def makePlot(label, tracks):
tracks = tracks.copy()
xBounds = [
NumericUtils.roundToOrder(tracks.length.min() - 0.05, -1, math.floor),
NumericUtils.roundToOrder(tracks.length.max() + 0.05, -1, math.ceil)]
yBounds = [
NumericUtils.roundToOrder(tracks.width.min() - 0.05, -1, math.floor),
NumericUtils.roundToOrder(tracks.width.max() + 0.05, -1, math.ceil)]
fig = plotlyTools.make_subplots(
rows=1, cols=2,
subplot_titles=('Length vs Width','Aspect Ratios'),
print_grid=False)
traces = []
for site in tracks.site.unique():
color = PlotConfigs.SITE_SPECS[site]['color']
siteSlice = tracks[tracks.site == site]
traces.append(plotlyGraph.Scatter(
name=site,
mode='markers',
xaxis='x1', yaxis='y1',
marker=plotlyGraph.Marker(color=color),
x=siteSlice.length,
y=siteSlice.width))
traces.append(plotlyGraph.Box(
name=site,
y=siteSlice.length/siteSlice.width,
marker=plotlyGraph.Marker(color=color),
xaxis='x2', yaxis='y2'))
fig['data'] += plotlyGraph.Data(traces)
fig['layout'].update(
title='%s Length & Width by Tracksite' % label,
xaxis1=plotlyGraph.XAxis(
title='Length (m)',
range=xBounds,
autorange=False ),
yaxis1=plotlyGraph.YAxis(
title='Width (m)',
range=yBounds,
autorange=False ))
url = plotly.plot(
filename='A16/%s-Length-Width' % label,
figure_or_data=fig,
auto_open=False)
print('PLOT[%s]:' % label, PlotlyUtils.toEmbedUrl(url))
def plotTraces(
plotType, label, traces, title, metadata, layoutOptions, suffix =None
):
suffix = '' if not suffix else ('-' + suffix)
url = plotly.plot(
filename=PlotlyUtils.getPlotlyFilename(
filename='{}{}'.format(label.replace(' ', '-'), suffix),
folder=PLOTLY_FOLDER),
figure_or_data=plotlyGraph.Figure(
data=plotlyGraph.Data(traces),
layout=_getLayout(
metadata=metadata,
title=title, **layoutOptions)),
auto_open=False)
print('{}[{}]: {}'.format(plotType, label, PlotlyUtils.toEmbedUrl(url)))
def makeStackedBars(label, columnName, tracks):
traces = []
xStart = tracks[columnName].min()
xEnd = tracks[columnName].max()
binDelta = 0.01
bins = [xStart]
while bins[-1] < xEnd:
bins.append(min(xEnd, bins[-1] + binDelta))
for site in tracks.site.unique():
color = PlotConfigs.SITE_SPECS[site]['color']
siteSlice = tracks[tracks.site == site]
data = np.histogram(a=siteSlice[columnName].values, bins=bins)
traces.append(plotlyGraph.Bar(
name=site,
x=data[1],
y=data[0],
marker=plotlyGraph.Marker(color=color) ))
data = plotlyGraph.Data(traces)
layout = plotlyGraph.Layout(
title='%s Distributions by Tracksite' % label,
barmode='stack',
xaxis=plotlyGraph.XAxis(
title='Track %s' % label,
range=[xStart - 0.01, xEnd + 0.01],
autorange=False ),
yaxis=plotlyGraph.YAxis(
title='Count',
autorange=True))
url = plotly.plot(
filename='A16/%s-Stacked-Distributions' % label,
figure_or_data=plotlyGraph.Figure(data=data, layout=layout),
auto_open=False)
print('STACK[%s]:' % label, PlotlyUtils.toEmbedUrl(url))
def plotComparison(df, key, label, binCount):
xMin = df[key].min()
xMax = df[key].max()
count = df.shape[0]
test = np.histogram(
a=df[key].values,
bins=np.linspace(xMin, xMax, 512))
cdf = 100.0*np.cumsum(test[0])/float(count)
for i in range(len(cdf)):
if cdf[i] >= 98.0:
xMax = test[1][i]
break
areaTraces = []
xValues = np.linspace(xMin, xMax, 64)
areaValues = np.zeros(len(xValues) - 1)
histTraces = []
bins = np.linspace(xMin, xMax, int(binCount))
index = 0
for sizeClass in PlotConfigs.SIZE_CLASSES:
color = sizeClass['color']
dataSlice = df[
(df['width'] >= sizeClass['range'][0]) &
(df['width'] < sizeClass['range'][1] )]
sliceCountLabel = locale.format(
'%d', int(dataSlice.shape[0]), grouping=True)
histValues = np.histogram(a=dataSlice[key].values, bins=bins)
histTraces.append(plotlyGraph.Bar(
name='%s (%s)' % (sizeClass['name'], sliceCountLabel),
x=100.0*histValues[1],
y=histValues[0],
marker=plotlyGraph.Marker(color=color) ))
histValues = np.histogram(a=dataSlice[key].values, bins=xValues)
