def bounding_box(self, data, ax, label, bBoundingBoxes, bLabels):
"""Draw bounding box around data."""
data = np.array(data)
width = max(data[:, 0]) - min(data[:, 0])
height = max(data[:, 1]) - min(data[:, 1])
r = Rectangle((min(data[:, 0]), min(data[:, 1])), width, height)
if bBoundingBoxes:
ax.add_artist(r)
r.set_clip_box(ax.bbox)
r.set_alpha(0.1)
r.set_facecolor((0.5, 0.5, 0.5))
if bLabels:
ax.annotate(label,
xy=(min(data[:, 0]), max(data[:, 1])),
xytext=(0, 0),
textcoords='offset points',
ha='right',
va='bottom',
bbox=dict(boxstyle='round,pad=0.5',
fc=(0.5, 0.5, 0.5),
alpha=0.1))
def draw_box(x1, x2, y1, y2, ax, col):
c = array([[x1], [y1]])
rect = Rectangle(c, width=x2 - x1, height=y2 - y1, angle=0)
rect.set_facecolor(array([0.4, 0.3, 0.6]))
ax.add_patch(rect)
rect.set_clip_box(ax.bbox)
rect.set_alpha(0.7)
rect.set_facecolor(col)
def highlight_artist(self, val, artist=None):
# print val, artist
figure = self.get_figpage()._artists[0]
ax = self.get_figaxes()
if artist is None:
alist = self._artists
else:
alist = artist
if val == True:
container = self.get_container()
if container is None: return
de = self.get_data_extent()
from ifigure.matplotlib_mod.art3d_gl import AxesImageGL
if isinstance(alist[0], AxesImageGL):
hl = alist[0].add_hl_mask()
for item in hl:
alist[0].figobj_hl.append(item)
# hl = alist[0].make_hl_artist(container)
# rect_alpha = 0.0
else:
x = [de[0], de[1], de[1], de[0], de[0]]
y = [de[2], de[2], de[3], de[3], de[2]]
hl = container.plot(x,
y,
marker='s',
color='k',
linestyle='None',
markerfacecolor='None',
markeredgewidth=0.5,
scalex=False,
scaley=False)
rect_alpha = 0.3
hlp = Rectangle((de[0], de[2]),
de[1] - de[0],
de[3] - de[2],
alpha=rect_alpha,
facecolor='k',
figure=figure,
transform=container.transData)
if ax is not None:
x0, y0 = ax._artists[0].transAxes.transform((0, 0))
x1, y1 = ax._artists[0].transAxes.transform((1, 1))
bbox = Bbox([[x0, y0], [x1, y1]])
hlp.set_clip_box(bbox)
hlp.set_clip_on(True)
figure.patches.append(hlp)
for item in (hl[0], hlp):
alist[0].figobj_hl.append(item)
else:
for a in alist:
if len(a.figobj_hl) != 0:
a.figobj_hl[0].remove()
figure.patches.remove(a.figobj_hl[1])
a.figobj_hl = []
def draw_filled_rectangle(self, x, y, width, height):
r = Rectangle((x, y),
width,
height,
self.angle,
color=self.draw_color,
fill=True)
r.set_clip_box(self.a.bbox)
self.a.add_artist(r)
def highlight_artist(self, val, artist=None):
# print val, artist
figure=self.get_figpage()._artists[0]
ax = self.get_figaxes()
if artist is None:
alist=self._artists
else:
alist=artist
if val == True:
container = self.get_container()
if container is None: return
de = self.get_data_extent()
from ifigure.matplotlib_mod.art3d_gl import AxesImageGL
if isinstance(alist[0], AxesImageGL):
hl = alist[0].add_hl_mask()
for item in hl:
alist[0].figobj_hl.append(item)
# hl = alist[0].make_hl_artist(container)
# rect_alpha = 0.0
else:
x=[de[0],de[1],de[1],de[0],de[0]]
y=[de[2],de[2],de[3],de[3],de[2]]
hl= container.plot(x, y, marker='s',
color='k', linestyle='None',
markerfacecolor='None',
markeredgewidth = 0.5,
scalex=False, scaley=False)
rect_alpha = 0.3
hlp = Rectangle((de[0],de[2]),
de[1]-de[0],
de[3]-de[2],
alpha=rect_alpha, facecolor='k',
figure = figure,
transform= container.transData)
if ax is not None:
x0, y0 = ax._artists[0].transAxes.transform((0,0))
x1, y1 = ax._artists[0].transAxes.transform((1,1))
bbox = Bbox([[x0,y0],[x1,y1]])
hlp.set_clip_box(bbox)
hlp.set_clip_on(True)
figure.patches.append(hlp)
for item in (hl[0], hlp):
alist[0].figobj_hl.append(item)
else:
for a in alist:
if len(a.figobj_hl) != 0:
a.figobj_hl[0].remove()
figure.patches.remove(a.figobj_hl[1])
a.figobj_hl=[]
def on_press(event):
global id_motion, xs, ys, r
print 'INAXES: ', event.inaxes
if event.inaxes!=ax: return
xs, ys = event.xdata, event.ydata
print 'PRESS button=%d, x=%d, y=%d, xdata=%f, ydata=%f' % (
event.button, event.x, event.y, event.xdata, event.ydata)
r = Rectangle(xy=(xs,ys), height=0, width=0, fill=False, lw=2, alpha=0.2)
ax.add_artist(r)
r.set_clip_box(ax.bbox)
draw()
id_motion = fig.canvas.mpl_connect('motion_notify_event', on_motion)
def on_press(event):
global id_motion, xs, ys, r
print 'INAXES: ', event.inaxes
if event.inaxes != ax: return
xs, ys = event.xdata, event.ydata
print 'PRESS button=%d, x=%d, y=%d, xdata=%f, ydata=%f' % (
event.button, event.x, event.y, event.xdata, event.ydata)
r = Rectangle(xy=(xs, ys), height=0, width=0, fill=False, lw=2, alpha=0.2)
ax.add_artist(r)
r.set_clip_box(ax.bbox)
draw()
id_motion = fig.canvas.mpl_connect('motion_notify_event', on_motion)
class rectSelection(GuiSelection):
"""Interactive selection of a rectangular region on the axis.
Used by hist2d_alex().
