search for: end__

...uva_for_each_va_range - iternator to walk over a range of &drm_gpuvas >> + * @va__: &drm_gpuva structure to assign to in each iteration step >> + * @mgr__: &drm_gpuva_manager to walk over >> + * @start__: starting offset, the first gpuva will overlap this >> + * @end__: ending offset, the last gpuva will start before this (but may >> + * overlap) >> + * >> + * This iterator walks over all &drm_gpuvas in the &drm_gpuva_manager that lie >> + * between @start__ and @end__. It is implemented similarly to list_for_each(), >> + * b...

...> I see this patch is to allow for anonymous maple states, this looks > good. > > I've a lengthy comment about the iterator that I'm adding here to head > off anyone that may copy your example below. > >> >> \#define sample_iter_for_each_range(it__, start__, end__) \ >> for ((it__).mas.index = start__, (it__).entry = mas_find(&(it__).mas, end__ - 1); \ >> (it__).entry; (it__).entry = mas_find(&(it__).mas, end__ - 1)) > > I see you've added something like the above in your patch set as well. > I'd like to point out...

...22 22 22 22 [26] 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 [51] 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 [76] 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 Slot "dimension": [1] 100 1 __ END__ How can I acces "Slot 'ra'" only? I tried print(x$ra) but fail. - Gundala Viswanath Jakarta - Indonesia

...9] (69,79] 10063374 79 16 4 3 4 4 3 (79,89] (89,99] 6 2 I tried to plot a histogram overlayed with curve. With the following snippet: library(lattice) pdf("myfile.pdf") hist(dat) lines(dat,col="red") dev.off() __ END__ However the number of bins it plot is not the same with "dat" (i.e. 10 bins). It only gives 6 bins. The actual output can be seen in this URL http://docs.google.com/Doc?id=dcvdrfrh_5cm5qkchw How can I fix the code so that it gives a exact plot to "dat" above, with same number...

...ry(grid) library(gridBase) opar <- par(no.readonly=TRUE) par(opar) grid.newpage() pushViewport(viewport(width=0.5, height=0.5)) grid.rect(gp=gpar(col="grey", lty="dashed")) par(omi=gridOMI()) par(mfrow=c(2, 2), mfg=c(1, 1), mar=c(3, 3, 1, 0)) for (i in 1:4) { plot(1:10) } __ END__ - Gundala Viswanath Jakarta - Indonesia

...ER_LOCK_EXTERN; +} + +/** + * drm_gpuva_for_each_va_range - iternator to walk over a range of &drm_gpuvas + * @va__: &drm_gpuva structure to assign to in each iteration step + * @mgr__: &drm_gpuva_manager to walk over + * @start__: starting offset, the first gpuva will overlap this + * @end__: ending offset, the last gpuva will start before this (but may + * overlap) + * + * This iterator walks over all &drm_gpuvas in the &drm_gpuva_manager that lie + * between @start__ and @end__. It is implemented similarly to list_for_each(), + * but is using the &drm_gpuva_manager's...

...ntry); + + return NULL; +} + +/** + * drm_gpuva_for_each_va_range() - iterate over a range of &drm_gpuvas + * @va__: &drm_gpuva structure to assign to in each iteration step + * @mgr__: &drm_gpuva_manager to walk over + * @start__: starting offset, the first gpuva will overlap this + * @end__: ending offset, the last gpuva will start before this (but may + * overlap) + * + * This iterator walks over all &drm_gpuvas in the &drm_gpuva_manager that lie + * between @start__ and @end__. It is implemented similarly to list_for_each(), + * but is using the &drm_gpuva_manager's...

...ntry); + + return NULL; +} + +/** + * drm_gpuva_for_each_va_range() - iterate over a range of &drm_gpuvas + * @va__: &drm_gpuva structure to assign to in each iteration step + * @mgr__: &drm_gpuva_manager to walk over + * @start__: starting offset, the first gpuva will overlap this + * @end__: ending offset, the last gpuva will start before this (but may + * overlap) + * + * This iterator walks over all &drm_gpuvas in the &drm_gpuva_manager that lie + * between @start__ and @end__. It is implemented similarly to list_for_each(), + * but is using the &drm_gpuva_manager's...

...= ", nofc, "\n") maxlogl <- -(mlogl_process(vsamples,error_,thetastart)) bic_k <- find_bic(maxlogl,vsamples,nofc) aic_k <- find_aic(maxlogl,vsamples,nofc) cat("BIC = ", bic_k, " - AIC = ", aic_k, "- MLL= ", maxlogl,"\n") } __ END__ We finally expect to choose K with the smallest AIC/BIC value. However, the problem I have is that the AIC/BIC value is always on the increase. Can anybody advice what's wrong with my above approach? Regards, Edward