In the second computer module, you will learn how to import files into R. In addition, you will learn how to select and order data within objects.
We can import flat files into R and start working with them. Flat files are typically files that contain table data. These types of files are saved as text files, csv files (comma-separated values) or tab delimited files. The first line in these types of files are the Field names that correspond to the columns of the dataframe in R. We can use the read.table()
function to read any file in table format to create a dataframe.
We will use different datasets. Therefore, you first need to download the following files from Teams:
Save the files in the same folder. The scripts that you have made can be saved in this folder as well. Use a proper name for your scripts to prevent chaos. Use for example the date (yy-mm-dd) + file name + version (e.g. 210907_RscriptCOO2_version1).
Let’s first use the manual way to import data as shown in the lecture: File > Import Dataset > From Text (base) > Import.
1. Import the Mammogram dataset manually.
You can see the command RStudio used to import the data in the Console. As you can see, the function RStudio used is read.csv()
. You can see that the only argument in the function is the path to your text file, including the name and extension (.txt) of your file. And R automatically assigned the data to a variable with the name of the file (Mammogram <- read.csv()
).
read.csv()
is a variant of the more general function read.table()
. ‘csv’ Indicates that the values are comma-separated. If you open the original .txt file, you can see that each line contains a row of values, which can be numbers or letters, and each value is separated by a comma. In addition, read.csv()
by default uses the first line in the text file as column names for the dataframe.
Now, let’s import another dataset by using the more general function read.table()
in your script. The advantages of scripting instead of manually importing are that you can find the command again when you need to, and you automatically open the data the next time you run this script.
2. Import the Heart_disease data by copying and editing the commands from your Console.
Change the variable name, the name of the .txt file and change the function to read.table().
As you can see when you view your new data, it is loaded as a dataframe with one column and multiple values separated by commas in one cell. read.table()
by default uses spaces in the text file to separate columns. Since our data is separated by commas instead of spaces, it is all put into one column. In addition, the first row is not used for column names. Therefore we need to define some new arguments (as shown in the lecture).
3. Adapt the following commands to correctly load the Heart_disease data:
Heart_disease <- read.table("C:/Folder1/Folder2/Heart_disease.txt",
header = TRUE,
sep = ",")
View(Heart_disease)
The next dataset we are going to import is the Countries dataset. This data does not only contain data of the type numeric (the other datasets did), but also text, such as country names.
4. What R data type is used to store text?
As explained before, many arguments in a function are set to default settings. One of the default settings of the read.table()
function is that strings (data type ‘character’) will be converted to factors in older R versions (before R 4.0.0).
5. What is the difference between the data types ‘character’ and ‘factor’?
6. Suppose a column in our dataframe contains 7 countries and the data type is factor. How many levels will this column have?
7. What will happen if we want to add another country to this column?
To keep our options open, we will import character strings as character data and not as factors. Therefore, we make sure to set the argument stringsAsFactors
to FALSE. We can call our dataframe df.countries. ‘df’ is short for dataframe, which helps us remember that the object with this name is a dataframe.
8. Import the dataset with the following commands:
df.countries <- read.table("C:/Folder1/Folder2/Countries.txt",
header = TRUE,
sep = ",",
stringsAsFactors = FALSE)
df.countries
Now, take a look at the document “CountriesTD.txt” and try to find what looks different in this document compared to the document “Countries”. You can see that the text is not separated anymore by commas but now by tabs. We can still use the same functions as before but now slightly different in that we must change the argument sep
to "\t"
which means that this file is tab delimited.
countriestd <- read.table("C:/Folder1/Folder2/CountriesTD.txt",
header = TRUE,
sep = "\t",
stringsAsFactors = FALSE)
countriestd
Notice how this gives the exact same table as before.
We can write this shorter as well, with the read.delim()
function:
countriestd2 <- read.delim("CountriesTD.txt",
stringsAsFactors = FALSE)
countriestd2
There are different ways to get information on our data. With these functions we can do some quality control, which is very important.
We can view the dataframe in our Console:
df.countries
We can see the whole dataframe at once since this dataframe is not so big. But this is not always the case. Then, you can use:
View(df.countries)# view whole dataframe in separate window
We can then check the class of the df.countries object:
class(df.countries)
With the function dim()
we can see how many rows and columns there are in this dataframe or we can see them separately using the nrow()
and ncol()
functions. The dim()
function is different from the length()
function shown previously. The length()
function is typically applied to a one-dimensional vector or array and returns the number of elements. The dim()
function, on the other hand, is applied on objects with multiple dimensions and gives you the number of rows and columns instead of the number of elements.
dim(df.countries)# the first being the number of rows, the second being the number of columns
nrow(df.countries)
ncol(df.countries)
We now have a sense of how big the dataset is. We can see the elements included in the dataset:
names(df.countries)
The head()
function allows us to see the first few rows of the dataset:
head(df.countries)
Note that you can now only see the first 6 rows. We can also narrow it down to the exact number of rows we want to see:
head(df.countries,3)# Selecting to only see the first three rows of the dataframe
We can do this the same with the last couple of rows with the tail() function:
tail(df.countries,2)# Selecting to only see the last two rows of the dataframe
Another useful function to study your data is the str() function. It compactly displays the structure of your data object.
str(df.countries)
To select data from any data type, use the index operator []
. In one-dimensional data, such as a vector, you provide one index. So, to select the third value of a vector, you use vector[3]
. For two-dimensional data, if you want to select one value you need to indicate both the row, and column. Therefore, you need two indices. dataframe[2, 5]
selects the value from the second row, fifth column.
Use the following commands to create a vector and select some values from this vector:
a <- c(2, 3, 4, 5)
a
Select the third element of vector a:
a[3] # The third element of vector a.
Select the first and third elements:
a[c(1, 3)] # returning the first and third elements of vector a.
You can also do calculations with selected elements in a vector:
a[1 + 3] # The fourth element of a vector.
a[1] + a[3] # Adding the first to the third element, returning the sum.
9. Now, select the first two elements of vector a.
You can also select multiple values in a row:
b <- 10:1
b[2:4] # Second to fourth element of vector b
You can also select a subset of a vector using logical values by asking R a question.
b > 3 # Which values in the vector of b are greater than 3?
10:4 are all greater than 3 and therefore return TRUE, 1, 2 and 3 are smaller or equal to 3 and therefore return FALSE.
Lastly, you can select by excluding values from your vector by using a minus: [-1]
selects every value except 1.
10. Select every value of b except the second and sixth.
We can assign new values to a specific subset that we selected. For example we can select the fifth element of vector b
and replace it with 0
, using the assignment operator <-
.
b[5] <- 0
We can also replace larger parts.
b[6:10] <- 9
As explained before, to select from a matrix you can use two indices. You can also select a whole column or row. Then, we have to specify whether we want to select either the rows or columns by carefully placing commas. The first index is for rows, the second for columns [rows, columns]
.
First, we make a new matrix with the following vectors:
vector.a <- c(1, 2, 3) # vector 1
vector.b <- c(4, 5, 6) # vector 2
vector.c <- c(7, 8, 9) # vector 3
11. Combine these vectors into columns of a new matrix, called matrix.a.
Now, you can select the first row:
matrix.a[1,] # select row 1 from matrix C
Now we see just the first row of the matrix created before. We can also show more than 1 row by making a vector in which we command to see both the first and second row c(1,2)
.
matrix.a[c(1,2),] # select rows 1 and 2 from matrix C
To select columns put your indices after the comma:
matrix.a[,c(1,3)] # select columns 1 and 3 from matrix C
12. Now, select the value in the third row, second column of matrix.a.
13. Can you describe what this next line of code does to matrix.a
?
matrix.a[2,1] <- 999
First, we need to create a list before we can subset it.
list1 <- list("hello","how","are","you","?")
list1[3] # calling for the third element in the list stored in list1
In a list you can store different data types of different lengths as well. You basically gather information under one object. Via that object name, you can then easily access these data. Let’s store our vector a, matrix.a, and list1 in a new list. For easy access we can also name the items in our list, using the following command:
list2 <- list(my_vec = a, my_matrix = matrix.a, my_list = list1)
Now, we can acces our vector with two commands. You can use the index number to select an item on the list []
, or you can use the name, with the $
sign:
list2[1] # first item on the list
list2$my_vec # the item called 'my_vec'
As you can see, when you use the $
to access the list item it provides you with a pop-up list of the names of your items and a symbol that resembles the data type. You can choose an item from this pop-up list by clicking on it, or select the first item by pressing ‘Tab’.
We can also select the first item of an item on our list, for example:
list2$my_list[4] # selects fourth item in the item called my_list
list2[[3]][4] # selects fourth item in the third item
14. Select the value in the second row, third column of the matrix in list2.
There are multiple ways to select data from a dataframe. You can use the index operator []
, you can use the dollar sign $
, or you can provide the name of a column as character data:
df.countries[4,] # selecting row 4
df.countries[,2] # selecting column 2
df.countries["Capital"] # selecting the column called Capital
df.countries[,"Capital"] # selecting the information in the column called Capital
df.countries$Capital # selecting the information in the column called Capital
Note that [,2]
, [,"Capital"]
, and $Capital
reproduced the information in the column as a vector with character data, while ["Capital"]
reproduced the whole column, as a dataframe with one column.
15. Use the class()
function to return the class for each of the dataframe access commands above.
One example is provided:
class(df.countries[4,])
We can also provide some statistics on our dataframe with these selection commands. Some basic statistic functions are mean()
, min()
, and max()
.
16. Calculate the mean of the inhabitants in the df.countries dataframe.
17. Calculate the minimum and maximum age in the Heart_disease dataframe, using the dollar sign to get suggestions for the column names.
We can also select using logical operators, explained in the previous COO. The expressions created with logical operators are also called Boolean expressions. To get an overview of the countries with more than 12,000,000 inhabitants, you can use:
df.countries["Inhabitants"] > 12000000
We created a boolean expression that shows us that the second and sixth countries have fewer than 12,000,000 inhabitants. We can also use this information to select data from another column. Therefore, we us this boolean expression we created to select rows. You can do this with the following commands:
many_inhabitants <- df.countries$Inhabitants > 12000000
df.countries[many_inhabitants, "Countries"]
We first created a vector containing the logical information [1] TRUE FALSE TRUE TRUE TRUE FALSE TRUE
. Then, we wanted to produce the country names with many inhabitants, so we used "Countries"
to select the column and our logical vector to select the rows. It then selected the information in the first, third, fourth, fifth and seventh row of the column ‘Countries’, because those equaled ‘TRUE’. It left out the names of the countries with fewer inhabitants, because those equaled ‘FALSE’.
18. Produce the country names of the countries with fewer than 12,000,000 inhabitants in a similar manner.
In this next bit, we will discuss the sort()
and order()
functions. The sort function returns the input data from lowest to highest value or in alphabetically ascending order. The order function returns the order in which the data are present in the object from lowest to highest value or in alphabetically ascending order. So for alphabet <- c("c", "a", "b"
, sort(alphabet)
will return: "a", "b", "c"
and order(alphabet)
would return 2, 3, 1
, because the second value (a) is the highest in the alphabet, then the third value (b), and then the first value (c).
So, we can (temporarily) sort the countries in our dataframe with:
sort(df.countries$Countries)
sort(df.countries$Countries, decreasing = TRUE)
As you can see in the df.countries dataframe, the actual order of the countries in the column ‘Countries’ has not changed. The sort function has just returned the column in alphabetical order in the Console.
We can use the order function to create a new dataframe with our data sorted alphabetically on country name:
countries_sorted1 <- df.countries[order(df.countries$Countries),] # ordering our countries alphabetically
countries_sorted1
The order we used is the following:
order(df.countries$Countries)
We use this order to indicate the rows to be used for our new dataframe. So, our new dataframe is constructed as follows: For the first row of countries_ordered1 the second row of the df.countries dataframe is used (containing Belgium), the second row is then filled with the third row of df.countries (containing France), and so on.
19. Now, create a dataframe called countries_sorted2, which is sorted on number of inhabitants.
In the lecture, the iris dataframe was sorted on two values. To try this yourself:
20. Import the iris_dataset.csv as a dataframe.
The following commands were used in the lecture:
volgorde <- order(iris_dataset$sepal_width)
iris_sorted <- iris_dataset[volgorde,]
iris_sorted <- iris_dataset[order(iris_dataset$sepal_width),]
iris_sorted <- iris_dataset[order(iris_dataset$flower, iris_dataset$sepal_width),]
iris_sorted <- iris_dataset[order(iris_dataset$flower, iris_dataset$sepal_width,
decreasing = c(FALSE, TRUE)),]
The iris_sorted dataframe has sorted the iris_dataset data first in increasing order on flower name, and then in decreasing order on sepal width.
Now, let’s try a similar sorting for our Heart_disease dataframe.
21. Create one new dataframe in which you sort the Heart_disease data first in decreasing order on sex, and then in increasing order on age.
It sometimes happens that you use a data.frame that is missing information. This will be displayed with a NA value (not available). It can be difficult to work with this because then, you are, for example, not able to calculate the mean. We must be cautious when drawing conclusions when our dataframe contains NAs. We can, for example remove observations with NA values.
Let’s work with the iris dataset with missing values from the lecture. We will use a new variable name for our incomplete dataset.
22. Import the iris_data_incomplete.txt as a dataframe called iris_data_incomplete.
23. Run the commands from the lecture:
summary(iris_data_incomplete)
which(is.na(iris_data_incomplete$sepal_width)) # which row contains NA?
iris_clean <- na.exclude(iris_dataset) # removes whole row containing NA
mean(iris_data_incomplete$sepal_width) # includes the NA value
mean(iris_data_incomplete$sepal_width, na.rm = TRUE) # excludes the NA value for this calculation
Note that the na.exclude()
function itself does not remove the row containing NA, only if you assign it to a variable, this new variable will contain the original dataset with the row containing NA removed.
You can also check the number of NA values with sum(is.na())
.
24. Check the number of NA values in the iris_dataset, iris_data_incomplete and iris_clean dataframes.
Now, take a look at the Grades.txt file. Use scripting to answer the following questions.
A1. Import the Grades.txt file as a dataframe and check whether it worked correctly.
A2. How many rows and columns does the dataframe have?
A3. What are the column names?
A4. What does the first part of this dataframe look like?
A5. Provide a summary of the data.
A6. Are there errors in your data?
A7. Calculate the number of NA values.
A8. Calculate the mean of each exam. Exclude the NA values in your calculation.
A9. Make a new dataframe that excludes the rows that contain NA values.
A10. For both exams, create a logical vector that shows which grades are bigger than 10.
A11. Use the vector that contains a ‘TRUE’ to return the grade that was bigger than 10.
A12. For both exams, create a logical vector that shows which grades are lower than 0.
A13. Use the vector that contains a ‘TRUE’ to return the grade that was lower than 0.
Since grades can vary from 0 to 10, we are quite certain that the grade which is higher than 10 contains a typo and should be 7.5. And the grade lower than 0 accidentially got a minus in front of it. You check this on the original exams, and indeed the grades should be 7.5 and 6.5 respectively. Now, you can change the grades, with the following commands:
A14. Change the name of the dataframe and check whether the grades you change are indeed in the 10th and 9th row, in your dataframe. Then, change the grades with the following commands:
grades_complete[10, "Exam1"] <- 7.5
grades_complete[9, "Exam2"] <- 6.5
A15. Create a vector of the grades in Exam1 sorted with the lowest grade first.
A16. Create a vector of the grades in Exam2 sorted with the highest grade first.
A17. Create a new, sorted dataframe which first sorts on the first exam and then on the second exam.
A18. Calculate the average grade again for both exams.
A19. What is the highest grade for the first exam?
A20. Create a logical vector that shows on which row(s) contain the highest grade.
Hint: use the code we used before for the number of inhabitants as an example of creating a logical vector:
many_inhabitants <- df.countries$Inhabitants > 12000000
A21. Now, use this vector to get the name of the person with the highest grade.
A22. Now, produce the name of the person with the lowest grade for the second exam.


