DeviceHealthAttestationState extends Entity
DeviceHealthAttestationState class
Tags
Table of Contents
- $_propDict : array<string|int, mixed>
- The array of properties available to the model
- __construct() : mixed
- Construct a new Entity
- getAttestationIdentityKey() : string|null
- Gets the attestationIdentityKey TWhen an Attestation Identity Key (AIK) is present on a device, it indicates that the device has an endorsement key (EK) certificate.
- getBitLockerStatus() : string|null
- Gets the bitLockerStatus On or Off of BitLocker Drive Encryption
- getBootAppSecurityVersion() : string|null
- Gets the bootAppSecurityVersion The security version number of the Boot Application
- getBootDebugging() : string|null
- Gets the bootDebugging When bootDebugging is enabled, the device is used in development and testing
- getBootManagerSecurityVersion() : string|null
- Gets the bootManagerSecurityVersion The security version number of the Boot Application
- getBootManagerVersion() : string|null
- Gets the bootManagerVersion The version of the Boot Manager
- getBootRevisionListInfo() : string|null
- Gets the bootRevisionListInfo The Boot Revision List that was loaded during initial boot on the attested device
- getCodeIntegrity() : string|null
- Gets the codeIntegrity When code integrity is enabled, code execution is restricted to integrity verified code
- getCodeIntegrityCheckVersion() : string|null
- Gets the codeIntegrityCheckVersion The version of the Boot Manager
- getCodeIntegrityPolicy() : string|null
- Gets the codeIntegrityPolicy The Code Integrity policy that is controlling the security of the boot environment
- getContentNamespaceUrl() : string|null
- Gets the contentNamespaceUrl The DHA report version. (Namespace version)
- getContentVersion() : string|null
- Gets the contentVersion The HealthAttestation state schema version
- getDataExcutionPolicy() : string|null
- Gets the dataExcutionPolicy DEP Policy defines a set of hardware and software technologies that perform additional checks on memory
- getDeviceHealthAttestationStatus() : string|null
- Gets the deviceHealthAttestationStatus The DHA report version. (Namespace version)
- getEarlyLaunchAntiMalwareDriverProtection() : string|null
- Gets the earlyLaunchAntiMalwareDriverProtection ELAM provides protection for the computers in your network when they start up
- getHealthAttestationSupportedStatus() : string|null
- Gets the healthAttestationSupportedStatus This attribute indicates if DHA is supported for the device
- getHealthStatusMismatchInfo() : string|null
- Gets the healthStatusMismatchInfo This attribute appears if DHA-Service detects an integrity issue
- getId() : string|null
- Gets the id Read-only.
- getIssuedDateTime() : DateTime|null
- Gets the issuedDateTime The DateTime when device was evaluated or issued to MDM
- getLastUpdateDateTime() : string|null
- Gets the lastUpdateDateTime The Timestamp of the last update.
- getODataType() : string|null
- Gets the ODataType
- getOperatingSystemKernelDebugging() : string|null
- Gets the operatingSystemKernelDebugging When operatingSystemKernelDebugging is enabled, the device is used in development and testing
- getOperatingSystemRevListInfo() : string|null
- Gets the operatingSystemRevListInfo The Operating System Revision List that was loaded during initial boot on the attested device
- getPcr0() : string|null
- Gets the pcr0 The measurement that is captured in PCR[0]
- getPcrHashAlgorithm() : string|null
- Gets the pcrHashAlgorithm Informational attribute that identifies the HASH algorithm that was used by TPM
- getProperties() : array<string|int, mixed>
- Gets the property dictionary of the Entity
- getResetCount() : int|null
- Gets the resetCount The number of times a PC device has hibernated or resumed
- getRestartCount() : int|null
- Gets the restartCount The number of times a PC device has rebooted
- getSafeMode() : string|null
- Gets the safeMode Safe mode is a troubleshooting option for Windows that starts your computer in a limited state
- getSecureBoot() : string|null
- Gets the secureBoot When Secure Boot is enabled, the core components must have the correct cryptographic signatures
- getSecureBootConfigurationPolicyFingerPrint() : string|null
- Gets the secureBootConfigurationPolicyFingerPrint Fingerprint of the Custom Secure Boot Configuration Policy
- getTestSigning() : string|null
- Gets the testSigning When test signing is allowed, the device does not enforce signature validation during boot
- getTpmVersion() : string|null
- Gets the tpmVersion The security version number of the Boot Application
- getVirtualSecureMode() : string|null
- Gets the virtualSecureMode VSM is a container that protects high value assets from a compromised kernel
- getWindowsPE() : string|null
- Gets the windowsPE Operating system running with limited services that is used to prepare a computer for Windows
- jsonSerialize() : array<string|int, mixed>
- Serializes the object by property array Manually serialize DateTime into RFC3339 format
- setAttestationIdentityKey() : DeviceHealthAttestationState
- Sets the attestationIdentityKey TWhen an Attestation Identity Key (AIK) is present on a device, it indicates that the device has an endorsement key (EK) certificate.
- setBitLockerStatus() : DeviceHealthAttestationState
- Sets the bitLockerStatus On or Off of BitLocker Drive Encryption
- setBootAppSecurityVersion() : DeviceHealthAttestationState
- Sets the bootAppSecurityVersion The security version number of the Boot Application
- setBootDebugging() : DeviceHealthAttestationState
- Sets the bootDebugging When bootDebugging is enabled, the device is used in development and testing
- setBootManagerSecurityVersion() : DeviceHealthAttestationState
- Sets the bootManagerSecurityVersion The security version number of the Boot Application
- setBootManagerVersion() : DeviceHealthAttestationState
- Sets the bootManagerVersion The version of the Boot Manager
- setBootRevisionListInfo() : DeviceHealthAttestationState
- Sets the bootRevisionListInfo The Boot Revision List that was loaded during initial boot on the attested device
- setCodeIntegrity() : DeviceHealthAttestationState
- Sets the codeIntegrity When code integrity is enabled, code execution is restricted to integrity verified code
- setCodeIntegrityCheckVersion() : DeviceHealthAttestationState
- Sets the codeIntegrityCheckVersion The version of the Boot Manager
- setCodeIntegrityPolicy() : DeviceHealthAttestationState
- Sets the codeIntegrityPolicy The Code Integrity policy that is controlling the security of the boot environment
- setContentNamespaceUrl() : DeviceHealthAttestationState
- Sets the contentNamespaceUrl The DHA report version. (Namespace version)
- setContentVersion() : DeviceHealthAttestationState
- Sets the contentVersion The HealthAttestation state schema version
- setDataExcutionPolicy() : DeviceHealthAttestationState
- Sets the dataExcutionPolicy DEP Policy defines a set of hardware and software technologies that perform additional checks on memory
- setDeviceHealthAttestationStatus() : DeviceHealthAttestationState
- Sets the deviceHealthAttestationStatus The DHA report version. (Namespace version)
- setEarlyLaunchAntiMalwareDriverProtection() : DeviceHealthAttestationState
- Sets the earlyLaunchAntiMalwareDriverProtection ELAM provides protection for the computers in your network when they start up
- setHealthAttestationSupportedStatus() : DeviceHealthAttestationState
- Sets the healthAttestationSupportedStatus This attribute indicates if DHA is supported for the device
- setHealthStatusMismatchInfo() : DeviceHealthAttestationState
- Sets the healthStatusMismatchInfo This attribute appears if DHA-Service detects an integrity issue
- setId() : Entity
- Sets the id Read-only.
- setIssuedDateTime() : DeviceHealthAttestationState
- Sets the issuedDateTime The DateTime when device was evaluated or issued to MDM
- setLastUpdateDateTime() : DeviceHealthAttestationState
- Sets the lastUpdateDateTime The Timestamp of the last update.
- setODataType() : Entity
- Sets the ODataType
- setOperatingSystemKernelDebugging() : DeviceHealthAttestationState
- Sets the operatingSystemKernelDebugging When operatingSystemKernelDebugging is enabled, the device is used in development and testing
- setOperatingSystemRevListInfo() : DeviceHealthAttestationState
- Sets the operatingSystemRevListInfo The Operating System Revision List that was loaded during initial boot on the attested device
- setPcr0() : DeviceHealthAttestationState
- Sets the pcr0 The measurement that is captured in PCR[0]
- setPcrHashAlgorithm() : DeviceHealthAttestationState
- Sets the pcrHashAlgorithm Informational attribute that identifies the HASH algorithm that was used by TPM
- setResetCount() : DeviceHealthAttestationState
- Sets the resetCount The number of times a PC device has hibernated or resumed
- setRestartCount() : DeviceHealthAttestationState
- Sets the restartCount The number of times a PC device has rebooted
- setSafeMode() : DeviceHealthAttestationState
- Sets the safeMode Safe mode is a troubleshooting option for Windows that starts your computer in a limited state
- setSecureBoot() : DeviceHealthAttestationState
- Sets the secureBoot When Secure Boot is enabled, the core components must have the correct cryptographic signatures
- setSecureBootConfigurationPolicyFingerPrint() : DeviceHealthAttestationState
- Sets the secureBootConfigurationPolicyFingerPrint Fingerprint of the Custom Secure Boot Configuration Policy
- setTestSigning() : DeviceHealthAttestationState
- Sets the testSigning When test signing is allowed, the device does not enforce signature validation during boot
- setTpmVersion() : DeviceHealthAttestationState
- Sets the tpmVersion The security version number of the Boot Application
- setVirtualSecureMode() : DeviceHealthAttestationState
- Sets the virtualSecureMode VSM is a container that protects high value assets from a compromised kernel
- setWindowsPE() : DeviceHealthAttestationState
- Sets the windowsPE Operating system running with limited services that is used to prepare a computer for Windows
Properties
$_propDict
The array of properties available to the model
protected
array<string|int, mixed>
$_propDict
Methods
__construct()
Construct a new Entity
public
__construct([array<string|int, mixed> $propDict = array() ]) : mixed
Parameters
- $propDict : array<string|int, mixed> = array()
-
A list of properties to set
Return values
mixed —getAttestationIdentityKey()
Gets the attestationIdentityKey TWhen an Attestation Identity Key (AIK) is present on a device, it indicates that the device has an endorsement key (EK) certificate.
public
getAttestationIdentityKey() : string|null
Return values
string|null —The attestationIdentityKey
getBitLockerStatus()
Gets the bitLockerStatus On or Off of BitLocker Drive Encryption
public
getBitLockerStatus() : string|null
Return values
string|null —The bitLockerStatus
getBootAppSecurityVersion()
Gets the bootAppSecurityVersion The security version number of the Boot Application
public
getBootAppSecurityVersion() : string|null
Return values
string|null —The bootAppSecurityVersion
getBootDebugging()
Gets the bootDebugging When bootDebugging is enabled, the device is used in development and testing
public
getBootDebugging() : string|null
Return values
string|null —The bootDebugging
getBootManagerSecurityVersion()
Gets the bootManagerSecurityVersion The security version number of the Boot Application
public
getBootManagerSecurityVersion() : string|null
Return values
string|null —The bootManagerSecurityVersion
getBootManagerVersion()
Gets the bootManagerVersion The version of the Boot Manager
public
getBootManagerVersion() : string|null
Return values
string|null —The bootManagerVersion
getBootRevisionListInfo()
Gets the bootRevisionListInfo The Boot Revision List that was loaded during initial boot on the attested device
public
getBootRevisionListInfo() : string|null
Return values
string|null —The bootRevisionListInfo
getCodeIntegrity()
Gets the codeIntegrity When code integrity is enabled, code execution is restricted to integrity verified code
public
getCodeIntegrity() : string|null
Return values
string|null —The codeIntegrity
getCodeIntegrityCheckVersion()
Gets the codeIntegrityCheckVersion The version of the Boot Manager
public
getCodeIntegrityCheckVersion() : string|null
Return values
string|null —The codeIntegrityCheckVersion
getCodeIntegrityPolicy()
Gets the codeIntegrityPolicy The Code Integrity policy that is controlling the security of the boot environment
public
getCodeIntegrityPolicy() : string|null
Return values
string|null —The codeIntegrityPolicy
getContentNamespaceUrl()
Gets the contentNamespaceUrl The DHA report version. (Namespace version)
public
getContentNamespaceUrl() : string|null
Return values
string|null —The contentNamespaceUrl
getContentVersion()
Gets the contentVersion The HealthAttestation state schema version
public
getContentVersion() : string|null
Return values
string|null —The contentVersion
getDataExcutionPolicy()
Gets the dataExcutionPolicy DEP Policy defines a set of hardware and software technologies that perform additional checks on memory
public
getDataExcutionPolicy() : string|null
Return values
string|null —The dataExcutionPolicy
getDeviceHealthAttestationStatus()
Gets the deviceHealthAttestationStatus The DHA report version. (Namespace version)
public
getDeviceHealthAttestationStatus() : string|null
Return values
string|null —The deviceHealthAttestationStatus
getEarlyLaunchAntiMalwareDriverProtection()
Gets the earlyLaunchAntiMalwareDriverProtection ELAM provides protection for the computers in your network when they start up
public
getEarlyLaunchAntiMalwareDriverProtection() : string|null
Return values
string|null —The earlyLaunchAntiMalwareDriverProtection
getHealthAttestationSupportedStatus()
Gets the healthAttestationSupportedStatus This attribute indicates if DHA is supported for the device
public
getHealthAttestationSupportedStatus() : string|null
Return values
string|null —The healthAttestationSupportedStatus
getHealthStatusMismatchInfo()
Gets the healthStatusMismatchInfo This attribute appears if DHA-Service detects an integrity issue
public
getHealthStatusMismatchInfo() : string|null
Return values
string|null —The healthStatusMismatchInfo
getId()
Gets the id Read-only.
public
getId() : string|null
Return values
string|null —The id
getIssuedDateTime()
Gets the issuedDateTime The DateTime when device was evaluated or issued to MDM
public
getIssuedDateTime() : DateTime|null
Return values
DateTime|null —The issuedDateTime
getLastUpdateDateTime()
Gets the lastUpdateDateTime The Timestamp of the last update.
public
getLastUpdateDateTime() : string|null
Return values
string|null —The lastUpdateDateTime
getODataType()
Gets the ODataType
public
getODataType() : string|null
Return values
string|null —The ODataType
getOperatingSystemKernelDebugging()
Gets the operatingSystemKernelDebugging When operatingSystemKernelDebugging is enabled, the device is used in development and testing
public
getOperatingSystemKernelDebugging() : string|null
Return values
string|null —The operatingSystemKernelDebugging
getOperatingSystemRevListInfo()
Gets the operatingSystemRevListInfo The Operating System Revision List that was loaded during initial boot on the attested device
public
getOperatingSystemRevListInfo() : string|null
Return values
string|null —The operatingSystemRevListInfo
getPcr0()
Gets the pcr0 The measurement that is captured in PCR[0]
public
getPcr0() : string|null
Return values
string|null —The pcr0
getPcrHashAlgorithm()
Gets the pcrHashAlgorithm Informational attribute that identifies the HASH algorithm that was used by TPM
public
getPcrHashAlgorithm() : string|null
Return values
string|null —The pcrHashAlgorithm
getProperties()
Gets the property dictionary of the Entity
public
getProperties() : array<string|int, mixed>
Return values
array<string|int, mixed> —The list of properties
getResetCount()
Gets the resetCount The number of times a PC device has hibernated or resumed
public
getResetCount() : int|null
Return values
int|null —The resetCount
getRestartCount()
Gets the restartCount The number of times a PC device has rebooted
public
getRestartCount() : int|null
Return values
int|null —The restartCount
getSafeMode()
Gets the safeMode Safe mode is a troubleshooting option for Windows that starts your computer in a limited state
public
getSafeMode() : string|null
Return values
string|null —The safeMode
getSecureBoot()
Gets the secureBoot When Secure Boot is enabled, the core components must have the correct cryptographic signatures
public
getSecureBoot() : string|null
Return values
string|null —The secureBoot
getSecureBootConfigurationPolicyFingerPrint()
Gets the secureBootConfigurationPolicyFingerPrint Fingerprint of the Custom Secure Boot Configuration Policy
public
getSecureBootConfigurationPolicyFingerPrint() : string|null
Return values
string|null —The secureBootConfigurationPolicyFingerPrint
getTestSigning()
Gets the testSigning When test signing is allowed, the device does not enforce signature validation during boot
public
getTestSigning() : string|null
Return values
string|null —The testSigning
getTpmVersion()
Gets the tpmVersion The security version number of the Boot Application
public
getTpmVersion() : string|null
Return values
string|null —The tpmVersion
getVirtualSecureMode()
Gets the virtualSecureMode VSM is a container that protects high value assets from a compromised kernel
public
getVirtualSecureMode() : string|null
Return values
string|null —The virtualSecureMode
getWindowsPE()
Gets the windowsPE Operating system running with limited services that is used to prepare a computer for Windows
public
getWindowsPE() : string|null
Return values
string|null —The windowsPE
jsonSerialize()
Serializes the object by property array Manually serialize DateTime into RFC3339 format
public
jsonSerialize() : array<string|int, mixed>
Return values
array<string|int, mixed> —The list of properties
setAttestationIdentityKey()
Sets the attestationIdentityKey TWhen an Attestation Identity Key (AIK) is present on a device, it indicates that the device has an endorsement key (EK) certificate.
public
setAttestationIdentityKey(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the attestationIdentityKey
Return values
DeviceHealthAttestationState —setBitLockerStatus()
Sets the bitLockerStatus On or Off of BitLocker Drive Encryption
public
setBitLockerStatus(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the bitLockerStatus
Return values
DeviceHealthAttestationState —setBootAppSecurityVersion()
Sets the bootAppSecurityVersion The security version number of the Boot Application
public
setBootAppSecurityVersion(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the bootAppSecurityVersion
Return values
DeviceHealthAttestationState —setBootDebugging()
Sets the bootDebugging When bootDebugging is enabled, the device is used in development and testing
public
setBootDebugging(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the bootDebugging
Return values
DeviceHealthAttestationState —setBootManagerSecurityVersion()
Sets the bootManagerSecurityVersion The security version number of the Boot Application
public
setBootManagerSecurityVersion(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the bootManagerSecurityVersion
Return values
DeviceHealthAttestationState —setBootManagerVersion()
Sets the bootManagerVersion The version of the Boot Manager
public
setBootManagerVersion(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the bootManagerVersion
Return values
DeviceHealthAttestationState —setBootRevisionListInfo()
Sets the bootRevisionListInfo The Boot Revision List that was loaded during initial boot on the attested device
public
setBootRevisionListInfo(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the bootRevisionListInfo
Return values
DeviceHealthAttestationState —setCodeIntegrity()
Sets the codeIntegrity When code integrity is enabled, code execution is restricted to integrity verified code
public
setCodeIntegrity(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the codeIntegrity
Return values
DeviceHealthAttestationState —setCodeIntegrityCheckVersion()
Sets the codeIntegrityCheckVersion The version of the Boot Manager
public
setCodeIntegrityCheckVersion(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the codeIntegrityCheckVersion
Return values
DeviceHealthAttestationState —setCodeIntegrityPolicy()
Sets the codeIntegrityPolicy The Code Integrity policy that is controlling the security of the boot environment
public
setCodeIntegrityPolicy(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the codeIntegrityPolicy
Return values
DeviceHealthAttestationState —setContentNamespaceUrl()
Sets the contentNamespaceUrl The DHA report version. (Namespace version)
public
setContentNamespaceUrl(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the contentNamespaceUrl
Return values
DeviceHealthAttestationState —setContentVersion()
Sets the contentVersion The HealthAttestation state schema version
public
setContentVersion(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the contentVersion
Return values
DeviceHealthAttestationState —setDataExcutionPolicy()
Sets the dataExcutionPolicy DEP Policy defines a set of hardware and software technologies that perform additional checks on memory
public
setDataExcutionPolicy(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the dataExcutionPolicy
Return values
DeviceHealthAttestationState —setDeviceHealthAttestationStatus()
Sets the deviceHealthAttestationStatus The DHA report version. (Namespace version)
public
setDeviceHealthAttestationStatus(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the deviceHealthAttestationStatus
Return values
DeviceHealthAttestationState —setEarlyLaunchAntiMalwareDriverProtection()
Sets the earlyLaunchAntiMalwareDriverProtection ELAM provides protection for the computers in your network when they start up
public
setEarlyLaunchAntiMalwareDriverProtection(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the earlyLaunchAntiMalwareDriverProtection
Return values
DeviceHealthAttestationState —setHealthAttestationSupportedStatus()
Sets the healthAttestationSupportedStatus This attribute indicates if DHA is supported for the device
public
setHealthAttestationSupportedStatus(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the healthAttestationSupportedStatus
Return values
DeviceHealthAttestationState —setHealthStatusMismatchInfo()
Sets the healthStatusMismatchInfo This attribute appears if DHA-Service detects an integrity issue
public
setHealthStatusMismatchInfo(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the healthStatusMismatchInfo
Return values
DeviceHealthAttestationState —setId()
Sets the id Read-only.
public
setId(string $val) : Entity
Parameters
- $val : string
-
The id
Return values
Entity —setIssuedDateTime()
Sets the issuedDateTime The DateTime when device was evaluated or issued to MDM
public
setIssuedDateTime(DateTime $val) : DeviceHealthAttestationState
Parameters
- $val : DateTime
-
The value to assign to the issuedDateTime
Return values
DeviceHealthAttestationState —The DeviceHealthAttestationState
setLastUpdateDateTime()
Sets the lastUpdateDateTime The Timestamp of the last update.
public
setLastUpdateDateTime(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the lastUpdateDateTime
Return values
DeviceHealthAttestationState —setODataType()
Sets the ODataType
public
setODataType(string $val) : Entity
Parameters
- $val : string
-
The ODataType
Return values
Entity —setOperatingSystemKernelDebugging()
Sets the operatingSystemKernelDebugging When operatingSystemKernelDebugging is enabled, the device is used in development and testing
public
setOperatingSystemKernelDebugging(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the operatingSystemKernelDebugging
Return values
DeviceHealthAttestationState —setOperatingSystemRevListInfo()
Sets the operatingSystemRevListInfo The Operating System Revision List that was loaded during initial boot on the attested device
public
setOperatingSystemRevListInfo(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the operatingSystemRevListInfo
Return values
DeviceHealthAttestationState —setPcr0()
Sets the pcr0 The measurement that is captured in PCR[0]
public
setPcr0(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the pcr0
Return values
DeviceHealthAttestationState —setPcrHashAlgorithm()
Sets the pcrHashAlgorithm Informational attribute that identifies the HASH algorithm that was used by TPM
public
setPcrHashAlgorithm(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the pcrHashAlgorithm
Return values
DeviceHealthAttestationState —setResetCount()
Sets the resetCount The number of times a PC device has hibernated or resumed
public
setResetCount(int $val) : DeviceHealthAttestationState
Parameters
- $val : int
-
The value of the resetCount
Return values
DeviceHealthAttestationState —setRestartCount()
Sets the restartCount The number of times a PC device has rebooted
public
setRestartCount(int $val) : DeviceHealthAttestationState
Parameters
- $val : int
-
The value of the restartCount
Return values
DeviceHealthAttestationState —setSafeMode()
Sets the safeMode Safe mode is a troubleshooting option for Windows that starts your computer in a limited state
public
setSafeMode(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the safeMode
Return values
DeviceHealthAttestationState —setSecureBoot()
Sets the secureBoot When Secure Boot is enabled, the core components must have the correct cryptographic signatures
public
setSecureBoot(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the secureBoot
Return values
DeviceHealthAttestationState —setSecureBootConfigurationPolicyFingerPrint()
Sets the secureBootConfigurationPolicyFingerPrint Fingerprint of the Custom Secure Boot Configuration Policy
public
setSecureBootConfigurationPolicyFingerPrint(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the secureBootConfigurationPolicyFingerPrint
Return values
DeviceHealthAttestationState —setTestSigning()
Sets the testSigning When test signing is allowed, the device does not enforce signature validation during boot
public
setTestSigning(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the testSigning
Return values
DeviceHealthAttestationState —setTpmVersion()
Sets the tpmVersion The security version number of the Boot Application
public
setTpmVersion(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the tpmVersion
Return values
DeviceHealthAttestationState —setVirtualSecureMode()
Sets the virtualSecureMode VSM is a container that protects high value assets from a compromised kernel
public
setVirtualSecureMode(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the virtualSecureMode
Return values
DeviceHealthAttestationState —setWindowsPE()
Sets the windowsPE Operating system running with limited services that is used to prepare a computer for Windows
public
setWindowsPE(string $val) : DeviceHealthAttestationState
Parameters
- $val : string
-
The value of the windowsPE


