Food is a massive and complex arena in which culture, geography, climate, and social factors combine to create unique cuisines around the world. With the age of the internet, millions of recipes are now shared instantly and easily accessible. Many ingredients previously specific to certain regions of the world are now also widely available due to online commerce.
With a dataset containing information on the cuisine and ingredients for ~40,000 recipes, provided by Yummly, I have explored the ingredients that make up the signature flavors of cuisines around the world, along with some information on how they relate to each other. More details on the project can be found here.
This site hosts several recommendation engines built from the results of analysis of this data using Natural Language Processing techniques. Try them out!
Recipe ID Recommendations
Click here to receive recipe recommendations based on Recipe ID numbers.
Recipe Discovery
Click here to receive recipe recommendations similar to your recipe ID, from other cuisines.
Ingredient List-Based Recipe Recommendations
Click here to receive recipe recommendations based on a list of ingredients that you have on hand.
Complimentary Ingredient Recommendations
Click here to receive complimentary ingredient suggestions that are likely to pair well with your favorite recipe ingredients!
Links
Project Repository - github
Yummly - Website
Acknowledgements
I would like to thank the Springboard Data Science Career Track course, for all of the wonderful resources and tools that they have provided on my journey as an aspiring data scientist.
I would especially like to thank Alex Rutherford, who is my data science mentor and introduced me to the many techniques that made this project possible.
This site was built using templates and resources provided by w3schools.com


|
MXQuery 0.6.0 API Documentation - Copyright 2006-2009 ETH Zurich | ||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object ch.ethz.mxquery.sms.btree.Leaf
public class Leaf
Represents a b-tree leaf node.
| Constructor Summary | |
|---|---|
Leaf(int k_star)
|
|
Leaf(int k_star,
LeafArrayMap entries)
|
|
Leaf(int k_star,
LeafArrayMap entries,
InternalNode parent)
|
| Method Summary | |
|---|---|
SplitInfo |
add(DeweyIdentifier key,
LinguisticToken value,
DeweyIdentifier lowKey,
DeweyIdentifier highKey,
LeafCarrier leafCarrier)
Add (generally updates) is not supported in the BTree |
ObjectObjectPair |
bulkAdd(ObjectObjectPair data,
int k,
double F)
adds a data pair (key,value) if the leaf is full, create new leaf and return value and leaf else insert value into leaf |
BTreeNode |
get(DeweyIdentifier key)
|
BTreeNode |
getBTreeNode(DeweyIdentifier key)
Returns the internal node/ leaf that contains the key "key" |
void |
getFirstKeyAfter(DeweyIdentifier key,
Leaf[] inLeaf,
int[] atPos)
Creates pointers to the given key or if the key is not in the tree, to the smallest key larger than the given one that is in the tree. |
DeweyIdentifier |
getHighestKey()
|
void |
getLastKeyBefore(DeweyIdentifier key,
Leaf[] inLeaf,
int[] atPos)
Creates pointers to the given key or if the key is not in the tree, to the largest key smaller than the given one that is in the tree. |
DeweyIdentifier |
getLowestKey()
gets the lowest key recursively |
Leaf |
getNextLeaf()
|
Leaf |
getPrevLeaf()
|
BTreeNode |
getRoot()
To get the root of the btree this node is sitting in |
boolean |
isEmpty()
Indicates if this node is empty. |
boolean |
isEqual(Leaf leaf)
|
boolean |
isLeaf()
Indicates if this node is a leaf. |
void |
queryRange(DeweyIdentifier lowKey,
DeweyIdentifier highKey,
BtreePushOperator results)
Obtains all values mapped to the given key range (low and high, inclusive) |
void |
remove(DeweyIdentifier key,
LinguisticToken value,
DeweyIdentifier lowKey,
DeweyIdentifier highKey)
Remove (generally updates) is not supported in the BTree |
void |
removeValue(LinguisticToken value)
|
void |
setNextLeaf(Leaf nextLeaf)
|
void |
setParent(InternalNode parentNode)
sets the parentNode. |
java.lang.String |
toString()
|
| Methods inherited from class java.lang.Object |
|---|
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
| Constructor Detail |
|---|
public Leaf(int k_star, LeafArrayMap entries)
public Leaf(int k_star, LeafArrayMap entries, InternalNode parent)
public Leaf(int k_star)
| Method Detail |
|---|
public SplitInfo add(DeweyIdentifier key, LinguisticToken value, DeweyIdentifier lowKey, DeweyIdentifier highKey, LeafCarrier leafCarrier)
add
in interface BTreeNode
public void remove(DeweyIdentifier key, LinguisticToken value, DeweyIdentifier lowKey, DeweyIdentifier highKey)
remove
in interface BTreeNode
public java.lang.String toString()
toString
in class java.lang.Object
public BTreeNode get(DeweyIdentifier key)
public void queryRange(DeweyIdentifier lowKey, DeweyIdentifier highKey, BtreePushOperator results)
queryRange
in interface BTreeNode
lowKey
- highKey
- results
- public boolean isLeaf()
BTreeNode
isLeaf
in interface BTreeNode
public boolean isEmpty()
BTreeNode
isEmpty
in interface BTreeNode
public void removeValue(LinguisticToken value)
public ObjectObjectPair bulkAdd(ObjectObjectPair data, int k, double F)
bulkAdd
in interface BTreeNode
data
- k
- F
-
public BTreeNode getRoot()
BTreeNode
getRoot
in interface BTreeNode
public void setParent(InternalNode parentNode)
BTreeNode
setParent
in interface BTreeNode
public DeweyIdentifier getLowestKey()
BTreeNode
getLowestKey
in interface BTreeNode
public DeweyIdentifier getHighestKey()
public void setNextLeaf(Leaf nextLeaf)
public Leaf getNextLeaf()
public Leaf getPrevLeaf()
public boolean isEqual(Leaf leaf)
public void getFirstKeyAfter(DeweyIdentifier key, Leaf[] inLeaf, int[] atPos)
BTreeNode
getFirstKeyAfter
in interface BTreeNode
inLeaf
- points to the leaf where to get the keyatPos
- points to the position of the key inside the leafpublic void getLastKeyBefore(DeweyIdentifier key, Leaf[] inLeaf, int[] atPos)
BTreeNode
getLastKeyBefore
in interface BTreeNode
inLeaf
- points to the leaf where to get the keyatPos
- points to the position of the key inside the leafpublic BTreeNode getBTreeNode(DeweyIdentifier key)
BTreeNode
getBTreeNode
in interface BTreeNode
|
MXQuery 0.6.0 API Documentation - Copyright 2006-2009 ETH Zurich | ||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |


CardBean
object from the file system.CardBean
objects, by managing an internal
JDialog
object which provides the corresponding UI.JDialog
based dialog to display a given image file.JFileChooser
object in order to provide the functionality
to select a directory.CardBean
object is required.SetBean
object is required.


Expanded Project Information ..
The remote system (Basecamp) requires you to grant access before proceeding
Grant Access
Exit
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Project:
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Vist this project at Basecamp
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Lorem ipsum dolor, sit amet consectetur adipisicing elit.
...
It uses utility classes for typography and spacing to space content out within the larger container.
Lorem ipsum dolor, sit amet consectetur adipisicing elit.
...
It uses utility classes for typography and spacing to space content out within the larger container.


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Search for existed questionaires data
Release desired questionaires.The paid money will be deliveried to answers.
Answer questionaire and get paid.


IFTransmitter Class Reference
| Inherits from | NSObject |
|---|---|
| Declared in | IFTransmitter.h |
Overview
Every beacon object it’s a type of IFTransmitter, we can get it’s identifier, RSSI, distance, radius, coordinate, etc.
RSSI
Last RSSI value
@property (nonatomic, strong) NSNumber *RSSI
Discussion
Last RSSI value
Declared In
IFTransmitter.h
filteredRSSI
RSSI value filtered with our algorithms. This value is more ‘stable’ and less sensitive to signal strength fluctuations.
@property (nonatomic, readonly) NSNumber *filteredRSSI
Discussion
RSSI value filtered with our algorithms. This value is more ‘stable’ and less sensitive to signal strength fluctuations.
Declared In
IFTransmitter.h
nearRSSI
Parameter describing transmitter as near (is in near proximity), default is -30
@property (nonatomic) NSInteger nearRSSI
Discussion
Parameter describing transmitter as near (is in near proximity), default is -30
Declared In
IFTransmitter.h
UUID
Peripheral identifier as string. This value is created from calling [[CBPeripheral identifier] UUIDString]
@property (nonatomic, strong, readonly) NSString *UUID
Discussion
Peripheral identifier as string. This value is created from calling [[CBPeripheral identifier] UUIDString]
Declared In
IFTransmitter.h
– filteredDistance
– isNear
Is device very near to reciver (ca. 0.3m)
- (BOOL)isNear
Return Value
YES when near
Discussion
Is device very near to reciver (ca. 0.3m)
Declared In
IFTransmitter.h
– hasDisappeared
Disappearing mean no transmitter signal for some time.
- (BOOL)hasDisappeared
Return Value
YES when disappeared
Discussion
Disappearing mean no transmitter signal for some time.
Declared In
IFTransmitter.h
beacon
Get assigned model object describing beacon in geos system.
@property (nonatomic, retain) IFMBeacon *beacon
Discussion
Get assigned model object describing beacon in geos system.
Declared In
IFTransmitter.h
coordinate
Transmitter geo coordinates assigned in geos system.
@property (nonatomic) CLLocationCoordinate2D coordinate
Discussion
Transmitter geo coordinates assigned in geos system.
Declared In
IFTransmitter.h


This web page demonstrates a small portion of Lotus compiled to WebAssembly. Click on the buttons below to query "Ask" information from live miners on mainnet.
Connects to a configured Lotus JSON-RPC endpoint via WebSockets to perform a Filecoin.StateMinerInfo JSON-RPC call. The p2pd portion of the demo depends on a go-libp2p-daemon p2pd service that has been deployed publicly.
Note: The URLs are baked into the demo and there is no error handling, so the demo will fail if the services are offline or unreachable.
Signature verification and DHT lookups are currently disabled.


“Saddhāya pabbajitvāna,
agārasmānagāriyaṁ;
Vicariṁhaṁ tena tena,
lābhasakkāraussukā.
Having gone forth out of faith
from the lay life to homelessness,
I wandered here and there,
jealous of possessions and honors.
Riñcitvā paramaṁ atthaṁ,
hīnamatthaṁ asevihaṁ;
Kilesānaṁ vasaṁ gantvā,
sāmaññatthaṁ na bujjhihaṁ.
Neglecting the highest goal,
I pursued the lowest.
Under the sway of corruptions,
I never knew the goal of the ascetic life.
Tassā me ahu saṁvego,
nisinnāya vihārake;
Ummaggapaṭipannāmhi,
taṇhāya vasamāgatā.
I was struck with a sense of urgency
as I was sitting in my hut:
“I’m walking the wrong path,
under the sway of craving.
Appakaṁ jīvitaṁ mayhaṁ,
jarā byādhi ca maddati;
Purāyaṁ bhijjati kāyo,
na me kālo pamajjituṁ.
My life is short,
trampled by old age and sickness.
Before this body breaks apart,
there is no time for me to be careless.”
Yathābhūtamavekkhantī,
khandhānaṁ udayabbayaṁ;
Vimuttacittā uṭṭhāsiṁ,
kataṁ buddhassa sāsanan”ti.
I examined in line with reality
the rise and fall of the aggregates.
I stood up with mind liberated,
having fulfilled the Buddha’s instructions.
… Mittā kāḷī therī ….


