def draw(self, state, plotCoordinates, plotDefinitions, performanceTable):
"""Draw the plot element.
This stage consists of creating an SVG image of the
pre-computed data.
@type state: ad-hoc Python object
@param state: State information that persists long enough to use quantities computed in C{prepare} in the C{draw} stage. This is a work-around of lxml's refusal to let its Python instances maintain C{self} and it is unrelated to DataTableState.
@type plotCoordinates: PlotCoordinates
@param plotCoordinates: The coordinate system in which this plot element will be placed.
@type plotDefinitions: PlotDefinitions
@type plotDefinitions: The dictionary of key-value pairs that forms the <defs> section of the SVG document.
@type performanceTable: PerformanceTable
@param performanceTable: Measures and records performance (time and memory consumption) of the drawing process.
@rtype: SvgBinding
@return: An SVG fragment representing the fully drawn plot element.
"""
svg = SvgBinding.elementMaker
performanceTable.begin("PlotHistogram draw")
cumulative = self.get("cumulative",
defaultFromXsd=True,
convertType=True)
vertical = self.get("vertical", defaultFromXsd=True, convertType=True)
visualization = self.get("visualization", defaultFromXsd=True)
output = svg.g()
if len(state.count) > 0:
if state.fieldType is not self.fieldTypeNumeric:
if vertical:
strings = plotCoordinates.xstrings
else:
strings = plotCoordinates.ystrings
newCount = []
for string in strings:
try:
index = state.edges.index(string)
except ValueError:
newCount.append(0.0)
else:
newCount.append(state.count[index])
state.count = newCount
state.edges = [(i - 0.5, i + 0.5)
for i in xrange(len(strings))]
if vertical:
Ax = NP("array", [
low if low is not None else float("-inf")
for low, high in state.edges
],
dtype=NP.dtype(float))
Bx = NP(Ax.copy())
Cx = NP("array", [
high if high is not None else float("inf")
for low, high in state.edges
],
dtype=NP.dtype(float))
Dx = NP(Cx.copy())
Ay = NP("zeros", len(state.count), dtype=NP.dtype(float))
if cumulative:
Cy = NP("cumsum",
NP("array", state.count, dtype=NP.dtype(float)))
By = NP("roll", Cy, 1)
By[0] = 0.0
else:
By = NP("array", state.count, dtype=NP.dtype(float))
Cy = NP(By.copy())
Dy = NP(Ay.copy())
else:
if cumulative:
Cx = NP("cumsum",
NP("array", state.count, dtype=NP.dtype(float)))
Bx = NP("roll", Cx, 1)
Bx[0] = 0.0
else:
Bx = NP("array", state.count, dtype=NP.dtype(float))
Cx = NP(Bx.copy())
Ax = NP("zeros", len(state.count), dtype=NP.dtype(float))
Dx = NP(Ax.copy())
Ay = NP("array", [
low if low is not None else float("-inf")
for low, high in state.edges
],
dtype=NP.dtype(float))
By = NP(Ay.copy())
Cy = NP("array", [
high if high is not None else float("inf")
for low, high in state.edges
],
dtype=NP.dtype(float))
Dy = NP(Cy.copy())
AX, AY = plotCoordinates(Ax, Ay)
BX, BY = plotCoordinates(Bx, By)
CX, CY = plotCoordinates(Cx, Cy)
DX, DY = plotCoordinates(Dx, Dy)
if visualization == "skyline":
gap = self.get("gap", defaultFromXsd=True, convertType=True)
if vertical:
if gap > 0.0 and NP(
NP(DX - gap / 2.0) -
NP(AX + gap / 2.0)).min() > 0.0:
AX += gap / 2.0
BX += gap / 2.0
CX -= gap / 2.0
DX -= gap / 2.0
else:
if gap > 0.0 and NP(
NP(AY + gap / 2.0) -
NP(DY - gap / 2.0)).min() > 0.0:
AY -= gap / 2.0
BY -= gap / 2.0
CY += gap / 2.0
DY += gap / 2.0
pathdata = []
nextIsMoveto = True
for i in xrange(len(state.count)):
iprev = i - 1
inext = i + 1
if vertical and By[i] == 0.0 and Cy[i] == 0.0:
if i > 0 and not nextIsMoveto:
pathdata.append("L %r %r" % (DX[iprev], DY[iprev]))
nextIsMoveto = True
