Here, the sentence will be shown with highlighting...
Here, the raw parse output will be shown...
Here, the parse result will be shown as a tree...
Here, the parse result will be shown as a simplified tree...
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bold: Interface to Bold Systems API
A programmatic interface to the Web Service methods provided by
Bold Systems (<http://www.boldsystems.org/>) for genetic 'barcode' data.
Functions include methods for searching by sequences by taxonomic names,
ids, collectors, and institutions; as well as a function for searching
for specimens, and downloading trace files.
| Version: |
0.8.6 |
| Imports: |
xml2, crul (≥ 0.3.8), stringr, jsonlite, reshape, plyr, data.table, tibble |
| Suggests: |
roxygen2 (≥ 6.1.1), sangerseqR, knitr, testthat, vcr (≥
0.2.0) |
| Published: |
2018-12-14 |
| Author: |
Scott Chamberlain [aut, cre] |
| Maintainer: |
Scott Chamberlain <myrmecocystus at gmail.com> |
| BugReports: |
https://github.com/ropensci/bold/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/ropensci/bold |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| CRAN checks: |
bold results |
Downloads:
Reverse dependencies:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=bold
to link to this page.


Hello World
This is TEAM BLACK
Alarm
Calendar
Call
To-do
Just a testing page
Click Me
This will dissapear as well as the button when clicked


Where to Start With Developer Content
Commonly at developer focused companies the question from a marketing team will come up of “How do we get content that developers find interesting”? Or how can I get our developers to blog more? Or some other similar question. I general the question of creating content and engaging with developers is a very common one, and often theres a mismatch between what marketing wants to do and what developers appreciate.
Stop marketing
Forget trying to “market” to developers. Hopefully you at least have developers that believe in the product their building, if thats not the case then find a new product or a new team. If you’ve got a product targetted at developers and a team that believes in it then you’re already half way there to marketing it. Now back to the first point, forget trying to market it. Start with building some form of an audience, reputation, respect among other developers. This isn’t done through ads, email marketing, SEO or any of that. Its done by creating content that developers find interesting, as a first step forget your product entirely, but don’t worry we’ll get there soon enough.
Sourcing content
The first piece of it on finding content should actually be extremely simple. Typically engineers love sharing knowledge and information. At least once a week there’s an email out to all the engineers of a truly interesting approach to something. This content is often not in a perfect form for external publication, but quite close. In particular Heroku has one employee, an early employee and now architect, that every email he sends to such a group I pull down and save for future reading. Another example of this was one of the Heroku founder Adam Wiggins, you can find many similar emails slightly cleaned up as blog posts on his own blog.
Take these emails, find someone technical enough to clean them up and ship them. Your goals here are to simply build some level of connection with other developers. Now a lot of time these may not be in the right “voice” for your company blog. Thats quite fine, I’m a strong proponent of letting developers create their own personalitiies. The place for the content then may not always be on the company blog. In general I find there’s three groupings:
- Content for the company blog by an employee
- Content for an individuals blog (the caveat here is they need to regularly create content – every 6 months doesnt cut it)
- Content for an engineering blog (if you have enough of the above that blog infrequently this is a great home for it)
Don’t worry about the product yet
No really don’t worry about pitching your product. There was an awesome piece on the intercom blog talking about why most features fail and how companies pitch the details versus the problem they solve. Though there was a hidden gem in there:
Telling your customers something is a “ground up rewrite”, “HTML5 based”, “responsive” or anything like that will miss the mark unless you’re selling to developers.
For companies targetting developers this actually works really well, as a developer I care about the how. Simply put its interesting. Another great example of this is priceonomics. To be honest I only checked what they actually do in writing this post, but their posts I regularly find interesting.
Whats next
What do you want to know about? Creating a voice/brand, starting to pitch your product, content distribution? Let me know. A good about of my time is spent on these and happy to discuss further on whats valuable to others so we don’t have to suffer through painful marketing. Let me know<EMAIL_ADDRESS>or @craigkerstiens


--- date: "2019-08-22T15:33:00+02:00" title: Advanced and Miscellaneous weight: 13 ---
Factors are a special variable class in which data are stored internally as integers, but each integer level has a corresponding character value label that is used when the data are displayed. This can be partularly helpful when running statistical models which expect numeric (e.g. 0/1) inputs.
{{% notice tip %}}
Factors are similar to labeled values of categorical variables in Stata.
{{% /notice %}}
You can read more about factors here.
The package forcats provides useful tools for working with factor variables. You can read more about forcats here.
For example, in the automatically generated AJS dataset, the variable
sex
is a factor. In the underlying dataset the levels are F, M, and U, but we can attach longer character labels that are displayed.
# Use auto-generated dataset for this example
linelist_cleaned <- gen_data("AJS")
# the variable is a factor.
class(linelist_cleaned$sex)
## [1] "factor"
{{% notice tip %}}
To convert use as.factor()
linelist_cleaned$sex <- as.factor(linelist_cleaned$sex)
{{% /notice %}}
To change the labels for a variable, use the function fct_recode()
from the package forcats.
After providing the name of the factor give the conversion statements, separated by commas, in the format NEW = “OLD”. Note that everything on the right-hand side (RHS) must be a character. So, if you want to give a new label to missing values, use the special term NA_character_
.
First we use fct_count()
from the package forcats to see the values in the factor:
# View the levels present in the variable
fct_count(linelist_cleaned$sex)
## # A tibble: 3 x 2
## f n
## <fct> <int>
## 1 M 101
## 2 F 116
## 3 U 83
Now we re-label the values using fct_recode()
, also from the package forcats.
# Re-define the labels for the factor variable (pay attention to spelling!)
linelist_cleaned$sex <- fct_recode(linelist_cleaned$sex,
Male = "M",
Female = "F",
Unknown = "U")
# View the levels present in the variable
fct_count(linelist_cleaned$sex)
## # A tibble: 3 x 2
## f n
## <fct> <int>
## 1 Male 101
## 2 Female 116
## 3 Unknown 83
To change the arrangement of the levels, use fct_relevel()
.
This will impact the arrangement of the levels as displayed in graphs and tables. Give the name of the factor followed by the new arrangement (pay attention to spelling!).
# Provide new arrangement of levels
linelist_cleaned$sex <- fct_relevel(linelist_cleaned$sex, "Female", "Male", "Unknown")
# Check arrangement of levels
levels(linelist_cleaned$sex)
## [1] "Female" "Male" "Unknown"
If a variable is already a factor, it can be difficult to remove levels that do not have any observations. These levels will continue to appear in graphs, tables, etc.
For example: here we look at the values present in the variable sex. We want to convert those that are “Unknown” to proper R missing values (
NA
).
# Convert "Unknown" values to missing
linelist_cleaned$sex[linelist_cleaned$sex == "Unknown"] <- NA
# see the values and counts in the factor variable sex
fct_count(linelist_cleaned$sex)
## # A tibble: 4 x 2
## f n
## <fct> <int>
## 1 Female 116
## 2 Male 101
## 3 Unknown 0
## 4 <NA> 83
We can see that the value “Unknown” now has a count of zero, but it is still present as a level of the factor variable and will appear in tables and graphs. To remove this level entirely we use
fct_drop()
, which drops unused levels from a factor.
# Drop unused levels
linelist_cleaned$sex <- fct_drop(linelist_cleaned$sex)
# see the values and counts in the factor variable sex
fct_count(linelist_cleaned$sex)
## # A tibble: 3 x 2
## f n
## <fct> <int>
## 1 Female 116
## 2 Male 101
## 3 <NA> 83
{{% notice tip %}}
Use the argument only =
to drop specific levels: fct_drop(linelist_cleaned$sex, only = "Unknown")
{{% /notice %}}
%in%
operatorThe %in%
operator looks to see if any elements of a vector are within another vector. You can use this to filter your data to a specific set of values. It’s like a parallel version of ==
. A vector can be created with the function c()
, and a variable in a data frame is also a vector.
Here, we show how %in%
can be used to find which letters in the word “epidemiology” are vowels:
epi <- c("e", "p", "i", "d", "e", "m", "i", "o", "l", "o", "g", "y")
epi
## [1] "e" "p" "i" "d" "e" "m" "i" "o" "l" "o" "g" "y"
# use %in% to ask "for each letter in epi, is it in the list of vowels (a, e, i, o, u)?"
are_vowels <- epi %in% c("a", "e", "i", "o", "u")
# the result is a logical (TRUE/FALSE) vector
are_vowels
## [1] TRUE FALSE TRUE FALSE TRUE FALSE TRUE TRUE FALSE TRUE FALSE FALSE
# this new vector can be used to subset our original vector
# the following returns only the letters in epi that evaluated to TRUE in epi_vowels
epi[are_vowels]
## [1] "e" "i" "e" "i" "o" "o"
In the templates, %in%
can be used when creating the variable DIED
(when a patient died). The variable DIED
is logical (either TRUE
or FALSE
). It will be TRUE
if the value in exit_status
is either “DD” or “DOA” - those are the two character values present in the vector. You can add to or change the terms listed in the vector.
# DIED is set to TRUE if value in exit_status is "DD" or "DOA"
linelist_cleaned$DIED <- linelist_cleaned$exit_status %in% c("DD", "DOA")
You can read more about the %in%
here
The package dplyr contains functions that are used in the templates for joining (“merging”) data frames. There are many ways to conduct a join, and it is important that you use the correct option - otherwise you risk unexpectedly losing data!
It is wise to verify any join by inspecting the joined data frames and the resulting data frame.
There are more reference materials on dplyr join functions in the cheat sheet from UBC’s STAT545 course (by Jenny Bryan) and course notes from William Srules. The animations below were originally from https://github.com/gadenbuie/tidyexplain.
An inner join of data frames x and y (inner_join(x, y)
) returns only the rows from x which have matching values in y, and includes all the columns from both x and y.
The argument by =
specifies the column name in both data frames to compare for the join (it must be spelled the same in both data frames).
A left join of data frames x and y (left_join(x, y)
) prioritizes only the “left” data frame (x), thus returning all rows from x with all columns from x and y. If a row in x has multiple matches in y, all combinations are returned as separate rows.
The argument by =
specifies the column name in both data frames to compare for the join (it must be spelled the same in both data frames).
For example, a left join occurs in the AJS template when calculating attack rate by region, where cases
and population_data
are joined by their variable patient_origin
.
cases <- count(linelist_cleaned, patient_origin) %>% # cases for each region
left_join(population_data, by = "patient_origin") # merge population data
A full join of data frames x and y (full_join(x, y)
) returns all rows from x and y. If there are any rows in x not in y (or visa-versa), the missing values are NA
.
This is often used to inspect which rows are unique to a data frame. An anti join of data frames x and y (anti_join(x, y)
) returns the rows from data frame x that do not have matching values in data frame y. Only columns from x are returned.
R has the capability to make beautiful and versatile graphics using the package ggplot2 and its function ggplot()
. Below is a brief overview of the use of ggplot()
. There are too many aspects of ggplot()
to cover here, so it is highly encouraged that you download and review this ggplot cheatsheet.
For further reading, see this data visualization tutorial and this gallery of visualizations and extensions for inspiration.
A ggplot()
command is typically built using sub-commands linked by +
symbols. The sub-commands are executed one-after-another to build the final plot. The core components to provide are:
The first command ggplot()
creates an empty coordinate system to which layers of visualization and nuance are added.
aes()
argument establishes the variables to be mapped to the x and y axes.Secondly, the geom is specified, indicating whether the data should be displayed as points, lines, bars, a map, etc. Without a geom, the data will not be visualized and the coordinate plane will be empty.
Other optional sub-commands can address the scales (e.g scale_fill_brewer()
chooses a scale for the fill
aesthetic based on the Color Brewer 2 color scales), labels (e.g. labs(title = "Attack Rate by Region")
to define a specific title for the plot), themes (e.g. theme(text = element_text(size = 18))
makes all the text in the plot be a minimum size of 18 points), etc.
{{% notice tip %}}
A command beginning with ggplot()
will print the visualization but not save it. Using the assignment operator <-
in the first line will assign the visualization to an R object and save it for later use. Print it by running a command of just the object name.
{{% /notice %}}
In the “Place” section of the template, ggplot()
is used to create geospatial maps of attack rates and other indicators.
In these cases, the coordinate system reflects latitude/longitude, and geom_sf()
displays the spatial tiles of the regions contained in the map.
In the outbreak templates, detailed aesthetics parameters are managed by creating “theme” objects that can be referenced multiple in multiple ggplot()
commands.
Below, the object epicurve_theme
is assigned certain superficial plot parameters that are not associated with the data such as x-axis text angle, absence of legend title, and grid-line color. This object is then referenced in ggplot()
commands throughout the template.
# this sets the theme in ggplot for epicurves
epicurve_theme <- theme(
axis.text.x = element_text(angle = 45, hjust = 1, vjust = 1),
legend.title = element_blank(),
panel.grid.major.x = element_line(color = "grey60", linetype = 3),
panel.grid.major.y = element_line(color = "grey60", linetype = 3)
)
Likewise, this chunk establishes the settings for the labels in epidemic curve graphics. The settings for x-axis and y-axis labels, title, and subtitle are stored in the epicurve_labels
object, which is referenced in several epidemic curve ggplot()
commands.
# This sets the labels in ggplot for the epicurves
epicurve_labels <- labs(x = "Calendar week",
y = "Cases (n)",
title = "Cases by week of onset",
subtitle = str_glue("Source: MSF data from {reporting_week}")
)
A for loop is used to repeat or iterate code, making repetitive tasks more efficient. The “loop” repeats a series of commands, altering them slightly to account for different input values that are stored in a vector. This vector, or sequence of values, can be the values within a data frame variable.
In the outbreak templates, a for loop is used at the end of the Place analyses to create bar graphs and maps of regional attack rates for each epidemiological week.
The basic structure of a for loop is as follows:
for
(note the lowercase)in
{
}
A basic example for loop is below. number_list
is defined as a vector of four numbers. The for loop is set-up to examine each item (“i”) in number_list
. The only command in the for loop is to print the value of “i” plus 2. Finally, the brackets are closed. As the loop executes, it produces one output for each item in number_list
.
number_list <- c(102, 53, 14, 88)
for (i in number_list) {
print(i + 2)
}
## [1] 104
## [1] 55
## [1] 16
## [1] 90
In the outbreak templates, the for loop is more complex than the simple example above, but follows the same basic structure.
The loop is set-up for each item “i” of all the unique values in the variable epiweek
within the data frame cases
. This vector is a list of the epidemiological weeks with no repeated values. If you want to see this vector of epidemiological weeks, highlight and run just unique(cases$epiweek)
.
Numerous commands are located within the loop’s brackets { }
, but the most important is the first: this_ar <- filter(ar, epiweek == i)
. This command restricts the large data frame ar
to only the epiweek currently under consideration by the for loop. Thus, the data frame this_ar
will be different for each iteration of the for loop . All the subsequent steps (producing a map and a barplot) are performed on this filtered dataset.
The final step creates a combined plot of the map and barplot for the current epiweek “i” using the plot_grid()
function from the cowplot package. This plot is aligned horizontally based on the top and bottom of each plot. After producing the combined plot, the loop advances “i” to the next epiweek item in the vector, repeats all the commands in the brackets { }
, and produces a new combined plot.
# go through each epiweek, fiter and plot the data
for (i in unique(cases$epiweek)) {
this_ar <- filter(ar, epiweek == i)
# map
mapsub <- left_join(map, this_ar, by = c("name" = "Region"))
# choropleth
map_plot <- ggplot() +
geom_sf(data = mapsub, aes(fill = categories), col = "grey50") + # shapefile as polygon
coord_sf(datum = NA) + # needed to avoid gridlines being drawn
annotation_scale() + # add a scalebar
scale_fill_brewer(drop = FALSE,
palette = "OrRd",
name = "AR (per 10,000)") + # color the scale to be perceptually uniform (keep levels)
theme_void() # remove coordinates and axes
# plot with the region on the x axis sorted by increasing ar
# ar value on the y axis
barplot <- ggplot(this_ar, aes(x = reorder(Region, `AR (per 10,000)`),
y = `AR (per 10,000)`)) +
geom_bar(stat = "identity", col = "black", fill = "red") + # plot as bars (identity = as is)
geom_errorbar(aes(ymin = `Lower 95%CI`, ymax = `Upper 95%CI`), width = 0.2) + # add CIs
scale_y_continuous(expand = c(0, 0), limits = c(0, max_ar)) + # set origin for axes
# add labels to axes and below chart
labs(x = "Region", y = "AR (per 10,000)",
captions = str_glue("Source: MSF data from {reporting_week}")) +
epicurve_theme
# combine the barplot and map plot into one
print(
cowplot::plot_grid(
barplot + labs(title = str_glue("Epiweek: {i}")),
map_plot,
nrow = 1,
align = "h",
axis = "tb"
)
)
}
Here you can read more about for loops and iteration in R.


