation will be performed here.
Declaration
Swift
override public var isHighlighted: Bool { get set }
-
Creates a button that can be added to the NewYorkAlert.
Declaration
Swift
public init(title: String, style: Style, handler: ((NewYorkButton) -> Void)? = nil)
Parameters
title
A button title.
style
A style that is applied to the button.
handler
A block to execute when the user taps the button.
Return Value
A NewYorkButton object.
-
Set button’s title color from
NewYorkDynamicColor
.Declaration
Swift
public func setDynamicColor(_ color: NewYorkDynamicColor)
Parameters
color
A color to apply to the button’s title


@x:Act has a single grammar that describes both lexical and context-free syntax. The grammar is specified using an extended BNF.
The complete grammar can be found in Combined Syntax. The grammar can also be browsed starting with the <script> root non-terminal.
The grammar is ambiguous for <exp>s with <prefix op>s and <infix op>s. This is resolved with a Precedence table.
Each @x:Act script will be a single <script> contained in a file with extension .xact.


| DOSE: |
21 g |
oral |
Nutmeg |
(ground / crushed) |
I am someone who is relatively experienced with psychoactives and other mind altering substances. I decided one weekend that I would try it out because none of my friends had the guts and we wanted to know what it was like. I had procured a 63 gram package of ground nutmeg, and was planning on mixing it with liquid to cut the taste. That was a mistake. It only brings out the awful taste that is already hard to handle. I ended up tossing it in my mouth as it is, swallowing, and having a chaser of root beer. It sucks, but it's the least painful way. I tried mixing it with root beer and the results were horrible. It all rose to the surface in a bubbly mush which made it hard to handle. The taste was amplified greatly, and it ruined the drink.
It can get pretty sedative and nice at times, but there were no hallucinogenic qualities in any of my 3 experiences (all at quite high doses). The biggest problems have yet to come.  Gas is also very prominent, and occurs often (the infamous 'megers are awful). Nutmeg burps are bad too, and usually occur during the experience.
The timing went something like this:
8:00 PM: 21 grams (a third of a 63 gram package bye eye) of nutmeg ingested
9:00 PM: Waiting for results. Numerous unpleasant burps occur.
9:30 PM: I think it starts to kick in a bit, but it may be a placebo type effect.
10:00 PM: I finally feel something for sure, it is a drunk like feeling, with less motor skill impairment and more perception alteration.
11:00 PM: Sedation and more 'mental' impairment occur (mental = perception or thought processes).
12:00 PM: More effects come on, and though I donít actually see anything, there are very slight hallucinogenic effects like streaming lights and/or shadows in the corners of eyes.
1:00 PM: Sedative effects are so strong I fall asleep (luckily in my bed).
The next week: Bad side-effects ranging from horrible gas to stomache pain to light sensitivity (yes, light sensitivity). There are others, but too many to list.
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.


comparisonOperator
Syntax
A comparisonOperator is one of:
| |
(a) |
< |
|
% Less than |
| |
(b) |
> |
|
% Greater than |
| |
(c) |
= |
|
% Equal |
| |
(d) |
<= |
|
% Less than or equal; subset |
| |
(e) |
>= |
|
% Greater than or equal; superset |
| |
(f) |
not= |
|
% Not equal |
Description
A comparison operator is placed between two values to determine their equality or ordering. For example, 7 > 2 is true and so is "Adam" < "Cathy". The comparison operators can be applied to numbers as well as to enumerated types. They can also be applied to strings to determine the ordering between strings (see the string type for details). Arrays, records, unions and collections cannot be compared. Boolean values (true and false) can be compared only for equality (= and not=); the same is true of pointer values. Set values can be compared using <= and >=, which are the subset and superset operators. The not= operator can be written as ~=.
Comparisons among classes is also supported (see class). If C and D are classes, C <= D means D is a descendant of (inherits from) C. See class.
See also
See also infix operators and precedence of operators. See also the int, real, string, set, boolean and enum types. See also string comparison.


--- title: dictionaries keywords: fastai sidebar: home_sidebar summary: "Note: Going through the basics of dictionaries" description: "Note: Going through the basics of dictionaries" nb_path: "07_Dictionaries.ipynb" ---
Dictionaries can have multiple data types and are defined by key-value pairs. To each key correspnds a value
myCat = {'size':'fat','color':'gray', 'disposition':'loud'}
print(myCat['size'])
print('My cat has ' + myCat['color'] + ' fur.')
Items in dictionaries do not have orders
[1,2,3] == [3,2,1]
myCat = {'size':'fat','color':'gray', 'disposition':'loud'}
myDog = {'disposition':'loud','color':'gray', 'size':'fat'}
myCat == myDog
'size' in myCat
'size' not in myCat
list(myCat.keys())
list(myCat.values())
list(myCat.items()) # this return a list tuple
tuples are like list only that they are unmutable and are in parenthesis
myCat.keys()
for k in myCat.keys():
print(k)
for v in myCat.values():
print(v)
for k, v in myCat.items():
print(k, v)
for i in myCat.items():
print(i)
print(myCat)
'gray' in myCat.values()
myCat.get('color',0)
myCat.get('species',0)
picnicItems = {'apples': 5, 'cups':2}
print('I am bringing '+ str(picnicItems.get('napkins', 0)) + ' to the picknic')
print(myCat)
if 'species' not in myCat:
myCat['species'] = 'feline'
print(myCat)
print(myCat)
myCat.setdefault('age', '12')
print(myCat)
myCat.setdefault('age', '8') # age is already definied, this is unmutable
print(myCat)
message = 'This was getting late at night and Thierry was still going though Automate the Boring Stuff'
count = {} # example 'r':12 but empty right now
for character in message:
count.setdefault(character, 0)
count[character] = count[character] + 1
print(count)
For now this program is countign upper and lower case separately
message = 'This was getting late at night and Thierry was still going though Automate the Boring Stuff'
count = {} # example 'r':12 but empty right now
for character in message.upper():
count.setdefault(character, 0)
count[character] = count[character] + 1
print(count)
tp get the result in alphabetical order we are going to import pprint (pretty print)
import pprint
message = 'This was getting late at night and Thierry was still going though Automate the Boring Stuff'
count = {} # example 'r':12 but empty right now
for character in message.upper():
count.setdefault(character, 0)
count[character] = count[character] + 1
pprint.pprint(count)
print("space")
stringFormatted = pprint.pformat(count)
print(stringFormatted)
cat = {'name': 'Zophie', 'age': 7, 'color':'gray'}
allCats = []
allCats.append({'name': 'Zophie', 'age': 7, 'color':'gray'})
allCats.append({'name': 'Pooka', 'age': 5, 'color':'black'})
allCats.append({'name': 'Fat-tail', 'age': 5, 'color':'grey'})
allCats.append({'name': '???', 'age': -1, 'color':'orange'})
print(allCats)
allCats here is a "data structure, here a list of Dictionaries"