In addition to the challenge specific reflections, answer the following questions:
The Command Line is a text version of the Graphical Interface you use to navigate your computers system. Instead of clicking and using Icons to navigate the system, the Command Line uses text based commands and inputs to navigate the computer, usually in a quicker fashion.
I roughly stuck to the timeframe but I undershot the time limit mostly. Instead of finishing up early and moving on I think next time I will just look at any stretch material, or go over the notes that I wrote in the session.
I did not know about Powershell nor did I realise it was already on my PC as a command tool I could use.
Git is the tool that allows a user to branch, commit and pull work to and from their Github Repository. Github is the host of the users project where all the versions of the project are stored and viewable for the user and their team.
An analogy I can think of is a bank account. The bank account is the Github repository where the money(project files) are stored. While the Eftpos card is the Git Tool that allows you to utilize the Money. Using the card(Git) will update the repository(bank account) for anyone who has access to the account to see.
I would understand the concept of what it is, but the terminology would be harder to remember and would probably involve me looking through notes or googling the answer.
I stuck to the timeframes this time around, although reflection didn't require quite as much time as it said, so I used the remaining time to brush over notes.
A GitHub work flow involves either creating a repo from a directory using git init, or cloning an existing repo using git clone. From there it is a case of working on files using branches, staging and committing to push the working versions onto the master repo.
I notice that I got into a bit of a flow state rather quickly which was encouraging and I found that because I could see the relation between what I was learning and how useful it would be later on in projects, that I picked up the information a lot easier and enjoyed doing so. If there was something that caused confusion or a block, I would take myself further back in the resource and continue in case I missed a detail.
I was quite happy with how this section went, I accidentally continued learning through past section 4 but thats only because I was curious and lost attention to where I was in the course.
 The process of staging is when you add the things you want to send and put it into a parcel. The process of committing is to send that parcel off to its recipient.
Master is the main Repo that contains all of the approved features that have been worked on in other branches. It is what contains the final deployable product.
Creating a branch allows you to make any changes or additions to features without affecting the master. This means that if something breaks, it will not affect the most important part of the repo. It also allows for multiple people to work on features and bugs at one time without impacting eachothers work or slowing productivity in any way.
The concepts themselves are easy enough to understand. I have worked with similar workflows in previous jobs. Although I am yet to fully understand all of the git commands, with repitition and time spent using git, I think I will be able to pick it up relatively smoothly.
Perhaps you are looking at an open source project with lots of contributors. In order to make changes without affecting or potentially breaking the main product, it is best to create a fork. This allows you to make all the changes you want to the master without affecting the actual project because you have forked it into your own personal repo.
I think I understood initially what I was trying to do. But the point where it clicked was when I went through and did the whole process and it worked. It just confirmed that what I was thinking was correct, intially I was unsure if that was right. The concepts of the process make a lot of sense to me so that clicked earlier than the commands.
The point of most frustration was mainly just navigating the settings. I am not used to the ins and outs of GitHub yet so navigation isn't autonomous yet.
I am aware of the process of making websites outside of GitHub (although I havent fully deployed one myself) but that only involved me working on a project without Git or GitHub.
The process of solving a problem involves making a calculated, strategic apporach to overcoming a problem rather than blindly hacking away hoping that a solution will stick. The approach involves understanding the problem that needs to be solved, breaking that problem down into sub problems, and creating a plan or roadmap to fixing said problem. Effective problem solving also includes refactoring and reflection once a problem has been solved so that it is solved well and that the solution has been understood and learned from.
I want to train myself to make this approach a habit. This requires me to use these methods as often as possible in any problem solving situation, even if I know its a google search away. Although there is nothing wrong with quickly googling an answer. Developing the habit of going through the process to solve a problem is the best way for the habit to stick.
I learnt that a Flipped Classroom encourages an Intentional Learning Culture that sees instruction move from the group to the individual. Rather than a Teacher being the source of information and answers, it is passed off to the students and the Teacher acts as more of a guide for the students. When moved back into the group space, it allows for students to practice concepts and ideas through intentional learning exercises compared to simply having concepts explained to them in a traditional classroom setting.
A little bit difficult, and a little bit confronting. It can often be hard to make sure what youre saying about yourself actually reflects who you are, I tried my best to make it not sound like a standard job interview answer where you only say the good things about yourself in an exaggerated way. But I like that people in my cohort will have a better idea about who I am and what I am trying to do, as well as where I come from. It will also let me know a bit about the people I am working with.
For sure! I defintely felt that in writing my introduction, I wanted to be percieved well but also didnt want to sound like a pretentious 'goodie good'. It isnt the worst thing in the world though, expressing the person I want to be to the Cohort gives me an opportunity to make sure I meet the standard that I set for myself.