|
Figure 1
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TEM images of red CdSe/ZnS quantum dots (a) and green CdSe/Z ... |
|
Figure 2
|
UV–visible spectra (a) and PL spectra of CdSe/ZnS quantum do ... |
|
Figure 3
|
Cross-sectional EDS mapping of the green and red-mixed CdSe/ ... |
|
Figure 4
|
(a) Topographical AFM image and (b) a three-dimensional surf ... |
|
Figure 5
|
Green and red-mixed CdSe/ZnS (0.1 wt %) quantum dot–polymer ... |
|
Figure 6
|
CIE coordinates and PL spectra of CdSe/ZnS QD–polymer hybrid ... |
|
Figure 7
|
Green CdSe/ZnS (0.1 wt %) quantum dot–polymer hybrid light-e ... |
|
Figure 8
|
PL spectra and CIE coordinate of white light LED devices der ... |
|
Figure 9
|
(a) Color rendering index (CRI), (b) color temperature ( T c ... |
|
Figure 10
|
Plot of pull-off strength (adhesion) against 3-(trimethoxysi ... |


1. introduce¶
good good study ,day day up !
good good study ,day day up !
good good study ,day day up !
good good study ,day day up !oMygod
good good study ,day day up !oMygod
good good study ,day day up !
- one
- two three
- onechild
- twochild
- one
- two我是一个ingnew
onetwo
| Treat | Quantity | Description |
|---|---|---|
| Albatross | 2.99 | On a stick! |
| Crunchy Frog | 1.49 | If we took the bones out, it wouldn’t be crunchy, now would it? |
| Gannet Ripple | 1.99 | On a stick! |
1.1. read the docs¶
1.1.1. refer¶
See also
1.1.2. install¶
- apt install build-essential
- apt install python-dev
- apt install python-pip
- apt install python-setuptools
- apt install libxml2-dev
- apt install libxslt1-dev
- apt install zlib1g-dev
- apt install elasticsearch
- apt install redis-server
- pip install virtualenv
- virtualenv rtd && cd rtd
- source bin/activate
- apt install git
- git clone https://github.com/rtfd/readthedocs.org.git
- cd readthedocs.org
- pip install -r requirements.txt
- python manage.py migrate
- python manage.py collectstatic
- python manage.py loaddata test_data
- python manage.py runserver <IP_ADDRESS>:8000
- apt install texlive-latex-recommended
- apt install texlive-fonts-recommended
- apt install texlive-latex-extra
- apt install latexmk
- make latexpdf LATEXMKOPTS=”-silent”
- apt install texlive-xetex
- apt install latex-cjk-all
1.1.3. usage¶
install Sphinx
apt install python-pip -y pip install sphinx sphinx-autobuild pip install --upgrade pip 安装最新版pip mkdir doc && cd doc sphinx-quickstart make html
- conf.py
latex_engine=xelatex 解决无法生成pdf问题 texhash 不知道干啥用的 ‘preamble’: ‘’‘
usepackage{xeCJK} 解决无法显示中文的问题
‘’‘


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Basic ML prediction with EEG features¶
In this tutorial, we’ll introduce the following characteristics of DEEG package:
1. Data loading 2. Quality check of dataset 3. Signal banding (delta, theta, alpha, beta and gamma frequency bands) 4. Feature extraction 5. Prediction with machine learning models built by scikit-learn
Step 1: Load deeg and sklearn package, together necessary dependencies
[1]:
# !pip install deeg
import deeg
import sklearn
import numpy as np
Step 2: Load dataset. Here we used commonly-used DEAP dataset as an example
After loading, the program will outout the shape of data and labels
[6]:
# Specify the directory of your downloaded DEAP dataset below
data_dir = "/data1/ljq/datasets/EEG/DEAP/"
deap_dataset = deeg.load_DEAP(data_dir)
deap_data, deap_label = deap_dataset[0], deap_dataset[1]
Shape of data: (1240, 40, 8064)
Shape of labels: (1240, 4)
Step 3: Check whether the loaded dataset has missing values.
If missing value (NaN) occurs (“check_result” is not none), you may need to check your data.
[3]:
check_result = deeg.process.data_quality_check(deap_data)
print(check_result=={})
*** Data Quality Check ***
True
Step 4: Filter temporal signal by several bands for further feature extraction
This step will return a dictionary with keys as band name, and values as filtered signal
[15]:
deap_data, deap_label = deap_data[:100, ...], deap_label[:100, ...]
print(deap_data.shape, deap_label.shape)
(100, 40, 8064) (100, 4)
[16]:
deap_bands = deeg.process.band(deap_data)
Step 5: Feature extraction
Extract commonly-used EEG features on all frequency bands
[18]:
deap_features, names = deeg.features.cal_eeg_features(deap_bands["delta"], sf=1000, ws=2000)
for band in ["theta", "alpha", "beta", "gamma"]:
temp_features, names = deeg.features.cal_eeg_features(deap_bands[band], sf=1000, ws=2000)
deap_features = np.concatenate([deap_features, temp_features], axis=-1)
print(deap_features.shape)
(100, 40, 1001) (100, 40, 1)
(100, 40, 1001) (100, 40, 1)
(100, 40, 1001) (100, 40, 1)
(100, 40, 1001) (100, 40, 1)
(100, 40, 1001) (100, 40, 1)
(100, 40, 5025)
Step 6: Reshape the extracted features and corresponding labels to (samples, features/labels) format for ML operations
[19]:
deap_features = deap_features.reshape(deap_features.shape[0], -1)
print(deap_features.shape)
[[ 2.24507164e-09 3.11940765e-07 3.03837908e-06 ... 2.65723488e-03
1.05805435e+01 -7.59288472e+00]
[ 6.34293586e-07 4.16585084e-06 4.13876008e-05 ... 4.07333451e-03
2.54002987e+01 -7.78019837e+00]
[ 2.75466318e-07 1.81367955e-06 1.75321840e-05 ... 3.08742616e-05
4.47279497e+00 -7.70771464e+00]
...
[ 2.19018476e-06 1.62185397e-05 1.74806438e-04 ... -2.30126623e-03
3.67409821e+00 -7.64874794e+00]
[ 2.73488689e-07 1.79152229e-06 1.85823390e-05 ... 8.68680725e-04
1.21490870e+01 -7.42536039e+00]
[ 1.36297845e-06 1.02303531e-05 1.11483876e-04 ... -1.92467443e-03
6.84929673e+00 -7.64153889e+00]]
Step 7: Emotion prediction by ML models built by scikit-learn
Including train-test split, training and evaluation processes
For the convenience of illustration, we binarized the 9-level labels in to 0(1-4) and 1(5-9)
[29]:
from sklearn.model_selection import train_test_split
deap_label = (deap_label>=5).astype("int")
X_train, X_test, y_train, y_test = train_test_split(deap_features, deap_label, test_size=0.33, random_state=0)
[33]:
from sklearn.svm import SVC
model = SVC(kernel="rbf")
model.fit(X_train, y_train[:,0])
model.score(X_test, y_test[:,0])
[33]:
0.6363636363636364


