search for: sum2

...help files or books. So I created a simplified version of what I'm doing: rm( list=ls() ) x1<-c(1,3,3) x2<-c(3,2,1) x3<-c(2,5,2) x4<-c(5,6,9) myDF<-data.frame(x1,x2,x3,x4) rm(x1,x2,x3,x4) ls() myDF This creates two new variables just fine" transform(myDF, sum1=x1+x2, sum2=x3+x4 ) This next code does not see sum1, so it appears that "transform" cannot see the variables that it creates. Would I need to transform new variables in a second pass? transform(myDF, sum1=x1+x2, sum2=x3+x4, total=sum1+sum2 ) Next I'm trying the same thing using "wi...

I am having the following error in my function function(theta,reqdIRR) { theta1<-theta[1] theta2<-theta[2] n<-length(reqdIRR) constant<- n*(theta1+theta2) sum1<-lapply(reqdIRR*exp(theta1),FUN = sum) sum2<-lapply(exp(theta2 - reqdIRR*exp(theta1)),FUN = sum) sum = sum1 + sum2 log.fcn = constant - as.numeric(sum) result = - log.fcn return(result) } *error : neg.log.gumbel(1,reqdIRR) Error in sum1 + sum2 : non-numeric argument to binary operator > how can i rectify the error?Its really urgent....

...test statistic which involves double sums of max(X_i,Y_j) where X and Y are vectors of differing length. I am currently using ifelse pointwise in a vector, but have a nagging suspicion that there is a more efficient way to do this. Basically, I require three sums: sum1: \sum_i\sum_j max(X_i,X_j) sum2: \sum_i\sum_j max(Y_i,Y_j) sum3: \sum_i\sum_j max(X_i,Y_j) Here is my current implementation - any pointers to more efficient computation greatly appreciated. nx <- length(x) ny <- length(y) sum1 <- 0 sum3 <- 0 for(i in 1:nx) { sum1 <- sum1 + sum(ifelse(x[i]>...

The attached patch eliminates some warnings while compiling for ARM4 targets. It also simplifies the asm constraints a bit. Now we can use the ARM4 optimisations when compiling for PortalPlayer targets in Rockbox. Cheers, Dan -------------- next part -------------- A non-text attachment was scrubbed... Name: speex_arm4.patch Type: text/x-diff Size: 1550 bytes Desc: not available Url :

...dating that transmission in the new (read|write)_sum_head functions. A added bonus is that write_sum_head replaces the send_null_sums function. The Adleresque checksum1 is in no way affected. The varsumlen patch builds on that groundwork by implementing a simple heuristic to generate the per-file sum2 lengths. It remains two bytes until the file is 8193 blocks at which it increments and continues incrementing each time the block count quadruples. This builds on the dynamic block size code (which is consolidated as well) so that the point where we go to a 3 byte sum2 is approximately 125MB. Sp...

...m, (__m128d) _mm_movehl_ps((__m128) sum, (__m128) sum)); + sum = _mm_add_sd(sum, _mm_unpackhi_pd(sum, sum)); _mm_store_sd(&ret, sum); return ret; } @@ -120,7 +120,7 @@ static inline double interpolate_product_double(const float *a, const float *b, sum1 = _mm_mul_pd(f1, sum1); sum2 = _mm_mul_pd(f2, sum2); sum = _mm_add_pd(sum1, sum2); - sum = _mm_add_sd(sum, (__m128d) _mm_movehl_ps((__m128) sum, (__m128) sum)); + sum = _mm_add_sd(sum, _mm_unpackhi_pd(sum, sum)); _mm_store_sd(&ret, sum); return ret; }

...ple, but the above benchmarking disagree. It looks like there is a big overhead keeping track of the sum `s` being NA, which is supported by the fact that summing over 'z' is costs half of 'y'. Now, I *cannot* reproduce the above using the following 'inline' example: > sum2 <- inline::cfunction(sig=c(x="double", narm="logical"), body=' double *x_ = REAL(x); int narm_ = asLogical(narm); int n = length(x); double sum = 0; for (R_xlen_t i = 0; i < n; i++) { if (!narm_ || !ISNAN(x_[i])) sum += x_[i]; } return ScalarReal(sum); ')...

