def write_body(self):
try:
from matplotlib.path import Path
except ImportError:
Path = None
from matplotlib.patches import Circle, Polygon
else:
from matplotlib.patches import Circle, PathPatch
indices = self.X[:, 2].argsort()
for a in indices:
xy = self.X[a, :2]
if a < self.natoms:
r = self.d[a] / 2
if ((xy[1] + r > 0) and (xy[1] - r < self.h) and
(xy[0] + r > 0) and (xy[0] - r < self.w)):
circle = Circle(xy, r, facecolor=self.colors[a])
circle.draw(self.renderer)
else:
a -= self.natoms
c = self.T[a]
if c != -1:
hxy = self.D[c]
if Path is None:
line = Polygon((xy + hxy, xy - hxy))
else:
line = PathPatch(Path((xy + hxy, xy - hxy)))
line.draw(self.renderer)
def animate(currentNode = currentNode):
while 1:
newNode = q.get()
if currentNode: currentNode.remove()
circle = Circle(newNode,0.1)
currentNode = ax.add_patch(circle)
circle.set_fc('r')
fig.canvas.draw()
def circle(xy=None, x=None, y=None, **kwargs): if xy is None: if x is None or y is None: raise 'circle: need x and y' xy = array([x,y]) c = Circle(xy=xy, **kwargs) a=gca() c.set_clip_box(a.bbox) a.add_artist(c) return c
def draw_vswr_circles(self, vswr_radii, labels=False):
for r in vswr_radii:
c = Circle((0, 0), r, ls='dashed', **self.patch_options_light)
c.set_clip_path(self.smith_circle)
c.set_clip_box(self.ax.bbox)
self.ax.add_patch(c)
if labels:
for r in vswr_radii:
if r > 0:
vswr = (1 + r)/(1 - r)
self.ax.text(0, r, '%.1f' % vswr, **self.label_options)
def make_animation_frames(name, semimajor, planet_radius, star_radius, star_color, orbital_period):
#not affiliated with Animal Planet.
center = np.array([0.5,0.5])
angle = np.random.uniform(0, 2*np.pi)
planet_center = center+semimajor*np.array([1,0])
fig = Figure(figsize=(6,6))
axis = fig.add_subplot(1, 1, 1)
star = Circle(center, radius=star_radius, color=star_color)
orbit = Circle(center, radius=semimajor, fill=False, linestyle='dashed', color='gray')
planet = Circle(planet_center, radius=planet_radius, color='green')
axis.add_patch(star)
axis.add_patch(orbit)
axis.add_patch(planet)
axis.axis('off')
filenames = []
#set 50 days to be 5 seconds
orbital_period = orbital_period/100.*5.
#let's put the period in seconds
fps = 100.
print 'orbital period = ', orbital_period
nframe = int(orbital_period*fps)
#round off
orbital_period = nframe/fps
omega = 2*np.pi/orbital_period
angles = np.linspace(0, 2*np.pi, nframe)
if not os.path.exists("frames"):
os.makekdir("frames")
if not os.path.exists("gifs"):
os.makekdir("gifss")
print angles
print "nframe = ", nframe
for i,theta in enumerate(angles):
canvas = FigureCanvas(fig)
planet.center = center+semimajor*np.array([np.cos(theta),np.sin(theta)])
filename = ("frames/%.4d_"%i)+remove_space(name)+'.png'
fig.savefig(filename)
filenames.append(filename)
#animate
gifname = "gifs/%s.gif" % remove_space(name)
frame_names = " ".join(filenames)
cmd = "convert -delay 1 %s %s" % (frame_names, gifname)
print cmd
os.system(cmd)
def add_breadcrumb(self):
""" Adds a breadcrumb """
c = Circle(self._loc, radius = 16.25)
c.set_facecolor('0.65') # grey
c.set_edgecolor('black')
c.set_zorder(zorders['breadcrumbs'])
c.set_fill(True)
self.view.add_artist(c)
self.breadcrumbs.append(c)
self.draw()
def circle( xy, radius, color="lightsteelblue", facecolor="none", alpha=1, ax=None ):
""" add a circle to ax= or current axes
"""
# from .../pylab_examples/ellipse_demo.py
e = Circle( xy=xy, radius=radius )
if ax is None:
ax = plt.gca() # ax = subplot( 1,1,1 )
ax.add_artist(e)
e.set_clip_box(ax.bbox)
e.set_edgecolor( color )
e.set_facecolor( facecolor ) # "none" not None
e.set_alpha( alpha )
def scatter_plot(self, equators=True, tagging=True, depth_cap=None):
if depth_cap is None:
depth_cap = self.height
fig = plt.figure(figsize=(12, 10))
ax = fig.add_subplot(111, projection="3d")
plt.subplots_adjust(left=0, bottom=0, right=1, top=1, wspace=0, hspace=0)
xs = [self.nodes[self.root].coord.x]
ys = [self.nodes[self.root].coord.y]
zs = [self.nodes[self.root].coord.z]
plot_color_board = ["blue", "red", "yellow", "green", "black"]
font0 = FontProperties()
font0.set_size(8)
current_generation = deque([self.root])
next_generation = True
while next_generation:
next_generation = deque()
while current_generation:
n = current_generation.popleft()
if self.nodes[n].depth <= depth_cap:
xs.append(self.nodes[n].coord.x)
ys.append(self.nodes[n].coord.y)
zs.append(self.nodes[n].coord.z)
if tagging:
ax.text(self.nodes[n].coord.x + 0.01,
self.nodes[n].coord.y + 0.01,
self.nodes[n].coord.z + 0.01,
("n{0}".format(n)), fontproperties=font0)
for child in self.nodes[n].children:
next_generation.append(child)
if self.nodes[n].depth <= depth_cap:
xe = [self.nodes[n].coord.x, self.nodes[child].coord.x]
ye = [self.nodes[n].coord.y, self.nodes[child].coord.y]
ze = [self.nodes[n].coord.z, self.nodes[child].coord.z]
ax.plot(xe, ye, ze, plot_color_board[self.nodes[n].depth % 5])
current_generation = next_generation
ax.scatter(xs, ys, zs, c="r", marker="o")
global_radius = self.nodes[self.root].radius * 1.12
if equators:
for axis in ["x", "y", "z"]:
circle = Circle((0, 0), global_radius * 1.1)
circle.set_clip_box(ax.bbox)
circle.set_edgecolor("gray")
circle.set_alpha(0.3)
circle.set_facecolor("none") # "none" not None
ax.add_patch(circle)
art3d.pathpatch_2d_to_3d(circle, z=0, zdir=axis)
ax.set_xlim([-1.2 * global_radius, 1.2 * global_radius])
ax.set_ylim([-1.2 * global_radius, 1.2 * global_radius])
ax.set_zlim([-1.2 * global_radius, 1.2 * global_radius])
ax.set_xlabel("X Label")
ax.set_ylabel("Y Label")
ax.set_zlabel("Z Label")
plt.show()
class Annotate(object):
def __init__(self):
self.ax = plt.gca()
# self.rect = Rectangle((0,0), 1, 1)
self.circ = Circle((0,0), 1, alpha=0.1)
self.x0 = None
self.y0 = None
self.x1 = None
self.y1 = None
# self.ax.add_patch(self.rect)
self.ax.add_patch(self.circ)
self.press = None
self.ax.figure.canvas.mpl_connect('button_press_event', self.on_press)
self.ax.figure.canvas.mpl_connect('motion_notify_event', self.on_motion)
self.ax.figure.canvas.mpl_connect('button_release_event', self.on_release)
def on_press(self, event):
print 'press'
self.press = 1
self.x0 = event.xdata
self.y0 = event.ydata
def on_motion(self, event):
if self.press is None:
return
self.x1 = event.xdata
self.y1 = event.ydata
radius = ((self.x1 - self.x0)**2 + (self.y1 - self.y0)**2)**0.5
self.circ.set_radius(radius)
self.circ.center = self.x0, self.y0
# ###self.rect.set_width(self.x1 - self.x0)
# ###self.rect.set_height(self.y1 - self.y0)
# ###self.rect.set_xy((self.x0, self.y0))
self.ax.figure.canvas.draw()
def on_release(self, event):
print 'release'
self.press = None
self.x1 = event.xdata
self.y1 = event.ydata
radius = ((self.x1 - self.x0) ** 2 + (self.y1 - self.y0) ** 2) ** 0.5
self.circ.set_radius(radius)
self.circ.center = self.x0, self.y0
# ###self.rect.set_width(self.x1 - self.x0)
# ###self.rect.set_height(self.y1 - self.y0)
# ###self.rect.set_xy((self.x0, self.y0))
self.ax.figure.canvas.draw()
def __init__(self, axes, sim, type_to_radius, type_to_color):
assert len(type_to_radius) == len(type_to_color)
particle_types_arr = sim.types
self._typeToRadius = type_to_radius
self._typeToColor = type_to_color
self._particleCircles = []
self._sim = sim
for particleType in particle_types_arr:
c = Circle((0, 0, 0), type_to_radius[particleType], )
c.set_color(self._typeToColor[particleType])
self._particleCircles.append(c)
axes.add_patch(c)
axes.set_xlim([0, sim.domain_size[0]])
axes.set_ylim([0, sim.domain_size[1]])
axes.set_aspect('equal')
def draw_chart_axes(self):
# make outer circle
self.smith_circle = Circle((0, 0), 1, transform=self.ax.transData, fc='none',
**self.patch_options_axis)
self.ax.add_patch(self.smith_circle)
# make constant r=1 circle
z0_circle = Circle((0.5, 0), 0.5, transform=self.ax.transData, fc='none',
**self.patch_options_axis)
z0_circle.set_clip_path(self.smith_circle)
z0_circle.set_clip_box(self.ax.bbox)
self.ax.add_patch(z0_circle)
# make x-axis
line = Line2D([-1,1],[0,0], **self.patch_options_axis)
line.set_clip_path(self.smith_circle)
line.set_clip_box(self.ax.bbox)
self.ax.add_line(line)
class SelectablePoint:
def __init__(self, xy, label, fig):
self.point = Circle( (xy[0], xy[1]), .25, figure=fig)
self.label = label
self.cidpress = self.point.figure.canvas.mpl_connect('button_press_event', self.onClick)
def onClick(self, e):
if self.point.contains(e)[0]:
print self.label
def myCorrPlot(df):
"""
Correlation plot ( ~ corrplot with R)
Takes a Pandas DataFrame as input and returns
the plot which can then be shown with
plot.show(), saved to a file with plot.savefig(), or
manipulated in any other standard matplotlib way.