Apply for help with NHS costs
You can't apply online yet
This service is being developed
You need to apply using a paper form called an HC1.
You can download an HC1 or get one from Jobcentres, GP practices, pharmacies and Citizens Advice centres.
Apply for help with NHS costs
You need to apply using a paper form called an HC1.
You can download an HC1 or get one from Jobcentres, GP practices, pharmacies and Citizens Advice centres.


PCB Order
After laying out your PCB, you probably want to order some PCBs. We have made it easy for you to save time and money by using our awesome service to order low cost, high quality PCBs directly from EasyEDA. More importantly, if you are not satisfied with the quality of our PCBs, EasyEDA will refund your money in full.
Although EasyEDA makes it easy to order PCBs for your projects and offers an exceptionally low PCB Manufacturing fee, you are free to download the Gerber files and order your PCBs from any other vendor. However, if you like EasyEDA, please give us a chance to fab. the PCB for you. We think you won't be disappointed.
PCB Quality
As engineers, we have spent more than 6 years building EasyEDA. As artisans, we believe that if you like using our EDA tools, then you will like our PCBs.
EasyEDA's PCB are in a group buy model and all PCBs are given 100% E-test This allows us to provide you with good quality, tested PCBs at a great price. We have shipped thousands to our users, all of whom like our PCBs.
No matter how good we tell you our service is, maybe you still have doubts. The easy way to remove those doubts is to try it out because - as we have said above - if you are not satisfied with the quality of our PCBs, we will refund your money in full. For details of this offer, please check the Warranty and Return.
Order Button
To order PCBs from us, just click the Fabrication Output... button in the PCB Editor window, as shown in the image below, and you will be redirected to an order page. In that page you can place an order quickly and easily. At the same time, at the clcik of a button, you can check the Gerber and drill files in our Online Gerber Viewer and then download your files. Obviously, we hope that you will support EasyEDA by ordering your PCBs from us but you are welcome to download the Gerber and drill files and send them to your favorite PCB house.
PCB Order from EasyEDA Editor
When you click the Fabrication Output...
button your order is coming from within the EasyEDA editor environment so you don't need to input information about Layers, Width and Height; EasyEDA fills this information in for you.
On the order form page you will find a real time price. Most of the time this price is the final cost however if, for example, you change the Layers to 4 or 6, you will find the price field changes to Quote. If that happens, don't worry: just click the Save to Cart
button and we will email a quote for the final price to you ASAP.
Note. When you add your PCB to the cart, EasyEDA saves a copy of Gerber files at that time. If you then change your PCB back in the PCB editor, EasyEDA does not synchronize your Gerber files to the updated PCB design. The only way is to delete the earlier version of the PCB from your Cart and then add the updated design as a new item.
PCB Order from Order Link
If you would like to upload your own Gerber files from a third party PCB tool such as Eagle, Pads, or Altium Design. To do this, just click this link https://easyeda.com/order to order. This page will let you upload your own Gerber Files.
PCB Capabilities
| Number of Copper Layers* | 1-16 |
| PCB Material | FR-4, FR4-Tg, FR4-High Tg |
| Available Solder Mask Colors | Green, Red, Yellow, Blue, White, Black |
| Silk Screen Colors | White, Black (For White Solder Mask only) |
| Minimum Quantity | 5 |
| Minimum dimensions* | 0.4cm x 0.4cm |
| Maximum dimensions* | 100cm x 100cm |
-
If your PCB requires more than the default maximum of 6 layers (up to a maximum of 16) or larger dimensions, please contact us before placing your order
-
If your PCB dimensions are bigger than 45cm * 45cm, maybe add a few addition cost
Manufacturing Specifications:
| Item | Specs | ||
| Unit: mm | Unit: mil | ||
| Available Board Thickness | 0.4, 0.6 (except 4 layer), 0.8, 1.0, 1.2, 1.6, 2.0 | 15.7, 23.6 (except 4 layer), 31.5, 39.4, 47.2, 63.0, 78.7 | |
| Thickness Tolerance | (t >= 1.0) ± 10% | (t >= 39.4) ± 10% | |
| Thickness Tolerance | (t < 1.0) ± 0.1% | (t < 39.4) ± 0.1% | |
| Insulation Layer Thickness | 0.075 - 5.0 | 2.95 - 196.85 | |
| Minimum trace width | 0.089 | 3.5 | |
| Minimum inner trace width | 0.127 | 5 | |
| Minimum trace/vias/pads space | 0.102 | 4 | |
| Minimum inner trace/vias/pads space | 0.102 | 4 | |
| Minimum silkscreen width | 0.1524 | 6 | |
| Minimum silkscreen text size | 0.8128 | 32 | |
| Outer Layer Copper Thickness | > 0.03 | > 1.18 | |
| Drilled Hole Diameter (Mechanical) | 0.3 - 6.35 | 11.81 - 250.00 | |
| Drilled Hole Diameter (Laser) | 0.2 - 0.3 | 7.87 - 11.81 | |
| Diameter Tolerance (Mechanical) | ±0.08 | ± 3.148 | |
| Solder Mask Bridges | 0.1 | 3.94 | |
| Circuit to edge | ≥0.3 | ≥11.8 | |
| Slot | ≥0.6 | ≥23.6 | |
| Slot Tolerance(Mechanical) | ±0.15 | ±6 | |
| Aspect Ratio | 8:1 | ||
| Solder Mask Type | Photosensitive ink |
If you have any special PCB requirements, please contact us before placing your order.
Price
All Prices stated are FOB Shenzhen. This does not include transportation costs which shall be borne by the customer.
Manufacturing Price
Price is dependant on many factors, such as the quantity of PCBs you order, PCB Color, Surface Finish, PCB Thickness, PCB Dimensions, Hole size etc.
EasyEDA uses a group buy business model and we are sure it will be hard to find a better PCB suppler than EasyEDA offering the same price and quality.
EasyEDA needs 2~4 days to manufacture the PCBs after you submit payment.
Shipping Costs
| Method | note | Price | Service |
| Air Mail | Delivery Time: 8-35 days. Most of our users receive their PCBs in two weeks. | From $6 | Usually http://www.singpost.com/ |
| Express | Delivery Time: 3-7 days | From $24 | Usually delivered by http://www.DHL.com/ |
Note: The shipping cost is estimated. EasyEDA will always try to find the best shipping option. If you are in some Remote Areas, we will ask you to pay for more or change to some other express service such as Fedex, UPS. Sometimes, we will use Hongkongpost for delivery by Airmail.
File Name
If your gerber files name are good, this will save us a lot of time in checking your design. There are many different PCB design software packages so there are many variations of gerber file names and filename extensions.
Gerber Type
If you don't know how to map your files, don't worry about changing the file names please contact support for help.
We encourage you to use our free online gerber viewer to check your gerber files before place an order.
E-Test
All PCBs undergo a 100% AOI (Automated Optical Inspection) to make sure that all tracks and pads are connected. In addition to this the PCBs can be tested by a flying probe to make sure that all vias are connected, because this is not visible by the AOI. Single layer PCBs do not require this test because there are no vias but boards with 2 layers and above will always be 100% tested with a flying probe.
Payment
We accept the PayPal, Credit Card and Wire Transfers.
PayPal and Credit Card
We use Paypal as our payment; it is safe and easy. If you don't have a Paypal account, you can still use Paypal to pay with a debit or credit card.
Wire Transfers
Wire Transfers can only be used on orders with a grand total (subtotal plus all additions and deductions but excluding shipping fees) of at least $600. For orders > $2000, payment by Wire Transfer is preferred. In this circumstance, 3.5% extra discount will be applied for the grand total (subtotal plus all additions and deductions but excluding shipping fees). Wire Transfer payments usually take 3-5 business days to clear. We will not ship your order until your payment is verified by our bank. Please send a copy of the Wire Transfer receipt to our customer service because although it is not sufficient to release an order, it will help us to push the delivery date.
Customs, Duties and Taxes
You should expect to pay any amount charged by the government in your respective country. This includes but is not limited to: duties, taxes and any extra fees charged by the courier company. We will not be held responsible for any extra charges once the original package has been shipped. If the customer refuses to pay these extra charges, the return shipping and any additional fees will be taken out of the cost of the order, with any remaining funds being refunded to the customer. Customs are quite different in each country. Please include information about particular Customs requirements as necessary, while you are placing your order: we will support you as much as possible.
Warranty and Return
For your first order for a PCB laid out in EasyEDA, we have the top return policy on the planet! If you don't like them, just send an email to
, no reason needed. We will provide your full money back - including product + shipping costs - in one working day.
For subsequent orders, because you now know the quality level of our PCBs, if you are not satisfied with a product you bought from us for whatever reason, you just need to email us some pictures of the product and explain why you are not happy with it. We will then refund the full money of the product. Shipping fees will only be refunded if the return is a result of a shipping error on our part.


Tcl/Tk Keywords - L
- l10n
-
msgcat
- label
-
label
- labelframe
-
labelframe
- length
-
llength, ListObj
- level
-
info, uplevel, upvar
- library
-
library
- line
-
gets
- linemode
-
fconfigure
- link
-
LinkVar
- linked variable
-
UpVar
- list
-
foreach, join, lappend, lindex, linsert, list, llength, lrange, lreplace, lsearch, lset, lsort, split, ListObj, SetResult, SplitList
- list object
-
ListObj
- list type
-
ListObj
- listbox
-
listbox
- lists
-
concat
- load
-
safe, loadTk, Tk_Init
- loading
-
load
- localization
-
msgcat
- location
-
grid, pack, place, GetVRoot
- lookup
-
Hash
- loop
-
break, continue, while
- looping
-
for, foreach
- lower
-
lower
Copyright © 1989-1994 The Regents of the University of California.
Copyright © 1990-1994 The Regents of the University of California
Copyright © 1992-1999 Karl Lehenbauer and Mark Diekhans
Copyright © 1992-1999 Karl Lehenbauer and Mark Diekhans.
Copyright © 1993-1997 Bell Labs Innovations for Lucent Technologies
Copyright © 1994 The Australian National University
Copyright © 1994-2000 Sun Microsystems, Inc.
Copyright © 1997-2000 Ajuba Solutions.
Copyright © 1997-2000 Scriptics Corporation.
Copyright © 1998 Mark Harrison.
Copyright © 1998-1999 Scriptics Corporation
Copyright © 1998-2000 Ajuba Solutions
Copyright © 1999 Scriptics Corportation
Copyright © 2000 Jeffrey Hobbs.
Copyright © 2001 ActiveState Tool Corp.
Copyright © 2001 Kevin B. Kenny.
Copyright © 2001 Vincent Darley
Copyright © 2001-2002 ActiveState Corporation
Copyright © 2001-2002 Donal K. Fellows
Copyright © 2001-2002 Kevin B. Kenny. All rights reserved.
Copyright © 2001-2004 ActiveState Corporation.
Copyright © 2006-2007 Daniel A. Steffen
Copyright © 1995-1997 Roger E. Critchlow Jr.