elif not vertical and Bx[i] == 0.0 and Cx[i] == 0.0:
if i > 0 and not nextIsMoveto:
pathdata.append("L %r %r" % (DX[iprev], DY[iprev]))
nextIsMoveto = True
else:
if nextIsMoveto or gap > 0.0 or (
vertical and DX[iprev] != AX[i]) or (
not vertical and DY[iprev] != AY[i]):
pathdata.append("M %r %r" % (AX[i], AY[i]))
nextIsMoveto = False
pathdata.append("L %r %r" % (BX[i], BY[i]))
pathdata.append("L %r %r" % (CX[i], CY[i]))
if i == len(state.count) - 1 or gap > 0.0 or (
vertical and DX[i] != AX[inext]) or (
not vertical and DY[i] != AY[inext]):
pathdata.append("L %r %r" % (DX[i], DY[i]))
style = self.getStyleState()
del style["marker-size"]
del style["marker-outline"]
output.append(
svg.path(d=" ".join(pathdata),
style=PlotStyle.toString(style)))
elif visualization == "polyline":
pathdata = []
for i in xrange(len(state.count)):
if i == 0:
pathdata.append("M %r %r" % (AX[i], AY[i]))
pathdata.append("L %r %r" % ((BX[i] + CX[i]) / 2.0,
(BY[i] + CY[i]) / 2.0))
if i == len(state.count) - 1:
pathdata.append("L %r %r" % (DX[i], DY[i]))
style = self.getStyleState()
del style["marker-size"]
del style["marker-outline"]
output.append(
svg.path(d=" ".join(pathdata),
style=PlotStyle.toString(style)))
elif visualization == "smooth":
smoothingSamples = math.ceil(len(state.count) / 2.0)
BCX = NP(NP(BX + CX) / 2.0)
BCY = NP(NP(BY + CY) / 2.0)
xarray = NP("array", [AX[0]] + list(BCX) + [DX[-1]],
dtype=NP.dtype(float))
yarray = NP("array", [AY[0]] + list(BCY) + [DY[-1]],
dtype=NP.dtype(float))
samples = NP("linspace",
AX[0],
DX[-1],
int(smoothingSamples),
endpoint=True)
smoothingScale = abs(DX[-1] - AX[0]) / smoothingSamples
xlist, ylist, dxlist, dylist = PlotCurve.pointsToSmoothCurve(
xarray, yarray, samples, smoothingScale, False)
pathdata = PlotCurve.formatPathdata(xlist, ylist,
dxlist, dylist,
PlotCoordinates(), False,
True)
style = self.getStyleState()
fillStyle = dict(
(x, style[x]) for x in style if x.startswith("fill"))
fillStyle["stroke"] = "none"
strokeStyle = dict(
(x, style[x]) for x in style if x.startswith("stroke"))
if style["fill"] != "none" and len(pathdata) > 0:
if vertical:
firstPoint = plotCoordinates(Ax[0], 0.0)
lastPoint = plotCoordinates(Dx[-1], 0.0)
else:
firstPoint = plotCoordinates(0.0, Ay[0])
lastPoint = plotCoordinates(0.0, Dy[-1])
pathdata2 = [
"M %r %r" % firstPoint, pathdata[0].replace("M", "L")
]
pathdata2.extend(pathdata[1:])
pathdata2.append(pathdata[-1])
pathdata2.append("L %r %r" % lastPoint)
output.append(
svg.path(d=" ".join(pathdata2),
style=PlotStyle.toString(fillStyle)))
output.append(
svg.path(d=" ".join(pathdata),
style=PlotStyle.toString(strokeStyle)))
elif visualization == "points":
currentStyle = PlotStyle.toDict(self.get("style") or {})
style = self.getStyleState()
if "fill" not in currentStyle:
style["fill"] = "black"
BCX = NP(NP(BX + CX) / 2.0)
BCY = NP(NP(BY + CY) / 2.0)
svgId = self.get("svgId")
if svgId is None:
svgIdMarker = plotDefinitions.uniqueName()
else:
svgIdMarker = svgId + ".marker"
marker = PlotScatter.makeMarker(
svgIdMarker, self.get("marker", defaultFromXsd=True),
style, self.childOfTag("PlotSvgMarker"))
plotDefinitions[marker.get("id")] = marker
markerReference = "#" + marker.get("id")
output.extend(
svg.use(
**{
"x": repr(x),
"y": repr(y),
defs.XLINK_HREF: markerReference
}) for x, y in itertools.izip(BCX, BCY))
else:
raise NotImplementedError("TODO: add 'errorbars'")
svgId = self.get("svgId")
if svgId is not None:
output["id"] = svgId
performanceTable.end("PlotHistogram draw")
return output
def draw(self, state, plotCoordinates, plotDefinitions, performanceTable):
"""Draw the plot element.