Forked from https://github.com/louridas/corrplot
"""
plt.figure(1)
ax = plt.subplot(1, 1, 1, aspect='equal')
poscm = cm.get_cmap('Blues')
negcm = cm.get_cmap('Reds')
labels = df.columns
for pair in combinations(labels, 2):
corr = pearsonr(df[pair[0]].values, df[pair[1]].values)[0]
clrmap = poscm if corr >= 0 else negcm
circle = Circle((labels.get_loc(pair[0]),labels.get_loc(pair[1])), radius = 0.4)
circle.set_edgecolor('black')
circle.set_facecolor(clrmap(np.abs(corr)))
mirrorCircle = Circle((labels.get_loc(pair[1]),labels.get_loc(pair[0])), radius = 0.4)
mirrorCircle.set_edgecolor('black')
mirrorCircle.set_facecolor(clrmap(np.abs(corr)))
ax.add_artist(circle)
ax.add_artist(mirrorCircle)
ax.set_xlim(-1, len(labels))
ax.set_ylim(-1, len(labels))
ax.xaxis.tick_top()
xtickslocs = np.arange(len(labels))
ax.set_xticks(xtickslocs)
ax.set_xticklabels(labels, rotation=30, fontsize='small', ha='left')
ax.invert_yaxis()
ytickslocs = np.arange(len(labels))
ax.set_yticks(ytickslocs)
ax.set_yticklabels(labels, fontsize='small')
return plt
def draw_impedance_circles(self, intercept_x_coords, intercept_angles, labels=False):
r_circle_coords, x_circle_coords, rs, xs = self._impedance_circle_coords(intercept_x_coords, intercept_angles)
for center, radius in chain(r_circle_coords, x_circle_coords):
c = Circle(center, radius, **self.patch_options_dark)
c.set_clip_path(self.smith_circle)
c.set_clip_box(self.ax.bbox)
self.ax.add_patch(c)
if labels:
for x, r in zip(intercept_x_coords, rs):
self.ax.text(x + 0.04, 0.03, '%.0f' % round(self.z0*r), **self.label_options)
for a, x in zip(intercept_angles, xs):
r = (a - 90) if x > 0 else (a + 90)
a = np.radians(a)
d = 1.04
self.ax.text(d*cos(a), d*sin(a), '%.0fj' % round(self.z0*x), rotation=r, **self.label_options)
def draw_admittance_circles(self, intercept_x_coords, intercept_angles, labels=False):
r_circle_coords, x_circle_coords, rs, xs = self._impedance_circle_coords(intercept_x_coords, intercept_angles)
# admittance circles have same coords as impedance ones, except flipped
# on the y-axis
for (x, y), radius in chain(r_circle_coords, x_circle_coords):
c = Circle((-x, -y), radius, **self.patch_options_light)
c.set_clip_path(self.smith_circle)
c.set_clip_box(self.ax.bbox)
self.ax.add_patch(c)
if labels:
for x, r in zip(intercept_x_coords, rs):
self.ax.text(-x, 0, '%.1f' % (1/(50*r)), **self.label_options)
for a, x in zip(intercept_angles, xs):
r = (a - 90) if x < 0 else (a + 90)
a = np.radians(a)
self.ax.text(cos(pi - a), sin(pi - a), '%.1f' % (1/(50*x)), rotation=r, **self.label_options)
def __init__(self):
self.ax = plt.gca()
# self.rect = Rectangle((0,0), 1, 1)
self.circ = Circle((0,0), 1, alpha=0.1)
self.x0 = None
self.y0 = None
self.x1 = None
self.y1 = None
# self.ax.add_patch(self.rect)
self.ax.add_patch(self.circ)
self.press = None
self.ax.figure.canvas.mpl_connect('button_press_event', self.on_press)
self.ax.figure.canvas.mpl_connect('motion_notify_event', self.on_motion)
self.ax.figure.canvas.mpl_connect('button_release_event', self.on_release)
def shooting_plot(shot_df, plot_size=(12,11), gridNum=30, mymap=plt.get_cmap('Spectral')):
from matplotlib.patches import Circle
x = shot_df.LOC_X[shot_df['LOC_Y']<425.1]
y = shot_df.LOC_Y[shot_df['LOC_Y']<425.1]
(shotVals, shotNumber) = find_shot_vals(shot_df, gridNum)
fig = plt.figure(figsize=plot_size)
cmap = mymap
ax = plt.axes([0.1, 0.1, 0.8, 0.8])
draw_court(outer_lines=False)
plt.xlim(-250,250)
plt.ylim(422.5, -47.5)
norm = mpl.colors.Normalize(vmin=-0.5, vmax = -0.1)
import math
def logistic(x):
return 20 / (1 + math.exp(-0.18*(x-np.median(shotNumber.get_array()))))
for i, shots in enumerate(shotVals):
restricted = Circle(shotNumber.get_offsets()[i], radius=shotNumber.get_array()[i],
color=cmap(norm(shots)),alpha=0.8, fill=True)
restricted.radius = logistic( np.sqrt(restricted.radius) )
if restricted.radius > 240/gridNum: restricted.radius=240/gridNum
ax.add_patch(restricted)
ax2 = fig.add_axes([0.92, 0.1, 0.02, 0.8])
cb = mpl.colorbar.ColorbarBase(ax2,cmap=cmap, orientation='vertical')
cb.set_label('next-possession value')
cb.set_ticks([0.0, 0.25, 0.5, 0.75, 1.0])
cb.set_ticklabels(['-0.5','-0.4', '-0.3','-0.2', '-0.1'])
plt.show()
return ax
def __init__(self, vl, room_shape, start_iter):
super(EnvironmentReader,self).__init__(win_size=[700,700],
win_loc=pos,
title='Environment')
self.vl = vl
self.cur_iter = start_iter
self.cur_i = 0
self.max_iter = np.max(vl['Iter num'])
self.maxx = room_shape[0][1]
self.maxy = room_shape[1][1]
self.cntr_x = np.mean(room_shape[0])
self.cntr_y = np.mean(room_shape[1])
self.x_hist = []; self.y_hist = []
self.canvas.mpl_connect('resize_event',lambda x: self.update_background())
self.pos, = self.ax.plot([],[],color='g',animated=True)
self.vel = Arrow([0,0],[1,0],arrowstyle='-|>, head_length=3, head_width=3',
animated=True, linewidth=4)
self.ax.add_patch(self.vel)
#self.radius, = self.ax.plot([],[],color='r',animated=True)
self.clockcounter = self.ax.text(self.maxx,room_shape[1][0],
'',ha='right',size='large',
animated=True)
self.iters = self.ax.text(self.maxx-1, room_shape[1][0]+3,
'',ha='right',animated=True)
self.target = Circle([0,0],0,animated=True,color='r')
self.target.set_radius(11)
self.ax.add_artist(self.target)
self.ax.set_xlim(room_shape[0])
self.ax.set_ylim(room_shape[1])
self.draw_plc_flds()
self.draw_HMM_sectors()
self.predicted_counter = self.ax.text(self.maxx,room_shape[1][0]+10,'',
ha='right',size='large',animated=True)
self.prediction_hist = None
#self.cur_sec = Rectangle([0,0],self.HMM.dx,self.HMM.dy,fill=True,
# color='k',animated=True)
#self.ax_env.add_patch(self.cur_sec)
self.canvas.draw()
def __init__(self, cloud, selection_shape, z_color=False, unlabeled_color = (1,0,0), labeled_color = (0,0,1)):
self.selection_shape = selection_shape
self.unlabeled_color = np.array(unlabeled_color)
self.labeled_color = np.array(labeled_color)
assert not np.all(unlabeled_color == labeled_color)
self.fig = plt.figure('label rope ends', figsize=(24,12))
self.fig.clear()
self.ax = self.fig.add_subplot(111, aspect='equal')
if cloud.shape[1] == 6:
self.cloud = cloud
else:
self.cloud = np.c_[cloud[:,:3], np.tile(self.unlabeled_color, (cloud.shape[0],1))]
if z_color:
z_min = self.cloud[:,2].min()
z_max = self.cloud[:,2].max()
self.z_color = np.empty((len(self.cloud),3))
for i in range(len(self.cloud)):
f = (self.cloud[i,2] - z_min) / (z_max - z_min)
self.z_color[i,:] = np.array(colorsys.hsv_to_rgb(f,1,1))
else:
self.z_color = None
self.scatters = []
self.rescatter_cloud()
self.ax.autoscale(False)
if self.selection_shape == 'rectangle' or self.selection_shape == 'square':
self.rect = Rectangle((0,0), 0, 0, facecolor='None', edgecolor='green', linestyle='dashed')
self.ax.add_patch(self.rect)
elif self.selection_shape == 'circle':
self.circle = Circle((0,0), 0, facecolor='None', edgecolor='green', linestyle='dashed')
self.ax.add_patch(self.circle)
self.x0 = None
self.y0 = None
self.x1 = None
self.y1 = None
self.fig.canvas.mpl_connect('button_press_event', self.on_press)
self.fig.canvas.mpl_connect('button_release_event', self.on_release)
self.motion_notify_cid = None
self.fig.canvas.mpl_connect('key_press_event', self.on_key)
plt.show()
def enable_cursor(self):
self.cid_on_mouse_move = self.fig.canvas.mpl_connect('motion_notify_event', self._on_mouse_move)
self.fig.canvas.mpl_connect('button_press_event', self._on_mouse_press)
#self.cid_on_mouse_leave = self.fig.canvas.mpl_connect('axes_leave_event', self._on_mouse_leave)
#self.cid_resize = self.fig.canvas.mpl_connect('resize_event', self._resize)
self.cid_draw = self.fig.canvas.mpl_connect('draw_event', self._draw)
self.cursor_text = Text(0.7, 0.1, 'n/a',
horizontalalignment='left',
verticalalignment='center',
#bbox=dict(facecolor='white', alpha=1, ec='gray', pad=10),
color='white',
fontsize='small',
alpha=0.8,
backgroundcolor='gray',
family='monospace',
clip_box=self.ax.bbox,
animated=True,
transform = self.ax.transAxes)
self.ax.add_artist(self.cursor_text)
self.circle_matched_term = Circle((100,100), 0.02, alpha=0.5, color='green', animated=True)
self.ax.add_patch(self.circle_matched_term)
def __init__(self, message, net, direction, *args, **kwargs):
Circle.__init__(self, self._get_pos(message, net, direction), *args,
**kwargs)
def im_phot(directory,gain,im_file,aperture):
""" Perform photometry on the image """
# Read in fits image file and create array with wcs coordinates
os.chdir(directory)
hdulist = fits.open(im_file)
w = WCS(im_file)
data = hdulist[0].data
data[np.isnan(data)] = 0
hdulist.close()
# Calculate center point of image (RA, Dec) if not input by user
targetra, targetdec = w.all_pix2world(len(data[:,0])/2,len(data[0,:])/2,0)
# Use SEP for background subtraction and source detection
datasw = data.byteswap().newbyteorder().astype('float64')
bkg = sep.Background(datasw)
data_bgs = data - bkg
data_bgs[data_bgs < 0] = 0
mean = np.mean(data_bgs)
median = np.median(data_bgs)
std = bkg.globalrms
objects = sep.extract(data_bgs,3,err=bkg.globalrms)
objra, objdec = w.all_pix2world(objects['x'],objects['y'],0)
# Find dummy magnitudes using aperture photometry and plot images
fig, ax = plt.subplots()
image = plt.imshow(data_bgs,cmap='gray',vmin=(mean-3*std),
vmax=(mean+3*std),origin='lower')
sepmag = []
sepmagerr = []
ra = []
dec = []
xpixel = []
ypixel = []
for i in range(len(objects)):
# Perform circular aperture photometry
flux,fluxerr,flag = sep.sum_circle(data_bgs,objects['x'][i],
objects['y'][i],aperture,err=std,gain=gain)
mag = -2.5*np.log10(flux)
maglimit1 = -2.5*np.log10((flux+fluxerr))
maglimit2 = -2.5*np.log10((flux-fluxerr))
magerr1 = np.abs(mag-maglimit1)
magerr2 = np.abs(mag-maglimit2)
magerr = (magerr1+magerr2)/2
# Save object properties to arrays
sepmag.append(mag)
sepmagerr.append(magerr)
ra.append(objra[i])
dec.append(objdec[i])
xpixel.append(objects['x'][i])
ypixel.append(objects['y'][i])
# Plot the detections on the image
out = Circle(xy=(objects['x'][i],objects['y'][i]),radius=aperture)
out.set_facecolor('none')
out.set_edgecolor('red')
ax.add_artist(out)
plt.savefig(directory+'detections.png')
return targetra,targetdec,sepmag,sepmagerr,ra,dec,xpixel,ypixel
def gauge(labels=['LOW','MEDIUM','HIGH','EXTREME'], \
colors=['#007A00','#0063BF','#FFCC00','#ED1C24'], Probability=1, fname=False):
N = len(labels)
colors = colors[::-1]
"""
begins the plotting
"""
gauge_img = io.BytesIO()
fig, ax = plt.subplots()
ang_range, mid_points = degree_range(4)
labels = labels[::-1]
"""
plots the sectors and the arcs
"""
patches = []
for ang, c in zip(ang_range, colors):
# sectors
patches.append(Wedge((0., 0.), .4, *ang, facecolor='w', lw=2))
# arcs
patches.append(
Wedge((0., 0.),
.4,
*ang,
width=0.10,
facecolor=c,
lw=2,
alpha=0.5))
[ax.add_patch(p) for p in patches]
"""
set the labels (e.g. 'LOW','MEDIUM',...)
"""
for mid, lab in zip(mid_points, labels):
ax.text(0.35 * np.cos(np.radians(mid)), 0.35 * np.sin(np.radians(mid)), lab, \
horizontalalignment='center', verticalalignment='center', fontsize=14, \
fontweight='bold', rotation = rot_text(mid))
"""
set the bottom banner and the title
"""
r = Rectangle((-0.4, -0.1), 0.8, 0.1, facecolor='w', lw=2)
ax.add_patch(r)
ax.text(0, -0.05, 'Churn Probability ' + np.round(Probability,2).astype(str), horizontalalignment='center', \
verticalalignment='center', fontsize=22, fontweight='bold')
"""
plots the arrow now
"""
pos = (1 - Probability) * 180
ax.arrow(0, 0, 0.225 * np.cos(np.radians(pos)), 0.225 * np.sin(np.radians(pos)), \
width=0.04, head_width=0.09, head_length=0.1, fc='k', ec='k')
ax.add_patch(Circle((0, 0), radius=0.02, facecolor='k'))
ax.add_patch(Circle((0, 0), radius=0.01, facecolor='w', zorder=11))
"""
removes frame and ticks, and makes axis equal and tight
"""
ax.set_frame_on(False)
ax.axes.set_xticks([])
ax.axes.set_yticks([])
ax.axis('equal')
plt.tight_layout()
plt.savefig(gauge_img, format='png')
gauge_img.seek(0)
url = base64.b64encode(gauge_img.getvalue()).decode()
return url
def create_base(box_bg='#CCCCCC',
arrow1='#88CCFF',
arrow2='#88FF88',
supervised=True):
plt.figure(figsize=(9, 6), facecolor='w')
ax = plt.axes((0, 0, 1, 1), xticks=[], yticks=[], frameon=False)
ax.set_xlim(0, 9)
ax.set_ylim(0, 6)
patches = [Rectangle((0.3, 3.6), 1.5, 1.8, zorder=1, fc=box_bg),
Rectangle((0.5, 3.8), 1.5, 1.8, zorder=2, fc=box_bg),
Rectangle((0.7, 4.0), 1.5, 1.8, zorder=3, fc=box_bg),
Rectangle((2.9, 3.6), 0.2, 1.8, fc=box_bg),
Rectangle((3.1, 3.8), 0.2, 1.8, fc=box_bg),
Rectangle((3.3, 4.0), 0.2, 1.8, fc=box_bg),
Rectangle((0.3, 0.2), 1.5, 1.8, fc=box_bg),
Rectangle((2.9, 0.2), 0.2, 1.8, fc=box_bg),
Circle((5.5, 3.5), 1.0, fc=box_bg),
Polygon([[5.5, 1.7],
[6.1, 1.1],
[5.5, 0.5],
[4.9, 1.1]], fc=box_bg),
FancyArrow(2.3, 4.6, 0.35, 0, fc=arrow1,
width=0.25, head_width=0.5, head_length=0.2),
FancyArrow(3.75, 4.2, 0.5, -0.2, fc=arrow1,
width=0.25, head_width=0.5, head_length=0.2),
FancyArrow(5.5, 2.4, 0, -0.4, fc=arrow1,