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Please enter a comma (or space) seperated set of zipcodes to check the weather.
NOTE: The temperature is given to 2 decimal places at the most.
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|---|---|---|
| {{result.zipcode}} | {{result.temperatureInCelsius}} | {{result.temperatureInFahrenheit}} |


Manual control
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|
Pangolin
Pangolin is a lightweight rapid development library for managing OpenGL display / interaction and video input
|
Public Member Functions | |
| PacketStreamWriter (const std::string &filename, size_t buffer_size=100 *1024 *1024) | |
| void | Open (const std::string &filename, size_t buffer_size=100 *1024 *1024) |
| void | Close () |
| void | ForceClose () |
| PacketStreamSourceId | AddSource (PacketStreamSource &source) |
| PacketStreamSourceId | AddSource (const PacketStreamSource &source) |
| void | WriteSourcePacket (PacketStreamSourceId src, const char *source, const int64_t receive_time_us, size_t sourcelen, const picojson::value &meta=picojson::value()) |
| void | WriteSync () |
| void | WriteEnd () |
| const std::vector< PacketStreamSource > & | Sources () const |
| bool | IsOpen () const |


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| Time Finished: | 2021-03-08 16:38:35 +0100 |


Includes all classes related to servlet Context:
ServletContextListener
s implementation
Classes that use servletContext in order to link Spring context to/from it
For
Filter
see org.unitedinternet.cosmo.filters package.


