本文整理汇总了Python中boomslang.Plot.xLimits方法的典型用法代码示例。如果您正苦于以下问题：Python Plot.xLimits方法的具体用法？Python Plot.xLimits怎么用？Python Plot.xLimits使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类boomslang.Plot的用法示例。
在下文中一共展示了Plot.xLimits方法的6个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: constructImage
# 需要导入模块: from boomslang import Plot [as 别名]
# 或者: from boomslang.Plot import xLimits [as 别名]
def constructImage(self):
plot = Plot()
# Uneven error bars
line = Line()
line.xValues = [6,10,4,0,8,2,12]
line.yValues = [50,90,30,10,70,20,110]
line.yMins = [y - 30 for y in line.yValues]
line.yMaxes = [y + 50 for y in line.yValues]
line.label = "Asymmetric Errors"
line.color = "red"
# Even error bars
line2 = Line()
line2.xValues = [1,5,3,9,7,11]
line2.yValues = [100, 120, 110, 140, 130, 150]
line2.color = "blue"
line2.label = "Symmetric Errors"
line2.yErrors = [5,25,15,45,35,55]
plot.add(line)
plot.add(line2)
plot.xLabel = "X Label"
plot.yLabel = "Y Label"
plot.hasLegend()
plot.xLimits = (-1, 13)
plot.save(self.imageName)示例2: main
# 需要导入模块: from boomslang import Plot [as 别名]
# 或者: from boomslang.Plot import xLimits [as 别名]
def main():
output_graph = sys.argv[1]
plot = Plot()
plot.hasLegend(location='lower right')
plot.xLabel = 'Per-client throughput (Mbps)' # Change this
plot.yLabel = 'CDF'
plot.xLimits = (0, 50)
plot.yLimits = (0, 1)
plot.legendLabelSize = FONT_SIZE
plot.xTickLabelSize = FONT_SIZE - 2
plot.yTickLabelSize = FONT_SIZE - 2
plot.axesLabelSize = FONT_SIZE
for csv_file in sys.argv[2:]:
cdf_table = _make_cdf(csv_file)
line = Line()
line.xValues = [x for (x, _) in cdf_table]
line.yValues = [y for (_, y) in cdf_table]
line.color = colors.pop(0)
line.lineStyle = line_styles.pop(0)
# Extract the filename
line.label = capitalize( csv_file.split('/')[-2].replace('.csv', '') )
plot.add(line)
plot.save(output_graph)示例3: generatePlot
# 需要导入模块: from boomslang import Plot [as 别名]
# 或者: from boomslang.Plot import xLimits [as 别名]
def generatePlot(stepType):
line = Line()
line.xValues = xVals
line.yValues = yVals
line.marker = 'o'
line.stepFunction(stepType)
plot = Plot()
plot.add(line)
plot.title = r'"%s" Steps' % (stepType)
plot.xLimits = (0, 6)
plot.yLimits = (0, 6)
return plot示例4: constructImage
# 需要导入模块: from boomslang import Plot [as 别名]
# 或者: from boomslang.Plot import xLimits [as 别名]
def constructImage(self):
line = Line()
line.xValues = numpy.arange(0, 150, 0.01)
line.yValues = numpy.cos(.02 * numpy.pi * line.xValues)
plot = Plot()
plot.add(line)
plot.xLimits = (0, 150)
plot.yLimits = (-1, 1)
plot.xLabel = "X"
plot.yLabel = "cos(X)"
splitPlots = plot.split(2)
layout = PlotLayout()
layout.width = 2
layout.addPlot(plot, grouping="unsplit")
for s in splitPlots:
layout.addPlot(s, grouping="splits")
layout.save(self.imageName)示例5: constructImage
# 需要导入模块: from boomslang import Plot [as 别名]
# 或者: from boomslang.Plot import xLimits [as 别名]
def constructImage(self):
line1 = Line()
line2 = Line()
line3 = Line()
line1.xValues = range(0,10)
line1.yValues = [2,5,2,3,2,2,1,0,1,0]
line2.xValues = range(0,10)
line2.yValues = [3,1,2,3,2,1,5,3,1,7]
line3.xValues = range(0,10)
line3.yValues = [2,1,3,1,3,4,1,4,5,0]
stack = StackedLines()
stack.addLine(line1, "red")
stack.addLine(line2, "green")
stack.addLine(line3, "blue")
plot = Plot()
plot.xLimits = (0, 9)
plot.yLimits = (0, 7)
plot.add(stack)
plot.save(self.imageName)示例6: PlotLayout
# 需要导入模块: from boomslang import Plot [as 别名]
# 或者: from boomslang.Plot import xLimits [as 别名]
scatterPlot.yLabel = "dHeight/dX"
scatterPlot.title = "Surface - Gradient"
layout = PlotLayout()
layout.addPlot(scatterPlot)
#layout.plot()
layout.save("profile1_gradient.png")
#now plot the fft of the surface
line = Line()
line.xValues = freqs
line.yValues = abs(FFT)
linePlot = Plot()
linePlot.add(line)
linePlot.xLimits = (0, .5)
linePlot.xLabel = "Freqs [Hz]"
linePlot.yLabel = "Amplitude"
linePlot.title = "Surface - FFT (zoomed)"
layout = PlotLayout()
layout.addPlot(linePlot)
#layout.plot()
layout.save("profile1_fft.png")
#pylab.subplot(212)
#pylab.plot(freqs,20*scipy.log10(FFT),'x')
#pylab.show()
# plot the filtered surface with the gradient
scatter1 = Scatter()
scatter1.xValues = x