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[plotting] restructuring more and more

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This commit is contained in:
mzwiessele 2015-10-04 12:31:22 +01:00
parent c07f3dbe98
commit 831e032ade
18 changed files with 330 additions and 272 deletions
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27
GPy/plotting/gpy_plot/data_plots.py
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@ -27,10 +27,8 @@
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#===============================================================================
from . import pl
import numpy as np
from . import pl
from .plot_util import get_x_y_var, get_free_dims, get_which_data_ycols,\
get_which_data_rows, update_not_existing_kwargs, helper_predict_with_model
@ -47,12 +45,14 @@ def _plot_data(self, canvas, which_data_rows='all',
plots = {}
plots['dataplot'] = []
plots['xerrorplot'] = []
if X_variance is not None: plots['xerrorplot'] = []
#one dimensional plotting
if len(free_dims) == 1:
for d in ycols:
update_not_existing_kwargs(plot_kwargs, pl.defaults.data_1d)
update_not_existing_kwargs(plot_kwargs, pl.defaults.data_1d) # @UndefinedVariable
plots['dataplot'].append(pl.scatter(canvas, X[rows, free_dims], Y[rows, d], **plot_kwargs))
if X_variance is not None:
update_not_existing_kwargs(error_kwargs, pl.defaults.xerrorbar)
@ -62,7 +62,7 @@ def _plot_data(self, canvas, which_data_rows='all',
#2D plotting
elif len(free_dims) == 2:
for d in ycols:
update_not_existing_kwargs(plot_kwargs, pl.defaults.data_2d)
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]],
c=Y[rows, d], vmin=Y.min(), vmax=Y.max(), **plot_kwargs))
elif len(free_dims) == 0:
@ -84,7 +84,7 @@ def plot_data(self, which_data_rows='all',
:param which_data_rows: which of the training data to plot (default all)
:type which_data_rows: 'all' or a slice object to slice self.X, self.Y
:param which_data_ycols: when the data has several columns (independant outputs), only plot these
:type which_data_rows: 'all' or a list of integers
:type which_data_ycols: 'all' or a list of integers
:param visible_dims: an array specifying the input dimensions to plot (maximum two)
:type visible_dims: a numpy array
:param dict error_kwargs: kwargs for the error plot for the plotting library you are using
@ -94,7 +94,7 @@ def plot_data(self, which_data_rows='all',
"""
canvas, kwargs = pl.get_new_canvas(plot_kwargs)
plots = _plot_data(self, canvas, which_data_rows, which_data_ycols, visible_dims, error_kwargs, **kwargs)
return pl.show_canvas(canvas, plots)
return pl.show_canvas(canvas, plots, xlabel='x', ylabel='y', legend='dataplot')
def plot_inducing(self, visible_dims=None, **plot_kwargs):
@ -116,11 +116,11 @@ def _plot_inducing(self, canvas, visible_dims, **plot_kwargs):
#one dimensional plotting
if len(free_dims) == 1:
update_not_existing_kwargs(plot_kwargs, pl.defaults.inducing_1d)
update_not_existing_kwargs(plot_kwargs, pl.defaults.inducing_1d) # @UndefinedVariable
plots['inducing'] = pl.plot_axis_lines(canvas, Z[:, free_dims], **plot_kwargs)
#2D plotting
elif len(free_dims) == 2:
update_not_existing_kwargs(plot_kwargs, pl.defaults.inducing_2d)
update_not_existing_kwargs(plot_kwargs, pl.defaults.inducing_2d) # @UndefinedVariable
plots['inducing'] = pl.scatter(canvas, Z[:, free_dims[0]], Z[:, free_dims[1]],
**plot_kwargs)
elif len(free_dims) == 0:
@ -184,15 +184,16 @@ def _plot_errorbars_trainset(self, canvas,
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, (0, 100),
apply_link, (2.5, 97.5),
ycols, predict_kw)
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]]),
**plot_kwargs))
return dict(yerrorbars=plots)
else:
pass #Nothing to plot!
else:
raise NotImplementedError("Cannot plot in more then one dimension.")
return plots
return dict(yerrorbars=plots)