Here are some of my latest projects:
The project can be found here. Also, enjoy the demo:
Built using HTML/CSS, JavaScript and Node.js
The project can be found here.
See more of my work here:


Kernel generating functions.
AUTHORS:
Get a Gaussian distribution that sums to 1 along 1 dimension, quantized by discrete steps.
Make a rectangle (really a vector) that has a particular length.
| Parameters: | window – Length of the kernel, in ms. A value of zero (default), will still make a kernel of len == 1, corresponding to 1 time interval value, and filtering with such a kernel will yield the input. |
|---|
Note
A time window of 5 ms, say, will be different depending on the value of dt. If dt == 1, then the kernel will range from [-2,2] across 5 values. If dt == 0.1, then the kernel will range from [-2.5, 2.5] across 51 values.
Make a ramp from 0 to 1 back to 0 again by dt.
| Parameters: |
|
|---|


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wm_admitance
Author(s): Kevin Blackburn
autogenerated on Sat Mar 23 2019 17:33:32


Hello, Code School!
These are some of the skills I would like to learn, or improve on, through code school:
Git
Ruby
HTML/CSS
There are some more things I'd like to work on, but baby steps :)


Here's a situation you're probably familiar with! We've got a light plugged into a wall, and—surprise—it's lit up!
What makes this happen? Let's take a particularly close look.


Copy this number and give it to the new admin user:
They will use it to create a user account on this website.


PerfScope is a neat tool to evaluate a patch's performance impact to the software system. It can work seamlessly with existing performance testing harness to guide the prioritization of testing. Also, it can provide hint in respect of which change set is more risky when doing triaging of performance regression issues.