"""
def on_press_draw(self):
if 'r' in self.__dict__:
self.r.set_height(0)
self.r.set_width(0)
self.r.set_xy((self.xs, self.ys))
self.e.height = 0
self.e.width = 0
self.e.center = (self.xs, self.ys)
else:
self.r = Rectangle(xy=(self.xs, self.ys),
height=0,
width=0,
fill=False,
lw=2,
alpha=0.5,
color='blue')
self.e = Ellipse(xy=(self.xs, self.ys),
height=0,
width=0,
fill=False,
lw=2,
alpha=0.6,
color='blue')
self.ax.add_artist(self.r)
self.ax.add_artist(self.e)
self.r.set_clip_box(self.ax.bbox)
self.r.set_zorder(10)
self.e.set_clip_box(self.ax.bbox)
self.e.set_zorder(10)
def on_motion_draw(self):
self.r.set_height(self.ye - self.ys)
self.r.set_width(self.xe - self.xs)
self.e.height = (self.ye - self.ys)
self.e.width = (self.xe - self.xs)
self.e.center = (np.mean([self.xs,
self.xe]), np.mean([self.ys, self.ye]))
self.fig.canvas.draw()
def on_release_print(self):
# This is the only custom method for hist2d_alex()
E1, E2 = min((self.xs, self.xe)), max((self.xs, self.xe))
S1, S2 = min((self.ys, self.ye)), max((self.ys, self.ye))
self.selection = dict(E1=E1, E2=E2, S1=S1, S2=S2)
pprint("Selection: \nE1=%.2f, E2=%.2f, S1=%.2f, S2=%.2f\n" %\
(E1,E2,S1,S2))
def plot_rectangle(bboxes, ax, step, c='#ff7f0e'):
for bbox in bboxes[bboxes['ts'] % step == 0]:
s_phi_offset, c_phi_offset = np.sin(bbox['orientation']), np.cos(bbox['orientation'])
rot = np.array([[c_phi_offset, - s_phi_offset], [s_phi_offset, c_phi_offset]])
offset_xy = np.dot(rot, 0.5 * bbox['dimension'])
r = Rectangle(xy=bbox['center_xy'] - offset_xy, width=bbox['dimension'][0], height=bbox['dimension'][1],
angle=np.rad2deg(bbox['orientation']))
ax.add_artist(r)
r.set_clip_box(ax.bbox)
r.set_alpha(0.8)
r.set_facecolor('none')
r.set_edgecolor(c)
def highlight_artist(self, val, artist=None):
figure = self.get_figpage()._artists[0]
ax = self.get_figaxes()
if val:
if len(self._artists[0].figobj_hl) != 0:
return
box = self.get_artist_extent_all()
self._artist_extent = box
if box[0] is None:
return
x = [box[0], box[0], box[1], box[1], box[0]]
y = [box[3], box[2], box[2], box[3], box[3]]
hl = Line2D(x,
y,
marker='s',
color='k',
linestyle='None',
markerfacecolor='k',
markeredgewidth=0.5,
figure=figure,
alpha=0.3)
figure.lines.append(hl)
xy = (box[0], box[2])
w = box[1] - box[0]
h = box[3] - box[2]
hlp = Rectangle(xy, w, h, alpha=0.3, facecolor='k', figure=figure)
if ax is not None:
x0, y0 = ax._artists[0].transAxes.transform((0, 0))
x1, y1 = ax._artists[0].transAxes.transform((1, 1))
bbox = Bbox([[x0, y0], [x1, y1]])
hlp.set_clip_box(bbox)
hlp.set_clip_on(True)
figure.patches.append(hlp)
# if ax is not None and ax.get_3d():
# import mpl_toolkits.mplot3d.art3d as art3d
# art3d.patch_2d_to_3d(hl)
# if len(ax._artists) != 0:
# a.axes = self.get_figaxes()._artists[0]
self._artists[0].figobj_hl.extend([hl, hlp])
else:
if len(self._artists[0].figobj_hl) == 2:
figure.lines.remove(self._artists[0].figobj_hl[0])
figure.patches.remove(self._artists[0].figobj_hl[1])
self._artists[0].figobj_hl = []
def boundingBox(self, data, ax, label, bBoundingBoxes, bLabels): ''' Draw bounding box around data.''' data = np.array(data) width = max(data[:,0]) - min(data[:,0]) height = max(data[:,1]) - min(data[:,1]) r = Rectangle((min(data[:,0]), min(data[:,1])), width, height) if bBoundingBoxes: ax.add_artist(r) r.set_clip_box(ax.bbox) r.set_alpha(0.1) r.set_facecolor((0.5, 0.5, 0.5)) if bLabels: ax.annotate(label, xy = (min(data[:,0]), max(data[:,1])), xytext = (0, 0), textcoords = 'offset points', ha = 'right', va = 'bottom', bbox = dict(boxstyle = 'round,pad=0.5', fc = (0.5, 0.5, 0.5), alpha = 0.1))
def visualize_generation(self, generation):
"""
Draw each ab combination color and size coded
:param generation:
:param ax:
:return:
"""
fig, ax = plt.subplots()
# ax.clear()
for ind in range(len(self.ga_solver.population[generation])):
child = self.ga_solver.population[generation][ind]
xy = self._ab_to_xy(child)
rect = Rectangle(xy=xy, width=0.5, height=0.5, angle=90)
ax.add_artist(rect)
rect.set_clip_box(ax.bbox)
# alpha = float(child[3]) / ANTIBODY_CNT
# rgb = [float(child[0])/ANTIBODY_CNT, float(child[1])/ANTIBODY_CNT, float(child[2])/ANTIBODY_CNT/ ANTIBODY_CNT]
#
# rect.set_alpha(alpha)
# rect.set_facecolor(rgb)
fitness = self.ga_solver.get_fitness_value(child)
if fitness > 0.5:
rect.set_facecolor('r')
else:
rect.set_facecolor('b')
rect.set_width(fitness * 100)
rect.set_height(fitness * 100)
ax.set_xlim(
0, self.ga_solver.antibody_cnt * self.ga_solver.antibody_cnt + 10)
ax.set_ylim(
0, self.ga_solver.antibody_cnt * self.ga_solver.antibody_cnt + 10)
plt.show()
plt.pause(1)
plt.close()
class rectSelection(GuiSelection):
"""Interactive selection of a rectangular region on the axis.
Used by hist2d_alex().
"""
def on_press_draw(self):
if 'r' in self.__dict__:
self.r.set_height(0)
self.r.set_width(0)
self.r.set_xy((self.xs, self.ys))
self.e.height = 0
self.e.width = 0
self.e.center = (self.xs, self.ys)
else:
self.r = Rectangle(xy=(self.xs, self.ys), height=0, width=0,
fill=False, lw=2, alpha=0.5, color='blue')
self.e = Ellipse(xy=(self.xs, self.ys), height=0, width=0,
fill=False, lw=2, alpha=0.6, color='blue')
self.ax.add_artist(self.r)
self.ax.add_artist(self.e)
self.r.set_clip_box(self.ax.bbox)
self.r.set_zorder(10)
self.e.set_clip_box(self.ax.bbox)
self.e.set_zorder(10)
def on_motion_draw(self):
self.r.set_height(self.ye - self.ys)
self.r.set_width(self.xe - self.xs)
self.e.height = (self.ye - self.ys)
self.e.width = (self.xe - self.xs)
self.e.center = (np.mean([self.xs, self.xe]),
np.mean([self.ys, self.ye]))
self.fig.canvas.draw()
def on_release_print(self):
# This is the only custom method for hist2d_alex()
E1, E2 = min((self.xs, self.xe)), max((self.xs, self.xe))
S1, S2 = min((self.ys, self.ye)), max((self.ys, self.ye))
self.selection = dict(E1=E1, E2=E2, S1=S1, S2=S2)
pprint("Selection: \nE1=%.2f, E2=%.2f, S1=%.2f, S2=%.2f\n" %\
(E1,E2,S1,S2))
def highlight_artist(self, val, artist=None):
figure=self.get_figpage()._artists[0]
ax = self.get_figaxes()
if val:
if len(self._artists[0].figobj_hl) != 0: return
box = self.get_artist_extent_all()
self._artist_extent = box
if box[0] is None: return
x = [box[0], box[0], box[1], box[1], box[0]]
y = [box[3], box[2], box[2], box[3], box[3]]
hl= Line2D(x, y, marker='s',
color='k', linestyle='None',
markerfacecolor='k',
markeredgewidth = 0.5,
figure=figure, alpha=0.3)
figure.lines.append(hl)
xy = (box[0], box[2])
w = box[1] - box[0]
h = box[3] - box[2]
hlp = Rectangle(xy, w, h, alpha=0.3, facecolor='k',
figure = figure)
if ax is not None:
x0, y0 = ax._artists[0].transAxes.transform((0,0))
x1, y1 = ax._artists[0].transAxes.transform((1,1))
bbox = Bbox([[x0,y0],[x1,y1]])
