def as_html(data, fields):
"""Create HTML representation of a plot
Parameters
----------
data : Plot instance
The plot object to display.
fields : sequence of strings
The fields of data to use.
"""
# Would like a nicer way to set the summary label, but without
# adding a per-class field for this it is safest just to use
# the object name.
meta = []
for name in fields:
# skip records which we don't know about. This indicates
# an error in the calling code, but we don't want it to
# stop the generation of the HTML.
#
try:
val = getattr(data, name)
except Exception as e:
lgr.debug("Skipping field {}: {}".format(name, e))
continue
meta.append((name, val))
ls = [formatting.html_section(meta, open_block=True,
summary=type(data).__name__)]
return formatting.html_from_sections(data, ls)
def html_data1dint(data):
"""HTML representation: Data1DInt
If have matplotlib then plot the data, otherwise summarize it.
"""
from sherpa.plot import DataHistogramPlot, backend
dtype = type(data).__name__
plotter = DataHistogramPlot()
plotter.prepare(data)
summary = '{} Plot'.format(dtype)
try:
out = backend.as_html_plot(plotter, summary)
except AttributeError:
out = None
if out is not None:
return formatting.html_from_sections(data, [out])
# Summary properties
#
meta = []
if data.name is not None and data.name != '':
meta.append(('Identifier', data.name))
meta.append(('Number of bins', len(data.xlo)))
# Should this only be displayed if a filter has been applied?
#
fexpr = data.get_filter_expr()
nbins = data.get_dep(filter=True).size
meta.append(('Using', '{} with {} bins'.format(fexpr, nbins)))
# Rely on the _fields ordering, ending at staterror
for f in data._fields[1:]:
if f == 'staterror':
break
meta.append((f.upper(), getattr(data, f)))
if data.staterror is not None:
meta.append(('Statistical error', data.staterror))
if data.syserror is not None:
meta.append(('Systematic error', data.syserror))
ls = [formatting.html_section(meta, summary=dtype + ' Summary',
open_block=True)]
return formatting.html_from_sections(data, ls)
def html_data2d(data):
"""HTML representation: Data2D and derived classes
"""
dtype = type(data).__name__
"""
It would be nice to plot the plot, but there are several questions to
resolve, such as:
- do we plot each point (okay for sparse data) or binned
- simple binning, adaptive binning, hexagonal binning?
- do we just pick a number, like 100, to bin the data to
"""
# Summary properties
#
meta = []
if data.name is not None and data.name != '':
meta.append(('Identifier', data.name))
# NOTE: shape is not well defined, is it x by y or
# the inverse, so I am not going to display it at the
# moment.
# if data.shape != None:
# meta.append(('Shape', data.shape))
meta.append(('Number of bins', len(data.y)))
# Rely on the _fields ordering, ending at shape
for f in data._fields[1:]:
if f == 'shape':
break
meta.append((f.upper(), getattr(data, f)))
if data.staterror is not None:
meta.append(('Statistical error', data.staterror))
if data.syserror is not None:
meta.append(('Systematic error', data.syserror))
ls = [formatting.html_section(meta, summary=dtype + ' Summary',
open_block=True)]
return formatting.html_from_sections(data, ls)