{% extends 'main/layout.html' %} {% load static %} {% load i18n %} {% block og %} {% endblock %} {% block content %}
{% blocktrans %} OK!Thess invites startup teams to meet investors from Greece and South-East Europe by applying to participate in the next Thessaloniki Demo Day, taking place on 12 September 2019. {% endblocktrans %}
{% blocktrans %} Thessaloniki Demo Days are events organised by OK!Thess to promote networking between startups and investors of risk capital from Greece and abroad. {% endblocktrans %}
{% blocktrans %}
The previous Demo Day was held in March 2019 at OK!Thess and was the largest ever gathering of Venture Capital funds and business angel networks in Thessaloniki with the sole purpose of holding private meetings with groups of the startup ecosystem. 24 investors participated in more than 130 meetings with 36 startups from Greece and Cyprus.
{% endblocktrans %}
{% blocktrans %} The following active investors from Greece and Europe are participating:
{% blocktrans %}
The only prerequisite for the participation of a startup in the Thessaloniki Demo Day is to have reached a level of maturity and preparation sufficient for the founding team to present a complete investment proposal (the “ask”).
Startups do not need to have gone through the incubation and acceleration program of OK!Thess. Applications are open to any startup from anywhere. It is also not obligatory for a team to present itself to investors for the first time.
{% endblocktrans %}
{% blocktrans %} Startup applications are submitted through this form. Applications are screened by OK!Thess and forwarded to investors for their review. Investors express their interest in meeting with specific startups and OK!Thess arranges the one-on-one meetings for September 12th. Startups are notified about their meeting schedule at least one week in advance. {% endblocktrans %}
{% blocktrans %}
Dimitrios Kourtesis, OK!Thess Program Manager
Email<EMAIL_ADDRESS>{% endblocktrans %}


Security Knowledge Framework
OWASP-SKF is an open source web application that explains secure coding principles in multiple programming languages. The goal of OWASP-SKF is to help you learn and integrate security by design in your software development and build applications that are secure by design. OWASP-SKF does this through manageable software development projects with checklists (using OWASP-ASVS/OWASP-MASVS or custom security checklists) and labs to practise security verification (using SKF-Labs, OWASP Juice-shop, and best practice code examples from SKF and the OWASP-Cheatsheets). If you want a simple set of courses on the fundamentals of developing secure software that don’t involve programming exercises, you might instead consider the Secure Software Development Fundamentals Courses available on edX from OpenSSF.
The code examples show how to approach some common functionalities and how to apply the secure coding principles! We have secure code examples in different languages.
Show different checklists that you can select for reference material. Click on the security control in the checklist to show the correlated knowledgebase item.
All the information which is correlated throughout the project can be found here! Need specific information on the spot then search through the Knowledge base items.
We created SKF Labs for Developers and security specialist to train their security testing skills. Also provided are write-ups for the labs to teach the correct testing methodology.


Based on Angular Seed - a starter project that implements best practices in coding, building and testing Angular apps.
Sprint 1
- Focus on Devops continuous integration toolset
- A chance to review some of the latest version and best practices
- Setup Jira and build workflow
- Setup Infrastructure to use for end-to-end continued learning


Nicolai Brodersen Hansen and Peter Dalsgaard
Explores the possible relevant qualities which artefacts can have within design events.
"we focus on how different design situations evolve as an interplay among participants, things, surroundings, and social constructs...it draws our attention to how participants in a design event frame and reframe their understanding, and resolve problematic situations through the use of design materials."
"Material design artefacts are employed in a wide range of collaborative design events, for instance mock-ups [8] probes [15], props [2] and card-based design games, such as Inspiration Card Workshops [4]."
inquiring materials [credited to Gednryd]
interactive cognition [credited to Gednryd]
Gedenryd (1998) "How designers work: Cognitive studies." - the concept of inquiring materials
Bertelsen, O. W. Elements of a Theory of Design Artefacts – a contribution to critical systems development research. [PhD] 'Bertelsen’s approach directs our attention to the fact that design artefacts often act as go-betweens for the various participants in design experiments.'
Lim et al. 2008 "The anatomy of prototypes: Prototypes as filters, prototypes as manifestations of design ideas."
Ehn and Kyng (1992) "Cardboard computers: mocking-it-up or hands-on the future." 'we find Kyng's approach valuable, as it highlights the role of material design artefacts by focusing on the interplay between material aspects and cooperation'


A jQuery plugin that automagically makes your user generated content responsive.
Demo's and documentation: respontent.frebsite.nl
| Population | Food source | Shelter |
|---|---|---|
| Pedigree | Fed by guardian | Human guardian |
| Pet | Fed by guardian | Human homes |
| Semi-feral | General feeding | Buildings |
| Population | Food source | Shelter |
|---|---|---|
| Pedigree | Fed by guardian | Human guardian |
| Pet | Fed by guardian | Human homes |
| Semi-feral | General feeding | Buildings |


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Venice hit by another exceptional high tide; worst week in 150 years
by Francesca LandiniVENICE (Reuters) - Reeling from devastating floods this week, Venice suffered another exceptional high tide on Sunday, with the water peaking at 150 cm (4.9 feet), marking the worst week for the city since official tide statistics were produced in 1872.
The city’s center for tide forecasts had warned the tide could reach 160 cm on Sunday and the high mark hit at 1210 GMT was not far short of that.
Water flooded St. Mark’s Square and hundreds of voluntary workers were helping citizens cope with the emergency.
The city beloved around the world for its canals, historic architecture and art, was hit by a high tide at 187 cm (6.14 feet) on Tuesday. That was just short of the record 194 cm set in 1966 and caused the city’s worst flooding in 50 years.
In normal conditions, tides of 80-90 cm are generally seen as high but manageable.
With four tides above 140 cm since Monday, this is the worst week for high tides in Venice since 1872 when official statistics were first produced.
Mayor Luigi Brugnaro, who has been appointed special commissioner to deal with the emergency, estimated damages from the flooding in the city since Tuesday at around 1 billion euros ($1.10 billion).
Authorities in Florence and Pisa were also closely monitoring the Arno river, whose water levels rose rapidly in the night due to heavy rain.
Italy’s longest river, the Po, which runs across northern Italy passing through Turin, was also being monitored after its level rose by 1.5 meters in the last 24 hours due to heavy rain.


| Figure 1 |
Map of Lake Superior with sediment core locations. BH03-3, B ... |
| Figure 2 |
Paleoproductivity proxies plotted versus calendar years befo ... |
| Figure 3 |
Temporal relationship between %TOC and δ 13C org in eight se ... |
| Figure 4 |
Profiles of measured and modelled %TOC. Black diamonds are t ... |


using an image without resizing ...
using an image and resizing...
using an image ,resizing and making it link to GOOGLE.COM