width=0.25, head_width=0.5, head_length=0.2),
FancyArrow(2.0, 1.1, 0.5, 0, fc=arrow2,
width=0.25, head_width=0.5, head_length=0.2),
FancyArrow(3.3, 1.1, 1.3, 0, fc=arrow2,
width=0.25, head_width=0.5, head_length=0.2),
FancyArrow(6.2, 1.1, 0.8, 0, fc=arrow2,
width=0.25, head_width=0.5, head_length=0.2)]
if supervised:
patches += [Rectangle((0.3, 2.4), 1.5, 0.5, zorder=1, fc=box_bg),
Rectangle((0.5, 2.6), 1.5, 0.5, zorder=2, fc=box_bg),
Rectangle((0.7, 2.8), 1.5, 0.5, zorder=3, fc=box_bg),
FancyArrow(2.3, 2.9, 2.0, 0, fc=arrow1,
width=0.25, head_width=0.5, head_length=0.2),
Rectangle((7.3, 0.85), 1.5, 0.5, fc=box_bg)]
else:
patches += [Rectangle((7.3, 0.2), 1.5, 1.8, fc=box_bg)]
for p in patches:
ax.add_patch(p)
plt.text(1.45, 4.9, "Training\nText,\nDocuments,\nImages,\netc.",
ha='center', va='center', fontsize=14)
plt.text(3.6, 4.9, "Feature\nVectors",
ha='left', va='center', fontsize=14)
plt.text(5.5, 3.5, "Machine\nLearning\nAlgorithm",
ha='center', va='center', fontsize=14)
plt.text(1.05, 1.1, "New Text,\nDocument,\nImage,\netc.",
ha='center', va='center', fontsize=14)
plt.text(3.3, 1.7, "Feature\nVector",
ha='left', va='center', fontsize=14)
plt.text(5.5, 1.1, "Predictive\nModel",
ha='center', va='center', fontsize=12)
if supervised:
plt.text(1.45, 3.05, "Labels",
ha='center', va='center', fontsize=14)
plt.text(8.05, 1.1, "Expected\nLabel",
ha='center', va='center', fontsize=14)
plt.text(8.8, 5.8, "Supervised Learning Model",
ha='right', va='top', fontsize=18)
else:
plt.text(8.05, 1.1,
"Likelihood\nor Cluster ID\nor Better\nRepresentation",
ha='center', va='center', fontsize=12)
plt.text(8.8, 5.8, "Unsupervised Learning Model",
ha='right', va='top', fontsize=18)
class SmithChart(object):
z0 = 50
current_plane = None
two_port = None
show_matched_termination_cursor = True
gain_cursor = False
def __init__(self, ax=None, show_cursor=True, admittance=True, labels=False):
self.ax = ax if ax else gca()
self.fig = self.ax.figure
self.draw_smith_chart(admittance, labels)
if show_cursor:
self.enable_cursor()
def _impedance_circle_coords(self, intercept_x_coords, intercept_angles):
# find coords for constant R circles
rs = 2/(1 - asarray(intercept_x_coords)) - 1 # convert to desired resistances
r_circle_coords = [((r/(r+1), 0), 1/(r + 1)) for r in rs]
# find coords for constant X circles
intercept_angles = np.radians(intercept_angles)
xs = np.sin(intercept_angles)/(1 - np.cos(intercept_angles)) # convert to desired reactances
x_circle_coords = [((1, 1/x), abs(1/x)) for x in xs]
return r_circle_coords, x_circle_coords, rs, xs
def draw_impedance_circles(self, intercept_x_coords, intercept_angles, labels=False):
r_circle_coords, x_circle_coords, rs, xs = self._impedance_circle_coords(intercept_x_coords, intercept_angles)
for center, radius in chain(r_circle_coords, x_circle_coords):
c = Circle(center, radius, **self.patch_options_dark)
c.set_clip_path(self.smith_circle)
c.set_clip_box(self.ax.bbox)
self.ax.add_patch(c)
if labels:
for x, r in zip(intercept_x_coords, rs):
self.ax.text(x + 0.04, 0.03, '%.0f' % round(self.z0*r), **self.label_options)
for a, x in zip(intercept_angles, xs):
r = (a - 90) if x > 0 else (a + 90)
a = np.radians(a)
d = 1.04
self.ax.text(d*cos(a), d*sin(a), '%.0fj' % round(self.z0*x), rotation=r, **self.label_options)
def draw_admittance_circles(self, intercept_x_coords, intercept_angles, labels=False):
r_circle_coords, x_circle_coords, rs, xs = self._impedance_circle_coords(intercept_x_coords, intercept_angles)
# admittance circles have same coords as impedance ones, except flipped
# on the y-axis
for (x, y), radius in chain(r_circle_coords, x_circle_coords):
c = Circle((-x, -y), radius, **self.patch_options_light)
c.set_clip_path(self.smith_circle)
c.set_clip_box(self.ax.bbox)
self.ax.add_patch(c)
if labels:
for x, r in zip(intercept_x_coords, rs):
self.ax.text(-x, 0, '%.1f' % (1/(50*r)), **self.label_options)
for a, x in zip(intercept_angles, xs):
r = (a - 90) if x < 0 else (a + 90)
a = np.radians(a)
self.ax.text(cos(pi - a), sin(pi - a), '%.1f' % (1/(50*x)), rotation=r, **self.label_options)
def draw_vswr_circles(self, vswr_radii, labels=False):
for r in vswr_radii:
c = Circle((0, 0), r, ls='dashed', **self.patch_options_light)
c.set_clip_path(self.smith_circle)
c.set_clip_box(self.ax.bbox)
self.ax.add_patch(c)
if labels:
for r in vswr_radii:
if r > 0:
vswr = (1 + r)/(1 - r)
self.ax.text(0, r, '%.1f' % vswr, **self.label_options)
def draw_chart_axes(self):
# make outer circle
self.smith_circle = Circle((0, 0), 1, transform=self.ax.transData, fc='none',
**self.patch_options_axis)
self.ax.add_patch(self.smith_circle)
# make constant r=1 circle
z0_circle = Circle((0.5, 0), 0.5, transform=self.ax.transData, fc='none',
**self.patch_options_axis)
z0_circle.set_clip_path(self.smith_circle)
z0_circle.set_clip_box(self.ax.bbox)
self.ax.add_patch(z0_circle)
# make x-axis
line = Line2D([-1,1],[0,0], **self.patch_options_axis)
line.set_clip_path(self.smith_circle)
line.set_clip_box(self.ax.bbox)
self.ax.add_line(line)
def draw_smith_chart(self, admittance, labels):
# plot options for constant z/y circles and axes
self.patch_options_light = {'fc':'none', 'color':'#474959', 'alpha':0.2, 'lw':1}
self.patch_options_dark = {'fc':'none', 'color':'#474959', 'alpha':0.5, 'lw':1}
self.patch_options_axis = {'color':'black', 'alpha':0.8, 'lw':1.5}
# options for z/y circle labels
self.label_options = {'ha':'center', 'va':'center', 'size':'9', 'alpha':0.5}#,
#'bbox':dict(fc='white', ec='none', alpha=0.5)}
#self.label_options = {'ha':'center', 'va':'center', 'size':'10', 'alpha':0.5}
# x-axis coordinates where constant R circles will intersect
intercept_x_coords = arange(-0.75, 1, 0.25)
# angles where constant X circles will intersect (in degrees relative
# to positive x-axis)
intercept_angles = arange(40, 360, 40)
# radii for vswr circles
vswr_radii = arange(0, 1, 0.2)
self.draw_chart_axes()
self.draw_impedance_circles(intercept_x_coords, intercept_angles, labels)
self.draw_admittance_circles(intercept_x_coords, intercept_angles, labels=0)
self.draw_vswr_circles(vswr_radii, labels)
self.ax.grid(0)
self.ax.axis('equal')
self.ax.axis(np.array([-1.1, 1.1, -1.1, 1.1]))
self.save_background()
def enable_cursor(self):
self.cid_on_mouse_move = self.fig.canvas.mpl_connect('motion_notify_event', self._on_mouse_move)
self.fig.canvas.mpl_connect('button_press_event', self._on_mouse_press)
#self.cid_on_mouse_leave = self.fig.canvas.mpl_connect('axes_leave_event', self._on_mouse_leave)
#self.cid_resize = self.fig.canvas.mpl_connect('resize_event', self._resize)
self.cid_draw = self.fig.canvas.mpl_connect('draw_event', self._draw)
self.cursor_text = Text(0.7, 0.1, 'n/a',
horizontalalignment='left',
verticalalignment='center',
#bbox=dict(facecolor='white', alpha=1, ec='gray', pad=10),
color='white',
fontsize='small',
alpha=0.8,
backgroundcolor='gray',
family='monospace',
clip_box=self.ax.bbox,
animated=True,
transform = self.ax.transAxes)
self.ax.add_artist(self.cursor_text)
self.circle_matched_term = Circle((100,100), 0.02, alpha=0.5, color='green', animated=True)
self.ax.add_patch(self.circle_matched_term)
def plot_circle(self, center, radius, text='', text_color='black', circle_color='red',\
filled=False, circle_alpha=0.2, linestyle='solid', hatch=None):
text_alpha = 0.7
text_x_offset = 0.15
text_y_offset = 0.1
# calculate position for text
a, b = center
# find closet point to edge of circle
x = a*(1 - radius/sqrt(a**2 + b**2))
y = b*(1 - radius/sqrt(a**2 + b**2))
dist_to_circle = sqrt(x**2 + y**2)
#print 'dist to sphere: ', sqrt(x**2 + y**2)
if (x**2 + y**2) == 1:
text_x_offset *= -1
text_y_offset *= -1
#textpos = ((a - x)/radius + text_x_offset, (b - y)/radius + text_y_offset)
textpos = (x/dist_to_circle + text_x_offset, y/dist_to_circle + text_y_offset)
else:
textpos = (x + text_x_offset, y + text_y_offset)
#print 'textpos: ', textpos
# make actual circle
c = Circle(center, radius, fc=circle_color, ec='white', alpha=circle_alpha, fill=filled, linestyle=linestyle, hatch=hatch)
self.ax.add_patch(c)
self.ax.annotate(text, (x, y), color=text_color,\
fontsize='small', alpha=text_alpha, xycoords='data', xytext=textpos,\
arrowprops=dict(arrowstyle="->", alpha=text_alpha,\
connectionstyle="arc3,rad=0.17"))
def draw_stability_circles(self, two_port, plane='both', label=None):
filled = True
if plane == 'source' or plane == 'both':
for i, (center, radius, circle_stable) in enumerate(zip(*two_port.source_stability_circle())):
if circle_stable:
hatch = None
color = 'green'
else:
hatch = '/'
color = 'red'
if label is None:
label_actual = '\n(%0.2f MHz)' % (two_port.f[i]/1e6) if two_port.f is not None else ''
label_actual = 'Source' + label_actual
else:
label_actual = label
self.plot_circle((center.real, center.imag), radius, text=label_actual, filled=filled,\
text_color='black', circle_color=color, hatch=hatch)
if plane == 'load' or plane == 'both':
for i, (center, radius, circle_stable) in enumerate(zip(*two_port.load_stability_circle())):
if circle_stable:
hatch = None
color = 'green'
else:
hatch = '/'
color = 'red'
if label is None:
label_actual = '\n(%0.2f MHz)' % (two_port.f[i]/1e6) if two_port.f is not None else ''
label_actual = 'Load' + label_actual
else:
label_actual = label
self.plot_circle((center.real, center.imag), radius, text=label_actual, filled=filled,\
text_color='black', circle_color=color, hatch=hatch)
self.save_background()
def plot_gain_circles(self, two_port, gains_db=None, plane='source', \
gain_cursor=True, surface=False):
self.two_port = two_port
self.gain_cursor = gain_cursor
self.current_plane = plane
max_gain = self.two_port.g_max()
if (self.two_port.kt() < 1).any():
max_gain = self.two_port.max_double_sided_mismatched_gain()
if gains_db == None:
gains_db = np.trunc(10*db(max_gain)[0]*linspace(0.5, 1, 4))/10
if surface:
filled = False
circle_alpha = 0.7
linestyle = 'dashed'
else:
filled = True
circle_alpha = 0.2
linestyle = 'solid'
for g in gains_db:
if plane == 'source':
center, radius = self.two_port.available_gain_circle(un_db(g))
self.ax.set_title('Source plane')
elif plane == 'load':
center, radius = self.two_port.operating_gain_circle(un_db(g))
self.ax.set_title('Load plane')
text = str(g) + ' dB'
self.plot_circle((center[0].real, center[0].imag), radius[0], text=text, filled=filled,\
text_color='black', circle_color='orange', circle_alpha=circle_alpha,\
linestyle=linestyle)
if not surface:
self.save_background()
return
num_segments = 1000
i, r = meshgrid(linspace(-1.1, 1.1, num_segments), linspace(-1.1, 1.1, num_segments))
gamma = i + 1j*r
term = OnePort(s=gamma.reshape(-1))
if plane == 'source':
g = self.two_port.g_a(term)
elif plane == 'load':
g = self.two_port.g_p(term)
g = db(g).reshape(num_segments, num_segments)
g[abs(gamma) > 1] = nan
im = self.ax.imshow(g, origin='lower', extent=(-1.1, 1.1, -1.1, 1.1), interpolation='bicubic', alpha=0.9)
im.set_clim(gains_db[0], db(max_gain))
self.save_background()
def _on_mouse_press(self, event):
if event.button == 3:
print 'clearing'
self.fig.canvas.restore_region(self.background, bbox=self.ax.bbox)
def _on_mouse_move(self, event):
if event.xdata is None or event.ydata is None:
return
gamma = event.xdata + 1j*event.ydata
cursor_port = OnePort(s=gamma)
self.fig.canvas.restore_region(self.background, bbox=self.ax.bbox)
self.update_gain_cursor(cursor_port)
self.update_info_box(cursor_port)
#self.fig.canvas.draw()
self.fig.canvas.blit(self.ax.bbox)
def update_gain_cursor(self, cursor_port):
if not self.gain_cursor or self.two_port is None:
return
if self.current_plane == 'source':
term_matched = (cursor_port*self.two_port).out().conj()
term_resulting = (self.two_port*term_matched).inp()
else:
term_matched = (self.two_port*cursor_port).inp().conj()
term_resulting = (term_matched*self.two_port).out()
self.circle_matched_term.center = real(term_matched.s), imag(term_matched.s)
if abs(term_matched.s) > 1 or abs(term_resulting.s) > 1:
self.circle_matched_term.set_color('r')
else:
self.circle_matched_term.set_color('g')
self.ax.draw_artist(self.circle_matched_term)
def update_info_box(self, cursor_port):
z = cursor_port.z
y = cursor_port.y
data = '$\\Gamma$ = {:>7.2f} $\\angle$ {:>+8.3f}$^{{\\circ}}$'.format(float(abs(cursor_port.s)), float(degrees(angle(cursor_port.s))))
data += '\nVSWR = {:>7.2f}'.format(float(cursor_port.vswr()))
data += '\nMM = {:>7.2f} dB'.format(float(db(cursor_port.mismatch())))
data += '\nZ = {:>7.2f}{:>+8.2f}j '.format(float(real(z)), float(imag(z)))
if self.two_port is not None:
if self.current_plane == 'source':
term_matched = (cursor_port*self.two_port).out().conj()
gain = self.two_port.g_t(cursor_port, term_matched)
else:
term_matched = (self.two_port*cursor_port).inp().conj()
gain = self.two_port.g_t(term_matched, cursor_port)
x = float(imag(z))
w = 2*pi*self.two_port.f[0]
if x > 0:
hf = 'H'
lc = x/w
else:
hf = 'F'
lc = 1/(w*x)
val, prefix = to_eng_form(abs(lc))
