SOLDIERS
问题描述 :
N soldiers of the land Gridland are randomly scattered around the country.
A position in Gridland is given by a pair (x,y) of integer coordinates. Soldiers can move – in one move, one soldier can go one unit up, down, left or right (hence, he can change either his x or his y coordinate by 1 or -1).
A position in Gridland is given by a pair (x,y) of integer coordinates. Soldiers can move – in one move, one soldier can go one unit up, down, left or right (hence, he can change either his x or his y coordinate by 1 or -1).
The soldiers want to get into a horizontal line next to each other (so that their final positions are (x,y), (x+1,y), …, (x+N-1,y), for some x and y). Integers x and y, as well as the final order of soldiers along the horizontal line is arbitrary.
The goal is to minimise the total number of moves of all the soldiers that takes them into such configuration.
Two or more soldiers must never occupy the same position at the same time.
输入:
The first line of the input contains the integer N, 1 <= N <= 10000, the number of soldiers.
The following N lines of the input contain initial positions of the soldiers : for each i, 1 <= i <= N, the (i+1)st line of the input file contains a pair of integers x[i] and y[i] separated by a single blank character, representing the coordinates of the ith soldier, -10000 <= x[i],y[i] <= 10000.
The following N lines of the input contain initial positions of the soldiers : for each i, 1 <= i <= N, the (i+1)st line of the input file contains a pair of integers x[i] and y[i] separated by a single blank character, representing the coordinates of the ith soldier, -10000 <= x[i],y[i] <= 10000.
输出:
The first and the only line of the output should contain the minimum total number of moves that takes the soldiers into a horizontal line next to each other.
样例输入:
5 1 2 2 2 1 3 3 -2 3 3
样例输出:
8
解题代码:
import java.io.BufferedInputStream; import java.util.Arrays; import java.util.Scanner; public class Main { static int x[]; static int y[]; public static void main(String[] args) { Scanner scan = new Scanner(new BufferedInputStream(System.in)); if (scan.hasNext()) { int n = scan.nextInt(); x = new int[n]; y = new int[n]; for (int i = 0; i < n; i++) { x[i] = scan.nextInt(); y[i] = scan.nextInt(); } Arrays.sort(x); Arrays.sort(y); for (int i = 0; i < n; i++) { x[i] -= i; } Arrays.sort(x); int midX = x[(n + 1) / 2 - 1]; int midY = y[(n + 1) / 2 - 1]; int num = 0; for (int i = 0; i < n; i++) { num += Math.abs(x[i] - midX) + Math.abs(y[i] - midY); } System.out.println(num); } } }
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不考虑最后将结果排序的话，快排的时间复杂度是O(N) ，而堆排的是O(N*logK)
好的，多谢指出
惊艳了，没想到代码如此简洁
刚开始学习，为啥会报错了
给力的文章，例子也非常好
这怎么用Catalan数啊？求解答！
问题3是不是应该为1/4 .因为截取的三段，无论是否能组成三角形， x， y-x ，1-y,都应大于0，所以 x<y,基础应该是一个大三角形。小三角是大三角的 1/4.
可以参考算法导论中的时间戳。就是结束访问时间，最后结束的顶点肯定是入度为0的顶点，因为DFS要回溯
#include <cstdio>
#include <cstring>
const int MAXSIZE=256;
//char store[MAXSIZE];
char str1[MAXSIZE];
/*
void init(char *store) {
int i;
store['A']=’V', store['B']=’W',store['C']=’X',store['D']=’Y',store['E']=’Z';
for(i=’F';i<=’Z';++i) store =i-5;
}
*/
int main() {
//freopen("input.txt","r",stdin);
//init(store);
char *p;
while(fgets(str1,MAXSIZE,stdin) && strcmp(str1,"STARTn")==0) {
if(p=fgets(str1,MAXSIZE,stdin)) {
for(;*p;++p) {
//*p=store[*p]
if(*p<’A’ || *p>’Z') continue;
if(*p>’E') *p=*p-5;
else *p=*p+21;
}
printf("%s",str1);
}
fgets(str1,MAXSIZE,stdin);
}
return 0;
}
0000
很赞的解答
wt[n - 1]没错，因为下标是[0...n-1]
好厉害～
顶一个 赞一个


This is the API documentation for 'actionmailer-3.2.12 Documentation'.
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This app helps you determine the likely diminution of sentence ("good time") for offenders sentenced to imprisonment in Louisiana under La. R.S. 15:571.3. To use it, you must know the sentence the offender received along with the amount of time that was credited for time served while awaiting sentencing. Enter these values with numbers and time units, like "8 years" or "1 year 6 months 5 days". Click on "Calculate Good Time" and the likely number of days the offender will serve before being released on parole will appear at the top of your screen.
Please note that if the offender was sentenced as a habitual offender under La. R.S. 15:529.1, they will not receive good time
This app is for informational purposes only and should not be considered legal advice. Determinations about good time are made by the La. Department of Corrections only. Their determinations may differ from the information provided here.