Note: This is an experimental feature.
The scriptable render pipeline is not supplied with the standard Unity Editor installer which you download from the Unity store. Instead, download the scriptable render pipeline from the Unity Technologies GitHub and install it separately.
This page contains:
Feature summary
Reimagine the rendering pipeline to support more flexibility and transparency. The main Unity rendering pipeline will be replaced by multiple “Render Loops”, built in C# on a C++ foundation. The C# code for the “Render Loops” will be open-sourced on GitHub, enabling users to investigate, enhance, or create their own custom render loops.
Current Unity’s rendering pipeline is described in Appendix - Current Rendering Pipeline. There are several improvements we want to make – the major ones are spelled below.
Both “one light per draw call” forward rendering, and “stencil mark + draw shape per light” deferred shading are not exactly modern approaches – they were fine for roughly DX9 hardware, but with advent of compute shaders generally we can do much better. Our forward shading suffers from too many draw calls (CPU + vertex transform cost) and bandwidth consumed by repeated sampling of surface textures & blending; whereas deferred shading suffers from draw call count, not enough light culling, cost of doing stencil mark + draw call per light and repeated fetching of G-buffer data. Additionally, on tile-based GPUs it does tile store+load too much when realtime shadows are involved, and does not take advantage of tile storage or framebuffer fetch.
We’d like to ship Unity with an out-of-the box rendering pipeline that is targeted at modern hardware – where we can rely on API & GPU features like compute shaders, draw call instancing, constant buffers etc.
Most of Unity users would probably not modify the built-in rendering pipeline, but some of the more advanced teams do want to modify or extend it. So it has to be extensible and much less opaque than today.
While the current rendering pipeline is somewhat extensible (users can write their own shaders, manually control camera rendering, change settings, extend the rendering pipeline with command buffers), it is not extensible enough. Additionally, it is too much of a “black box”, and while the documentation, conference presentations, MIT-licensed built-in shader source code and community knowledge does fill in the gaps, some parts are hard to understand without a Unity source code license. We want all the high level code and shader/compute code to be a MIT-licensed open source project, similar to how Post-Processing, UI or Networking already are.
A “single render pipeline for everything” likely has some compromises that make it more flexible at expense of performance. We imagine that, for example, these kinds of rendering pipelines would make sense in many cases:
Optimized for modern PC/console (DX11 baseline, “high end” graphics).
Optimized for on-tile storage of mobile GPUs, using framebuffer fetch or other available techniques.
Optimized for VR (e.g. forward shading + MSAA, single-pass rendering, caching/sharing eye rendering results in distance, various schemes of viewport/resolution stitching).
Optimized for low-end devices (old mobile, old PC) or simple 2D games: simple one pass lighting (limited # of lights, and/or vertex lighting).
These don’t have to be physically separate rendering pipelines, could be options in some other existing pipelines.
This is a hard problem for us at Unity R&D, basically doing big changes to how the rendering engine works is quite hard – mostly because people do expect to update to a more recent Unity version and have things “still working as they did”. Except when they don’t, i.e. they actively want new changes… For example, we changed Standard shader from Blinn-Phong to GGX specular in Unity 5.3 – mostly this is a good thing, except for people who were mid-production and now their specular behaves differently (so they probably have to re-tweak their lighting setups and materials).
We’re thinking, that if the high level structure of the rendering code, and all the shader code, was easily “forkable” and versionable, then this problem could become easier.
We think all or most of the problems listed above can be solved fairly elegantly by having a solid, orthogonal, performant foundation to build upon, which would basically be “an ability to render sets of objects with various filtering criteria efficiently”. The division of work would be:
| Unity C++ code | C#/shader code (MIT open source) |
|---|---|
| Culling Render set of objects with filter/sort/params Internal graphics platform abstraction |
Camera setup Light setup Shadows setup Frame render pass structure & logic Shader/compute code |
The C++ side would be mostly not even aware that things like “Camera” or “Light” exist; e.g. culling code gets arrays of bounding primitives and matrices / culling planes as input. It does not care whether it’s culling main view, reflection rendering view or a shadow map view.
Likewise, rendering code is expressed in terms of “from the culling results, render everything that is within opaque render queues range, has this shader pass and does not have that shader pass, sort by material then by distance, setup light probe constants per-object”. There is some amount of conventions and built-in things in there, mostly in what kind of data should be set as per-instance data for each object (light probes, reflection probes, lightmaps, per-object light lists etc.).
There’s a lot of underlying platform graphics abstraction changes that we’re doing in order to be able to provide a robust, high performance and orthogonal set of “building blocks” to build scriptable render loops upon, but they are mostly outside of the scope of this document. Some of the changes worked on are:
Expose “Buffer” as a C# class, that would be used for all kinds of buffer data (vertices, indices, uniforms, compute data etc.). Ability to create and manually update uniform/constant buffers from C# side.
Compute shader related improvements, particularly how data is passed to them.
Remove split between TextureFormat and RenderTextureFormat, have something like “DataFormat” instead that is used in all graphics related code (similar to DXGI formats on D3D). Expose more formats than today.
Asynchronous readbacks of GPU data. Asynchronous compute.
Note: the API is in flux, and this document might not be exact wrt whatever Unity version you’re testing with right now.
The main entry point is RenderLoop.renderLoopDelegate, which is in a form of bool PrepareRenderLoop(Camera[] cameras, RenderLoop outputLoop);
When the render loop delegate is registered, then all rendering goes into that function, and the existing built-in rendering loops are not executed at all.
Inside of the render loop delegate, typically it would do culling for all the cameras (via the new CullResults class), and then do series of calls to RenderLoop.DrawRenderers intermixed with CommandBuffer calls to setup global shader properties, change render targets, dispatch compute shaders etc.
Overall, the design is that the C# render loop code has full control over per-camera logic (it gets all cameras as input), and all per-light logic (it gets all visible lights as a culling result), but generally does not do per-object logic. Objects are rendered in “sets” – DrawRenderers call that specifies which subset of visible objects to render, how to sort them, and what kind of per-object data to setup.
The simplest possible render loop would look something like this:
public bool __Render__(Camera[] cameras, RenderLoop renderLoop)
{
foreach (var camera in cameras)
{
// cull a camera
CullResults cull;
CullingParameters cullingParams;
if (!CullResults.GetCullingParameters (camera, out cullingParams))
continue;
cull = __CullResults.Cull__ (ref cullingParams, renderLoop);
renderLoop.SetupCameraProperties (camera);
// setup render target and clear it
var cmd = new CommandBuffer();
cmd.SetRenderTarget(BuiltinRenderTextureType.CameraTarget);
cmd.ClearRenderTarget(true, true, Color.black);
renderLoop.__ExecuteCommandBuffer__(cmd);
cmd.Dispose();
// draw all the opaque objects using ForwardBase shader pass
var settings = new __DrawRendererSettings__(cull, camera, "ForwardBase");
settings.sorting.sortOptions = SortOptions.SortByMaterialThenMesh;
settings.inputFilter.SetQueuesOpaque();
renderLoop.__DrawRenderers__(ref settings);
renderLoop.Submit ();
}
return true;
}
Most important new scripting APIs:
// main entry point
struct RenderLoop
{
void ExecuteCommandBuffer (CommandBuffer);
void DrawRenderers (ref DrawRendererSettings);
void DrawShadows (ref DrawShadowsSettings); // similar, slightly specialized
void DrawSkybox (Camera);
static PrepareRenderLoop renderLoopDelegate;
}
// Setup and control how sets of objects are rendered by RenderLoop.DrawRenderers
struct DrawRendererSettings
{
DrawRendererSortSettings sorting;
ShaderPassName shaderPassName;
InputFilter inputFilter;
RendererConfiguration rendererConfiguration;
CullResults cullResults { set };
}
struct DrawRendererSortSettings
{
Matrix4x4 worldToCameraMatrix;
Vector3 cameraPosition;
SortOptions sortOptions;
bool sortOrthographic;
}
enum SortOptions { None, FrontToBack, BackToFront, SortByMaterialThenMesh, ... };
struct InputFilter
{
int renderQueueMin, renderQueueMax;
int layerMask;
};
// what kind of data should be set up per-object when rendering them
[Flags] enum RendererConfiguration
{
None,
PerObjectLightProbe,
PerObjectReflectionProbes,
PerObjectLightProbeProxyVolume,
PerObjectLightmaps,
ProvideLightIndices,
// ...
};
// Culling and cull results
struct CullResults
{
VisibleLight[] visibleLights;
VisibleReflectionProbe[] visibleReflectionProbes;
bool GetCullingParameters(Camera, out CulingParameters);
static CullResults Cull(ref CullingParameters, RenderLoop renderLoop);
// utility functions, like
// ComputeDirectionalShadowMatricesAndCullingPrimitives etc
}
struct CullingParameters
{
int isOrthographic;
LODParameters lodParameters;
Plane cullingPlanes[10];
int cullingPlaneCount;
int cullingMask;
float layerCullDistances[32];
Matrix4x4 cullingMatrix;
Vector3 position;
float shadowDistance;
ReflectionProbeSortOptions reflectionProbeSortOptions;
Camera camera;
}
struct VisibleLight
{
LightType lightType;
Color finalColor;
Rect screenRect;
Matrix4x4 localToWorld;
Matrix4x4 worldToLocal;
float range;
float invCosHalfSpotAngle;
VisibleLightFlags flags;
Light light { get }
}
struct VisibleReflectionProbe; // similar to VisibleLight…
The API outlined above is very much not final! Things that are very likely to change:
Considering an option to not have RenderLoop class, but instead have CommandBuffer contain functions like DrawRenderers etc., and possibly have nested command buffers too.
Culling API changes to enable more performance, i.e. jobified culling overlapping with other work.
Possibly more renderer filtering options.
More explicit “render pass” controls, instead of current “set render target” API.
The general flow is that your own render loop code is responsible for culling, and for rendering everything. Including setting up per-frame or per-renderpass shader uniform variables, managing temporary render targets and setting them up, dispatching compute shaders etc.
Visible lights and probes can be queried from the cull results, and for example their information put into compute shader buffers for tiled light culling. Alternatively, the render loop provides several ways of setting up per-object light lists for DX9-style forward rendering.
On the CPU performance side, the API is built in a way where there’s generally no per-object operations going on – the C# side of the code is independent of the scene complexity. It typically loops over cameras, and does some iteration over visible lights to either render shadows, or to pack light data for shader usage. The rest of code that is written in C# is setting up render passes / render textures, and issuing “draw this subset of visible objects” commands.
The C++ part of code (culling, DrawRenderers, DrawShadows) is written in a high-performance style that generally just goes over tightly packed data arrays, and is internally multithreaded. Our current experiments show that with this split (high level frame setup in C#, culling/rendering in C++) we can get same or even better performance of our previous rendering loop implementations.
The C# side looks like it would create a lot of garbage-collected objects; we are looking into ways of exposing “native” (C++ side) data directly to C# without extra round-trips; in C# that would look very similar to an array that writes directly into native side memory. This is a somewhat separate topic, which we’ll talk about separately.
We plan to provide a built-in “HD Render Loop” targeted at modern (compute-capable) platforms. Currently it is developed with PC and PS4/XB1 consoles in mind, but we’ll be looking at optimizing it for high-end mobile platforms too. Of particular interest for mobile is optimizing it for on-tile storage / framebuffer fetch and other bandwidth-saving techniques.
Internally, shaders are written in a way that is less reliant on separate shader variants for every imaginable knob, and more using “static” (uniform based) branching, with shader variant specializations only used where that makes sense based on shader analysis / profiling on modern GPUs.
The new HDRenderLoop is being developed at github ScriptableRenderLoop (might be messy at any point, only use if you’re super-curious right now).
Tiled light culling with compute shaders:
Fine pruned tiled lighting (FPTL) for deferred shaded opaque objects.
Clustered tiled lighting for forward-rendered objects and transparencies.
Rendering can be switched between deferred and forward, depending on what is better for the project.
Lights:
Usual punctual (point/spot) and directional lights.
Area lights (polygonal lights and line lights).
Correct linear lighting & PBR.
Physical light units, IES lights.
(Later) Frustum lights (i.e. bounded directional light).
Shadows:
All realtime shadows are suballocated from a single atlas.
Intuitive controls over shadow memory budget and per-light resolution overrides.
Better PCF filtering, particularly for spot/point lights.
Shadows on semitransparent objects.
GI:
Correct HDR.
Consistency with direct illumination.
(Later) Improved Shadows
Exponential shadow maps (ESM/EVSM).
Improved shadows for area lights.
(Later) Volumetric Lighting
Sky/fog atmospheric scattering model.
Local fog.
GGX with Metal & Specular parametrizations, similar to current Standard shader.
Anisotropic GGX (Metal parametrization)
Sub-surface scattering & transmission
Clear coat
Double sided support
Good specular occlusion
Layered materials (mix & mask inputs of other materials, with up to 4 layers)
Heightmaps either via parallax or displacement tessellation
(later) Built-in LOD cross-fade / dithering
(later) Hair, Eye, Cloth shading models
Physically based camera parameters
Support for Unity’s PostProcessing stack
Distortion
Velocity buffer (for motion blur / temporal AA)
(later) Half/quarter resolution rendering (e.g. for particles) and compositing.
Views of shader inputs (albedo, normals etc.)
Views of all intermediate buffers of rendering (lighting, motion vectors etc.)
Debug menu to control rendering of various passes
Currently (Unity 5.5 and earlier) Unity supports two rendering pipelines for scene (forward rendering and deferred shading), and one way to render realtime shadows. Following is the description of the current pipeline in more detail:
Shadowing system mostly works the same no matter whether the forward or deferred shading is used.
Each realtime light with shadows enabled gets a separate shadow map.
Shadow maps are traditional depth texture maps, in shaders sampled with PCF filtering (no VSM/EVSM etc. shadows).
Directional lights can use cascaded shadow maps (2 or 4 cascades); the shadow map space is divided into cascades like in an atlas.
Spot lights always use simple 2D shadowmap; point lights use a cubemap.
Shadowmap size is computed based on quality settings, screen resolution and light’s projection size on screen; or can be controlled by game developer explicitly from scripts per-light.
Cascaded shadow maps are applied in “screen space” – there’s a separate “gather and do PCF filtering” step that produces screenspace shadow mask texture; later on regular object rendering just does one sample into this texture.
No support for receiving shadows onto semitransparent objects.
The default mode of operation is largely DX9-style “one draw call per light with additive blending”. Quality settings of the game determine how many lights per-object will be rendered in realtime; the rest are folded into a spherical harmonics (SH) representation and rendered together with other ambient lighting.
Optionally before main scene rendering: a “depth texture” rendering pass. This kicks in if scripts require it, or other features (e.g. realtime cascaded shadows) need it. Conceptually this is similar to Z-prepass; produces a texture with scene depth buffer.
Optionally before main scene rendering: a “motion vectors” rendering pass. This kicks in if scripts (e.g. motion blur or temporal AA) require it. Renders a texture of velocity vectors for objects that need them.
Realtime shadow maps are rendered before main scene rendering; all shadows are in memory at once.
Actual scene rendering pass specialized in two shader sets: “ForwardBase” (ambient/probes + lightmaps + lighting/shadows from main directional light), followed by additive blending “ForwardAdd”, that does realtime lighting one light at a time.
This is “traditional” DX9-style deferred shading: G-buffer rendering pass, followed by “render light shapes one by one” pass where each of them reads G-buffer data, computes illumination and adds it into lighting buffer.
Similar to forward rendering, an optional motion vectors pass before the G-buffer.
Reflection probes are rendered one by one similar to lights, by rendering box shapes and adding reflections into a texture.
Lights are rendered one by one, by rendering light shapes (fullscreen quad or sphere or cone) and adding reflections into a texture.
Shadow map for a light is rendered just before rendering each light, and generally discarded right after done with it.
Stencil marking is used for both lights and reflection probes to limit the amount of pixels actually computed.
Objects that don’t support deferred shading, and all semitransparent objects, are rendered using forward rendering.
It is possible to customize the above behavior to some extent, but not much. For example, Valve’s The Lab Renderer (on Asset Store) replaces the built-in behavior by (purely in C# + shaders):
Implementing a custom shadows system, where all shadows are packed into one atlas.
Custom forward rendering system, where all lights are rendered in one pass; light information is setup into custom shader uniform variables.
2017–05–26 Page published with limited editorial review - Leave page feedback
New feature in 5.6