| Package | Description |
|---|---|
| javafx.animation |
Provides the set of classes for ease of use transition based animations.
|
| javafx.application |
Provides the application life-cycle classes.
|
| javafx.beans.binding |
Characteristics of Bindings
|
| javafx.beans.property |
The package
javafx.beans.property defines read-only
properties and writable properties, plus a number of implementations. |
| javafx.beans.property.adapter | |
| javafx.collections.transformation | |
| javafx.concurrent |
Provides the set of classes for javafx.task.
|
| javafx.css |
Provides API for making properties styleable via CSS and for supporting
pseudo-class state.
|
| javafx.print |
Provides the public classes for the JavaFX Printing API.
|
| javafx.scene |
Provides the core set of base
classes for the JavaFX Scene Graph API.
|
| javafx.scene.canvas |
Provides the set of classes for canvas, an immediate mode style of rendering API.
|
| javafx.scene.chart |
The JavaFX User Interface provides a set of chart components that
are a very convenient way for data visualization.
|
| javafx.scene.control |
The JavaFX User Interface Controls (UI Controls or just Controls) are
specialized Nodes in the JavaFX Scenegraph especially suited for reuse in
many different application contexts.
|
| javafx.scene.control.cell |
The
javafx.scene.control.cell package is where all cell-related
classes are located, other than the core classes such as
Cell , IndexedCell ,
ListCell , TreeCell ,
and TableCell . |
| javafx.scene.effect |
Provides the set of classes for attaching graphical filter effects to JavaFX Scene Graph Nodes.
|
| javafx.scene.image |
Provides the set of classes for loading and displaying images.
|
| javafx.scene.layout |
Provides classes to support user interface layout.
|
| javafx.scene.media |
Provides the set of classes for integrating audio and video into Java FX
Applications.
|
| javafx.scene.paint |
Provides the set of classes for colors and gradients used to fill shapes and
backgrounds when rendering the scene graph.
|
| javafx.scene.shape |
Provides the set of 2D classes for defining and performing operations on
objects related to two-dimensional geometry.
|
| javafx.scene.text |
Provides the set of classes for fonts and renderable Text Node.
|
| javafx.scene.transform |
Provides the set of convenient classes to perform rotating, scaling,
shearing, and translation transformations for
Affine objects. |
| javafx.scene.web |
This package provides means for loading and displaying Web content.
|
| javafx.stage |
Provides the top-level container classes for JavaFX content.
|
| Class and Description |
|---|
| BooleanProperty
This class provides a full implementation of a
Property wrapping a
boolean value. |
| DoubleProperty
This class defines a
Property wrapping a double value. |
| IntegerProperty
This class defines a
Property wrapping an int value. |
| ObjectProperty
This class provides a full implementation of a
Property wrapping an
arbitrary Object . |
| ReadOnlyDoubleProperty
Super class for all readonly properties wrapping a
double . |
| ReadOnlyObjectProperty
Super class for all readonly properties wrapping an arbitrary
Object . |
| Class and Description |
|---|
| ReadOnlyBooleanProperty
Super class for all readonly properties wrapping a
boolean . |
| Class and Description |
|---|
| Property
Generic interface that defines the methods common to all (writable)
properties independent of their type.
|
| ReadOnlyBooleanProperty
Super class for all readonly properties wrapping a
boolean . |
| ReadOnlyIntegerProperty
Super class for all readonly properties wrapping an
int . |
| Class and Description |
|---|
| BooleanProperty
This class provides a full implementation of a
Property wrapping a
boolean value. |
| BooleanPropertyBase
The class
BooleanPropertyBase is the base class for a property
wrapping a boolean value. |
| DoubleProperty
This class defines a
Property wrapping a double value. |
| DoublePropertyBase
The class
DoublePropertyBase is the base class for a property
wrapping a double value. |
| FloatProperty
This class defines a
Property wrapping a float value. |
| FloatPropertyBase
The class
FloatPropertyBase is the base class for a property wrapping
a float value. |
| IntegerProperty
This class defines a
Property wrapping an int value. |
| IntegerPropertyBase
The class
IntegerPropertyBase is the base class for a property
wrapping a int value. |
| ListProperty
This class provides a full implementation of a
Property wrapping a
ObservableList . |
| ListPropertyBase
The class
ListPropertyBase is the base class for a property
wrapping an ObservableList . |
| LongProperty
This class defines a
Property wrapping a long value. |
| LongPropertyBase
The class
LongPropertyBase is the base class for a property wrapping
a long value. |
| MapProperty
This class provides a full implementation of a
Property wrapping a
ObservableMap . |
| MapPropertyBase
The class
MapPropertyBase is the base class for a property
wrapping an ObservableMap . |
| ObjectProperty
This class provides a full implementation of a
Property wrapping an
arbitrary Object . |
| ObjectPropertyBase
The class
ObjectPropertyBase is the base class for a property
wrapping an arbitrary Object . |
| Property
Generic interface that defines the methods common to all (writable)
properties independent of their type.
|
| ReadOnlyBooleanProperty
Super class for all readonly properties wrapping a
boolean . |
| ReadOnlyDoubleProperty
Super class for all readonly properties wrapping a
double . |
| ReadOnlyFloatProperty
Super class for all readonly properties wrapping a
float . |
| ReadOnlyIntegerProperty
Super class for all readonly properties wrapping an
int . |
| ReadOnlyListProperty
Super class for all readonly properties wrapping an
ObservableList . |
| ReadOnlyLongProperty
Super class for all readonly properties wrapping a
long . |
| ReadOnlyMapProperty
Super class for all readonly properties wrapping an
ObservableMap . |
| ReadOnlyObjectProperty
Super class for all readonly properties wrapping an arbitrary
Object . |
| ReadOnlyProperty
Generic interface that defines the methods common to all readable properties
independent of their type.
|
| ReadOnlySetProperty
Super class for all readonly properties wrapping an
ObservableSet . |
| ReadOnlyStringProperty
Super class for all readonly properties wrapping an
String . |
| SetProperty
This class provides a full implementation of a
Property wrapping a
ObservableSet . |
| SetPropertyBase
The class
SetPropertyBase is the base class for a property
wrapping an ObservableSet . |
| SimpleBooleanProperty
This class provides a full implementation of a
Property wrapping a
boolean value. |
| SimpleDoubleProperty
This class provides a full implementation of a
Property wrapping a
double value. |
| SimpleFloatProperty
This class provides a full implementation of a
Property wrapping a
float value. |
| SimpleIntegerProperty
This class provides a full implementation of a
Property wrapping a
int value. |
| SimpleListProperty
This class provides a full implementation of a
Property wrapping an
ObservableList . |
| SimpleLongProperty
This class provides a full implementation of a
Property wrapping a
long value. |
| SimpleMapProperty
This class provides a full implementation of a
Property wrapping an
ObservableMap . |
| SimpleObjectProperty
This class provides a full implementation of a
Property wrapping an
arbitrary Object . |
| SimpleSetProperty
This class provides a full implementation of a
Property wrapping an
ObservableSet . |
| SimpleStringProperty
This class provides a full implementation of a
Property wrapping a
String value. |
| StringProperty
This class provides a full implementation of a
Property wrapping a
String value. |
| StringPropertyBase
The class
StringPropertyBase is the base class for a property
wrapping a String value. |
| Class and Description |
|---|
| BooleanProperty
This class provides a full implementation of a
Property wrapping a
boolean value. |
| DoubleProperty
This class defines a
Property wrapping a double value. |
| FloatProperty
This class defines a
Property wrapping a float value. |
| IntegerProperty
This class defines a
Property wrapping an int value. |
| LongProperty
This class defines a
Property wrapping a long value. |
| ObjectProperty
This class provides a full implementation of a
Property wrapping an
arbitrary Object . |
| Property
Generic interface that defines the methods common to all (writable)
properties independent of their type.
|
| ReadOnlyBooleanProperty
Super class for all readonly properties wrapping a
boolean . |
| ReadOnlyBooleanPropertyBase
Base class for all readonly properties wrapping a
boolean . |
| ReadOnlyDoubleProperty
Super class for all readonly properties wrapping a
double . |
| ReadOnlyDoublePropertyBase
Base class for all readonly properties wrapping a
double . |
| ReadOnlyFloatProperty
Super class for all readonly properties wrapping a
float . |
| ReadOnlyFloatPropertyBase
Base class for all readonly properties wrapping a
float . |
| ReadOnlyIntegerProperty
Super class for all readonly properties wrapping an
int . |
| ReadOnlyIntegerPropertyBase
Base class for all readonly properties wrapping an
int . |
| ReadOnlyLongProperty
Super class for all readonly properties wrapping a
long . |
| ReadOnlyLongPropertyBase
Base class for all readonly properties wrapping a
long . |
| ReadOnlyObjectProperty
Super class for all readonly properties wrapping an arbitrary
Object . |
| ReadOnlyObjectPropertyBase
Base class for all readonly properties wrapping an arbitrary
Object . |
| ReadOnlyProperty
Generic interface that defines the methods common to all readable properties
independent of their type.
|
| ReadOnlyStringProperty
Super class for all readonly properties wrapping an
String . |
| ReadOnlyStringPropertyBase
Base class for all readonly properties wrapping a
String . |
| StringProperty
This class provides a full implementation of a
Property wrapping a
String value. |
| Class and Description |
|---|
| ObjectProperty
This class provides a full implementation of a
Property wrapping an
arbitrary Object . |
| Class and Description |
|---|
| BooleanProperty
This class provides a full implementation of a
Property wrapping a
boolean value. |
| IntegerProperty
This class defines a
Property wrapping an int value. |
| ObjectProperty
This class provides a full implementation of a
Property wrapping an
arbitrary Object . |
| ReadOnlyBooleanProperty
Super class for all readonly properties wrapping a
boolean . |
| ReadOnlyDoubleProperty
Super class for all readonly properties wrapping a
double . |
| ReadOnlyIntegerProperty
Super class for all readonly properties wrapping an
int . |
| ReadOnlyObjectProperty
Super class for all readonly properties wrapping an arbitrary
Object . |
| ReadOnlyStringProperty
Super class for all readonly properties wrapping an
String . |
| Class and Description |
|---|
| BooleanProperty
This class provides a full implementation of a
Property wrapping a
boolean value. |
| BooleanPropertyBase
The class
BooleanPropertyBase is the base class for a property
wrapping a boolean value. |
| DoubleProperty
This class defines a
Property wrapping a double value. |
| DoublePropertyBase
The class
DoublePropertyBase is the base class for a property
wrapping a double value. |
| FloatProperty
This class defines a
Property wrapping a float value. |
| FloatPropertyBase
The class
FloatPropertyBase is the base class for a property wrapping
a float value. |
| IntegerProperty
This class defines a
Property wrapping an int value. |
| IntegerPropertyBase
The class
IntegerPropertyBase is the base class for a property
wrapping a int value. |
| LongProperty
This class defines a
Property wrapping a long value. |
| LongPropertyBase
The class
LongPropertyBase is the base class for a property wrapping
a long value. |
| ObjectProperty
This class provides a full implementation of a
Property wrapping an
arbitrary Object . |
| ObjectPropertyBase
The class
ObjectPropertyBase is the base class for a property
wrapping an arbitrary Object . |
| Property
Generic interface that defines the methods common to all (writable)
properties independent of their type.
|
| ReadOnlyBooleanProperty
Super class for all readonly properties wrapping a
boolean . |
| ReadOnlyDoubleProperty
Super class for all readonly properties wrapping a
double . |
| ReadOnlyFloatProperty
Super class for all readonly properties wrapping a
float . |
| ReadOnlyIntegerProperty
Super class for all readonly properties wrapping an
int . |
| ReadOnlyLongProperty
Super class for all readonly properties wrapping a
long . |
| ReadOnlyObjectProperty
Super class for all readonly properties wrapping an arbitrary
Object . |
| ReadOnlyProperty
Generic interface that defines the methods common to all readable properties
independent of their type.
|
| ReadOnlyStringProperty
Super class for all readonly properties wrapping an
String . |
| StringProperty
This class provides a full implementation of a
Property wrapping a
String value. |
| StringPropertyBase
The class
StringPropertyBase is the base class for a property
wrapping a String value. |
| Class and Description |
|---|
| IntegerProperty
This class defines a
Property wrapping an int value. |
| ObjectProperty
This class provides a full implementation of a
Property wrapping an
arbitrary Object . |
| ReadOnlyIntegerProperty
Super class for all readonly properties wrapping an
int . |
| ReadOnlyObjectProperty
Super class for all readonly properties wrapping an arbitrary
Object . |
| StringProperty
This class provides a full implementation of a
Property wrapping a
String value. |
| Class and Description |
|---|
| BooleanProperty
This class provides a full implementation of a
Property wrapping a
boolean value. |
| DoubleProperty
This class defines a
Property wrapping a double value. |
| ObjectProperty
This class provides a full implementation of a
Property wrapping an
arbitrary Object . |
| ReadOnlyBooleanProperty
Super class for all readonly properties wrapping a
boolean . |
| ReadOnlyDoubleProperty
Super class for all readonly properties wrapping a
double . |
| ReadOnlyObjectProperty
Super class for all readonly properties wrapping an arbitrary
Object . |
| StringProperty
This class provides a full implementation of a
Property wrapping a
String value. |
| Class and Description |
|---|
| DoubleProperty
This class defines a
Property wrapping a double value. |
| Class and Description |
|---|
| BooleanProperty
This class provides a full implementation of a
Property wrapping a
boolean value. |
| DoubleProperty
This class defines a
Property wrapping a double value. |
| IntegerProperty
This class defines a
Property wrapping an int value. |
| ObjectProperty
This class provides a full implementation of a
Property wrapping an
arbitrary Object . |
| ReadOnlyDoubleProperty
Super class for all readonly properties wrapping a
double . |
| ReadOnlyObjectProperty
Super class for all readonly properties wrapping an arbitrary
Object . |
| StringProperty
This class provides a full implementation of a
Property wrapping a
String value. |
| Class and Description |
|---|
| BooleanProperty
This class provides a full implementation of a
Property wrapping a
boolean value. |
| DoubleProperty
This class defines a
Property wrapping a double value. |
| IntegerProperty
This class defines a
Property wrapping an int value. |
| ObjectProperty
This class provides a full implementation of a
Property wrapping an
arbitrary Object . |
| ReadOnlyBooleanProperty
Super class for all readonly properties wrapping a
boolean . |
| ReadOnlyDoubleProperty
Super class for all readonly properties wrapping a
double . |
| ReadOnlyIntegerProperty
Super class for all readonly properties wrapping an
int . |
| ReadOnlyObjectProperty
Super class for all readonly properties wrapping an arbitrary
Object . |
| ReadOnlyStringProperty
Super class for all readonly properties wrapping an
String . |
| StringProperty
This class provides a full implementation of a
Property wrapping a
String value. |
| Class and Description |
|---|
| BooleanProperty
This class provides a full implementation of a
Property wrapping a
boolean value. |
| ObjectProperty
This class provides a full implementation of a
Property wrapping an
arbitrary Object . |
| Class and Description |
|---|
| BooleanProperty
This class provides a full implementation of a
Property wrapping a
boolean value. |
| DoubleProperty
This class defines a
Property wrapping a double value. |
| IntegerProperty
This class defines a
Property wrapping an int value. |
| ObjectProperty
This class provides a full implementation of a
Property wrapping an
arbitrary Object . |
| Class and Description |
|---|
| BooleanProperty
This class provides a full implementation of a
Property wrapping a
boolean value. |
| DoubleProperty
This class defines a
Property wrapping a double value. |
| ObjectProperty
This class provides a full implementation of a
Property wrapping an
arbitrary Object . |
| ReadOnlyBooleanProperty
Super class for all readonly properties wrapping a
boolean . |
| ReadOnlyDoubleProperty
Super class for all readonly properties wrapping a
double . |
| ReadOnlyObjectProperty
Super class for all readonly properties wrapping an arbitrary
Object . |
| Class and Description |
|---|
| BooleanProperty
This class provides a full implementation of a
Property wrapping a
boolean value. |
| DoubleProperty
This class defines a
Property wrapping a double value. |
| IntegerProperty
This class defines a
Property wrapping an int value. |
| ObjectProperty
This class provides a full implementation of a
Property wrapping an
arbitrary Object . |
| ReadOnlyDoubleProperty
Super class for all readonly properties wrapping a
double . |
| ReadOnlyObjectProperty
Super class for all readonly properties wrapping an arbitrary
Object . |
| Class and Description |
|---|
| BooleanProperty
This class provides a full implementation of a
Property wrapping a
boolean value. |
| DoubleProperty
This class defines a
Property wrapping a double value. |
| IntegerProperty
This class defines a
Property wrapping an int value. |
| ObjectProperty
This class provides a full implementation of a
Property wrapping an
arbitrary Object . |
| ReadOnlyDoubleProperty
Super class for all readonly properties wrapping a
double . |
| ReadOnlyIntegerProperty
Super class for all readonly properties wrapping an
int . |
| ReadOnlyObjectProperty
Super class for all readonly properties wrapping an arbitrary
Object . |
| Class and Description |
|---|
| BooleanProperty
This class provides a full implementation of a
Property wrapping a
boolean value. |
| DoubleProperty
This class defines a
Property wrapping a double value. |
| ObjectProperty
This class provides a full implementation of a
Property wrapping an
arbitrary Object . |
| Class and Description |
|---|
| BooleanProperty
This class provides a full implementation of a
Property wrapping a
boolean value. |
| DoubleProperty
This class defines a
Property wrapping a double value. |
| ObjectProperty
This class provides a full implementation of a
Property wrapping an
arbitrary Object . |
| StringProperty
This class provides a full implementation of a
Property wrapping a
String value. |
| Class and Description |
|---|
| BooleanProperty
This class provides a full implementation of a
Property wrapping a
boolean value. |
| DoubleProperty
This class defines a
Property wrapping a double value. |
| IntegerProperty
This class defines a
Property wrapping an int value. |
| ObjectProperty
This class provides a full implementation of a
Property wrapping an
arbitrary Object . |
| ReadOnlyDoubleProperty
Super class for all readonly properties wrapping a
double . |
| ReadOnlyObjectProperty
Super class for all readonly properties wrapping an arbitrary
Object . |
| StringProperty
This class provides a full implementation of a
Property wrapping a
String value. |
| Class and Description |
|---|
| DoubleProperty
This class defines a
Property wrapping a double value. |
| ObjectProperty
This class provides a full implementation of a
Property wrapping an
arbitrary Object . |
| ReadOnlyBooleanProperty
Super class for all readonly properties wrapping a
boolean . |
| Class and Description |
|---|
| BooleanProperty
This class provides a full implementation of a
Property wrapping a
boolean value. |
| DoubleProperty
This class defines a
Property wrapping a double value. |
| IntegerProperty
This class defines a
Property wrapping an int value. |
| ObjectProperty
This class provides a full implementation of a
Property wrapping an
arbitrary Object . |
| ReadOnlyDoubleProperty
Super class for all readonly properties wrapping a
double . |
| ReadOnlyIntegerProperty
Super class for all readonly properties wrapping an
int . |
| ReadOnlyObjectProperty
Super class for all readonly properties wrapping an arbitrary
Object . |
| ReadOnlyStringProperty
Super class for all readonly properties wrapping an
String . |
| StringProperty
This class provides a full implementation of a
Property wrapping a
String value. |
| Class and Description |
|---|
| BooleanProperty
This class provides a full implementation of a
Property wrapping a
boolean value. |
| DoubleProperty
This class defines a
Property wrapping a double value. |
| ObjectProperty
This class provides a full implementation of a
Property wrapping an
arbitrary Object . |
| ReadOnlyBooleanProperty
Super class for all readonly properties wrapping a
boolean . |
| ReadOnlyDoubleProperty
Super class for all readonly properties wrapping a
double . |
| ReadOnlyObjectProperty
Super class for all readonly properties wrapping an arbitrary
Object . |
| StringProperty
This class provides a full implementation of a
Property wrapping a
String value. |
Submit a bug or feature
For further API reference and developer documentation, see Java SE Documentation. That documentation contains more detailed, developer-targeted descriptions, with conceptual overviews, definitions of terms, workarounds, and working code examples.
Copyright © 2008, 2021, Oracle and/or its affiliates. All rights reserved. Use is subject to license terms. Also see the documentation redistribution policy.