This tool converts all existing post content to Power Blog deltas.
This will download a CSV of all of your posts
Total Posts left to Convert: = $posts->count() ?>


public interface BinaryEqualityComparator
If both the BTree and duplicate comparators used by a databse are binary-equality comparators, then certain internal optimizations can be enabled. Specifically, the "BIN-delta blind-puts" optimization described below is made possible.
We say that a record operation (insertion, update, or deletion) is performed blindly in a BIN-delta when the delta does not contain a slot with the operation's key and we don't need to access the full BIN to check whether such a slot exists there or to extract any information from the full-BIN slot, if it exists. Performing a blind operation involves inserting the record in the BIN-delta, and in case of deletion, marking the BIN slot as deleted. When the delta and the full BIN are merged at a later time, the blind operation will be translated to an insertion, update, or delete depending on whether the full BIN contained the record or not.
Normally, blind puts are not possible: we need to know whether the put is actually an update or an insertion, i.e., whether the key exists in the full BIN or not. Furthermore, in case of update we also need to know the location of the previous record version to make the current update abortable. However, it is possible to answer at least the key existence question by adding a small amount of extra information in the deltas. If we do so, puts that are actual insertions can be done blindly.
To answer whether a key exists in a full BIN or not, each BIN-delta stores a bloom filter, which is a very compact, approximate representation of the set of keys in the full BIN. Bloom filters can answer set membership questions with no false negatives and very low probability of false positives. As a result, put operation that are actual insertions can almost always be performed blindly.
Because bloom filters work by applying hash functions on keys (where each key byte participates in the hash computation), an additional requirement for blind puts is that a database uses "binary equality" comparators, that is, a comparator that considers two keys to be equal if and only if they have the same length and they are equal byte-per-byte. Inheriting from the BinaryEqualityComparator interface marks an actual comparator as having the "binary equality" property.
Comparators are configured using
DatabaseConfig.setBtreeComparator(java.util.Comparator)
or
DatabaseConfig.setBtreeComparator(Class)
, and
DatabaseConfig.setDuplicateComparator(java.util.Comparator)
or
DatabaseConfig.setDuplicateComparator(Class)
.
As described in the javadoc for these methods, comparators must be used with great caution, since a badly behaved comparator can cause B-tree corruption.
Copyright (c) 2002, 2017 Oracle and/or its affiliates. All rights reserved.


I'm A Celebrity viewers fuming as technical fault makes them miss 10 minutes of show
Dan Osborne was also affected!
by Nancy BrownViewers were left fuming after ITV Hub crashed 45 minutes into the second episode of I'm A Celebrity – Get Me Out Of Here!.
The incident happened as Roman Kemp told his campmates about the Christmas gifts his godfather, Wham! singer George Michael, had bought him.
Dan Osborne – who is married to campmate Jacqueline Jossa – was also affected.
Read more: Harry and Meghan start their "well-deserved" extended break
It meant that he missed her meltdown over an emu rump stir fry as she claimed James Haskell took credit for her idea.
"I missed the last ten minutes," said Dan on Instagram.  The television wasn't working. I'm back now."
Read more: IAC viewers divided over Adele Roberts' luxury item
He added: "So many people saying their TV just stopped working."
Many took to Twitter to vent their frustration.
One said they thought Kris Jenner – who was previously married to campmate Caitlyn – had engineered the outage.
Others complained they'd missed the Dingo Dollar Challenge.
Some joked that the streaming service couldn't handle all the name dropping the stars were doing on the show, so it stopped working.
Others were so distraught at missing ten minutes of the show that they said their life was "ruined".
Did the outage affect you? Let us know on our Facebook page @EntertainmentDailyFix.


Name
Email
Phone Number
Please select all desired services:
House Washing
Deck Cleaning
Roof Cleaning
Concrete Cleaning
Rust Removal
Gutter Brightening


This is some text.
This is some text.
Note:
For :first-child to work in IE8 and earlier, a DOCTYPE must be declared.


"I crept toward the patterns of waves and crouched down to take off my sneakers. The knots seemed at first impossible. Double knots. Extra security. Double knots. Security for what? Shoe thieves. Double knots for shoe thieves. I laughed and the sound echoed off the water. I pulled the laces of my left shoe, and at last my feet were free. But then there were my socks. The curve of my toes inside the dimpled white cotton seemed to form a smile. I decided to leave them on."
Eustis Anne Avery wasn’t a normal girl, and she liked it like that. At the age of six, after an extensive...
read moreAlways eat breakfast—protein, fiber, and not too much sugar.1 Take care of your teeth. Brush and floss every day.2
read more“I can’t go into that place dressed like this.” Jerome Walker shakes his shoulders inside the loose, green Henley.
read more


Brute Force?
问题描述 :
Brute force may refer to any of several problem-solving methods involving the evaluation of multiple (or every) possible answer(s) for fitness. There is a very familiar brute-force problem for you.
There is an N * M grid, some are black while some are white. As iSea loves white more than black, he tries to change the color of all grids into white. Each time, he can choose one grid, and then the grid and its four adjacent grids will flip its color, that is, white to black, or black to white.
To make things worse, some grids are broken, and iSea can’t change color on this grid, but he can change its color with its unbroken adjacent grids. Is this task possible for him?
There is an N * M grid, some are black while some are white. As iSea loves white more than black, he tries to change the color of all grids into white. Each time, he can choose one grid, and then the grid and its four adjacent grids will flip its color, that is, white to black, or black to white.
To make things worse, some grids are broken, and iSea can’t change color on this grid, but he can change its color with its unbroken adjacent grids. Is this task possible for him?
输入:
The first line contains a single integer T, indicating the number of test cases.
Each test case includes three integers N, M, K, K means the number of broken grids. Then N lines following, each line contains a string only contains ‘B’ or ‘W’, ‘B’ indicates black grid, ‘W’ indicates white grid.
Then K lines following, each line contains two integers Xi, Yi (1-based), means grid (Xi, Yi) is broken.
Each test case includes three integers N, M, K, K means the number of broken grids. Then N lines following, each line contains a string only contains ‘B’ or ‘W’, ‘B’ indicates black grid, ‘W’ indicates white grid.
Then K lines following, each line contains two integers Xi, Yi (1-based), means grid (Xi, Yi) is broken.
Technical Specification
1. 1 <= T <= 64
2. 1 <= N, M, K <= 256
3. 1 <= Xi <= N, 1 <= Yi <= M, no grid appears more than once.
输出:
The first line contains a single integer T, indicating the number of test cases.
Each test case includes three integers N, M, K, K means the number of broken grids. Then N lines following, each line contains a string only contains ‘B’ or ‘W’, ‘B’ indicates black grid, ‘W’ indicates white grid.
Then K lines following, each line contains two integers Xi, Yi (1-based), means grid (Xi, Yi) is broken.
Each test case includes three integers N, M, K, K means the number of broken grids. Then N lines following, each line contains a string only contains ‘B’ or ‘W’, ‘B’ indicates black grid, ‘W’ indicates white grid.
Then K lines following, each line contains two integers Xi, Yi (1-based), means grid (Xi, Yi) is broken.
Technical Specification
1. 1 <= T <= 64
2. 1 <= N, M, K <= 256
3. 1 <= Xi <= N, 1 <= Yi <= M, no grid appears more than once.
样例输入:
3 2 2 0 BW BB 2 2 1 BW BW 2 1 4 3 2 WBW BBB WBW WWW 2 2 3 2
样例输出:
Case 1: Yes Case 2: Yes Case 3: No
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这已经不是普通的大了
这已经不是普通的大了
这已经不是普通的大了
这已经不是普通的大了
这已经不是普通的大了
这已经不是普通的大了
这已经不是普通的大了
这已经不是普通的大了
这已经不是普通的大了
这已经不是普通的大了
这已经不是普通的大了