I’m not in the College of Engineering, can I still join?
YES! All that we ask of our members is an interest in Machine Learning and a willingness to learn. As long as you meet these criteria, you’re all set to join, regardless of major or school.
I’ve not taken any classes on Artificial Intelligence or Machine Learning, can I still join?
YES! We don’t assume any formal training in Machine Learning or AI, in fact many of our members had not taken EECS 445, 492, or 442 before joining MSAIL. We encourage you to check out one of our classes as part of our weekly curriculum.
I’ve not taken any coding classes, can I still join?
YES!  That being said, we have a weekly seminary series targeted at students with little to no familiarity with the tools of Machine Learning and Data Science.
It’s the middle of the semester, most student orgs have closed recruiting; can I still join MSAIL?
YES! You’re in luck, MSAIL takes new members on a rolling basis, which means you can apply to join now if you would like. Be aware that some of our groups will have already started work, and may not be taking new members, but there’s still plenty of ways to get involved. IF you are interested in joing MSAIL, contact
Aaron Pollack.
I’m new to Machine Learning and want to learn more about the tools used, how do I do this?
Here’s a list of
resources relating to Machine Learning, Artificial Intelligence, and Data Science. This should get you started. If you have any specific questions, feel free to
contact us. We’ve likely had your question before, and can at least point you in the direction of something that answers it.
I saw something really awesome relating to Machine Learning, Data Science, or Artificial Intelligence, how can I share it with the group?
If you have a resource, tutorial, paper, or project you’d like to share with MSAIL's membership,
contact us and we might just put it on our site for all to see.


{% extends "groupbuilds/base.html" %}
{% load i18n brouwers l10n %}
{% block eye-catcher %}
{% blocktrans %}A group build is basically a themed build with a set start
and end date. Builders who share interests for a certain theme can poll other
forum members if they are interested to take part in a group build. Group builds
usually result in tight groups of builders around a narrow field, providing
valuable theme-specific reference documentation and small facts.
{% endblocktrans %} {% blocktrans %}'Ok, sounds cool and all' I hear you think. But what if you have your
own idea? Just click the button below to submit your idea! We provide the
platform and forum-integration to get your idea going!
{% endblocktrans %}
{% trans "Group builds - some information" %}


We'll put descriptions of the assignments here. Will get loaded dynamically once we have them written.


Amazing transformation of dog attacked with scalding water
WARNING: Distressing images
by Alan WestonAn animal rescue centre posted heartwarming pictures of a dog's miraculous recovery - a year after a sickening attack in which she had boiling water poured over her.
Staff at Freshfields Animal Rescue said they were left "reeling" over the horrific state of the injured puppy when she was brought to their door.
Although they were told the puppy had been found in the street, her injuries pointed strongly to her having been subjected to severe, sustained cruelty and abuse.
On further examination by a vet, it was found the puppy's horrendous injuries were caused by boiling water being poured over her.
She was covered in wounds consistent with untreated scald burns. Her ears were torn and bleeding and she showed obvious signs of malnourishment.
The animal rescue centre has now posted new pictures on Facebook of the amazing transformation of the puppy - named Maple by staff - over the past year.
Thanks to donations of the charity, Maple has now made a full recovery and has been adopted by one of the centre's long-term supporters.


Select a time of day close to the nearest 15 minutes, via a simple dropdown.
To use the components here you first need to include this module in your application @NgModule


Axial slice thickness: mm
Intravenous contrast:
Reformatted images:
History of trauma.
None.
Fracture:
Vertebral alignment:
Neck soft tissues:
Negative cervical spine.


Before Change
from mindsdb import *
// We tell mindsDB what we want to learn and from what data
MindsDB().read_csv(filepath="shakes.train.numLines.csv" ,delimiter="," ,encoding="GB18030")\
.learn(
//from_file="real_estate_description.xlsx", // the path to the file where we can learn from
//predict="number_of_rooms", // the column we want to learn to predict given all the data in the file
After Change
from mindsdb import *
mdb = Predictor(name="real_estate_desc")
// We tell mindsDB what we want to learn and from what data
mdb.learn(


@* * Copyright 2023 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import _root_.implicits.ImplicitCurrencyFormatter.CurrencyFormatter @import _root_.implicits.ImplicitDateFormatterImpl @import models.financialDetails.PaymentsWithChargeType @import models.financialDetails.FinancialDetailsModel @import models.financialDetails.DocumentDetailWithDueDate @import exceptions.MissingFieldException @import java.time.LocalDate @this(implicitDateFormatter: ImplicitDateFormatterImpl) @( paymentAllocations: List[PaymentsWithChargeType], payments: FinancialDetailsModel, documentDetailWithDueDate: DocumentDetailWithDueDate, isAgent: Boolean = false, isMFADebit: Boolean, origin: Option[String] = None, codingOutFrom: String, codingOutTo: String)(implicit messages: Messages) @import implicitDateFormatter.longDate @taxYearTo = @{documentDetailWithDueDate.documentDetail.taxYear} @allocationLinkHTML(link: String, linkText: String) = { @linkText @taxYearTo } @for(allocation <- paymentAllocations ; payment <- allocation.payments) {


#include <state_ops.h>
Optional attribute setters for Assign.
Public attributes |
|
|---|---|
use_locking_ = true
|
bool
|
validate_shape_ = true
|
bool
|
Public functions |
|
|---|---|
UseLocking(bool x)
|
TF_MUST_USE_RESULT Attrs
If True, the assignment will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.
|
ValidateShape(bool x)
|
TF_MUST_USE_RESULT Attrs
If true, the operation will validate that the shape of 'value' matches the shape of the Tensor being assigned to.
|
bool tensorflow::ops::Assign::Attrs::use_locking_ = true
bool tensorflow::ops::Assign::Attrs::validate_shape_ = true
TF_MUST_USE_RESULT Attrs tensorflow::ops::Assign::Attrs::UseLocking( bool x )
If True, the assignment will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.
Defaults to true


-- | This module provides the public interface to the template lifting -- library. It provides functions that input a Haskell declaration or -- expression (in the form of a Haskell abstract syntax tree), and -- lift this to another declaration or expression, with all functions -- lifted into a specified monad. -- -- This can be combined with Template Haskell to convert source code -- to Haskell abstract syntax trees and vice versa. module Libraries.Template ( -- * Example -- $EXAMPLE -- * General lifting functions decToMonad, expToMonad, -- * Liftings of specific constants module Libraries.Template.Auxiliary ) where import Libraries.Template.Lifting import Libraries.Template.Auxiliary -- $EXAMPLE -- -- We give an example to illustrate what is meant by \"lifting\" a -- term to a monad. Consider the expression -- -- > f = \g x -> g x x, -- -- which has type -- -- > f :: (a -> a -> b) -> (a -> b). -- -- We can lift this to the 'IO' monad by -- -- * converting the expression to an abstract syntax tree, using the -- special Template Haskell notation [nobr @[| ... |]@]; -- -- * applying the 'expToMonad' function; -- -- * converting the resulting abstract syntax tree back to a term, -- using the special Template Haskell notation [nobr @$( ... )@]. -- -- This allows us to write the following: -- -- > f' = $( expToMonad "IO" [| \g x -> g x x |] ), -- -- which has type -- -- > f' :: IO ((a -> IO (a -> IO b)) -> IO (a -> IO b)), -- -- and is in fact equivalent to -- -- > f'' = return $ \g -> -- > return $ \x -> do -- > h <- g x -- > y <- h x -- > return y


--- title: "Inputs" date: 2021-04-29T16:00:58+02:00 draft: false main_title: "Tailwind inputs" subheading: "" seo_title: "Tailwind inputs - examples & templates" description: "Responsive inputs built with Tailwind. Get data from the users in password inputs, text areas, email fields, and many more types of data. " image: "" video: "" url: "/docs/standard/forms/inputs/" menu: forms: name: "Inputs" --- {{< example lang="html" title="Basic inputs">}}


'use strict';
Fabric is like an operating system for the distributed web. It manages application state, storage, and network interactions behind the scenes while providing your application with a convenient event-oriented interface.
We use strict mode to improve error handling and debugging, so we recommend you do the same.
'use strict';
Fabric is easily imported into existing applications. When using JavaScript,
use the require
semantic to import as a library.
const Fabric = require('@fabric/core');
Most interactions with Fabric are asynchronous, so let’s define our program’s primary behavior.
async function main () {
let app = new Fabric();
await app._POST(`/inscriptions`, { input: 'Hello, world!' });
console.log('app:', app);
}
main();
Now that we’ve defined our program, let’s run it to see the results.