Core Legacy
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Research frequency self-assessment
Conduct research repeatedly through all phases of product development.
Research isn’t confined to one phase of product development. And each phase of product development should include more than one research study. For example:
- Discovery could include observations, interviews, secondary literature review or other background data gathering.
- Alpha could include prototype testing, usability testing or larger scale testing.
- Beta could include repeated usability testing, A/B testing or analytics analysis.
There’s no simple guideline for how often research should happen.
How often should you usability test in alpha and beta? How often should you conduct interviews in discovery? There is no simple answer to these questions. Instead, conduct research often enough that you score well on the following self-assement.
Use this self-assessment to evaluate your research pace:
Check each statement you agree with.
-
We make major delivery decisions based on research. We decide what to build, how to build it, and what order to build it in, based on research. Conduct research often enough that you can make those decisions based on research.
-
We identify substantial issues before we release to the public. Our research doesn’t just help us make decisions; it also identifies problems we didn’t know we had. Conduct research often enough that you can identify those problems before you release.
-
We test whether we actually fixed the issues we’ve found. When we try to fix issues, we can sometimes make them worse. Conduct research often enough that we can be sure our fixes have the intended effect.
-
We don’t just conduct research to support decisions we’ve already made. We think about how research informs design before plunging ahead into building more. We’re not just conducting research to test things we’ve already built. Conduct research slowly enough that you figure out what’s happening.
-
We have enough time to address major issues before testing again. We don’t retest and find the same issues over and over again. Conduct research at a pace that allows you to fix problems before you test again.
-
We include all the participants we should (including preferred language, assistive technology, bandwidth). Fast past research can come at the expense of groups that are harder to recruit or take longer to interview. We often forget to include people with disabilities. Or people with low bandwidth in our testing. Research isn’t complete without them. Conduct research at a pace that allows us to include and listen to everyone.
-
Our team and researcher isn’t burnt out. Research is intellectually, emotionally and physically consuming. Tired researchers don’t do their best work. Tired teams aren’t the most supportive. Conduct research at a speed that’s challenging, but not overwhelming.
Scoring the self assessment
- Did you check six or seven boxes? You’re doing well. Pat yourself on the back.
- Did you not check numbers 1-3? Consider ways to speed up your research. You’re likely conducting high quality research that isn’t as influential as it might be.
- Did you not check numbers 4-7? Consider ways to slow down your research. You may be conducting enough research, but could make better use of it.
- Missing checkmarks on both 1-3 and 4-7? Focus on getting 1-3 right, and then refining your process to meet 4-7.
- Last updated by Colin on May 27, 2019


Simultaneous rotation around multiple axes. 3D animation of mouse colon tumors using blood vessel staining (CD31; red), ECi-based tissue clearing and a LaVision BioTec lightsheet UltraMicroscope II (see also Figure 1). The image volume is rotated around its y-axis (with a higher speed) and around the x-axis of the view (with a lower speed). Only a couple of text lines are required to describe an animation which is hard to achieve with key frame-based animation.
Animated transformation through time. Animation of a growing zebrafish nervous system, imaged on a custom built lightsheet microscope. While the time-lapse progresses, the image volume is spatially transformed. Scale bar 100 µm
Simultaneous pivoting and channel switching. Animation of a mouse paw, imaged on a LaVision BioTec lightsheet UltraMicroscope II. Pivoting is implemented using a macro.
Consecutive zoom-in and scroll-through at different positions. Animation of a mouse paw, imaged on a LaVision BioTec lightsheet UltraMicroscope II.
Macro for parameterized zooming. Animation of a human cornea, imaged on a Zeiss LSM880 NLO 2-photon microscope. The data set is elongated in one dimension. Instead of zooming out during the entire animation, the zoom is adjusted to the rotation to always fill the available movie canvas optimally, using a macro.
Rendering of an MRI image volume of a human head using the BigDataViewer. To demonstrate the extendibility of our framework, we wrote an adapter for Fiji’s BigDataViewer.
Rendering of an organoid from the mouse intestine in an artificial laboratory environment. To demonstrate extendibility of our framework, we wrote an adapter that uses POV-Ray, a software for photorealistic rendering, instead of the integrated 3D renderer.
Composing an animation. This screencast demonstrates how the animation of the human cornea is built up and highlights the auto-completion features of the Animation Editor. A detailed step-by-step description is also found in the manual.
A dedicated animation editor, based on Fiji's script editor, facilitates the composition of the animation description with auto-completion and recording capabilities.
The dedicated animation editor can record different rendering states and automatically create the description text to transition between them.


Tree-Walking with Nuthatch
Nuthatch is a system of traversing, collecting information from, and rewriting trees, based on the idea of tree walking. The main application is software analysis and transformation. We provide a library, Nuthatch/J, for doing tree walking in Java, with adapters for interfacing with popular software transformation tools like Stratego/XT and Rascal.
Transformations are described as walks that proceed in programmer-defined steps. Each step may which may observe join points of a traversal, and affect state associated with the walk and also rewrite the walked tree. Each step ends by walking to a different node in the tree, following the tree branches.
Nuthatch is described in the upcoming paper Walk Your Tree Any Way You Want.


Our team of experts research the world for your perfect vehicle. Afer locating it we negotiate a price on your behalf.
We offer a range of financing options to tailored to your needs. We offer discrete and privacy with our transactions eliminating any concerns of security.
Our fully insured and bonded delivery experts cover every details of import/export logistics. We offer a variety of delivery options to best fit your needs.


August 2015
- Right Questions for Right Answers
- SQL Injection
- Misunderstood Professionalism
- Exploring My Values
- OOP and FP
- Have a Cup of JavaScript
- Object-Oriented and Functional Programming
- Disengaging the Autopilot
July 2015
- Class is in Session
- Cycling Through Music
- Life in Structure
- Feedbackinator
- On-demand Failure
- Abstract Thinking
- Style for the Modern Gentleman
- Version Control, Git and GitHub


‘Gandhi villages’ to be established in Rajasthan
To apprise the people of the Mahatma’s life and contributions
The Congress government in Rajasthan has decided to constitute a new Department of Peace and Non-Violence, along with “Gandhi villages” in each district, to apprise the people of the contributions of the Mahatma. The Department will act as a nodal agency for the implementation of Gandhian thought.
The Gandhi villages will promote Gandhian ideology through exhibitions in schools, spread the digital contents and publicise his role in the freedom struggle. The programmes marking the birth anniversary will be organised across the State till October 2, 2020.
The discussion on “Gandhi: An Illustrated Biography”, authored by Pramod Kapoor, centred on some untouched aspects of the Mahatma’s life. The participants said the Gandhian philosophy required a deeper research for its full understanding.
The discussion was organised by the IAS Association at the HCM State Institute of Public Administration. A pictorial exhibition of Gandhiji’s life on a 121-foot-long khadi cloth was a special attraction.
IAS Association's literary secretary Mugdha Sinha said the present generation was getting an inspiration from Mahatma Gandhi’s life by exploring newer aspects of his thoughts, long after his death in 1948.


class CC3K – control CC3000 WiFi modules¶
This class provides a driver for CC3000 WiFi modules. Example usage:
import network
nic = network.CC3K(pyb.SPI(2), pyb.Pin.board.Y5, pyb.Pin.board.Y4, pyb.Pin.board.Y3)
nic.connect('your-ssid', 'your-password')
while not nic.isconnected():
pyb.delay(50)
print(nic.ifconfig())
# now use socket as usual
...
For this example to work the CC3000 module must have the following connections:
MOSI connected to Y8
MISO connected to Y7
CLK connected to Y6
CS connected to Y5
VBEN connected to Y4
IRQ connected to Y3
It is possible to use other SPI busses and other pins for CS, VBEN and IRQ.
Constructors¶
-
class
network.
CC3K
(spi, pin_cs, pin_en, pin_irq)¶ Create a CC3K driver object, initialise the CC3000 module using the given SPI bus and pins, and return the CC3K object.
Arguments are:
spi is an SPI object which is the SPI bus that the CC3000 is connected to (the MOSI, MISO and CLK pins).
pin_cs is a Pin object which is connected to the CC3000 CS pin.
pin_en is a Pin object which is connected to the CC3000 VBEN pin.
pin_irq is a Pin object which is connected to the CC3000 IRQ pin.
All of these objects will be initialised by the driver, so there is no need to initialise them yourself. For example, you can use:
nic = network.CC3K(pyb.SPI(2), pyb.Pin.board.Y5, pyb.Pin.board.Y4, pyb.Pin.board.Y3)
Methods¶
-
CC3K.
connect
(ssid, key=None, *, security=WPA2, bssid=None)¶ Connect to a WiFi access point using the given SSID, and other security parameters.
-
CC3K.
disconnect
()¶ Disconnect from the WiFi access point.
-
CC3K.
isconnected
()¶ Returns True if connected to a WiFi access point and has a valid IP address, False otherwise.
-
CC3K.
ifconfig
()¶ Returns a 7-tuple with (ip, subnet mask, gateway, DNS server, DHCP server, MAC address, SSID).
-
CC3K.
patch_version
()¶ Return the version of the patch program (firmware) on the CC3000.
-
CC3K.
patch_program
('pgm')¶ Upload the current firmware to the CC3000. You must pass ‘pgm’ as the first argument in order for the upload to proceed.


Honda-Powered, all-wheel drive Classic Mini for sale at $49,000
The tuning potential of BMW cars is one of the reasons why people love them to death, including the E36 generation. That potential has been …
by Gabriel NicaStraight out of the ‘world of ingenious creations’ we’re bringing you one tough classic Mini today. This car is no longer in sync with its British origins but to some it may be even better this way. This Mini has been heavily modified by some crazy shop in Georgia and now sports a Honda CR-V engine. It also comes with an all-wheel drive system along with a myriad of other changes that make it unique. The best bit is that it can be yours right now, for $49,000.
That’s quite a lot for such an old Mini but then again, you need to hear the rest of the story before passing judgement. The car was built by Minitec, a shop in Royston, Georgia that specializes in swapping Honda powertrains into Minis. According to the ad, over $80,000 has been invested into making it the proper pocket rocket it is today and I have to say, the build quality and the specs are impressive.
Over the course of its transformation the car received new subframes, a new anti-roll cage, coilover suspension, wide-body kit and even racing bucket seats. The engine is a B20 Honda unit with Vtec, and limited slip differentials both up front and in the back because the Mini is now all-wheel drive. The engine and AWD system are controlled by a Hondata S3000 ECU. The car also has a new exhaust, bigger brakes to keep up with the new engine and AC.
For the amount of work that went into it (you can check out the entire list here) the $49,000 price tag doesn’t seem such a ludicrous proposal anymore. This thing could probably enter rally stages and finish them without breaking a sweat. You can also check it out in the video below, in case you want to hear how it sounds. So, would you be interested? Is it worth the money?