MCHD
Menu
Parents
For Current Parents
School Plus!
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No school Camp
Parents Association
Montessori
Montessori at MCHD
MCHD Mission Statement
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MCHD Community
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and Academics
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What to Bring
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Tuition and Fees
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FAQs
{{content}}


Entrees
| Ham Sandwich | $10 |
| Swiss Cheese Steak | $12 |
| Asian Cabbage Stuffers | $10 |
| Salmon Roll | $11 |
| Baked Ziti | $10.50 |
Sides
| Bacon Fries | $5 |
| Mashed Potatoes | $4 |
| Apple Pie Fillers | $4 |
| Green Beans | $4 |
| Edamame | $6 |
Dessert
| Chocolate Rice Pudding | $3 |
| Cherry Pie | $4 |
| Apple Pie Smoothie | $5 |
| Seven Layer Cheesecake | $4 |
| Fried Ice Cream | $5 |


Unsurprisingly, Coordel is built on Coords. Coords are how you go from setting to achieving a goal through a series of tasks executed by a team of experts. Coords bring communication, agreements, productivity, transparency and accountability to the process.
Coords enable you to get work started and completed -with one or more other people- in just a few clicks.
When you start a Coord, you will have the following options to complete. No fields are mandatory but some default to values when not provided:
When you need to accomplish something, but aren’t exactly sure how, just start a Coord. Add People who have the skills you need and use the Stream to discuss how to meet your objective. The task or series of tasks that are needed to reach the goal will emerge from your back-and-forth with these experts.
Coords are designed to coordinate the work People do, and to distribute the authority and responsibility needed to ensure everyone is highly productive and to make progress transparent automatically.


You must add the assets you'd like to analyze to your QuantBook
to request historical data for them. Adding assets uses the same API as QCAlgorithm. For more information on these methods see the Initializing Algorithms section.
qb = QuantBook() spy = qb.AddEquity("SPY") # add equity data eur = qb.AddForex("EURUSD") # add forex data btc = qb.AddCrypto("BTCUSD") # add crypto data goog = qb.AddOption("GOOG") # add goog options es = qb.AddFuture("ES") # add SP 500 futures xau = qb.AddCfd("XAUUSD", Resolution.Minute, Market.Oanda) # add CFD data. Need to specify Market.Oanda


{% include "top.html" %}
Daily Basis (last day's data - ok for investment) - now configured through cron 1. Fetch Bhav and 52-week high and low 1.1. Fetch 52-week High & Low data ftwhl 1.2. Fetch Bhav data bhav Take a buy/sell call - for user's portfolio 2. Get stock with healthy margin 2.1 Phealth
Whenever portfolio has been updated (bought/sold) 3. Demat data 3.1 Upload the demat data demat summary 3.2 Upload demat txn data demat txn 3.3 add support for others like zerodha Quarterly/Monthly Basis 4. Upload the bank stmt that has dividend data. 4.1 Bank Statement Dividend 4.2 Refresh dividend table (currently it is not automated) 4.2.1 Dividend Quarterly/Monthly Basis 5. Upload BAT data - Trendlyne (get rid of dependency slowly) 5.1 Trendlyne 5.2 Refresh the global recommendation (currently it is not automated) 5.2.1 Gfundareco


The source repository can be viewed in your web browser at the URL http://svn.jmock.codehaus.org/.
The source can be checked out anonymously with Subversion from http://svn.codehaus.org/jmock/. The latest jMock 1 source is at the URL http://svn.codehaus.org/jmock/trunk/jmock1. The latest jMock 2 source is at the URL http://svn.codehaus.org/jmock/trunk/jmock2.
You can build jMock with Ant. You will need to install Ant version 1.7. Running the "ant" command in the root of the source tree will perform compile, test and build the jMock JARs, generate Javadoc and package it all into ZIP archives. The built artefacts are left in the build subdirectory.
Commits to the repository are announced to an RSS news feed: http://svn.jmock.codehaus.org/changelog/~rss/jmock/rss.xml.


The startup has been building a financial hub and already lets you purchase cryptocurrencies and buy public shares. Gold is part of a new feature called Commodities
Hopefully, this list will help you and your company stay out of startup purgatory.
YC-backed Giveaway lets folks give away their unused or unnecessary items in a marketplace. Unlike other buy and sell or donation platforms, Giveaway uses a virtual currency on


Nesting Button Group
Cricket
Football
Hockey
Sports
Cricket
Football
Hockey
Button Styles
Primary Button
Secondary Button
Success Button
Danger Button
Warning Button
Info Button
Light Button
Dark Button
Link Button
Button Outlines
Primary Button
Secondary Button
Success Button
Danger Button
Light Button
Warning Button
Info Button
Dark Button
Button Sizes
Small button
Default button
Large button
Block Level Button
Block Level Info Button
Active State
Active button
Disabled State
Disabled Button
Checkbox
HTML-5
CSS-3
Bootstrap-4
Radio Buttons
HTML-5
CSS-3
Bootstrap-4
Button Toolbar
Cricket
Football
Hockey
Tennis
Basketball
Volleyball
Boxing
Archery
Badminton
Button Group Sizes
Cricket
Football
Hockey
Cricket
Football
Hockey
Cricket
Football
Hockey
Button Group
Cricket
Football
Hockey
Button Toolbar
Cricket
Football
Hockey
Tennis
Basketball
Volleyball
Boxing
Archery
Badminton
Button Group Sizes
Cricket
Football
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Traditionally, each file and directory can only have one user owner and one group owner at a time. If you want to apply a more specific set of permissions to a file or directory (allow certain users outside the group to gain access to a specific file within a directory but not to other files) without changing the ownership and permissions of a file or directory, you can use the access control lists (ACL).
The following section describes how to:
-
Display the current ACL.
-
Set the ACL.
Displaying the current ACL
The following section describes how to display the current ACL.
-
To display the current ACL for a particular file or directory, use:
$ getfacl file-name
Replace file-name with the name of the file or directory.
This is glue text!!!
Setting the ACL
The following section describes how to set the ACL.
-
Root
access
-
To set the ACL for a file or directory, use:
# setfacl -m u:username:symbolic_value file-name
Replace username with the name of the user, symbolic_value with a symbolic value, and file-name with the name of the file or directory. For more information see the setfacl
man page.
The following example describes how to modify permissions for the group-project
file owned by the root
user that belongs to the root
group so that this file is:
-
Not executable by anyone.
-
The user
andrew
has therw-
permission. -
The user
susan
has the---
permission. -
Other users have the
r--
permission.
# setfacl -m u:andrew:rw- group-project # setfacl -m u:susan:--- group-project
-
To verify that the user
andrew
has therw-
permission, the usersusan
has the---
permission, and other users have ther--
permission, use:$ getfacl group-project
The output returns:
# file: group-project # owner: root # group: root user:andrew:rw- user:susan:--- group::r-- mask::rw- other::r--