{% load widget_tweaks %}
" || Mikealson Academy || "
{% include "school/navbar.html" %}
{% csrf_token %}
Add New Admin To School
{% render_field form.first_name class="form-control" placeholder="First Name" %}
{% render_field form.username class="form-control" placeholder="Username" %}
{% render_field form.last_name class="form-control" placeholder="Last Name" %}
{% render_field form.password class="form-control" placeholder="Password" %}
Submit
Already have an account?
Login here
{% include "school/footer.html" %}


{% extends "qraz/base.html" %} {% block content %}
QRAZ provides a simple integration of Hovercraft with GitHub.
You can login to QRAZ with your GitHub account and activate one or more of your repositories that contain hovercraft presentations.
Once you have enabled a repository QRAZ will start monitoring it for pushes, using GitHub webhooks. To tell QRAz which file to convert with hovercraft, you need
to create a file called .hovercraft.yml
inside your repository. This works similar to services like Travis-CI
and their .travis.yml
. The content of the file needs to be valid YAML.
Here is an example for .hovercraft.yml
:
04-html: source: 04-html.rst css: - css/campus02.css template: default auto-console: false skip-help: true skip-notes: true assets: - figures - videos - images - examples 04-html-simple: source: 04-html.rst template: simpleThis would build two presentations named
04-html
and 04-html-simple
using the file 04-html.rst
at the root of the repository as input for hovercraft.
Each presentation in the YAML file can have several attributes, all of which are optional:
source
<presentation-name>.rst
.
css
template
default
is used.
auto-console
auto-console
auto-console
auto-console


- cappuccinoUID - Static variable in class com.example.vybe.SocialActivityTest
-
- check(View, NoMatchingViewException) - Method in class com.example.vybe.Helpers.RecyclerViewItemCountAssertion
-
- clear() - Method in class com.example.vybe.ProfileAdapter
-
- clearLocation() - Method in class com.example.vybe.AddEdit.AddEditVibeEventActivity
-
- clearMap() - Method in class com.example.vybe.MapFragment
-
- ClickOnInternalView - Class in com.example.vybe.Helpers
-
- ClickOnInternalView(int) - Constructor for class com.example.vybe.Helpers.ClickOnInternalView
-
- com.example.vybe - package com.example.vybe
-
- com.example.vybe.AddEdit - package com.example.vybe.AddEdit
-
- com.example.vybe.Helpers - package com.example.vybe.Helpers
-
- com.example.vybe.Models - package com.example.vybe.Models
-
- com.example.vybe.util - package com.example.vybe.util
-
- ConnectionsActivity - Class in com.example.vybe
-
ConnectionsActivity displays the follower and following lists
- ConnectionsActivity() - Constructor for class com.example.vybe.ConnectionsActivity
-
- ConnectionsPageAdapter - Class in com.example.vybe
-
- ConnectionsPageAdapter(FragmentManager, int, Context, User) - Constructor for class com.example.vybe.ConnectionsPageAdapter
-
- Constants - Class in com.example.vybe.util
-
This class holds various constant values to be used for
Google Maps API functionality
- Constants() - Constructor for class com.example.vybe.util.Constants
-
- CountMethodVerify() - Method in class com.example.vybe.UserTest
-
- createAccount(String, String, String) - Method in class com.example.vybe.CreateAccountActivity
-
This method will create the account in Firebase Authentication as well as add it to Firestore if
Authentication does not fail
- CreateAccountActivity - Class in com.example.vybe
-
This activity gets the username and password and validates said fields
with Firestore.
- CreateAccountActivity() - Constructor for class com.example.vybe.CreateAccountActivity
-
- CreateAccountActivityTest - Class in com.example.vybe
-
This tests for user Registration and on the sign up activity
- CreateAccountActivityTest() - Constructor for class com.example.vybe.CreateAccountActivityTest
-
- CustomScrollView - Class in com.example.vybe
-
Allows the user to interact with a map fragment inside a scroll view
- CustomScrollView(Context) - Constructor for class com.example.vybe.CustomScrollView
-
- CustomScrollView(Context, AttributeSet) - Constructor for class com.example.vybe.CustomScrollView
-
- CustomScrollView(Context, AttributeSet, int) - Constructor for class com.example.vybe.CustomScrollView
-


For function "addodd", write
the missing recursive call. This function
should return the sum of all positive odd numbers less than or
equal to "n".
When n is odd, accumlate n's value to whatever will be returned from the recursive call.


35. Bass Drum 2, file 128.35.Jazz_4632.js, var _drum_Jazz_4632_35
36. Bass Drum 1, file 128.36.Jazz_4632.js, var _drum_Jazz_4632_36
37. Side Stick/Rimshot, file 128.37.Jazz_4632.js, var _drum_Jazz_4632_37
38. Snare Drum 1, file 128.38.Jazz_4632.js, var _drum_Jazz_4632_38
39. Hand Clap, file 128.39.Jazz_4632.js, var _drum_Jazz_4632_39
40. Snare Drum 2, file 128.40.Jazz_4632.js, var _drum_Jazz_4632_40
41. Low Tom 2, file 128.41.Jazz_4632.js, var _drum_Jazz_4632_41
42. Closed Hi-hat, file 128.42.Jazz_4632.js, var _drum_Jazz_4632_42
43. Low Tom 1, file 128.43.Jazz_4632.js, var _drum_Jazz_4632_43
44. Pedal Hi-hat, file 128.44.Jazz_4632.js, var _drum_Jazz_4632_44
45. Mid Tom 2, file 128.45.Jazz_4632.js, var _drum_Jazz_4632_45
46. Open Hi-hat, file 128.46.Jazz_4632.js, var _drum_Jazz_4632_46
47. Mid Tom 1, file 128.47.Jazz_4632.js, var _drum_Jazz_4632_47
48. High Tom 2, file 128.48.Jazz_4632.js, var _drum_Jazz_4632_48
49. Crash Cymbal 1, file 128.49.Jazz_4632.js, var _drum_Jazz_4632_49
50. High Tom 1, file 128.50.Jazz_4632.js, var _drum_Jazz_4632_50
51. Ride Cymbal 1, file 128.51.Jazz_4632.js, var _drum_Jazz_4632_51
52. Chinese Cymbal, file 128.52.Jazz_4632.js, var _drum_Jazz_4632_52
53. Ride Bell, file 128.53.Jazz_4632.js, var _drum_Jazz_4632_53
54. Tambourine, file 128.54.Jazz_4632.js, var _drum_Jazz_4632_54
55. Splash Cymbal, file 128.55.Jazz_4632.js, var _drum_Jazz_4632_55
56. Cowbell, file 128.56.Jazz_4632.js, var _drum_Jazz_4632_56
57. Crash Cymbal 2, file 128.57.Jazz_4632.js, var _drum_Jazz_4632_57
58. Vibra Slap, file 128.58.Jazz_4632.js, var _drum_Jazz_4632_58
59. Ride Cymbal 2, file 128.59.Jazz_4632.js, var _drum_Jazz_4632_59
60. High Bongo, file 128.60.Jazz_4632.js, var _drum_Jazz_4632_60
61. Low Bongo, file 128.61.Jazz_4632.js, var _drum_Jazz_4632_61
62. Mute High Conga, file 128.62.Jazz_4632.js, var _drum_Jazz_4632_62
63. Open High Conga, file 128.63.Jazz_4632.js, var _drum_Jazz_4632_63
64. Low Conga, file 128.64.Jazz_4632.js, var _drum_Jazz_4632_64
65. High Timbale, file 128.65.Jazz_4632.js, var _drum_Jazz_4632_65
66. Low Timbale, file 128.66.Jazz_4632.js, var _drum_Jazz_4632_66
67. High Agogo, file 128.67.Jazz_4632.js, var _drum_Jazz_4632_67
68. Low Agogo, file 128.68.Jazz_4632.js, var _drum_Jazz_4632_68
69. Cabasa, file 128.69.Jazz_4632.js, var _drum_Jazz_4632_69
70. Maracas, file 128.70.Jazz_4632.js, var _drum_Jazz_4632_70
71. Short Whistle, file 128.71.Jazz_4632.js, var _drum_Jazz_4632_71
72. Long Whistle, file 128.72.Jazz_4632.js, var _drum_Jazz_4632_72
73. Short Guiro, file 128.73.Jazz_4632.js, var _drum_Jazz_4632_73
74. Long Guiro, file 128.74.Jazz_4632.js, var _drum_Jazz_4632_74
75. Claves, file 128.75.Jazz_4632.js, var _drum_Jazz_4632_75
76. High Wood Block, file 128.76.Jazz_4632.js, var _drum_Jazz_4632_76
77. Low Wood Block, file 128.77.Jazz_4632.js, var _drum_Jazz_4632_77
78. Mute Cuica, file 128.78.Jazz_4632.js, var _drum_Jazz_4632_78
79. Open Cuica, file 128.79.Jazz_4632.js, var _drum_Jazz_4632_79
80. Mute Triangle, file 128.80.Jazz_4632.js, var _drum_Jazz_4632_80
81. Open Triangle, file 128.81.Jazz_4632.js, var _drum_Jazz_4632_81