hlp.set_clip_box(bbox)
hlp.set_clip_on(True)
figure.patches.append(hlp)
# if ax is not None and ax.get_3d():
# import mpl_toolkits.mplot3d.art3d as art3d
# art3d.patch_2d_to_3d(hl)
# if len(ax._artists) != 0:
# a.axes = self.get_figaxes()._artists[0]
self._artists[0].figobj_hl.extend([hl, hlp])
else:
if len(self._artists[0].figobj_hl) == 2:
figure.lines.remove(self._artists[0].figobj_hl[0])
figure.patches.remove(self._artists[0].figobj_hl[1])
self._artists[0].figobj_hl = []
class xspanSelection(GuiSelection):
"""Interactive selection of an x range on the axis"""
def on_press_draw(self):
if 'r' in self.__dict__:
self.r.set_width(0)
self.r.set_xy((self.xs, self.ax.get_ylim()[0]))
self.r.set_height(self.ax.get_ylim()[1] - self.ax.get_ylim()[0])
else:
self.r = Rectangle(xy=(self.xs, self.ax.get_ylim()[0]),
height=self.ax.get_ylim()[1] - \
self.ax.get_ylim()[0],
width=0, fill=True, lw=2, alpha=0.5,
color='blue')
self.ax.add_artist(self.r)
self.r.set_clip_box(self.ax.bbox)
self.r.set_zorder(10)
def on_motion_draw(self):
self.r.set_width(self.xe - self.xs)
def on_release_print(self):
pprint('X Span: (%d, %d)\n' % (self.xs, self.xe))
class xspanSelection(GuiSelection):
"""Interactive selection of an x range on the axis"""
def on_press_draw(self):
if 'r' in self.__dict__:
self.r.set_width(0)
self.r.set_xy((self.xs, self.ax.get_ylim()[0]))
self.r.set_height(self.ax.get_ylim()[1] - self.ax.get_ylim()[0])
else:
self.r = Rectangle(xy=(self.xs, self.ax.get_ylim()[0]),
height=self.ax.get_ylim()[1] - \
self.ax.get_ylim()[0],
width=0, fill=True, lw=2, alpha=0.5,
color='blue')
self.ax.add_artist(self.r)
self.r.set_clip_box(self.ax.bbox)
self.r.set_zorder(10)
def on_motion_draw(self):
self.r.set_width(self.xe - self.xs)
def on_release_print(self):
pprint('X Span: (%d, %d)\n' % (self.xs, self.xe))
def _init_legend_box(self, handles, labels):
"""
Initiallize the legend_box. The legend_box is an instance of
the OffsetBox, which is packed with legend handles and
texts. Once packed, their location is calculated during the
drawing time.
"""
fontsize = self.fontsize
# legend_box is a HPacker, horizontally packed with
# columns. Each column is a VPacker, vertically packed with
# legend items. Each legend item is HPacker packed with
# legend handleBox and labelBox. handleBox is an instance of
# offsetbox.DrawingArea which contains legend handle. labelBox
# is an instance of offsetbox.TextArea which contains legend
# text.
text_list = [] # the list of text instances
handle_list = [] # the list of text instances
label_prop = dict(
verticalalignment='baseline',
horizontalalignment='left',
fontproperties=self.prop,
)
labelboxes = []
for l in labels:
textbox = TextArea(l,
textprops=label_prop,
multilinebaseline=True,
minimumdescent=True)
text_list.append(textbox._text)
labelboxes.append(textbox)
handleboxes = []
# The approximate height and descent of text. These values are
# only used for plotting the legend handle.
height = self._approx_text_height() * 0.7
descent = 0.
# each handle needs to be drawn inside a box of (x, y, w, h) =
# (0, -descent, width, height). And their corrdinates should
# be given in the display coordinates.
# NOTE : the coordinates will be updated again in
# _update_legend_box() method.
# The transformation of each handle will be automatically set
# to self.get_trasnform(). If the artist does not uses its
# default trasnform (eg, Collections), you need to
# manually set their transform to the self.get_transform().
for handle in handles:
if isinstance(handle, RegularPolyCollection):
npoints = self.scatterpoints
else:
npoints = self.numpoints
if npoints > 1:
# we put some pad here to compensate the size of the
# marker
xdata = np.linspace(0.3 * fontsize,
(self.handlelength - 0.3) * fontsize,
npoints)
xdata_marker = xdata
elif npoints == 1:
xdata = np.linspace(0, self.handlelength * fontsize, 2)
xdata_marker = [0.5 * self.handlelength * fontsize]
if isinstance(handle, Line2D):
ydata = ((height - descent) / 2.) * np.ones(xdata.shape, float)
legline = Line2D(xdata, ydata)
legline.update_from(handle)
self._set_artist_props(legline) # after update
legline.set_clip_box(None)
legline.set_clip_path(None)
legline.set_drawstyle('default')
legline.set_marker('None')
handle_list.append(legline)
legline_marker = Line2D(xdata_marker,
ydata[:len(xdata_marker)])
legline_marker.update_from(handle)
self._set_artist_props(legline_marker)
legline_marker.set_clip_box(None)
legline_marker.set_clip_path(None)
legline_marker.set_linestyle('None')
# we don't want to add this to the return list because
# the texts and handles are assumed to be in one-to-one
# correpondence.
legline._legmarker = legline_marker
elif isinstance(handle, Patch):
p = Rectangle(
xy=(0., 0.),
width=self.handlelength * fontsize,
height=(height - descent),
)
p.update_from(handle)
self._set_artist_props(p)
p.set_clip_box(None)
p.set_clip_path(None)
handle_list.append(p)
elif isinstance(handle, LineCollection):
ydata = ((height - descent) / 2.) * np.ones(xdata.shape, float)
legline = Line2D(xdata, ydata)
self._set_artist_props(legline)
legline.set_clip_box(None)
legline.set_clip_path(None)
lw = handle.get_linewidth()[0]
dashes = handle.get_dashes()[0]
color = handle.get_colors()[0]
legline.set_color(color)
legline.set_linewidth(lw)
legline.set_dashes(dashes)
handle_list.append(legline)
elif isinstance(handle, RegularPolyCollection):
#ydata = self._scatteryoffsets
ydata = height * self._scatteryoffsets
size_max, size_min = max(handle.get_sizes()),\
min(handle.get_sizes())
# we may need to scale these sizes by "markerscale"
# attribute. But other handle types does not seem
# to care about this attribute and it is currently ignored.
if self.scatterpoints < 4:
sizes = [.5 * (size_max + size_min), size_max, size_min]
else:
sizes = (size_max - size_min) * np.linspace(
0, 1, self.scatterpoints) + size_min
p = type(handle)(
handle.get_numsides(),
rotation=handle.get_rotation(),
sizes=sizes,
offsets=zip(xdata_marker, ydata),
transOffset=self.get_transform(),
)
p.update_from(handle)
p.set_figure(self.figure)
p.set_clip_box(None)
p.set_clip_path(None)
handle_list.append(p)
else:
handle_list.append(None)
handlebox = DrawingArea(width=self.handlelength * fontsize,
height=height,
xdescent=0.,
ydescent=descent)
handle = handle_list[-1]
handlebox.add_artist(handle)
if hasattr(handle, "_legmarker"):
handlebox.add_artist(handle._legmarker)
handleboxes.append(handlebox)
# We calculate number of lows in each column. The first
# (num_largecol) columns will have (nrows+1) rows, and remaing
# (num_smallcol) columns will have (nrows) rows.
nrows, num_largecol = divmod(len(handleboxes), self._ncol)