Andreas Bommarius (Georgia Tech, Atlanta, USA)
Frank Hollmann (TU Delft, The Netherlands)
Tukayi Kudanga (DTU Durban, South Africa)
Marilize Le Roes-Hill (CPUT, Cape Town, South Africa)
Marina Lotti (University of Milano-Bicocca, Italy)
Caroline Paul (TU Delft, The Netherlands)
Brett Pletschke (Rhodes University, Grahamstown, South Africa)
Dörte Rother (Forschungszentrum Jülich, Germany)
John Woodley (DTU, Denmark)
William Finnigan (University of Manchester, UK): RetroBioCat
Nicole Radde (Universität Stuttgart, Germany)
Johann Rohwer (University of Stellenbosch, South Africa): PySCeS
Frank Perrella (FDA-CDER, USA): BestCurvFit
Pedro Martins (University of Porto): interferENZY
Dorothea Iglezakis (University of Stuttgart, Germany) : Dataverse
Ulrike Wittig (Heidelberg Institute for Theoretical Studies, Germany): SABIO-RK
Neil Swainston (University of Liverpool, UK)
Andreas Weidemann (Heidelberg Institute for Theoretical Studies, Germany)
Andrew McDonald (Beilstein-Institut, Frankfurt, Germany)
Nicole Jung (KIT Karlsruhe, Germany): Chemotion
The EnzymeML Project Team is responsible for the development of the EnzymeML standard, specifications and administrating EnzymeML community resources.


18 May 1999
Disease Outbreak Reported
Bolivia: Cases of sylvatic yellow fever are still occurring, bringing the total number of confirmed cases for 1999 to 53 with 21 deaths (case fatality rate of 39.6%). All of the cases have occurred in the Department of Santa Cruz. A majority of the cases have been in males (75.5%) and in persons >15 years of age (76.9%). No cases in children <1 year have been reported. Mass yellow fever vaccination campaigns have occurred in the two municipalities that have been most affected- Cabezas and Postrervalle- achieving coverage rates of 93% and 97% respectively. The last case identified occurred on 15 April 1999. The goal of the Ministry of Health is to vaccinate 100% of the population in the endemic yellow fever zones this year.
Brazil: For 1999, the total number of confirmed sylvatic yellow fever cases has reached 18, with 3 deaths (case fatality rate of 16.7%). Fifty percent of the cases have been in persons >15 years old, 44.4% have been in children ages 1-15 years and 5.6% (representing one case) have been in children <1 year of age. Most of the cases have occurred in males (72.2%). The outbreak seems to be concentrated in two municipalities Afuá and Breves, in the State of Para. Reports from Brazil show that many of the cases from Afuá were identified through active surveillance and serological surveys after a death due to yellow fever occurred in February 1999.
Although a vaccination campaign was carried out in Afuá achieving 100% coverage, cases continue to occur due to the migration of unimmunized people into the area. Families are migrating to this area for work, primarily harvesting heart of palm. In the process of harvesting the trees, the habitat of the mosquitoes is disrupted and contact with humans, including unimmunized young children, occurs.
Colombia: To date in 1999, the total number of confirmed sylvatic cases is two and both cases were fatal. These two cases were in males, ages 17 and 21 years. The cases occurred in the Departments of Caqueta and Meta. No cases have been reported since January.
Peru: The first confirmed case of sylvatic yellow fever for 1999 was reported in a 25 year old male from the department of Loreto, Amazon region who died on 7 April. In response to this case, mass yellow fever vaccination was initiated in the area. Other cases have occurred in San Martin Department, in the districts of Moyobamba, Jepelacio and Alonso de Alvarado (26 cases), Ayacucho Department in the province of La Mar, district of Anco y Santa Rosa (12 cases), Huanuco Department (5 cases) and Junin Department (5 cases). Of these a total of 13 cases have been confirmed to date.