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@ Olcott Memorial School, Besant Nagar
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--- title: "PXE booting from one PXE server to another" date: "2012-01-29" redirect_from: "/post/16690497775/pxe-booting-from-one-pxe-server-to-another" categories: - "PXE" - "bootchaining" - "gpxe" - "pxelinux" - "syslinux" ---
Linux 2.6.18, Syslinux 4.02, nasm 2.09
I've spent the past several days trying to figure out how to add a new PXE server to our environment at work. We have a corporate PXE server which I do not have access to, but I can request that a hook be put into place on the main PXE server and build my own. It seems this process is typically called PXE chaining.
Currently
CORP PXE SERVER MENU 1) Install Linux 2) Install Windows ..
Desired
+---------------------------------------------------------------+ | | \ / | CORP PXE SERVER (<IP_ADDRESS>) +--> QA PXE SERVER (<IP_ADDRESS>) | MENU | MENU | 1) Install Linux | 1) Update BIOS | 2) Install Windows | 2) Install Xen | 3) QA PXE Server------------+ 3) Return to CORP PXE Server--+
The best method of accomplishing this is with pxechain.com, which is part of the syslinux project. To set it up, you need at least version 4.04 of syslinux. Then your CORP server's /tftpboot/pxelinux.cfg/default would have an entry like this:
LABEL qapxe MENU LABEL QA PXE Server KERNEL pxechain.com APPEND <IP_ADDRESS>::pxelinux.0
The issue I ran into is that the corporate PXE server is on an old version of syslinux (4.02), which has a bug in pxechain.com/pxelinux.0 that causes the machine being PXE booted to hang when pxechain.com is loaded. So pxechain.com was not an option for me as I could not upgrade syslinux on the corporate server.
The second option I came across was gpxe. Turns out it works with syslinux 4.02. To configure it:
1) Download syslinux 4.02
2) Compile (make) the package with cd syslinux-4.02 ; make
3) Go into the syslinux-4.02/gpxe
4) Modify the pxelinux.gpxe script to look like this:
#!gpxe set use-cached 1 dhcp net0 set net0/209:string pxelinux.cfg/default set net0/210:string tftp://<IP_ADDRESS>/ imgload pxelinux.0 boot pxelinux.0
5) Run make again in the gpxe directory. This will produce a binary called gpxelinux.0 that contains the above script embedded within it. Install gpxelinux.0 on the corporate PXE server in the /tftpboot/ directory
6) Add an entry similar to this to /tftpboot/pxelinux.cfg/default:
LABEL qapxe MENU LABEL QA PXE Server KERNEL gpxelinux.0
The process for creating the menu entry on the QA PXE server that returns to the CORP PXE server is similar. Edit the pxelinux.gpxe script and change the IP address to <IP_ADDRESS>. Compile and place that gpxelinux.0 on the QA PXE server in the /tftpboot/ directory.
If you need to troubleshoot pxechain.com, you need to uncomment the %define DEBUG in modules/pxechain.asm and be sure to use nasm 2.09. nasm 2.03.01 on CentOS 5.5 wouldn't compile for me. I had better luck with Debian Squeeze, which has a modern nasm.


//# Ternary Conditional Operator This is the only operator in Swift that takes 3 arguments. It is used as a shortcut for if expression1 { expression2 } else { expression3 }. This operator also returns the value of expression2 or expression3 once it is evaluated, unlike an if statement. Even though this is handy, it can produce hard-to-read code, if nested / overused.


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Vector (F=qE+qv x B)
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Ayane
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I am Ayane and I am a bot who does a lot of things as:
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Made with ♥ by AugvstxD#1793