| # | Method or Atribute | Scope | Description |
|---|---|---|---|
| 1 | isFit | PolynomialModel Class | Attribute that defines if the model is already trained or not |
| 2 | solutions | PolynomialRegression Class | Array of floats that stores the solutions for the polynomial model |
| 3 | fit | PolynomialRegression Class | This method creates the solutions for the polynomial model based in the logic that will be described below |
| 4 | xArray | Method fit - PolynomialModel Class | Array parameter of x values that are used to train the model |
| 5 | yArray | Method fit - PolynomialRegression Class | Array parameter of y values that are used to train the model |
| 6 | degree | Method fit - PolynomialRegression Class | Paramter with the desired degree for the model |
| 7 | equationSize | Method fit - PolynomialRegression Class | Attribute that defines the number of equations that are going to be used in the model based in the degree of the model |
| 8 | nElements | Method fit - PolynomialRegression Class | Attribute that defines the number columns that are going to be used in the matrix for the model |
| 9 | equations | Method fit - PolynomialRegression Class | Matrix that stores the equations and solutions for the polynomial model |
| 10 | predict | PolynomialRegression Class | Function that returns the predicted values based on the traning done before by the model |
| 10 | xArray | Method predict - PolynomialRegression Class | Parameter with the x Array values to be predicted |
| 11 | yArray | Method predict - PolynomialRegression Class | Array with y values predicted by the model |
| 12 | calculateR2 | Method calculateR2 - PolynomialRegression Class | Method that creates the r^2 error of the trained model |
| 13 | getError | Method getError - PolynomialRegression Class | Method that return the r^2 value for the trained model |
In order to train the model to get an accurate prediction based in the input degree, it was used several math concepts to get a precise function for the model, in this library it was used the following concepts to develop the solution:
This method was used to build a coefficent matrix for the equation system solution, this matrix is simetric and it is created based in an input degree that we call "m", the logic of least squares is pretty simple, it just consist in creating a matrix that contains a group of equations that increase their degree as we create new equations in the matrix, this matrix is later solved to get the coefficents for the solution of the Regression Model.
| n | Σx | Σx^2 | Σx^3 | ... | Σx^m | Σy |
| Σx | Σx^2 | Σx^3 | Σx^4 | ... | Σx^m | Σxy |
| Σx^2 | Σx^3 | Σx^4 | Σx^5 | ... | Σx^m | Σx^2*y |
| ... | ... | ... | ... | ... | ... | ... |
| Σx^m | Σx^m+1 | Σx^m+2 | Σx^m+3 | ... | Σx^m+n | Σx^m*y |
This method was used to build the solution for the model, once we have the equations matrix to be solved it was used Gauss Jordan to get the coefficent of the equations to be later stored in the array of solutions.
| 1 | 2 | 3 | 4 | ... | n | m |
| 0 | 1 | 2 | 3 | ... | n | m |
| 0 | 0 | 1 | 2 | ... | n | m |
| ... | ... | ... | ... | ... | ... | ... |
| 0 | 0 | 0 | 0 | ... | n | m |
The usage of the PolynomialRegression Library is pretty simple you just have to follow the next steps
In order to use the library you must import it into your html code, you can find the library in the dist folder as PolynomialRegression.js file
After importing the library into your html code you need to train the model. In order to train your model you must create 2 training array data that will be used when instanciating the library
In orther to train the model you must create an instance of the PolynomialRegression library, then you must call the method fit, in this method you will send the xArray and yArray of training data followed by the degree of training for the model
To create a prediction you must create an array of x values to be predicted, to create the prediction you only have to call the function precit and then you send the values to predict to the function
| Name | Description |
|---|---|
| dataset | 2-dimensional matrix that contains the data header in the first row and the last column contains the 2 possible classes. |
| generalEntropy | Stores the overall entropy of the data set. |
| primaryCount | Stores how many times the first class found appears in the data set. |
| secondaryCount | Stores how many times the second class found appears in the data set. |
| primaryPosibility | Stores the first class found in the data set. |
| secondaryPosibility | Stores the second class found in the data set. |
| root | It is the root of the tree resulting from training |
| Name | Description |
|---|---|
| calculateEntropy | Receives 2 parameters, the first is how many times the first label appears, the second parameter is how many times the second label appears and returns the calculation of the entropy equation |
| train | This method is in charge of generating the decision tree through the data set it receives, it returns the root node of the generated tree. |
| predict | This function classifies the 2xm matrix it receives as a parameter, starts the search from the node it receives as a parameter, returns the node with the class it belongs to or null if it is not able to classify. |
| recursivePredict | This function is used as an aid to traversing the decision tree. |
| calculateGeneralEntropy | This function analyzes the received data set, it counts the number of times the first and second class appear, the index parameter that it receives indicates the number of column in which the count must be performed, it makes use of the calculateEntropy function and returns the value of the entropy of the entire data set. |
| classifierFeatures | This function analyzes the received data set, using the index parameter, separates each data into the corresponding characteristic, and returns a list of characteristics. |
| calculateInformationEntropy | This function receives a list of characteristics and returns the value of the entropy of the information for the received characteristic. |
| calculateGain | This function receives the general entropy and the information entropy and returns the value of the profit. |
| selectBestFeature | This function receives a set of characteristics and returns the index of the characteristic with the highest gain. |
| generateDotString | This function is used to generate the string in the format that the visjs tool accepts to generate a tree type graph. |
| recursiveDotString | This function is auxiliary to traverse the tree and generate the string for visjs |
This Machine Learning process works with the ID3 algorithm. It is a simple implementation to classify data matrices with the following characteristics
[
Note: Attr#, lorem, Result and Class# can be any string.
["Attr1", "Attr2", "Attr3", "Result"],
["lorem", "lorem", "lorem", "Class1"],
["lorem", "lorem", "lorem", "Class2"],
["lorem", "lorem", "lorem", "Class1"],
["lorem", "lorem", "lorem", "Class2"],
["lorem", "lorem", "lorem", "Class1"],
]
The data to be predicted consists of a matrix with 2 rows and m columns. The first row will be the header, the second row will consist of the data for decision making.
[
Note: The header must be in the data
["Attr1", "Attr2", "Attr3"],
["lorem", "lorem", "lorem"],
]
The result of the classification consists of an object of type NodeTree which has in its value attribute the classification of the data entered.
{
childs: []
id: "3eb4d4228163"
tag: "Overcast"
value: "Yes"
}
| Name | Description |
|---|---|
| k | Number of clusters in wich the points will be grouped. |
| data | Array of numbers representing each point on the X axis. |
| iterations | Amount of repetitions that the algorithm will perform. The iterations apply specifically to the randomization of possible cluster points. |
| Name | Parameters | Description |
|---|---|---|
| clusterize |
|
This is the main method of the KMeans algorithm, which follows the following steps:
|
| distance |
|
This method returns the distance between two points (point_b - point_a) |
| calculateMeanVariance |
|
This method returns the mean and variance of an array of values. The mean of arr is the sum of all the data divided by the item count. The variance of arr is the sum of the substraction of each point and the mean, to the power of 2, divided by de item count. |
data = [
-99,
-92,
-89,
-87,
-83,
-82,
-78,
-76,
-70,
-62,
-57,
-55,
-50,
-42,
-35,
-33,
-32,
-30,
-27,
-17,
-12,
-10,
0,
1,
2,
25,
29,
33,
39,
41,
53,
54,
67
]
k = 3
iterations = 3
The result is showed on a graphic, each point has a color wich identifies the cluster group it is assigned to. The cluster points are drawn as red dots.
| Name | Description |
|---|---|
| k | Number of clusters in wich the points will be grouped. |
| data | Array of coordinates [x,y] representing each point. |
| iterations | Amount of repetitions that the algorithm will perform. The iterations apply specifically to the randomization of possible cluster points. |
| Name | Parameters | Description |
|---|---|---|
| clusterize |
|
This is the main method of the KMeans algorithm, which follows the following steps:
|
| distance |
|
This method returns the distance between two points |
| calculateMeanVariance |
|
This method returns the mean and variance of an array of values. The mean of arr is the sum of all the data divided by the item count. The variance of arr is the sum of the substraction of each point and the mean, to the power of 2, divided by de item count. |
data = [
[11,6],
[4,2],
[15,0],
[10,6],
[7,8],
[9,12],
[13,0],
[5,1],
[0,13],
[7,5],
[6,1],
[3,6],
[0,10],
[14,10],
[6,14],
[6,4],
[4,9],
[5,14],
[9,9],
[13,8]
]
k = 3
iterations = 10
The result is showed on a graphic, each point has a color wich identifies the cluster group it is assigned to. The cluster points are drawn as red dots.
| Name | Description |
|---|---|
| k | Number of clusters in wich the points will be grouped. |
| data | Array of numbers representing each point on the X axis. |
| iterations | Amount of repetitions that the algorithm will perform. The iterations apply specifically to the randomization of possible cluster points. |
| Name | Parameters | Description |
|---|---|---|
| clusterize |
|
This is the main method of the KMeans algorithm, which follows the following steps:
|
| distance |
|
This method returns the distance between two points (point_b - point_a) |
| calculateMeanVariance |
|
This method returns the mean and variance of an array of values. The mean of arr is the sum of all the data divided by the item count. The variance of arr is the sum of the substraction of each point and the mean, to the power of 2, divided by de item count. |
| Name | Description |
|---|---|
| attributes | Attributes that the model to evaluate will contain |
| classes | Classes that the model to evaluate will contain |
| frecuencyTables | Table containing the data of the probabilities of each event |
| attributesNames | Stores the name of each attribute registered in the model |
| className | Stores the value of the last class that was added |
| Name | Parameters | Description |
|---|---|---|
| addAttribute |
|
Method used to add an attribute to the array of attributes that belong to a specific model. Its values parameter will contain the values to add the attribute and the name to associate it. |
| addClass |
|
Method used to add a class to the array of classes that belong to a specific model. Its values parameter will contain the values to add the class and the name to associate it. |
| train | Method used to train our model with its corresponding attributes and classes. This method also makes use of the frequency table to store the probabilities found. | |
| probability |
|
Method used to calculate the probabilities of an attribute using its cause and effect |
| predict |
|
Method used to predict an outcome through a given event. To predict these events, the cause and effect parameters are used. |
| isModelValid | Method used to validate if a model is valid through its minimum requirements, such as the one that contains classes, attributes, etc. | |
| toFrecuencyTable |
|
Method used to store and return the frequency table that contains the probabilities, frequencies and values of the model |
The result is shown below
| Name | Description |
|---|---|
| causes | Array of the causes to be taken in count for the prediction |
| Name | Parameters | Description |
|---|---|---|
| insertCause |
|
This method fills the data usted to make the predictions. Each cause added must have the
same events array as the others inserted, otherwise it will throw an error through console .
|
| predict |
|
This is the main method that runs the prediction for the data entered through on the
parameters.
|
| getSimpleProbability |
|
This method returns the probability that an event ocurrs. Events are represented by tuples with the format ["column_name", value]. In other words it returns the probability of finding "value" on cause "column_name" |
| getConditionalProbability |
|
Returns probability of event_A occurring given that event_B occurs. Events are represented by tuples with the format ["column_name", value]. |
| getCauseByName |
|
Returns the array of values corresponding to the column/cause identified with the value recieved in the parameter. |
| Name | Description |
|---|---|
| alpha | percentage of certainty |
| lambda | Number of lambda of the function |
| iterations | number of iterations that the algorithm must perform |
| Name | Parameters | Description |
|---|---|---|
| fit |
|
This method separates the input matrix into respective arrays of X, Y, and the current value (s). To later carry out the transformation and evaluation of the function
|
| computeThreshold |
|
This Method obtains the threshold of the coordinates obtained in X and Y |
| grad |
|
this method calculates and obtains the gradient with which the function will be evaluated |
| h |
|
This method evaluates the X coordinate with the theta coefficient in the logistic regression function. |
| transform |
|
This method returns the transformation of the prediction, in this case if it is binary it checks if it is 1 or 0 and if it is multiclass it compares the classes with the array. |
| cost |
|
The method returns the cost of the function, this is achieved by evaluating the function in the equation of the method h () |


--- layout: post title: Marco Pulls Apart a Microsoft Sponsored Study on the "Apple Tax" ---
Marco Pulls Apart a Microsoft Sponsored Study on the "Apple Tax"
I totally agree that Apple stuff is overpriced as far as the high end stuff goes, that is, Macbook Pros and Mac Pros. Although that could just be a hunch because I’ve never researched a PC with identical or very similar specifications to Apple’s top of the line computers.
But when it comes to the consumer stuff, Macbooks, iMacs and Mac Minis, the prices are on par. Find a PC with the same specs as a Macbook and it costs about the same. You see really cheap, sub $1000 PC laptops because they’re simply not as good, Apple don’t even make a comparable computer so comparing a bottom of the range $600 Dell to a $1600 Macbook on price is unfair.


You can quickly find a setting you need in the Settings/Preferences dialog, without browsing through the numerous options. Just type some characters that, in your opinion, exist in the option description, and the list of settings will reduce to the matching ones. Select the desired entry, and see the setting that contains the entered characters highlighted:


InPlaceRichEditor
Functional Tests
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