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IN THE HIGH COURT OF JUDICATURE AT PATNA Criminal Miscellaneous No.49049 of 2018 Arising Out of PS.Case No. -120 Year- 2018 Thana -BARUN District- AURANGABAD ====================================================== Sunil Kumar, Son of Ramesh Kumar Yadav, resident of Village Gogo Thengo, P.O.- Naur, P.S.- Nabinagar, District- Aurangabad (Bihar). .... .... Petitioner Versus 1. The State of Bihar. 2. The State of Bihar through the Principal Secretary cum Commissioner Department of Mines and Geology Government of Bihar, Patna. .... .... Opposite Parties ====================================================== Appearance : For the Petitioner/s : Mr. Sanjeet Kumar Singh For the Opposite Party/s : Mr. Dr. Rabindra Kumar ====================================================== CORAM: HONOURABLE MR. JUSTICE VINOD KUMAR SINHA ORAL ORDER
2 27-08-2018 Heard learned counsel for the petitioner.
Petitioner apprehends his arrest in connection with Barun P.S.Case No. 120 of 2018 registered for the offences punishable under Sections 379, 411, 420/34 of the Indian Penal Code, 4/40 of Bihar Mines and Minerals Concession Rules, 1972 and Section 15 of Prevention of Pollution Act, 1986.
Allegation as per FIR is that police intercepted 12 trucks loaded with sand, including the truck of the petitioner.
Submission of learned counsel for the petitioner is that petitioner is owner-cum-driver of the truck and as he was not there he could not produce the challan and he has valid challan for extracting the sand.
Patna High Court Cr.M isc. No.49049 of 2018 (2) dt.27-08-20182/2
Heard learned APP also.
Having heard both sides and in the facts and circumstances, let the petitioner, named above, in the event of his arrest or surrender, be released on bail on furnishing bail bond of Rs.25,000/- (Rupees twenty five thousand) with two sureties of the like amount each to the satisfaction of the Chief Judicial Magistrate, Aurangabad, in connection with Barun P.S.Case No. 120 of 2018, subject to the conditions as laid down under Section 438(2) Cr.P.C. and further condition is that one of the bailors shall be a local person having sufficient immoveable properties within the jurisdiction of court concerned.
(Vinod Kumar Sinha, J) spal/-
U


WELCOME
TO DELANI STUDIO
AMAZING PEOPLE ARE MAKING AMAZING DESIGNS IN A FUN ENVIRONMENT
AMAZING PEOPLE ARE MAKING AMAZING DESIGNS IN A FUN ENVIRONMENT
When you work with us, you are part of a team of committed collaboraters. All aspects of our software development process are intergrated, interactive and agile
Our approach unifies design development and product management to create exceptional products.We start each project by understanding your business goals, the user's needs and product requirements.
Then we halp translate them into effective and elegant solutions.
Before we sign a contract,or write a line of code, our team will spend the necessary time needed to understand your product vision.
The outcome of this scoping session is the proposal or high-level statement of work.
based on your requirements, we can provide a complete offering or just the pieces you need.
Our design practise offers a full range of services including brand startegy, interaction and visual design, and user experience
Throughout your project, our designers create and implement visual design and workflows, solicit user feedback and work with you to make sure what gets build is what is needed.
All engineers are fluent in the latest enterprise, mobile and web development, technologies.
They collaborate with your team to right and improve code on a daily basis, using practises such as test-driven development and pair programming.
Planning and development is iterative.Because we are constantly coding and testing, the products we build are always ready to go live.
This iterative process allows for changes as business requirements evolve.


Ask for what you want.
Get predictable results.
{
commonFriends(id1: 1, id2: 2) {
name,
address { city }
}
}
{
"commonFriends": [
{ "name": "Nobody", "address": { "city": "Nowhere" }},
...
]
}
{
commonFriends(id1: 1, id2: 2) {
name,
address { city },
friends { friends { friends { name } } }
}
}
{
"commonFriends": [
{
"name": "Nobody",
"address": { "city": "Nowhere" },
"friends": [{ "friends": [{ "friends": [{ "name": "Who" }]}]}]
},
...
]
}
(engine/run!!
{:friends1 (->FriendsOf 1)
:friends2 (->FriendsOf 2)})
;; => {:friends1 #{2 3}, :friends2 #{2 5}}
(muse/run!!
(muse/fmap
#(hash-map :friends1 %1 :friends2 %2)
(->FriendsOf 1)
(->FriendsOf 2)))
;; => {:friends1 #{2 3}, :friends2 #{2 5}}
(defrecord User [id]
data/Resolvable
(resolve! [_ env]
(d/future
(when-let [user (fetch-user! (:db env) id)]
(assoc user :friends (->FriendsOf (:id user)))))))
fewer (fmap ...)
calls
unnecessary data‽
(defrecord FriendsOf [id]
data/Resolvable
(resolve! [_ env]
(d/future
(let [friends (fetch-friend-ids! (:db env) id)]
(set (map #(->User %) friends))))))
(engine/run!! (->User 1))
;; => IllegalStateException: maximum batch count exceeded (33/32).
{:id projection/leaf
:name projection/leaf
:friends [{:name projection/leaf}]}
(engine/run!! (projection/apply (->User 1) ...))
;; => {:id 1,
;; :name "Someone",
;; :friends [{:name "Nobody"} {:name "NobodyElse"}]}
(projection/union
base-user
{:friends [(projection/extract :name)]})
(engine/run!! (projection/apply (->User 1) ...))
;; => {:id 1,
;; :name "Someone",
;; :friends ["Nobody" "NobodyElse"]}
tree projections are composable!
{:id projection/leaf
:name projection/leaf
:friends (projection/transform count [{}])}
(engine/run!! (projection/apply (->User 1) ...))
;; => {:id 1,
;; :name "Someone",
;; :friends 2}
(def Root
{:user (map->User {})
:users (map->Users {})
...})
(defn fetch-view-data!
[view]
(->> (build-projection view)
(projection/apply Root)
(engine/run!!)))


Ruleset Clone Implementation Rules
Language -
Description
The Clone Implementation ruleset contains a collection of rules that find questionable usages of the clone() method.
Rule ProperCloneImplementation::
TOC
Description
Object clone() should be implemented with super.clone().
- Message
- Object clone() should be implemented with super.clone()
- Class
- net.sourceforge.pmd.rules.XPathRule
- Reference
- -
- ExternalInfoUrl
- http://pmd.sourceforge.net/rules/clone.html#ProperCloneImplementation
- TypeResolution
- -
- Priority
- 2
Example
Example code snippet of this rule.
class Foo{
public Object clone(){
return new Foo(); // This is bad
}
}
Properties
Following properties are defined:
- Name
- xpath
- Description
- -
- Value
-
//MethodDeclarator
[@Image = 'clone']
[count(FormalParameters/*) = 0]
[count(../Block//*[
(self::AllocationExpression) and
(./ClassOrInterfaceType/@Image = ancestor::
ClassOrInterfaceDeclaration[1]/@Image)
])> 0
]
TOC
Rule CloneThrowsCloneNotSupportedException::
TOC
Description
The method clone() should throw a CloneNotSupportedException.
- Message
- clone() method should throw CloneNotSupportedException
- Class
- net.sourceforge.pmd.rules.XPathRule
- Reference
- -
- ExternalInfoUrl
- http://pmd.sourceforge.net/rules/clone.html#CloneThrowsCloneNotSupportedException
- TypeResolution
- -
- Priority
- 3
Example
Example code snippet of this rule.
public class MyClass implements Cloneable{
public Object clone() { // will cause an error
MyClass clone = (MyClass)super.clone();
return clone;
}
}
Properties
Following properties are defined:
- Name
- xpath
- Description
- -
- Value
-
//MethodDeclaration
[
MethodDeclarator/@Image = 'clone'
and count(MethodDeclarator/FormalParameters/*) = 0
and count(NameList/Name[contains
(@Image,'CloneNotSupportedException')]) = 0
]
[
../../../../ClassOrInterfaceDeclaration[@Final = 'false']
]
TOC
Rule CloneMethodMustImplementCloneable::
TOC
Description
The method clone() should only be implemented if the class implements the Cloneable interface with the exception of a final method that only throws CloneNotSupportedException.
- Message
- clone() method should be implemented only if implementing Cloneable interface
- Class
- net.sourceforge.pmd.rules.XPathRule
- Reference
- -
- ExternalInfoUrl
- http://pmd.sourceforge.net/rules/clone.html#CloneMethodMustImplementCloneable
- TypeResolution
- -
- Priority
- 3
Example
Example code snippet of this rule.
public class MyClass {
public Object clone() throws CloneNotSupportedException {
return foo;
}
}
Properties
Following properties are defined:
- Name
- xpath
- Description
- -
- Value
-
//ClassOrInterfaceDeclaration
[not(./ImplementsList/ClassOrInterfaceType
[@Image='Cloneable'])]
/ClassOrInterfaceBody/ClassOrInterfaceBodyDeclaration
[MethodDeclaration
[MethodDeclarator[@Image
= 'clone' and count(FormalParameters/*) = 0]]
[not((../MethodDeclaration[@Final = 'true'])
and Block[count(BlockStatement)=1]
/BlockStatement/Statement/ThrowStatement/Expression
/PrimaryExpression/PrimaryPrefix/AllocationExpression
/ClassOrInterfaceType[@Image = 'CloneNotSupportedException'])]]
TOC


{% trans 'Temporary password' %}
{% trans 'Selected user(s)' %}:
-
{% for u in for_users %}
- {{ u.get_full_name|default:u.username }}
{% trans 'Email' %}: {{ u.email|default:'-' }}
{% endfor %}
{% blocktrans %}If you continue a temporary password will be set for these users. They will be required to change their password on first usage. {% endblocktrans %}


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Welcome to our Export-Ready Questionnaire
We’ve put together a few simple questions to help you (and us) understand where you are on your export journey, and how we can help you reach your goals.
Along the way, we’ll point you in the direction of any relevant articles and resources on our website.
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Researchers growing bacterial cultures for protein expression must repeatedly determine the cell population manually by spectrophotometry before adding the inducing agent. This is a tedious, time-consuming task, that distracts from other work and increases the risk of making mistakes. Therefore, it would be beneficial to automate the process of optical density measurement. As no small-scale affordable device is commercially sold yet, we - a group of science and engineering students from Imperial College London - decided to fill the market gap. We aim to allow laboratories, schools, and individuals to enjoy their research at a high quality and convenience.
Our product is a small device that acts as a simple spectrophotometer. Light is emitted from a laser diode at a wavelength of 660nm, passes through the sample bacterial culture, and is detected by a photo diode. When passing through the solution, cells scatter the light. Our product is designed to use the difference in electrical signal strength between the laser and photo diodes to determine the absorbance and therefore cell population of the sample solution.
The BactViewer consists of two units. One part is a cuboid base that contains the electronics for absorbance measurements, magnets to position unit two, and Bluetooth to connect to your devices. It is placed underneath the sample flask. The base is designed not to come into contact with the sample solution, to avoid any contamination. This means that the base does not need to be sterilised completely to avoid the risk of damaging electronic components, but its smooth outer surface is designed to be cleaned easily.
The second unit is a mirror mounted with two magnets. This unit is dropped into the solution and will position itself automatically by the magnets being attracted to the base, which ensures that the mirror does not move during rigorous shaking in an incubator. Light from the laser diode is passed into the solution, is reflected off the mirror, and is the passed back through the solution to the photo diode. The mirror unit is a very simple, small unit that is easy to sterilise using either autoclaving or a solvent.
Hardware Designer
Tna is our expert on evaluating product mechanical feasibility and integrity. She has previously worked in designing process equipment and characterising material properties in relation to her background in chemical engineering.
Programmer
Grandon programmed the product and is heavily involved in testing modifications. He is an electrical bioengineer specialising in automation, making him an expert in understanding customer needs.
Hardware Designer
Caul focused on designing and prototyping the product using Computer Aided Drawing (CAD) for 3D printing and laser cutting. With a background in bioengineering, he was also heavily involved in analysing bacterial growth research.
Circuit Designer
Kaimei is very experienced with Arduino and used this to design the product’s electrical circuitry. Taking a material science degree focusing on material selection, further allowed him to contribute to hardware selection.