| | |
- django.db.models.base.Model(builtins.object)
-
- CommentReview
- Message
- ProductCatagory
- ProductOrders
- Products
- TransportOrders
- Transports
- WantedProducts
class CommentReview(django.db.models.base.Model) |
| |
CommentReview(*args, **kwargs)
CommentReview(id, commetned_by, comment, product_id, commented_date) |
| |
- Method resolution order:
- CommentReview
- django.db.models.base.Model
- builtins.object
Methods defined here:
- __str__(self)
- Return str(self).
comment = <django.db.models.query_utils.DeferredAttribute object>
commented_date = <django.db.models.query_utils.DeferredAttribute object>
- get_next_by_commented_date = _method(self, *, field=<django.db.models.fields.DateTimeField: commented_date>, is_next=True, **kwargs)
- get_previous_by_commented_date = _method(self, *, field=<django.db.models.fields.DateTimeField: commented_date>, is_next=False, **kwargs)
id = <django.db.models.query_utils.DeferredAttribute object>
product_id = <django.db.models.query_utils.DeferredAttribute object>
Data descriptors defined here:
- commetned_by
- Accessor to the related object on the forward side of a many-to-one or
one-to-one (via ForwardOneToOneDescriptor subclass) relation.
In the example::
class Child(Model):
parent = ForeignKey(Parent, related_name='children')
``Child.parent`` is a ``ForwardManyToOneDescriptor`` instance.
- commetned_by_id
Data and other attributes defined here:
- DoesNotExist = <class 'management.models.CommentReview.DoesNotExist'>
- MultipleObjectsReturned = <class 'management.models.CommentReview.MultipleObjectsReturned'>
- objects = <django.db.models.manager.Manager object>
Methods inherited from django.db.models.base.Model:
- __eq__(self, other)
- Return self==value.
- __getstate__(self)
- Hook to allow choosing the attributes to pickle.
- __hash__(self)
- Return hash(self).
- __init__(self, *args, **kwargs)
- Initialize self. See help(type(self)) for accurate signature.
- __reduce__(self)
- Helper for pickle.
- __repr__(self)
- Return repr(self).
- __setstate__(self, state)
- clean(self)
- Hook for doing any extra model-wide validation after clean() has been
called on every field by self.clean_fields. Any ValidationError raised
by this method will not be associated with a particular field; it will
have a special-case association with the field defined by NON_FIELD_ERRORS.
- clean_fields(self, exclude=None)
- Clean all fields and raise a ValidationError containing a dict
of all validation errors if any occur.
- date_error_message(self, lookup_type, field_name, unique_for)
- delete(self, using=None, keep_parents=False)
- full_clean(self, exclude=None, validate_unique=True)
- Call clean_fields(), clean(), and validate_unique() on the model.
Raise a ValidationError for any errors that occur.
- get_deferred_fields(self)
- Return a set containing names of deferred fields for this instance.
- prepare_database_save(self, field)
- refresh_from_db(self, using=None, fields=None)
- Reload field values from the database.
By default, the reloading happens from the database this instance was
loaded from, or by the read router if this instance wasn't loaded from
any database. The using parameter will override the default.
Fields can be used to specify which fields to reload. The fields
should be an iterable of field attnames. If fields is None, then
all non-deferred fields are reloaded.
When accessing deferred fields of an instance, the deferred loading
of the field will call this method.
- save(self, force_insert=False, force_update=False, using=None, update_fields=None)
- Save the current instance. Override this in a subclass if you want to
control the saving process.
The 'force_insert' and 'force_update' parameters can be used to insist
that the "save" must be an SQL insert or update (or equivalent for
non-SQL backends), respectively. Normally, they should not be set.
- save_base(self, raw=False, force_insert=False, force_update=False, using=None, update_fields=None)
- Handle the parts of saving which should be done only once per save,
yet need to be done in raw saves, too. This includes some sanity
checks and signal sending.
The 'raw' argument is telling save_base not to save any parent
models and not to do any changes to the values before save. This
is used by fixture loading.
- serializable_value(self, field_name)
- Return the value of the field name for this instance. If the field is
a foreign key, return the id value instead of the object. If there's
no Field object with this name on the model, return the model
attribute's value.
Used to serialize a field's value (in the serializer, or form output,
for example). Normally, you would just access the attribute directly
and not use this method.
- unique_error_message(self, model_class, unique_check)
- validate_unique(self, exclude=None)
- Check unique constraints on the model and raise ValidationError if any
failed.
Class methods inherited from django.db.models.base.Model:
- check(**kwargs) from django.db.models.base.ModelBase
- from_db(db, field_names, values) from django.db.models.base.ModelBase
Data descriptors inherited from django.db.models.base.Model:
- __dict__
- dictionary for instance variables (if defined)
- __weakref__
- list of weak references to the object (if defined)
- pk
|
class Message(django.db.models.base.Model) |
| |
Message(*args, **kwargs)
Message(id, user, full_name, email, subject, message) |
| |
- Method resolution order:
- Message
- django.db.models.base.Model
- builtins.object
Methods defined here:
- __str__(self)
- Return str(self).
email = <django.db.models.query_utils.DeferredAttribute object>
full_name = <django.db.models.query_utils.DeferredAttribute object>
id = <django.db.models.query_utils.DeferredAttribute object>
message = <django.db.models.query_utils.DeferredAttribute object>
subject = <django.db.models.query_utils.DeferredAttribute object>
Data descriptors defined here:
- user
- Accessor to the related object on the forward side of a many-to-one or
one-to-one (via ForwardOneToOneDescriptor subclass) relation.
In the example::
class Child(Model):
parent = ForeignKey(Parent, related_name='children')
``Child.parent`` is a ``ForwardManyToOneDescriptor`` instance.
- user_id
Data and other attributes defined here:
- DoesNotExist = <class 'management.models.Message.DoesNotExist'>
- MultipleObjectsReturned = <class 'management.models.Message.MultipleObjectsReturned'>
- objects = <django.db.models.manager.Manager object>
Methods inherited from django.db.models.base.Model:
- __eq__(self, other)
- Return self==value.
- __getstate__(self)
- Hook to allow choosing the attributes to pickle.
- __hash__(self)
- Return hash(self).
- __init__(self, *args, **kwargs)
- Initialize self. See help(type(self)) for accurate signature.
- __reduce__(self)
- Helper for pickle.
- __repr__(self)
- Return repr(self).
- __setstate__(self, state)
- clean(self)
- Hook for doing any extra model-wide validation after clean() has been
called on every field by self.clean_fields. Any ValidationError raised
by this method will not be associated with a particular field; it will
have a special-case association with the field defined by NON_FIELD_ERRORS.
- clean_fields(self, exclude=None)
- Clean all fields and raise a ValidationError containing a dict
of all validation errors if any occur.
- date_error_message(self, lookup_type, field_name, unique_for)
- delete(self, using=None, keep_parents=False)
- full_clean(self, exclude=None, validate_unique=True)
- Call clean_fields(), clean(), and validate_unique() on the model.
Raise a ValidationError for any errors that occur.
- get_deferred_fields(self)
- Return a set containing names of deferred fields for this instance.
- prepare_database_save(self, field)
- refresh_from_db(self, using=None, fields=None)
- Reload field values from the database.
By default, the reloading happens from the database this instance was
loaded from, or by the read router if this instance wasn't loaded from
any database. The using parameter will override the default.
Fields can be used to specify which fields to reload. The fields
should be an iterable of field attnames. If fields is None, then
all non-deferred fields are reloaded.
When accessing deferred fields of an instance, the deferred loading
of the field will call this method.
- save(self, force_insert=False, force_update=False, using=None, update_fields=None)
- Save the current instance. Override this in a subclass if you want to
control the saving process.
The 'force_insert' and 'force_update' parameters can be used to insist
that the "save" must be an SQL insert or update (or equivalent for
non-SQL backends), respectively. Normally, they should not be set.
- save_base(self, raw=False, force_insert=False, force_update=False, using=None, update_fields=None)
- Handle the parts of saving which should be done only once per save,
yet need to be done in raw saves, too. This includes some sanity
checks and signal sending.
The 'raw' argument is telling save_base not to save any parent
models and not to do any changes to the values before save. This
is used by fixture loading.
- serializable_value(self, field_name)
- Return the value of the field name for this instance. If the field is
a foreign key, return the id value instead of the object. If there's
no Field object with this name on the model, return the model
attribute's value.
Used to serialize a field's value (in the serializer, or form output,
for example). Normally, you would just access the attribute directly
and not use this method.
- unique_error_message(self, model_class, unique_check)
- validate_unique(self, exclude=None)
- Check unique constraints on the model and raise ValidationError if any
failed.
Class methods inherited from django.db.models.base.Model:
- check(**kwargs) from django.db.models.base.ModelBase
- from_db(db, field_names, values) from django.db.models.base.ModelBase
Data descriptors inherited from django.db.models.base.Model:
- __dict__
- dictionary for instance variables (if defined)
- __weakref__
- list of weak references to the object (if defined)
- pk
|
class ProductCatagory(django.db.models.base.Model) |
| |
ProductCatagory(*args, **kwargs)
ProductCatagory(id, name) |
| |
- Method resolution order:
- ProductCatagory
- django.db.models.base.Model
- builtins.object
Methods defined here:
- __str__(self)
- Return str(self).
id = <django.db.models.query_utils.DeferredAttribute object>
name = <django.db.models.query_utils.DeferredAttribute object>
Data descriptors defined here:
- productprice_set
- Accessor to the related objects manager on the reverse side of a
many-to-one relation.
In the example::
class Child(Model):
parent = ForeignKey(Parent, related_name='children')
``Parent.children`` is a ``ReverseManyToOneDescriptor`` instance.
Most of the implementation is delegated to a dynamically defined manager
class built by ``create_forward_many_to_many_manager()`` defined below.
- products_set
- Accessor to the related objects manager on the reverse side of a
many-to-one relation.
In the example::
class Child(Model):
parent = ForeignKey(Parent, related_name='children')
``Parent.children`` is a ``ReverseManyToOneDescriptor`` instance.
Most of the implementation is delegated to a dynamically defined manager
class built by ``create_forward_many_to_many_manager()`` defined below.
Data and other attributes defined here:
- DoesNotExist = <class 'management.models.ProductCatagory.DoesNotExist'>
- MultipleObjectsReturned = <class 'management.models.ProductCatagory.MultipleObjectsReturned'>
- objects = <django.db.models.manager.Manager object>
Methods inherited from django.db.models.base.Model:
- __eq__(self, other)
- Return self==value.
- __getstate__(self)
- Hook to allow choosing the attributes to pickle.
- __hash__(self)
- Return hash(self).
- __init__(self, *args, **kwargs)
- Initialize self. See help(type(self)) for accurate signature.
- __reduce__(self)
- Helper for pickle.
- __repr__(self)
- Return repr(self).
- __setstate__(self, state)
- clean(self)
- Hook for doing any extra model-wide validation after clean() has been
called on every field by self.clean_fields. Any ValidationError raised
by this method will not be associated with a particular field; it will
have a special-case association with the field defined by NON_FIELD_ERRORS.
- clean_fields(self, exclude=None)
- Clean all fields and raise a ValidationError containing a dict
of all validation errors if any occur.
- date_error_message(self, lookup_type, field_name, unique_for)
- delete(self, using=None, keep_parents=False)
- full_clean(self, exclude=None, validate_unique=True)
- Call clean_fields(), clean(), and validate_unique() on the model.
Raise a ValidationError for any errors that occur.
- get_deferred_fields(self)
- Return a set containing names of deferred fields for this instance.
- prepare_database_save(self, field)
- refresh_from_db(self, using=None, fields=None)
- Reload field values from the database.
By default, the reloading happens from the database this instance was
loaded from, or by the read router if this instance wasn't loaded from
any database. The using parameter will override the default.
Fields can be used to specify which fields to reload. The fields
should be an iterable of field attnames. If fields is None, then
all non-deferred fields are reloaded.
When accessing deferred fields of an instance, the deferred loading
of the field will call this method.
- save(self, force_insert=False, force_update=False, using=None, update_fields=None)
- Save the current instance. Override this in a subclass if you want to
control the saving process.
The 'force_insert' and 'force_update' parameters can be used to insist
that the "save" must be an SQL insert or update (or equivalent for
non-SQL backends), respectively. Normally, they should not be set.
- save_base(self, raw=False, force_insert=False, force_update=False, using=None, update_fields=None)
- Handle the parts of saving which should be done only once per save,
yet need to be done in raw saves, too. This includes some sanity
checks and signal sending.
The 'raw' argument is telling save_base not to save any parent
models and not to do any changes to the values before save. This
is used by fixture loading.
- serializable_value(self, field_name)
- Return the value of the field name for this instance. If the field is
a foreign key, return the id value instead of the object. If there's
no Field object with this name on the model, return the model
attribute's value.
Used to serialize a field's value (in the serializer, or form output,
for example). Normally, you would just access the attribute directly
and not use this method.
- unique_error_message(self, model_class, unique_check)
- validate_unique(self, exclude=None)
- Check unique constraints on the model and raise ValidationError if any
failed.
Class methods inherited from django.db.models.base.Model:
- check(**kwargs) from django.db.models.base.ModelBase