data += '({:>3.2f} {}{}) '.format(val, prefix, hf)
data += '$\\Omega$'
data += '\n = {:>7.2f} // {:>+8.2f}j '.format(float(1/real(y)), float(-1/imag(y)))
if self.two_port is not None:
x = float(-1/imag(y))
w = 2*pi*self.two_port.f[0]
if x > 0:
hf = 'H'
lc = x/w
else:
hf = 'F'
lc = 1/(w*x)
val, prefix = to_eng_form(abs(lc))
data += '({:>3.2f} {}{}) '.format(val, prefix, hf)
data += '$\\Omega$'
if self.gain_cursor and self.two_port is not None:
gain_str = '{:>7.2f} dB'.format(float(db(gain))) if gain > 0 else 'n/a'
data += '\nG = ' + gain_str
self.cursor_text.set_text(data)
self.ax.draw_artist(self.cursor_text)
def plot_s_param(self, s, color='blue'):
self.plot_line(s, color)
self.save_background()
def plot_line(self, points, color='blue'):
r, t = abs(points), angle(points)
l = Line2D(r*cos(t), r*sin(t), color=color)
self.ax.add_line(l)
def save_background(self):
self.fig.canvas.draw()
self.background = self.fig.canvas.copy_from_bbox(self.ax.bbox)
def _on_mouse_leave(self, event):
pass
def _resize(self, event):
self.save_background()
print 'resize\n'
#self.ax.draw(None)
#self.fig.canvas.draw()
#self.fig.canvas.restore_region(self.background, bbox=self.ax.bbox)
def _draw(self, event):
self.fig.canvas.mpl_disconnect(self.cid_draw)
#self.fig.canvas.restore_region(self.background, bbox=self.ax.bbox)
self.save_background()
self.cid_draw = self.fig.canvas.mpl_connect('draw_event', self._draw)
class Annotate(object):
def __init__(self, cloud, selection_shape, z_color=False, unlabeled_color = (1,0,0), labeled_color = (0,0,1)):
self.selection_shape = selection_shape
self.unlabeled_color = np.array(unlabeled_color)
self.labeled_color = np.array(labeled_color)
assert not np.all(unlabeled_color == labeled_color)
self.fig = plt.figure('label rope ends', figsize=(24,12))
self.fig.clear()
self.ax = self.fig.add_subplot(111, aspect='equal')
if cloud.shape[1] == 6:
self.cloud = cloud
else:
self.cloud = np.c_[cloud[:,:3], np.tile(self.unlabeled_color, (cloud.shape[0],1))]
if z_color:
z_min = self.cloud[:,2].min()
z_max = self.cloud[:,2].max()
self.z_color = np.empty((len(self.cloud),3))
for i in range(len(self.cloud)):
f = (self.cloud[i,2] - z_min) / (z_max - z_min)
self.z_color[i,:] = np.array(colorsys.hsv_to_rgb(f,1,1))
else:
self.z_color = None
self.scatters = []
self.rescatter_cloud()
self.ax.autoscale(False)
if self.selection_shape == 'rectangle' or self.selection_shape == 'square':
self.rect = Rectangle((0,0), 0, 0, facecolor='None', edgecolor='green', linestyle='dashed')
self.ax.add_patch(self.rect)
elif self.selection_shape == 'circle':
self.circle = Circle((0,0), 0, facecolor='None', edgecolor='green', linestyle='dashed')
self.ax.add_patch(self.circle)
self.x0 = None
self.y0 = None
self.x1 = None
self.y1 = None
self.fig.canvas.mpl_connect('button_press_event', self.on_press)
self.fig.canvas.mpl_connect('button_release_event', self.on_release)
self.motion_notify_cid = None
self.fig.canvas.mpl_connect('key_press_event', self.on_key)
plt.show()
def rescatter_cloud(self):
for scatter in self.scatters:
scatter.remove()
self.scatters = []
if self.z_color is not None:
ul_inds = np.absolute((self.cloud[:,3:] - self.unlabeled_color)).sum(axis=1) == 0 # unlabeled inds
self.scatters.append(plt.scatter(self.cloud[ul_inds,0], self.cloud[ul_inds,1], c=self.z_color[ul_inds,:], edgecolors=self.z_color[ul_inds,:], marker=',', s=5))
self.scatters.append(plt.scatter(self.cloud[~ul_inds,0], self.cloud[~ul_inds,1], c=self.cloud[~ul_inds,3:], edgecolors=self.cloud[~ul_inds,3:], marker='o', s=20))
else:
self.scatters.append(plt.scatter(self.cloud[:,0], self.cloud[:,1], c=self.cloud[:,3:], edgecolors=self.cloud[:,3:], marker=',', s=5))
def on_press(self, event):
if event.xdata < self.ax.get_xlim()[0] or event.xdata > self.ax.get_xlim()[1] or \
event.ydata < self.ax.get_ylim()[0] or event.ydata > self.ax.get_ylim()[1]:
return
self.x0 = event.xdata
self.y0 = event.ydata
self.motion_notify_cid = self.fig.canvas.mpl_connect('motion_notify_event', self.on_motion)
def on_release(self, event):
if self.motion_notify_cid:
self.fig.canvas.mpl_disconnect(self.motion_notify_cid)
self.motion_notify_cid = None
if self.selection_shape == 'rectangle' or self.selection_shape == 'square':
x0 = min(self.x0, self.x1)
x1 = max(self.x0, self.x1)
y0 = min(self.y0, self.y1)
y1 = max(self.y0, self.y1)
inside_rect_inds = (x0 <= self.cloud[:,0]) * (self.cloud[:,0] <= x1) * (y0 <= self.cloud[:,1]) * (self.cloud[:,1] <= y1)
num_pts_inside_rect = inside_rect_inds.sum()
self.cloud[inside_rect_inds,3:] = np.tile(self.labeled_color, (num_pts_inside_rect,1))
elif self.selection_shape == 'circle':
inside_circle_inds = np.apply_along_axis(np.linalg.norm, 1, self.cloud[:,:2] - np.array(self.circle.center)) <= self.circle.get_radius()
num_pts_inside_circle = inside_circle_inds.sum()
self.cloud[inside_circle_inds,3:] = np.tile(self.labeled_color, (num_pts_inside_circle,1))
self.rescatter_cloud()
plt.draw()
def on_motion(self, event):
if event.xdata < self.ax.get_xlim()[0] or event.xdata > self.ax.get_xlim()[1] or \
event.ydata < self.ax.get_ylim()[0] or event.ydata > self.ax.get_ylim()[1]:
return
if self.selection_shape == 'rectangle':
self.x1 = event.xdata
self.y1 = event.ydata
elif self.selection_shape == 'circle' or self.selection_shape == 'square':
side = max(abs(event.xdata - self.x0), abs(event.ydata - self.y0))
self.x1 = self.x0 + np.sign(event.xdata - self.x0) * side
self.y1 = self.y0 + np.sign(event.ydata - self.y0) * side
if self.selection_shape == 'rectangle' or self.selection_shape == 'square':
self.rect.set_width(self.x1 - self.x0)
self.rect.set_height(self.y1 - self.y0)
self.rect.set_xy((self.x0, self.y0))
elif self.selection_shape == 'circle':
self.circle.center = ((self.x1 + self.x0)/2.0, (self.y0 + self.y1)/2.0)
self.circle.set_radius(side/2.0)
plt.draw()
def on_key(self, event):
if event.key == 'q':
sys.exit(0)
if event.key == 'd':
plt.close(self.fig)
def plot_state_qsphere(state, figsize=None, ax=None, show_state_labels=True,
show_state_phases=False, use_degrees=False, *, rho=None):
"""Plot the qsphere representation of a quantum state.
Here, the size of the points is proportional to the probability
of the corresponding term in the state and the color represents
the phase.
Args:
state (Statevector or DensityMatrix or ndarray): an N-qubit quantum state.
figsize (tuple): Figure size in inches.
ax (matplotlib.axes.Axes): An optional Axes object to be used for
the visualization output. If none is specified a new matplotlib
Figure will be created and used. Additionally, if specified there
will be no returned Figure since it is redundant.
show_state_labels (bool): An optional boolean indicating whether to
show labels for each basis state.
show_state_phases (bool): An optional boolean indicating whether to
show the phase for each basis state.
use_degrees (bool): An optional boolean indicating whether to use
radians or degrees for the phase values in the plot.
Returns:
Figure: A matplotlib figure instance if the ``ax`` kwag is not set
Raises:
ImportError: Requires matplotlib.
VisualizationError: if input is not a valid N-qubit state.
QiskitError: Input statevector does not have valid dimensions.
Example:
.. jupyter-execute::
from qiskit import QuantumCircuit
from qiskit.quantum_info import Statevector
from qiskit.visualization import plot_state_qsphere
%matplotlib inline
qc = QuantumCircuit(2)
qc.h(0)
qc.cx(0, 1)
state = Statevector.from_instruction(qc)
plot_state_qsphere(state)
"""
if not HAS_MATPLOTLIB:
raise ImportError('Must have Matplotlib installed. To install, run "pip install '
'matplotlib".')
try:
import seaborn as sns
except ImportError:
raise ImportError('Must have seaborn installed to use '
'plot_state_qsphere. To install, run "pip install seaborn".')
rho = DensityMatrix(state)
num = rho.num_qubits
if num is None:
raise VisualizationError("Input is not a multi-qubit quantum state.")
# get the eigenvectors and eigenvalues
eigvals, eigvecs = linalg.eigh(rho.data)
if figsize is None:
figsize = (7, 7)
if ax is None:
return_fig = True
fig = plt.figure(figsize=figsize)
else:
return_fig = False
fig = ax.get_figure()
gs = gridspec.GridSpec(nrows=3, ncols=3)
ax = fig.add_subplot(gs[0:3, 0:3], projection='3d')
ax.axes.set_xlim3d(-1.0, 1.0)
ax.axes.set_ylim3d(-1.0, 1.0)
ax.axes.set_zlim3d(-1.0, 1.0)
ax.axes.grid(False)
ax.view_init(elev=5, azim=275)
# start the plotting
# Plot semi-transparent sphere
u = np.linspace(0, 2 * np.pi, 25)
v = np.linspace(0, np.pi, 25)
x = np.outer(np.cos(u), np.sin(v))
y = np.outer(np.sin(u), np.sin(v))
z = np.outer(np.ones(np.size(u)), np.cos(v))
ax.plot_surface(x, y, z, rstride=1, cstride=1, color='k',
alpha=0.05, linewidth=0)
# Get rid of the panes
ax.w_xaxis.set_pane_color((1.0, 1.0, 1.0, 0.0))
ax.w_yaxis.set_pane_color((1.0, 1.0, 1.0, 0.0))
ax.w_zaxis.set_pane_color((1.0, 1.0, 1.0, 0.0))
# Get rid of the spines
ax.w_xaxis.line.set_color((1.0, 1.0, 1.0, 0.0))
ax.w_yaxis.line.set_color((1.0, 1.0, 1.0, 0.0))
ax.w_zaxis.line.set_color((1.0, 1.0, 1.0, 0.0))
# Get rid of the ticks
ax.set_xticks([])
ax.set_yticks([])
ax.set_zticks([])
# traversing the eigvals/vecs backward as sorted low->high
for idx in range(eigvals.shape[0]-1, -1, -1):
if eigvals[idx] > 0.001:
# get the max eigenvalue
state = eigvecs[:, idx]
loc = np.absolute(state).argmax()
# remove the global phase from max element
angles = (np.angle(state[loc]) + 2 * np.pi) % (2 * np.pi)
angleset = np.exp(-1j * angles)
state = angleset * state
d = num
for i in range(2 ** num):
# get x,y,z points
element = bin(i)[2:].zfill(num)
weight = element.count("1")
zvalue = -2 * weight / d + 1
number_of_divisions = n_choose_k(d, weight)
weight_order = bit_string_index(element)
angle = (float(weight) / d) * (np.pi * 2) + \
(weight_order * 2 * (np.pi / number_of_divisions))
if (weight > d / 2) or ((weight == d / 2) and
(weight_order >= number_of_divisions / 2)):
angle = np.pi - angle - (2 * np.pi / number_of_divisions)
xvalue = np.sqrt(1 - zvalue ** 2) * np.cos(angle)
yvalue = np.sqrt(1 - zvalue ** 2) * np.sin(angle)
# get prob and angle - prob will be shade and angle color
prob = np.real(np.dot(state[i], state[i].conj()))
if prob > 1: # See https://github.com/Qiskit/qiskit-terra/issues/4666
prob = 1
colorstate = phase_to_rgb(state[i])
alfa = 1
if yvalue >= 0.1:
alfa = 1.0 - yvalue
if not np.isclose(prob, 0) and show_state_labels:
rprime = 1.3
angle_theta = np.arctan2(np.sqrt(1 - zvalue ** 2), zvalue)
xvalue_text = rprime * np.sin(angle_theta) * np.cos(angle)
yvalue_text = rprime * np.sin(angle_theta) * np.sin(angle)
zvalue_text = rprime * np.cos(angle_theta)
element_text = '$\\vert' + element + '\\rangle$'
if show_state_phases:
element_angle = (np.angle(state[i]) + (np.pi * 4)) % (np.pi * 2)
if use_degrees:
element_text += '\n$%.1f^\\circ$' % (element_angle * 180/np.pi)
else:
element_angle = pi_check(element_angle, ndigits=3).replace('pi', '\\pi')
element_text += '\n$%s$' % (element_angle)
ax.text(xvalue_text, yvalue_text, zvalue_text, element_text,
ha='center', va='center', size=12)
ax.plot([xvalue], [yvalue], [zvalue],
markerfacecolor=colorstate,
markeredgecolor=colorstate,
marker='o', markersize=np.sqrt(prob) * 30, alpha=alfa)
a = Arrow3D([0, xvalue], [0, yvalue], [0, zvalue],
mutation_scale=20, alpha=prob, arrowstyle="-",
color=colorstate, lw=2)
ax.add_artist(a)
# add weight lines
for weight in range(d + 1):
theta = np.linspace(-2 * np.pi, 2 * np.pi, 100)
z = -2 * weight / d + 1
r = np.sqrt(1 - z ** 2)
x = r * np.cos(theta)
y = r * np.sin(theta)
ax.plot(x, y, z, color=(.5, .5, .5), lw=1, ls=':', alpha=.5)
# add center point
ax.plot([0], [0], [0], markerfacecolor=(.5, .5, .5),
markeredgecolor=(.5, .5, .5), marker='o', markersize=3,
alpha=1)
else:
break
n = 64
theta = np.ones(n)
ax2 = fig.add_subplot(gs[2:, 2:])
ax2.pie(theta, colors=sns.color_palette("hls", n), radius=0.75)
ax2.add_artist(Circle((0, 0), 0.5, color='white', zorder=1))
offset = 0.95 # since radius of sphere is one.
if use_degrees:
labels = ['Phase\n(Deg)', '0', '90', '180 ', '270']
else:
labels = ['Phase', '$0$', '$\\pi/2$', '$\\pi$', '$3\\pi/2$']
ax2.text(0, 0, labels[0], horizontalalignment='center',
verticalalignment='center', fontsize=14)
ax2.text(offset, 0, labels[1], horizontalalignment='center',
verticalalignment='center', fontsize=14)
ax2.text(0, offset, labels[2], horizontalalignment='center',
verticalalignment='center', fontsize=14)
ax2.text(-offset, 0, labels[3], horizontalalignment='center',
verticalalignment='center', fontsize=14)
ax2.text(0, -offset, labels[4], horizontalalignment='center',
verticalalignment='center', fontsize=14)
if return_fig:
if get_backend() in ['module://ipykernel.pylab.backend_inline',
'nbAgg']:
plt.close(fig)
return fig
def circles(x, y, s, c='b', vmin=None, vmax=None, **kwargs):
"""
Make a scatter of circles plot of x vs y, where x and y are sequence
like objects of the same lengths. The size of circles are in data scale.