Overview
The SharpVectors is packaged in several .NET assemblies. Here is the complete list of available assemblies to get you started on developing and using the library.
- SharpVectors.Core: This the core library defining all the required interfaces in the W3C SVG specifications, including the events and the style sheets interfaces. There is no official W3C interfaces defined for the .NET framework (like the Java, JavaScript and IDL interfaces), therefore the interfaces defined in this component are .NET specific, and not compactible in naming standards to the W3C interfaces.
- SharpVectors.Dom: This is an extension to the .NET Framework implementation of the XML DOM (XmlDocument) to support the SVG. The .NET XmlDocument class is extended to support the SVG interfaces defined in the
SharpVectors.Core
. - SharpVectors.Css: This is the implmentation of the style sheets interfaces defined in the
SharpVectors.Core
, and it is implemented as an extension to the XML DOM of the .NET framework. - SharpVectors.Model: This is the main implementation of the SVG DOM and interfaces. In includes the parser of the SVG documents, reducing the SVG file or stream to memory model of .NET objects. Note that this and the above assemblies do not depend on the GDI+ or WPF graphical primitives or objects.
- SharpVectors.Runtime.Wpf: This is an optional WPF library providing SVG object specific information at the runtime. This includes conversion classes to handle GlyphTypeface.FontUri, which will otherwise be hard-coded with the full path information that may not work on the user's machine, classes to handle embedded images etc.
- SharpVectors.Rendering.Wpf: This is WPF library, which handles the rendering of the SVG object to the WPF drawing objects.
- SharpVectors.Converters.Wpf: This is WPF library, which uses the SharpVectors.Rendering.Wpf library to perform actual conversion for viewing.
- SharpVectors.Rendering.Gdi: This is GDI+ library, which handles the rendering of the SVG object to the System.Drawing objects. This is less complete compared with the WPF renderer.
For the WPF components or assemblies, the dependencies are shown in the diagram below:
graph LR
B[SharpVectors.Dom] --> A[SharpVectors.Core]
C[SharpVectors.Css] --> A
D[SharpVectors.Model] --> A
E[SharpVectors.Rendering.Wpf] --> A
F[SharpVectors.Converters] --> A
E --> G[SharpVectors.Runtime]
E --> B
E --> C
E --> D
F --> G
F --> E
F --> D
F --> C
F --> B
D --> C
D --> B
C --> B
For the GDI+ components or assemblies, the dependencies are shown in the diagram below:
graph LR
B[SharpVectors.Dom] --> A[SharpVectors.Core]
C[SharpVectors.Css] --> A
D[SharpVectors.Model] --> A
E[SharpVectors.Rendering.Gdi] --> A
E --> B
E --> C
E --> D
D --> C
D --> B
C --> B
History
We believe understanding the beginning of this library or its initial goals will make it easy to understand why some features are implemented as it is currently.
- Years ago, Adobe decided to retired the only the most reliable SVG plugin for the Internet Explorer 6+.
- With no clear plans to implement native SVG support in browsers, a company using these features to create an interactive car wiring manual for repairing shops, decided to evaluate other options.
- With only one month to evaluate and present the options, we decided on WPF to take advantage of its flowdocument and animation features, combined with ClickOnce deployments.
- We needed to convert the SVG diagrams, but the only commercial option available was not rendering valid outputs, no options for user-defined fonts and it was obfuscated - it cannot be extended for our customized needs.
- Looking for a better solution, we decided to add WPF support to the abandoned SVG library SharpVectorGraphics (aka SVG#).
- We removed the scripting features (based on depreciated library), and separated the rendering component from the parsing component.
Now, since the shipped product will dynamically load the flowdocuments with the coverted SVG diagrams in XAML format:
- We provided an independent SharpVectors.Runtime.Wpf for viewing the XAML diagrams in the client environment.
- We also provided SvgDrawingCanvas to display the diagrams, SvgAnimator and SvgAnimationLayer (now modified) for animation.
- We created the ZAML format, a G-zip compression of the XAML files just like the SVGZ files, to reduce the download size and improve speed.
Well, we were disappointed with the results of the evaluation, the speed of WPF 3.5
on the expected basic specs PC in the repair shops, could not match the HTML/SVG
rendering speed in the browsers.
We released the updated library on CodePlex
for other developers to use - the effort could not be wasted! With the quick adoption by the community, some of the design flaws stayed to avoid breaking changes.
- The SharpVectors.Converters.Wpf library was later added due to increased demand for specialized converters and controls.
In the Version 2.0, we will finally make some breaking changes, including
- The SharpVectors.Converters.Wpf, SharpVectors.Runtime.Wpf and SharpVectors.Rendering.Wpf will be combined.
- SharpVectors.Runtime.Wpf namespace will be removed.
- .NET 4.0 (and maybe .NET 4.5) supports will be dropped. It makes no sense, since there is no feature change in WPF, but we can take advantage of C# improvements.
Further Information
For further information, click the documentation links below:


5 Simulation
Ali was hearing a lot of people talk about “what if” scenarios and frankly, the requests for new work was coming in too fast. After dealing with marketing and retail problems, they would keep coming back to ask more questions. “What if we would purchase this many items?”, Boa and Blaise both asked. Even Castel was asking for information when the greenhouse situations would change. It seemed like Ali really needed to turn all of the code into functions…but a thought started chewing away at Ali brain.
“What if all of those things are just variables from different distributions”.
“If I know the past, I can figure out the distribution, and spin up some tables”.
The final straw was this email from Chaman, the head of grow operations:
Good afternoon Ali,
We have an interesting problem in our grow operations right now. Our plants are very successful, but a new strain isn’t really behaving how we would expect, given the expected probability of full maturation. Nearly 99.9% of these plants live and the maturation cycle runs about 65 days. We started with a 1000 plants on our last run, but we only ended up with 750 plants at the end of the growing cycle. We also had some weird pump failures; we’d think it would only happen about 1/100 times.
Ali knew that two other analysts might be able to offer some insight: Shashi knew everything statistical and Alex was the simulation wizard.
Starting at the beginning is always important, so Ali swung by Shashi’s cubicle.
5.1 Distributions
“You were right to come to me first”, Shashi said, “I’ll fill you in on a few distributions that might be helpful to you.”
“Distributions drive every single part of simulation – every event that you can ever imagine comes from some type of distribution.”, Shashi said.
5.1.1 Normal Distribution
“For our normal distribution, we know the \(\mu\) and \(\sigma\).”
“It is likely the most common and you’ll find that a lot of processes are normally distributed.”
“You might get customer data and want to test if a variable is normally distributed.”
“Let’s start by creating a normal distribution.”
normal_variable <- rnorm(n = 5000, mean = 2.5, sd = .5)
“And an exponential distribution…I’ll tell you more about that in a few minutes.”
exponential_variable <- rexp(n = 5000, rate = 2.5)
“We can check both with a qq plot for normality.”
qqnorm(normal_variable)
qqnorm(exponential_variable)
“The normal distribution will follow the diagonal perfectly, but the exponential looks like it curves down”.
“If you ever want to test for the normal distribution, you can just use the Shapiro test.”
shapiro.test(normal_variable)
Shapiro-Wilk normality test
data: normal_variable
W = 0.99966, p-value = 0.5733
shapiro.test(exponential_variable)
Shapiro-Wilk normality test
data: exponential_variable
W = 0.81236, p-value < 2.2e-16
“Think about it like this”, Shashi said, “We are trying to test if our observed distribution is significantly different than a normal distribution.”
“We would want to see a p-value above .05 to suggest that we might be dealing with a normally-distributed variable.”
“Clearly, the exponential distribution is significantly different.”
“That is awesome!”, Ali said.
5.1.2 Binomial Distribution
“Anything that has two outcomes – dead/alive, failure/success, missed/made – can be modeled with a binomial distribution.”
5.1.3 Exponential Distribution
“We can only know one thing about the exponential distribution: \(\mu\) (also expressed as a rate).”
“Just about any arrival process can be approximated by an exponential distribution.”
“That rate parameter is a bit confusing…the easiest way to express it is as a ratio.”
“If 3 people enter the store every minute and a half, than it would be a rate of 3/1.5”.
“You could also just put the average rate in.”
“They are really the same thing.”
5.1.4 Poisson Distribution
“The poisson is an interesting distribution – it tends to deal with count-related variables. It tells us the probability of a count occurring. We know its \(\lambda\).”
“The \(\lambda\) is just a fancy way of saying the average number of events, or the incidence rate.”
5.1.5 Uniform Distribution
“While people tend to think about the Gaussian distribution as the most vanilla of all distributions, it really is not – I would say that distinction belongs to the uniform distribution.  Why? Because knowing the min and max will tell us that there is an equal probability of drawing a value anywhere within that range.”
“Sound cool?”, Shashi asked.
“For sure!”, Ali replied, and went off to find Alex.
5.2 An Arguement
As soon as Ali started talking to Alex, a tangent started. “First and foremost, I want to set you straight on something: simulation is not what-if analysis.”
“What’s the different?”, Ali asked.
“The what-if analysis isn’t really guided by distributions, but more along the lines of low, medium, and high values.”
“I think I need an example.”, Ali said.
“I thought you’d never ask!”, Alex exclaimed.
“Let’s look at a really simple process: the number of people who come into a retail store.”
“Let’s say that every person who buys something in the store, shops for 20 minutes on average, with a standard deviation of 2.5 minutes.”
“We might just be interested to know how much total time those people are in the store.”
what_if_times <- c(low_value = 50,
mid_value = 100,
high_value = 150)
what_if_sums <- sapply(what_if_times, function(x) {
sum(rnorm(x, mean = 20, sd = 2.5))
})
what_if_sums
low_value mid_value high_value
988.4935 2015.7349 3004.1466
mean(what_if_sums)
[1] 2002.792
“That seems simple enough.”, remarked Ali. “Those answers really seem pretty obvious.”
Alex nodded. “They definitely do, but we have a potential problem here.”
Ali had absolutely zero idea where Alex was going.
“Let me give you some more info; we are giving all of those an equal probability of occurring.” Alex asked, “Does that seem reasonable?”
“Probably not.”, Ali admitted.
“The most common number of people that come into the score is 100, but the highs and lows rarely happen.”
“Check this distribution out:”
“In the triangular distribution, we have a few parameters: the lower limit, the upper limit, and the mode.”
“That looks wild!”, Ali smiled.
“Now, let’s see how we can incorporate this into a really small simulation.”
library(triangle)
triangle_draws <- rtriangle(n = 1000, a = 50, b = 150, c = 100)
tri_sum <- sapply(triangle_draws, function(x) {
sum(rnorm(x, mean = 20, sd = 2.5))
})
hist(tri_sum)
“Is the average wildly different?”, Alex asked.
“Nope!”, Ali said, “but that is a much better representation of what we would expect!”