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Sophia compiler is part of the Software Development Kit (SDK) and used
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Æternity is not liable in any way for the
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Package org.drip.capital.allocation
Class EntityElasticityAttribution
java.lang.Object
org.drip.capital.allocation.EntityElasticityAttribution
public class EntityElasticityAttribution
extends java.lang.Object
EntityElasticityAttribution holds the Attributions across all Entity Components into Fixed, Float,
and Pro-rata Elasticities. The References are:
- Bank for International Supervision (2005): Stress Testing at Major Financial Institutions: Survey Results and Practice https://www.bis.org/publ/cgfs24.htm
- Glasserman, P. (2004): Monte Carlo Methods in Financial Engineering Springer
- Kupiec, P. H. (2000): Stress Tests and Risk Capital Risk 2 (4) 27-39
- Module = Portfolio Core Module
- Library = Capital Analytics
- Project = Basel Market Risk and Operational Capital
- Package = Economic Risk Capital Entity Allocation
- Author:
- Lakshmi Krishnamurthy
-
Constructor Summary
Constructors Constructor Description EntityElasticityAttribution(CorrelationCategoryBetaManager correlationCategoryBetaManager, boolean unitLoading)
EntityElasticityAttribution Constructor -
Method Summary
Modifier and Type Method Description boolean
accumulate(PnLAttribution pnlAttribution, EntityCapitalAssignmentSetting entityCapitalAssignmentSetting)
Accumulate with the Beta-Adjusted Component Attributionboolean
accumulateCorrelated(double correlatedAttribution, int correlatedAllocationCategory, int correlatedAllocationScheme)
Accumulate the Correlated Attribution with the Beta-Adjusted Component Attributionboolean
accumulateCorrelatedFixed(double correlatedFixedAttribution)
Accumulate the Correlated Fixed Attributionboolean
accumulateCorrelatedFloating(double correlatedFloatingAttribution)
Accumulate the Correlated Floating Attributionboolean
accumulateCorrelatedProRata(double correlatedProRataAttribution)
Accumulate the Correlated Pro-Rata Attributionboolean
accumulateIdiosyncratic(double idiosyncraticAttribution, int idiosyncraticAllocationCategory, int idiosyncraticAllocationScheme)
Accumulate the Idiosyncratic Attribution with the Beta-Adjusted Component Attributionboolean
accumulateIdiosyncraticFixed(double idiosyncraticFixedAttribution)
Accumulate the Idiosyncratic Fixed Attributionboolean
accumulateIdiosyncraticFloating(double idiosyncraticFloatingAttribution)
Accumulate the Idiosyncratic Floating Attributionboolean
accumulateIdiosyncraticProRata(double idiosyncraticProRataAttribution)
Accumulate the Idiosyncratic Pro-Rata Attributionboolean
accumulateNoStress(double noStressAttribution, int noStressAllocationCategory, int noStressAllocationScheme)
Accumulate the No Stress Attribution with the Beta-Adjusted Component Attributionboolean
accumulateNoStressFixed(double noStressFixedAttribution)
Accumulate the No-Stress Fixed Attributionboolean
accumulateNoStressFloating(double noStressFloatingAttribution)
Accumulate the No-Stress Floating Attributionboolean
accumulateNoStressProRata(double noStressProRataAttribution)
Accumulate the No-Stress Pro-Rata Attributionboolean
accumulateSystemic(double systemicAttribution, int systemicAllocationCategory, int systemicAllocationScheme)
Accumulate the Systemic Attribution with the Beta-Adjusted Component Attributionboolean
accumulateSystemicFixed(double systemicFixedAttribution)
Accumulate the Systemic Fixed Attributionboolean
accumulateSystemicFloating(double systemicFloatingAttribution)
Accumulate the Systemic Floating Attributionboolean
accumulateSystemicProRata(double systemicProRataAttribution)
Accumulate the Systemic Pro-Rata AttributionEntityComponentElasticityAttribution
correlated()
Retrieve the Correlated Elasticity Attributiondouble
correlatedProRata()
Retrieve the Pro-Rata Correlated Capitaldouble
correlatedTotal()
Retrieve the Total Correlated Component Capitaldouble
fixed()
Retrieve the Fixed Beta Capital Componentdouble
floating()
Retrieve the Floating Beta Capital ComponentEntityComponentElasticityAttribution
idiosyncratic()
Retrieve the Idiosyncratic Elasticity Attributiondouble
idiosyncraticProRata()
Retrieve the Pro-Rata Idiosyncratic Capitaldouble
idiosyncraticTotal()
Retrieve the Total Idiosyncratic Component CapitalEntityComponentElasticityAttribution
noStress()
Retrieve the "No Stress" Elasticity Attributiondouble
noStressProRata()
Retrieve the Pro-Rata No-Stress Capitaldouble
noStressTotal()
Retrieve the Total No Stress Component Capitaldouble
proRata()
Retrieve the Pro-Rata Beta Capital ComponentEntityComponentElasticityAttribution
systemic()
Retrieve the Systemic Elasticity Attributiondouble
systemicProRata()
Retrieve the Pro-Rata Systemic Capitaldouble
systemicTotal()
Retrieve the Total Systemic Component CapitalMethods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
-
Constructor Details
-
EntityElasticityAttribution
public EntityElasticityAttribution(CorrelationCategoryBetaManager correlationCategoryBetaManager, boolean unitLoading) throws java.lang.ExceptionEntityElasticityAttribution Constructor- Parameters:
correlationCategoryBetaManager
- The Correlation Category Beta ManagerunitLoading
- The Unit Loading Flag- Throws:
java.lang.Exception
- Thrown if the Inputs are Invalid
-
-
Method Details
-
systemic
Retrieve the Systemic Elasticity Attribution- Returns:
- The Systemic Elasticity Attribution
-
idiosyncratic
Retrieve the Idiosyncratic Elasticity Attribution- Returns:
- The Idiosyncratic Elasticity Attribution
-
noStress
Retrieve the "No Stress" Elasticity Attribution- Returns:
- The "No Stress" Elasticity Attribution
-
accumulateSystemicFixed
public boolean accumulateSystemicFixed(double systemicFixedAttribution)Accumulate the Systemic Fixed Attribution- Parameters:
systemicFixedAttribution
- Systemic Fixed Attribution- Returns:
- TRUE - The Systemic Fixed Attribution successfully updated
-
accumulateIdiosyncraticFixed
public boolean accumulateIdiosyncraticFixed(double idiosyncraticFixedAttribution)Accumulate the Idiosyncratic Fixed Attribution- Parameters:
idiosyncraticFixedAttribution
- Idiosyncratic Fixed Attribution- Returns:
- TRUE - The Idiosyncratic Fixed Attribution successfully updated
-
accumulateNoStressFixed
public boolean accumulateNoStressFixed(double noStressFixedAttribution)Accumulate the No-Stress Fixed Attribution- Parameters:
noStressFixedAttribution
- No-Stress Fixed Attribution- Returns:
- TRUE - The No-Stress Fixed Attribution successfully updated
-
accumulateSystemicFloating
public boolean accumulateSystemicFloating(double systemicFloatingAttribution)Accumulate the Systemic Floating Attribution- Parameters:
systemicFloatingAttribution
- Systemic Floating Attribution- Returns:
- TRUE - The Systemic Floating Attribution successfully updated
-
accumulateIdiosyncraticFloating
public boolean accumulateIdiosyncraticFloating(double idiosyncraticFloatingAttribution)Accumulate the Idiosyncratic Floating Attribution- Parameters:
idiosyncraticFloatingAttribution
- Idiosyncratic Floating Attribution- Returns:
- TRUE - The Idiosyncratic Floating Attribution successfully updated
-
accumulateNoStressFloating
public boolean accumulateNoStressFloating(double noStressFloatingAttribution)Accumulate the No-Stress Floating Attribution- Parameters:
noStressFloatingAttribution
- No-Stress Floating Attribution- Returns:
- TRUE - The No-Stress Floating Attribution successfully updated
-
accumulateSystemicProRata
public boolean accumulateSystemicProRata(double systemicProRataAttribution)Accumulate the Systemic Pro-Rata Attribution- Parameters:
systemicProRataAttribution
- Systemic Pro-Rata Attribution- Returns:
- TRUE - The Systemic Pro-Rata Attribution successfully updated
-
accumulateIdiosyncraticProRata
public boolean accumulateIdiosyncraticProRata(double idiosyncraticProRataAttribution)Accumulate the Idiosyncratic Pro-Rata Attribution- Parameters:
idiosyncraticProRataAttribution
- Idiosyncratic Pro-Rata Attribution- Returns:
- TRUE - The Idiosyncratic Pro-Rata Attribution successfully updated
-
accumulateNoStressProRata
public boolean accumulateNoStressProRata(double noStressProRataAttribution)Accumulate the No-Stress Pro-Rata Attribution- Parameters:
noStressProRataAttribution
- No-Stress Pro-Rata Attribution- Returns:
- TRUE - The No-Stress Pro-Rata Attribution successfully updated
-
accumulateSystemic
public boolean accumulateSystemic(double systemicAttribution, int systemicAllocationCategory, int systemicAllocationScheme)Accumulate the Systemic Attribution with the Beta-Adjusted Component Attribution- Parameters:
systemicAttribution
- The Systemic AttributionsystemicAllocationCategory
- The Systemic Allocation CategorysystemicAllocationScheme
- The Systemic Allocation Scheme- Returns:
- TRUE - The Systemic Partition with the Beta-Adjusted Increment
-
accumulateIdiosyncratic
public boolean accumulateIdiosyncratic(double idiosyncraticAttribution, int idiosyncraticAllocationCategory, int idiosyncraticAllocationScheme)Accumulate the Idiosyncratic Attribution with the Beta-Adjusted Component Attribution- Parameters:
idiosyncraticAttribution
- The Idiosyncratic AttributionidiosyncraticAllocationCategory
- The Idiosyncratic Allocation CategoryidiosyncraticAllocationScheme
- The Idiosyncratic Allocation Scheme- Returns:
- TRUE - The Idiosyncratic Partition with the Beta-Adjusted Increment
-
accumulateNoStress
public boolean accumulateNoStress(double noStressAttribution, int noStressAllocationCategory, int noStressAllocationScheme)Accumulate the No Stress Attribution with the Beta-Adjusted Component Attribution- Parameters:
noStressAttribution
- The No Stress AttributionnoStressAllocationCategory
- The No Stress Allocation CategorynoStressAllocationScheme
- The No Stress Allocation Scheme- Returns:
- TRUE - The No Stress Partition with the Beta-Adjusted Increment
-
accumulate
public boolean accumulate(PnLAttribution pnlAttribution, EntityCapitalAssignmentSetting entityCapitalAssignmentSetting)Accumulate with the Beta-Adjusted Component Attribution- Parameters:
pnlAttribution
- PnL AttributionentityCapitalAssignmentSetting
- Entity Capital Assignment Setting- Returns:
- TRUE - The Accumulation is successful
-
systemicTotal
public double systemicTotal()Retrieve the Total Systemic Component Capital- Returns:
- The Total Systemic Component Capital
-
idiosyncraticTotal
public double idiosyncraticTotal()Retrieve the Total Idiosyncratic Component Capital- Returns:
- The Total Idiosyncratic Component Capital
-
noStressTotal
public double noStressTotal()Retrieve the Total No Stress Component Capital- Returns:
- The Total No Stress Component Capital
-
fixed
public double fixed()Retrieve the Fixed Beta Capital Component- Returns:
- The Fixed Beta Capital Component
-
floating
public double floating()Retrieve the Floating Beta Capital Component- Returns:
- The Floating Beta Capital Component
-
proRata
public double proRata()Retrieve the Pro-Rata Beta Capital Component- Returns:
- The Pro-Rata Beta Capital Component
-
systemicProRata
public double systemicProRata()Retrieve the Pro-Rata Systemic Capital- Returns:
- The Pro-Rata Systemic Capital
-
idiosyncraticProRata
public double idiosyncraticProRata()Retrieve the Pro-Rata Idiosyncratic Capital- Returns:
- The Pro-Rata Idiosyncratic Capital
-
noStressProRata
public double noStressProRata()Retrieve the Pro-Rata No-Stress Capital- Returns:
- The Pro-Rata No-Stress Capital
-