Parameters
----------
x,y : scalar or array_like, shape (n, )
Input data
s : scalar or array_like, shape (n, )
Radius of circle in data unit.
c : color or sequence of color, optional, default : 'b'
`c` can be a single color format string, or a sequence of color
specifications of length `N`, or a sequence of `N` numbers to be
mapped to colors using the `cmap` and `norm` specified via kwargs.
Note that `c` should not be a single numeric RGB or RGBA sequence
because that is indistinguishable from an array of values
to be colormapped. (If you insist, use `color` instead.)
`c` can be a 2-D array in which the rows are RGB or RGBA, however.
vmin, vmax : scalar, optional, default: None
`vmin` and `vmax` are used in conjunction with `norm` to normalize
luminance data. If either are `None`, the min and max of the
color array is used.
kwargs : `~matplotlib.collections.Collection` properties
Eg. alpha, edgecolor(ec), facecolor(fc), linewidth(lw), linestyle(ls),
norm, cmap, transform, etc.
Returns
-------
paths : `~matplotlib.collections.PathCollection`
Examples
--------
a = np.arange(11)
circles(a, a, a*0.2, c=a, alpha=0.5, edgecolor='none')
plt.colorbar()
License
--------
This code is under [The BSD 3-Clause License]
(http://opensource.org/licenses/BSD-3-Clause)
"""
if np.isscalar(c):
kwargs.setdefault('color', c)
c = None
if 'fc' in kwargs: kwargs.setdefault('facecolor', kwargs.pop('fc'))
if 'ec' in kwargs: kwargs.setdefault('edgecolor', kwargs.pop('ec'))
if 'ls' in kwargs: kwargs.setdefault('linestyle', kwargs.pop('ls'))
if 'lw' in kwargs: kwargs.setdefault('linewidth', kwargs.pop('lw'))
patches = [Circle((x_, y_), s_) for x_, y_, s_ in np.broadcast(x, y, s)]
collection = PatchCollection(patches, **kwargs)
if c is not None:
collection.set_array(np.asarray(c))
collection.set_clim(vmin, vmax)
ax = plt.gca()
ax.add_collection(collection)
ax.autoscale_view()
if c is not None:
plt.sci(collection)
return collection
def myscatter(ax, colormap, x, y, radii, colors):
for x1,y1,r,c in zip(x, y, radii, colormap(colors)):
ax.add_patch(Circle((x1,y1), r, fc=c))
class BallBeam():
""" BallBeam
Simple ball and beam simulation built to interface easily with OpenAI's
gym environments.
System dynamics
---------------
dx/dt = v(t)
dv/dt = -m*g*sin(theta(t))/((I + 1)*m)
Parameters
----------
time_step : time of one simulation step, float (s)
beam_length : length of beam, float (units)
max_angle : max of abs(angle), float (rads)
init_velocity : initial speed of ball, float (units/s)
"""
def __init__(self, timestep=0.01, beam_length=1.08, max_angle=20*3.14/180, init_velocity=0.0):
self.dt = timestep # time step
self.g = 9.82 # gravity
self.r = 0.0159 # ball radius
self.L = beam_length # beam length
self.I = (2/5*self.r**2 ) # solid ball inertia (omits mass)
self.init_velocity = init_velocity # initial velocity
self.max_angle = max_angle # max beam angle (rad)
self.reset()
self.human_rendered = False
self.machine_rendered = False
def reset(self):
radius = self.L/2 # beam radius
self.t = 0.0 # time
self.x = 0.4 # ball position x
self.y = self.r # ball position y
self.v = self.init_velocity # ball velocity
self.theta = 0.0 # beam angle (rad)
self.dtheta = 0.0 # beam angle change (rad)
self.v_x = 0.0 # velocity x component
self.v_y = 0.0 # velocity y component
self.lim_x = [-cos(self.theta)*radius, # geam limits x
cos(self.theta)*radius]
self.lim_y = [-sin(self.theta)*radius, # beam limits y
sin(self.theta)*radius]
def update(self, angle):
"""
Update simulation with one time step
Parameters
----------
angle : angle the beam should be set to, float (rad)
"""
radius = self.L/2
# simulation could be improved further by using voltage as input and a
# motor simulation deciding theta
theta = max(-self.max_angle, min(self.max_angle, angle))
# store angle change for angular velocity
self.dtheta = (theta - self.theta)
self.theta = theta
if self.on_beam:
x = self.x
y = self.y
# dynamics on beam
self.v += (x*self.dtheta*self.dtheta-self.g*sin(self.theta))*(5/7)*self.dt
self.x += self.v*self.dt
self.y = self.r/cos(self.theta) + self.x*sin(self.theta)
# keep track of velocities for x and y
self.v_x = (self.x - x)/self.dt
self.v_y = (self.y - y)/self.dt
else:
# free fall dynamics off beam
self.v_y -= self.g*self.dt
self.v = (self.v_x**2 + self.v_y**2)**0.5
self.x += self.v_x*self.dt
self.y += self.v_y*self.dt
# edge of beam
self.lim_x = [-cos(self.theta)*radius, cos(self.theta)*radius]
self.lim_y = [-sin(self.theta)*radius, sin(self.theta)*radius]
# update time
self.t += self.dt
def _init_render(self, setpoint, mode):
""" Initialize rendering """
radius = self.L/2
if mode == 'human':
self.human_rendered = True
plt.ion()
fig, ax = plt.subplots(1, 1, figsize=(8, 4))
fig.canvas.set_window_title('Beam & Ball')
ax.set(xlim = (-2*radius, 2*radius), ylim = (-self.L/2, self.L/2))
# draw ball
self.ball_plot = Circle((self.x, self.y), self.r)
ax.add_patch(self.ball_plot)
ax.patches[0].set_color('red')
# draw beam
ax.plot([-cos(self.theta)*radius, cos(self.theta)*radius],
[-sin(self.theta)*radius, sin(self.theta)*radius], lw=4, color='black')
ax.plot(0.0, 0.0, '.', ms=20)
if setpoint is not None:
ax.add_patch(Polygon( \
[[setpoint*cos(self.theta), -0.01*self.L + setpoint*sin(self.theta)],
[setpoint*cos(self.theta) - 0.015*self.L, -0.03*self.L + setpoint*sin(self.theta)],
[setpoint*cos(self.theta) + 0.015*self.L, -0.03*self.L + setpoint*sin(self.theta)]]))
ax.patches[1].set_color('red')
self.fig = fig
self.ax = ax
else:
self.machine_rendered = True
fig, ax = plt.subplots(1, 1, figsize=(8, 4))
# avoid drawing plot but still initialize
_ = fig.canvas.set_window_title('Beam & Ball')
_ = ax.set(xlim = (-2*radius, 2*radius), ylim = (-self.L/2, self.L/2))
# draw ball
self.ball_plot = Circle((self.x, self.y), self.r)
_ = ax.add_patch(self.ball_plot)
_ = ax.patches[0].set_color('red')
# draw beam
_ = ax.plot([-cos(self.theta)*radius, cos(self.theta)*radius],
[-sin(self.theta)*radius, sin(self.theta)*radius], lw=4, color='black')
_ = ax.plot(0.0, 0.0, '.', ms=20)
if setpoint is not None:
_ = ax.add_patch(Polygon( \
[[setpoint*cos(self.theta), -0.01*self.L + setpoint*sin(self.theta)],
[setpoint*cos(self.theta) - 0.015*self.L, -0.03*self.L + setpoint*sin(self.theta)],
[setpoint*cos(self.theta) + 0.015*self.L, -0.03*self.L + setpoint*sin(self.theta)]]))
_ = ax.patches[1].set_color('red')
self.machine_fig = fig
self.machine_ax = ax
def render(self, setpoint=None, mode='human'):
"""
Render simulation at it's current state
Parameters
----------
setpoint : optional marking of the ball setpoint, float (units)
mode : rendering mode, str [human, machine]
"""
if (not self.human_rendered and mode == 'human') or \
(not self.machine_rendered and mode == 'machine'):
self._init_render(setpoint, mode)
if mode == 'human':
# update ball
self.ball_plot.set_center((self.x, self.y))
# update beam
self.ax.lines[0].set(xdata=self.lim_x, ydata=self.lim_y)
# mark setpoint
if setpoint is not None:
self.ax.patches[1].set_xy( \
[[setpoint*cos(self.theta), -0.01*self.L + setpoint*sin(self.theta)],
[setpoint*cos(self.theta) - 0.015*self.L, -0.03*self.L + setpoint*sin(self.theta)],
[setpoint*cos(self.theta) + 0.015*self.L, -0.03*self.L + setpoint*sin(self.theta)]])
# update figure
self.fig.canvas.draw()
self.fig.canvas.flush_events()
else:
# update ball
_ = self.ball_plot.set_center((self.x, self.y))
# update beam
_ = self.machine_ax.lines[0].set(xdata=self.lim_x, ydata=self.lim_y)
# mark setpoint
if setpoint is not None:
_ = self.machine_ax.patches[1].set_xy( \
[[setpoint*cos(self.theta), -0.01*self.L + setpoint*sin(self.theta)],
[setpoint*cos(self.theta) - 0.015*self.L, -0.03*self.L + setpoint*sin(self.theta)],
[setpoint*cos(self.theta) + 0.015*self.L, -0.03*self.L + setpoint*sin(self.theta)]])
# update figure
_ = self.machine_fig.canvas.draw()
_ = self.machine_fig.canvas.flush_events()
@property
def on_beam(self):
"""
Check if ball is still on the beam
Returns
-------
on_beam : if ball is still located on the beam, bool
"""
return self.lim_x[0] < self.x and self.lim_x[1] > self.x
def __init__(self, map, schedule):
self.map = map
self.schedule = schedule
aspect = map["map"]["dimensions"][0] / map["map"]["dimensions"][1]
self.fig = plt.figure(frameon=False, figsize=(4 * aspect, 4))
self.ax = self.fig.add_subplot(111, aspect='equal')
self.fig.subplots_adjust(left=0,
right=1,
bottom=0,
top=1,
wspace=None,
hspace=None)
# self.ax.set_frame_on(False)
self.patches = []
self.artists = []
self.agents = dict()
self.agent_names = dict()
# create boundary patch
xmin = -0.5
ymin = -0.5
xmax = map["map"]["dimensions"][0] - 0.5
ymax = map["map"]["dimensions"][1] - 0.5
# self.ax.relim()
plt.xlim(xmin, xmax)
plt.ylim(ymin, ymax)
# self.ax.set_xticks([])
# self.ax.set_yticks([])
# plt.axis('off')
# self.ax.axis('tight')
# self.ax.axis('off')
self.patches.append(
Rectangle((xmin, ymin),
xmax - xmin,
ymax - ymin,
facecolor='none',
edgecolor='red'))
for o in map["map"]["obstacles"]:
x, y = o[0], o[1]
self.patches.append(
Rectangle((x - 0.5, y - 0.5),
1,
1,
facecolor='red',
edgecolor='red'))
# create agents:
self.T = 0
# draw goals first
for d, i in zip(map["agents"], range(0, len(map["agents"]))):
if "goal" in d:
goals = [d["goal"]]
if "potentialGoals" in d:
goals = [goal for goal in d["potentialGoals"]]
for goal in goals:
self.patches.append(
Rectangle((goal[0] - 0.25, goal[1] - 0.25),
0.5,
0.5,
facecolor=Colors[i % len(Colors)],
edgecolor='black',
alpha=0.5))
for d, i in zip(map["agents"], range(0, len(map["agents"]))):
name = d["name"]
self.agents[name] = Circle((d["start"][0], d["start"][1]),
0.3,
facecolor=Colors[i % len(Colors)],
edgecolor='black')
self.agents[name].original_face_color = Colors[i % len(Colors)]
self.patches.append(self.agents[name])
self.T = max(self.T, schedule["schedule"][name][-1]["t"])
self.agent_names[name] = self.ax.text(d["start"][0], d["start"][1],
name.replace('agent', ''))
self.agent_names[name].set_horizontalalignment('center')
self.agent_names[name].set_verticalalignment('center')
self.artists.append(self.agent_names[name])
# self.ax.set_axis_off()
# self.fig.axes[0].set_visible(False)
# self.fig.axes.get_yaxis().set_visible(False)
# self.fig.tight_layout()
self.anim = animation.FuncAnimation(self.fig,
self.animate_func,
init_func=self.init_func,
frames=int(self.T + 1) * 10,
interval=100,
blit=True)
def circles(self, x, y, s, c='b', vmin=None, vmax=None, **kwargs):
"""
See https://gist.github.com/syrte/592a062c562cd2a98a83
Make a scatter plot of circles.