A SOLDIER'S DAUGHTER NEVER CRIES Cast: Kris Kristofferson, Barbara Hershey, Leelee Sobieski, Jesse Bradford, Anthony Ruth Costanzo, Dominique Blanc, Virginie Ledoyen, Samuel Gruen, Luisa Conlon Director: James Ivory Screenplay: James Ivory, Ruth Prawer Jhabvala based on the novel by Kaylie Jones Running time: 124 minutes Australian theatrical release: January 28, 1999 Reviewed by Luke Buckmaster
On the Buckmaster scale of 0 stars (bomb), to 5 stars (a masterpiece): 2 stars
Coming of age films - or films that develop their characters over decades of their lives - all face a similar problem. Obviously, it is impossible to fit all of life's experiences in the span of two hours, so the most that a writer can do is carefully choose scenes that examine their characters best. The aggravating thing about A Soldier's Daughter Never Cries is that it presents a trade off that isn't very fair: in order to watch its characters undergo their life defining experiences, you also have to sit through the uninteresting and dreary moments which shape their existence. No one can accuse director James Ivory of being unrealistic; instead, we can accuse him of being inefficient.
The film revolves around an American family living in Paris during the 60's and 70's. Father Bill Willis (Kris Kristofferson) is a successful writer and a World War II veteran, and Mother Marcella (Barbara Hershey) is a flamboyant heavy drinker. They have two children - daughter Channe (played by Luisa Conlon as a child and Deep Impact's Leelee Sobieski as a teenager) and adopted son Billy (Samuel Gruen then Jesse Bradford). The Willis family have a strong love and appreciation for each other; the two kids especially having an obvious respect for their wise and gentle father.
Each of the Willis' experience their own set of hardships. Mum and Dad worry that Billy will be taken away from them, Channe struggles to be accepted in her various high schools, and Billy becomes a social outcast.
The synopsis above does not indicate a one way storyboard, and rightfully so. A Soldiers Daughter Never Cries is multi-layered conventional drama, hiding the fact that it doesn't have much of a plot. Instead, it is primarily a collection of dramatic scenes that attempt to illustrate each of the characters' emotional breadth. Ivory pulls this off with only reasonable success. Some of the film's best moments are when Channe becomes best friends with a boy named Francis (Anthony Ruth Costanzo) who, by textbook definition, will grow up to be gay. "You're weird, you act like a girl," she tells him. Francis retorts by explaining that he acts like nobody but himself. But he is only one of the supporting characters who abruptly disappear from the screen. Ivory tries so hard to focus on the Willis family that none of his other characters have the chance to make a lasting impression. He succeeds in giving the film a heart, but in the process forgets to give it a brain.
Leelee Sobieski is able to grasp much of what her role requires. She plays Channe with a calm and controlled presence, but gives a gutsy (and risky) performance. Most of the faults in her portrayal can be narrowed down to the screenplay, which never accurately represents the hardships of puberty. It also never makes that much sense, as I was left pondering why we witness Channe having her period in class and wearing her first bra, when the loss of her virginity is only given a mention in one conversation. The rest of the cast are uniformly strong (especially the younger two actors, Luisa Conlon and Samuel Gruen), although each of their characters lack flair.
For those with patience and do not mind a flat ending, A Soldier's Daughter Never Cries may provide some pleasant viewing. Like many others like it, the film is paced very slowly and its tone and style remain consistent. But given his material, James Ivory should have bent over backwards to ensure that his film was never boring. He gives A Soldiers Daughter Never Cries a heart, but not much else. This is one trade-off that just doesn't seem fair.
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Read more of my reviews at Alphalink Movies: http://moviezone.alphalink.com.au
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PASRO is Pennsylvania's leading authority on school-based policing with an emphasis on the safety of those in the educational environment while serving as a mentor and teacher to students in the classroom.
The Office of Community Oriented Policing Services released a report on actions to improve school safety.
Despite COVID-19, PASRO had a successful second conference in State College, PA.
The PASRO Store is now open! Order online and have your order shipped to you.
Sgt. Sgro, in addition to serving as the past president of PASRO, was also PA SADD's inaugural SRO of the Year.


Martin Andrews @ redcatlabs.com
23 July 2016
Android feature since Jellybean (v4.3, 2012) using Cloud
Trained in ~5 days on 800 machine cluster
Embedded in phone since Android Lollipop (v5.0, 2014)
Google's Deep Models are on the phone
"Use your camera to translate text instantly in 26 languages"
Translations for typed text in 90 languages
Google Street-View (and ReCaptchas)
(now human competitive on ImageNet)
Some good, some not-so-good
Google's DeepMind purchase
Learn to play games from the pixels alone
Better than humans 2 hours after switching on
Google DeepMind's AlphaGo
Learn to play Go from (mostly) self-play
Change weights to change output function
Layers of neurons combine and
can form more complex functions
x
→ target_y
)output_y
from the x
output_y
is closer to target_y
for that x
Follow the gradient of the error
vs the connection weights
http://ConvNetJS.com/
(or search online for TensorFlow Playground)
deep-learning ... .OVA
'http://localhost:8080/
ssh
- it should Just Work
ssh -p 8282 user@localhost
# password=password
GoogLeNet (2014)
Play with a ~2014 pre-trained network
... need for GPU programmers
Quick Overview of VM
MNIST again...
Re-purpose a pretrained network
Google Inception-v3 (2015)
Play with a ~2015 pre-trained network
Careful! : Some images cannot be un-seen...
Style-Transfer an artist onto your photos
A Long Short-Term Memory (LSTM) Unit
Still a work-in-progress (training takes too long)
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?)9.#s7X]}$*sxZ"3tf ")
@'HW.;I5)C.*%}<jcNLN+Z__RWoryOb#
/`r
Som the riscele his nreing the timest stordor hep pIs dach suedests her, so for farmauteds?
By arnouy ig wore
Thou hoasul dove he five grom ays he bare as bleen,
The seend,
And, an neeer,
Whis with the rauk with, for be collenss ore his son froven faredure:
Then andy bround'd the CowE nom shmlls everom thoy men ellone per in the lave ofpen the way ghiind, thour eyes in is ple gull heart sind, I I wild,
Frreasuce anspeve, wrom fant beiver, not the afan
And in thou' histwish a it wheme-tis lating ble the liveculd;
Noorroint he fhallought, othelts.
AWhis grook my glass' to his sweet,
Bub my fears liken?
And of live every in seedher;
A Lood stall,
But tare tought than thencer sud earth,
Use'st bee sechion,
For all exprit' are a daud in heaven doth her infook perust the fork the tent.
For maud,
The pittent gover
This and rimp,
Who new
Thoir oldes and did hards, cound.
DEDENIUS Why shoulmeying to to wife,
And thou say: and wall you teading for
that struke you down as sweet one.
With be more bornow, bly unjout on the account:
I duked you did four conlian unfortuned drausing-
to sicgia stranss, or not sleepplins his arms
Gentlemen? as write lord; gave sold.
AENEMUUNS Met that will knop unhian, where ever have
of the keep his jangst?icks he I love hide,
Jach heard which offen, sir!'
[Exit PATIIUS, MARGARUS arr [Enter CLOTHUR]
Deep Reinforcement Learning for Bubble Breaker
* Please add a star... *
My blog : http://mdda.net/
GitHub : mdda
numpy
and BLAS
C/C++
or CUDA
(or OpenCL
)Use the 'play' button to walk through the workbook
... around 2-3% error rate on the test set
We using lasagne
as an additional layer on top of Theano
Three filter layers - nice visual interpretation
Using an Autoencoder
Re-purpose a pretrained network
Differentiable → Training : Even crazy stuff works!
* Please add a star... *
My blog : http://mdda.net/
GitHub : mdda


Nikhil & Pooja's Wedding
on 04 April 2018
It’s my big day! My fiance and I are very excited to invite you to our wedding. Lorem ipsum dolor sit amet, consectetur adipisicing elit. Ratione reiciendis, iusto distinctio debitis animi fugiat officia mollitia, aut possimus repellendus pariatur quod quasi ipsa ad tempora, itaque expedita eum dolores.


Select Tickets
Step 1 Please select the day you want to join the World Music Festival 2020
| Ticket | 1-Day-Ticket | 2-Day-Ticket | FM Affiliate/Partners | |
|---|---|---|---|---|
| Date | 15. Oct(Thu) | 16. Oct(Fri) | 15.-16. Oct(Thu-Fri) | 15.-16. Oct(Thu-Fri) |
| Normal |
$70,000 |
$70,000 |
$100,000 |
$0 |
| Students |
$30,000 |
$30,000 |
$50,000 |
$0 |
Select Your Lunch
Step 2 Please select your lunch for registration day
| Normal | ||||
|---|---|---|---|---|
| Menu 1 | Menu 2 | Menu 3 | Menu 4 | Menu 5 |
| Students | ||||
|---|---|---|---|---|
| Menu 1 | Menu 2 | Menu 3 | Menu 4 | Menu 5 |


Roles Refactor
In our second pass through the project we will take the now more modular solution a step further and break it into roles. In this case we will basically map each of the 3 playbooks from Part 3 into 1 role each
-
Create a new branch refactor-pass-02-roles
-
Create a roles sub-directory in the repo
-
Create each role
-
Copy the tasks from your playbook into the roles
tasks/main.yml
-
Consider moving some/all vars into the roles
defaults/main.yml
orvars/main.yml
-
Turning the Postgres Play into a Role
We will start here and document the steps for our first role. The remainimg 2 roles for flask
and HAProxy
will basically repeat the same pattern.
-
Create a new branch
refactor-pass-02-roles
git checkout -b refactor-pass-02-roles
Sample OutputSwitched to a new branch 'refactor-pass-02-roles'
-
Make a roles sub-directory
mkdir roles
-
Use
ansible-galaxy
to create the skeleton for thepostgres
roleansible-galaxy init roles/postgres
Sample Output- Role roles/postgres was created successfully
The
tree
command, not always installed, is useful to visualize directory structures. Try this,sudo yum install tree -y
thentree roles
to see your role:Sample Outputroles └── postgres ├── defaults │ └── main.yml ├── files ├── handlers │ └── main.yml ├── meta │ └── main.yml ├── README.md ├── tasks │ └── main.yml ├── templates ├── tests │ ├── inventory │ └── test.yml └── vars └── main.yml
-
Start by creating your roles
tasks/main.yml
The easiest starting place is to copy your provision_database_tier.yml into the roles
tasks/main.yml
.cp provision_database_tier.yml roles/postgres/tasks/main.yml
-
Now edit and fix the
tasks/main.yml
Delete everything except the tasks themselves, no need for to keep the
tasks:
directive and fix the indentation by moving everything left (vim
is extremely good for this with commands like<<
and n`<<` where n is the count operator. eg5<<
outdents 5 lines)Don’t forget to delete the
handler
section at the bottom of the play.Your top 10 lines should now look like this:
head roles/postgres/tasks/main.yml
Sample Output--- - name: Install Postgres packages package: name: "{{ __package }}" state: present loop: - "{{ postgres_rhel7_repo }}" - "{{ postgres_packages }}" - "{{ postgres_library }}" loop_control:
-
Now repeat a similar process to steps 4 and 5 above except this time with the roles
handlers/main.yml
Once you have finished your
roles/postgres/handlers.yml
should look like this:--- - name: restart_postgres service: name: "{{ postgres_service }}" state: restarted
-
Roles have in-built support for templates and your postgres playbook referenced
templates/pg_hba.conf.j2
-
Move your
templates/pg_hba.conf.j2
toroles/postgres/templates/
-
Update your
roles/postgres/tasks/main.yml
to remove the path to thepg_hba.conf.j2
template as the role knows "where to look"Your roles
template
task inroles/postgres/tasks/main.yml
should now look like this- name: Setup Postgres for remote password auth template: src: pg_hba.conf.j2 dest: "{{ postgres_10_data_dir }}/pg_hba.conf" notify: restart_postgres
-
-
Update your
provision_database_tier.yml
playbook to use the rolepostgres
and delete the oldtasks
andhandlers
codeYour
provision_database_tier.yml
should look like this:--- - name: Deploy, configure, and populate Postgres 10 hosts: database_servers become: true gather_facts: false tags: - database_servers roles: - postgres
-
Finally test your new role by running the
provision_database_tier.yml
either directly or viasite.yml
You mean want to delete your application first via
ansible-playbook teardown-app.yml
Success (hopefully)
If not debug your issues until you can successfully deploy and configure Postgres by your role.
-
Commit your changes
git add roles git commit -am "Moved postgres playbook to use new postgres role"
-
Push your changes to your repo
If you have set up your own fork
git push
git
may ask you to perform some adminstrative commands and if it is your first push on this branchgit push --set-upstream origin refactor-pass-02-roles
Repeat the above Process for your remaining playbooks
Once you have converted both provision_app_tier.yml
and provision_load_balancer_tier.yml
to roles based playbooks re-run the whole deploy end to end
ansible-playbook teardown-app.yml
ansible-playbook site.yml
Solution
One possible solution can be seen here in the solution refactor-pass-02-roles
branch, either:
-
Browse to the
refactor-pass-02-roles
branch -
Download the solution and checkout the
refactor-pass-02-roles
branchgit clone https://github.com/tonykay/solution_ansible_flask_app_loader_all_in_one cd solution_ansible_flask_app_loader_all_in_on git checkout refactor-pass-02-roles
Next Steps
Unfortunately your roles, whilst working, are not complete.
At this point they cannot be used standalone as they lack the necessary variables which are all being acquired through your group_vars
.
In the next lab we will look at what variables belong inside the roles, and where, and what variables should remain external.
Then we will also clean up your roles, removing redundant files etc.
In Part 5 we will continue to work with roles
and enhance them to be re-usable across multiple projects with sensible default behavior "out of the box".


