def draw_visits(self, track_graphics: TrackGraphics, brightness: int, color_palette: ColorPalette):
assert brightness in [-1, 0, 1, 2]
visits, min_visits, max_visits = self.get_visits_and_scope_range(brightness)
if not visits:
return
colour_multiplier = 255 / max_visits / max_visits * 2
if brightness == 1:
colour_multiplier *= 2
elif brightness == 2:
colour_multiplier *= 3.5
elif brightness == -1:
colour_multiplier /= 2
for yy, visits in enumerate(visits):
for xx, visit in enumerate(visits):
if visit >= min_visits:
x = self.min_x + self._granularity * xx
y = self.min_y + self._granularity * yy
data = min(1.0, 30/255 + colour_multiplier / 255 * visit * visit)
colour = get_color_for_data(data, color_palette)
track_graphics.plot_box(x, y, x + self._granularity, y + self._granularity, colour)
def multi_draw(track_graphics: TrackGraphics, visitors, colours, threshold):
assert len(colours) == len(visitors)
assert threshold >= 1
min_x = visitors[0].min_x
min_y = visitors[0].min_y
granularity = visitors[0].granularity
for yy in range(0, len(visitors[0].visits)):
for xx in range(0, len(visitors[0].visits[0])):
visits = []
for v in range(0, len(visitors)):
visits.append(visitors[v].visits[yy][xx])
if sum(visits) >= threshold:
target = max(visits)
colour = ""
for i, v in enumerate(visits):
if v >= target:
colour = colours[i]
x = min_x + granularity * xx
y = min_y + granularity * yy
track_graphics.plot_box(x, y, x + granularity, y + granularity,
colour)
def draw_brightness_statistic(self, track_graphics: TrackGraphics, adjust_brightness: int,
color_palette: ColorPalette, visits_heatmap):
assert adjust_brightness in [-1, 0, 1, 2]
if adjust_brightness == 1:
multiplier = 1.1
elif adjust_brightness == 2:
multiplier = 1.2
elif adjust_brightness == -1:
multiplier = 0.9
else:
multiplier = 1.0
(stats, _, _) = self._get_stats_array(np.median, adjust_brightness, visits_heatmap)
for yy, stats in enumerate(stats):
for xx, stat in enumerate(stats):
if not math.isnan(stat):
x = self.min_x + self._granularity * xx
y = self.min_y + self._granularity * yy
colour = get_color_for_data(max(0.1, min(1, stat * multiplier)), color_palette)
track_graphics.plot_box(x, y, x + self._granularity, y + self._granularity, colour)
def draw_statistic(self, track_graphics: TrackGraphics, brightness: int, color_palette: ColorPalette, visits_heatmap,
forced_max_stat=-1, forced_min_stat=-1):
assert brightness in [-1, 0, 1, 2]
(stats, min_stat, max_stat) = self._get_stats_array(np.median, brightness, visits_heatmap)
if max_stat == 0:
return
if forced_max_stat > 0:
max_stat = forced_max_stat
if forced_min_stat > 0:
min_stat = forced_min_stat
if brightness == 1:
max_stat *= 0.93
elif brightness == 2:
max_stat *= 0.85
min_stat *= 0.95
elif brightness == -1:
min_stat *= 1.1
if min_stat >= max_stat:
min_stat = 0.99 * max_stat
stat_range = max_stat - min_stat
for yy, stats in enumerate(stats):
for xx, stat in enumerate(stats):
if not math.isnan(stat):
x = self.min_x + self._granularity * xx
y = self.min_y + self._granularity * yy
gap_from_best = max_stat - stat
data = max(0.1, min(1, 1 - 0.9 * gap_from_best / stat_range))
colour = get_color_for_data(data, color_palette)
track_graphics.plot_box(x, y, x + self._granularity, y + self._granularity, colour)
def draw(self, track_graphics: TrackGraphics, brightness: int,
color_palette: ColorPalette):
# self.print_debug()
assert brightness in [-1, 0, 1, 2]
max_visits = max(max(x) for x in self.visits)
if max_visits == 0:
return
colour_multiplier = 255 / max_visits / max_visits * 2
min_visits = max_visits / 10
if brightness == 1:
colour_multiplier *= 2
min_visits /= 2
elif brightness == 2:
colour_multiplier *= 3.5
min_visits /= 3.5
elif brightness == -1:
colour_multiplier /= 2
min_visits *= 1.5
for yy, visits in enumerate(self.visits):
for xx, visit in enumerate(visits):
if visit >= min_visits:
x = self.min_x + self.granularity * xx
y = self.min_y + self.granularity * yy
data = min(
1.0,
30 / 255 + colour_multiplier / 255 * visit * visit)
colour = get_color_for_data(data, color_palette)
track_graphics.plot_box(x, y, x + self.granularity,
y + self.granularity, colour)