num_smallcol = self._ncol - num_largecol
# starting index of each column and number of rows in it.
largecol = safezip(range(0, num_largecol * (nrows + 1), (nrows + 1)),
[nrows + 1] * num_largecol)
smallcol = safezip(
range(num_largecol * (nrows + 1), len(handleboxes), nrows),
[nrows] * num_smallcol)
handle_label = safezip(handleboxes, labelboxes)
columnbox = []
for i0, di in largecol + smallcol:
# pack handleBox and labelBox into itemBox
itemBoxes = [
HPacker(pad=0,
sep=self.handletextpad * fontsize,
children=[h, t],
align="baseline") for h, t in handle_label[i0:i0 + di]
]
# minimumdescent=False for the text of the last row of the column
itemBoxes[-1].get_children()[1].set_minimumdescent(False)
# pack columnBox
columnbox.append(
VPacker(pad=0,
sep=self.labelspacing * fontsize,
align="baseline",
children=itemBoxes))
if self._mode == "expand":
mode = "expand"
else:
mode = "fixed"
sep = self.columnspacing * fontsize
self._legend_box = HPacker(pad=self.borderpad * fontsize,
sep=sep,
align="baseline",
mode=mode,
children=columnbox)
self._legend_box.set_figure(self.figure)
self.texts = text_list
self.legendHandles = handle_list
def highlight_artist(self, val, artist=None):
from ifigure.matplotlib_mod.art3d_gl import Poly3DCollectionGL
from ifigure.matplotlib_mod.art3d_gl import Line3DCollectionGL
figure=self.get_figpage()._artists[0]
ax = self.get_figaxes()
if artist is None:
alist=self._artists
else:
alist=artist
if val == True:
if self._parent is None: return
container = self.get_container()
if container is None: return
if isinstance(alist[0], Poly3DCollectionGL):
hl = alist[0].add_hl_mask()
for item in hl:
alist[0].figobj_hl.append(item)
else:
de = self.get_data_extent()
x=(de[0], de[1],de[1],de[0],de[0])
y=(de[2], de[2],de[3],de[3],de[2])
facecolor='k'
if isinstance(alist[0], Poly3DCollectionGL):
hl = alist[0].make_hl_artist(container)
facecolor = 'none'
self._hit_path = None
elif isinstance(alist[0], Line3DCollectionGL):
hl = alist[0].make_hl_artist(container)
facecolor = 'none'
self._hit_path = None
else:
hl= container.plot(x, y, marker='s',
color='k', linestyle='None',
markerfacecolor='None',
markeredgewidth = 0.5,
scalex=False, scaley=False)
for item in hl:
alist[0].figobj_hl.append(item)
if self._hit_path is not None:
v = self._hit_path.vertices
hl= container.plot(v[:,0], v[:,1], marker='s',
color='k', linestyle='None',
markerfacecolor='None',
markeredgewidth = 0.5,
scalex=False, scaley=False)
for item in hl:
alist[0].figobj_hl.append(item)
hlp = Rectangle((de[0],de[2]),
de[1]-de[0],
de[3]-de[2],
alpha=0.3, facecolor=facecolor,
figure = figure,
transform= container.transData)
if ax is not None:
x0, y0 = ax._artists[0].transAxes.transform((0,0))
x1, y1 = ax._artists[0].transAxes.transform((1,1))
bbox = Bbox([[x0,y0],[x1,y1]])
hlp.set_clip_box(bbox)
hlp.set_clip_on(True)
figure.patches.append(hlp)
alist[0].figobj_hl.append(hlp)
else:
for a in alist:
if len(a.figobj_hl) == 0: continue
for hl in a.figobj_hl[:-1]:
hl.remove()
if isinstance(alist[0], Poly3DCollectionGL):
a.figobj_hl[-1].remove()
else:
figure.patches.remove(a.figobj_hl[-1])
a.figobj_hl=[]
def plot_state_dependency_matrix(model, direct=False, knockout=[], axes=None):
"""
Creates a matrix showing state variable dependency distances.
To show only direct (first-order) dependencies, set the optional argument
``direct`` to ``True``.
Variables can be "knocked out" by adding them to the list in the
``knockout`` parameter. If x depends on y and y depends on z, knocking out
y will prevent the method from findind x's dependency on z.
Returns a matplotlib axes object.
"""
import matplotlib.pyplot as plt
# Create dependency matrix
m = create_state_dependency_matrix(model, direct, knockout)
n = len(m)
# Configure axes
a = axes if axes is not None else plt.gca()
a.set_aspect('equal')
a.set_xlim(0, n + 2)
a.set_ylim(0, n)
# Create matrix plot
from matplotlib.patches import Rectangle
w = 1.0 / (max(max(m))) # color weight
p1 = 0.1 # Padding
p2 = 1.0 - 2 * p1 # Square size
def c(v):
# Colormap
if v == 1:
return (0, 0, 0)
else:
vv = v * w
if (vv > 1.0):
return (0, 1.0, 0)
return (vv, vv, 1.0)
for y, row in enumerate(m):
y = n - y - 1
for x, v in enumerate(row):
r = Rectangle((x + p1, y + p1), p2, p2, color=c(v))
a.add_patch(r)
r.set_clip_box(a.bbox)
# Add colorbar
r = Rectangle((1 + n + p1, y + p1), p2, p2, color=c(1 + y))
a.add_patch(r)
r.set_clip_box(a.bbox)
a.text(1.5 + n,
y + 0.5,
str(y + 1),
horizontalalignment='center',
verticalalignment='center')
# Set tick labels
names = [i.qname() for i in model.states()]
a.set_xticks([i + 0.5 for i in range(0, n)])
a.set_xticklabels(names, rotation=90)
a.xaxis.set_ticks_position('top')
a.set_yticks([i + 0.5 for i in range(0, n)])
rnames = list(names)
rnames.reverse()
a.set_yticklabels(rnames)
# Add axes labels
a.set_xlabel('Affecting variable')
a.set_ylabel('Affected variable')
# Return
return a
def draw_regions2d(regions: RegionSet, plot: Axes, **kwargs):
"""
Draws the Regions on a 2D plot, to visualize the
overlapping or intersecting Regions (or rectangles).
Args:
regions: The set of 2D Regions to draw.
plot: The matplotlib plot to draw on.
kwargs: Additional arguments and options.
Keyword Args:
colored:
Boolean flag for colored output or greyscale.
If True, color codes the Regions based on the
Region's stored 'color' data property. Otherwise,
all Regions have black edges with transparent faces.
communities:
Boolean flag for whether or not to show the
connected communities (or Regions with same color).
Requires colored to be True.
tightbounds:
Boolean flag for whether or not to reduce the
bounding size to the minimum bounding Region,
instead of the defined bounds.
"""
assert regions.dimension == 2
black = (0, 0, 0)
groups = {}
colored = kwargs.get('colored', False)
communities = kwargs.get('communities', False)
tightbounds = kwargs.get('tightbounds', False)
bbox = regions.bbox if tightbounds else regions.minbounds
def mkrectangle(region: Region):
lower = tuple(region[d].lower for d in range(2))
w, h = tuple(region[d].length for d in range(2))
return lower, w, h
if colored and communities:
for region in regions:
color = region.getdata('color')
if color is not None:
group = groups.setdefault(tuple(color), RegionSet(dimension=2))
group.add(region)
for color, group in groups.items():
rectangle = Rectangle(*mkrectangle(group.bbox),
facecolor=(*color, 0.05),
edgecolor='none')
rectangle.set_clip_box(plot)
plot.add_artist(rectangle)
for region in regions:
color = region.getdata('color', black) if colored else black
rectangle = Rectangle(*mkrectangle(region),
facecolor=(*color, 0.1),
edgecolor=color)
rectangle.set_clip_box(plot)
plot.add_artist(rectangle)
plot.set_xlim(astuple(bbox[0]))
plot.set_ylim(astuple(bbox[1]))
def _init_legend_box(self, handles, labels):
"""
Initiallize the legend_box. The legend_box is an instance of
the OffsetBox, which is packed with legend handles and
texts. Once packed, their location is calculated during the
drawing time.
