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cleanup: split out divecomputer functions from dive.c

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Since dive.c is so huge, split out divecomputer-related functions
into divecomputer.[c|h], sample.[c|h] and extradata.[c|h].

This does not give huge compile time improvements, since
struct dive contains a struct divecomputer and therefore
dive.h has to include divecomputer.h. However, it make things
distinctly more clear.

Signed-off-by: Berthold Stoeger <bstoeger@mail.tuwien.ac.at>
This commit is contained in:
Berthold Stoeger 2020-10-25 13:28:55 +01:00 • committed by Dirk Hohndel
parent 4aa571d5a0
commit 0e196310f9
38 changed files with 777 additions and 680 deletions
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184
core/device.cpp
View file

@ -8,190 +8,6 @@
#include "core/settings/qPrefDiveComputer.h"
#include <QString> // for QString::number
/*
* Good fake dive profiles are hard.
*
* "depthtime" is the integral of the dive depth over
* time ("area" of the dive profile). We want that
* area to match the average depth (avg_d*max_t).
*
* To do that, we generate a 6-point profile:
*
* (0, 0)
* (t1, max_d)
* (t2, max_d)
* (t3, d)
* (t4, d)
* (max_t, 0)
*
* with the same ascent/descent rates between the
* different depths.
*
* NOTE: avg_d, max_d and max_t are given constants.
* The rest we can/should play around with to get a
* good-looking profile.
*
* That six-point profile gives a total area of:
*
* (max_d*max_t) - (max_d*t1) - (max_d-d)*(t4-t3)
*
* And the "same ascent/descent rates" requirement
* gives us (time per depth must be same):
*
* t1 / max_d = (t3-t2) / (max_d-d)
* t1 / max_d = (max_t-t4) / d
*
* We also obviously require:
*
* 0 <= t1 <= t2 <= t3 <= t4 <= max_t
*
* Let us call 'd_frac = d / max_d', and we get:
*
* Total area must match average depth-time:
*
* (max_d*max_t) - (max_d*t1) - (max_d-d)*(t4-t3) = avg_d*max_t
* max_d*(max_t-t1-(1-d_frac)*(t4-t3)) = avg_d*max_t
* max_t-t1-(1-d_frac)*(t4-t3) = avg_d*max_t/max_d
* t1+(1-d_frac)*(t4-t3) = max_t*(1-avg_d/max_d)
*
* and descent slope must match ascent slopes:
*
* t1 / max_d = (t3-t2) / (max_d*(1-d_frac))
* t1 = (t3-t2)/(1-d_frac)
*
* and
*
* t1 / max_d = (max_t-t4) / (max_d*d_frac)
* t1 = (max_t-t4)/d_frac
*
* In general, we have more free variables than we have constraints,
* but we can aim for certain basics, like a good ascent slope.
*/
static int fill_samples(struct sample *s, int max_d, int avg_d, int max_t, double slope, double d_frac)
{
double t_frac = max_t * (1 - avg_d / (double)max_d);
int t1 = lrint(max_d / slope);
int t4 = lrint(max_t - t1 * d_frac);
int t3 = lrint(t4 - (t_frac - t1) / (1 - d_frac));
int t2 = lrint(t3 - t1 * (1 - d_frac));
if (t1 < 0 || t1 > t2 || t2 > t3 || t3 > t4 || t4 > max_t)
return 0;
s[1].time.seconds = t1;
s[1].depth.mm = max_d;
s[2].time.seconds = t2;
s[2].depth.mm = max_d;
s[3].time.seconds = t3;
s[3].depth.mm = lrint(max_d * d_frac);
s[4].time.seconds = t4;
s[4].depth.mm = lrint(max_d * d_frac);
return 1;
}
/* we have no average depth; instead of making up a random average depth
* we should assume either a PADI rectangular profile (for short and/or
* shallow dives) or more reasonably a six point profile with a 3 minute
* safety stop at 5m */
static void fill_samples_no_avg(struct sample *s, int max_d, int max_t, double slope)
{
// shallow or short dives are just trapecoids based on the given slope
if (max_d < 10000 || max_t < 600) {
s[1].time.seconds = lrint(max_d / slope);
s[1].depth.mm = max_d;
s[2].time.seconds = max_t - lrint(max_d / slope);
s[2].depth.mm = max_d;
} else {
s[1].time.seconds = lrint(max_d / slope);
s[1].depth.mm = max_d;
s[2].time.seconds = max_t - lrint(max_d / slope) - 180;
s[2].depth.mm = max_d;
s[3].time.seconds = max_t - lrint(5000 / slope) - 180;
s[3].depth.mm = 5000;
s[4].time.seconds = max_t - lrint(5000 / slope);
s[4].depth.mm = 5000;
}
}
extern "C" void fake_dc(struct divecomputer *dc)
{
alloc_samples(dc, 6);
struct sample *fake = dc->sample;
int i;
dc->samples = 6;
/* The dive has no samples, so create a few fake ones */
int max_t = dc->duration.seconds;
int max_d = dc->maxdepth.mm;
int avg_d = dc->meandepth.mm;
memset(fake, 0, 6 * sizeof(struct sample));
fake[5].time.seconds = max_t;
for (i = 0; i < 6; i++) {
fake[i].bearing.degrees = -1;
fake[i].ndl.seconds = -1;
}
if (!max_t || !max_d) {
dc->samples = 0;
return;
}
/* Set last manually entered time to the total dive length */
dc->last_manual_time = dc->duration;
/*
* We want to fake the profile so that the average
* depth ends up correct. However, in the absence of
* a reasonable average, let's just make something
* up. Note that 'avg_d == max_d' is _not_ a reasonable
* average.
* We explicitly treat avg_d == 0 differently */
if (avg_d == 0) {
/* we try for a sane slope, but bow to the insanity of
* the user supplied data */
fill_samples_no_avg(fake, max_d, max_t, MAX(2.0 * max_d / max_t, (double)prefs.ascratelast6m));
if (fake[3].time.seconds == 0) { // just a 4 point profile
dc->samples = 4;
fake[3].time.seconds = max_t;
}
return;
}
if (avg_d < max_d / 10 || avg_d >= max_d) {
avg_d = (max_d + 10000) / 3;
if (avg_d > max_d)
avg_d = max_d * 2 / 3;
}
if (!avg_d)
avg_d = 1;
/*
* Ok, first we try a basic profile with a specific ascent
* rate (5 meters per minute) and d_frac (1/3).
*/
if (fill_samples(fake, max_d, avg_d, max_t, (double)prefs.ascratelast6m, 0.33))
return;
/*
* Ok, assume that didn't work because we cannot make the
* average come out right because it was a quick deep dive
* followed by a much shallower region
*/
if (fill_samples(fake, max_d, avg_d, max_t, 10000.0 / 60, 0.10))
return;
/*
* Uhhuh. That didn't work. We'd need to find a good combination that
* satisfies our constraints. Currently, we don't, we just give insane
* slopes.
*/
if (fill_samples(fake, max_d, avg_d, max_t, 10000.0, 0.01))
return;
/* Even that didn't work? Give up, there's something wrong */
}
struct device_table device_table;
bool device::operator==(const device &a) const