---
layout: post
title: RS232 with a PIC 16F627
date: '2007-08-03T01:34:00.000+02:00'
author: Steven Van Acker
tags:
- English
- PIC
- Building Stuff
modified_time: '2009-02-03T14:05:56.353+01:00'
blogger_id: tag:blogger.com,1999:blog-5513234137363262204.post-3440546645534743841
blogger_orig_url: http://www.singularity.be/2007/08/rs232-with-pic-16f627.html
---
Yesterday I wrote some assembly programs to do halfstep, fullstep and wavedrive control of a steppermotor, but the program just ran continuously in 1 direction. That's of course not so cool.
What I want is to tell the PIC how many steps it should make in a certain direction, and then it should do so. This means I need to send commands to it once it's running (i.e. interactively). The most likely way good way to do this, is by using the RS232 functionality (serial line).
Here is some example code on how to use a serial line with a PIC:
http://piccourses.50megs.com/code/codesamples.htm#rs232sendback


Page has moved
This page has moved to a new location. Please visit
http://www.w3.org/2005/04/fresnel-info/fsl/
.


| Class and Description |
|---|
| DrillTable |
| Class and Description |
|---|
| DrillScanRel
GroupScan of a Drill table.
|
| DrillTable |
| Class and Description |
|---|
| CreateTableEntry
Interface that provides the info needed to create a new table.
|
| DrillJoin
Interface which needs to be implemented by all the join relation expressions.
|
| DrillParseContext |
| DrillTable |
| FieldsReWriterUtil.DesiredField
Holder class to store field information (name and type) with the list of nodes this field is used in.
|
| FieldsReWriterUtil.FieldsReWriter
Replaces original node with provided in mapper, otherwise returns original node.
|
| Class and Description |
|---|
| DrillFilterRel |
| DrillOptiq.RexToDrill |
| DrillParseContext |
| DrillProjectRel
Project implemented in Drill.
|
| DrillScanRel
GroupScan of a Drill table.
|
| DrillSortRel
Sort implemented in Drill.
|
| DrillTable |
| Class and Description |
|---|
| DrillScanRel
GroupScan of a Drill table.
|
| Class and Description |
|---|
| ConvertMetadataAggregateToDirectScanRule
Rule which converts
|
| CreateTableEntry
Interface that provides the info needed to create a new table.
|
| DrillAggregateRel
Aggregation implemented in Drill.
|
| DrillAnalyzeRel
Drill logical node for "Analyze".
|
| DrillFilterRel |
| DrillImplementor
Context for converting a tree of
DrillRel nodes into a Drill logical plan. |
| DrillJoin
Interface which needs to be implemented by all the join relation expressions.
|
| DrillJoinRel
Logical Join implemented in Drill.
|
| DrillLimitRel |
| DrillLimitRule
This rule converts a Sort that has either a offset and fetch into a Drill Sort and LimitPOP Rel
|
| DrillMergeFilterRule
MergeFilterRule implements the rule for combining two
Filter s |
| DrillMergeProjectRule
Rule for merging two projects provided the projects aren't projecting identical sets of
input references.
|
| DrillParseContext |
| DrillProjectLateralJoinTransposeRule |
| DrillProjectPushIntoLateralJoinRule |
| DrillProjectRel
Project implemented in Drill.
|
| DrillPushLimitToScanRule |
| DrillPushRowKeyJoinToScanRule
This rule implements the run-time filter pushdown via the rowkey join for queries with row-key filters.
|
| DrillReduceAggregatesRule
Rule to reduce aggregates to simpler forms.
|
| DrillRel
Relational expression that is implemented in Drill.
|
| DrillScanRel
GroupScan of a Drill table.
|
| DrillSemiJoinRel |
| DrillSortRel
Sort implemented in Drill.
|
| DrillTable |
| DrillUnionRel
Union implemented in Drill.
|
| DrillViewInfoProvider
Interface used by Drill components such as InformationSchema generator to get view info.
|
| EnumerableDrillRule
Rule that converts any Drill relational expression to enumerable format by adding a
DrillScreenRelBase . |
| PreProcessLogicalRel
This class rewrites all the project expression that contain convert_to/ convert_from
to actual implementations.
|
| RowKeyJoinCallContext |
| RowKeyJoinCallContext.RowKey |
| RowKeyJoinRel |
| ScanFieldDeterminer.FieldList |
| StoragePlugins
Map of storage plugin *configurations* indexed by name.
|
| Class and Description |
|---|
| CreateTableEntry
Interface that provides the info needed to create a new table.
|
| DrillAggregateRel
Aggregation implemented in Drill.
|
| DrillJoin
Interface which needs to be implemented by all the join relation expressions.
|
| DrillParseContext |
| RowKeyJoinRel |
| Class and Description |
|---|
| DrillScanRel
GroupScan of a Drill table.
|
| Class and Description |
|---|
| DrillRel
Relational expression that is implemented in Drill.
|
| DrillScanRel
GroupScan of a Drill table.
|
| DrillTable |
| Class and Description |
|---|
| CreateTableEntry
Interface that provides the info needed to create a new table.
|
| DrillTable |
| StoragePlugins
Map of storage plugin *configurations* indexed by name.
|
| Class and Description |
|---|
| DrillFilterRel |
| DrillProjectRel
Project implemented in Drill.
|
| DrillScanRel
GroupScan of a Drill table.
|
| Class and Description |
|---|
| CreateTableEntry
Interface that provides the info needed to create a new table.
|
| DrillTable |
| Class and Description |
|---|
| DrillTable |
| Class and Description |
|---|
| DrillTable |
| DrillViewInfoProvider
Interface used by Drill components such as InformationSchema generator to get view info.
|
| DrillViewTable |
| Class and Description |
|---|
| DrillTable |
| Class and Description |
|---|
| DrillImplementor
Context for converting a tree of
DrillRel nodes into a Drill logical plan. |
| DrillRel
Relational expression that is implemented in Drill.
|
| Class and Description |
|---|
| DrillTable |
| DynamicDrillTable |
| Class and Description |
|---|
| DrillTable |
| Class and Description |
|---|
| DrillTable |
| Class and Description |
|---|
| DrillTable |
| Class and Description |
|---|
| DrillTable |
| DynamicDrillTable |
| Class and Description |
|---|
| DrillTable |
| Class and Description |
|---|
| DrillTable |
| Class and Description |
|---|
| DrillTable |
Copyright © 2021 The Apache Software Foundation. All rights reserved.