"""
fontsize = self.fontsize
# legend_box is a HPacker, horizontally packed with
# columns. Each column is a VPacker, vertically packed with
# legend items. Each legend item is HPacker packed with
# legend handleBox and labelBox. handleBox is an instance of
# offsetbox.DrawingArea which contains legend handle. labelBox
# is an instance of offsetbox.TextArea which contains legend
# text.
text_list = [] # the list of text instances
handle_list = [] # the list of text instances
label_prop = dict(verticalalignment='baseline',
horizontalalignment='left',
fontproperties=self.prop,
)
labelboxes = []
for l in labels:
textbox = TextArea(l, textprops=label_prop,
multilinebaseline=True, minimumdescent=True)
text_list.append(textbox._text)
labelboxes.append(textbox)
handleboxes = []
# The approximate height and descent of text. These values are
# only used for plotting the legend handle.
height = self._approx_text_height() * 0.7
descent = 0.
# each handle needs to be drawn inside a box of (x, y, w, h) =
# (0, -descent, width, height). And their corrdinates should
# be given in the display coordinates.
# NOTE : the coordinates will be updated again in
# _update_legend_box() method.
# The transformation of each handle will be automatically set
# to self.get_trasnform(). If the artist does not uses its
# default trasnform (eg, Collections), you need to
# manually set their transform to the self.get_transform().
for handle in handles:
if isinstance(handle, RegularPolyCollection):
npoints = self.scatterpoints
else:
npoints = self.numpoints
if npoints > 1:
# we put some pad here to compensate the size of the
# marker
xdata = np.linspace(0.3*fontsize,
(self.handlelength-0.3)*fontsize,
npoints)
xdata_marker = xdata
elif npoints == 1:
xdata = np.linspace(0, self.handlelength*fontsize, 2)
xdata_marker = [0.5*self.handlelength*fontsize]
if isinstance(handle, Line2D):
ydata = ((height-descent)/2.)*np.ones(xdata.shape, float)
legline = Line2D(xdata, ydata)
legline.update_from(handle)
self._set_artist_props(legline) # after update
legline.set_clip_box(None)
legline.set_clip_path(None)
legline.set_drawstyle('default')
legline.set_marker('None')
handle_list.append(legline)
legline_marker = Line2D(xdata_marker, ydata[:len(xdata_marker)])
legline_marker.update_from(handle)
self._set_artist_props(legline_marker)
legline_marker.set_clip_box(None)
legline_marker.set_clip_path(None)
legline_marker.set_linestyle('None')
# we don't want to add this to the return list because
# the texts and handles are assumed to be in one-to-one
# correpondence.
legline._legmarker = legline_marker
elif isinstance(handle, Patch):
p = Rectangle(xy=(0., 0.),
width = self.handlelength*fontsize,
height=(height-descent),
)
p.update_from(handle)
self._set_artist_props(p)
p.set_clip_box(None)
p.set_clip_path(None)
handle_list.append(p)
elif isinstance(handle, LineCollection):
ydata = ((height-descent)/2.)*np.ones(xdata.shape, float)
legline = Line2D(xdata, ydata)
self._set_artist_props(legline)
legline.set_clip_box(None)
legline.set_clip_path(None)
lw = handle.get_linewidth()[0]
dashes = handle.get_dashes()[0]
color = handle.get_colors()[0]
legline.set_color(color)
legline.set_linewidth(lw)
legline.set_dashes(dashes)
handle_list.append(legline)
elif isinstance(handle, RegularPolyCollection):
#ydata = self._scatteryoffsets
ydata = height*self._scatteryoffsets
size_max, size_min = max(handle.get_sizes()),\
min(handle.get_sizes())
# we may need to scale these sizes by "markerscale"
# attribute. But other handle types does not seem
# to care about this attribute and it is currently ignored.
if self.scatterpoints < 4:
sizes = [.5*(size_max+size_min), size_max,
size_min]
else:
sizes = (size_max-size_min)*np.linspace(0,1,self.scatterpoints)+size_min
p = type(handle)(handle.get_numsides(),
rotation=handle.get_rotation(),
sizes=sizes,
offsets=zip(xdata_marker,ydata),
transOffset=self.get_transform(),
)
p.update_from(handle)
p.set_figure(self.figure)
p.set_clip_box(None)
p.set_clip_path(None)
handle_list.append(p)
else:
handle_list.append(None)
handlebox = DrawingArea(width=self.handlelength*fontsize,
height=height,
xdescent=0., ydescent=descent)
handle = handle_list[-1]
handlebox.add_artist(handle)
if hasattr(handle, "_legmarker"):
handlebox.add_artist(handle._legmarker)
handleboxes.append(handlebox)
# We calculate number of lows in each column. The first
# (num_largecol) columns will have (nrows+1) rows, and remaing
# (num_smallcol) columns will have (nrows) rows.
nrows, num_largecol = divmod(len(handleboxes), self._ncol)
num_smallcol = self._ncol-num_largecol
# starting index of each column and number of rows in it.
largecol = safezip(range(0, num_largecol*(nrows+1), (nrows+1)),
[nrows+1] * num_largecol)
smallcol = safezip(range(num_largecol*(nrows+1), len(handleboxes), nrows),
[nrows] * num_smallcol)
handle_label = safezip(handleboxes, labelboxes)
columnbox = []
for i0, di in largecol+smallcol:
# pack handleBox and labelBox into itemBox
itemBoxes = [HPacker(pad=0,
sep=self.handletextpad*fontsize,
children=[h, t], align="baseline")
for h, t in handle_label[i0:i0+di]]
# minimumdescent=False for the text of the last row of the column
itemBoxes[-1].get_children()[1].set_minimumdescent(False)
# pack columnBox
columnbox.append(VPacker(pad=0,
sep=self.labelspacing*fontsize,
align="baseline",
children=itemBoxes))
if self._mode == "expand":
mode = "expand"
else:
mode = "fixed"
sep = self.columnspacing*fontsize
self._legend_box = HPacker(pad=self.borderpad*fontsize,
sep=sep, align="baseline",
mode=mode,
children=columnbox)
self._legend_box.set_figure(self.figure)
self.texts = text_list
self.legendHandles = handle_list
def draw_regions1d(regions: RegionSet, plot: Axes, **kwargs):
"""
Draws the Regions on a 1D plot, to visualize the
overlapping or intersecting Regions (or intervals).
Args:
regions: The set of 1D Regions to draw.
plot: The matplotlib plot to draw on.
kwargs: Additional arguments and options.
Keyword Args:
colored:
Boolean flag for colored output or greyscale.
If True, color codes the Regions based on the
Region's stored 'color' data property. Otherwise,
all Regions have black edges with transparent faces.
communities:
Boolean flag for whether or not to show the
connected communities (or Regions with same color).
Requires colored to be True.
tightbounds:
Boolean flag for whether or not to reduce the
bounding size to the minimum bounding Region,
instead of the defined bounds.
"""
assert regions.dimension == 1
black = (0, 0, 0)
groups = {}
colored = kwargs.get('colored', False)
communities = kwargs.get('communities', False)
tightbounds = kwargs.get('tightbounds', False)
bbox = regions.bbox if tightbounds else regions.minbounds
spacing = max(bbox[0].length / len(regions), 10)
if colored and communities:
for region in regions:
color = region.getdata('color')
if color is not None:
group = groups.setdefault(tuple(color), RegionSet(dimension=1))
group.add(region)
for color, group in groups.items():
gbbox = group.bbox[0]
lows = (gbbox.lower, 0)
w, h = (gbbox.length, spacing * (len(regions) + 2))
rectangle = Rectangle(lows,
w,
h,
facecolor=(*color, 0.05),
edgecolor='none')
rectangle.set_clip_box(plot)
plot.add_artist(rectangle)
for i, region in enumerate(regions):
color = region.getdata('color', black) if colored else black
plot.plot(list(astuple(region[0])), [spacing * (i + 1)] * 2,
color=color)
plot.set_xlim(astuple(bbox[0]))
plot.yaxis.set_visible(False)
def _init_legend_box(self, handles, labels):
"""
Initiallize the legend_box. The legend_box is an instance of
the OffsetBox, which is packed with legend handles and
texts. Once packed, their location is calculated during the
drawing time.