Similar to plt.scatter, but the size of circles are in data scale.
Parameters
----------
x, y : scalar or array_like, shape (n, )
Input data
s : scalar or array_like, shape (n, )
Radius of circles.
c : color or sequence of color, optional, default : 'b'
`c` can be a single color format string, or a sequence of color
specifications of length `N`, or a sequence of `N` numbers to be
mapped to colors using the `cmap` and `norm` specified via kwargs.
Note that `c` should not be a single numeric RGB or RGBA sequence
because that is indistinguishable from an array of values
to be colormapped. (If you insist, use `color` instead.)
`c` can be a 2-D array in which the rows are RGB or RGBA, however.
vmin, vmax : scalar, optional, default: None
`vmin` and `vmax` are used in conjunction with `norm` to normalize
luminance data. If either are `None`, the min and max of the
color array is used.
kwargs : `~matplotlib.collections.Collection` properties
Eg. alpha, edgecolor(ec), facecolor(fc), linewidth(lw), linestyle(ls),
norm, cmap, transform, etc.
Returns
-------
paths : `~matplotlib.collections.PathCollection`
Examples
--------
a = np.arange(11)
circles(a, a, s=a*0.2, c=a, alpha=0.5, ec='none')
plt.colorbar()
License
--------
This code is under [The BSD 3-Clause License]
(http://opensource.org/licenses/BSD-3-Clause)
"""
if np.isscalar(c):
kwargs.setdefault('color', c)
c = None
if 'fc' in kwargs:
kwargs.setdefault('facecolor', kwargs.pop('fc'))
if 'ec' in kwargs:
kwargs.setdefault('edgecolor', kwargs.pop('ec'))
if 'ls' in kwargs:
kwargs.setdefault('linestyle', kwargs.pop('ls'))
if 'lw' in kwargs:
kwargs.setdefault('linewidth', kwargs.pop('lw'))
# You can set `facecolor` with an array for each patch,
# while you can only set `facecolors` with a value for all.
zipped = np.broadcast(x, y, s)
patches = [Circle((x_, y_), s_) for x_, y_, s_ in zipped]
collection = PatchCollection(patches, **kwargs)
if c is not None:
c = np.broadcast_to(c, zipped.shape).ravel()
collection.set_array(c)
collection.set_clim(vmin, vmax)
ax = plt.gca()
ax.add_collection(collection)
ax.autoscale_view()
# plt.draw_if_interactive()
if c is not None:
plt.sci(collection)
def extract_minutiae_cylinder(img_input,
minutiae_input,
ROI=None,
num_ori=12,
angle=None,
processing=None):
# for the latent or the low quality rolled print
minutiae = minutiae_input.copy()
img = img_input.copy()
if processing == 'STFT':
img = LP.STFT(img)
elif processing == 'contrast':
img = LP.local_constrast_enhancement(img)
elif processing == 'texture':
img = LP.FastCartoonTexture(img)
sigma = 5**2
if ROI is not None:
h, w = ROI.shape
for i in range(h):
for j in range(w):
if ROI[i, j] == 0:
img[i, j] = 255
h, w = ROI.shape
col_sum = np.sum(ROI, axis=0)
ind = [x for x in range(len(col_sum)) if col_sum[x] > 0]
min_x = np.max([np.min(ind) - 32, 0])
max_x = np.min([np.max(ind) + 32, w])
row_sum = np.sum(ROI, axis=1)
ind = [x for x in range(len(row_sum)) if row_sum[x] > 0]
min_y = np.max([np.min(ind) - 32, 0])
max_y = np.min([np.max(ind) + 32, h])
ROI = ROI[min_y:max_y, min_x:max_x]
img = img[min_y:max_y, min_x:max_x]
minutiae[:, 0] = minutiae[:, 0] - min_x
minutiae[:, 1] = minutiae[:, 1] - min_y
else:
h, w = img.shape[0:2]
ROI = np.ones((h, w))
# rotate the image and ROI, and also update minutiae points
h0, w0 = ROI.shape
if angle is not None:
h02 = (h0 + 1) / 2
w02 = (w0 + 1) / 2
img = rotate(img, angle)
ROI = rotate(ROI, angle)
h, w = ROI.shape
h2 = (h + 1) / 2
w2 = (w + 1) / 2
angle = -angle / 180.0 * math.pi
cosTheta = math.cos(angle)
sinTheta = math.sin(angle)
xx = (minutiae[:, 0] - w02) * cosTheta - (minutiae[:, 1] -
h02) * sinTheta + w2
yy = (minutiae[:, 0] - w02) * sinTheta + (minutiae[:, 1] -
h02) * cosTheta + h2
ori = minutiae[:, 2] - angle
#
minutiae[:, 0] = xx
minutiae[:, 1] = yy
minutiae[:, 2] = ori
show = 0
if show:
minu_num = minutiae.shape[0]
fig, ax = plt.subplots(1)
ax.set_aspect('equal')
R = 10
arrow_len = 15
ax.imshow(img, cmap='gray')
for i in range(0, minu_num):
xx = minutiae[i, 0]
yy = minutiae[i, 1]
circ = Circle((xx, yy), R, color='r', fill=False)
ax.add_patch(circ)
ori = -minutiae[i, 2]
dx = math.cos(ori) * arrow_len
dy = math.sin(ori) * arrow_len
ax.arrow(xx,
yy,
dx,
dy,
head_width=0.05,
head_length=0.1,
fc='r',
ec='r')
plt.show()
h, w = ROI.shape
minutiae_cylinder = np.zeros((h, w, num_ori), dtype=float)
cylinder_ori = np.asarray(range(num_ori)) * math.pi * 2 / num_ori
Y, X = np.mgrid[0:h, 0:w]
minu_num = minutiae.shape[0]
for i in range(0, minu_num):
xx = minutiae[i, 0]
yy = minutiae[i, 1]
if yy < 0 or xx < 0:
continue
print xx, yy
minu_num = minutiae.shape[0]
fig, ax = plt.subplots(1)
ax.set_aspect('equal')
R = 10
arrow_len = 15
ax.imshow(img, cmap='gray')
for i in range(0, minu_num):
xx = minutiae[i, 0]
yy = minutiae[i, 1]
circ = Circle((xx, yy), R, color='r', fill=False)
ax.add_patch(circ)
ori = -minutiae[i, 2]
dx = math.cos(ori) * arrow_len
dy = math.sin(ori) * arrow_len
ax.arrow(xx,
yy,
dx,
dy,
head_width=0.05,
head_length=0.1,
fc='r',
ec='r')
plt.show()
weight = np.exp(-((X - xx) * (X - xx) + (Y - yy) * (Y - yy)) / sigma)
ori = minutiae[i, 2]
if ori < 0:
ori += np.pi * 2
if ori > np.pi * 2:
ori -= np.pi * 2
for j in range(num_ori):
ori_diff = np.fabs(ori - cylinder_ori[j])
if ori_diff > np.pi * 2:
ori_diff = ori_diff - np.pi * 2
ori_diff = np.min([ori_diff, np.pi * 2 - ori_diff])
minutiae_cylinder[:, :,
j] += weight * np.exp(-ori_diff / np.pi * 6)
show = 0
if show:
fig, ax = plt.subplots(1)
ax.set_aspect('equal')
R = 10
arrow_len = 15
ax.imshow(img, cmap='gray')
for i in range(0, minu_num):
xx = minutiae[i, 0]
yy = minutiae[i, 1]
circ = Circle((xx, yy), R, color='r', fill=False)
ax.add_patch(circ)
ori = -minutiae[i, 2]
dx = math.cos(ori) * arrow_len
dy = math.sin(ori) * arrow_len
ax.arrow(xx,
yy,
dx,
dy,
head_width=0.05,
head_length=0.1,
fc='r',
ec='r')
plt.show()
return img, ROI, minutiae_cylinder
def circleFromRMS(xy, rad): cir = Circle(xy, rad) cir.set_clip_box(ax.bbox) cir.set_alpha(0.2) cir.set_facecolor(tableau20[0]) return cir
class CircleSpanSelector:
"""
Select a center/radius range of the circle for a matplotlib Axes
Example usage:
ax = subplot(111)
ax.plot(x,y)
def onselect(center, radius, x, y):
print center, radius
span = CircleSpanSelector(ax, onselect)
"""
def __init__(self, ax, onselect, minspan=None, useblit=False, circprops=None):
"""
Create a span selector in ax. When a selection is made, clear
the span and call onselect with
onselect(center, radius, x, y)
where x and y are the coordinate used to calculate the radius
and clear the span.
If minspan is not None, ignore events smaller than minspan
The span rect is drawn with rectprops; default
circprops = dict(fc='blue', alpha=0.5)
set the visible attribute to False if you want to turn off
the functionality of the span selector
"""
if circprops is None:
circprops = dict(fc='w', alpha=0.5)
self.ax = ax
self.visible = True
self.canvas = ax.figure.canvas
self.canvas.mpl_connect('motion_notify_event', self.onmove)
self.canvas.mpl_connect('button_press_event', self.press)
self.canvas.mpl_connect('button_release_event', self.release)
self.canvas.mpl_connect('draw_event', self.update_background)
self.circ = None
self.background = None
self.circprops = circprops
self.onselect = onselect
self.useblit = useblit
self.minspan = minspan
self.circ = Circle( (0,0), 1, **self.circprops)
self.unit_verts = [v for v in self.circ.verts]
self.circ.set_visible(False)
if not self.useblit: self.ax.add_patch(self.circ)
self.pressx = None
def update_background(self, event):
'force an update of the background'
if self.useblit:
self.background = self.canvas.copy_from_bbox(self.ax.bbox)
def ignore(self, event):
'return True if event should be ignored'
return event.inaxes!=self.ax or not self.visible or event.button !=1
def press(self, event):
'on button press event'
if self.ignore(event): return
print "press"
self.circ.set_visible(self.visible)
self.pressx = event.xdata
self.pressy = event.ydata
self.circ.set_visible(False)
return False
def release(self, event):
'on button release event'
if self.pressx is None or self.ignore(event): return
if self.pressy is None or self.ignore(event): return
self.canvas.draw()
self.center = [self.pressx, self.pressy]
self.radius = sqrt((event.xdata-self.center[0])**2 + (event.ydata-self.center[1])**2)
y = event.ydata
x = event.xdata
if self.minspan is not None and radius<self.minspan: return
self.onselect(self.center, self.radius, x, y)
self.pressx = None
self.pressy = None
return False
def update(self):
'draw using newfangled blit or oldfangled draw depending on useblit'
if self.useblit:
if self.background is not None:
self.canvas.restore_region(self.background)
self.ax.draw_artist(self.circ)
self.canvas.blit(self.ax.bbox)
else:
self.canvas.draw_idle()
return False
def onmove(self, event):
'on motion notify event'
if self.pressx is None or self.ignore(event): return
if self.pressy is None or self.ignore(event): return
self.center = [self.pressx,self.pressy]
self.radius = sqrt((event.xdata-self.center[0])**2 + (event.ydata-self.center[1])**2)
if self.radius > 0.5:
self.circ.set_visible(True)
else:
self.circ.set_visible(False)
self.circ.verts = [(v[0]*self.radius+self.center[0],v[1]*self.radius+self.center[1]) for v in self.unit_verts]
pylab.draw()
self.update()
return False
min = tf.math.reduce_min(prediction)
fps = 1 / (end_time - start_time)
# prediction = prediction > 0.5
print(f"{image_file_name} MIN = {min}, MAX = {max}, FPS = {fps:.2f}")
fig, axes = plt.subplots(
4, 5, figsize=(16, 16)) # the number of images in the grid is 5*5 (25)
threshold = 0.5
for i, ax in enumerate(axes.flat):
if i == prediction.shape[0]:
break
show_img = np.zeros((64, 64))
ax.imshow(prediction[i], cmap='gray', vmin=0, vmax=1)
# ax.imshow(img[0])
cx, cy = np.unravel_index(prediction[i].argmax(), prediction[i].shape)
if prediction[i, cx, cy] > threshold:
patches = [Circle((cy, cx), radius=1, color='red')]
for p in patches:
ax.add_patch(p)
ax.set_title(labels[i])
ax.imshow(img[0])
plt.subplots_adjust(left=0,
bottom=0,
right=1,
top=0.97,
wspace=0,
hspace=0.25)
plt.show()
pass
def _add_patches(self, df, method, fill, ax, diagonal=True):
width, height = df.shape
patches = []
colors = []
for x in range(width):
for y in range(height):
if fill == 'lower' and x > y:
continue
elif fill == 'upper' and x < y:
continue
if diagonal is False and x == y:
continue
datum = (df.ix[x, y] + 1.) / 2.
d = df.ix[x, y]
d_abs = np.abs(d)
#c = self.pvalues[x, y]
rotate = -45 if d > 0 else +45
#cmap = self.poscm if d >= 0 else self.negcm
if method in ['ellipse', 'square', 'rectangle', 'color']:
if method == 'ellipse':
func = Ellipse
patch = func((x, y), width=1 * self.shrink,
height=(self.shrink - d_abs * self.shrink), angle=rotate)
else:
func = Rectangle
w = h = d_abs * self.shrink
# FIXME shring must be <=1
offset = (1 - w) / 2.
if method == 'color':
w = 1
h = 1
offset = 0
patch = func((x + offset - .5, y + offset - .5), width=w,
height=h, angle=0)
if self.edgecolor:
patch.set_edgecolor(self.edgecolor)
# patch.set_facecolor(cmap(d_abs))
colors.append(datum)
if d_abs > 0.05:
patch.set_linestyle('dotted')
# ax.add_artist(patch)
patches.append(patch)
# FIXME edgecolor is always printed
elif method == 'circle':
patch = Circle((x, y), radius=d_abs * self.shrink / 2.)