This stage consists of creating an SVG image of the
pre-computed data.
@type state: ad-hoc Python object
@param state: State information that persists long enough to use quantities computed in C{prepare} in the C{draw} stage. This is a work-around of lxml's refusal to let its Python instances maintain C{self} and it is unrelated to DataTableState.
@type plotCoordinates: PlotCoordinates
@param plotCoordinates: The coordinate system in which this plot element will be placed.
@type plotDefinitions: PlotDefinitions
@type plotDefinitions: The dictionary of key-value pairs that forms the <defs> section of the SVG document.
@type performanceTable: PerformanceTable
@param performanceTable: Measures and records performance (time and memory consumption) of the drawing process.
@rtype: SvgBinding
@return: An SVG fragment representing the fully drawn plot element.
"""
svg = SvgBinding.elementMaker
performanceTable.begin("PlotHistogram draw")
cumulative = self.get("cumulative", defaultFromXsd=True, convertType=True)
vertical = self.get("vertical", defaultFromXsd=True, convertType=True)
visualization = self.get("visualization", defaultFromXsd=True)
output = svg.g()
if len(state.count) > 0:
if state.fieldType is not self.fieldTypeNumeric:
if vertical:
strings = plotCoordinates.xstrings
else:
strings = plotCoordinates.ystrings
newCount = []
for string in strings:
try:
index = state.edges.index(string)
except ValueError:
newCount.append(0.0)
else:
newCount.append(state.count[index])
state.count = newCount
state.edges = [(i - 0.5, i + 0.5) for i in xrange(len(strings))]
if vertical:
Ax = NP("array", [low if low is not None else float("-inf") for low, high in state.edges], dtype=NP.dtype(float))
Bx = NP(Ax.copy())
Cx = NP("array", [high if high is not None else float("inf") for low, high in state.edges], dtype=NP.dtype(float))
Dx = NP(Cx.copy())
Ay = NP("zeros", len(state.count), dtype=NP.dtype(float))
if cumulative:
Cy = NP("cumsum", NP("array", state.count, dtype=NP.dtype(float)))
By = NP("roll", Cy, 1)
By[0] = 0.0
else:
By = NP("array", state.count, dtype=NP.dtype(float))
Cy = NP(By.copy())
Dy = NP(Ay.copy())
else:
if cumulative:
Cx = NP("cumsum", NP("array", state.count, dtype=NP.dtype(float)))
Bx = NP("roll", Cx, 1)
Bx[0] = 0.0
else:
Bx = NP("array", state.count, dtype=NP.dtype(float))
Cx = NP(Bx.copy())
Ax = NP("zeros", len(state.count), dtype=NP.dtype(float))
Dx = NP(Ax.copy())
Ay = NP("array", [low if low is not None else float("-inf") for low, high in state.edges], dtype=NP.dtype(float))
By = NP(Ay.copy())
Cy = NP("array", [high if high is not None else float("inf") for low, high in state.edges], dtype=NP.dtype(float))
Dy = NP(Cy.copy())
AX, AY = plotCoordinates(Ax, Ay)
BX, BY = plotCoordinates(Bx, By)
CX, CY = plotCoordinates(Cx, Cy)
DX, DY = plotCoordinates(Dx, Dy)
if visualization == "skyline":
gap = self.get("gap", defaultFromXsd=True, convertType=True)
if vertical:
if gap > 0.0 and NP(NP(DX - gap/2.0) - NP(AX + gap/2.0)).min() > 0.0:
AX += gap/2.0
BX += gap/2.0
CX -= gap/2.0
DX -= gap/2.0
else:
if gap > 0.0 and NP(NP(AY + gap/2.0) - NP(DY - gap/2.0)).min() > 0.0:
AY -= gap/2.0
BY -= gap/2.0
CY += gap/2.0
DY += gap/2.0
pathdata = []
nextIsMoveto = True
for i in xrange(len(state.count)):
iprev = i - 1
inext = i + 1
if vertical and By[i] == 0.0 and Cy[i] == 0.0:
if i > 0 and not nextIsMoveto:
pathdata.append("L %r %r" % (DX[iprev], DY[iprev]))
nextIsMoveto = True
elif not vertical and Bx[i] == 0.0 and Cx[i] == 0.0:
if i > 0 and not nextIsMoveto:
pathdata.append("L %r %r" % (DX[iprev], DY[iprev]))
nextIsMoveto = True
else:
if nextIsMoveto or gap > 0.0 or (vertical and DX[iprev] != AX[i]) or (not vertical and DY[iprev] != AY[i]):
pathdata.append("M %r %r" % (AX[i], AY[i]))
nextIsMoveto = False
pathdata.append("L %r %r" % (BX[i], BY[i]))
pathdata.append("L %r %r" % (CX[i], CY[i]))
if i == len(state.count) - 1 or gap > 0.0 or (vertical and DX[i] != AX[inext]) or (not vertical and DY[i] != AY[inext]):
pathdata.append("L %r %r" % (DX[i], DY[i]))
style = self.getStyleState()
del style["marker-size"]
del style["marker-outline"]
output.append(svg.path(d=" ".join(pathdata), style=PlotStyle.toString(style)))
elif visualization == "polyline":
pathdata = []
for i in xrange(len(state.count)):
if i == 0:
pathdata.append("M %r %r" % (AX[i], AY[i]))
pathdata.append("L %r %r" % ((BX[i] + CX[i])/2.0, (BY[i] + CY[i])/2.0))
if i == len(state.count) - 1:
pathdata.append("L %r %r" % (DX[i], DY[i]))
style = self.getStyleState()
del style["marker-size"]
del style["marker-outline"]
output.append(svg.path(d=" ".join(pathdata), style=PlotStyle.toString(style)))
elif visualization == "smooth":
smoothingSamples = math.ceil(len(state.count) / 2.0)
BCX = NP(NP(BX + CX) / 2.0)
BCY = NP(NP(BY + CY) / 2.0)
xarray = NP("array", [AX[0]] + list(BCX) + [DX[-1]], dtype=NP.dtype(float))
yarray = NP("array", [AY[0]] + list(BCY) + [DY[-1]], dtype=NP.dtype(float))
samples = NP("linspace", AX[0], DX[-1], int(smoothingSamples), endpoint=True)
smoothingScale = abs(DX[-1] - AX[0]) / smoothingSamples
xlist, ylist, dxlist, dylist = PlotCurve.pointsToSmoothCurve(xarray, yarray, samples, smoothingScale, False)
pathdata = PlotCurve.formatPathdata(xlist, ylist, dxlist, dylist, PlotCoordinates(), False, True)
style = self.getStyleState()
fillStyle = dict((x, style[x]) for x in style if x.startswith("fill"))
fillStyle["stroke"] = "none"
strokeStyle = dict((x, style[x]) for x in style if x.startswith("stroke"))
if style["fill"] != "none" and len(pathdata) > 0:
if vertical:
firstPoint = plotCoordinates(Ax[0], 0.0)
lastPoint = plotCoordinates(Dx[-1], 0.0)
else:
firstPoint = plotCoordinates(0.0, Ay[0])
lastPoint = plotCoordinates(0.0, Dy[-1])
pathdata2 = ["M %r %r" % firstPoint, pathdata[0].replace("M", "L")]
pathdata2.extend(pathdata[1:])
pathdata2.append(pathdata[-1])
pathdata2.append("L %r %r" % lastPoint)
output.append(svg.path(d=" ".join(pathdata2), style=PlotStyle.toString(fillStyle)))
output.append(svg.path(d=" ".join(pathdata), style=PlotStyle.toString(strokeStyle)))
elif visualization == "points":
currentStyle = PlotStyle.toDict(self.get("style") or {})
style = self.getStyleState()
if "fill" not in currentStyle:
style["fill"] = "black"
BCX = NP(NP(BX + CX) / 2.0)
BCY = NP(NP(BY + CY) / 2.0)
svgId = self.get("svgId")
if svgId is None:
svgIdMarker = plotDefinitions.uniqueName()
else:
svgIdMarker = svgId + ".marker"
marker = PlotScatter.makeMarker(svgIdMarker, self.get("marker", defaultFromXsd=True), style, self.childOfTag("PlotSvgMarker"))
plotDefinitions[marker.get("id")] = marker
markerReference = "#" + marker.get("id")
output.extend(svg.use(**{"x": repr(x), "y": repr(y), defs.XLINK_HREF: markerReference}) for x, y in itertools.izip(BCX, BCY))
else:
raise NotImplementedError("TODO: add 'errorbars'")
svgId = self.get("svgId")
if svgId is not None:
output["id"] = svgId
performanceTable.end("PlotHistogram draw")
return output