"""
fontsize = self._fontsize
text_list = [] # the list of text instances
handle_list = [] # the list of text instances
label_prop = dict(verticalalignment='baseline',
horizontalalignment='left',
fontproperties=self.prop,
)
labelboxes = []
handleboxes = []
height = self._approx_text_height() * 0.7
descent = 0.
for handle, lab in zip(handles, labels):
if isinstance(handle, RegularPolyCollection) or \
isinstance(handle, CircleCollection):
npoints = self.scatterpoints
else:
npoints = self.numpoints
if npoints > 1:
xdata = np.linspace(0.3*fontsize,
(self.handlelength-0.3)*fontsize,
npoints)
xdata_marker = xdata
elif npoints == 1:
xdata = np.linspace(0, self.handlelength*fontsize, 2)
xdata_marker = [0.5*self.handlelength*fontsize]
if isinstance(handle, Line2D):
ydata = ((height-descent)/2.)*np.ones(xdata.shape, float)
legline = Line2D(xdata, ydata)
legline.update_from(handle)
self._set_artist_props(legline) # after update
legline.set_clip_box(None)
legline.set_clip_path(None)
legline.set_drawstyle('default')
legline.set_marker('None')
handle_list.append(legline)
legline_marker = Line2D(xdata_marker, ydata[:len(xdata_marker)])
legline_marker.update_from(handle)
self._set_artist_props(legline_marker)
legline_marker.set_clip_box(None)
legline_marker.set_clip_path(None)
legline_marker.set_linestyle('None')
legline._legmarker = legline_marker
elif isinstance(handle, Patch):
p = Rectangle(xy=(0., 0.),
width = self.handlelength*fontsize,
height=(height-descent),
)
p.update_from(handle)
self._set_artist_props(p)
p.set_clip_box(None)
p.set_clip_path(None)
handle_list.append(p)
elif isinstance(handle, LineCollection):
ydata = ((height-descent)/2.)*np.ones(xdata.shape, float)
legline = Line2D(xdata, ydata)
self._set_artist_props(legline)
legline.set_clip_box(None)
legline.set_clip_path(None)
lw = handle.get_linewidth()[0]
dashes = handle.get_dashes()[0]
color = handle.get_colors()[0]
legline.set_color(color)
legline.set_linewidth(lw)
if dashes[0] is not None: # dashed line
legline.set_dashes(dashes[1])
handle_list.append(legline)
elif isinstance(handle, RegularPolyCollection):
ydata = height*self._scatteryoffsets
size_max, size_min = max(handle.get_sizes()),\
min(handle.get_sizes())
if self.scatterpoints < 4:
sizes = [.5*(size_max+size_min), size_max,
size_min]
else:
sizes = (size_max-size_min)*np.linspace(0,1,self.scatterpoints)+size_min
p = type(handle)(handle.get_numsides(),
rotation=handle.get_rotation(),
sizes=sizes,
offsets=zip(xdata_marker,ydata),
transOffset=self.get_transform(),
)
p.update_from(handle)
p.set_figure(self.figure)
p.set_clip_box(None)
p.set_clip_path(None)
handle_list.append(p)
elif isinstance(handle, CircleCollection):
ydata = height*self._scatteryoffsets
size_max, size_min = max(handle.get_sizes()),\
min(handle.get_sizes())
if self.scatterpoints < 4:
sizes = [.5*(size_max+size_min), size_max,
size_min]
else:
sizes = (size_max-size_min)*np.linspace(0,1,self.scatterpoints)+size_min
p = type(handle)(sizes,
offsets=zip(xdata_marker,ydata),
transOffset=self.get_transform(),
)
p.update_from(handle)
p.set_figure(self.figure)
p.set_clip_box(None)
p.set_clip_path(None)
handle_list.append(p)
else:
handle_type = type(handle)
warnings.warn("Legend does not support %s\nUse proxy artist instead.\n\nhttp://matplotlib.sourceforge.net/users/legend_guide.html#using-proxy-artist\n" % (str(handle_type),))
handle_list.append(None)
handle = handle_list[-1]
if handle is not None: # handle is None is the artist is not supproted
textbox = TextArea(lab, textprops=label_prop,
multilinebaseline=True, minimumdescent=True)
text_list.append(textbox._text)
labelboxes.append(textbox)
handlebox = DrawingArea(width=self.handlelength*fontsize,
height=height,
xdescent=0., ydescent=descent)
handlebox.add_artist(handle)
if isinstance(handle, RegularPolyCollection) or \
isinstance(handle, CircleCollection):
handle._transOffset = handlebox.get_transform()
handle.set_transform(None)
if hasattr(handle, "_legmarker"):
handlebox.add_artist(handle._legmarker)
handleboxes.append(handlebox)
if len(handleboxes) > 0:
ncol = min(self._ncol, len(handleboxes))
nrows, num_largecol = divmod(len(handleboxes), ncol)
num_smallcol = ncol-num_largecol
largecol = safezip(range(0, num_largecol*(nrows+1), (nrows+1)),
[nrows+1] * num_largecol)
smallcol = safezip(range(num_largecol*(nrows+1), len(handleboxes), nrows),
[nrows] * num_smallcol)
else:
largecol, smallcol = [], []
handle_label = safezip(handleboxes, labelboxes)
columnbox = []
for i0, di in largecol+smallcol:
itemBoxes = [HPacker(pad=0,
sep=self.handletextpad*fontsize,
children=[h, t], align="baseline")
for h, t in handle_label[i0:i0+di]]
itemBoxes[-1].get_children()[1].set_minimumdescent(False)
columnbox.append(VPacker(pad=0,
sep=self.labelspacing*fontsize,
align="baseline",
children=itemBoxes))
if self._mode == "expand":
mode = "expand"
else:
mode = "fixed"
sep = self.columnspacing*fontsize
self._legend_handle_box = HPacker(pad=0,
sep=sep, align="baseline",
mode=mode,
children=columnbox)
self._legend_title_box = TextArea("")
self._legend_box = VPacker(pad=self.borderpad*fontsize,
sep=self.labelspacing*fontsize,
align="center",
children=[self._legend_title_box,
self._legend_handle_box])
self._legend_box.set_figure(self.figure)
self.texts = text_list
self.legendHandles = handle_list
addEntry('Car Battery With CFL', cost = 1.0, cpLh = 0.12)
#addEntry('SharedSolar With CFL', cost = 1.0, cpLh = 0.10)
#addEntry('Grid Mali With CFL', cost = 16, cpLh = 16/0.2)
fig = plt.figure()
axes = fig.add_subplot(111)
for key in dict.keys():
axes.loglog(dict[key]['cost'], dict[key]['cpLh'], 'ko')
axes.text(dict[key]['cost'], dict[key]['cpLh'], key)
from matplotlib.patches import Rectangle
rect = Rectangle((1, .017), 5, .07, facecolor="#dddddd")
axes.add_artist(rect)
rect.set_clip_box(axes.bbox)
axes.text(1.1,0.03, 'Shared Solar With CFL')
plt.xlim((0.1,10))
plt.ylim((0.01,10))
plt.title('Lumen-Hour Cost vs. Purchase Price')
plt.xlabel('Purchase Cost (USD)')
plt.ylabel('Cost Per Lumen-Hour')
plt.grid()
plt.savefig('costVsLumens.pdf')
plt.show()
plt.close()
def visualise(cls,
sensor,
sL=None,
show_sun=False,
sides=True,
interactive=False,
colormap=None,
scale=[0, 1],
title=None):
"""
:param sensor:
:type sensor: CompassSensor
:return:
"""
import matplotlib.pyplot as plt
from matplotlib.patches import Ellipse, Rectangle
from matplotlib.cm import get_cmap
import matplotlib as mpl
if interactive:
plt.ion()
if colormap is not None:
get_colour = lambda x: get_cmap(colormap)(x)
else:
get_colour = lambda x: x * np.array([.5, .5, 1.])
