def export_json(self, subplot, line):
plot = Plot.frompref()
sp = plot.subplots[int(subplot) - 1]
line = sp.lines[int(line)]
web.setmime(web.mime.csv)
io = StringIO()
line.export_json(io, plot.startdate, plot.enddate)
io.seek(0)
return io
def linedatasets_json(self, subplot, line):
web.setmime(web.mime.json)
plot = Plot.frompref()
sp = plot.subplots[int(subplot) - 1]
line = sp.lines[int(line)]
session = db.Session()
datasets = line.getdatasets(session)
res = web.as_json(datasets)
session.close()
return res
def exportall_csv(self, tolerance):
plot = Plot.frompref()
# datasetids=[]
# session=db.Session()
# for sp in plot.subplots:
# for line in sp.lines:
# datasetids.extend(ds.id for ds in line.getdatasets(session))
# session.close()
lines = []
for sp in plot.subplots:
lines.extend(sp.lines)
stream = StringIO()
from tools.exportdatasets import exportLines
exportLines(stream, lines, web.conv(float, tolerance, 60))
web.setmime(web.mime.csv)
return stream.getvalue()
def RegularTimeseries_csv(self, tolerance=12, interpolation=''):
plot = Plot.frompref()
datasetids = []
session = db.Session()
lines = []
for sp in plot.subplots:
lines.extend(sp.lines)
for line in sp.lines:
datasetids.extend(ds.id for ds in line.getdatasets(session))
session.close()
stream = StringIO()
from tools.ExportRegularData import createPandaDfs
# explicit decode() for byte to string
stream.write(codecs.BOM_UTF8.decode())
createPandaDfs(lines,
plot.startdate,
plot.enddate,
stream,
interpolationtime=interpolation,
tolerance=float(tolerance))
web.setmime(web.mime.csv)
return stream.getvalue()
def image_pdf(self, **kwargs):
web.setmime(web.mime.pdf)
plot = Plot.frompref()
if not plot:
raise web.HTTPRedirect('/plot?error=No plot available')
return plot.draw(format='pdf')
def listplotfiles(self):
web.setmime(web.mime.json)
return web.as_json(Plot.listdir())