Contact Information
- Instructor: Michael Levet (He/Him/His)
- Contact: TODO
- Office Hours (Tentative):
- Monday: 9:45-10:45 AM (Zoom; Link TBD)
- Thursday: 2:45-3:45 PM (In-Person)
- Syllabus
- Official Course Textbook
- Lectures:
- Google Forms: (You must be signed in to your CofC account to access these forms.)
Announcements
- 8/5:
- The Syllabus Quiz will open on 8/21 at 12:01 AM and is due on 9/2 at 8 PM.
One function this assignment serves is to provide a low-stakes way to get set up with
LaTeX, as well as to ask questions about using LaTeX. Please note that during quizzes,
you may wish to include images in the PDF. It is worth figuring out how to do this
before you wish to do so in a timed environment.
- HW1 will open on 8/22 at 12:45 PM. It is due on 9/2 at 8 PM. This assignment is intended to be
doable in a week; the long deadline is intended to accommodate folks who add the class late.
- 4/4: Website created.


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By itself represents a fully associative cache. More...
#include <idealcache.H>
Public Member Functions | |
| IdealCache (uint32_t, uint32_t, uint32_t) | |
| ~IdealCache () | |
| Destructor : cleans up the cacheMap in case purge is not called. | |
| int32_t | access (memblock, uint64_t, uint32_t) |
| Probe set for requested memblock. | |
| void | print (void) |
| Print debug information. | |
| void | setAccessPattern (cacheBlock *, uint64_t, uint32_t) |
| Deprecated. | |
| void | updateAccessPattern (cacheBlock *, uint64_t, uint32_t) |
| Deprecated. | |
| void | purge (uint64_t) |
| Evict all items from the cache at the end of the simulation run. | |
| bool | isFullHit (uint64_t, uint32_t) |
| Checks for a full hit, i.e. requested access is present in a single cacheBlock in the set. | |
| cacheBlock * | isCollatedHit (memblock) |
| Checks for a collated hit. | |
| cacheBlock * | blockHit (uint64_t) |
| Get the block on Full Hit. | |
| int32_t | loadMemBlock (memblock, uint64_t, uint32_t) |
| Load requested memblock into IdealCache, i.e set. | |
| void | relocateToHead (cacheBlock *) |
| Relocates a cacheBlock to the top of the LRU Queue. | |
| void | pushIntoQueue (cacheBlock *) |
| Pushes a given block into the LRU Queue. | |
| void | processBlock (cacheBlock *) |
| Process a collated cacheBlock. | |
| cacheBlock * | collatePartial (memblock) |
| Collate a given memblock. | |
| void | deleteFromQueue (cacheBlock *) |
| Deletes a given block from the LRU Queue. | |
| bool | splitCacheBlock (cacheBlock *, uint64_t, uint32_t) |
| Split Cache Block if too large. | |
| map< uint64_t, cacheBlock * > ::iterator | lowerBound (uint64_t) |
| Custom lower bound function. | |
| bool | evict (cacheBlock *, uint64_t) |
| Evict a specific cacheBlock. | |
| bool | isFullMiss (memblock) |
| Checks for Full Miss. | |
| int32_t | calculateMissBW (cacheBlock *) |
| Calculate the number of words required to be brought in from lower level. | |
| cacheBlock * | getVictim (void) |
| Get the cacheBlock to evict. | |
| void | updateWordsInCache (cacheBlock *pNewBlock) |
| Increment the word count of the set. | |
| uint32_t | getCacheSize (void) |
| Returns the size of the cache in words. | |
| bool | isCacheEmpty (void) |
| Check if set is empty. | |
| uint32_t | getWordsInCache (void) |
| Get current word count. | |
| uint32_t | getBlockCount (void) |
| Get the number of blocks in the cache. | |
Public Attributes | |
| DataLogger | data |
| Statistics collector. | |
Private Attributes | |
| uint32_t | cacheSize |
| Size of the set in words. | |
| uint32_t | wordsInCache |
| Current used words. | |
| uint32_t | maxGran |
| Max size of a single cacheBlock; anything larger is split into multiple cacheBlocks. | |
| uint32_t | tagOverhead |
| Tag Overhead per block can be 0 or 1 (representing the number of words) depending on aligned or unaligned access. | |
| cacheBlock * | QHead |
| LRU Queue Head pointer. | |
| cacheBlock * | QTail |
| LRU Queue Tail pointer. | |
| map< uint64_t, cacheBlock * > | cacheMap |
| Cachemap for quick lookup of cacheBlocks. |
By itself represents a fully associative cache.
The IdealCache class by itself represents a fully associative cache. Many such objects can be made to simulate a set based cache model. Each IdealCache can operate in aligned mode or in flexible mode. In aligned mode it is only provided with fixed size blocks to load and work with from the CacheController and Predictor. This simulates a traditional cache memory system.
| IdealCache::IdealCache | ( | uint32_t | cS, | |
| uint32_t | mG, | |||
| uint32_t | tO | |||
| ) |
| cS | Set Size in words | |
| mG | Maximum Granularity of each cacheBlock |
| IdealCache::~IdealCache | ( | ) |
Destructor : cleans up the cacheMap in case purge is not called.
| int32_t IdealCache::access | ( | memblock | mb, | |
| uint64_t | effectiveAddress, | |||
| uint32_t | memoryAccessSize | |||
| ) |
Probe set for requested memblock.
When the access method of the set, i.e the IdealCache is called, it checks for one of the following scenarios with respect to the requested memblock:
| mb | Requested memblock | |
| effectiveAddress | Word aligned start address of actual load | |
| memoryAccessSize | Size of access in Bytes |
| cacheBlock * IdealCache::blockHit | ( | uint64_t | effectiveAddress | ) |
Get the block on Full Hit.
In the case of the full hit, this method is used to get a pointer to the block which wholly contains the requested access.
| effectiveAddress | Word aligned start address of the current access |
| int32_t IdealCache::calculateMissBW | ( | cacheBlock * | pNewBlock | ) |
Calculate the number of words required to be brought in from lower level.
This method calculates the number of words to be brought in from the lower level for each miss request. It is to be noted that the miss request can be a partial miss or a complete miss. We assume that it is possible for us to fetch non-contigous blocks for the lower level in a single request.
| pNewBlock | The cacheBlock being brought into the set |
| cacheBlock * IdealCache::collatePartial | ( | memblock | mb | ) |
Collate a given memblock.