|
ActionComponents
04.05.00
Customizable UI and time-saving tools for iOS development with Xamarin and Visual Studio.
|
Handles the Navigation Bar that can be shown at the top of a ACTileController
. The developer can include Buttons
on the left and right hand sides of the bar.
More...
Public Member Functions | |
| ACTileNavigationBar () | |
Initializes a new instance of the ACTileNavigationBar class. More... | |
| ACTileNavigationBar (ACTileController controller) | |
Initializes a new instance of the ACTileNavigationBar class. More... | |
| ACTileNavigationBar (NSCoder coder) | |
Initializes a new instance of the ACTileNavigationBar class. More... | |
| ACTileNavigationBar (NSObjectFlag flag) | |
Initializes a new instance of the ACTileNavigationBar class. More... | |
| ACTileNavigationBar (RectangleF bounds) | |
Initializes a new instance of the ACTileNavigationBar class. More... | |
| ACTileNavigationBar (IntPtr ptr) | |
Initializes a new instance of the ACTileNavigationBar class. More... | |
| virtual void | BarShownCompleted () |
| Bars the shown completed. More... | |
| virtual void | BarHiddenCompleted () |
| Bars the hidden completed. More... | |
| void | Redraw () |
Forces this ACTileNavigationBar to fully redraw itself More... | |
| void | Resize (nfloat width) |
| Resize to the specified width. More... | |
| void | ShowNavigationBar (bool animated) |
Shows the ACTileNavigationBar More... | |
| void | HideNavigationBar (bool animated) |
Hides the ACTileNavigationBar More... | |
| UIButton | AddLeftButton (string title, UIImage icon, nfloat width, nfloat height, EventHandler action) |
| Adds a new button to the left side of the navigation bar. More... | |
| void | AddLeftButton (UIButton button) |
| Adds the given button to the left side of the control. More... | |
| void | RemoveLeftButton (int n) |
| Removes the requested button from the left side of the navigation bar. More... | |
| UIButton | AddRightButton (string title, UIImage icon, nfloat width, nfloat height, EventHandler action) |
| Adds a button to the right side of the navigation bar. More... | |
| void | AddRightButton (UIButton button) |
| Adds the given button to the right side of the navigation bar. More... | |
| void | RemoveRightButton (int n) |
| Removes a button from the right side of the navigation bar. More... | |
| override void | Draw (CGRect rect) |
| Draw the specified rect. More... | |
| override void | LayoutSubviews () |
| Layouts the subviews. More... | |
| delegate void | ACTileNavigationBarShownDelegate (ACTileNavigationBar navigationBar) |
Occurs when this ACTileNavigationBar is shown More... | |
| delegate void | ACTileNavigationBarHiddenDelegate (ACTileNavigationBar navigationBar) |
Occurs when the ACTileNavigationBar hidden. More... | |
Properties | |
| Object | tag [get, set] |
Gets or sets the [OPTIONAL] tag that can be assosciated with this ACTileNavigationBar More... | |
| List< UIButton > | leftButtons [get] |
| Gets the left navigation bar buttons. More... | |
| List< UIButton > | rightButtons [get] |
| Gets the right navigation bar buttons. More... | |
| ACTileNavigationBarAppearance | appearance [get, set] |
Gets or sets the ACTileNavigationBarAppearance for this ACTileNavigationBar More... | |
| string | title [get, set] |
Gets or sets the title for this ACTileNavigationBar More... | |
| bool | hidden [get] |
Gets a value indicating whether this ACTileNavigationBar is hidden. More... | |
Events | |
| ACTileNavigationBarShownDelegate | BarShown |
| ACTileNavigationBarHiddenDelegate | BarHidden |
Handles the Navigation Bar that can be shown at the top of a ACTileController
. The developer can include Buttons
on the left and right hand sides of the bar.
| ActionComponents.ACTileNavigationBar.ACTileNavigationBar | ( | ) |
Initializes a new instance of the ACTileNavigationBar
class.
| ActionComponents.ACTileNavigationBar.ACTileNavigationBar | ( | ACTileController | controller | ) |
Initializes a new instance of the ACTileNavigationBar
class.
| controller | Controller. |
| ActionComponents.ACTileNavigationBar.ACTileNavigationBar | ( | NSCoder | coder | ) |
Initializes a new instance of the ACTileNavigationBar
class.
| coder | Coder. |
| ActionComponents.ACTileNavigationBar.ACTileNavigationBar | ( | NSObjectFlag | flag | ) |
Initializes a new instance of the ACTileNavigationBar
class.
| flag | Flag. |
| ActionComponents.ACTileNavigationBar.ACTileNavigationBar | ( | RectangleF | bounds | ) |
Initializes a new instance of the ACTileNavigationBar
class.
| bounds | Bounds. |
| ActionComponents.ACTileNavigationBar.ACTileNavigationBar | ( | IntPtr | ptr | ) |
Initializes a new instance of the ACTileNavigationBar
class.
| ptr | Ptr. |
| delegate void ActionComponents.ACTileNavigationBar.ACTileNavigationBarHiddenDelegate | ( | ACTileNavigationBar | navigationBar | ) |
Occurs when the ACTileNavigationBar
hidden.
| delegate void ActionComponents.ACTileNavigationBar.ACTileNavigationBarShownDelegate | ( | ACTileNavigationBar | navigationBar | ) |
| UIButton ActionComponents.ACTileNavigationBar.AddLeftButton | ( | string | title, |
| UIImage | icon, | ||
| nfloat | width, | ||
| nfloat | height, | ||
| EventHandler | action | ||
| ) |
Adds a new button to the left side of the navigation bar.
| title | Title. |
| icon | Icon. |
| width | Width. |
| height | Height. |
| action | Action. |
| void ActionComponents.ACTileNavigationBar.AddLeftButton | ( | UIButton | button | ) |
Adds the given button to the left side of the control.
| button | Button. |
| UIButton ActionComponents.ACTileNavigationBar.AddRightButton | ( | string | title, |
| UIImage | icon, | ||
| nfloat | width, | ||
| nfloat | height, | ||
| EventHandler | action | ||
| ) |
Adds a button to the right side of the navigation bar.
| title | Title. |
| icon | Icon. |
| width | Width. |
| height | Height. |
| action | Action. |
| void ActionComponents.ACTileNavigationBar.AddRightButton | ( | UIButton | button | ) |
Adds the given button to the right side of the navigation bar.
| button | Button. |
|
virtual |
Bars the hidden completed.
|
virtual |
Bars the shown completed.
| override void ActionComponents.ACTileNavigationBar.Draw | ( | CGRect | rect | ) |
Draw the specified rect.
| rect | Rect. |
| void ActionComponents.ACTileNavigationBar.HideNavigationBar | ( | bool | animated | ) |
Hides the ACTileNavigationBar
| animated | If set to true animated. |
| override void ActionComponents.ACTileNavigationBar.LayoutSubviews | ( | ) |
Layouts the subviews.
| void ActionComponents.ACTileNavigationBar.Redraw | ( | ) |
| void ActionComponents.ACTileNavigationBar.RemoveLeftButton | ( | int | n | ) |
Removes the requested button from the left side of the navigation bar.
| n | The location of the button to remove |
| void ActionComponents.ACTileNavigationBar.RemoveRightButton | ( | int | n | ) |
Removes a button from the right side of the navigation bar.
| n | The location of the button to remove. |
| void ActionComponents.ACTileNavigationBar.Resize | ( | nfloat | width | ) |
Resize to the specified width.
| width | Width. |
| void ActionComponents.ACTileNavigationBar.ShowNavigationBar | ( | bool | animated | ) |
Shows the ACTileNavigationBar
| animated | If set to true animated. |
|
getset |
Gets or sets the ACTileNavigationBarAppearance
for this ACTileNavigationBar
The appearance.
|
get |
Gets a value indicating whether this ACTileNavigationBar
is hidden.
true
if hidden; otherwise, false
.
|
get |
Gets the left navigation bar buttons.
The left buttons.
|
get |
Gets the right navigation bar buttons.
The right buttons.
|
getset |
Gets or sets the [OPTIONAL] tag that can be assosciated with this ACTileNavigationBar
The tag.
|
getset |
Gets or sets the title for this ACTileNavigationBar
The title.
| ACTileNavigationBarHiddenDelegate ActionComponents.ACTileNavigationBar.BarHidden |
| ACTileNavigationBarShownDelegate ActionComponents.ACTileNavigationBar.BarShown |


Balanced Binary Tree
Given a binary tree, determine if it is height-balanced.
For this problem, a height-balanced binary tree is defined as a binary tree in which the depth of the two subtrees of every node never differ by more than 1.
标签: Tree Depth-first Search
分析
无
代码1
// LeetCode, Balanced Binary Tree // 时间复杂度O(n)，空间复杂度O(logn) class Solution { public: bool isBalanced (TreeNode* root) { return balancedHeight (root) >= 0; } /** * Returns the height of `root` if `root` is a balanced tree, * otherwise, returns `-1`. */ int balancedHeight (TreeNode* root) { if (root == nullptr) return 0; // 终止条件 int left = balancedHeight (root->left); int right = balancedHeight (root->right); if (left < 0 || right < 0 || abs(left - right) > 1) return -1; // 剪枝 return max(left, right) + 1; // 三方合并 } };
(adsbygoogle = window.adsbygoogle || []).push({});
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.
学习了。找到这题
第二个程序编译都通不过， int L[m+1][n+1];这样定义出错，应该换成具体的数字ac
博主，你这个是wordpress哪个主题啊，不错哦~
如果两个序列的最后字符不匹配（即X [M-1]！= Y [N-1]）
L（X [0 .. M-1]，Y [0 .. N-1]）= MAX（L（X [0 .. M-2]，Y [0 .. N-1]），L（X [0 .. M-1]，Y [0 .. N-1]）
这里写错了吧。
涨姿势了
很强大啊，佩服
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.
网站不错
失误失误，转载错了。已经改正，抱歉。
m /= i; 是一直在变的。参考这一篇关于质因数的http://www.acmerblog.com/integer-factorization-5124.html
不同的编译器，printf(),执行的顺序不同，所以结果也就不同，建议不要那么写
[…] 如果此题没有要求 相对位置不变，可以参考文章：http://www.acmerblog.com/interview-9-2427/ […]
很棒的网站，加油！⛽


{% extends "base.html" %} {% load url %} {% block title %}Delete a Token - {{ block.super }}{% endblock %} {% block breadcrumbs %}
{% endblock %} {% block content %}Please click below to delete the token that begins with {{ object.token_key }}. Please note that this action is not reversible.
{% endblock %}


Understand how to create a simple tempate that maps data using both shorthand and longhand notation along with some simple logic to toggle the class name of an element.
Right click and 'View page source' to see how this page was rendered.


{% extends 'store/base.html' %} {% load static %} {% block no-bootstrap %}{% endblock no-bootstrap %} {% block navigation %}
Success isn't always about greatness. It's about consistency. Consistent
hard work gains
success. Greatness will come.
Exclusively Availble on RedStore
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever.
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever.
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever.


BNF
`Prev `__
B
`Next `__
--------------
**BNF**: /B·N·F/, n.
1. [techspeak] Acronym for Backus Normal Form (later retronymed to
Backus-Naur Form because BNF was not in fact a normal form), a
metasyntactic notation used to specify the syntax of programming
languages, command sets, and the like. Widely used for language
descriptions but seldom documented anywhere, so that it must usually be
learned by osmosis from other hackers. Consider this BNF for a U.S.
postal address:
|
| ::=
|
| ::= \| "."
|
| ::= []
| \|
|
| ::= []
|
| ::= ","
This translates into English as: “A postal-address consists of a
name-part, followed by a street-address part, followed by a zip-code
part. A personal-part consists of either a first name or an initial
followed by a dot. A name-part consists of either: a personal-part
followed by a last name followed by an optional jr-part (Jr., Sr., or
dynastic number) and end-of-line, or a personal part followed by a name
part (this rule illustrates the use of recursion in BNFs, covering the
case of people who use multiple first and middle names and/or initials).
 A zip-part consists of a
town-name, followed by a comma, followed by a state code, followed by a
ZIP-code followed by an end-of-line.” Note that many things (such as the
format of a personal-part, apartment specifier, or ZIP-code) are left
unspecified. These are presumed to be obvious from context or detailed
somewhere nearby. See also `*parse* <../P/parse.html>`__.
2. Any of a number of variants and extensions of BNF proper, possibly
containing some or all of the `*regexp* <../R/regexp.html>`__ wildcards
such as **\*** or **+**. In fact the example above isn't the pure form
invented for the Algol-60 report; it uses **[]**, which was introduced a
few years later in IBM's PL/I definition but is now universally
recognized.
3. In `*science-fiction fandom* <../S/science-fiction-fandom.html>`__, a
‘Big-Name Fan’ (someone famous or notorious). Years ago a fan started
handing out black-on-green BNF buttons at SF conventions; this confused
the hacker contingent terribly.
--------------
+----------------------------+----------------------------+------------------------+
| `Prev `__ | `Up <../B.html>`__ | `Next `__ |
+----------------------------+----------------------------+------------------------+
| blurgle | `Home <../index.html>`__ | boa |
+----------------------------+----------------------------+------------------------+


Get items¶
Some functionalities are preimplemented to access the items and stuff
API¶
-
h5xplorer.menu_tools.
get_current_item
(self, treeview, single=False)[source]¶ Get the item(s) that was selected
Parameters: - treeview (HDF5TreeWidget) – the treeview
- single (bool, optional) – if true only single item possible
Returns: Description
Return type: TYPE
-
h5xplorer.menu_tools.
get_current_hdf5_group
(self, item)[source]¶ Get the HDF5 group of the selected item
Parameters: item (HDF5TreeItem) – treeview item Returns: the corresponding group Return type: HDF5 group
-
h5xplorer.menu_tools.
get_group_data
(group)[source]¶ Get the dataset of the item
Parameters: group (HDF5 group) – group of the treeview item Returns: return np.array if the group has a dataset or None otherwise Return type: dataset or None
-
h5xplorer.menu_tools.
get_actions
(treeview, position, list_action)[source]¶ Generate a singlelevel context menu of action and return the selected one
Example:
>>> list_operations = ['Print attrs','-','Plot Hist', 'Plot Map'] >>> action,actions = get_actions(treeview,position,list_operations) >>> if action == actions['Print attrs']: send_dict_to_console(self,item,treeview)
Parameters: - treeview (HDF5TreeWidget) – the treeview
- position (TYPE) – Description
- list_action (list) – List of string giving the action names
Returns: dict of QTMenu actions actions: the selected action
Return type: actions
-
h5xplorer.menu_tools.
get_multilevel_actions
(treeview, position, list_action, sub_list)[source]¶ Generate a multilevel context menu of action and return the selected one
Example:
>>> list_operations = ['Hit Rate','Av. Prec.'] >>> list_subop = [['Train','Valid','Test'],['Train','Valid','Test']] >>> action,actions = get_multilevel_actions(treeview,position,list_operations,list_subop)
Parameters: - treeview (HDF5TreeWidget) – the treeview
- position (TYPE) – Description
- list_action (list) – List of string giving the action names
- sub_list (list) – list of string giving the subactions
Returns: dict of QTMenu actions actions: the selected action
Return type: actions
-
h5xplorer.menu_tools.
send_dict_to_console
(self, item, treeview)[source]¶ Send a dictionany to the QT console
Parameters: - item (HDF5TreeItem) – treeview item
- treeview (HDF5TreeWidget) – the treeview
-
h5xplorer.menu_tools.
print_attributes
(self, item, treeview)[source]¶ Print the attribute in the console
Parameters: - item (HDF5TreeItem) – treeview item
- treeview (HDF5TreeWidget) – the treeview
-
h5xplorer.menu_tools.
get_user_values
(varnames, windowtitle='Enter Values')[source]¶ Get the values of variables from the users
Parameters: - varnames (list) – list of strings of all the desired variables
- windowtitle (str, optional) – Name of the window
Returns: list of float of the desired variables
Return type: list