- from_db(db, field_names, values) from django.db.models.base.ModelBase
Data descriptors inherited from django.db.models.base.Model:
- __dict__
- dictionary for instance variables (if defined)
- __weakref__
- list of weak references to the object (if defined)
- pk
|
class ProductOrders(django.db.models.base.Model) |
| |
ProductOrders(*args, **kwargs)
ProductOrders(id, ordered_item, ordered_by, prouct_owner, order_date, order_destination, order_source_adress, orderer_optional_adress, accecpted) |
| |
- Method resolution order:
- ProductOrders
- django.db.models.base.Model
- builtins.object
Methods defined here:
- __str__(self)
- Return str(self).
accecpted = <django.db.models.query_utils.DeferredAttribute object>
- get_next_by_order_date = _method(self, *, field=<django.db.models.fields.DateTimeField: order_date>, is_next=True, **kwargs)
- get_previous_by_order_date = _method(self, *, field=<django.db.models.fields.DateTimeField: order_date>, is_next=False, **kwargs)
id = <django.db.models.query_utils.DeferredAttribute object>
order_date = <django.db.models.query_utils.DeferredAttribute object>
order_destination = <django.db.models.query_utils.DeferredAttribute object>
order_source_adress = <django.db.models.query_utils.DeferredAttribute object>
orderer_optional_adress = <django.db.models.query_utils.DeferredAttribute object>
Data descriptors defined here:
- ordered_by
- Accessor to the related object on the forward side of a many-to-one or
one-to-one (via ForwardOneToOneDescriptor subclass) relation.
In the example::
class Child(Model):
parent = ForeignKey(Parent, related_name='children')
``Child.parent`` is a ``ForwardManyToOneDescriptor`` instance.
- ordered_by_id
- ordered_item
- Accessor to the related object on the forward side of a many-to-one or
one-to-one (via ForwardOneToOneDescriptor subclass) relation.
In the example::
class Child(Model):
parent = ForeignKey(Parent, related_name='children')
``Child.parent`` is a ``ForwardManyToOneDescriptor`` instance.
- ordered_item_id
- prouct_owner
- Accessor to the related object on the forward side of a many-to-one or
one-to-one (via ForwardOneToOneDescriptor subclass) relation.
In the example::
class Child(Model):
parent = ForeignKey(Parent, related_name='children')
``Child.parent`` is a ``ForwardManyToOneDescriptor`` instance.
- prouct_owner_id
Data and other attributes defined here:
- DoesNotExist = <class 'management.models.ProductOrders.DoesNotExist'>
- MultipleObjectsReturned = <class 'management.models.ProductOrders.MultipleObjectsReturned'>
- objects = <django.db.models.manager.Manager object>
Methods inherited from django.db.models.base.Model:
- __eq__(self, other)
- Return self==value.
- __getstate__(self)
- Hook to allow choosing the attributes to pickle.
- __hash__(self)
- Return hash(self).
- __init__(self, *args, **kwargs)
- Initialize self. See help(type(self)) for accurate signature.
- __reduce__(self)
- Helper for pickle.
- __repr__(self)
- Return repr(self).
- __setstate__(self, state)
- clean(self)
- Hook for doing any extra model-wide validation after clean() has been
called on every field by self.clean_fields. Any ValidationError raised
by this method will not be associated with a particular field; it will
have a special-case association with the field defined by NON_FIELD_ERRORS.
- clean_fields(self, exclude=None)
- Clean all fields and raise a ValidationError containing a dict
of all validation errors if any occur.
- date_error_message(self, lookup_type, field_name, unique_for)
- delete(self, using=None, keep_parents=False)
- full_clean(self, exclude=None, validate_unique=True)
- Call clean_fields(), clean(), and validate_unique() on the model.
Raise a ValidationError for any errors that occur.
- get_deferred_fields(self)
- Return a set containing names of deferred fields for this instance.
- prepare_database_save(self, field)
- refresh_from_db(self, using=None, fields=None)
- Reload field values from the database.
By default, the reloading happens from the database this instance was
loaded from, or by the read router if this instance wasn't loaded from
any database. The using parameter will override the default.
Fields can be used to specify which fields to reload. The fields
should be an iterable of field attnames. If fields is None, then
all non-deferred fields are reloaded.
When accessing deferred fields of an instance, the deferred loading
of the field will call this method.
- save(self, force_insert=False, force_update=False, using=None, update_fields=None)
- Save the current instance. Override this in a subclass if you want to
control the saving process.
The 'force_insert' and 'force_update' parameters can be used to insist
that the "save" must be an SQL insert or update (or equivalent for
non-SQL backends), respectively. Normally, they should not be set.
- save_base(self, raw=False, force_insert=False, force_update=False, using=None, update_fields=None)
- Handle the parts of saving which should be done only once per save,
yet need to be done in raw saves, too. This includes some sanity
checks and signal sending.
The 'raw' argument is telling save_base not to save any parent
models and not to do any changes to the values before save. This
is used by fixture loading.
- serializable_value(self, field_name)
- Return the value of the field name for this instance. If the field is
a foreign key, return the id value instead of the object. If there's
no Field object with this name on the model, return the model
attribute's value.
Used to serialize a field's value (in the serializer, or form output,
for example). Normally, you would just access the attribute directly
and not use this method.
- unique_error_message(self, model_class, unique_check)
- validate_unique(self, exclude=None)
- Check unique constraints on the model and raise ValidationError if any
failed.
Class methods inherited from django.db.models.base.Model:
- check(**kwargs) from django.db.models.base.ModelBase
- from_db(db, field_names, values) from django.db.models.base.ModelBase
Data descriptors inherited from django.db.models.base.Model:
- __dict__
- dictionary for instance variables (if defined)
- __weakref__
- list of weak references to the object (if defined)
- pk
|
class Products(django.db.models.base.Model) |
| |
Products(*args, **kwargs)
Products(id, user, product_name, catagory, description, product_image, post_date, amount, specific_adress, price) |
| |
- Method resolution order:
- Products
- django.db.models.base.Model
- builtins.object
Methods defined here:
- __str__(self)
- Return str(self).
amount = <django.db.models.query_utils.DeferredAttribute object>
description = <django.db.models.query_utils.DeferredAttribute object>
- get_absloute_url(self)
- get_amount_display = _method(self, *, field=<django.db.models.fields.CharField: amount>)
- get_next_by_post_date = _method(self, *, field=<django.db.models.fields.DateTimeField: post_date>, is_next=True, **kwargs)
- get_previous_by_post_date = _method(self, *, field=<django.db.models.fields.DateTimeField: post_date>, is_next=False, **kwargs)
id = <django.db.models.query_utils.DeferredAttribute object>
post_date = <django.db.models.query_utils.DeferredAttribute object>
price = <django.db.models.query_utils.DeferredAttribute object>
product_name = <django.db.models.query_utils.DeferredAttribute object>
specific_adress = <django.db.models.query_utils.DeferredAttribute object>
Data descriptors defined here:
- catagory
- Accessor to the related object on the forward side of a many-to-one or
one-to-one (via ForwardOneToOneDescriptor subclass) relation.
In the example::
class Child(Model):
parent = ForeignKey(Parent, related_name='children')
``Child.parent`` is a ``ForwardManyToOneDescriptor`` instance.
- catagory_id
- ordered_product
- Accessor to the related objects manager on the reverse side of a
many-to-one relation.
In the example::
class Child(Model):
parent = ForeignKey(Parent, related_name='children')
``Parent.children`` is a ``ReverseManyToOneDescriptor`` instance.
Most of the implementation is delegated to a dynamically defined manager
class built by ``create_forward_many_to_many_manager()`` defined below.
- product_image
- Just like the FileDescriptor, but for ImageFields. The only difference is
assigning the width/height to the width_field/height_field, if appropriate.
- user
- Accessor to the related object on the forward side of a many-to-one or
one-to-one (via ForwardOneToOneDescriptor subclass) relation.
In the example::
class Child(Model):
parent = ForeignKey(Parent, related_name='children')
``Child.parent`` is a ``ForwardManyToOneDescriptor`` instance.
- user_id
Data and other attributes defined here:
- DoesNotExist = <class 'management.models.Products.DoesNotExist'>
- MultipleObjectsReturned = <class 'management.models.Products.MultipleObjectsReturned'>
- objects = <django.db.models.manager.Manager object>
Methods inherited from django.db.models.base.Model:
- __eq__(self, other)
- Return self==value.
- __getstate__(self)
- Hook to allow choosing the attributes to pickle.
- __hash__(self)
- Return hash(self).
- __init__(self, *args, **kwargs)
- Initialize self. See help(type(self)) for accurate signature.
- __reduce__(self)
- Helper for pickle.
- __repr__(self)
- Return repr(self).
- __setstate__(self, state)
- clean(self)
- Hook for doing any extra model-wide validation after clean() has been
called on every field by self.clean_fields. Any ValidationError raised
by this method will not be associated with a particular field; it will
have a special-case association with the field defined by NON_FIELD_ERRORS.
- clean_fields(self, exclude=None)
- Clean all fields and raise a ValidationError containing a dict
of all validation errors if any occur.
- date_error_message(self, lookup_type, field_name, unique_for)
- delete(self, using=None, keep_parents=False)
- full_clean(self, exclude=None, validate_unique=True)
- Call clean_fields(), clean(), and validate_unique() on the model.
Raise a ValidationError for any errors that occur.
- get_deferred_fields(self)
- Return a set containing names of deferred fields for this instance.
- prepare_database_save(self, field)
- refresh_from_db(self, using=None, fields=None)
- Reload field values from the database.
By default, the reloading happens from the database this instance was
loaded from, or by the read router if this instance wasn't loaded from
any database. The using parameter will override the default.
Fields can be used to specify which fields to reload. The fields
should be an iterable of field attnames. If fields is None, then
all non-deferred fields are reloaded.
When accessing deferred fields of an instance, the deferred loading
of the field will call this method.
- save(self, force_insert=False, force_update=False, using=None, update_fields=None)
- Save the current instance. Override this in a subclass if you want to
control the saving process.
The 'force_insert' and 'force_update' parameters can be used to insist
that the "save" must be an SQL insert or update (or equivalent for
non-SQL backends), respectively. Normally, they should not be set.
- save_base(self, raw=False, force_insert=False, force_update=False, using=None, update_fields=None)
- Handle the parts of saving which should be done only once per save,
yet need to be done in raw saves, too. This includes some sanity
checks and signal sending.
The 'raw' argument is telling save_base not to save any parent
models and not to do any changes to the values before save. This
is used by fixture loading.
- serializable_value(self, field_name)
- Return the value of the field name for this instance. If the field is
a foreign key, return the id value instead of the object. If there's
no Field object with this name on the model, return the model
attribute's value.
Used to serialize a field's value (in the serializer, or form output,
for example). Normally, you would just access the attribute directly
and not use this method.
- unique_error_message(self, model_class, unique_check)
- validate_unique(self, exclude=None)
- Check unique constraints on the model and raise ValidationError if any
failed.
Class methods inherited from django.db.models.base.Model:
- check(**kwargs) from django.db.models.base.ModelBase
- from_db(db, field_names, values) from django.db.models.base.ModelBase
Data descriptors inherited from django.db.models.base.Model:
- __dict__
- dictionary for instance variables (if defined)
- __weakref__
- list of weak references to the object (if defined)
- pk
|
class TransportOrders(django.db.models.base.Model) |
| |
TransportOrders(*args, **kwargs)
TransportOrders(id, transport, ordered_by, transport_owner, order_date, message, order_source_adress, orderer_optional_adress, status) |
| |
- Method resolution order:
- TransportOrders
- django.db.models.base.Model
- builtins.object
Methods defined here:
- __str__(self)
- Return str(self).
- get_next_by_order_date = _method(self, *, field=<django.db.models.fields.DateTimeField: order_date>, is_next=True, **kwargs)
- get_previous_by_order_date = _method(self, *, field=<django.db.models.fields.DateTimeField: order_date>, is_next=False, **kwargs)
id = <django.db.models.query_utils.DeferredAttribute object>
message = <django.db.models.query_utils.DeferredAttribute object>
order_date = <django.db.models.query_utils.DeferredAttribute object>
order_source_adress = <django.db.models.query_utils.DeferredAttribute object>
orderer_optional_adress = <django.db.models.query_utils.DeferredAttribute object>
status = <django.db.models.query_utils.DeferredAttribute object>
Data descriptors defined here:
- ordered_by
- Accessor to the related object on the forward side of a many-to-one or
one-to-one (via ForwardOneToOneDescriptor subclass) relation.
In the example::
class Child(Model):
parent = ForeignKey(Parent, related_name='children')
``Child.parent`` is a ``ForwardManyToOneDescriptor`` instance.
- ordered_by_id
- transport
- Accessor to the related object on the forward side of a many-to-one or
one-to-one (via ForwardOneToOneDescriptor subclass) relation.
In the example::
class Child(Model):
parent = ForeignKey(Parent, related_name='children')
``Child.parent`` is a ``ForwardManyToOneDescriptor`` instance.
- transport_id
- transport_owner
- Accessor to the related object on the forward side of a many-to-one or
one-to-one (via ForwardOneToOneDescriptor subclass) relation.
In the example::
class Child(Model):
parent = ForeignKey(Parent, related_name='children')
``Child.parent`` is a ``ForwardManyToOneDescriptor`` instance.
- transport_owner_id
Data and other attributes defined here:
- DoesNotExist = <class 'management.models.TransportOrders.DoesNotExist'>
- MultipleObjectsReturned = <class 'management.models.TransportOrders.MultipleObjectsReturned'>
- objects = <django.db.models.manager.Manager object>
Methods inherited from django.db.models.base.Model:
- __eq__(self, other)
- Return self==value.
- __getstate__(self)
- Hook to allow choosing the attributes to pickle.
