def optimize_colorbar(self,
number_of_ticks=5,
tolerance=5,
step_prec_max=1):
vmin, vmax = self.vmin, self.vmax
_range = vmax - vmin
step = _range / (number_of_ticks - 1)
step_oom = math_tools.order_of_magnitude(step)
def optimize_for_oom(oom):
self.colorbar_step = math.floor(step / 10**oom) * 10**oom
self.colorbar_vmin = math.floor(vmin / 10**oom) * 10**oom
self.colorbar_vmax = self.colorbar_vmin + \
self.colorbar_step * (number_of_ticks - 1)
self.colorbar_locs = (
np.arange(0, number_of_ticks) * self.colorbar_step +
self.colorbar_vmin)
def check_tolerance():
if abs(self.colorbar_vmax - vmax) / vmax > (
tolerance / 100.) or abs(self.colorbar_vmin -
vmin) > (tolerance / 100.):
return True
else:
return False
optimize_for_oom(step_oom)
i = 1
while check_tolerance() and i <= step_prec_max:
optimize_for_oom(step_oom - i)
i += 1
def optimize_colorbar(self,
number_of_ticks=5,
tolerance=5,
step_prec_max=1):
vmin, vmax = self.vmin, self.vmax
_range = vmax - vmin
step = _range / (number_of_ticks - 1)
step_oom = math_tools.order_of_magnitude(step)
def optimize_for_oom(oom):
self.colorbar_step = math.floor(step / 10 ** oom) * 10 ** oom
self.colorbar_vmin = math.floor(vmin / 10 ** oom) * 10 ** oom
self.colorbar_vmax = self.colorbar_vmin + \
self.colorbar_step * (number_of_ticks - 1)
self.colorbar_locs = (
np.arange(0, number_of_ticks) *
self.colorbar_step +
self.colorbar_vmin)
def check_tolerance():
if abs(self.colorbar_vmax - vmax) / vmax > (
tolerance / 100.) or abs(self.colorbar_vmin - vmin
) > (tolerance / 100.):
return True
else:
return False
optimize_for_oom(step_oom)
i = 1
while check_tolerance() and i <= step_prec_max:
optimize_for_oom(step_oom - i)
i += 1