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© 2015 Growlah


This example is an exploration of using linear regression with categorical/nominal variables. Specifically: with day of week. It will answer two questions:
This is a bit of an odd way to go about this, in that we would typically perform “time-series decomposition” and then look at the details for a “7-day season.” In theory, that would return a pretty similar result. But, it’s instructive to walk through a regression to get an understanding on how to perform regression with categorical (aka, nominal) variables, which “day of week” actually is.
Note that this approach – unlike a time-series decomposition – does not take into account overall trends in the data, such as a general trend of increasing traffic over time. Again, though, that’s okay for shorter-term assessments, and for pedagogical purposes.
The broader application of this approach probably wouldn’t be on “traffic,” but, rather, would be on some form of conversion, and the model would give the multiplier for each session that had a given set of characteristics (e.g., a mobile visitor from paid search) on whatever that conversion (or other outcome – such as revenue) would have.
We’re only using “day of week” here because sessions is our independent variable, and a session is a session. So, a mobile visit from paid search contributes one session just like a tablet visit from organic search contributes one session – “characteristics of a session” don’t impact “the fact that it’s as session.” “What day of the week it is,” though, is an entirely independent variable, so it works to check the degree to which the day of week impacts the number of sessions.
Start by the initial configuration of variables.
# Load the necessary libraries.
if (!require("pacman")) install.packages("pacman")
## Loading required package: pacman
pacman::p_load(googleAnalyticsR, # How we actually get the Google Analytics data
tidyverse, # Includes dplyr, ggplot2, and others; very key!
knitr, # Nicer looking tables
kableExtra, # Even nicer looking tables
plotly, # We're going to make the charts interactive
scales, # Useful for some number formatting in the visualizations
MASS) # For our stepwise regression
# Authorize GA. Depending on if you've done this already and a .ga-httr-oauth file has
# been saved or not, this may pop you over to a browser to authenticate.
ga_auth(token = ".httr-oauth")
# Set the view ID and the date range. If you want to, you can swap out the Sys.getenv()
# call and just replace that with a hardcoded value for the view ID.
view_id <- Sys.getenv("GA_VIEW_ID")
start_date <- Sys.Date() - 90 # The last 90 days
end_date <- Sys.Date() - 1 # Yesterday
start_date <- as.Date("2018-10-19") # The last 90 days
end_date <- as.Date("2019-01-16") # Yesterday
# Define our theme -- this will be used later for visualizations
theme_main <- theme_light() +
theme(text = element_text(family="Nunito"),
plot.title = element_text(hjust=0.5, size=18, face="bold"),
legend.title = element_blank(),
axis.text = element_text(size=16),
axis.text.x = element_text(face = "bold", margin = margin(t = 5, unit = "pt")),
axis.line.x = element_line(color = "gray20", size=0.5),
axis.title.y = element_blank(),
axis.title.x = element_blank(),
legend.position = "top",
panel.border = element_blank(),
panel.grid.major.y = element_line(color = "gray80"),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank())
This is a simple data pull. We’re just pulling data by day (because each day is a different day of the week) and sessions. And, since Google Analytics has a “Day of Week Name” dimension, we’ll go ahead and pull that, too (although we could have easily calculated this afterwards).
# Pull the data. See ?google_analytics_4() for additional parameters. The anti_sample = TRUE
# parameter will slow the query down a smidge and isn't strictly necessary, but it will
# ensure you do not get sampled data.
ga_data <- google_analytics(viewId = view_id,
date_range = c(start_date, end_date),
metrics = "sessions",
dimensions = c("date", "dayOfWeekName"),
anti_sample = TRUE)
# Shorten the day of week values and make it a factor with and order for easier plotting later
# Check the variability of data by weekday
ga_data <- ga_data %>%
mutate(Weekday = substring(dayOfWeekName, 1, 3)) %>%
mutate(Weekday = toupper(Weekday)) %>%
mutate(Weekday = factor(Weekday,
levels = c("SUN", "MON", "TUE", "WED", "THU", "FRI", "SAT"))) %>%
dplyr::select(date, Weekday, sessions)
names(ga_data) <- c("Date", "Weekday", "Sessions")
# Show the head of the returned data
head(ga_data, 12) %>% kable() %>% kable_styling(full_width = F,
font_size = 24,
bootstrap_options = "condensed") %>%
column_spec(1, width = "8em") %>%
column_spec(2, width = "6em") %>%
column_spec(3, width = "6em")
| Date | Weekday | Sessions |
|---|---|---|
| 2018-10-19 | FRI | 6564 |
| 2018-10-20 | SAT | 4574 |
| 2018-10-21 | SUN | 4133 |
| 2018-10-22 | MON | 7237 |
| 2018-10-23 | TUE | 6786 |
| 2018-10-24 | WED | 6660 |
| 2018-10-25 | THU | 6957 |
| 2018-10-26 | FRI | 6580 |
| 2018-10-27 | SAT | 4735 |
| 2018-10-28 | SUN | 4370 |
| 2018-10-29 | MON | 7725 |
| 2018-10-30 | TUE | 7434 |
# Go ahead and do a quick visualization of the resulting data
gg <- ggplot(ga_data, aes(x = Date, y = Sessions)) +
geom_line(color = "#9a258f", size=1) +
scale_y_continuous(expand = c(0,0), limits=c(0, max(ga_data$Sessions)*1.05), label = comma) +
labs(title = "Sessions by Day",
x = "Date") +
theme_main
gg
This step is not really necessary to do the regression. It’s just useful to realize that, essentially, we’re looking at all of the dates, organized by weekday, and the median and variability, as well as how many outliers there are, helps with some intuition for later.
# Make a boxplot where we combine all of the data points for each day of week together
gg <- ggplot(ga_data, aes(x = Weekday, y = Sessions)) +
geom_boxplot(fill = "gray90", color = "gray40", outlier.colour = "#9a258f", outlier.size=2.5) +
scale_y_continuous(expand = c(0,0), limits=c(0, max(ga_data$Sessions)*1.05), label = comma) +
labs(title = "Sessions Variation by Day of Week") +
theme_main
gg
We need convert each day of week to a binary – or “dummy” – variable. This will make sense as we get into it.
Note that the last step in this munging drops the “Saturday” column entirely. Any day of the week could be excluded. This gets explained by saying, “we only need k-1 values,” but, to maybe provide a bit more intuition, this really is pointing out that, if there are 7 possible days of the week, then we only need 6 variables to identify each observation (each row of data) by day. In the way this example is set up, we don’t need Saturday, because we know that any row that is not Sunday, Monday, Tuesday, Wednesday, Thursday, or Friday must be Saturday.
It doesn’t really matter which variable you drop (you can update the code to drop a different day and see that, while the resulting model has different coefficients, it actually returns the exact same results).
# Get the data set up where each day of the week has its own column. That means one of the
# columns will be a "1" and the rest will be "0s" for each date
ga_data_dummies <- ga_data %>%
mutate(var = 1) %>% # Put a 1 in all reows of a column
spread(key = Weekday, value = var, fill = 0) %>% # Create the dummy variables
dplyr::select(Date, SUN, MON, TUE, WED, THU, FRI, Sessions) # Re-order and drop "SAT"
# Display what the data now looks like
kable(head(ga_data_dummies, 12)) %>% kable_styling(full_width = F,
font_size = 24,
bootstrap_options = "condensed") %>%
column_spec(1, width = "10em") %>%
column_spec(2:7, width = "5em") %>%
column_spec(8, width = "8em")
| Date | SUN | MON | TUE | WED | THU | FRI | Sessions |
|---|---|---|---|---|---|---|---|
| 2018-10-19 | 0 | 0 | 0 | 0 | 0 | 1 | 6564 |
| 2018-10-20 | 0 | 0 | 0 | 0 | 0 | 0 | 4574 |
| 2018-10-21 | 1 | 0 | 0 | 0 | 0 | 0 | 4133 |
| 2018-10-22 | 0 | 1 | 0 | 0 | 0 | 0 | 7237 |
| 2018-10-23 | 0 | 0 | 1 | 0 | 0 | 0 | 6786 |
| 2018-10-24 | 0 | 0 | 0 | 1 | 0 | 0 | 6660 |
| 2018-10-25 | 0 | 0 | 0 | 0 | 1 | 0 | 6957 |
| 2018-10-26 | 0 | 0 | 0 | 0 | 0 | 1 | 6580 |
| 2018-10-27 | 0 | 0 | 0 | 0 | 0 | 0 | 4735 |
| 2018-10-28 | 1 | 0 | 0 | 0 | 0 | 0 | 4370 |
| 2018-10-29 | 0 | 1 | 0 | 0 | 0 | 0 | 7725 |
| 2018-10-30 | 0 | 0 | 1 | 0 | 0 | 0 | 7434 |
# When performing the regression, we don't actually need the date value, so make a data
# set that has that removed
analysis_data <- ga_data_dummies %>% dplyr::select(-Date)
This is the “easy” part. We’re just going to run a straight-up regression on all of the data. This has some problems, as there will be a tendency to overfit a model. We’ll come back to that in a bit!
This is a “stepwise regression,” in that it’s going to find the “best” subset of variables for fitting the model – dropping ones that are not really helping the cause. There are tons of articles and posts explaining the nuts and bolts of this, so Google away! Or, here’s one: http://www.sthda.com/english/articles/37-model-selection-essentials-in-r/154-stepwise-regression-essentials-in-r/.
# Fit the full model
full_model <- lm(Sessions ~., data = analysis_data)
# Now, see if stepwise can knock some things out (it shouldn't in this case,
# but it doesn't hurt to try)
step_model <- stepAIC(full_model, direction = "both", trace = FALSE)
Let’s look a summary of the model:
# Get just the overall model summary
model_summary <- summary(step_model)
# Output that summary
model_summary
##
## Call:
## lm(formula = Sessions ~ SUN + MON + TUE + WED + THU + FRI, data = analysis_data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4356.9 -319.7 79.0 380.3 2569.5
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5090.2 268.2 18.979 < 2e-16 ***