- __hash__(self)
- Return hash(self).
- __init__(self, *args, **kwargs)
- Initialize self. See help(type(self)) for accurate signature.
- __reduce__(self)
- Helper for pickle.
- __repr__(self)
- Return repr(self).
- __setstate__(self, state)
- clean(self)
- Hook for doing any extra model-wide validation after clean() has been
called on every field by self.clean_fields. Any ValidationError raised
by this method will not be associated with a particular field; it will
have a special-case association with the field defined by NON_FIELD_ERRORS.
- clean_fields(self, exclude=None)
- Clean all fields and raise a ValidationError containing a dict
of all validation errors if any occur.
- date_error_message(self, lookup_type, field_name, unique_for)
- delete(self, using=None, keep_parents=False)
- full_clean(self, exclude=None, validate_unique=True)
- Call clean_fields(), clean(), and validate_unique() on the model.
Raise a ValidationError for any errors that occur.
- get_deferred_fields(self)
- Return a set containing names of deferred fields for this instance.
- prepare_database_save(self, field)
- refresh_from_db(self, using=None, fields=None)
- Reload field values from the database.
By default, the reloading happens from the database this instance was
loaded from, or by the read router if this instance wasn't loaded from
any database. The using parameter will override the default.
Fields can be used to specify which fields to reload. The fields
should be an iterable of field attnames. If fields is None, then
all non-deferred fields are reloaded.
When accessing deferred fields of an instance, the deferred loading
of the field will call this method.
- save(self, force_insert=False, force_update=False, using=None, update_fields=None)
- Save the current instance. Override this in a subclass if you want to
control the saving process.
The 'force_insert' and 'force_update' parameters can be used to insist
that the "save" must be an SQL insert or update (or equivalent for
non-SQL backends), respectively. Normally, they should not be set.
- save_base(self, raw=False, force_insert=False, force_update=False, using=None, update_fields=None)
- Handle the parts of saving which should be done only once per save,
yet need to be done in raw saves, too. This includes some sanity
checks and signal sending.
The 'raw' argument is telling save_base not to save any parent
models and not to do any changes to the values before save. This
is used by fixture loading.
- serializable_value(self, field_name)
- Return the value of the field name for this instance. If the field is
a foreign key, return the id value instead of the object. If there's
no Field object with this name on the model, return the model
attribute's value.
Used to serialize a field's value (in the serializer, or form output,
for example). Normally, you would just access the attribute directly
and not use this method.
- unique_error_message(self, model_class, unique_check)
- validate_unique(self, exclude=None)
- Check unique constraints on the model and raise ValidationError if any
failed.
Class methods inherited from django.db.models.base.Model:
- check(**kwargs) from django.db.models.base.ModelBase
- from_db(db, field_names, values) from django.db.models.base.ModelBase
Data descriptors inherited from django.db.models.base.Model:
- __dict__
- dictionary for instance variables (if defined)
- __weakref__
- list of weak references to the object (if defined)
- pk
|
class Transports(django.db.models.base.Model) |
| |
Transports(*args, **kwargs)
Transports(id, user, transport_name, description, transport_image, post_date, specific_adress, price) |
| |
- Method resolution order:
- Transports
- django.db.models.base.Model
- builtins.object
Methods defined here:
- __str__(self)
- Return str(self).
description = <django.db.models.query_utils.DeferredAttribute object>
- get_absloute_url(self)
- get_next_by_post_date = _method(self, *, field=<django.db.models.fields.DateTimeField: post_date>, is_next=True, **kwargs)
- get_previous_by_post_date = _method(self, *, field=<django.db.models.fields.DateTimeField: post_date>, is_next=False, **kwargs)
id = <django.db.models.query_utils.DeferredAttribute object>
post_date = <django.db.models.query_utils.DeferredAttribute object>
price = <django.db.models.query_utils.DeferredAttribute object>
specific_adress = <django.db.models.query_utils.DeferredAttribute object>
transport_name = <django.db.models.query_utils.DeferredAttribute object>
Data descriptors defined here:
- transport
- Accessor to the related objects manager on the reverse side of a
many-to-one relation.
In the example::
class Child(Model):
parent = ForeignKey(Parent, related_name='children')
``Parent.children`` is a ``ReverseManyToOneDescriptor`` instance.
Most of the implementation is delegated to a dynamically defined manager
class built by ``create_forward_many_to_many_manager()`` defined below.
- transport_image
- Just like the FileDescriptor, but for ImageFields. The only difference is
assigning the width/height to the width_field/height_field, if appropriate.
- user
- Accessor to the related object on the forward side of a many-to-one or
one-to-one (via ForwardOneToOneDescriptor subclass) relation.
In the example::
class Child(Model):
parent = ForeignKey(Parent, related_name='children')
``Child.parent`` is a ``ForwardManyToOneDescriptor`` instance.
- user_id
Data and other attributes defined here:
- DoesNotExist = <class 'management.models.Transports.DoesNotExist'>
- MultipleObjectsReturned = <class 'management.models.Transports.MultipleObjectsReturned'>
- objects = <django.db.models.manager.Manager object>
Methods inherited from django.db.models.base.Model:
- __eq__(self, other)
- Return self==value.
- __getstate__(self)
- Hook to allow choosing the attributes to pickle.
- __hash__(self)
- Return hash(self).
- __init__(self, *args, **kwargs)
- Initialize self. See help(type(self)) for accurate signature.
- __reduce__(self)
- Helper for pickle.
- __repr__(self)
- Return repr(self).
- __setstate__(self, state)
- clean(self)
- Hook for doing any extra model-wide validation after clean() has been
called on every field by self.clean_fields. Any ValidationError raised
by this method will not be associated with a particular field; it will
have a special-case association with the field defined by NON_FIELD_ERRORS.
- clean_fields(self, exclude=None)
- Clean all fields and raise a ValidationError containing a dict
of all validation errors if any occur.
- date_error_message(self, lookup_type, field_name, unique_for)
- delete(self, using=None, keep_parents=False)
- full_clean(self, exclude=None, validate_unique=True)
- Call clean_fields(), clean(), and validate_unique() on the model.
Raise a ValidationError for any errors that occur.
- get_deferred_fields(self)
- Return a set containing names of deferred fields for this instance.
- prepare_database_save(self, field)
- refresh_from_db(self, using=None, fields=None)
- Reload field values from the database.
By default, the reloading happens from the database this instance was
loaded from, or by the read router if this instance wasn't loaded from
any database. The using parameter will override the default.
Fields can be used to specify which fields to reload. The fields
should be an iterable of field attnames. If fields is None, then
all non-deferred fields are reloaded.
When accessing deferred fields of an instance, the deferred loading
of the field will call this method.
- save(self, force_insert=False, force_update=False, using=None, update_fields=None)
- Save the current instance. Override this in a subclass if you want to
control the saving process.
The 'force_insert' and 'force_update' parameters can be used to insist
that the "save" must be an SQL insert or update (or equivalent for
non-SQL backends), respectively. Normally, they should not be set.
- save_base(self, raw=False, force_insert=False, force_update=False, using=None, update_fields=None)
- Handle the parts of saving which should be done only once per save,
yet need to be done in raw saves, too. This includes some sanity
checks and signal sending.
The 'raw' argument is telling save_base not to save any parent
models and not to do any changes to the values before save. This
is used by fixture loading.
- serializable_value(self, field_name)
- Return the value of the field name for this instance. If the field is
a foreign key, return the id value instead of the object. If there's
no Field object with this name on the model, return the model
attribute's value.
Used to serialize a field's value (in the serializer, or form output,
for example). Normally, you would just access the attribute directly
and not use this method.
- unique_error_message(self, model_class, unique_check)
- validate_unique(self, exclude=None)
- Check unique constraints on the model and raise ValidationError if any
failed.
Class methods inherited from django.db.models.base.Model:
- check(**kwargs) from django.db.models.base.ModelBase
- from_db(db, field_names, values) from django.db.models.base.ModelBase
Data descriptors inherited from django.db.models.base.Model:
- __dict__
- dictionary for instance variables (if defined)
- __weakref__
- list of weak references to the object (if defined)
- pk
|
class WantedProducts(django.db.models.base.Model) |
| |
WantedProducts(*args, **kwargs)
WantedProducts(id, user, product_name, description, product_image, post_date, amount_need, specific_adress, price_range, found) |
| |
- Method resolution order:
- WantedProducts
- django.db.models.base.Model
- builtins.object
Methods defined here:
- __str__(self)
- Return str(self).
amount_need = <django.db.models.query_utils.DeferredAttribute object>
description = <django.db.models.query_utils.DeferredAttribute object>
found = <django.db.models.query_utils.DeferredAttribute object>
- get_absloute_url(self)
- get_amount_need_display = _method(self, *, field=<django.db.models.fields.CharField: amount_need>)
- get_next_by_post_date = _method(self, *, field=<django.db.models.fields.DateTimeField: post_date>, is_next=True, **kwargs)
- get_previous_by_post_date = _method(self, *, field=<django.db.models.fields.DateTimeField: post_date>, is_next=False, **kwargs)
id = <django.db.models.query_utils.DeferredAttribute object>
post_date = <django.db.models.query_utils.DeferredAttribute object>
price_range = <django.db.models.query_utils.DeferredAttribute object>
product_name = <django.db.models.query_utils.DeferredAttribute object>
specific_adress = <django.db.models.query_utils.DeferredAttribute object>
Data descriptors defined here:
- product_image
- Just like the FileDescriptor, but for ImageFields. The only difference is
assigning the width/height to the width_field/height_field, if appropriate.
- user
- Accessor to the related object on the forward side of a many-to-one or
one-to-one (via ForwardOneToOneDescriptor subclass) relation.
In the example::
class Child(Model):
parent = ForeignKey(Parent, related_name='children')
``Child.parent`` is a ``ForwardManyToOneDescriptor`` instance.
- user_id
Data and other attributes defined here:
- DoesNotExist = <class 'management.models.WantedProducts.DoesNotExist'>
- MultipleObjectsReturned = <class 'management.models.WantedProducts.MultipleObjectsReturned'>
- objects = <django.db.models.manager.Manager object>
Methods inherited from django.db.models.base.Model:
- __eq__(self, other)
- Return self==value.
- __getstate__(self)
- Hook to allow choosing the attributes to pickle.
- __hash__(self)
- Return hash(self).
- __init__(self, *args, **kwargs)
- Initialize self. See help(type(self)) for accurate signature.
- __reduce__(self)
- Helper for pickle.
- __repr__(self)
- Return repr(self).
- __setstate__(self, state)
- clean(self)
- Hook for doing any extra model-wide validation after clean() has been
called on every field by self.clean_fields. Any ValidationError raised
by this method will not be associated with a particular field; it will
have a special-case association with the field defined by NON_FIELD_ERRORS.
- clean_fields(self, exclude=None)
- Clean all fields and raise a ValidationError containing a dict
of all validation errors if any occur.
- date_error_message(self, lookup_type, field_name, unique_for)
- delete(self, using=None, keep_parents=False)
- full_clean(self, exclude=None, validate_unique=True)
- Call clean_fields(), clean(), and validate_unique() on the model.
Raise a ValidationError for any errors that occur.
- get_deferred_fields(self)
- Return a set containing names of deferred fields for this instance.
- prepare_database_save(self, field)
- refresh_from_db(self, using=None, fields=None)
- Reload field values from the database.
By default, the reloading happens from the database this instance was
loaded from, or by the read router if this instance wasn't loaded from
any database. The using parameter will override the default.
Fields can be used to specify which fields to reload. The fields
should be an iterable of field attnames. If fields is None, then
all non-deferred fields are reloaded.
When accessing deferred fields of an instance, the deferred loading
of the field will call this method.
- save(self, force_insert=False, force_update=False, using=None, update_fields=None)
- Save the current instance. Override this in a subclass if you want to
control the saving process.
The 'force_insert' and 'force_update' parameters can be used to insist
that the "save" must be an SQL insert or update (or equivalent for
non-SQL backends), respectively. Normally, they should not be set.
- save_base(self, raw=False, force_insert=False, force_update=False, using=None, update_fields=None)
- Handle the parts of saving which should be done only once per save,
yet need to be done in raw saves, too. This includes some sanity
checks and signal sending.
The 'raw' argument is telling save_base not to save any parent
models and not to do any changes to the values before save. This
is used by fixture loading.
- serializable_value(self, field_name)
- Return the value of the field name for this instance. If the field is
a foreign key, return the id value instead of the object. If there's
no Field object with this name on the model, return the model
attribute's value.
Used to serialize a field's value (in the serializer, or form output,
for example). Normally, you would just access the attribute directly
and not use this method.
- unique_error_message(self, model_class, unique_check)
- validate_unique(self, exclude=None)
- Check unique constraints on the model and raise ValidationError if any
failed.
Class methods inherited from django.db.models.base.Model:
- check(**kwargs) from django.db.models.base.ModelBase
- from_db(db, field_names, values) from django.db.models.base.ModelBase
Data descriptors inherited from django.db.models.base.Model:
- __dict__
- dictionary for instance variables (if defined)
- __weakref__
- list of weak references to the object (if defined)
- pk
| |