Given a memblock, this method creates a new cacheBlock while absorbing existing overlapping cacheBlocks.
| mb | Requested memblock to collate into cacheBlock |
| void IdealCache::deleteFromQueue | ( | cacheBlock * | pOldBlock | ) |
Deletes a given block from the LRU Queue.
Given a pointer of a cacheBlock, this method removes the block from the LRU Queue and updates the other members of the queue. It also updates the words in cache counter and de-allocates the cacheBlock.
| pOldBlock | Pointer to cacheBlock to remove from LRU Queue and delete |
Deleting the only block from the LRU Queue
| bool IdealCache::evict | ( | cacheBlock * | pEvictBlock, | |
| uint64_t | insCount | |||
| ) |
Evict a specific cacheBlock.
This method evicts a specific cacheBlock from the set. The data collection methods are called before the contents are removed.
| pEvictBlock | The cacheBlock to be evicted | |
| insCount | The instruction count at the time of eviction |
| uint32_t IdealCache::getBlockCount | ( | void | ) | [inline] |
Get the number of blocks in the cache.
| uint32_t IdealCache::getCacheSize | ( | void | ) | [inline] |
Returns the size of the cache in words.
| cacheBlock* IdealCache::getVictim | ( | void | ) | [inline] |
Get the cacheBlock to evict.
| uint32_t IdealCache::getWordsInCache | ( | void | ) | [inline] |
Get current word count.
| bool IdealCache::isCacheEmpty | ( | void | ) | [inline] |
Check if set is empty.
| cacheBlock * IdealCache::isCollatedHit | ( | memblock | mb | ) |
Checks for a collated hit.
A collated hit occurs when all the words requested by the predictor (specified in the memblock) is present in the set, but are not present in a single cacheBlock. This method checks for a collated hit and if it finds such a case, collates teh blocks and returns a pointer to the new collated block
| mb | Requested memblock |
| bool IdealCache::isFullHit | ( | uint64_t | effectiveAddress, | |
| uint32_t | memoryAccessSize | |||
| ) |
Checks for a full hit, i.e. requested access is present in a single cacheBlock in the set.
| effectiveAddress | Word aligned start address of the current access | |
| memoryAccessSize | Memory access size in Bytes |
| bool IdealCache::isFullMiss | ( | memblock | mb | ) |
Checks for Full Miss.
Checks whether a Full Miss occurs for the given memblock; i.e none of the words in the memblock are present in the cache
| mb | The memblock to be checked |
| int32_t IdealCache::loadMemBlock | ( | memblock | mb, | |
| uint64_t | effectiveAddress, | |||
| uint32_t | memoryAccessSize | |||
| ) |
Load requested memblock into IdealCache, i.e set.
This method is called whenever one of the following occurs:
| mb | Requested memblock | |
| effectiveAddress | Word aligned start address of access | |
| memoryAccessSize | Size of the memory access in Bytes |
| map< uint64_t, cacheBlock * >::iterator IdealCache::lowerBound | ( | uint64_t | addr | ) |
Custom lower bound function.
A custom lower bound function for maps indexed with the start address of the cacheBlocks
| addr | The addr to find teh lower bound of |
| void IdealCache::print | ( | void | ) |
Print debug information.
Prints out the contents of the LRU Queue of this set
| void IdealCache::processBlock | ( | cacheBlock * | collateBlock | ) |
Process a collated cacheBlock.
Once the bounds of the new cacheBlock have been determined by collatePartial and the cacheBlock is allocated, this method absorbs the overlapping blocks into the collated block by:
| collateBlock | Pointer to cacheBlock which is to be processed |
| void IdealCache::purge | ( | uint64_t | insCount | ) |
Evict all items from the cache at the end of the simulation run.
| insCount | Latest instruction seen by the set / cachecontroller |
| void IdealCache::pushIntoQueue | ( | cacheBlock * | pLoadBlock | ) |
Pushes a given block into the LRU Queue.
This method pushes a given cacheBlock into the top of the LRU Queue and also updates the words in the cache counter value.
| pLoadBlock | Pointer to cacheBlock to be pushed into the LRU Queue |
| void IdealCache::relocateToHead | ( | cacheBlock * | relocateBlock | ) |
Relocates a cacheBlock to the top of the LRU Queue.
| relocateBlock | Pointer to the cacheBlock to relocate |
| void IdealCache::setAccessPattern | ( | cacheBlock * | pNewBlock, | |
| uint64_t | effectiveAddress, | |||
| uint32_t | memoryAccessSize | |||
| ) |
Deprecated.
| bool IdealCache::splitCacheBlock | ( | cacheBlock * | pBlock, | |
| uint64_t | effectiveAddress, | |||
| uint32_t | size | |||
| ) |
Split Cache Block if too large.
The cacheBlock is checked to see if it needs to be split into smaller blocks. It needs to be split if it is greater than the maximum granularity set by the command line argument to the idealsim simulator. The split blocks are the pushed back into the queue in proper order.
| pBlock | Pointer to cacheBlock to be split | |
| effectiveAddress | Word aligned start address of the current access | |
| size | The maximum allowed granularity / size of a cacheBlock |
1. break it into pieces - store in vector 2. if effectiveAddress in range push_back else insert forward 3. delete original block from queue and cachemap 4. insert chunks into queue and cachemap
| void IdealCache::updateAccessPattern | ( | cacheBlock * | pNewBlock, | |
| uint64_t | effectiveAddress, | |||
| uint32_t | memoryAccessSize | |||
| ) |
Deprecated.
| void IdealCache::updateWordsInCache | ( | cacheBlock * | pNewBlock | ) | [inline] |
Increment the word count of the set.
| pNewBlock | The block being inserted into the set |
map< uint64_t, cacheBlock* > IdealCache::cacheMap [private] |
Cachemap for quick lookup of cacheBlocks.
uint32_t IdealCache::cacheSize [private] |
Size of the set in words.
Statistics collector.
uint32_t IdealCache::maxGran [private] |
Max size of a single cacheBlock; anything larger is split into multiple cacheBlocks.
cacheBlock* IdealCache::QHead [private] |
LRU Queue Head pointer.
cacheBlock* IdealCache::QTail [private] |
LRU Queue Tail pointer.
uint32_t IdealCache::tagOverhead [private] |
Tag Overhead per block can be 0 or 1 (representing the number of words) depending on aligned or unaligned access.
uint32_t IdealCache::wordsInCache [private] |
Current used words.