Recipe 1.22. Printing Unicode Charactersto Standard OutputProblemYou want to print Unicode strings to standard output (e.g., for debugging), but they don't fit in the default encoding. SolutionWrap the sys.stdout stream with a converter, using the codecs module of Python's standard library. For example, if you know your output is going to a terminal that displays characters according to the ISO-8859-1 encoding, you can code: import codecs, sys sys.stdout = codecs.lookup('iso8859-1')[-1](sys.stdout) DiscussionUnicode strings live in a large space, big enough for all of the characters in every language worldwide, but thankfully the internal representation of Unicode strings is irrelevant for users of Unicode. Alas, a file stream, such as sys.stdout, deals with bytes and has an encoding associated with it. You can change the default encoding that is used for new files by modifying the site module. That, however, requires changing your entire Python installation, which is likely to confuse other applications that may expect the encoding you originally configured Python to use (typically the Python standard encoding, which is ASCII). Therefore, this kind of modification is not to be recommended. This recipe takes a sounder approach: it rebinds sys.stdout as a stream that expects Unicode input and outputs it in ISO-8859-1 (also known as "Latin-1"). This approach doesn't change the encoding of any previous references to sys.stdout, as illustrated here. First, we keep a reference to the original, ASCII-encoded sys.stdout: >>> old = sys.stdout Then, we create a Unicode string that wouldn't normally be able to go through sys.stdout: >>> char = u"\N{LATIN SMALL LETTER A WITH DIAERESIS}" >>> print char Traceback (most recent call last): File "<stdin>", line 1, in ? UnicodeError: ASCII encoding error: ordinal not in range(128) If you don't get an error from this operation, it's because Python thinks it knows which encoding your "terminal" is using (in particular, Python is likely to use the right encoding if your "terminal" is IDLE, the free development environment that comes with Python). But, suppose you do get this error, or get no error but the output is not the character you expected, because your "terminal" uses UTF-8 encoding and Python does not know about it. When that is the case, we can just wrap sys.stdout in the codecs stream writer for UTF-8, which is a much richer encoding, then rebind sys.stdout to it and try again: >>> sys.stdout = codecs.lookup('utf-8')[-1](sys.stdout) >>> print char ä This approach works only if your "terminal", terminal emulator, or other window in which you're running the interactive Python interpreter supports the UTF-8 encoding, with a font rich enough to display all the characters you need to output. If you don't have such a program or device available, you may be able to find a suitable one for your platform in the form of a free program downloadable from the Internet. Python tries to determine which encoding your "terminal" is using and sets that encoding's name as attribute sys.stdout.encoding. Sometimes (alas, not always) it even manages to get it right. IDLE already wraps your sys.stdout, as suggested in this recipe, so, within the environment's interactive Python shell, you can directly print Unicode strings. See AlsoDocumentation for the codecs and site modules, and setdefaultencoding in module sys, in the Library Reference and Python in a Nutshell; Recipe 1.20 and Recipe 1.21. |


Every weekday at {{vm.convertTime1(vm.customer.delivery.time)}}, you'll get an email with at least one great question to ask {{vm.kidsNames(' and ')}}.
If {{vm.teachersNames(' or ')}} submits a specific question for students, you'll see that, too!


C# code documentation
The golden rule of code documentation:
Try to document why (code design decisions) and avoid what (code design descriptions).
To keep up with the increasing complexity of the project, it’s very important to document the coding decisions. It’s one of the best practices.
Visual studio provides some elegant ways for code documentation to keep the code understandable. It can also understand the changes that one make on hard code.
Single or multi line comments
- Short (or long) functional descriptions
//single line comment
These are necessary to describe functionality in little.
/*
multiple
line
comments
*/
Avoid them. It is advisable to avoid writing essays about code. The end product shall be code not their long descriptions.
Collapsible regions
- Summary of the functional block
#region Some code block
//some code here
//some foo bar
//Fizz Buzz
//some unicorns
#endregion
Regions are collapsible. Just hover over the collapsed region and get a glance.
Summary
- Summary of the function or property
/// <summary>
/// Summary description for the function or property goes here
/// </summary>
- Summary of the function parameter
/// <param name="TestParameter">Summary description for the parameter goes here</param>
Visual studio changes this section after change of the parameter name.
- Summary of the returning stuff
///<returns>Summary description for the function result goes here</returns>
A simple example:
/// <summary>
/// Main class of the project
/// </summary>
class Program
{
/// <summary>
/// Main entry point of the program
/// </summary>
/// <param name="args">Command line args</param>
static void Main(string[] args)
{
//Do stuff
}
}


Want to keep track of the books you already read? Or the books that you are currently reading? Wait no more! Using this easy to use application you can do so in just a couple of steps! First, you click the New Book button, fill in the book information in the form, and click the green Add button, you will notice that the book gets added to the books' table at the top, and now you are tracking that book!
| Title | Author | Pages | Actions | Already Read? |
|---|


Pinhole¶
Note
The pinhole model is represented in a single vector as follows:
- where:
\((r_x, r_y, r_z)\) is the rotation vector in angle-axis convention.
\((t_x, t_y, t_z)\) is the translation vector.
-
torchgeometry.
inverse_pose
(pose, eps=1e-06)[source]¶ Function that inverts a 4x4 pose.
Parameters: points (Tensor) – tensor with poses. Returns: tensor with inverted poses. Return type: Tensor - Shape:
- Input: \((N, 4, 4)\)
- Output: \((N, 4, 4)\)
Example
>>> pose = torch.rand(1, 4, 4) # Nx4x4 >>> pose_inv = tgm.inverse_pose(pose) # Nx4x4
-
torchgeometry.
pinhole_matrix
(pinholes, eps=1e-06)[source]¶ Function that returns the pinhole matrix from a pinhole model
Parameters: pinholes (Tensor) – tensor of pinhole models. Returns: tensor of pinhole matrices. Return type: Tensor - Shape:
- Input: \((N, 12)\)
- Output: \((N, 4, 4)\)
Example
>>> pinhole = torch.rand(1, 12) # Nx12 >>> pinhole_matrix = tgm.pinhole_matrix(pinhole) # Nx4x4
-
torchgeometry.
inverse_pinhole_matrix
(pinhole, eps=1e-06)[source]¶ Returns the inverted pinhole matrix from a pinhole model
Parameters: pinholes (Tensor) – tensor with pinhole models. Returns: tensor of inverted pinhole matrices. Return type: Tensor - Shape:
- Input: \((N, 12)\)
- Output: \((N, 4, 4)\)
Example
>>> pinhole = torch.rand(1, 12) # Nx12 >>> pinhole_matrix_inv = tgm.inverse_pinhole_matrix(pinhole) # Nx4x4
-
torchgeometry.
scale_pinhole
(pinholes, scale)[source]¶ Scales the pinhole matrix for each pinhole model.
Parameters: - pinholes (Tensor) – tensor with the pinhole model.
- scale (Tensor) – tensor of scales.
Returns: tensor of scaled pinholes.
Return type: Tensor
- Shape:
- Input: \((N, 12)\) and \((N, 1)\)
- Output: \((N, 12)\)
Example
>>> pinhole_i = torch.rand(1, 12) # Nx12 >>> scales = 2.0 * torch.ones(1) # N >>> pinhole_i_scaled = tgm.scale_pinhole(pinhole_i) # Nx12
-
torchgeometry.
homography_i_H_ref
(pinhole_i, pinhole_ref)[source]¶ Homography from reference to ith pinhole
\[H_{ref}^{i} = K_{i} * T_{ref}^{i} * K_{ref}^{-1}\]Parameters: - pinhole_i (Tensor) – tensor with pinhole model for ith frame.
- pinhole_ref (Tensor) – tensor with pinhole model for reference frame.
Returns: tensors that convert depth points (u, v, d) from pinhole_ref to pinhole_i.
Return type: Tensor
- Shape:
- Input: \((N, 12)\) and \((N, 12)\)
- Output: \((N, 4, 4)\)
Example
>>> pinhole_i = torch.rand(1, 12) # Nx12 >>> pinhole_ref = torch.rand(1, 12) # Nx12 >>> i_H_ref = tgm.homography_i_H_ref(pinhole_i, pinhole_ref) # Nx4x4
-
class
torchgeometry.
InversePose
[source]¶ Creates a transformation that inverts a 4x4 pose.
Parameters: points (Tensor) – tensor with poses. Returns: tensor with inverted poses. Return type: Tensor - Shape:
- Input: \((N, 4, 4)\)
- Output: \((N, 4, 4)\)
Example
>>> pose = torch.rand(1, 4, 4) # Nx4x4 >>> transform = tgm.InversePose() >>> pose_inv = transform(pose) # Nx4x4
-
class
torchgeometry.
PinholeMatrix
[source]¶ Creates an object that returns the pinhole matrix from a pinhole model
Parameters: pinholes (Tensor) – tensor of pinhole models. Returns: tensor of pinhole matrices. Return type: Tensor - Shape:
- Input: \((N, 12)\)
- Output: \((N, 4, 4)\)
Example
>>> pinhole = torch.rand(1, 12) # Nx12 >>> transform = tgm.PinholeMatrix() >>> pinhole_matrix = transform(pinhole) # Nx4x4
-
class
torchgeometry.
InversePinholeMatrix
[source]¶ Returns and object that inverts a pinhole matrix from a pinhole model
Parameters: pinholes (Tensor) – tensor with pinhole models. Returns: tensor of inverted pinhole matrices. Return type: Tensor - Shape:
- Input: \((N, 12)\)
- Output: \((N, 4, 4)\)
Example
>>> pinhole = torch.rand(1, 12) # Nx12 >>> transform = tgm.InversePinholeMatrix() >>> pinhole_matrix_inv = transform(pinhole) # Nx4x4


#include <dune/xt/grid/walker.hh>
Public Types | |
| typedef GPV::GridViewType | type |
Public Member Functions | |
| GridPartViewHolder (GPV grid_part) | |
| const type & | real_grid_view () const |
Public Attributes | |
| const GPV | grid_view_ |
| const type | grid_part_ |
| typedef GPV::GridViewType Dune::XT::Grid::internal::GridPartViewHolder< GPV, false >::type |
|
inline |
|
inline |
| const type Dune::XT::Grid::internal::GridPartViewHolder< GPV, false >::grid_part_ |
| const GPV Dune::XT::Grid::internal::GridPartViewHolder< GPV, false >::grid_view_ |