This chapter describes key concepts related to importing imagery, terrain, and vector source data to define resources in Google Earth Enterprise Fusion. It describes all of the tasks related to creating, modifying, organizing, and managing resources. For information about building resources and other assets, see the chapter titled Building Assets.
You first import your source data into Google Earth Enterprise Fusion as a resource. There is a one-to-one correspondence between the type of source file and the type of resource that is created from it:
You can create a single resource from a single source file, or you can create a single resource from many different source files. See Defining Resources for more information.
Providers often split large source files into several smaller source files to make them more acceptable to download. The main purpose of grouping multiple source files into a single resource in Google Earth Enterprise Fusion is to return source files that were split up for artificial reasons (such as file size) to their original state as a single entity. For example, you might acquire four source files that together comprise a large single data set, such as an image of the state of Texas. You combine all four source files into a single resource to put the original data back together.
When you combine source files in a single resource, the source files must be of the same type (imagery, terrain, or vector). In addition, they must be similar in other ways.
An important difference between vector resources and raster (imagery and terrain) resources is that the display rules for vector data can differ between projects. You can use different colors, icons, and filters for the same resource in different projects. With raster resources, however, most of the display settings are specified when you first import the imagery or terrain resource. These settings “stick” with the resource, regardless of which project is using it.
The following tables list the raster data (imagery and terrain) file formats and the vector file formats that are supported by Google Earth Enterprise Fusion.
All raster (imagery and terrain) data must have geographic coordinates and projection information included in the file headers or contained in external text-based world files and projection files. All imagery data must be in 8-bit format with either one band for panchromatic or three bands for color. All terrain data can be in 16-bit or 32-bit format with a single band.
| File Format | Notes |
|---|---|
| DTED | |
| Erdas Imagine (IMG) | |
| GeoTIFF | |
| GIF | Geographic coordinates and projection information must be accompanied by external world and projection files. |
| JPEG | Geographic coordinates and projection information must be accompanied by external world and projection files. |
| JPEG2000 | |
| Microstation (DGN) | Microstation DGN files from prior to version 8 are supported. Versions 8 and later are not supported. |
| MrSID | |
| NITF | |
| PNG | Geographic coordinates and projection information must be accompanied by external world and projection files. |
| TAB | |
| TIF | Geographic coordinates and projection information must be accompanied by external world and projection files. |
| USGS ASCII DEM | |
| USGS SDTS DEM |
Note: Google Earth Enterprise Fusion does not allow you to import imagery resources larger than 80GB in raw size. (Raw size = number of pixels width * number of pixels height * 3.)
| File Format | Notes |
|---|---|
ESRI Shape File (.shp )
|
For each ESRI shape file you import into Google Earth Enterprise Fusion, one DBF and one SHX configuration file, each with the same name as the original and the appropriate extension (.dbf and .shx) must be located in the same folder. In addition, if there is any projection in the image, a PRJ file with the same name as the original file and the appropriate extension (.prj) must be located in the same folder. Other associated files you can include with each SHP file are SBN, SBX, CPG, and LYR. |
| Generic ASCII | Point data only in comma-separated values or tab-delimited text format. |
| KML/KMZ | |
MapInfo File (.tab )
|
|
| US Census Tiger Line Files |
All raster data imported into Google Earth Enterprise Fusion must include geographic coordinates as well as information about the projection used to create the data. The supported data projections are:
| Albers Equal-Area Conic | Lambert Azimuthal Equal Area | Polar Stereographic |
| Azimuthal Equidistant | Lambert Conic Conformal (1SP) | Polyconic |
| Cassini-Soldner | Lambert Conic Conformal (2SP) | Robinson |
| Cylindrical Equal Area | Lambert Conic Conformal (2SP Belgium) | Rosenmund Oblique Mercator |
| Eckert IV | Lambert Cylindrical Equal Area | Sinusoidal |
| Eckert VI | Mercator (1SP) | Stereographic |
| Equidistant Conic | Mercator (2SP) | Swiss Oblique Cylindrical |
| Equi-rectangular | Miller Cylindrical | Swiss Oblique Mercator |
| Gall Stereographic | Mollweide | Transverse Mercator |
| Gauss-Kruger | New Zealand Map Grid | Transverse Mercator (Modified Alaska) |
| Gnomonic | Oblique Mercator | Transverse Mercator (South Oriented) |
| Hotine Oblique Mercator | Oblique Stereographic | Tunisia Mining Grid |
| Laborde Oblique Mercator | Orthographic | Van der Grinten |
The GIS tool you use to create your source data generally embeds projection and geotransform information in your source data file. Sometimes, however, the GIS tool improperly encodes this information or leaves it out altogether. The result is that Google Earth Enterprise Fusion cannot properly locate your source data on the globe.
When the projection and geotransform information is missing or inaccurate, you can provide the required data in the form of auxiliary files to ensure that Google Earth Enterprise Fusion properly converts your data. The auxiliary files must have the same file name as the source file, be located in the same folder, and have the appropriate extension, such as:
.prj
- Provides projection information
.tfw
- Provides geo-transform information
In addition to the standard PRJ format (OpenGIS well known text), Google Earth Enterprise Fusion supports two other file formats for projection data:
EPSG:
x where x is a valid EPSG projection number+proj=latlong +ellps=GRS80 +towgs84=-199.87,74.79,246.62
The first step in preparing your GIS data for use in Google Earth Enterprise Fusion involves importing it into the Asset Manager. When you import source data using the Asset Manager, Google Earth Enterprise Fusion creates a resource that you can add into your projects. The Asset Manager is available both with shell commands entered at the command line and as part the Google Earth Enterprise Fusion GUI. For information on importing large batches of source data, see the Command Line Reference.
As you import more data into the Asset Manager, you create a collection of resources that can be used in different projects. When you create resources for use in Google Earth Enterprise Fusion projects, keep in mind the following:
In general, when you create a resource from vector data, you are setting metadata for that resource, such as the source date, provider, and character encoding. On the other hand, when you create a resource from imagery and terrain data, your settings also affect the display of the data itself, such as mask, fill values, and mosaic options. Settings that affect the display of vector data are defined in the project that contains the vector resource.
Each new resource creation command creates a single resource. If you select multiple source data files, you are creating a single resource that is a composite of multiple sources. The source imagery must have identical resolution.
On the other hand, if you want to import several source files where each one is created as a single resource, you must issue a separate New command for each source file you want to import. Refer to the Command Line Reference for information on how to use batch commands for adding source data.
Typically, vector resources are created from multiple sources when you have contiguous data of the same type. For example, you can create a single resource that displays all of the zip code boundaries for a state by importing several vector files that each contain the zip code boundaries for a specific county. When combining vector source files in this manner, the data itself must have the same projection, and the attribute headers must match in order for the import to be successful.
 When you use data in this format, you must add all of the imagery source files to a single resource, rather than creating a separate resource for each source file.
Note: Recombining multiple imagery source files that were created by artificially splitting a large image is the only intended use for this process. It is not a general purpose, multi-resolution mosaic tool.
You can create a new resource only if a resource of that name/type does not already exist in the target folder. However, because imagery, terrain, and vector resources have different file extensions, you can use the same file name once for each type of resource.
Note: Because resources can be flagged as hidden so that they don’t appear in the Asset Manager, be aware that a name for a resource you create might be used by a hidden resource. Select the Show hidden resources check box before creating new resources if you have many hidden resources in your tree.
Each resource is a separate entity from the source file or files. If you want to specify a different (or updated) source file for an existing resource, you use a different command. See Modifying Resources for more information.