xyz = sph2vec(np.pi / 2 - sensor.theta_local, np.pi + sensor.phi_local,
sensor.R_c)
xyz[0] *= -1
lat, lon = hp.Rotator(rot=(np.rad2deg(-sensor.yaw),
np.rad2deg(-sensor.pitch),
np.rad2deg(-sensor.roll)))(
sensor.sky.lat, np.pi - sensor.sky.lon)
xyz_sun = sph2vec(np.pi / 2 - lat, np.pi + lon, sensor.R_c)
xyz_sun[0] *= -1
if sides:
figsize = (10, 10)
else:
if colormap is None or scale is None:
figsize = (5, 5)
else:
figsize = (5.05, 5.05)
plt.figure("Sensor Design" if title is None else title,
figsize=figsize)
# top view
if sides:
ax_t = plt.subplot2grid((4, 4), (1, 1),
colspan=2,
rowspan=2,
aspect="equal",
adjustable='box-forced')
else:
if colormap is not None and scale is not None:
ax_t = plt.subplot2grid((10, 10), (0, 0),
colspan=9,
rowspan=9,
aspect="equal",
adjustable='box-forced')
else:
ax_t = plt.subplot(111)
outline = Ellipse(xy=np.zeros(2),
width=2 * sensor.R_c,
height=2 * sensor.R_c)
sensor_outline = Ellipse(xy=np.zeros(2),
width=2 * sensor.alpha + 2 * sensor.R_l,
height=2 * sensor.alpha + 2 * sensor.R_l)
ax_t.add_artist(outline)
outline.set_clip_box(ax_t.bbox)
outline.set_alpha(.2)
outline.set_facecolor("grey")
ax_t.add_artist(sensor_outline)
sensor_outline.set_clip_box(ax_t.bbox)
sensor_outline.set_alpha(.5)
sensor_outline.set_facecolor("grey")
stheta, sphi = sensor.theta_local, np.pi + sensor.phi_local
sL = sL if sL is not None else sensor.L
if sensor.mode == "event":
sL = np.clip(1. * sL + .5, 0., 1.)
for (x, y, z), th, ph, L in zip(xyz.T, stheta, sphi, sL):
lens = Ellipse(xy=[x, y],
width=1.5 * sensor.r_l,
height=1.5 * np.cos(th) * sensor.r_l,
angle=np.rad2deg(ph))
ax_t.add_artist(lens)
lens.set_clip_box(ax_t.bbox)
lens.set_facecolor(get_colour(np.asscalar(L)))
if show_sun:
ax_t.plot(xyz_sun[0], xyz_sun[1], 'ro', markersize=22)
ax_t.set_xlim(-sensor.R_c - 2, sensor.R_c + 2)
ax_t.set_ylim(-sensor.R_c - 2, sensor.R_c + 2)
ax_t.set_xticklabels([])
ax_t.set_yticklabels([])
if sides:
# side view #1 (x, z)
ax = plt.subplot2grid((4, 4), (0, 1),
colspan=2,
aspect="equal",
adjustable='box-forced',
sharex=ax_t)
outline = Ellipse(xy=np.zeros(2),
width=2 * sensor.R_c,
height=2 * sensor.R_c)
fade_one = Rectangle(xy=[-sensor.R_c, -sensor.R_c],
width=2 * sensor.R_c,
height=2 * sensor.R_c - sensor.height -
sensor.R_l)
ax.add_artist(outline)
outline.set_clip_box(ax.bbox)
outline.set_alpha(.5)
outline.set_facecolor("grey")
ax.add_artist(fade_one)
fade_one.set_clip_box(ax.bbox)
fade_one.set_alpha(.6)
fade_one.set_facecolor("white")
for (x, y, z), th, ph, L in zip(xyz.T, stheta, sphi, sL):
if y > 0:
continue
lens = Ellipse(xy=[x, z],
width=1.5 * sensor.r_l,
height=np.sin(-y / sensor.R_c) * 1.5 *
sensor.r_l,
angle=np.rad2deg(np.arcsin(-x / sensor.R_c)))
ax.add_artist(lens)
lens.set_clip_box(ax.bbox)
lens.set_facecolor(get_colour(L))
ax.set_xlim(-sensor.R_c - 2, sensor.R_c + 2)
ax.set_ylim(0, sensor.R_c + 2)
ax.set_xticks([])
ax.set_yticks([])
# side view #2 (-x, z)
ax = plt.subplot2grid((4, 4), (3, 1),
colspan=2,
aspect="equal",
adjustable='box-forced',
sharex=ax_t)
outline = Ellipse(xy=np.zeros(2),
width=2 * sensor.R_c,
height=2 * sensor.R_c)
fade_one = Rectangle(
xy=[-sensor.R_c, -sensor.R_c + sensor.height + sensor.R_l],
width=2 * sensor.R_c,
height=2 * sensor.R_c - sensor.height - sensor.R_l)
ax.add_artist(outline)
outline.set_clip_box(ax.bbox)
outline.set_alpha(.5)
outline.set_facecolor("grey")
ax.add_artist(fade_one)
fade_one.set_clip_box(ax.bbox)
fade_one.set_alpha(.6)
fade_one.set_facecolor("white")
for (x, y, z), th, ph, L in zip(xyz.T, stheta, sphi, sL):
if y < 0:
continue
lens = Ellipse(xy=[x, -z],
width=1.5 * sensor.r_l,
height=np.sin(-y / sensor.R_c) * 1.5 *
sensor.r_l,
angle=np.rad2deg(np.arcsin(x / sensor.R_c)))
ax.add_artist(lens)
lens.set_clip_box(ax.bbox)
lens.set_facecolor(get_colour(L))
ax.set_xlim(-sensor.R_c - 2, sensor.R_c + 2)
ax.set_ylim(-sensor.R_c - 2, 0)
ax.set_yticks([])
# side view #3 (y, z)
ax = plt.subplot2grid((4, 4), (1, 3),
rowspan=2,
aspect="equal",
adjustable='box-forced',
sharey=ax_t)
outline = Ellipse(xy=np.zeros(2),
width=2 * sensor.R_c,
height=2 * sensor.R_c)
fade_one = Rectangle(xy=[-sensor.R_c, -sensor.R_c],
width=2 * sensor.R_c - sensor.height -
sensor.R_l,
height=2 * sensor.R_c)
ax.add_artist(outline)
outline.set_clip_box(ax.bbox)
outline.set_alpha(.5)
outline.set_facecolor("grey")
ax.add_artist(fade_one)
fade_one.set_clip_box(ax.bbox)
fade_one.set_alpha(.6)
fade_one.set_facecolor("white")
for (x, y, z), th, ph, L in zip(xyz.T, stheta, sphi, sL):
if x > 0:
continue
lens = Ellipse(
xy=[z, y],
width=1.5 * sensor.r_l,
height=np.sin(-x / sensor.R_c) * 1.5 * sensor.r_l,
angle=np.rad2deg(np.arcsin(y / sensor.R_c)) + 90)
ax.add_artist(lens)
lens.set_clip_box(ax.bbox)
lens.set_facecolor(get_colour(L))
ax.set_ylim(-sensor.R_c - 2, sensor.R_c + 2)
ax.set_xlim(0, sensor.R_c + 2)
ax.set_yticks([])
ax.set_xticks([])
# side view #4 (-y, z)
ax = plt.subplot2grid((4, 4), (1, 0),
rowspan=2,
aspect="equal",
adjustable='box-forced',
sharey=ax_t)
outline = Ellipse(xy=np.zeros(2),
width=2 * sensor.R_c,
height=2 * sensor.R_c)
fade_one = Rectangle(
xy=[-sensor.R_c + sensor.height + sensor.R_l, -sensor.R_c],
width=2 * sensor.R_c - sensor.height - sensor.R_l,
height=2 * sensor.R_c)
ax.add_artist(outline)
outline.set_clip_box(ax.bbox)
outline.set_alpha(.5)
outline.set_facecolor("grey")