|
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"Feliz Navidad !!!!" ?Posted by devon on Tuesday, December 24, 2002
Merry Christmas everybody, I am just about to head out to do all the last minute schminaegle. To all my family back in inglaterra, I wish you a very happy christmas, and I hope you all enjoy the good food that I will be missing. To mother, I book my flight today for the 6th, I will be in manchester on the 7th. To John, Margot and the littleuns, have a great christmas with everybody, Gran, Gramps, doug, dermicheal, everybody have a merry christmas. I shall see you all soon, As I am coming out there for a couple months to work and make some pounds to take back here before I leave. Be ready for me!!!!. Thanks for the card Gran!. Merry christmas!
|


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Kyle Schwarber Interview
Podcast Episode 6.23"
author:
display_name: Corey Fineran
login: Corey
email<EMAIL_ADDRESS>url: ''
author_login: Corey
author_email<EMAIL_ADDRESS>wordpress_id: 10235
wordpress_url: http://ivyenvy.com/?p=10235
date: '2014-07-15 11:18:01 +0000'
date_gmt: '2014-07-15 16:18:01 +0000'
categories:
- Minor Leagues
- Podcast
- Prospects
- Interview
tags:
- Daytona
- Kane County
- Boise Hawks
- Kyle Schwarber
- Cubs 2014 draft
comments:
- id: 11966
author: Jason Mollett
author_email: ''
author_url: ''
date: '2014-07-15 12:00:28 +0000'
date_gmt: '2014-07-15 17:00:28 +0000'
content: So, Meet Up in Daytona this weekend?
- id: 11967
author: Ivy Envy
author_email: ''
author_url: ''
date: '2014-07-15 12:10:23 +0000'
date_gmt: '2014-07-15 17:10:23 +0000'
content: Well, Andy IS in Florida right now.
- id: 11988
author: Aamir Bhojani
author_email: ''
author_url: ''
date: '2014-07-16 10:28:49 +0000'
date_gmt: '2014-07-16 15:28:49 +0000'
content: Arif Rahim
- id: 12040
author: '"Hey Girls! I'm Not Messing Around!" - Podcast Episode 6.24 - Ivy
Envy Podcast'
author_email: ''
author_url: http://ivyenvy.com/hey-girls-im-messing-around-podcast-episode-6-24/
date: '2014-07-21 23:27:30 +0000'
date_gmt: '2014-07-22 04:27:30 +0000'
content: "[…] If you’d like to hear our interview with Cubs 2014 1st
round pick Kyle Schwarber, listen here: Kyle Schwarber Interview […]"
---
We have a bonus episode of the podcast for you this week. Kyle Schwarber was the Cubs 1st round selection (4th overall) in the 2014 MLB Draft. I had the opportunity speak with Schwarber last week when the Kane County Cougars visited the Quad Cities River Bandits.
Schwarber has since been promoted to High-A Daytona. Considered the best college bat in the draft, he quickly demonstrated that he was prepared for competition greater than he faced with Boise and Kane County.
In the interview, Schwarber talks about his draft day experience, a possible future position change and how it feels to be part of this young and exciting Cubs system.
If you enjoy this podcast, check out the other prospect interviews we've done:
Javier Baez
Albert Almora
Dan Vogelbach
If this is the first episode of our podcast that you've heard, we put out weekly episodes. This is our 6th of podcasting on the Chicago Cubs. In addition to being available on our website, you can listen to our episode in iTunes, Stitcher and any podcast app.


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--- layout: page title: About Us background: '/assets/images/about.jpeg' ---
SmartCow is an AI engineering company that develops affordable video analytics applications
We enable you to extract accurate, real-time insights from your security and service-related monitoring systems - regardless of whether they have 10 or 1000 cameras.


--- layout: post title: An important milestone in space travel date: 2010-06-05 11:15:25.000000000 +05:30 categories: - random - tech tags: - elonmusk - falcon9 - spacex status: publish type: post published: true meta: _edit_last: '1' author: login: admin email<EMAIL_ADDRESS>display_name: admin first_name: '' last_name: '' ---
[caption id="" align="alignright" width="215" caption="Falcon 9 Maiden launch"][/caption]
About a couple years ago, in an argument on space and science, I took the position that the government should invest more in science, and space travel. I lost the debate.. the government has no business using public funds for endeavours like these, and that it's only true calling should be maintaining liberty. Everything else would follow.
I've since watched the evolution of SpaceX, through it's many failures, rallied on by it's gritty founder and chief Elon Musk.
“We're not going to cut and run if we have a few issues. We're not going to cut and run if we have a lot of issues. We're going to see this through.”
Elon's been called "a Renaissance man in an era that needs them.". Read a very-well written profile of him at GQ.
Yesterday, SpaceX successfully launched it's indigenously built Falcon 9 into orbit.
Congratulations, Elon Musk. Many more successes to you.


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OpenM++ compiler (omc)
ModelSymbol.cpp File Reference
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ModelSymbol.cpp
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--- title: ARC members: Kevin Jalbert, Jeremy S. Bradbury links: http://kevinjalbert.com, http://faculty.uoit.ca/bradbury url: http://faculty.uoit.ca/bradbury/sqrg/projects/directed_search.html description: This research project focuses on the development of a new approach that automatically repairs concurrency bugs using genetic algorithms. ---
The goal of ARC - Automatically Repair Concurrency is to provide a tool that attempts to repair concurrency bugs in source code. This tool is aimed towards Java due to its maturity in concurrency and known concurrency bugs and idioms.
A genetic algorithm is used to progressively mutate the buggy program's source code to a state where it executes in a timely fashion without errors. The mutations used are all related to adding and removing synchronization to the source code. The mutations used can only effect the thread schedules, and as a side-effect the performance overhead/reduction of added/removed synchronization. Two main criteria used in determining the fitness of a mutant are the:
Essentially the end purpose is to automatically repair concurrency by minimizing the bugs and maximizing the performance.