Note: Certain characters in Fusion asset names caused problems with the Publisher and Server. Fusion prevents the creation and use of assets with invalid characters in their names. The following characters are no longer allowed in Fusion asset names:
& % ' \ " * = + ~ ` ? < > : ; and the space character
If any assets have a name containing any of the characters mentioned previously, rename the asset (and path) to a valid name that does not include and of those characters. This requires you to rebuild the assets, as well as the projects and databases that contain them.
The Fusion installer checks the current asset root (if any) to detect, and subsequently warn, if invalid asset names exists before installation will continue.
In cases where creating new copies of the assets requires too much effort or expensive rebuilding of resources, a script is available from Google Earth Enterprise Support that will rename the assets automatically. This script requires using great care, and that is why it is not run automatically.
When you acquire updated source data for a resource that is already included in a Google Earth Enterprise Fusion database, you can easily replace the old source data with the new source data. If the new source file has the same name as the old source file and you are not changing anything else, simply replace the old source file with the new source file on disk, and rebuild the database. The next time you publish the database, everything else remains the same except for the new source data.
The first time you save a new resource, the Save dialog appears. Navigate to the folder where you want to save the resource, provide a unique name for it, and click Save.
Caution: Assets can not be deleted once they are saved. They can be cleaned, so that they are no longer available to use in Google Earth Enterprise Fusion; see Cleaning Asset Versions in the Building Assets chapter for more information.
When you finish defining each resource, you can build it individually or build several resources at the same time; however, you must build a vector resource before you can include it in a project. See the Building Assets chapter for complete details.
You use the Vector Resource Editor to define the following properties:
The acquisition date appears in year-month-day format.
Note: You can decide whether to use the date you acquire the data, the date you import it into Google Earth Enterprise Fusion, or the actual date of the source image. Regardless of which method you use, it is best to adopt a consistent policy for all your resources to avoid confusion.
Click each section of the date and enter the values. Alternatively, you can use the right and left arrow keys to move among the three parts of the date.
Select the source provider from the Provider drop-down list. The provider identifies the source of the data and its copyright information in Google Earth EC.
Note: If you specify the same provider for multiple resources that end up appearing together in Google Earth EC, Google Earth EC is smart enough to display the provider’s name and copyright information only once.
The providers that appear on the list are defined in the Provider Manager. See the section on Managing Data Providers in the Setting Up Your Workspace chapter for more information.
If the field data in your vector resource has a particular encoding for characters, such as ISO8859-1, select the appropriate option, so your data is displayed correctly in Google Earth EC. If you do not select an encoding option, the character encoding defaults to ASCII (plain text).
Use this option if your source data contains multiple layers and you want to extract a specific layer from the data for your resource. If you leave this option set to 0 and your source data contains more than one layer, Google Earth Enterprise Fusion extracts the first layer of the source file to create the resource.
Note: In most cases, source vector data has only one layer; however, Tiger vector data can contain multiple layers. Because there is a one-to-one correspondence between a vector resource and a single vector source layer, resource creation from multi-layer source data must specify a layer.
If you are unsure which layer to indicate when creating a resource from multi-layer source data, you can open the vector source file in Preview pane to display all of the layers in the source data. Examine each layer, and select the appropriate layer to import.
Google Earth Enterprise Fusion interprets elevation in meters, so the default selection for this option is Meters.
Enter the multiplier for Google Earth Enterprise Fusion to use to convert the data to meters. For example, if the elevation is in yards, enter 0.9144. When you click OK, the number you enter here appears as the Elevation Units value.
Google Earth Enterprise Fusion imports polygon features as they are classified in the data set, so the default selection for this option is None. But if for some reason polygon features in the data set are classified incorrectly, you can apply force conversion.
Select force 2D to force conversion of 2.5D polygon features to 2D polygon features.
Select force 2.5D to force conversion of 2D polygon features to 2.5D polygon features.
Note: The 2.5D polygonal features are mainly used in “buildings” data sets. Fusion does an analysis of area of features during the vector resource import and based on the result of this analysis it can propose force converting to 2D for source data set originally classified as 2.5D polygonal resource. Information is reported in resource import log: “Found number of very large features classified as Polygon25D. Possibly the source data is classified incorrectly. Consider importing with --force2D".
By default, if there are bad features in a source file, Google Earth Enterprise Fusion fails to build the resource. The error log states that there are bad features. If you check the box next to Ignore Bad Features, Google Earth Enterprise Fusion ignores the bad features and builds the resource anyway.
By default, if there are invalid geometries in a source file Google Earth Enterprise Fusion detects and tries to fix them. It removes zero length edges and "spikes" in polygonal geometry. As a result of removing invalid geometries polygonal features may become degenerate (zero area polygon). The resource import log states that there are degenerate features and they are skipped. If you check the box next to Don't Fix Invalid Geometries, Google Earth Enterprise Fusion does not clean up invalid geometries and builds the resource anyway.
The Source Files list displays the names of the source files selected for this resource. Click Add to add a source file. See the next section, Adding a Source File to a Resource, for more information.
To delete a file on the Source Files list and no longer associate it with this resource, select the file and click Delete. A message prompts you to confirm the deletion. Click OK. The file no longer appears on the list.
Note: You can select one or more source files to create a single resource, such as an imagery mosaic or a vector composite. If you use more than one source data file for a single resource, all of the raster data must have the same projection and attribute values, and all of the vector data must be of the same type (lines, points, or polygons).
Each resource must contain at least one data source file. Perform the following procedure for each source file you want to add.
You can import KML or KMZ files created in Google Earth as resources in Google Earth Enterprise Fusion. There are a few limitations on the type of KML files that Google Earth Enterprise Fusion can import:
To import KML/KMZ files:
The first time you save a new resource, the Save dialog appears. Navigate to the folder where you want to save the resource, provide a unique name for it, and click Save.
Caution: Assets can not be deleted once they are saved. They can be cleaned, so that they are no longer available to use in Google Earth Enterprise Fusion; see Cleaning Asset Versions in the Building Assets chapter for more information.
When you finish defining each resource, you can build it individually or build several resources at the same time. See the Building Assets chapter for complete details.
Use the Imagery Resource Editor to define the following properties:
The acquisition date appears in year-month-day format. This is required for historical imagery projects.
The date you set for the Imagery Acquisition Date is visible in the Google Earth Client when hovering the cursor over a tile. This requires that the imagery resource has acquisition dates recorded with it and requires a rebuild of the imagery project (since for this feature the date needs to be encoded in the JPEG tiles). Imagery and Vector Resource dialogs now support an improved acquistion date format: unspecified days and months are now supported, for example:
Google Earth Enterprise supports the creation and displaying of historical imagery that works just as the historical imagery in the Google Earth client.
Note: You can decide whether to use the date you acquire the data, the date you import it into Google Earth Enterprise Fusion, or the actual date of the source image. Regardless of which method you use, it is best to adopt a consistent policy for all your resources to avoid confusion.
Click each section of the date and enter the values. Alternatively, you can use the right and left arrow keys to move among the three parts of the date.
Select the source provider from the Provider drop-down list. The provider identifies the source of the data and its copyright information in Google Earth EC.
Note: If you specify the same provider for multiple resources that end up appearing together in Google Earth EC, Google Earth EC will display the provider’s name and copyright information only once.
