def autoScale(self, maxNumSteps, x1, x2, stepSize):
if x1 > x2:
x1, x2 = x2, x1
logBase = self.base()
interval = QwtInterval(x1/np.power(logBase, self.lowerMargin()),
x2*np.power(logBase, self.upperMargin()))
if interval.maxValue()/interval.minValue() < logBase:
linearScaler = QwtLinearScaleEngine()
linearScaler.setAttributes(self.attributes())
linearScaler.setReference(self.reference())
linearScaler.setMargins(self.lowerMargin(), self.upperMargin())
x1, x2, stepSize = linearScaler.autoScale(maxNumSteps,
x1, x2, stepSize)
linearInterval = QwtInterval(x1, x2).normalized()
linearInterval = linearInterval.limited(LOG_MIN, LOG_MAX)
if linearInterval.maxValue()/linearInterval.minValue() < logBase:
if stepSize < 0.:
stepSize = -qwtLog(logBase, abs(stepSize))
else:
stepSize = qwtLog(logBase, stepSize)
return x1, x2, stepSize
logRef = 1.
if self.reference() > LOG_MIN/2:
logRef = min([self.reference(), LOG_MAX/2])
if self.testAttribute(QwtScaleEngine.Symmetric):
delta = max([interval.maxValue()/logRef,
logRef/interval.minValue()])
interval.setInterval(logRef/delta, logRef*delta)
if self.testAttribute(QwtScaleEngine.IncludeReference):
interval = interval.extend(logRef)
interval = interval.limited(LOG_MIN, LOG_MAX)
if interval.width() == 0.:
interval = self.buildInterval(interval.minValue())
stepSize = self.divideInterval(
qwtLogInterval(logBase, interval).width(), max([maxNumSteps, 1]))
if stepSize < 1.:
stepSize = 1.
if not self.testAttribute(QwtScaleEngine.Floating):
interval = self.align(interval, stepSize)
x1 = interval.minValue()
x2 = interval.maxValue()
if self.testAttribute(QwtScaleEngine.Inverted):
x1, x2 = x2, x1
stepSize = -stepSize
def autoScale(self, maxNumSteps, x1, x2, stepSize):
if x1 > x2:
x1, x2 = x2, x1
logBase = self.base()
interval = QwtInterval(x1 / np.power(logBase, self.lowerMargin()),
x2 * np.power(logBase, self.upperMargin()))
if interval.maxValue() / interval.minValue() < logBase:
linearScaler = QwtLinearScaleEngine()
linearScaler.setAttributes(self.attributes())
linearScaler.setReference(self.reference())
linearScaler.setMargins(self.lowerMargin(), self.upperMargin())
x1, x2, stepSize = linearScaler.autoScale(maxNumSteps, x1, x2,
stepSize)
linearInterval = QwtInterval(x1, x2).normalized()
linearInterval = linearInterval.limited(LOG_MIN, LOG_MAX)
if linearInterval.maxValue() / linearInterval.minValue() < logBase:
if stepSize < 0.:
stepSize = -qwtLog(logBase, abs(stepSize))
else:
stepSize = qwtLog(logBase, stepSize)
return x1, x2, stepSize
logRef = 1.
if self.reference() > LOG_MIN / 2:
logRef = min([self.reference(), LOG_MAX / 2])
if self.testAttribute(QwtScaleEngine.Symmetric):
delta = max(
[interval.maxValue() / logRef, logRef / interval.minValue()])
interval.setInterval(logRef / delta, logRef * delta)
if self.testAttribute(QwtScaleEngine.IncludeReference):
interval = interval.extend(logRef)
interval = interval.limited(LOG_MIN, LOG_MAX)
if interval.width() == 0.:
interval = self.buildInterval(interval.minValue())
stepSize = self.divideInterval(
qwtLogInterval(logBase, interval).width(), max([maxNumSteps, 1]))
if stepSize < 1.:
stepSize = 1.