{% extends 'base_error.html' %} {% block headerone %}
You might have typed in the wrong URL or don't have privileges to view this file.


Copyright Bruce Wilcox<EMAIL_ADDRESS>www.brilligunderstanding.com
Revision 10/16/2022 cs12.3
User variables $xxx
and $$xxx
are all
global in scope.
Anyone can access them to get or set them.
But if you want to write safe code, you also want local variables
that no one can access and ruin on you. $_xxx
are local
variables.
When you use them inside an outputmacro or a topic, they only have meaning and access inside that code. No other code can see them. They can use the same variable name, and get their own local instance.
Local variables always start out initialized to null. If you pass them to an outputmacro, unlike normal variables which are passed by reference (hence can be written upon if you use Indirection Variables below), local variables are passed by value. Their content is passed, so no one can touch the variable itself.
Local variables used in a topic all remain accessible while in that
topic. If you do ^gambit(~topic)
and then inside you do
^gambit(~)
or ^reuse(MYLABEL)
, you have not
left the topic and so the variables remain intact. But if you call
outside the topic, then a deeper call to the original topic sees new
variables (just as a recursive call to an outputmacro would).
Hence ^gambit(~mytopic)
which calls
^reuse(~histopic.label)
which then calls
^gambit(~mytopic)
will get two different instances of
~mytopic
and the variables separately handled by each.
By definition, local variables are transient and do not get saved in a user’s topic file.
You can, of course, merely refer to a variable in a script to set or get its value. But suppose you wanted to associate a variable with every topic you have.
Maybe when the user says I’m bored you want to leave a topic
and not reopen it yourself for any near future (say 200 volleys).
In that case, you don’t have a variable but you need to create one
dynamically.
$$topicname = substitute(character %topic ~ "")
The above gives you a topic name without the ~
. Pretend
the current topic is ~washing
. Then you can create a
dynamic variable name simply by using
$$tmp = ^join($ $$topicname)
which would create the name $washing.
Now suppose you wanted to set that variable to some number representing the turn after which you might return.
$$tmp = 25
doesn’t work. It wipes out the $washing
value of `$$tmpand replaces it with
25`.
You can set indirectly through $$tmp
using function
notation ^$$tmp
The above says take the value of
$$tmp
, treat it as the name of a variable, and assign into
it. Which means it does the equivalent of
$washing = 25
If you want to an indirect value back, you can’t do:
$$val = $$tmp
because that just passes the name of $washing
over to
$$val
. Instead you do indirection again:
$$val = ^$$tmp # $$val becomes 25
Indirection works with values that are user variables and with values that are match variables or quoted match variables.
Many routines automatically evaluate a variable when using it as an
argument, like ^gambit($$tmp)
. But if you want the value of
the variable it represents, then you need to evaluate it another
time.
$$tmp1 = ^$$tmp
^gambit($$tmp1)
Equivalently ^gambit(^$$tmp1)
is legal.
Similarly, ^eval evaluates its argument, but if its argument is a variable whose value is the name of a variable, you just get back that name. If you want the value of that, you need to indirect again:
$nox = 1
$$tmp = join($ no x)
$$val = eval($$tmp) # returns $nox the name, not the value 1
$$val = eval(^$$tmp) # returns the value of the name content in $$tmp, i.e. 1
See also Indirect Pattern Elements in ChatScript Pattern Redux manual.
You can create a variable which is a function name, then make a call using it. It can only do runtime testing on the number of arguments you supply to the actual call.
$_fn = ^join( ^testing _ en_us)
$_text = ^$_fn($_tmp)
You can also define variables that are “owned” by the server. Any variables you create as part of layer 0 or layer 1 are always resident. As are any variables you define on the command line starting ChatScript or in cs_init.txt or cs_initmore.txt You can see them and even change them during a volley, but they will always refresh back to their original values at the start of the next volley.
Match variables like _5
are generally the result of
using an underscore in a pattern match. Match variables hold 3 pieces of
data
You can transfer part of Assigning match variables to user variables:
$$stuff = _0
but user variables only have a single piece of data. So on assignment you lose 2 of the 3 pieces from the match variable. You can choose which words (original or canonical) when you assign.
$$stuff = '_0 # original words
You can store positional data onto a different variable using
^position(start _0)
or
^position(end _0).
_0 = $$stuff
When you assign onto a match variable from a user variable, you make both original and canonical values of the match variable the same, and the positional data is set to 0.
_0 = _10
This is a transfer from one match variable to another, so no data is lost.
One unusual property of match variables is that they are not cleared between volleys. This makes them the ONLY way you can pass data between volleys on a server where different users are involved.
Note: Match variables have a 20,000 character limit.
If a variable holds a JSON object value, you can directly set and get from fields of that object using dotted notation.
This can be a fixed static fieldname or a variable value-
$myvar.$myfield
is legal.
Dotted notation is cleaner and faster than ^jsonpath
and
jsonobjectinsert
and for get, has the advantage that it
never fails, it only returns null if it can’t find the field. On the
other hand, assignment fails if the path does not contain a json object
at some level.
$x = $$$obj.name.value.data.side
$$$obj.name.value.data.side = 7
Assigning null
will remove a JSON key entirely.
Assigning ""
^""
will set the field to the
JSON literal null
.
If $$f
holds a fact id, then
$$f.subject
$$f.verb
$$f.object
will return those components. You may NOT, however, assign into them.


