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"""Miscellaneous utility functions"""
__authors__ = ["T. Vincent"]
__license__ = "MIT"
__date__ = "22/02/2016"
import math
import numpy
# Float 32 info ###############################################################
# Using min/max value below limits of float32
# so operation with such value (e.g., max - min) do not overflow
FLOAT32_SAFE_MIN = -1e37
FLOAT32_MINPOS = numpy.finfo(numpy.float32).tiny
FLOAT32_SAFE_MAX = 1e37
# TODO double support
[docs]def addMarginsToLimits(margins, isXLog, isYLog,
xMin, xMax, yMin, yMax, y2Min=None, y2Max=None):
"""Returns updated limits by extending them with margins.
:param margins: The ratio of the margins to add or None for no margins.
:type margins: A 4-tuple of floats as
(xMinMargin, xMaxMargin, yMinMargin, yMaxMargin)
:return: The updated limits
:rtype: tuple of 4 or 6 floats: Either (xMin, xMax, yMin, yMax) or
(xMin, xMax, yMin, yMax, y2Min, y2Max) if y2Min and y2Max
are provided.
"""
if margins is not None:
xMinMargin, xMaxMargin, yMinMargin, yMaxMargin = margins
if not isXLog:
xRange = xMax - xMin
xMin -= xMinMargin * xRange
xMax += xMaxMargin * xRange
elif xMin > 0. and xMax > 0.: # Log scale
# Do not apply margins if limits < 0
xMinLog, xMaxLog = numpy.log10(xMin), numpy.log10(xMax)
xRangeLog = xMaxLog - xMinLog
xMin = pow(10., xMinLog - xMinMargin * xRangeLog)
xMax = pow(10., xMaxLog + xMaxMargin * xRangeLog)
if not isYLog:
yRange = yMax - yMin
yMin -= yMinMargin * yRange
yMax += yMaxMargin * yRange
elif yMin > 0. and yMax > 0.: # Log scale
# Do not apply margins if limits < 0
yMinLog, yMaxLog = numpy.log10(yMin), numpy.log10(yMax)
yRangeLog = yMaxLog - yMinLog
yMin = pow(10., yMinLog - yMinMargin * yRangeLog)
yMax = pow(10., yMaxLog + yMaxMargin * yRangeLog)
if y2Min is not None and y2Max is not None:
if not isYLog:
yRange = y2Max - y2Min
y2Min -= yMinMargin * yRange
y2Max += yMaxMargin * yRange
elif y2Min > 0. and y2Max > 0.: # Log scale
# Do not apply margins if limits < 0
yMinLog, yMaxLog = numpy.log10(y2Min), numpy.log10(y2Max)
yRangeLog = yMaxLog - yMinLog
y2Min = pow(10., yMinLog - yMinMargin * yRangeLog)
y2Max = pow(10., yMaxLog + yMaxMargin * yRangeLog)
if y2Min is None or y2Max is None:
return xMin, xMax, yMin, yMax
else:
return xMin, xMax, yMin, yMax, y2Min, y2Max
[docs]def scale1DRange(min_, max_, center, scale, isLog):
"""Scale a 1D range given a scale factor and an center point.
Keeps the values in a smaller range than float32.
:param float min_: The current min value of the range.
:param float max_: The current max value of the range.
:param float center: The center of the zoom (i.e., invariant point).
:param float scale: The scale to use for zoom
:param bool isLog: Whether using log scale or not.
:return: The zoomed range.
:rtype: tuple of 2 floats: (min, max)
"""
if isLog:
# Min and center can be < 0 when
# autoscale is off and switch to log scale
# max_ < 0 should not happen
min_ = numpy.log10(min_) if min_ > 0. else FLOAT32_MINPOS
center = numpy.log10(center) if center > 0. else FLOAT32_MINPOS
max_ = numpy.log10(max_) if max_ > 0. else FLOAT32_MINPOS
if min_ == max_:
return min_, max_
offset = (center - min_) / (max_ - min_)
range_ = (max_ - min_) / scale
newMin = center - offset * range_
newMax = center + (1. - offset) * range_
if isLog:
# No overflow as exponent is log10 of a float32
newMin = pow(10., newMin)
newMax = pow(10., newMax)
newMin = numpy.clip(newMin, FLOAT32_MINPOS, FLOAT32_SAFE_MAX)
newMax = numpy.clip(newMax, FLOAT32_MINPOS, FLOAT32_SAFE_MAX)
else:
newMin = numpy.clip(newMin, FLOAT32_SAFE_MIN, FLOAT32_SAFE_MAX)
newMax = numpy.clip(newMax, FLOAT32_SAFE_MIN, FLOAT32_SAFE_MAX)
return newMin, newMax
[docs]def applyZoomToPlot(plot, scaleF, center=None):
"""Zoom in/out plot given a scale and a center point.
:param plot: The plot on which to apply zoom.
:param float scaleF: Scale factor of zoom.
:param center: (x, y) coords in pixel coordinates of the zoom center.
:type center: 2-tuple of float
"""
xMin, xMax = plot.getGraphXLimits()
yMin, yMax = plot.getGraphYLimits()
if center is None:
left, top, width, height = plot.getPlotBoundsInPixels()
cx, cy = left + width // 2, top + height // 2
else:
cx, cy = center
dataCenterPos = plot.pixelToData(cx, cy)
assert dataCenterPos is not None
xMin, xMax = scale1DRange(xMin, xMax, dataCenterPos[0], scaleF,
plot.isXAxisLogarithmic())
yMin, yMax = scale1DRange(yMin, yMax, dataCenterPos[1], scaleF,
plot.isYAxisLogarithmic())
dataPos = plot.pixelToData(cx, cy, axis="right")
assert dataPos is not None
y2Center = dataPos[1]
y2Min, y2Max = plot.getGraphYLimits(axis="right")
y2Min, y2Max = scale1DRange(y2Min, y2Max, y2Center, scaleF,
plot.isYAxisLogarithmic())
plot.setLimits(xMin, xMax, yMin, yMax, y2Min, y2Max)
[docs]def applyPan(min_, max_, panFactor, isLog10):
"""Returns a new range with applied panning.
Moves the range according to panFactor.
If isLog10 is True, converts to log10 before moving.
:param float min_: Min value of the data range to pan.
:param float max_: Max value of the data range to pan.
Must be >= min.
:param float panFactor: Signed proportion of the range to use for pan.
:param bool isLog10: True if log10 scale, False if linear scale.
:return: New min and max value with pan applied.
:rtype: 2-tuple of float.
"""
if isLog10 and min_ > 0.:
# Negative range and log scale can happen with matplotlib
logMin, logMax = math.log10(min_), math.log10(max_)
logOffset = panFactor * (logMax - logMin)
newMin = pow(10., logMin + logOffset)
newMax = pow(10., logMax + logOffset)
# Takes care of out-of-range values
if newMin > 0. and newMax < float('inf'):
min_, max_ = newMin, newMax
else:
offset = panFactor * (max_ - min_)
newMin, newMax = min_ + offset, max_ + offset
# Takes care of out-of-range values
if newMin > - float('inf') and newMax < float('inf'):
min_, max_ = newMin, newMax
return min_, max_
[docs]def clamp(value, min_=0., max_=1.):
"""Clip a value to a range [min, max].
:param value: The value to clip
:param min_: The min edge of the range
:param max_: The max edge of the range
:return: The clipped value
"""
if value < min_:
return min_
elif value > max_:
return max_
else:
return value