if self.edgecolor:
patch.set_edgecolor(self.edgecolor)
# patch.set_facecolor(cmap(d_abs))
colors.append(datum)
if d_abs > 0.05:
patch.set_linestyle('dotted')
# ax.add_artist(patch)
patches.append(patch)
elif method in ['number', 'text']:
if d < 0:
edgecolor = self.cm(-1.0)
elif d >= 0:
edgecolor = self.cm(1.0)
d_str = "{:.2f}".format(d).replace(
"0.", ".").replace(".00", "")
ax.text(x, y, d_str, color=edgecolor,
fontsize=self.fontsize, horizontalalignment='center',
weight='bold', alpha=max(0.5, d_abs),
withdash=False)
elif method == 'pie':
S = 360 * d_abs
patch = [
Wedge((x, y), 1 * self.shrink / 2., -90, S - 90),
Wedge((x, y), 1 * self.shrink / 2., S - 90, 360 - 90),
]
# patch[0].set_facecolor(cmap(d_abs))
# patch[1].set_facecolor('white')
colors.append(datum)
colors.append(0.5)
if self.edgecolor:
patch[0].set_edgecolor(self.edgecolor)
patch[1].set_edgecolor(self.edgecolor)
# ax.add_artist(patch[0])
# ax.add_artist(patch[1])
patches.append(patch[0])
patches.append(patch[1])
else:
raise ValueError(
'Method for the symbols is not known. Use e.g, square, circle')
if self.binarise_color:
colors = [1 if color > 0.5 else -1 for color in colors]
if len(patches):
col1 = PatchCollection(
patches, array=np.array(colors), cmap=self.cm)
ax.add_collection(col1)
self.collection = col1
if __name__ == "__main__":
import matplotlib.pyplot as plt
ax = plt.gca()
ax.set_aspect(1.)
at = AnchoredText("Figure 1a",
loc=2, frameon=True)
at.patch.set_boxstyle("round,pad=0.,rounding_size=0.2")
ax.add_artist(at)
from matplotlib.patches import Circle
ada = AnchoredDrawingArea(20, 20, 0, 0,
loc=1, pad=0., frameon=False)
p = Circle((10, 10), 10)
ada.da.add_artist(p)
ax.add_artist(ada)
# draw an ellipse of width=0.1, height=0.15 in the data coordinate
ae = AnchoredEllipse(ax.transData, width=0.1, height=0.15, angle=0.,
loc=3, pad=0.5, borderpad=0.4, frameon=True)
ax.add_artist(ae)
# draw a horizontal bar with length of 0.1 in Data coordinate
# (ax.transData) with a label underneath.
asb = AnchoredSizeBar(ax.transData,
0.1,
r"1$^{\prime}$",
loc=8,
def __init__(self,
subarray,
axes=None,
autoupdate=True,
tel_scale=2.0,
alpha=0.7,
title=None,
radius=None,
frame=GroundFrame()):
self.frame = frame
self.subarray = subarray
# get the telescope positions. If a new frame is set, this will
# transform to the new frame.
self.tel_coords = subarray.tel_coords.transform_to(frame)
# set up colors per telescope type
tel_types = [str(tel) for tel in subarray.tels.values()]
if radius is None:
# set radius to the mirror radius (so big tels appear big)
radius = [
np.sqrt(tel.optics.mirror_area.to("m2").value) * tel_scale
for tel in subarray.tel.values()
]
if title is None:
title = subarray.name
# get default matplotlib color cycle (depends on the current style)
color_cycle = cycle(plt.rcParams['axes.prop_cycle'].by_key()['color'])
# map a color to each telescope type:
tel_type_to_color = {}
for tel_type in list(set(tel_types)):
tel_type_to_color[tel_type] = next(color_cycle)
tel_color = [tel_type_to_color[ttype] for ttype in tel_types]
patches = []
for x, y, r, c in zip(list(self.tel_coords.x.value),
list(self.tel_coords.y.value), list(radius),
tel_color):
patches.append(
Circle(
xy=(x, y),
radius=r,
fill=True,
color=c,
alpha=alpha,
))
# build the legend:
legend_elements = []
for ttype in list(set(tel_types)):
color = tel_type_to_color[ttype]
legend_elements.append(
Line2D([0], [0],
marker='o',
color=color,
label=ttype,
markersize=10,
alpha=alpha,
linewidth=0))
plt.legend(handles=legend_elements)
self.tel_colors = tel_color
self.autoupdate = autoupdate
self.telescopes = PatchCollection(patches, match_original=True)
self.telescopes.set_linewidth(2.0)
self.axes = axes or plt.gca()
self.axes.add_collection(self.telescopes)
self.axes.set_aspect(1.0)
self.axes.set_title(title)
self._labels = []
self._quiver = None
self.axes.autoscale_view()
def example():
#--------------------------------#
# Parameters
#--------------------------------#
# Simulation
wl = 400.
k = 2*pi/wl
w = 200
h = 800
m = 1
n = 2
# Plotting
res = 500
xmax = 800
Ro = 1. #distance to measure field (m)
angle_res = 100
#--------------------------------#
# Algorithm
dipoles = getDipoles(m,n,w,h)
xs = ys = np.linspace(-xmax,xmax,res)
X,Y = np.meshgrid(xs,ys)
for di,d in enumerate(dipoles):
R = getR(d[0],d[1],X,Y)
phi = pi*(getPhase(m,n,di))
if di==0: Fz = 1/R*exp(1j*(k*R + phi))
else: Fz += 1/R*exp(1j*(k*R + phi))
# Plot Real Field
fig = plt.figure()
ax = fig.add_subplot(111)
Fz *= -1 #flip values so plot color matches dipole color
Fz /= np.amax(abs(Fz))
scale = 0.01
im = ax.imshow(Fz.real,extent=putil.getExtent(xs,ys),vmax=scale,vmin=-1*scale,cmap='RdBu')
fig.colorbar(im)
drawDipoleBox(m,n,w,h,ax)
for di,d in enumerate(dipoles):
p = getPhase(m,n,di)
ax.add_patch(Circle(d,15,facecolor=colors[p]))
# Power plot
fig = plt.figure()
ax = fig.add_subplot(111)
P = abs(Fz)**2
P /= np.amax(P)
im = ax.imshow(P,extent=putil.getExtent(xs,ys),vmax=sqrt(scale),cmap='hot')
fig.colorbar(im)
# Plot Farfield
ff_fig = plt.figure()
ff_ax = ff_fig.add_subplot(111,polar=True)
ff_ax.grid(True)
FFplot(ff_ax,wl,w,h,m,n,Ro=Ro,angle_res=angle_res)
print getFF(wl,w,h,m,n,0)
plt.show()
return 0
for i in range(3):
for j in range(n_col):
ax = add_subplot(i, j, projection="3d")
ax.axis("off")
col1_axs = axs[:, :3]
plot_neuron_morphology(
label1_ids, label1_inputs, label1_outputs, col1_axs, row_label=True
)
col1_axs[0, 1].set_title(label1)
legend_elements = []
for ct in connection_types:
p = Circle(
(-1, -1), facecolor=connection_colors[ct], label=ct, linewidth=0, radius=1
)
legend_elements.append(p)
col1_axs[2, 0].legend(
handles=legend_elements, bbox_to_anchor=(0, 0), loc="upper left"
)
col2_axs = axs[:, 3:]
plot_neuron_morphology(
label2_ids, label2_inputs, label2_outputs, col2_axs, row_label=True
)
col2_axs[0, 1].set_title(label2)
plt.tight_layout()
stashfig(f"morpho-compare-{label1}_{label2}")
def add3Dcircle(x, y, z, r, color, axe, direction):
#edgecolor="black"
p = Circle((x, y), r, facecolor=color)
axe.add_patch(p)
art3d.pathpatch_2d_to_3d(p, z=z, zdir=direction)
import matplotlib.cm as cm
import matplotlib.pyplot as plt
from matplotlib.patches import Circle, PathPatch
from matplotlib.path import Path
from matplotlib.transforms import Affine2D
import numpy as np
r = np.random.rand(50)
t = np.random.rand(50) * np.pi * 2.0
x = r * np.cos(t)
y = r * np.sin(t)
fig, ax = plt.subplots(figsize=(6, 6))
circle = Circle((0, 0),
1,
facecolor='none',
edgecolor=(0, 0.8, 0.8),
linewidth=3,
alpha=0.5)
ax.add_patch(circle)
im = plt.imshow(np.random.random((100, 100)),
origin='lower',
cmap=cm.winter,
interpolation='spline36',
extent=([-1, 1, -1, 1]))
im.set_clip_path(circle)
plt.plot(x, y, 'o', color=(0.9, 0.9, 1.0), alpha=0.8)
# Dolphin from OpenClipart library by Andy Fitzsimon
# <cc:License rdf:about="http://web.resource.org/cc/PublicDomain">
def runSlices(opsimName,
metadata,
simdata,
fields,
bins,
args,
opsDb,
verbose=False):
# Set up the movie slicer.
movieslicer = setupMovieSlicer(simdata, bins)
# Set up formatting for output suffix.
sliceformat = '%s0%dd' % ('%', int(np.log10(len(movieslicer))) + 1)
# Get the telescope latitude info.
lat_tele = Site(name='LSST').latitude_rad
# Run through the movie slicer slicePoints and generate plots at each point.
for i, ms in enumerate(movieslicer):
t = time.time()
slicenumber = sliceformat % (i)
if verbose:
print(slicenumber)
# Set up metrics.
if args.movieStepsize != 0:
tstep = args.movieStepsize
else:
tstep = ms['slicePoint']['binRight'] - bins[i]
if tstep > 1:
tstep = 40. / 24. / 60. / 60.
# Add simple view of time to plot label.
times_from_start = ms['slicePoint']['binRight'] - (int(bins[0]) +
0.16 - 0.5)
# Opsim years are 365 days (not 365.25)
years = int(times_from_start / 365)
days = times_from_start - years * 365
plotlabel = 'Year %d Day %.4f' % (years, days)
# Set up metrics.
metricList, plotDictList = setupMetrics(
opsimName,
metadata,
plotlabel=plotlabel,
t0=ms['slicePoint']['binRight'],
tStep=tstep,
years=years,
verbose=verbose)
# Identify the subset of simdata in the movieslicer 'data slice'
simdatasubset = simdata[ms['idxs']]
# Set up opsim slicer on subset of simdata provided by movieslicer
opslicer = slicers.OpsimFieldSlicer()
# Set up metricBundles to combine metrics, plotdicts and slicer.
bundles = []
sqlconstraint = ''
for metric, plotDict in zip(metricList, plotDictList):
bundles.append(
metricBundles.MetricBundle(metric,
opslicer,
constraint=sqlconstraint,
metadata=metadata,
runName=opsimName,
plotDict=plotDict))
# Remove (default) stackers from bundles, because we've already run them above on the original data.
for mb in bundles:
mb.stackerList = []
bundledict = metricBundles.makeBundlesDictFromList(bundles)
# Set up metricBundleGroup to handle metrics calculation + plotting
bg = metricBundles.MetricBundleGroup(bundledict,
opsDb,
outDir=args.outDir,
resultsDb=None,
saveEarly=False)
# 'Hack' bundleGroup to just go ahead and run the metrics, without querying the database.
simData = simdatasubset
bg.fieldData = fields
bg.setCurrent(sqlconstraint)
bg.runCurrent(constraint=sqlconstraint, simData=simData)
# Plot data each metric, for this slice of the movie, adding slicenumber as a suffix for output plots.
# Plotting here, rather than automatically via sliceMetric method because we're going to rotate the sky,
# and add extra legend info and figure text (for FilterColors metric).
ph = plots.PlotHandler(outDir=args.outDir,
figformat='png',
dpi=72,
thumbnail=False,
savefig=False)
obsnow = np.where(simdatasubset['observationStartMJD'] ==
simdatasubset['observationStartMJD'].max())[0]
raCen = np.radians(
np.mean(simdatasubset[obsnow]['observationStartLST']))
# Calculate horizon location.
horizonlon, horizonlat = addHorizon(lat_telescope=lat_tele)
# Create the plot for each metric and save it (after some additional manipulation).
for mb in bundles:
ph.setMetricBundles([mb])
fignum = ph.plot(plotFunc=plots.BaseSkyMap(),
plotDicts={'raCen': raCen})
fig = plt.figure(fignum)
ax = plt.gca()
# Add horizon and zenith.
plt.plot(horizonlon, horizonlat, 'k.', alpha=0.3, markersize=1.8)
plt.plot(0, lat_tele, 'k+')
# For the FilterColors metric, add some extra items.
if mb.metric.name == 'FilterColors':
# Add the time stamp info (plotlabel) with a fancybox.
plt.figtext(0.75,
0.9,
'%s' % (plotlabel),
bbox=dict(boxstyle='Round, pad=0.7',
fc='w',
ec='k',
alpha=0.5))
# Add a legend for the filters.
filterstacker = stackers.FilterColorStacker()
for i, f in enumerate(['u', 'g', 'r', 'i', 'z', 'y']):
plt.figtext(0.92,
0.55 - i * 0.035,
f,
color=filterstacker.filter_rgb_map[f])
# Add a moon.
moonRA = np.radians(np.mean(simdatasubset[obsnow]['moonRA']))
lon = -(moonRA - raCen - np.pi) % (np.pi * 2) - np.pi
moonDec = np.radians(np.mean(simdatasubset[obsnow]['moonDec']))
# Note that moonphase is 0-100 (translate to 0-1). 0=new.
moonPhase = np.mean(simdatasubset[obsnow]['moonPhase']) / 100.