## SUN -632.0 379.3 -1.666 0.0994 .
## MON 2515.5 379.3 6.632 3.15e-09 ***
## TUE 2071.2 379.3 5.461 4.84e-07 ***
## WED 2471.3 379.3 6.515 5.27e-09 ***
## THU 2662.7 387.1 6.878 1.05e-09 ***
## FRI 2167.5 379.3 5.714 1.67e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 967 on 83 degrees of freedom
## Multiple R-squared: 0.6424, Adjusted R-squared: 0.6165
## F-statistic: 24.85 on 6 and 83 DF, p-value: < 2.2e-16
This can be a bit confusing to read, so let’s try to come up with something that, perhaps, is a bit easier to read.
Start by getting the p-value and the adjusted R-squared for the model overall.
 This is just a lightly cleaned up visualization of the “variables list” from the model output above. Note that not all days may appear in this table, as the nature of the stepwise regression is that it will add and subtract different features (variables) trying to find the “best” model.
# Make a data frame with just the coefficients and their significance levels. This is converting
# the p-values to confidence levels
ind_vars <- model_summary$coefficients %>% as.data.frame() %>%
mutate(Variable = rownames(.),
Estimate = round(Estimate),
`Confidence Level` = ifelse(`Pr(>|t|)` < 0.01, "99%",
ifelse(`Pr(>|t|)` < 0.05, "95%",
ifelse(`Pr(>|t|)` < 0.1, "90%",
ifelse(`Pr(>|t|)` < 0.2, "80%","<80%"))))) %>%
dplyr::select(Variable, Coefficient = Estimate, `Confidence Level`)
# Output a table with the independent variables
kable(ind_vars, align = c("l", "r", "c")) %>%
kable_styling(full_width = F, bootstrap_options = "condensed", font_size=24) %>%
column_spec(1, width = "6em") %>%
column_spec(2, width = "6em") %>%
column_spec(3, width = "10em")
| Variable | Coefficient | Confidence Level |
|---|---|---|
| (Intercept) | 5090 | 99% |
| SUN | -632 | 90% |
| MON | 2515 | 99% |
| TUE | 2071 | 99% |
| WED | 2471 | 99% |
| THU | 2663 | 99% |
| FRI | 2168 | 99% |
It might be helpful to display the above in equation notation – just to get it mapped back to our days with algebra.
# Generate a string that introduces RMarkdown equation notation so that we have values that
# can be pasted together and output as RMarkdown. This gets a little screwy, but it's
# just so we can output a "normal" looking equation.
model_equation <- ind_vars %>%
mutate(rmd = ifelse(Variable == "(Intercept)", round(Coefficient, 0),
paste0(round(Coefficient, 0), " \\times ", Variable)))
model_equation <- model_equation$rmd %>%
paste(collapse = " + ") %>%
paste0("$$Sessions = ", ., "$$")
\[Sessions = 5090 + -632 \times SUN + 2515 \times MON + 2071 \times TUE + 2471 \times WED + 2663 \times THU + 2168 \times FRI\]
But, wait. How do I multiply a number by a day?! This gets back to our creation of “dummy variables” earlier. Remember that the data we’re working with created a variable for each day of the week and then assigned each row in the table (each day, each “observation”) as a 1
(yes, it’s that day) or a 0
(no, it’s not that day). That means, in the equation above, most of the values will be multipled by 0
for any given day, while one value will be multiplied by 1
.
# Re-display what the data looks like with dummy variables
kable(head(ga_data_dummies, 12)) %>% kable_styling(full_width = F,
font_size = 24,
bootstrap_options = "condensed") %>%
column_spec(1, width = "10em") %>%
column_spec(2:7, width = "5em") %>%
column_spec(8, width = "8em")
| Date | SUN | MON | TUE | WED | THU | FRI | Sessions |
|---|---|---|---|---|---|---|---|
| 2018-10-19 | 0 | 0 | 0 | 0 | 0 | 1 | 6564 |
| 2018-10-20 | 0 | 0 | 0 | 0 | 0 | 0 | 4574 |
| 2018-10-21 | 1 | 0 | 0 | 0 | 0 | 0 | 4133 |
| 2018-10-22 | 0 | 1 | 0 | 0 | 0 | 0 | 7237 |
| 2018-10-23 | 0 | 0 | 1 | 0 | 0 | 0 | 6786 |
| 2018-10-24 | 0 | 0 | 0 | 1 | 0 | 0 | 6660 |
| 2018-10-25 | 0 | 0 | 0 | 0 | 1 | 0 | 6957 |
| 2018-10-26 | 0 | 0 | 0 | 0 | 0 | 1 | 6580 |
| 2018-10-27 | 0 | 0 | 0 | 0 | 0 | 0 | 4735 |
| 2018-10-28 | 1 | 0 | 0 | 0 | 0 | 0 | 4370 |
| 2018-10-29 | 0 | 1 | 0 | 0 | 0 | 0 | 7725 |
| 2018-10-30 | 0 | 0 | 1 | 0 | 0 | 0 | 7434 |
So, what does our model look like when comparing its predictions to the actual data?
We can simply run the model on the original data set and return a plot that shows the actual vs. predicted values. This is a shortcut to “plotting the residuals” and other checks, but, hopefully, won’t give anyone using this too much heartburn.
Here’s your chance to check the math from the equation above with some of the actual data in the new data frame we’ve created.
# Predict the results using the data -- to get a visualization of the results (basically,
# visualizing the residuals). This is just a vector of predicted sessions.
predict_vs_actual <- predict(step_model, ga_data_dummies)
# Add those predictions to a data frame that shows the actuals. We'll hold onto
# this so we can preview it in the output.
predict_vs_actual_df <- ga_data_dummies %>%
cbind(data.frame(`Predicted Sessions` = predict_vs_actual)) %>%
mutate(`Predicted.Sessions` = round(`Predicted.Sessions`))
# Rename "Sessions" to "Actual Sessions" for clarity
names(predict_vs_actual_df) <- gsub("Sessions", "Actual Sessions", names(predict_vs_actual_df)) %>%
gsub("Predicted.Actual.Sessions", "Predicted", .)
# Output the head
kable(head(predict_vs_actual_df, 12)) %>%
kable_styling(full_width = F, bootstrap_options = "condensed", font_size=20) %>%
column_spec(1, width = "60em") %>%
column_spec(2:7, width = "6em") %>%
column_spec(8, width = "80em") %>%
column_spec(9, width = "40em")
| Date | SUN | MON | TUE | WED | THU | FRI | Actual Sessions | Predicted |
|---|---|---|---|---|---|---|---|---|
| 2018-10-19 | 0 | 0 | 0 | 0 | 0 | 1 | 6564 | 7258 |
| 2018-10-20 | 0 | 0 | 0 | 0 | 0 | 0 | 4574 | 5090 |
| 2018-10-21 | 1 | 0 | 0 | 0 | 0 | 0 | 4133 | 4458 |
| 2018-10-22 | 0 | 1 | 0 | 0 | 0 | 0 | 7237 | 7606 |
| 2018-10-23 | 0 | 0 | 1 | 0 | 0 | 0 | 6786 | 7161 |
| 2018-10-24 | 0 | 0 | 0 | 1 | 0 | 0 | 6660 | 7562 |
| 2018-10-25 | 0 | 0 | 0 | 0 | 1 | 0 | 6957 | 7753 |
| 2018-10-26 | 0 | 0 | 0 | 0 | 0 | 1 | 6580 | 7258 |
| 2018-10-27 | 0 | 0 | 0 | 0 | 0 | 0 | 4735 | 5090 |
| 2018-10-28 | 1 | 0 | 0 | 0 | 0 | 0 | 4370 | 4458 |
| 2018-10-29 | 0 | 1 | 0 | 0 | 0 | 0 | 7725 | 7606 |
| 2018-10-30 | 0 | 0 | 1 | 0 | 0 | 0 | 7434 | 7161 |
For reference (if you want to do some math with the above):
\[Sessions = 5090 + -632 \times SUN + 2515 \times MON + 2071 \times TUE + 2471 \times WED + 2663 \times THU + 2168 \times FRI\]
Finally, let’s plot the results showing three things:
# Get just the intercept (for a horizontal line we'll add)
y_intercept <- ind_vars %>% filter(Variable == "(Intercept)") %>%
dplyr::select(Coefficient) %>% as.numeric()
# Add that y-intercept as a constant to the data to be plotted. geom_hline()
# would be better for this, but I gave up fighting to get the legend I was
# wanting, so hacking around it this way
predict_vs_actual_for_plot <- predict_vs_actual_df %>%
mutate(Intercept = y_intercept)
# For cleaner plotting, convert that to a tidy format and then turn it into a ggplot
predict_vs_actual_for_plot <- predict_vs_actual_for_plot %>%
dplyr::select(Date = Date, `Actual Sessions`, `Predicted`, Intercept) %>%
gather(key = metric, value = value, -Date) %>%
# Total hack to add better spacing in the legend
mutate(metric = paste0(metric, " "))
# Get the max value so we can expand the limits
y_lim <- max(predict_vs_actual_for_plot$value) * 1.1
# Plot the actuals vs. predicted.
gg_predict_vs_actual <- ggplot() +
geom_line(data = predict_vs_actual_for_plot,
mapping = aes(x = Date, y = value, color = metric,
linetype = metric), size = 1) +
# geom_hline(mapping = aes(linetype = "Intercept", yintercept = y_intercept),
# color="#ed1c24") +
scale_color_manual(values=c("#9a258f", "#ed1c24", "gray30" )) +
scale_linetype_manual(values = c("solid", "dashed", "dotted" )) +
scale_y_continuous(expand = c(0,0), limits = c(0,y_lim), label=number_format(accuracy=1, big.mark=",")) +
labs(x = "Date", y = "Sessions", title = "Sessions by Day: Actual vs. Predicted") +
# guides(fill=guide_legend(keywidth=0.8, keyheight=0.1, default.unit="inch")) +
theme_main +
theme(legend.key.width=unit(4,"line"),
legend.text = element_text(size=16),
axis.line.x = element_line(color = "gray20"),
plot.title = element_blank())
# Output the chart
gg_predict_vs_actual
So, yes, the Predicted Sessions follow a recurring pattern. That’s because our categorical variable – day of week – only has seven values, so our model is destined to just repeat.
Of course, if there was another variable thrown in (that had significance), this may not be the case, as this recurring pattern would then have some other factor (or set of factors) layered on top of it that added more variability to the prediction.
In this example, we had a relatively small number of variables, and we used stepwise regression to pick the subset (which may be “all”) that were most predictive of the actual results.
We also did not look at interaction effects, because days of week are quite independent of each other.
Consider if, for instance, we had also used mobile device category and wanted to include the interactions between day of week and device category as a predictor of a result like orders or revenue, then we would have had a bunch more variables (either overtly or behind the scenes). In addition to each day of the week and each device category – the “main effects,” we would have a slew of “interaction effects” to consider as well: Monday + Mobile
, Monday + Tablet
, Monday + Desktop
, Tuesday + Mobile
, etc.
Conceivably, we would get to a point pretty easily where we had as many variables as we had observations, which causes all sorts of issues! But, even if things did not get that extreme, having many more variables to consider runs a greater risk of “overfitting the model.” One way to lessen the risk of this is to use k-fold cross validation, which is a mechanism by which the data set is iteratively split into “training” and “testing” groups, and then the different models are run on different sets of training data and then evaluated based on how well they then predict the results in the test data.
We started to include that in this simple model… but, given the (relative) simplicity of this example, we determined it was not sufficiently illustrative to warrant including.