The providers that appear on the list are defined in the Provider Manager. See Managing Data Providers in the Setting Up Your Workspace chapter for more information.
Tip: If you create a single resource from multiple source files that you received from multiple providers, you can create a special entry in the Provider Manager that gives credit to all providers who contributed to that resource. For example, if you combine source files from USGS and i3 into one resource, you can use the Provider Manager to create a special provider called USGS/i3. In the copyright field, you can enter Imagery © USGS 2005 and i3 2006. When you define the resource, select USGS/i3.
When image data is captured, certain areas contain unusable data. This unusable data is called fill, since it exists simply to fill out the rest of the tile or tiles. Fill data is usually true black (0,0,0), true white (255,255,255), or a value close to one of those two values.
Since the fill data contains no useful information, Google Earth Enterprise Fusion needs to mask the fill areas, allowing the underlying image layers (with usable data) to show through. You can create a mask for a given area yourself, or you can allow Google Earth Enterprise Fusion to create a mask for the fill area automatically. The Auto Mask feature is sufficient in most cases.
If you create a mask yourself, it must either be of the same file format as the original image file, or it must be a TIFF file. See Creating Custom Masks for more information.
If you select Auto Mask for an image, you can set some options to adjust the mask you create. The values you can adjust are described in the following sections.
Select the mask type from the Mask Type drop-down list.
In most situations, particularly when you are creating a mosaic from contiguous source imagery, the Auto Mask setting is the best choice. For example, if you have four square contiguous pieces of imagery that are bounded by land on all sides, you would likely select Auto Mask. The Auto Mask function automatically uses a fill value based on the colors in the four corners of the source imagery to create the mask.
If you select Auto Mask, you can set the following options:
The feathering value allows you to provide a smooth transition between the image (usable) data and the fill (unusable) data. You use the feathering option to define a blending region between the actual image and the transparent mask.
At the edge of the feather area closest to the image, 100 percent of the image area is visible. From this point to the edge of the mask, the transparency of the image increases and its opacity decreases. At the same time, the opacity of the mask increases and its transparency decreases. At the edge of the feather area closest to the mask, the image value is 100 percent transparent, and the underlying imagery shows through completely.
The default feather value is 100 pixels. If the default feather value results in masking out too much data, you can specify a lower value (that is, a narrower band of blending) and experiment with the results. However, if you specify a value that is too low, you could create sharp edges between insets, possibly even leaving black lines between insets. See Defining Terrain Resources for more information. See also the Tutorial for an example.
Use this option to indicate which channel to use when generating the mask (Red, Green, or Blue). Typically, green provides the best contrast between Earth data and no data and is, consequently, the default. However, some data works best when the blue channel is used for mask selection.
Tolerance specifies the color range for mask selection. The default tolerance is 0, which is adequate for many fill colors that are pure black or pure white. However, when data is compressed and uncompressed, it is sometimes modified slightly. Although these modifications are imperceptible to the human eye, a computer can detect them. A fill pixel with an original value of (0,0,0), for example, might decompress to a value of (0,1,0).
If you want to ignore slight variations in fill color values, you can specify a tolerance value, which represents the amount of variation from true black or true white that Google Earth Enterprise Fusion ignores when it creates the Auto Mask. Typically, a setting of 1 or 2 is adequate.
Use this option if you have fill regions inside the boundaries of your imagery data. The default setting for hole size is 0, which is off.
The hole size indicates the number of contiguous pixels Google Earth Enterprise Fusion uses when matching any color region inside your imagery with the same value specified as your fill. For example, if you set the Hole Size value to 100 and the imagery has a block of pixels that is 100 or more pixels in width or height with the same color as one of the corners (fill value), Google Earth Enterprise Fusion treats that area as a hole in the data and applies the mask to it. The end result is that whatever data is under the masked data shows through.
Be aware that if you use the hole-checking feature, there are trade-offs that can dramatically increase the time it takes to generate a mask, including:
Specifying an appropriate hole size involves some familiarity with the actual data.
Fill data is usually indicated by areas of black pixels, so the default fill color is black (0,0,0). If you know that the vendor has used white (255,255,255) as well as black as a fill color, be sure to check the Fill White box when you import the imagery. Checking this box allows both black and white to be considered as fill data when the Auto Mask is created. The following image is an example of source imagery with both black and white fill data.
Use this option to specify the pixel value for NoData in the terrain
data (the pixel values to include in the mask). Multiple values may be
specified in this field, including ranges (two numbers separated by a
colon ":") and individual values. For example,
-99999:0
is
the default which will mask any pixel value from -99999
through 0
, inclusive.
The values -99999
and 0
alone, can be masked
by using -99999, 0
instead
of -99999:0
. Alternatively,
‘-99999:-32768, 32768:999999’
means mask
pixel values -99999
through -32768
and
32768
through 999999
.
Select Have Mask if you have a corresponding alpha mask or file for your source. (See Creating Custom Masks for details about creating your own custom masks.) Google Earth Enterprise Fusion automatically applies the mask file to the source file. The mask for your input must be located in the same folder as the source file, and the file name must match the name of the source file with -mask
appended. For example, if your source file is called NewYork.tif
, its mask file must be named NewYork-mask.tif
.
You might select the Have Mask option in a situation where your source file imagery is bounded by water, and a significant portion of the image is water. In that case, you would likely create a mask by hand in order to preserve the high-resolution detail around your shoreline while masking the water imagery.
If you are creating a resource from multiple imagery source files, you cannot select Have Mask as the mask setting value.
Select No Mask only for base map imagery that extends to the entire database, such as the NASA Blue Marble imagery.
The simplest way to import source data is to create one resource from each data file. In some cases, though, it is actually necessary or just more efficient to import multiple source images into a single resource, called a mosaic. To create a mosaic, the source images must meet the following requirements:
Use the Mosaic Options area for setting the tile fill values and fill tolerance for fill areas of overlapping imagery tiles. These options are available only when you import more than one imagery file.
Note: This process of recombining images that were artificially split is the only intended use for combining multiple imagery source files into a single resource. It is not a general purpose, multi-resolution mosaic tool.
When there is an overlap between the tiles, the pixels in the top tile obscure the pixels in lower tiles. To expose the pixel beneath the top tile, you specify the color to make transparent.
Note: The Tile Fill setting makes the specified pixels transparent. Masking blocks the specified pixels. Both methods, however, define the pixels to be maintained and the pixels that show through.
For example:
Note: Google Earth Enterprise Fusion applies the Tile Fill setting and other mosaic-related settings to the imagery to create a single larger image before it applies the mask. Any fill value you set here has no impact on the mask you use for the entire image.
The tolerance setting functions just as it does for fill values on the Auto Mask. See Tolerance under the Auto Mask bullet above.
The Source Files list displays the names of the source files selected for this resource. Click Add to add a source file. See Adding a Source File to a Resource for more information.
Note: You can select one or more source files to create a single resource, such as an imagery mosaic or a vector composite. If you use more than one source data file for a single resource, all of the source data must have the same projection and attribute values.
Google Earth Enterprise Fusion does not allow you to import raw imagery source files larger than 80 GB. (Raw size = number of pixels width * number of pixels height * 3.) Therefore, if you have an imagery source file that is larger than 80GB, you can create two or more source files using the gesplitkhvr
command. (See gesplitkhvr in the Command Line Reference chapter for details.)