{% load humanize %}
{% if submitted_count == 1 %} {{ submitted_by }} unsuccessfully submitted a grade for one student to the Registrar on {{ submitted_date }}. There was a problem processing this grade and it has not been submitted.{% else %}{{ submitted_by }} unsuccessfully submitted grades for {{ submitted_count|apnumber }} students to the Registrar on {{ submitted_date }}. There was a problem processing these grades and they have not been submitted.{% endif %} For more information, see the grade submission receipt.
No changes can be made through GradePage. To change submitted grades, use the Change of Grade form.
{% if grading_window_open %}To submit more grades for a different class, return to GradePage.
All grades must be submitted by {{ grade_submission_deadline }}.
{% endif %}


Believe it or not the system is actually sorta working in the case of @haejin.  Well, check out his blog. He does technical analysis of cryptos to determine which are good buys. It involves a quantum mentality that patterns exist in the stock ticker that can be used to understand universal trends of stocks and then pick good ones based on knowledge of those repeating patterns. He’s been doing this for 15 years and brings a measure of expertise to the system.
Does it work? Fuck if I know, but I believe that he is able to recognize patterns and it does seem some of those patterns are repetitive, but I’m not sure the extent to which it works. He’s made some good calls, but also didn’t call the massive correction. He had two posts in trending at the same time. One was calling for 23k BTC and the other saying corrections are healthy as we took a dive.
Some of his picks have seen substantial growth, but we’re in a bull market. Some of his stuff seems pretty cool, but there are other explanations. It’s enough that I’ve purchased a few picks on his recommendations, but I’m not betting a house on it.  I was wondering if he wanted to come on the Minnow Mayor Town Hall with me before all this stuff blew up.
Rancho
I found @haejin because another whale told me about him. He was getting 4000 views on his $20 rewards posts. It seems a lot of traders are coming here to figure out what @haejin is telling them to do.
I don’t know how Rancho found @haejin, but Rancho is one of the largest accounts on here and a very early investor in Steem, but he’s been passive af. The guy barely ever votes and almost never notices what’s going on here it would seem, but some how he found haejin and started hitting his posts, of which there are several a day, with massive $260+ upvotes. I don’t know what he liked because he never commented or anything, but maybe he made some money on a @haejin tip? Maybe he liked the views to rewards ratio? IDk, but he started dropping lovebombs on @haejin.
As a result of the extra love on his posts basically everything that haejin wrote went into trending right away. He picked up thousands of followers and a few prominent members of the community displeased by his share of the rewards pool
Flagging
As much I believe that Rancho has every single right to upvote posts to whatever level he wants I also believe this community has the power and authority to use their votes to nullify those rewards. If the community thinks that the technical analysis posts aren’t worth it they have every right to flag. This is actually how we as a community can turn trending page, which basically just states who has the most votes, into a trending page to where there’s some level of consensus on what a good article is.
 Flag it.
Right now there’s a lot of stigma against flags, but as long as we’re in linear rewards if we’re not flagging then we’re not actually helping to discover content. That’s bad for us as a platform. We used to be able to avoid some of this with exponential rewards, but those days are gone. Right now we’re often just discovering who can trade or buy votes the best. What we really need to do is figure out how to get good content on our front page so that people come here to find good content!
Violence
Now, I’ve stated before and stand by my argument that flagging is a type of violence. It’s financial violence. You’re removing value that other people put there. I get the argument that it’s not yours until pay day, but that’s more of an experienced trader perspective than a typical author on the block. They think it’s theirs, and when you take it away through a flag it feels like you have stolen from them, and I tend to see merit in both sides.
But the part that may not always be clear coming from the leader of a peace group is that sometimes violence is ok.  If you think that the reward pool is being raped or taken advantage of then by all means flag.  If you don’t we all suffer from their theft!
If you think the rewards are way out of line then flag. We’re not going to have real content, people, or project discovery if we never flag.
 So, flagging because of rewards disagreement is actually an ok thing to do. Sometimes it’s necessary for people abusing the pool. Sometimes it’s necessary to bring rewards down to sensible levels.  It can be scary af because you’re stepping into trouble when you flag right now because it’s a heated thing to do these days.
Also, it’s clouded because at other times people are just being a dick, opinion flagging, or going on offense… at that point the community may not respect your choices. You may simply be drawing attention to the exact person you’re trying to smush and that doesn’t always work out well.
If you’re a minnow you have to be careful flagging people because you don’t have a lot of steem power. Other accounts can nuke your rep, nuke your rewards, and basically revenge flag you to pieces.
My point however is that the system is mostly sorta working
Rancho used his power to vote.
This community used it’s power to down vote.
This is actually healthy. This isn’t making Steem a horrible place. This is actually a good thing for this platform to have some level of balance.
3 Unhealthy Parts
I don’t think @haejin’s posts are worth 260 each. I don’t think they are worth 0 each.  I don’t currently believe he has some agreement or anything like that with Rancho.  I respect the flaggers saying he’s rewarded too high. I’d ask you don’t take him down to 0, but let him continue to earn something on the posts. I’m sure you can find a healthy line, but I think 0 is taking it too far.  He is bringing a lot of views to the platform.
@haejin you’re following a handful of recent bad examples of how to deal with flagging poorly. You’re currently in the spotlight like no other person on the platform. This isn’t a time for a ragequit letter. You should be thankful to get this attention and work to mitigate some of the fall out. Shouting “well, I’m gonna take my ball and go home, and you guys are dicks” which is the rough equivalent of what you wrote isn’t a good response. I’d suggest you take a second to ponder a better less angry response and realize that the rest of this community has a point too.
Name calling. It would be nice if all the people could express frustration with actions and less with people. I know tempers get high, but I would continue to express that what we’re seeing is multiple people trying to do what they think is best for them and this platform. This can be a healthy discussion, but not when it focuses on attacking other people. That makes a good resolution harder. So, if folks could try to cool it with some language. The upvoting whales aren’t evil, the flagging whales aren’t evil, the author isn’t evil, and from what I’ve seen the commenters aren’t evil. They’re just people. All of them. If you could all try to be mildly civil with one another that would be swell.
 We need it for honest content and people discovery. I also don’t think it should cost the flagger money (they don’t receive curation rewards for flagging, so it costs money relative to just upvoting a different post). Flagging can be an incredibly valuable service to this community because it returns all those flagged rewards back to the community for the rest of us to share.
Flags can be healthy, flags can be useful, people upvoting and flagging are ok humans.
Whales have rights to upvote AND flag, and that can be a healthy part of this place.
If you’re getting flagged take a deep breath, realize it might be the biggest thing that could happen to your account, and try not to write up rage quit letters that put you in a negative light. Be gracious, see the story from the other perspective, and try to work with folks rather than against them.
This place is pretty amazing. Please treat it and one another with respect even when you disagree and especially when you’re mad.
This page is synchronized from the post: ‘Let’’s talk about flagging and use this recent @haejin stuff as an example.’


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{% extends "base.html" %} {% load custom_tags %} {% load humanize %} {% block content %}
| ID | INSTANCE NAME | WAN_DNS | DEPLOY COUNT | XMX | |
| {{ worker.id }} | {{ worker.instance_name }} | {{ worker.wan_dns }} | {{ worker.deploys.all|length }} | {{ worker.get_used_ram }}M / {{ worker.ram }}M | Check Stats |
| There is a total of {{ workers|length }} workers running. |


--- title: "John Prine Concert Refund" layout: "default" published: true ---
Red Butte Garden received notice from the John Prine family and Oh Boy Records that Mr. Prine had “an elevated risk for a stroke” and would undergo surgery to remedy the issue. Red Butte Garden and Mr. Prine’s team are working to reschedule the July 30 show. The current time period being considered is June of 2020.
If you purchased valid tickets through Ticketfly or in person at Red Butte Garden we will issue you a full refund now and place you on a priority list to purchase the same number of tickets for the re-scheduled date. When a new date has been set, we will send you an email with information about how to purchase tickets to the rescheduled show.
A couple of notes about what happens next:
If you purchased tickets online via Ticketfly:
If you purchased your tickets in person or over the phone from Red Butte Garden:
We are all disappointed that we will not be together Tuesday, July 30 as planned, and we send our best wishes for John’s full recovery and return to the stage.
If you have any other questions, please call the Red Butte Garden box office -<PHONE_NUMBER>


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| virtual scribe_ptr | new_scribe (native_socket fd)=0 |
| | Creates a new scribe from a native socket handle.
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| virtual expected< scribe_ptr > | new_tcp_scribe (const std::string &host, uint16_t port)=0 |
| | Tries to connect to host on given port and returns a scribe instance on success.
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| virtual doorman_ptr | new_doorman (native_socket fd)=0 |
| | Creates a new doorman from a native socket handle.
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| virtual expected< doorman_ptr > | new_tcp_doorman (uint16_t port, const char *in=nullptr, bool reuse_addr=false)=0 |
| | Tries to create an unbound TCP doorman bound to port , optionally accepting only connections from IP address in .
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| virtual datagram_servant_ptr | new_datagram_servant (native_socket fd)=0 |
| | Creates a new datagram_servant from a native socket handle.
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virtual datagram_servant_ptr | new_datagram_servant_for_endpoint (native_socket fd, const ip_endpoint &ep)=0 |
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| virtual expected< datagram_servant_ptr > | new_remote_udp_endpoint (const std::string &host, uint16_t port)=0 |
| | Create a new datagram_servant to contact a remote endpoint host and port .
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| virtual expected< datagram_servant_ptr > | new_local_udp_endpoint (uint16_t port, const char *in=nullptr, bool reuse_addr=false)=0 |
| | Create a new datagram_servant that receives datagrams on the local port , optionally only accepting connections from IP address in .
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virtual supervisor_ptr | make_supervisor ()=0 |
| | Creates a supervisor to keep the event loop running.
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| virtual bool | try_run_once ()=0 |
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virtual void | run_once ()=0 |
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virtual void | run ()=0 |
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| void | dispatch (F fun) |
| | Invokes fun in the multiplexer's event loop, calling fun() immediately when called from inside the event loop.
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| void | post (F fun) |
| | Invokes fun in the multiplexer's event loop, forcing execution to be delayed when called from inside the event loop.
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virtual multiplexer_backend * | pimpl () |
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const std::thread::id & | thread_id () const |
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execution_unit & | operator= (execution_unit &&)=default |
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execution_unit & | operator= (const execution_unit &)=default |
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| virtual void | exec_later (resumable *ptr)=0 |
| | Enqueues ptr to the job list of the execution unit.
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| actor_system & | system () const |
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proxy_registry * | proxy_registry_ptr () |
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void | proxy_registry_ptr (proxy_registry *ptr) |
| | Associated a new proxy factory to this unit.
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Low-level backend for IO multiplexing.


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{% extends 'layouts/layout.html' %} {% block content %}
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