I hang around people who talk about
security and privacy and activists
quite a bit. When talking security
beyond the typical attackers —
people committing identity theft,
simple vandals, spammers, etc.
— there’s the topic of
government surveillance and legal
attacks, and privacy as a way to
defend political activists against
the powers-that-be. I want to talk
about this security question in
particular.
(Nothing I say here relates to China
or Iran or other places with overtly
oppressive political systems and
without basic legal rights. I
don’t think worth trying to
generalize that far.)
I’m not sure we are getting
this stuff right. I don’t
think the political attacks that are
imagined are serious risks, and the
attacks that are taking place are
far less sophisticated than we
imagine.
Background
I’m taking these lessons
primarily from the experiences
of my sister, who
along with 7 others
is currently facing felony
conspiracy charges in Minnesota
(felony conspiracy to riot with
a dangerous weapon and to commit
property damage). These charges
are specifically for organizing
protests in the lead up to the
2008 RNC convention
in St. Paul. It’s only one
data point, but in these matters
there’s only a handful of
cases that inform the
discussion.
The city of St. Paul and other
local governments received over
$50 million for security for the
RNC, and some of that money was
quickly put into hiring
informants to infiltrate
organizations,
anarchist
organizations in particular. My
sister among others were part of
an organization known as the
RNC Welcoming Committee. In total three informants
were highly involved in the
organization, each of them
attending literally hundreds of
hours of meetings. The Committee
primarily worked on things like
promoting the protests against
the RNC, acquiring meeting space
and internet access for people,
finding housing and food for
people visiting for the
protests, and distributing
logistical information like
where protests would occur.
"Anarchism" means
"without rulers": in
line with their anarchist
principles they didn’t try
to prescribe how people would
protest, they felt people should
make their own choices about how
to protest. The choices people
made were widespread, ranging
from staying in a "free
speech zone" to a few
permitted marches, some
unpermitted marches, some civil
disobedience, some blockading,
and in a very small number of
cases some people committed
property damage. The Welcoming
Committee did not advocate any
particular kind of protest, they
would not be their
brother’s keeper, nor did
they want to disparage any kind
of protest as too timid. Each
person should act on their own
conscience.
Immediately before the RNC
started the 8 were arrested and
held for the duration of the
convention before being charged
and released on bail. Their
houses and cars were searched.
Nothing interesting was found,
though at the time the Sheriff
misrepresented things like bike
inner tubes as possible
slingshot material, or that
having paint thinner in the
basement, rags in the laundry,
and empty bottles in the pantry
constituted Molotov cocktail
ingredients.
The Evidence
The case has progressed very
slowly, but with
recent
hearings
more of the prosecution’s
case has been coming out.
It’s been over a year and
a half and only now are we
getting any indication of what
the real claims are
against the defendants, though
the prosecution continues to
avoid presenting any real case
or plausible complaint.
From the hearings we’re
also learning something about
the form of the investigation.
The FBI was closely involved
with the case and recruited the
most active informant, and the
primary investigator was
previously with the Secret
Service (which
somewhat oddly has a
computer-related duties), and at the time there was a
great deal of national attention
on the convention. So presumably
they had the resources to
investigate seriously if they
wished to do so.
From the perspective of online
security the case is very
boring. The defendants have been
given all the evidence collected
during the investigation
(including benign or even
helpful evidence). It’s a
huge amount of evidence, and
hard for them to understand or
sort through, but some kinds of
investigation aren’t
there. No email accounts were
subpoenaed. Their computers were
all confiscated, and will no
doubt be kept until after the
trial, but there’s nothing
high-tech about that. Some of
them had whole-disk encryption,
and there is no indication it
was broken nor were they even
asked to provide passwords.
There’s also no evidence
of sniffing internet
connections, tapping phones,
breaking into email…
nothing fancy was done.
From what we can tell the
evidence against them will be
primarily from informants’
testimony about open meetings,
widely distributed literature,
a video posted on
YouTube, a password-protected but
essentially open wiki (the wiki
provider was not subpoenaed,
despite things like edit history
being potentially interesting).
If they had been any more
security-conscious it would have
worked against them — it
would have been out of line with
their ideals and would have made
them less effective and
transparent in their organizing
efforts. The biggest danger now
is that they’ll be
demonized, that they’ll be
judged based on caricatures of
their actual beliefs, privacy
only makes this worse.
Credit Where Credit Is Due
Perhaps one reason the
surveillance was low-tech and
subpoenaed evidence is not
playing a large part in the case
is that it’s
just too hard. They
used
Riseup
for many services, which is a
set of online services for
activists, who take privacy very
seriously, log as little as
possible, and try to host
everything outside of the
country so regardless of an
activists locality it will be a
bureaucratic challenge to get
access to the servers.
Outside of the core group most
people acted anonymously, so the
prosecution would not be able to
follow up on most of what they
found anyway. Even if they got
all the logs and email from
everything the Welcoming
Committee touched, I’m not
sure they could make use of it.
If they could somehow relate all
that anonymous information,
they’d still have to
explain those
techniques and convince a jury.
Data mining and other
data-driven techniques could be
useful if they were trying to
attach people
who had done anything
wrong. You can use surveillance to
find the smoking gun, and once
you’ve found it you
don’t have to justify the
techniques you used in the
process. But only if
there’s a smoking gun.
It’s a peculiar situation
where the prosecution
doesn’t appear to actually
believe they did anything
demonstrably wrong; I fear they
plan a case where they redefine
"wrong".
Privacy
Besides the security issue
there’s the privacy issue,
and privacy is big on the
internet these last few months.
One of the oft-claimed benefits
of privacy is to allow political
dissent. And maybe that makes
sense in China, but I
don’t know how it relates
to the things in the U.S. or
Europe.
Political beliefs held in
private don’t much matter.
Complaining about politics in
private situations is fine,
because it just
doesn’t matter. So sure, you are safe from
political persecution if your
privacy is maintained… but
it’s because you are
impotent not because
privacy is some part of a
political struggle.
This reminds me of a playground
sense of privacy. On the
playground you might say you
like They Might Be Giants and
the playground bully says
that’s so gay,
and you think
I shouldn’t have said
anything. But it doesn’t really
matter how much you reveal in
that situation, it doesn’t
matter what you say you like
— the bully isn’t
making a pointed critique on
your preferences, they are just
trying to hurt you. The only way
privacy will help you is if you
are so quiet that the
bully doesn’t notice you
at all and picks on someone else
instead.
Ramsey County (where the RNC 8
are being charged) is a bully.
They decided before the
Welcoming Committee even existed
that people were going to be
arrested, charges were going to
be made. The Welcoming Committee
stuck their necks out further
than anyone else.
 They have to spend their
evenings reading through
evidence or listening to the
tapes of their meetings (which
were boring enough to listen to
the first time around).
There’s a certain stigma
to having pending felony
charges, I know at least my
sister has lost a job because of
it. And they each have to have
their own lawyer, and even
though the lawyers aren’t
charging them what would be the
full rate it’s still a lot
of money (like a quarter of a
million dollars). Depressingly,
in some sense this is all the
government has to do; the trial
is punishment enough to deter
people from being activist
organizers.
So I wish a
donation
was equivalent to Sticking It To
The Man, but really it’s
just adding some balance because
The Man Is Already Sticking It
To Them On Your Behalf.
Still,
your support would be
really helpful.
If it gives you any satisfaction
County Attorney Susan
Gaertner’s run for the
Democratic gubernatorial
nomination never went anywhere,
I suspect in large part because
she wasn’t brave enough to
show her face at public events
in the Twin Cities because she
was consistently protested over
this case. I doubt this has
influenced the prosecution (at
least in any positive way), but
it’s satisfying.


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@* * Copyright 2019 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 forms.{Field, Form2} @import utils.HtmlElementHelpers.AttrMinMax @( f: Form2[_], p: String = "", labelText: String = "", hintText: String = "", example: Boolean = true, hintId: String = "", jsHidden: Boolean = false, legendHidden: Boolean = false, heading: String = "", section: String = "" )(implicit lang:Lang, m: Messages) @field = @{ f(p) } @fieldsetContent = { @if(section.nonEmpty) {
This section is: @Messages(section)


Hi {name},
We appeciate you helping our team during piloting.
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Racine confronts vulnerability and insecurity on new LP for Danse Noire
by Henry Bruce-JonesPhoto by: Press
Listen to a new track, ‘Quelque Chose Tombe II’, now.
Next up on Aïsha Devi’s Danse Noire imprint is a new project from Racine.
Drawing on themes of vulnerability and insecurity that are symptomatic of modern living, Quelque Chose Tombe is a collection of nine electronic compositions and features contributions from Enchanted Lands and Keru Not Ever. In the words of Danse Noire: “the music is both a grotesque dance of the goblins and the gentle opiatic breath of the protectors.”
The label has also recently released a new EP from Russian duo Narcissi, which sees the two producers using knackered Soviet and Japanese synths, guitar pedals, cheap drum machines and samplers loaded to interpret old Slavic and Russian folk songs and Cossack spiritual traditions.
Quelque Chose Tombe arrives on February 21, 2020, via Danse Noire. Check out the cover art and tracklist below.
Tracklist:
01. ‘Quelque Chose Tombe I’
02. ‘Quelque Chose Tombe II’
03. ‘Sujet’
04. ‘Désordre Baroque’
05. ‘Nérol’
06. ‘Sans Titre’ (feat. Enchanted Lands & Keru Not Ever)
07. ‘Sujet Perdu’
08. ‘Geranium’
09. ‘Sans Titre’ (feat. Keru Not Ever)
Read next: 7 must-hear mixes from October 2019
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{{define "body"}}
Copy contacts from a character, corporation or alliance to a character. Useful for copying between entities. CCP currently does not allow us to set corporation and alliance contacts.
To use this tool, add characters on the account page with Character Contact and Corp Role permissions. You can then copy contacts around in bulk.