The first time you save a new resource, the Save dialog appears. Navigate to the folder where you want to save the resource, provide a unique name for it, and click Save.
Caution: Assets can not be deleted once they are saved. They can be cleaned, so that they are no longer available to use in Google Earth Enterprise Fusion; see Cleaning Asset Versions in the Building Assets chapter for more information.
When you finish defining each resource, you can build it individually or build several resources at the same time.
Use the Terrain Resource Editor to define the following properties:
The acquisition date appears in year-month-day format.
Note: You can decide whether to use the date you acquire the data, the date you import it into Google Earth Enterprise Fusion, or the actual date of the source image. Regardless of which method you use, it is best to adopt a consistent policy for all your resources to avoid confusion.
Click each section of the date and enter the values. Alternatively, you can use the right and left arrow keys to move among the three parts of the date.
When terrain data is captured, certain areas contain unusable data. This unusable data is called fill, since it exists simply to fill out the rest of the tile or tiles.
Since the fill data contains no useful information, Google Earth Enterprise Fusion needs to mask the fill areas, allowing the underlying terrain layers (with usable data) to show through. You can create a mask for a given area yourself, or you can allow Google Earth Enterprise Fusion to create a mask for the fill area automatically. The Auto Mask feature is sufficient in most cases.
If you create a mask yourself, it must either be of the same file format as the original image file, or it must be a TIFF file. See Creating Custom Masks in the chapter titled Creating Your Own Source Data, Icons, and Masks for more information.
If you select Auto Mask for terrain data, you can set some options to adjust the mask you create. The values you can adjust are described in the following sections.
Select the mask type from the Mask Type drop-down list.
In most situations, particularly when you are creating a mosaic from contiguous terrain source data, the Auto Mask setting is the best choice. The Auto Mask function automatically uses a fill value based on the elevation value in the four corners of the source terrain to create the mask.
If you select Auto Mask, you can set the following options:
Feathering blends the edges of your terrain tile into adjacent areas for a smoother transition. The default feather value for Auto Mask is 100 pixels, but you can adjust it for a wider or narrower margin, if desired. See Defining Imagery Resources for more details about feathering.
Use this option if you have masked regions inside the boundaries of your terrain data. The default setting for hole size is 0, which is off. See Defining Imagery Resources for more details about hole size.
Use this option to specify the pixel value for NoData in the terrain
data (the pixel values to include in the mask). Multiple values
may be specified in this field, including ranges (two numbers separated
by a colon ":") and individual values. For example,
-99999:0
is
the default which will mask any pixel value from -99999
through 0
, inclusive.
The values -99999
and 0
alone, can be masked
by using -99999, 0
instead
of -99999:0
. Alternatively, ‘-99999:-32768, 32768:999999’
means mask
pixel values -99999
through -32768
and 32768
through 999999
.
Select Have Mask if you have a corresponding alpha mask or file
for your source. Google Earth Enterprise Fusion automatically applies
the mask file to the source file. The mask for your input must be located
in the same folder as the source file, and the file name must match the
name of the source file with -mask
appended. For example,
if your source file is called NewYork.tif
, its mask file
must be named NewYork-mask.tif
.
You might select the Have Mask option in a situation where your terrain data is bounded by water, and a significant portion of the terrain is water. In that case, you would likely create a mask by hand in order to avoid processing the water data.
If you are creating a resource from multiple terrain source files, you cannot select Have Mask as the mask setting value.
Select No Mask only for base map terrain that extends to the entire
database, such as the gtopo30_4km
terrain data.
The simplest way to import source data is to create one resource from each data file. In some cases, though, it is actually necessary or just more efficient to import multiple source files into a single resource, called a mosaic. See Mosaic Options in Defining Imagery Resources for details.
When there is an overlap between the tiles, the pixels in the top tile obscure the elevation samples in lower tiles. To expose the elevation samples beneath the top tile, you specify the elevation value to make transparent.
Note: The Tile Fill setting makes the specified pixels transparent. Masking blocks the specified pixels. Both methods, however, define the pixels to be maintained and the pixels that show through.
For example:
Note: 1.Google Earth Enterprise Fusion applies the Tile Fill setting and other mosaic-related settings to the terrain to create a single larger image before it applies the mask. Any fill value you set here has no impact on the mask you use for the entire image.
The tolerance setting functions just as it does for fill values on the Auto Mask. The default tolerance is 0, which is adequate for most terrain data. However, you can adjust the tolerance to compensate for any possible loss in precision. Typically, a setting of 1 or 2 is the highest tolerance value required.
Google Earth Enterprise Fusion interprets elevation in meters, so the default selection for this option is Meters.
Enter the multiplier for Google Earth Enterprise Fusion to use when it converts the data to its metric equivalent. When you click OK, the number you enter here appears as the Elevation Units value.
The Source Files list displays the names of the source files selected for this resource. Click Add to add a source file. See Adding a Source File to a Resource for more information.
Note: You can select one or more source files to create a single resource, such as an terrain mosaic or a vector composite. If you use more than one source data file for a single resource, all of the source data must have the same projection and attribute values.
By using negative elevation resources, you can build elevation models for the world sea floors, lake beds, and below sea surface locations (Death Valley, CA) along with positive value terrain data for land masses. Properly importing negative elevation terrain requires additional data preparation, however, the end-to-end data workflow is the same for importing terrain resources and building terrain projects.
Previous versions of Fusion Pro would impose an artificial elevation floor value of 0 to any data sets with negative elevation values. This restriction was enforced because the Google Earth Enterprise Client (EC) could not display negative elevations. The Google Earth Enterprise Client software can display negative elevation models, as of version 5.0, and the Fusion artificial elevation ‘floor’ is no longer imposed. Data users can build terrain models with only positive values only – if no negative elevation terrain is available – or build terrain models with both positive and negative elevation data.
In the following example, a terrain project is built from the GTOPO world terrain dataset (1-kilometer resolution). It includes positive elevation values for land, a NoData value of -9999, a pixel value of 0 for the oceans and lakes, and a world-wide bathymetric terrain dataset with a NoData value of -9999 for all pixels out of the oceans and on the land. The entire globe has terrain coverage:
If you purchase preprocessed data from Google or receive preprocessed data from another Google Earth Enterprise Fusion user, it arrives as a complementary pair of folders. These folders share the same name but have different extensions. Folders with a .kip
extension are imagery data. Folders with a .ktp
extension are terrain data. Folders with a .kmp
extension are mask files.
You must use the Google Earth Enterprise Fusion shell commands to add preprocessed data to your asset root. See Importing Preprocessed Resources in the Command Line Reference chapter for complete details.
After you create any type of resource, you can use the Asset Manager to modify it in any of the following ways:
Note: When you save a modified resource, Google Earth Enterprise Fusion replaces the old resource definition with the new one. When you build that new resource, Google Earth Enterprise Fusion creates a new version. When you select a resource to include in a project, it is always the latest version of the resource. However, your modifications to a resource have no effect on earlier versions of that resource that were previously built into a database.
The Resource Editor for that resource type displays all of the current settings.
See the section on defining Vector, Imagery, or Terrain resources for details about each option.
If one or more source files have changed since you last saved the resource, a message at the bottom of this dialog informs you that the original source files have changed on disk. You do not have to change anything to take advantage of the updated source files; Google Earth Enterprise Fusion automatically includes any updated source files when you save the resource.
Google Earth Enterprise Fusion saves the resource in the same place with the same name. If you have already built the resource, you must rebuild it after making changes.