values = 100.0*(dataSlice.shape[0] - np.cumsum(histValues[0]))/count
areaValues = np.add(areaValues, values)
areaTraces.append(plotlyGraph.Scatter(
name='%s (%s)' % (sizeClass['name'], sliceCountLabel),
x=100.0*histValues[1],
y=areaValues,
mode='lines',
fill='tozeroy' if index < 1 else 'tonexty',
line=plotlyGraph.Line(
width=1.0,
color=color) ))
index += 1
countLabel = locale.format('%d', count, grouping=True)
data = plotlyGraph.Data(histTraces)
layout = plotlyGraph.Layout(
title='Distribution of Track %s Deviations (%s Tracks)' % (
label, countLabel),
barmode='stack',
xaxis=plotlyGraph.XAxis(
title='Deviation (%)'),
yaxis=plotlyGraph.YAxis(
title='Frequency',
autorange=True))
url = plotly.plot(
filename=PlotlyUtils.getPlotlyFilename(
filename='%s' % label.replace(' ', '-'),
folder=PLOTLY_FOLDER),
figure_or_data=plotlyGraph.Figure(data=data, layout=layout),
auto_open=False)
print(
'COMPARE|HIST[%s]' % label,
'x:(%s, %s)' % (xMin, xMax),
PlotlyUtils.toEmbedUrl(url))
expected = []
for x in xValues:
expected.append(100.0*(1.0 - (norm.cdf(x) - norm.cdf(-x))))
areaTraces.append(plotlyGraph.Scatter(
name='Normal Threshold',
x=100.0*xValues,
y=expected,
mode='lines',
line=plotlyGraph.Line(
color='rgba(0, 0, 0, 0.75)',
dash='dash',
width=1.0) ))
data = plotlyGraph.Data(areaTraces)
layout = plotlyGraph.Layout(
title=('Inverse Cumulative Distribution of Track ' +
'%s Deviations (%s Tracks)') % (label, countLabel),
xaxis=plotlyGraph.XAxis(
title='Deviation (%)',
range=[100.0*xMin, 100.0*xMax],
autorange=False),
yaxis=plotlyGraph.YAxis(
title='Cumulative Remainder (%)',
range=[0, 100],
autorange=False))
url = plotly.plot(
filename=PlotlyUtils.getPlotlyFilename(
filename='%s-cdf-remainder' % label.replace(' ', '-'),
folder=PLOTLY_FOLDER),
figure_or_data=plotlyGraph.Figure(data=data, layout=layout),
auto_open=False)
print(
'COMPARE|AREA[%s]' % label,
'x:(%s, %s)' % (xMin, xMax),
PlotlyUtils.toEmbedUrl(url))
def makeHistograms(label, columnName, errorColumnName, tracks):
index = 0
histTraces = []
densityTraces = []
xStart = tracks[columnName].min()
xEnd = tracks[columnName].max()
sites = tracks.site.unique()
for site in sites:
index += 1
color = PlotConfigs.SITE_SPECS[site]['color']
siteSlice = tracks[tracks.site == site]
histTraces.append(plotlyGraph.Histogram(
name=site,
x=siteSlice[columnName],
autobinx=False,
xbins=plotlyGraph.XBins(
start=xStart,
end=xEnd,
size=0.01),
xaxis='x1',
yaxis='y%s' % int(index),
marker=plotlyGraph.Marker(color=color) ))
distributionValues = []
for i, row in siteSlice.iterrows():
distributionValues.append(NumericUtils.toValueUncertainty(
value=row[columnName],
uncertainty=row[errorColumnName]))
dd = DensityDistribution(values=distributionValues)
xValues = dd.getAdaptiveRange(10)
yValues = dd.createDistribution(xValues=xValues, scaled=True)
densityTraces.append(plotlyGraph.Scatter(
name=site,
x=xValues,
y=yValues,
xaxis='x1',
yaxis='y%s' % int(index),
mode='lines',
fill='tozeroy',
marker=plotlyGraph.Marker(color=color) ))
fig = plotlyTools.make_subplots(
rows=len(sites), cols=1,
shared_xaxes=True,
print_grid=False)
fig['data'] += plotlyGraph.Data(histTraces)
fig['layout'].update(title='%s Distributions by Tracksite' % label)
url = plotly.plot(
filename='A16/%s-Distributions' % label.replace(' ', '-'),
figure_or_data=fig,
auto_open=False)
print('HISTOGRAM[%s]:' % label, PlotlyUtils.toEmbedUrl(url))
fig = plotlyTools.make_subplots(
rows=len(sites), cols=1,
shared_xaxes=True,
print_grid=False)
fig['data'] += plotlyGraph.Data(densityTraces)
fig['layout'].update(
title='%s Distributions by Tracksite' % label,
xaxis1=plotlyGraph.XAxis(
autorange=False,
range=[xStart, xEnd]))
url = plotly.plot(
filename='A16/%s-Kernel-Distributions' % label.replace(' ', '-'),
figure_or_data=fig,
auto_open=False)
print('KERNEL-DENSITY[%s]:' % label, PlotlyUtils.toEmbedUrl(url))