apunkt/GPy
1
0
Fork 0
mirror of https://github.com/SheffieldML/GPy.git synced 2026-05-18 13:55:14 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

Use super().__init__ consistently, instead of sometimes calling base class __init__ directly

Browse source
This commit is contained in:
Julien Bect 2020-05-03 22:07:19 +02:00
parent 5d44eadfae
commit 5dd81288f2
19 changed files with 47 additions and 42 deletions
Download patch file Download diff file Expand all files Collapse all files

24
GPy/plotting/matplot_dep/visualize.py
View file

@ -36,7 +36,7 @@ class vpython_show(data_show):
"""
def __init__(self, vals, scene=None):
data_show.__init__(self, vals)
super(vpython_show, self).__init__(vals)
# If no axes are defined, create some.
if scene==None:
@ -54,7 +54,7 @@ class matplotlib_show(data_show):
the matplotlib_show class is a base class for all visualization methods that use matplotlib. It is initialized with an axis. If the axis is set to None it creates a figure window.
"""
def __init__(self, vals, axes=None):
data_show.__init__(self, vals)
super(matplotlib_show, self).__init__(vals)
# If no axes are defined, create some.
if axes==None:
@ -72,7 +72,7 @@ class vector_show(matplotlib_show):
vector elements alongside their indices.
"""
def __init__(self, vals, axes=None):
matplotlib_show.__init__(self, vals, axes)
super(vector_show, self).__init__(vals, axes)
#assert vals.ndim == 2, "Please give a vector in [n x 1] to plot"
#assert vals.shape[1] == 1, "only showing a vector in one dimension"
self.size = vals.size
@ -102,7 +102,7 @@ class lvm(matplotlib_show):
vals = model.X.values
if len(vals.shape)==1:
vals = vals[None,:]
matplotlib_show.__init__(self, vals, axes=latent_axes)
super(lvm, self).__init__(vals, axes=latent_axes)
if isinstance(latent_axes,mpl.axes.Axes):
self.cid = latent_axes.figure.canvas.mpl_connect('button_press_event', self.on_click)
@ -198,10 +198,10 @@ class lvm_subplots(lvm):
if i == self.nplots-1:
if self.nplots*2!=Model.input_dim:
latent_index = [i*2, i*2]
lvm.__init__(self, self.latent_vals, Model, data_visualize, axis, sense_axes, latent_index=latent_index)
super(lvm_subplots, self).__init__(self.latent_vals, Model, data_visualize, axis, sense_axes, latent_index=latent_index)
else:
latent_index = [i*2, i*2+1]
lvm.__init__(self, self.latent_vals, Model, data_visualize, axis, latent_index=latent_index)
super(lvm_subplots, self).__init__(self.latent_vals, Model, data_visualize, axis, latent_index=latent_index)
@ -223,7 +223,7 @@ class lvm_dimselect(lvm):
else:
self.sense_axes = sense_axes
self.labels = labels
lvm.__init__(self,vals,model,data_visualize,latent_axes,sense_axes,latent_index)
super(lvm_dimselect, self).__init__(vals,model,data_visualize,latent_axes,sense_axes,latent_index)
self.show_sensitivities()
print(self.latent_values)
print("use left and right mouse buttons to select dimensions")
@ -286,7 +286,7 @@ class image_show(matplotlib_show):
:type cmap: matplotlib.cm"""
def __init__(self, vals, axes=None, dimensions=(16,16), transpose=False, order='C', invert=False, scale=False, palette=[], preset_mean=0., preset_std=1., select_image=0, cmap=None):
matplotlib_show.__init__(self, vals, axes)
super(image_show, self).__init__(vals, axes)
self.dimensions = dimensions
self.transpose = transpose
self.order = order
@ -352,7 +352,7 @@ class mocap_data_show_vpython(vpython_show):
"""Base class for visualizing motion capture data using visual module."""
def __init__(self, vals, scene=None, connect=None, radius=0.1):
vpython_show.__init__(self, vals, scene)
super(mocap_data_show_vpython, self).__init__(vals, scene)
self.radius = radius
self.connect = connect
self.process_values()
@ -412,7 +412,7 @@ class mocap_data_show(matplotlib_show):
if axes==None:
fig = plt.figure()
axes = fig.add_subplot(111, projection='3d', aspect='equal')
matplotlib_show.__init__(self, vals, axes)
super(mocap_data_show, self).__init__(vals, axes)
self.color = color
self.connect = connect
@ -496,7 +496,7 @@ class stick_show(mocap_data_show):
def __init__(self, vals, connect=None, axes=None):
if len(vals.shape)==1:
vals = vals[None,:]
mocap_data_show.__init__(self, vals, axes=axes, connect=connect)
super(stick_show, self).__init__(vals, axes=axes, connect=connect)
def process_values(self):
self.vals = self.vals.reshape((3, self.vals.shape[1]/3)).T
@ -515,7 +515,7 @@ class skeleton_show(mocap_data_show):
self.skel = skel
self.padding = padding
connect = skel.connection_matrix()
mocap_data_show.__init__(self, vals, axes=axes, connect=connect, color=color)
super(skeleton_show, self).__init__(vals, axes=axes, connect=connect, color=color)
def process_values(self):
"""Takes a set of angles and converts them to the x,y,z coordinates in the internal prepresentation of the class, ready for plotting.