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Revert "Code Cleanup: RideFileCache remove mallocs"

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This reverts commit 6fdc55528f.

The performance decrease is considerable. Using mallocs across
my personal ride collection takes 5:19 to compute all the caches.
Using the QVector equivalent took 22:40.

Need to consider looking at QVector across the GC codebase.
This commit is contained in:
Mark Liversedge
2013-03-30 21:33:01 +00:00
parent 0ba93fe619
commit 61a144d705
2 changed files with 16 additions and 16 deletions
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25
src/RideFileCache.cpp
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@@ -489,11 +489,11 @@ void RideFileCache::RideFileCache::compute()
*/
void
data_t *
MeanMaxComputer::integrate_series(cpintdata &data)
{
// would be better to do pure QT and use QVector -- but no memory leak
integrated.resize(data.points.size()+1);
data_t *integrated= (data_t *)malloc(sizeof(data_t)*(data.points.size()+1));
int i;
data_t acc=0;
@@ -503,11 +503,11 @@ MeanMaxComputer::integrate_series(cpintdata &data)
}
integrated[i]=acc;
return;
return integrated;
}
data_t
MeanMaxComputer::partial_max_mean(int start, int end, int length, int *offset)
MeanMaxComputer::partial_max_mean(data_t *dataseries_i, int start, int end, int length, int *offset)
{
int i=0;
data_t candidate=0;
@@ -515,7 +515,7 @@ MeanMaxComputer::partial_max_mean(int start, int end, int length, int *offset)
int best_i=0;
for (i=start; i<(1+end-length); i++) {
data_t test_energy=integrated[length+i]-integrated[i];
data_t test_energy=dataseries_i[length+i]-dataseries_i[i];
if (test_energy>candidate) {
candidate=test_energy;
best_i=i;
@@ -528,7 +528,7 @@ MeanMaxComputer::partial_max_mean(int start, int end, int length, int *offset)
data_t
MeanMaxComputer::divided_max_mean(int datalength, int length, int *offset)
MeanMaxComputer::divided_max_mean(data_t *dataseries_i, int datalength, int length, int *offset)
{
int shift=length;
@@ -549,12 +549,12 @@ MeanMaxComputer::divided_max_mean(int datalength, int length, int *offset)
for (start=0; start+window_length<=datalength; start+=shift) {
end=start+window_length;
energy=integrated[end]-integrated[start];
energy=dataseries_i[end]-dataseries_i[start];
if (energy < candidate) {
continue;
}
data_t window_mm=partial_max_mean(start, end, length, &this_offset);
data_t window_mm=partial_max_mean(dataseries_i, start, end, length, &this_offset);
if (window_mm>candidate) {
candidate=window_mm;
@@ -568,11 +568,11 @@ MeanMaxComputer::divided_max_mean(int datalength, int length, int *offset)
if (end<datalength) {
start=datalength-window_length;
end=datalength;
energy=integrated[end]-integrated[start];
energy=dataseries_i[end]-dataseries_i[start];
if (energy >= candidate) {
data_t window_mm=partial_max_mean(start, end, length, &this_offset);
data_t window_mm=partial_max_mean(dataseries_i, start, end, length, &this_offset);
if (window_mm>candidate) {
candidate=window_mm;
@@ -760,12 +760,12 @@ MeanMaxComputer::run()
// the bests go in here...
QVector <double> ride_bests(total_secs + 1);
integrate_series(data);
data_t *dataseries_i = integrate_series(data);
for (int i=1; i<data.points.size(); i++) {
int offset;
data_t c=divided_max_mean(data.points.size(),i,&offset);
data_t c=divided_max_mean(dataseries_i,data.points.size(),i,&offset);
// snaffle it away
int sec = i*ride->recIntSecs();
@@ -778,6 +778,7 @@ MeanMaxComputer::run()
ride_bests[sec] = val;
}
}
free(dataseries_i);
//
// FILL IN THE GAPS AND FILL TARGET ARRAY