Thank you for taking your time to complet the survey. It will be reviewed and if required a team manager will be in touch shortly.


Glasgow Botanic Gardens, located in the West End of Glasgow and managed by Glasgow City Council is arguably the finest Garden in Glasgow, and is dominated by the recently restored Kibble Palace.
The Kibble Palace. a magnificent Curvilinular Glasshouse designed by John Kibble (full details elsewhere in this site) houses the National collection of tree ferns.
GoMA is located in the centre of Glasgow. It contains four galleries, a café, a shop and a library.
 We display, borrow and collect artworks from around the world.
Kelvingrove Museum opened in 1901 and is a firm favourite with local people and visitors. It has stunning architecture and a family friendly atmosphere.
Explore our 22 galleries and discover everything from art to animals, Ancient Egypt to Charles Rennie Mackintosh and so much more. We also have a changing programme of temporary exhibitions and displays.


<kwd>
The <kwd>
element defines a keyword within a syntax diagram. A keyword
must be typed or output, either by the user or application, exactly as specified in the
syntax definition. This element is part of the DITA programming domain, a special set of
DITA elements designed to document programming tasks, concepts, and reference
information.
Category: Programming elements


Carmelo Anthony officially joins Portland Trail Blazers
by Sports DeskThe Portland Trail Blazers have confirmed the signing of 10-time NBA All-Star Carmelo Anthony - and could hand their latest addition his debut for the team on Tuesday.
Anthony has not featured in the league in over a year, since a short-lived spell with the Houston Rockets came to an end.
However, the 35-year-old has played over 1,000 games in a career that has spanned 16 seasons since he was selected with the third overall pick in the 2003 draft.
Anthony has previously played for the Denver Nuggets - the team who drafted him - as well as the New York Knicks and the Oklahoma City Thunder.
"Carmelo is an established star in this league that will provide a respected presence in our locker room and a skill set at a position of need on the floor," said Neil Olshey, Portland's president of basketball operations.
Anthony will wear number 00 for the Trail Blazers, who reached last season's Western Conference Finals but are struggling at 5-9 this year.
The NBA's scoring champion for the 2012-13 campaign has been activated in time to feature against the New Orleans Pelicans.


{% extends "includes/layout.html" %} {% block content %} {% include "includes/breadcrumbs.html" %} {% include "includes/validation-error-messages.html" %} {% include "includes/title-subtitle.html" %} {% include "includes/sub-nav.html" %} {% include "includes/csrf-hidden-input.html"%} Please select the type of export to download: ARMS Case Details Case Management Support Group Supervision Scenario Suspended Lifers Percentage Capacity Breakdown {% if authorisation===false or userRole==='System Admin' or userRole==='Data Admin' or userRole==='Manager'%} Expiring Reductions {% endif %} {% include "includes/last-updated.html" %} {% endblock %}


|
Bank |
Interest Rate(p.a.) |
Processing Fee |
| SBI |
9.60%p.a. - 15.65%p.a. |
Up to 1.5% |
| ICICI Bank |
11.25%p.a. - 21%p.a. |
Up to 2.25% |
| HDFC Bank |
10.75%p.a. - 21.30%p.a. |
Up to 2.50% |
| Yes Bank |
13.99%p.a. - 16.99%p.a. |
Up to 2.50% |
| CitiBank |
9.99%p.a. - 16%p.a. |
Up to 3% |
| Kotak Mahindra Bank |
10.75% and above |
Up to 2.50% |
| Axis Bank |
12%p.a. - 24%p.a. |
1.5% - 2% |
| Bank of Baroda |
10.50%p.a. onwards |
Up to 2% |
| HSBC Bank |
10.50%p.a. - 17.84%p.a. |
Up to 1% |
| IDFC Bank |
10.75%p.a. and above |
Up to 3.5% |
| Tata Capital |
10.99% onwards |
Up to 2.75% |
| Karnatka Bank |
12%p.a. - 17%p.a. |
0.5 |
| Canara Bank |
12.40%p.a. - 13.90%p.a. |
1% |
| Federal Bank |
10.49%p.a. - 17.99%p.a. |
Up to 3% |
| Iduslnd Bank |
11%p.a. - 31%p.a. |
2.5% onwards |
| IIFL |
16%p.a. onwards |
Up to 3% |
| ICICI Bank |
11.25%p.a. - 21%p.a. |
Up to 2.25% |
| Bank of India |
10.85%p.a. - 12.85%p.a. |
Up to 2% |
| Aditya Birla Capital |
16.85% onwards |
0.5% and 1% |
| IDBI Bank |
8.55%p.a. - 11.30%p.a. |
Contact The Bank |
| Corporation Bank |
10.75% and above |
1.50% |
| Indian Overseas Bank |
10.80% and above |
Up to 0.50% |
| RBL Bank |
14%p.a. - 23%p.a. |
1.50% |
| Punjab National Bank |
6.90%p.a. - 11.65%p.a. |
Up to 1.80% |
| Central Bank of India |
9.85% and above |
Rs. 500 |
Please note that additional GST will be charged on the applicable processing fee
Eligibility:
The following factors are considered by lenders while going through your loan application. If you meet these
criteria, consider yourself eligible for a personal loan.
| Criteria |
Salaried |
Self-Employed |
| Age |
21 years to 60 years |
22 years to 55 years |
| Net Monthly Income |
Rs.15,000 |
Rs.25,000 |
| CIBIL Score |
Above 750 |
Above 750 |
| Minimum Loan Amount |
Rs.50,000 |
Rs.50,000 |
| Maximum Loan Amount |
Rs.25 lakh |
Rs.30 lakh |
Documents Required For Personal Loan
| Requirements |
Salaried |
Self - Employed |
| Proof of Identity |
Passport, Voter’s ID, Driving License or PAN Card |
Passport, Voter’s ID, Driving License or PAN Card |
| Proof of Residence |
Passport or utility bills |
Passport or utility bills |
| Proof of Income |
Bank statement of salary account for the past two years |
Audited financial statement of the past two years |
If you are an NRI looking to borrow a personal loan, these are the documents that you will need to submit to
the lender:
- Copy of your Passport
- Visa Copy
- Your official Email ID or the Email ID of the HR
- Bank Statements
- Salary Certificate or salary slips
- NRO/NRE bank statements of the last 6 Months
- Proof of Identity, Residence, Income, and Assets
- Recent passport-size Photographs of yourself and the guarantors


Provides static methods for constructing cells. More...
Static Public Member Functions | |
| static ICellRead< Unit > | UnitCell () |
| static ICellRead< T > | Const< T > (T value) |
| Construct a constant cell, with a lifetime equal to the given scope. If the value is reference counted, it will be released when the scope ends. More... | |
| static ICellRead< TOut > | Merge< T1, T2, TOut > (ICellRead< T1 > c1, ICellRead< T2 > c2, Func< T1, T2, TOut > selector) |
| Construct a cell derived from the values of two others. More... | |
| static ICellRead< TOut > | Merge< T1, T2, T3, TOut > (ICellRead< T1 > c1, ICellRead< T2 > c2, ICellRead< T3 > c3, Func< T1, T2, T3, TOut > selector) |
| Construct a cell derived from the values of two others. More... | |
| static ICellRead< TOut > | Merge< T1, T2, T3, T4, TOut > (ICellRead< T1 > c1, ICellRead< T2 > c2, ICellRead< T3 > c3, ICellRead< T4 > c4, Func< T1, T2, T3, T4, TOut > selector) |
| Construct a cell derived from the values of four others. More... | |
Provides static methods for constructing cells.
|
inlinestatic |
Construct a constant cell, with a lifetime equal to the given scope. If the value is reference counted, it will be released when the scope ends.
| T | The type of the constant value. |
| value | The constant value. |
|
inlinestatic |
Construct a cell derived from the values of four others.
| T1 | The type of the first source cell. |
| T2 | The type of the second source cell. |
| T3 | The type of the third source cell. |
| T4 | The type of the fourth source cell. |
| TOut | The result type. |
| c1 | The first source cell. |
| c2 | The second source cell. |
| c3 | The third source cell. |
| c4 | The fourth source cell. |
| selector | A function to compute the current value of the result from the source values. |
|
inlinestatic |
Construct a cell derived from the values of two others.
| T1 | The type of the first source cell. |
| T2 | The type of the second source cell. |
| T3 | The type of the third source cell. |
| TOut | The result type. |
| c1 | The first source cell. |
| c2 | The second source cell. |
| c3 | The third source cell. |
| selector | A function to compute the current value of the result from the source values. |
|
inlinestatic |
Construct a cell derived from the values of two others.
| T1 | The type of the first source cell. |
| T2 | The type of the second source cell. |
| TOut | The result type. |
| c1 | The first source cell. |
| c2 | The second source cell. |
| selector | A function to compute the current value of the result from the source values. |


The Heaven-Bound Bridge was inspired by various stories and mythologies.The primary influence is a folk tale "Cowherd and Weaver Maid" which originated in China and spread to Japan, Korea and Vietnam. In this story Cowherd and Weaver Maid are two celestial lovers separated by a great river in the sky by the maiden's father, as punishment for neglecting their duties while under the spell of marital bliss.


--- layout: base title: "Raphael's Playground" --- Home Images Buttons Canvas iFrame
Welcome to Raphael's Playground Web site! He uses this Web site to test things.


[Erowid Note: 800 mgs of tramadol is considered a high dose, see Tramadol Dosage]
Hello, I had an unpleasant experience with tramadol (the brand name was Ultram). They were 50mg pills. I had heard that it was similar to codeine, but after taking 4, I realized that it was less potent than codeine. So I ended up taking 16 pills in the course of 6 hours.
About 1 hr after I took the last 2 pills, hell broke loose (or something like that). The first thing I remember is 'waking up' talking to this guy I didn't know. He was asking me a bunch of simple questions.
Ok, now for the explanation. The last thing that I remember is going outside for a smoke. While I was outside, I had a seizure. Now, of course I donít remember this. My friends said they heard a loud noise and came outside to investigate. I had fallen down, and landed on something noisy. They said that they watched me writhe on the ground for about 3 minutes, and that for at least 1 minute, I was not breathing, and my face turned blue. They told me that I was groaning loudly, and basically spazzing out. They called an ambulance, which took about 12-15 minutes to arrive.
Before the ambulance came, the seizure stopped, and they got me to sit on a bench, and they tried to comfort me. Like I said, I donít remember this. My first post-seizure memory is talking to an EMT.
They forced me to go to the hospital. Since I felt fine, I didnít want to go. It was about a 20 minute ride to the hospital.  I also tried to sleep (I was lying down in a stretcher) and they would not let me.
At the hospital, they did an MRI, and blood tests, but I didnít have to drink any charcoal. I had no visible brain damage, but they said if I had drank any alcohol at all, that I probably wouldn't have come out alive.
To conclude: I trashed the rest of my Tramadol. My mom was pissed as hell, and now thinks I'm a drug addict (which I probably am).
Sorry for the long report, but I just wanted to give the facts.
Um... here's some more facts: I was taking no other substances at the time except for the occasional joint or 2, and I had no gotten high for about a week prior to the experience, and I had had no grass on the day of the experience. I'm not turned off from drugs, but I'm more cautious. I've taken vicodin since then, with no ill effects, as well as a variety of 'research chems'.
2nd conclusion: Tramadol is weak. Yes, even weaker than codeine. It depresses breathing in high doses, and for me, it is not worth it. If I saw a friend taking some, I'd slap it out of his hand. Not because I think that this drug is unsafe. But because of the fact that it is so weak, that it is easy to take too much, and not know it. That is all.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