Class InputConfig (v2.2.2)
The desired input location and metadata.
Generated from protobuf message google.cloud.vision.v1.InputConfig
Methods
__construct
Constructor.
| Name | Description |
| data |
array
Optional. Data for populating the Message object. |
| ↳ gcs_source |
Google\Cloud\Vision\V1\GcsSource
The Google Cloud Storage location to read the input from. |
| ↳ content |
string
File content, represented as a stream of bytes. Note: As with all |
| ↳ mime_type |
string
The type of the file. Currently only "application/pdf", "image/tiff" and "image/gif" are supported. Wildcards are not supported. |
getGcsSource
The Google Cloud Storage location to read the input from.
Generated from protobuf field .google.cloud.vision.v1.GcsSource gcs_source = 1;
| Type | Description |
| Google\Cloud\Vision\V1\GcsSource|null |
hasGcsSource
clearGcsSource
setGcsSource
The Google Cloud Storage location to read the input from.
Generated from protobuf field .google.cloud.vision.v1.GcsSource gcs_source = 1;
| Name | Description |
| var |
Google\Cloud\Vision\V1\GcsSource
|
| Type | Description |
| $this |
getContent
File content, represented as a stream of bytes.
Note: As with all bytes
fields, protobuffers use a pure binary
representation, whereas JSON representations use base64.
Currently, this field only works for BatchAnnotateFiles requests. It does
not work for AsyncBatchAnnotateFiles requests.
Generated from protobuf field bytes content = 3;
| Type | Description |
| string |
setContent
File content, represented as a stream of bytes.
Note: As with all bytes
fields, protobuffers use a pure binary
representation, whereas JSON representations use base64.
Currently, this field only works for BatchAnnotateFiles requests. It does
not work for AsyncBatchAnnotateFiles requests.
Generated from protobuf field bytes content = 3;
| Name | Description |
| var |
string
|
| Type | Description |
| $this |
getMimeType
The type of the file. Currently only "application/pdf", "image/tiff" and "image/gif" are supported. Wildcards are not supported.
Generated from protobuf field string mime_type = 2;
| Type | Description |
| string |
setMimeType
The type of the file. Currently only "application/pdf", "image/tiff" and "image/gif" are supported. Wildcards are not supported.
Generated from protobuf field string mime_type = 2;
| Name | Description |
| var |
string
|
| Type | Description |
| $this |


[% " Consider trying the \"netalyzr\". This is another site that runs a java applet (which can do more than my site can, in just javascript). I would find feedback about how you useful this site was for you. " | i18n %] [% " From the netalyzr staff: " | i18n %]
Netalyzr is a free network debugging and diagnostic service written by researchers at the International Computer Science Institute in Berkeley. This tool runs from within your Java-enabled web browser. It automatically detects many conditions which might cause problems with IPv6 connectivity, including creating a list of all IP addresses, discovering IPv6 addresses that don't work, detecting IPv6 rogue gateways, and a host of other network problems.


{{> head}}
{{> map_script}}
{{> nav}}
Show pickups from:
Today
(Zoomed in on your neighborhood?
Set this map as your default
.)
{{> footer}}


Safari IT Books Language Constructs Functional Programming Haskell Safari IT Books Programming Programming Programming Bryan O'Sullivan Donald Bruce Stewart John Goerzen O'Reilly Media, Inc. Real World Haskell, 1st Edition13.2. MapsThe Data.Map
module provides a Map type with behavior that is
similar to association lists but has much better performance. Maps give us the same capabilities as hash tables do in other languages. Internally, a map is
implemented as a balanced binary tree. Compared to a hash table, this is a
much more efficient representation in a language with immutable data. This
is the most visible example of how deeply pure functional programming
affects how we write code: we choose data structures and algorithms that
we can express cleanly and that perform efficiently, but our choices for
specific tasks are often different from their counterparts in imperative
languages. Some functions in the Data.Map module have
the same names as those in the Prelude. Therefore, we
will import it with import qualified Data.Map as
Map and use Map.name to refer to
names in that module. Let's start our tour of Data.Map by taking a look at some ways to build
a map: -- file: ch13/buildmap.hs
import qualified Data.Map as Map
-- Functions to generate a Map that represents an association list
-- as a map
al = [(1, "one"), (2, "two"), (3, "three"), (4, "four")]
{- | Create a map representation of 'al' by converting the association
- list using Map.fromList -}
mapFromAL =
Map.fromList al
{- | Create a map representation of 'al' by doing a fold -}
mapFold =
foldl (\map (k, v) -> Map.insert k v map) Map.empty al
{- | Manually create a map with the elements of 'al' in it -}
mapManual =
Map.insert 2 "two" .
Map.insert 4 "four" .
Map.insert 1 "one" .
Map.insert 3 "three" $ Map.empty
Functions such as Map.insert work in the usual Haskell way: they return a copy of the input
data, with the requested change applied. This is quite handy with maps. It
means that you can use foldl to build
up a map as in the mapFold example. Or,
you can chain together calls to Map.insert as in the mapManual example. Let's use ghci to verify that all of these maps are as
expected: ghci> :l buildmap.hs
[1 of 1] Compiling Main ( buildmap.hs, interpreted )
Ok, modules loaded: Main.
ghci> al
Loading package array-<IP_ADDRESS> ... linking ... done.
Loading package containers-<IP_ADDRESS> ... linking ... done.
[(1,"one"),(2,"two"),(3,"three"),(4,"four")]
ghci> mapFromAL
fromList [(1,"one"),(2,"two"),(3,"three"),(4,"four")]
ghci> mapFold
fromList [(1,"one"),(2,"two"),(3,"three"),(4,"four")]
ghci> mapManual
fromList [(1,"one"),(2,"two"),(3,"three"),(4,"four")] Notice that the output from mapManual differs from the order of the list we
used to construct the map. Maps do not guarantee that they will preserve
the original ordering. Maps operate similarly in concept to association lists.
The Data.Map module provides functions
for adding and removing data from maps. It also lets us filter them,
modify them, fold over them, and convert to and from association lists.
The library documentation for this module is good, so instead of going
into detail on each function, we will present an example that ties
together many of the concepts we've discussed in this chapter.
|