| 1252 | (A) | thay wastede clene at a wappe þer þe wallis stude |
| (C) | ---- no text ---- | |
| 1240 | (D) | The wightis made al wast þere þe wal stode |
| 1216 | (E) | ouer al þey made waast . þere þe walles stoode |
| (Ex) | ---- no text ---- | |
| 1281 | (L) | Maden wast at þe wappe þer þe walle stode |
| (P) | ---- no text ---- | |
| 1224 | (U) | The wyes maden al wast / there the walles stonden |
| 317 | (V) | Ałł þey made pleine . þere þe walle stoode |


Troll who taunted Jack Grealish over dead baby brother fractures skull after being hit by car
Alfie Perkins has shared pictures of his injuries after a speeding car failed to stop at a red light in Manchester city centre earlier this month
by Aaron Flanagan, https://www.mirror.co.uk/authors/aaron-flanagan/A young man who trolled Aston Villa footballer Jack Grealish over his dead baby brother has been left with a fractured skull after being hit by a car.
Alfie Perkins, 19, has shared photographs of his bloodied face and scarred body following the attack.
It came two weeks after Perkins avoided a jail sentence for posting vile messages on social media to Grealish about his brother Keelan.
Perkins claims that a driver failed to stop at a red light while driving at speed and hit him in Manchester city centre on November 2.
Writing on Twitter , Perkins said: "Life comes at you nearly as fast as speeding cars that don't stop on red lights do".
He added: "Didn't think it was possible for me to get any uglier but here we are with my face drooping to the right and the left side of it not working, you not reckon it's time I caught a break".
But Perkins believes that the incident was not "karma" after that was suggested by another Twitter user.
Perkins replied: "Leg it bruv, karma for laughing at somebody being dead is not fracturing your skull in two places hahaha."
Earlier this year, Perkins chugged nine pints of lager before watching Birmingham City vs Aston Villa, the Second City derby, following which he tweeted Grealish three horrific messages.
Grealish had just scored the winning goal in the game where he was also attacked by a rival fan on the pitch.
On one tweet, Perkins included a picture of Keelan's gravestone.
He tweeted: “He may have scored but will never bring his dead brother back and that brings me more satisfaction than anything else ever could.”
“Grealish went down quicker than his brother got lowered into the grave. Where’s your brother gone? Come on!”
Keelan fell victim to cot death in April 2000, aged just nine months old. Grealish was aged four at the time.
Perkins, an accountancy and finance student, was ordered to pay a fine and was seen smirking outside of court following the trial.
Keelan fell victim to cot death in April 2000, aged just nine months old. Grealish was aged four at the time.
Perkins, an accountancy and finance student, was ordered to pay a fine and was seen smirking outside of court following the trial.
When questioned about his smiles outside of court, Perkins tweeted: “I regret all of it but she says this like nobody would be smiling after being faced with the prospect of prison and the end result being only having to pay £350. Wallop.”
Perkins denied the charges against him and claimed that he was encouraged to post the tweets by those with him at the game.