if not self.testAttribute(QwtScaleEngine.Floating):
interval = self.align(interval, stepSize)
x1 = interval.minValue()
x2 = interval.maxValue()
if self.testAttribute(QwtScaleEngine.Inverted):
x1, x2 = x2, x1
stepSize = -stepSize
def autoScale(self, maxNumSteps, x1, x2, stepSize):
"""
Align and divide an interval
:param int maxNumSteps: Max. number of steps
:param float x1: First limit of the interval (In/Out)
:param float x2: Second limit of the interval (In/Out)
:param float stepSize: Step size
:return: tuple (x1, x2, stepSize)
.. seealso::
:py:meth:`setAttribute()`
"""
if x1 > x2:
x1, x2 = x2, x1
logBase = self.base()
interval = QwtInterval(
x1 / math.pow(logBase, self.lowerMargin()),
x2 * math.pow(logBase, self.upperMargin()),
)
interval = interval.limited(LOG_MIN, LOG_MAX)
if interval.maxValue() / interval.minValue() < logBase:
linearScaler = QwtLinearScaleEngine()
linearScaler.setAttributes(self.attributes())
linearScaler.setReference(self.reference())
linearScaler.setMargins(self.lowerMargin(), self.upperMargin())
x1, x2, stepSize = linearScaler.autoScale(maxNumSteps, x1, x2,
stepSize)
linearInterval = QwtInterval(x1, x2).normalized()
linearInterval = linearInterval.limited(LOG_MIN, LOG_MAX)
if linearInterval.maxValue() / linearInterval.minValue() < logBase:
if stepSize < 0.0:
stepSize = -math.log(abs(stepSize), logBase)
else:
stepSize = math.log(stepSize, logBase)
return x1, x2, stepSize
logRef = 1.0
if self.reference() > LOG_MIN / 2:
logRef = min([self.reference(), LOG_MAX / 2])
if self.testAttribute(QwtScaleEngine.Symmetric):
delta = max(
[interval.maxValue() / logRef, logRef / interval.minValue()])
interval.setInterval(logRef / delta, logRef * delta)
if self.testAttribute(QwtScaleEngine.IncludeReference):
interval = interval.extend(logRef)
interval = interval.limited(LOG_MIN, LOG_MAX)
if interval.width() == 0.0:
interval = self.buildInterval(interval.minValue())
stepSize = self.divideInterval(
qwtLogInterval(logBase, interval).width(), max([maxNumSteps, 1]))
if stepSize < 1.0:
stepSize = 1.0
if not self.testAttribute(QwtScaleEngine.Floating):
interval = self.align(interval, stepSize)
x1 = interval.minValue()
x2 = interval.maxValue()
if self.testAttribute(QwtScaleEngine.Inverted):
x1, x2 = x2, x1
stepSize = -stepSize
return x1, x2, stepSize
def autoScale(self, maxNumSteps, x1, x2, stepSize):
"""
Align and divide an interval
:param int maxNumSteps: Max. number of steps
:param float x1: First limit of the interval (In/Out)
:param float x2: Second limit of the interval (In/Out)
:param float stepSize: Step size
:return: tuple (x1, x2, stepSize)
.. seealso::
:py:meth:`setAttribute()`
"""
if x1 > x2:
x1, x2 = x2, x1
logBase = self.base()
interval = QwtInterval(x1 / np.power(logBase, self.lowerMargin()), x2 * np.power(logBase, self.upperMargin()))
if interval.maxValue() / interval.minValue() < logBase:
linearScaler = QwtLinearScaleEngine()
linearScaler.setAttributes(self.attributes())
linearScaler.setReference(self.reference())
linearScaler.setMargins(self.lowerMargin(), self.upperMargin())
x1, x2, stepSize = linearScaler.autoScale(maxNumSteps, x1, x2, stepSize)
linearInterval = QwtInterval(x1, x2).normalized()
linearInterval = linearInterval.limited(LOG_MIN, LOG_MAX)
if linearInterval.maxValue() / linearInterval.minValue() < logBase:
if stepSize < 0.0:
stepSize = -qwtLog(logBase, abs(stepSize))
else:
stepSize = qwtLog(logBase, stepSize)
return x1, x2, stepSize
logRef = 1.0
if self.reference() > LOG_MIN / 2:
logRef = min([self.reference(), LOG_MAX / 2])
if self.testAttribute(QwtScaleEngine.Symmetric):
delta = max([interval.maxValue() / logRef, logRef / interval.minValue()])
interval.setInterval(logRef / delta, logRef * delta)
if self.testAttribute(QwtScaleEngine.IncludeReference):
interval = interval.extend(logRef)
interval = interval.limited(LOG_MIN, LOG_MAX)
if interval.width() == 0.0:
interval = self.buildInterval(interval.minValue())
stepSize = self.divideInterval(qwtLogInterval(logBase, interval).width(), max([maxNumSteps, 1]))
if stepSize < 1.0:
stepSize = 1.0
if not self.testAttribute(QwtScaleEngine.Floating):
interval = self.align(interval, stepSize)
x1 = interval.minValue()
x2 = interval.maxValue()
if self.testAttribute(QwtScaleEngine.Inverted):
x1, x2 = x2, x1
stepSize = -stepSize
return x1, x2, stepSize