...er versions: the onus is on @@ -406,7 +406,8 @@ OFF_T flength; /**< total file length */ size_t count; /**< how many chunks */ size_t remainder; /**< flength % block_length */ - size_t n; /**< block_length */ + size_t blength; /**< block_length */ + size_t s2length; /**< sum2_length */ struct sum_buf *sums; /**< points to info for each chunk */ }; --- proto.h Sat Mar 29 12:18:02 2003 +++ proto.h Sat Mar 29 12:15:38 2003 @@ -91,6 +91,7 @@ struct file_list *flist_new(void); void flist_free(struct file_list *flist); char *f_name(struct file_struct *f); +void w...

The following series adds initial vector support for PowerPC64. On POWER9, flac --best is about 3.3x faster. Amitay Isaacs (2): Add m4 macro to check for C __attribute__ features Check if compiler supports target attribute on ppc64 Anton Blanchard (5): configure.ac: Remove SPE detection code configure.ac: Add VSX enable/disable configure.ac: Fix FLAC__CPU_PPC on little endian, and add

Just following up on this old thread since matrixStats 0.53.0 is now out, which supports this use case: > x <- rep(TRUE, times = 2^31) > y <- sum(x) > y [1] NA Warning message: In sum(x) : integer overflow - use sum(as.numeric(.)) > y <- matrixStats::sum2(x, mode = "double") > y [1] 2147483648 > str(y) num 2.15e+09 No coercion is taking place, so the memory overhead is zero: > profmem::profmem(y <- matrixStats::sum2(x, mode = "double")) Rprofmem memory profiling of: y <- matrixStats::sum2(x, mode = "double&...

...ar2 == mycombos$Var4),] mycombos<-mycombos[!(mycombos$Var3 == mycombos$Var4),] dim(mycombos) # I want to write sums of elements from values1, values2, and values 3 whose numbers are contained in each column of mycombos. Here is how I am going it now - using a loop: mycombos$sum1<-NA mycombos$sum2<-NA mycombos$sum3<-NA for(i in 1:nrow(mycombos)){ mycombos$sum1[i]<-values1[[mycombos[i,"Var1"]]] + values1[[mycombos[i,"Var2"]]] + values1[[mycombos[i,"Var3"]]] + values1[[mycombos[i,"Var4"]]] mycombos$sum2[i]<-values2[[mycombos[i,"Var1&...

...int len, const spx_uint32_t oversample, float *frac) { +static inline void interpolate_product_double(double *ret, const float *a, const float *b, unsigned int len, const spx_uint32_t oversample, float *frac) { int i; - double ret; __m128d sum; __m128d sum1 = _mm_setzero_pd(); __m128d sum2 = _mm_setzero_pd(); @@ -121,8 +114,7 @@ static inline double interpolate_product_double(const float *a, const float *b, sum2 = _mm_mul_pd(f2, sum2); sum = _mm_add_pd(sum1, sum2); sum = _mm_add_sd(sum, _mm_unpackhi_pd(sum, sum)); - _mm_store_sd(&ret, sum); - return ret; + _mm_store_s...

...rray1= array[1..2,1..num] of Double; array2=array[1..num,1..num] of longint; array3=array[1..num,1..num] of Double; array4=array[1..num] of longint; pA1=^array1; pA2=^array2; pA3=^array3; pA4=^array4; pD=^Double; procedure learning(loc1:pA1;adj1:pA2;alpha:pD); cdecl; var i1,i2,neighs:longint; sum1,sum2:double; newloc: array [1..2,1..num] of double; begin for i1:=1 to 2 do for i2:=1 to num do newloc[i1,i2]:=0; for i1:= 1 to num do begin neighs:=0; sum1:=0; sum2:=0; for i2:= 1 to num do begin if (adj1^[i1,i2]=1) then begin neighs:=neighs+1; sum1:=sum1+loc1[1,i2]; sum2:=sum2+lo...

This is a great example how you cannot figure it out after spending two hours troubleshooting, but a few minutes after you post to R-devel, it's just jumps to you (is there a word for this other than "impatient"?); Let me answer my own question. The discrepancy between my sum2() code and the internal code for base::sum() is that the latter uses LDOUBLE = long double (on some system it's only double, cf. https://github.com/wch/r-source/blob/trunk/src/nmath/nmath.h#L28-L33), whereas my sum2() code uses double. So using long double, I can reproduce the penalty of havin...

...ng to be - doing and how many bytes there are in the last - chunk */ - write_int(f_out, s->count); - write_int(f_out, s->n); - write_int(f_out, s->remainder); - - for (i = 0; i < s->count; i++) { - write_int(f_out, s->sums[i].sum1); - write_buf(f_out, s->sums[i].sum2, csum_length); - } - } else { - /* we don't have checksums */ - write_int(f_out, 0); - write_int(f_out, block_size); - write_int(f_out, 0); - } + /* we don't have checksums */ + write_int(f_out, 0); + write_int(f_out, block_size); + write_int(f_out, 0); } @@ -162,57 +146,43 @@...