---
layout: page
#title: GazeTheWeb
#subtitle: Explore the Web with your eyes!
#use-site-title: true
---
Story
GazeTheWeb has been evaluated as part of the MAMEM project at three clinical cohorts in Athens, Thessaloniki, and Tel Aviv, in two trial phases. At the first trial phase in February 2017, 18 participants with motor impairment succesfully performed dictated tasks in the World Wide Web.
The second phase has taken place in spring 2018, wheere 30 participants with motor impairment operated GazeTheWeb for one month a their homes on their own behalf. The system allowed the particitpants to browse the World Wide Web, perform communication, access entertainment and retrieve information.
Impact
If you use our software as part for your own research, please be kind and cite our publication:
@inproceedings{tochiGazeTheWeb,
author = {Menges, Raphael and Kumar, Chandan and Staab, Steffen},
title = {Improving User Experience of Eye Tracking-Based Interaction: Introspecting and Adapting Interfaces},
journal = {ACM Trans. Comput.-Hum. Interact.},
issue_date = {October 2019},
volume = {26},
number = {6},
month = nov,
year = {2019},
issn = {1073-0516},
pages = {37:1--37:46},
articleno = {37},
numpages = {46},
url = {http://doi.acm.org/10.1145/3338844},
doi = {10.1145/3338844},
acmid = {3338844},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {Eye tracking, GazeTheWeb, Web accessibility, gaze interaction experience, gaze-based emulation, gaze-controlled interface, interface semantics, introspection},}


DatePicker with Placeholder, Tooltip, Events, and ValueState
DatePicker with format-pattern='short'
DatePicker with format-pattern='long', value='yesterday'
DatePicker with format-pattern='QQQ yyyy, MMM dd', value='Q4 2018, Feb 14'
DatePicker with format-pattern='EEE, M/d/yyyy', value='today'
DatePicker with Japanese Calendar Type
DatePicker with Islamic Calendar Type
DatePicker with Buddhist Calendar Type


ELIN
ATONAL 3D SYNTH EXPERIMENT
Push mouse buttons and move to mold.
Scroll wheel to zoom. Grab outside the organ to look around.
Lauri-Matti Parppei 2016


2009 CAYSC Back-to-School Shop Hop
Mark your calendars for Thursday, September 17th through Sunday, September 20th for four days, four shops, and endless possibilities! ThreadBear Fiber Arts Studio, Yarn Garden in Charlotte, Rae's Yarn Boutique in Lansing, and Woven Art in East Lansing are hosting a shop hop to beat the band.
Passports are currently on sale and in limited supply (each shop only has 75), and our supply is moving VERY quickly! Call the shop (517-703-YARN locally or 866-939-BEAR at a distance) to reserve yours NOW.
Full details can be found on the
CAYSC website.


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Unable to confirm your email. This request has expired.


Square Coins
问题描述 :
People in Silverland use square coins. Not only they have square shapes but also their values are square numbers. Coins with values of all square numbers up to 289 (=17^2), i.e., 1-credit coins, 4-credit coins, 9-credit coins, …, and 289-credit coins, are available in Silverland.
There are four combinations of coins to pay ten credits:ten 1-credit coins,
one 4-credit coin and six 1-credit coins,
two 4-credit coins and two 1-credit coins, and
one 9-credit coin and one 1-credit coin.
There are four combinations of coins to pay ten credits:ten 1-credit coins,
one 4-credit coin and six 1-credit coins,
two 4-credit coins and two 1-credit coins, and
one 9-credit coin and one 1-credit coin.
Your mission is to count the number of ways to pay a given amount using coins of Silverland.
输入:
The input consists of lines each containing an integer meaning an amount to be paid, followed by a line containing a zero. You may assume that all the amounts are positive and less than 300.
输出:
For each of the given amount, one line containing a single integer representing the number of combinations of coins should be output. No other characters should appear in the output.
样例输入:
2 10 30 0
样例输出:
1 4 27
#include<iostream> #include<cstdio> #include<cstring> using namespace std; const int N=320; int money[]={0,1,4,9,16,25,36,49,64,81,100,121,144,169,196,225,256,289}; int c1[N],c2[N]; int main(){ //freopen("input.txt","r",stdin); int n; while(~scanf("%d",&n) && n){ for(int i=0;i<=n;i++){ c1[i]=0; c2[i]=0; } c1[0]=1; for(int i=1;i<=17;i++){ for(int j=0;j<=n;j++) for(int k=0;j+k*money[i]<=n;k++) c2[j+k*money[i]]+=c1[j]; for(int j=0;j<=n;j++){ c1[j]=c2[j]; c2[j]=0; } } printf("%d\n",c1[n]); } return 0; }
解题报告转自：http://www.cnblogs.com/jackge/archive/2013/04/18/3028177.html
(adsbygoogle = window.adsbygoogle || []).push({});
很不错的全功能战机，皮实耐操，又特TMD能装弹，难怪阿三能看上。
很不错的全功能战机，皮实耐操，又特TMD能装弹，难怪阿三能看上。
很不错的全功能战机，皮实耐操，又特TMD能装弹，难怪阿三能看上。
很不错的全功能战机，皮实耐操，又特TMD能装弹，难怪阿三能看上。
很不错的全功能战机，皮实耐操，又特TMD能装弹，难怪阿三能看上。
很不错的全功能战机，皮实耐操，又特TMD能装弹，难怪阿三能看上。
程序是对的。有些地方用了C++的写法
你指的哪个问题？
可是看了很多算法书什么的都是说的(start-end)/2哎。。。
题目和代码都不一样好吗！！！搞错了
Good task for the group. Hold it up for every yeara??s winner. This is a excellent oppotunity for a lot more enhancement. Indeed, obtaining far better and much better is constantly the crucial. Just like my pal suggests on the truth about ab muscles, he just keeps obtaining much better.
你好，这题给出的代码好像弄错了，这个是pow那道题目的解法
还真是，i7的cpu跑了3秒
先从简单的做起，归并排序，二叉树相关的遍历等
很好的思路，可以借鉴
第15行代码，/n/n，应该改为\n\n
约瑟夫也用说这么长……很成熟的一个问题了，分治的方法解起来o(n)就可以了，有兴趣可以看看具体数学的第一章，关于约瑟夫问题推导出了一系列的结论，很漂亮
多谢支持！
mark, 备用


It's a list
A right smart list
Within, another list
This is
deep
So
very
deep
A list of lists to see
And all the lists for me!


|
SdFat
|
BIOS parameter block. More...
#include <FatStructs.h>
Public Attributes | |
| uint16_t | bytesPerSector |
| uint16_t | fat32BackBootBlock |
| uint16_t | fat32Flags |
| uint16_t | fat32FSInfo |
| uint8_t | fat32Reserved [12] |
| uint32_t | fat32RootCluster |
| uint16_t | fat32Version |
| uint8_t | fatCount |
| uint16_t | headCount |
| uint32_t | hidddenSectors |
| uint8_t | mediaType |
| uint16_t | reservedSectorCount |
| uint16_t | rootDirEntryCount |
| uint8_t | sectorsPerCluster |
| uint16_t | sectorsPerFat16 |
| uint32_t | sectorsPerFat32 |
| uint16_t | sectorsPerTrtack |
| uint16_t | totalSectors16 |
| uint32_t | totalSectors32 |
BIOS parameter block.
The BIOS parameter block describes the physical layout of a FAT volume.
| uint16_t biosParmBlock::bytesPerSector |
Count of bytes per sector. This value may take on only the following values: 512, 1024, 2048 or 4096
| uint16_t biosParmBlock::fat32BackBootBlock |
If nonzero, indicates the sector number in the reserved area of the volume of a copy of the boot record. Usually 6. No value other than 6 is recommended.
| uint16_t biosParmBlock::fat32Flags |
This field is only defined for FAT32 media and does not exist on FAT12 and FAT16 media. Bits 0-3 – Zero-based number of active FAT. Only valid if mirroring is disabled. Bits 4-6 – Reserved. Bit 7 – 0 means the FAT is mirrored at runtime into all FATs. – 1 means only one FAT is active; it is the one referenced in bits 0-3. Bits 8-15 – Reserved.
| uint16_t biosParmBlock::fat32FSInfo |
Sector number of FSINFO structure in the reserved area of the FAT32 volume. Usually 1.
| uint8_t biosParmBlock::fat32Reserved[12] |
Reserved for future expansion. Code that formats FAT32 volumes should always set all of the bytes of this field to 0.
| uint32_t biosParmBlock::fat32RootCluster |
Cluster number of the first cluster of the root directory for FAT32. This usually 2 but not required to be 2.
| uint16_t biosParmBlock::fat32Version |
FAT32 version. High byte is major revision number. Low byte is minor revision number. Only 0.0 define.
| uint8_t biosParmBlock::fatCount |
The count of FAT data structures on the volume. This field should always contain the value 2 for any FAT volume of any type.
| uint16_t biosParmBlock::headCount |
Number of heads for interrupt 0x13. Not used otherwise.
| uint32_t biosParmBlock::hidddenSectors |
Count of hidden sectors preceding the partition that contains this FAT volume. This field is generally only relevant for media visible on interrupt 0x13.
| uint8_t biosParmBlock::mediaType |
This dates back to the old MS-DOS 1.x media determination and is no longer usually used for anything. 0xF8 is the standard value for fixed (nonremovable) media. For removable media, 0xF0 is frequently used. Legal values are 0xF0 or 0xF8-0xFF.
| uint16_t biosParmBlock::reservedSectorCount |
Number of sectors before the first FAT. This value must not be zero.
| uint16_t biosParmBlock::rootDirEntryCount |
For FAT12 and FAT16 volumes, this field contains the count of 32-byte directory entries in the root directory. For FAT32 volumes, this field must be set to 0. For FAT12 and FAT16 volumes, this value should always specify a count that when multiplied by 32 results in a multiple of bytesPerSector. FAT16 volumes should use the value 512.
| uint8_t biosParmBlock::sectorsPerCluster |
Number of sectors per allocation unit. This value must be a power of 2 that is greater than 0. The legal values are 1, 2, 4, 8, 16, 32, 64, and 128.
| uint16_t biosParmBlock::sectorsPerFat16 |
Count of sectors occupied by one FAT on FAT12/FAT16 volumes. On FAT32 volumes this field must be 0, and sectorsPerFat32 contains the FAT size count.
| uint32_t biosParmBlock::sectorsPerFat32 |
Count of sectors occupied by one FAT on FAT32 volumes.
| uint16_t biosParmBlock::sectorsPerTrtack |
Sectors per track for interrupt 0x13. Not used otherwise.
| uint16_t biosParmBlock::totalSectors16 |
This field is the old 16-bit total count of sectors on the volume. This count includes the count of all sectors in all four regions of the volume. This field can be 0; if it is 0, then totalSectors32 must be nonzero. For FAT32 volumes, this field must be 0. For FAT12 and FAT16 volumes, this field contains the sector count, and totalSectors32 is 0 if the total sector count fits (is less than 0x10000).
| uint32_t biosParmBlock::totalSectors32 |
This field is the new 32-bit total count of sectors on the volume. This count includes the count of all sectors in all four regions of the volume. This field can be 0; if it is 0, then totalSectors16 must be nonzero.


14-year-old boy stabbed during Bronx robbery
by WABCFORDHAM, The Bronx (WABC) -- A 14-year-old boy was stabbed during an apparent robbery in the Bronx Thursday, according to police.
It happened at Jerome and Fordham avenues in the Fordham section just before 12:30 p.m.
Authorities say the teen was stabbed and robbed of his cell phone.

The victim was taken to St. Barnabas Hospital in serious condition.