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[testing] updates again and plotly is going forward

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mzwiessele 2015-10-07 19:03:03 +01:00
parent 78128ea218
commit ccb6ebcadd
15 changed files with 409 additions and 309 deletions
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48
GPy/plotting/gpy_plot/data_plots.py
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@ -56,7 +56,7 @@ def plot_data(self, which_data_rows='all',
"""
canvas, plot_kwargs = pl.new_canvas(projection=projection, **plot_kwargs)
plots = _plot_data(self, canvas, which_data_rows, which_data_ycols, visible_dims, projection, label, **plot_kwargs)
return pl.show_canvas(canvas, plots)
return pl.add_to_canvas(canvas, plots)
def _plot_data(self, canvas, which_data_rows='all',
which_data_ycols='all', visible_dims=None,
@ -81,12 +81,12 @@ def _plot_data(self, canvas, which_data_rows='all',
for d in ycols:
update_not_existing_kwargs(plot_kwargs, pl.defaults.data_2d) # @UndefinedVariable
plots['dataplot'].append(pl.scatter(canvas, X[rows, free_dims[0]], X[rows, free_dims[1]],
color=Y[rows, d], vmin=Y.min(), vmax=Y.max(), label=label, **plot_kwargs))
color=Y[rows, d], label=label, **plot_kwargs))
else:
for d in ycols:
update_not_existing_kwargs(plot_kwargs, pl.defaults.data_2d) # @UndefinedVariable
plots['dataplot'].append(pl.scatter(canvas, X[rows, free_dims[0]], X[rows, free_dims[1]],
Z=Y[rows, d], vmin=Y.min(), color=Y[rows, d], vmax=Y.max(), label=label, **plot_kwargs))
Z=Y[rows, d], color=Y[rows, d], label=label, **plot_kwargs))
elif len(free_dims) == 0:
pass #Nothing to plot!
else:
@ -117,9 +117,9 @@ def plot_data_error(self, which_data_rows='all',
:returns list: of plots created.
"""
canvas, error_kwargs = pl.new_canvas(projection=='3d', **error_kwargs)
canvas, error_kwargs = pl.new_canvas(projection=projection, **error_kwargs)
plots = _plot_data_error(self, canvas, which_data_rows, which_data_ycols, visible_dims, projection, label, **error_kwargs)
return pl.show_canvas(canvas, plots)
return pl.add_to_canvas(canvas, plots)
def _plot_data_error(self, canvas, which_data_rows='all',
which_data_ycols='all', visible_dims=None,
@ -167,7 +167,7 @@ def plot_inducing(self, visible_dims=None, projection='2d', label=None, **plot_k
"""
canvas, kwargs = pl.new_canvas(projection=projection, **plot_kwargs)
plots = _plot_inducing(self, canvas, visible_dims, projection, label, **kwargs)
return pl.show_canvas(canvas, plots)
return pl.add_to_canvas(canvas, plots)
def _plot_inducing(self, canvas, visible_dims, projection, label, **plot_kwargs):
if visible_dims is None:
@ -220,7 +220,7 @@ def plot_errorbars_trainset(self, which_data_rows='all',
canvas, kwargs = pl.new_canvas(projection=projection, **plot_kwargs)
plots = _plot_errorbars_trainset(self, canvas, which_data_rows, which_data_ycols,
fixed_inputs, plot_raw, apply_link, label, projection, predict_kw, **kwargs)
return pl.show_canvas(canvas, plots)
return pl.add_to_canvas(canvas, plots)
def _plot_errorbars_trainset(self, canvas,
which_data_rows='all', which_data_ycols='all',
@ -245,25 +245,31 @@ def _plot_errorbars_trainset(self, canvas,
if len(free_dims)<=2:
update_not_existing_kwargs(plot_kwargs, pl.defaults.yerrorbar)
if len(free_dims)==1:
if predict_kw is None:
if predict_kw is None:
predict_kw = {}
if 'Y_metadata' not in predict_kw:
predict_kw['Y_metadata'] = self.Y_metadata or {}
_, percs, _ = helper_predict_with_model(self, Xgrid, plot_raw,
apply_link, (2.5, 97.5),
ycols, predict_kw)
if 'Y_metadata' not in predict_kw:
predict_kw['Y_metadata'] = self.Y_metadata or {}
mu, percs, _ = helper_predict_with_model(self, Xgrid, plot_raw,
apply_link, (2.5, 97.5),
ycols, predict_kw)
if len(free_dims)==1:
for d in ycols:
plots.append(pl.yerrorbar(canvas, X[rows,free_dims[0]], Y[rows,d],
np.vstack([Y[rows,d]-percs[0][rows,d], percs[1][rows,d]-Y[rows,d]]),
plots.append(pl.yerrorbar(canvas, X[rows,free_dims[0]], mu[rows,d],
np.vstack([mu[rows, d] - percs[0][rows, d], percs[1][rows, d] - mu[rows,d]]),
label=label,
**plot_kwargs))
elif len(free_dims) == 2:
plots.append(pl.yerrorbar(canvas, X[rows,free_dims[0]], X[rows,free_dims[1]],
np.vstack([Y[rows,d]-percs[0][rows,d], percs[1][rows,d]-Y[rows,d]]),
Y[rows,d],
label=label,
**plot_kwargs))
for d in ycols:
plots.append(pl.yerrorbar(canvas, X[rows,free_dims[0]], X[rows,free_dims[1]],
np.vstack([mu[rows, d] - percs[0][rows, d], percs[1][rows, d] - mu[rows,d]]),
color=Y[rows,d],
label=label,
**plot_kwargs))
plots.append(pl.xerrorbar(canvas, X[rows,free_dims[0]], X[rows,free_dims[1]],
np.vstack([mu[rows, d] - percs[0][rows, d], percs[1][rows, d] - mu[rows,d]]),
color=Y[rows,d],
label=label,
**plot_kwargs))
pass #Nothing to plot!
else:
raise NotImplementedError("Cannot plot in more then one dimension.")