...hen? test?the? x'Ax/x'Bx. However?I?dodnot?know?if?there?is?a?way?that?can?calculate?the?x? automatically?instead?of? I?typing?different?values?to?get?the?result?and?compare. =================================================== getMultiVal3?=?function?(a,?b,?cc,?x)?{ +?????i-1;?j=1;?sum=0;?sum2=0 +?????n=nrow(a);?v=?c(x,?cc) +?????for?(i?in?1:n)?{ +???????for?(j?in?1:n)?{ +??????????sum=sum+a[i,j]*v[i]*v[j];?sum2=sum2+b[i,j]*v[i]*v[j] +???????} +?????} +????return(sum/sum2) +???}

...red) msSMAPE <- function(obs,pred){ M <- numeric(length(obs)) for (i in 2:length(obs)) { n <- i-1 M[i] <- mean(obs[1:n]) } sum1 <- (abs(obs[1]-pred[1]))/(0.5*(abs(pred[1])+abs(obs[1]))) for (i in 2:length(obs)) { n <- i-1 sum2 <- 0 for (k in 1:n) {sum2 <- sum2+abs(obs[k]-M[k])} S <- sum2/n sum1 <- sum1+(abs(obs[i]-pred[i]))/(0.5*(abs(pred[i])+abs(obs[i]))+S) } my.SMAPE <- sum1/length(obs) return(my.SMAPE) } msSMAPE(obs,pred) [[alternative HTML version deleted]]

...6,7,8) mSMAPE <- function(obs,pred){ M <- numeric(length(obs)) for (i in 2:length(obs)) { n <- i-1 M[i] <- mean(obs[1:n]) } sum1 <- (abs(obs[1]-pred[1]))/(0.5*(abs(pred[1])+abs(obs[1]))) for (i in 2:length(obs)) { n <- i-1 sum2 <- 0 for (k in 1:n) {sum2 <- sum2+abs(obs[k]-M[k])} S <- sum2/n sum1 <- sum1+(abs(obs[i]-pred[i]))/(0.5*(abs(pred[i])+abs(obs[i]))+S) } my.SMAPE <- sum1/length(obs) return(my.SMAPE) } mSMAPE(obs,pred)*100 SMAPEper(obs,pred) [[alternative HTM...

...riance A=((n1-1)*v1+(n2-1)*v2+(n3-1)*v3)/(N-k) #calculate B B=((N-k)*(log(A)))-((n1-1)*log(v1)+(n2-1)*log(v2)+(n3-1)*log(v3)) #calculate C C=1+(1/(3*(k-1))*(((1/(n1-1))+(1/(n2-1))+(1/(n3-1)))-(1/(N-k)))) #calculate layard estimator xbar1=mean(g1) xbar2=mean(g2) xbar3=mean(g3) sum1=sum((g1-xbar1)^4) sum2=sum((g2-xbar2)^4) sum3=sum((g3-xbar3)^4) sum4=sum((g1-xbar1)^2) sum5=sum((g2-xbar2)^2) sum6=sum((g3-xbar3)^2) y= (N*(sum1+sum2+sum3))/((sum4+sum5+sum6)^2) #calculate bartlett modified statistic bar2=B/(C*(1/2)*(y-1)) bar2 pv[i]<-pchisq(bar2,2,lower=FALSE) } mean(pv<0.01) mean(pv<0.05) --...

...si32(acc1); - - for (;i<N;i++) - { - sum = silk_SMLABB(sum, x[i], y[i]); - } +#include <xmmintrin.h> +#include "arch.h" - return sum; +void xcorr_kernel_sse(const opus_val16 *x, const opus_val16 *y, opus_val32 sum[4], int len) +{ + int j; + __m128 xsum1, xsum2; + xsum1 = _mm_loadu_ps(sum); + xsum2 = _mm_setzero_ps(); + + for (j = 0; j < len-3; j += 4) + { + __m128 x0 = _mm_loadu_ps(x+j); + __m128 yj = _mm_loadu_ps(y+j); + __m128 y3 = _mm_loadu_ps(y+j+3); + + xsum1 = _mm_add_ps(xsum1,_mm_mul_ps(_mm_shuffle_ps(x0,x0,0x00),yj)...