ax.add_artist(fade_one)
fade_one.set_clip_box(ax.bbox)
fade_one.set_alpha(.6)
fade_one.set_facecolor("white")
for (x, y, z), th, ph, L in zip(xyz.T, stheta, sphi, sL):
if x < 0:
continue
lens = Ellipse(
xy=[-z, y],
width=1.5 * sensor.r_l,
height=np.sin(-x / sensor.R_c) * 1.5 * sensor.r_l,
angle=np.rad2deg(np.arcsin(-y / sensor.R_c)) - 90)
ax.add_artist(lens)
lens.set_clip_box(ax.bbox)
lens.set_facecolor(get_colour(L))
ax.set_ylim(-sensor.R_c - 2, sensor.R_c + 2)
ax.set_xlim(-sensor.R_c - 2, 0)
ax.set_xticks([])
else:
plt.axis('off')
if colormap is not None and not sides and scale is not None:
ax = plt.subplot2grid((10, 10), (9, 9),
aspect="equal",
adjustable='box-forced',
projection='polar')
ax._direction = 2 * np.pi
ax.set_theta_zero_location("N")
# quant_steps = 360
cb = mpl.colorbar.ColorbarBase(ax,
cmap=get_cmap(colormap),
norm=mpl.colors.Normalize(
0.0, 2 * np.pi),
orientation='horizontal',
ticks=np.linspace(0,
2 * np.pi,
4,
endpoint=False))
cb.outline.set_visible(False)
# cb.ax.set_xticks([0, np.pi/6, np.pi/3, np.pi/2, 2*np.pi/3, 5*np.pi/6, np.pi])
cb.ax.set_xticklabels(
np.linspace(scale[0], scale[1], 4, endpoint=False))
cb.ax.tick_params(pad=1, labelsize=8)
plt.tight_layout(pad=0.)
if interactive:
plt.draw()
plt.pause(.1)
else:
plt.show()
def plot_state_dependency_matrix(model, direct=False, knockout=[], axes=None):
"""
Creates a matrix showing state variable dependency distances.
To show only direct (first-order) dependencies, set the optional argument
``direct`` to ``True``.
Variables can be "knocked out" by adding them to the list in the
``knockout`` parameter. If x depends on y and y depends on z, knocking out
y will prevent the method from findind x's dependency on z.
Returns a matplotlib axes object.
"""
import matplotlib.pyplot as pl
# Create dependency matrix
m = create_state_dependency_matrix(model, direct, knockout)
n = len(m)
# Configure axes
#a = f.add_subplot(111, aspect='equal')
a = axes if axes is not None else pl.gca()
a.set_aspect('equal')
a.set_xlim(0, n + 2)
a.set_ylim(0, n)
# Create matrix plot
from matplotlib.patches import Rectangle
w = 1.0 / (max(max(m))) # color weight
p1 = 0.1 # Padding
p2 = 1.0 - 2 * p1 # Square size
def c(v):
# Colormap
if v == 1:
return (0, 0, 0)
else:
vv = v * w
if (vv > 1.0):
return (0, 1.0, 0)
return (vv, vv, 1.0)
for y, row in enumerate(m):
y = n - y - 1
for x, v in enumerate(row):
r = Rectangle((x + p1, y + p1), p2, p2, color=c(v))
a.add_patch(r)
r.set_clip_box(a.bbox)
# Add colorbar
r = Rectangle((1 + n + p1, y + p1), p2, p2, color=c(1 + y))
a.add_patch(r)
r.set_clip_box(a.bbox)
a.text(1.5 + n,
y + 0.5,
str(y + 1),
horizontalalignment='center',
verticalalignment='center')
# Set tick labels
names = [i.qname() for i in model.states()]
a.set_xticks([i + 0.5 for i in xrange(0, n)])
a.set_xticklabels(names)
from matplotlib.transforms import Affine2D
r = Affine2D.identity()
a.set_yticks([i + 0.5 for i in xrange(0, n)])
rnames = list(names)
rnames.reverse()
a.set_yticklabels(rnames)
for tick in a.xaxis.iter_ticks():
tick[0].label2On = True
tick[0].label1On = False
tick[0].label2.set_rotation('vertical')
# Add axes labels
a.annotate('Affecting variable -->',
xy=(0, -0.05),
ha='left',
va='center',
xycoords='axes fraction',
textcoords='offset points')
# Adjust subplot margins
return a
def highlight_artist(self, val, artist=None):
from ifigure.matplotlib_mod.art3d_gl import Poly3DCollectionGL
from ifigure.matplotlib_mod.art3d_gl import Line3DCollectionGL
figure = self.get_figpage()._artists[0]
ax = self.get_figaxes()
if artist is None:
alist = self._artists
else:
alist = artist
if val == True:
if self._parent is None: return
container = self.get_container()
if container is None: return
if isinstance(alist[0], Poly3DCollectionGL):
hl = alist[0].add_hl_mask()
for item in hl:
alist[0].figobj_hl.append(item)
else:
de = self.get_data_extent()
x = (de[0], de[1], de[1], de[0], de[0])
y = (de[2], de[2], de[3], de[3], de[2])
facecolor = 'k'
if isinstance(alist[0], Poly3DCollectionGL):
hl = alist[0].make_hl_artist(container)
facecolor = 'none'
self._hit_path = None
elif isinstance(alist[0], Line3DCollectionGL):
hl = alist[0].make_hl_artist(container)
facecolor = 'none'
self._hit_path = None
else:
hl = container.plot(x,
y,
marker='s',
color='k',
linestyle='None',
markerfacecolor='None',
markeredgewidth=0.5,
scalex=False,
scaley=False)
for item in hl:
alist[0].figobj_hl.append(item)
if self._hit_path is not None:
v = self._hit_path.vertices
hl = container.plot(v[:, 0],
v[:, 1],
marker='s',
color='k',
linestyle='None',
markerfacecolor='None',
markeredgewidth=0.5,
scalex=False,
scaley=False)
for item in hl:
alist[0].figobj_hl.append(item)
hlp = Rectangle((de[0], de[2]),
de[1] - de[0],
de[3] - de[2],
alpha=0.3,
facecolor=facecolor,
figure=figure,
transform=container.transData)
if ax is not None:
x0, y0 = ax._artists[0].transAxes.transform((0, 0))
x1, y1 = ax._artists[0].transAxes.transform((1, 1))
bbox = Bbox([[x0, y0], [x1, y1]])
hlp.set_clip_box(bbox)
hlp.set_clip_on(True)
figure.patches.append(hlp)
alist[0].figobj_hl.append(hlp)
else:
for a in alist:
if len(a.figobj_hl) == 0: continue
for hl in a.figobj_hl[:-1]:
hl.remove()
if isinstance(alist[0], Poly3DCollectionGL):
a.figobj_hl[-1].remove()
else:
figure.patches.remove(a.figobj_hl[-1])
a.figobj_hl = []
