def ply_fig(ts, points=False, color='jet', **kwds):
""" Convert a timespectra to plotly Figure. Figures can be then directly
plotted with plotly.iplot(figure) in the notebook. Use the layout keyword
to specify layout parameters; all other keywords are interpreted as line style
keywords (color
Parameters
----------
points: bool
If true, scatter plot; else, lineplots
color: str
Any valid matplotlib color or colormap.
layout: dict
Dictionary of keywords that go into layout.
"""
data = grobs.Data()
layoutkwds = kwds.pop('layout', {})
lout = layout(ts, **layoutkwds)
# List of colors, either single color or color map
try:
cmapper = put.cmget(color) #Validate color map
except AttributeError:
cmapper = [color for i in range(len(ts.columns))]
else:
cmapper = put._df_colormapper(ts, color, axis=0)
# Map colors to rgb
cmapper = map(put.to_normrgb, cmapper)
# Scale by 255 and string format for plotly
def _rgbplotlycolor(rgb):
r, g, b = rgb
return 'rgb(%s, %s, %s)' % (255.0 * r, 255.0 * g, 255.0 * b)
cmapper = map(_rgbplotlycolor, cmapper)
if points:
tracefcn = make_pointtrace
else:
tracefcn = make_linetrace
for idx, clabel in enumerate(ts):
trace = tracefcn(
x=np.array(
ts.index), # Not necessary to force to np.array.dtype(float)
y=np.array(ts[ts.columns[idx]]),
name=clabel,
color=cmapper[idx], #marker color
**kwds)
data.append(trace)
return grobs.Figure(data=data, layout=lout)
def ply_fig(ts, points=False, color='jet', **kwds):
""" Convert a timespectra to plotly Figure. Figures can be then directly
plotted with plotly.iplot(figure) in the notebook. Use the layout keyword
to specify layout parameters; all other keywords are interpreted as line style
keywords (color
Parameters
----------
points: bool
If true, scatter plot; else, lineplots
color: str
Any valid matplotlib color or colormap.
layout: dict
Dictionary of keywords that go into layout.
"""
data = grobs.Data()
layoutkwds = kwds.pop('layout', {})
lout = layout(ts, **layoutkwds)
# List of colors, either single color or color map
try:
cmapper = put.cmget(color) #Validate color map
except AttributeError:
cmapper = [color for i in range(len(ts.columns))]
else:
cmapper = put._df_colormapper(ts, color, axis=0)
# Map colors to rgb
cmapper = map(put.to_normrgb, cmapper)
# Scale by 255 and string format for plotly
def _rgbplotlycolor(rgb):
r,g,b = rgb
return 'rgb(%s, %s, %s)' % (255.0*r, 255.0*g, 255.0*b)
cmapper = map(_rgbplotlycolor, cmapper)
if points:
tracefcn = make_pointtrace
else:
tracefcn = make_linetrace
for idx, clabel in enumerate(ts):
trace = tracefcn(
x = np.array(ts.index), # Not necessary to force to np.array.dtype(float)
y = np.array(ts[ts.columns[idx]]),
name=clabel,
color=cmapper[idx], #marker color
**kwds
)
data.append(trace)
return grobs.Figure(data=data, layout=lout)
def timeplot(ts, **pltkwds):
''' Sends transposed dataframe into _genplot(); however, this is only useful if one wants to plot
every single row in a dataframe. For ranges of rows, see spec_utilities.wavelegnth_slices and
range_timeplot() below.'''
pltkwds['color']=pltkwds.pop('color', _df_colormapper(ts, 'jet', axis=1) )
pltkwds['legend']=pltkwds.pop('legend', True) #Turn legend on
xlabel=pltkwds.pop('xlabel', ts.full_timeunit)
ylabel=pltkwds.pop('ylabel', ts.full_iunit)
title=pltkwds.pop('title', str(ts.name) )
return _genplot(ts.transpose(), xlabel, ylabel, title, **pltkwds)
def timeplot(df, **pltkwds):
''' Sends transposed dataframe into _genplot(); however, this is only useful if one wants to plot
every single row in a dataframe. For ranges of rows, see spec_utilities.wavelegnth_slices and
range_timeplot() below.'''
pltkwds['color']=pltkwds.pop('color', _df_colormapper(df, 'jet', axis=1) )
pltkwds['legend']=pltkwds.pop('legend', True) #Turn legend on
pltkwds['ylabel_def']='Intensity'
pltkwds['xlabel_def']='Time'
pltkwds['title_def']='Intensity vs. Time Plot'
return _genplot(df.transpose(), **pltkwds)