alpha = np.max([moonPhase, 0.15])
circle = Circle((lon, moonDec),
radius=0.05,
color='k',
alpha=alpha)
ax.add_patch(circle)
# Add some explanatory text.
ecliptic = Line2D([], [], color='r', label="Ecliptic plane")
galaxy = Line2D([], [], color='b', label="Galactic plane")
horizon = Line2D([], [],
color='k',
alpha=0.3,
label="20 deg elevation limit")
moon = Line2D([], [],
color='k',
linestyle='',
marker='o',
markersize=8,
alpha=alpha,
label="\nMoon (Dark=Full)\n (Light=New)")
zenith = Line2D([], [],
color='k',
linestyle='',
marker='+',
markersize=5,
label="Zenith")
plt.legend(
handles=[horizon, zenith, galaxy, ecliptic, moon],
loc=[0.1, -0.35],
ncol=3,
frameon=False,
title=
'Aitoff plot showing HA/Dec of simulated survey pointings',
numpoints=1,
fontsize='small')
# Save figure.
plt.savefig(os.path.join(
args.outDir,
mb.metric.name + '_' + slicenumber + '_SkyMap.png'),
format='png',
dpi=72)
plt.close('all')
dt, t = dtime(t)
if verbose:
print('Ran and plotted slice %s of movieslicer in %f s' %
(slicenumber, dt))
def add_danger(self, danger_id):
""" Appends a new danger to the appropriate list of `env`, and updates
the `env` view. The position at which the danger is placed is computed
based on the rover's location and direction, but also where on the
robot that particular danger-detection sensor is located. """
"""if danger_id == left_bumper:
elif danger_id == right_bumper:
elif danger_id == left_and_right_bumper:
elif danger_id == front_left_cliff:
elif danger_id == front_right_cliff:
elif danger_id == left_cliff:
elif danger_id == right_cliff:
elif danger_id == white_tape_front_left:
elif danger_id == white_tape_front_right:
elif danger_id == white_tape_left:
elif danger_id == white_tape_right:
elif danger_id == left_wheel:
elif danger_id == right_wheel:
elif danger_id == middle_wheel:
else:
raise NotImplementedError()
"""
# Find the danger location using `danger_angle` and `danger_distance`
# TODO: maybe later
# danger_loc = conv_radial(self, danger_theta, danger_r)
# Plot
if (1 <= danger_id <= 3): # Bumper range in OIStopID
""" Adds a bump """
c = Circle(self._loc, radius = 6.25)
c.set_facecolor('0.65') # grey
c.set_edgecolor('black')
c.set_zorder(zorders['bumps'])
c.set_fill(True)
self.view.add_artist(c)
self.bumps.append(c)
self.draw()
elif (4 <= danger_id <= 7): # Cliff range in OIStopID
""" Adds a cliff """
c = Circle(self._loc, radius = 6.25)
c.set_facecolor('0.65') # grey
c.set_edgecolor('black')
c.set_zorder(zorders['cliffs'])
c.set_fill(True)
self.view.add_artist(c)
self.cliffs.append(c)
self.draw()
elif (12 <= danger_id <= 14): # Drop range in OIStopID
""" Adds a drop """
c = Circle(self._loc, radius = 6.25)
c.set_facecolor('0.65') # grey
c.set_edgecolor('black')
c.set_zorder(zorders['drops'])
c.set_fill(True)
self.view.add_artist(c)
self.drops.append(c)
self.draw()
elif (8 <= danger_id <= 11): # White tape range in OIStopID
""" Adds tape """
c = Circle(self._loc, radius = 6.25)
c.set_facecolor('0.65') # grey
c.set_edgecolor('black')
c.set_zorder(zorders['tape'])
c.set_fill(True)
self.view.add_artist(c)
self.tape.append(c)
self.draw()
else:
raise NotImplementedError()
# The following is the temporary workaround:
sys.stderr.write("danger found: " + str(danger_id)) # TODO: check to see if enum strig is a thing
Ex, Ey = np.zeros((ny, nx)), np.zeros((ny, nx))
potential = np.zeros((ny, nx))
fig = plotter.figure()
plot1 = fig.add_subplot(121)
plot2 = fig.add_subplot(122)
charge_colors = {True: '#aa0000', False: '#0000aa'}
for x, y in zip(xLocationsOnRing, yLocationsOnRing):
littleChargedParticle = chargedParticle(np.array([x, y]), dq)
ex, ey = littleChargedParticle.electricFieldforPlotting(X, Y)
Ex += ex
Ey += ey
potential += littleChargedParticle.electricPotentialforPlotting(X, Y)
plot1.add_artist(
Circle(littleChargedParticle.location,
0.01,
color=charge_colors[littleChargedParticle.charge > 0]))
plot2.add_artist(
Circle(littleChargedParticle.location,
0.01,
color=charge_colors[littleChargedParticle.charge > 0]))
color = np.log(np.sqrt(Ex**2 + Ey**2))
plot1.streamplot(X,
Y,
Ex,
Ey,
color=color,
linewidth=1,
cmap=plotter.cm.inferno,
density=3,
arrowstyle='->',
def __init__(self, xy, *args, **kwargs):
Circle.__init__(self, xy, *args, **kwargs)
xy1, z1 = (y, z), x
else:
xy1, z1 = (x, y), z
text_path = TextPath((0, 0), s, size=size, usetex=usetex)
trans = Affine2D().rotate(angle).translate(xy1[0], xy1[1])
p1 = PathPatch(trans.transform_path(text_path), **kwargs)
ax.add_patch(p1)
art3d.pathpatch_2d_to_3d(p1, z=z1, zdir=zdir)
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
p = Circle((5, 5), 3)
ax.add_patch(p)
art3d.pathpatch_2d_to_3d(p, z=0, zdir="x")
text3d(ax, (4, -2, 0), "X-axis", zdir="z", size=.5, usetex=False,
ec="none", fc="k")
text3d(ax, (12, 4, 0), "Y-axis", zdir="z", size=.5, usetex=False, angle=.5*3.14159,
ec="none", fc="k")
text3d(ax, (12, 10, 4), "Z-axis", zdir="y", size=.5, usetex=False, angle=.5*3.14159,
ec="none", fc="k")
text3d(ax, (1, 5, 0),
r"$\displaystyle G_{\mu\nu} + \Lambda g_{\mu\nu} = \frac{8\pi G}{c^4} T_{\mu\nu} $",
zdir="z", size=1, usetex=True,
ec="none", fc="k")
matplotlib.rcParams['lines.linewidth'] = 2
pyplot.axis([0, gridWidth, 0, gridHeight])
pyplot.grid(True)
# Setting the axis labels.
pyplot.xlabel('X Space')
pyplot.ylabel('Y Space')
#Give the plot a title
pyplot.title('Radius Search Plot Using Shapely (%d Points)' % (numberOfPoints))
# Draw the collision circle/boundary
cir = Circle((circleX, circleY), radius=circleRadius, fc='b')
cir.set_alpha(0.4)
pyplot.gca().add_patch(cir)
for idx, point in enumerate(pointList):
style = 'go'
iAlpha = 0.4
if(idx in matchingPoints):
style = 'ro'
iAlpha = 1
pyplot.plot(point[0], point[1], style, linewidth=1, markersize=3, alpha=iAlpha)
pyplot.savefig(os.getcwd()+'/'+str(filename))
if (label == -1):
xcord0.append(xPt)
ycord0.append(yPt)
else:
xcord1.append(xPt)
ycord1.append(yPt)
fr.close()
fig = plt.figure()
ax = fig.add_subplot(111)
ax.scatter(xcord0, ycord0, marker='s', s=90)
ax.scatter(xcord1, ycord1, marker='o', s=50, c='red')
plt.title('Support Vectors Circled')
circle = Circle((4.6581910000000004, 3.507396),
0.5,
facecolor='none',
edgecolor=(0, 0.8, 0.8),
linewidth=3,
alpha=0.5)
ax.add_patch(circle)
circle = Circle((3.4570959999999999, -0.082215999999999997),
0.5,
facecolor='none',
edgecolor=(0, 0.8, 0.8),
linewidth=3,
alpha=0.5)
ax.add_patch(circle)
circle = Circle((6.0805730000000002, 0.41888599999999998),
0.5,
facecolor='none',
edgecolor=(0, 0.8, 0.8),
linewidth=3,
def __init__(self, xy, label, fig):
self.point = Circle( (xy[0], xy[1]), .25, figure=fig)
self.label = label
self.cidpress = self.point.figure.canvas.mpl_connect('button_press_event', self.onClick)
def create_predict_update_chart(box_bg='#CCCCCC',
arrow1='#88CCFF',
arrow2='#88FF88'):
plt.figure(figsize=(3, 3), facecolor='w')
ax = plt.axes((0, 0, 1, 1), xticks=[], yticks=[], frameon=False)
#ax.set_xlim(0, 10)
#ax.set_ylim(0, 10)
pc = Circle((4, 5), 0.5, fc=box_bg)
uc = Circle((6, 5), 0.5, fc=box_bg)
ax.add_patch(pc)
ax.add_patch(uc)
plt.text(4, 5, "Predict\nStep", ha='center', va='center', fontsize=14)
plt.text(6, 5, "Update\nStep", ha='center', va='center', fontsize=14)
#btm
ax.annotate('',
xy=(4.1, 4.5),
xycoords='data',
xytext=(6, 4.5),
textcoords='data',
size=20,
arrowprops=dict(arrowstyle="simple",
fc="0.6",
ec="none",
patchB=pc,
patchA=uc,
connectionstyle="arc3,rad=-0.5"))
#top
ax.annotate('',
xy=(6, 5.5),
xycoords='data',
xytext=(4.1, 5.5),
textcoords='data',
size=20,
arrowprops=dict(arrowstyle="simple",
fc="0.6",
ec="none",
patchB=uc,
patchA=pc,
connectionstyle="arc3,rad=-0.5"))
ax.annotate('Measurement ($\mathbf{z_k}$)',
xy=(6.3, 5.4),
xycoords='data',
xytext=(6, 6),
textcoords='data',
size=18,
arrowprops=dict(arrowstyle="simple", fc="0.6", ec="none"))
ax.annotate('',
xy=(4.0, 3.5),
xycoords='data',
xytext=(4.0, 4.5),
textcoords='data',
size=18,
arrowprops=dict(arrowstyle="simple", fc="0.6", ec="none"))
ax.annotate('Initial\nConditions ($\mathbf{x_0}$)',
xy=(4.0, 5.5),
xycoords='data',
xytext=(2.5, 6.5),
textcoords='data',
size=18,
arrowprops=dict(arrowstyle="simple", fc="0.6", ec="none"))
plt.text(4,
3.4,
'State Estimate ($\mathbf{\hat{x}_k}$)',
ha='center',
va='center',
fontsize=18)
plt.axis('equal')
def plot_job_history(jobs, interval='year'):
"""Plots the job history of the user from the given list of jobs.
Args:
jobs (list): A list of jobs with type IBMQjob.
interval (str): Interval over which to examine.
Returns:
fig: A Matplotlib figure instance.
"""
def get_date(job):
"""Returns a datetime object from a IBMQJob instance.
Args:
job (IBMQJob): A job.
Returns:
dt: A datetime object.
"""
return datetime.datetime.strptime(job.creation_date(),
'%Y-%m-%dT%H:%M:%S.%fZ')
current_time = datetime.datetime.now()
if interval == 'year':
bins = [(current_time - datetime.timedelta(days=k * 365 / 12))
for k in range(12)]
elif interval == 'month':
bins = [(current_time - datetime.timedelta(days=k)) for k in range(30)]
elif interval == 'week':
bins = [(current_time - datetime.timedelta(days=k)) for k in range(7)]
binned_jobs = [0] * len(bins)
if interval == 'year':
for job in jobs:
for ind, dat in enumerate(bins):
date = get_date(job)
if date.month == dat.month:
binned_jobs[ind] += 1
break
else:
continue
else:
for job in jobs:
for ind, dat in enumerate(bins):
date = get_date(job)
if date.day == dat.day and date.month == dat.month:
binned_jobs[ind] += 1
break
else:
continue
nz_bins = []
nz_idx = []
for ind, val in enumerate(binned_jobs):
if val != 0:
nz_idx.append(ind)
nz_bins.append(val)
total_jobs = sum(binned_jobs)
colors = [
'#003f5c', '#ffa600', '#374c80', '#ff764a', '#7a5195', '#ef5675',
'#bc5090'
]
if interval == 'year':
labels = [
'{}-{}'.format(str(bins[b].year)[2:], bins[b].month)
for b in nz_idx
]
else:
labels = ['{}-{}'.format(bins[b].month, bins[b].day) for b in nz_idx]
fig, ax = plt.subplots(1, 1, figsize=(5, 5)) # pylint: disable=invalid-name
ax.pie(nz_bins[::-1],
labels=labels,
colors=colors,
textprops={'fontsize': 14},
rotatelabels=True,
counterclock=False)
ax.add_artist(Circle((0, 0), 0.7, color='white', zorder=1))
ax.text(0,
0,
total_jobs,
horizontalalignment='center',
verticalalignment='center',
fontsize=26)
fig.tight_layout()
return fig
Z = loss(B0, B1, a=1, b=1.2, c=1, cx=cx, cy=cy)
# Z = np.where(Z<600,Z,np.NAN)
# Create a figure and a 3D Axes
fig = plt.figure(figsize=(4.2, 3.1))
ax = fig.add_subplot(111, projection='3d')
vmax = 800
ax.plot_surface(B0, B1, Z, alpha=0.7, cmap='coolwarm', vmax=vmax)
ax.set_xlabel("$\\beta_1$", labelpad=0)
ax.set_ylabel("$\\beta_2$", labelpad=0)
ax.set_zlim(0, 500)
ax.tick_params(axis='x', pad=0)
ax.tick_params(axis='y', pad=0)
ax.set_xlim(-w, w)
ax.set_ylim(-h, h)
safe = Circle(xy=(0, 0), radius=lmbda, color='grey')
ax.add_patch(safe)
art3d.pathpatch_2d_to_3d(safe, z=0)
ax.plot([cx], [cy], marker='x', markersize=10, color='black')
contr = ax.contour(B0,
B1,
Z,
levels=50,
linewidths=.5,
cmap='coolwarm',
zdir='z',
offset=0,
vmax=vmax)
def _add_patches(self, df, method, fill, ax, diagonal=True):
from matplotlib.patches import Ellipse, Circle, Rectangle, Wedge
from matplotlib.collections import PatchCollection
width, height = df.shape
patches = []
colors = []
for x in range(width):
for y in range(height):
if fill == 'lower' and x > y:
continue
elif fill == 'upper' and x < y:
continue
if diagonal is False and x == y:
continue
datum = (df.ix[x, y] + 1.) / 2.
d = df.ix[x, y]
d_abs = np.abs(d)
#c = self.pvalues[x, y]
rotate = -45 if d > 0 else +45
#cmap = self.poscm if d >= 0 else self.negcm
if method in ['ellipse', 'square', 'rectangle', 'color']:
if method == 'ellipse':
func = Ellipse
patch = func(
(x, y),
width=1 * self.shrink,
height=(self.shrink - d_abs * self.shrink),
angle=rotate)
else:
func = Rectangle
w = h = d_abs * self.shrink
# FIXME shring must be <=1
offset = (1 - w) / 2.
if method == 'color':
w = 1
h = 1
offset = 0
patch = func((x + offset - .5, y + offset - .5),
width=w,
height=h,
angle=0)
if self.edgecolor:
patch.set_edgecolor(self.edgecolor)
# patch.set_facecolor(cmap(d_abs))
colors.append(datum)
if d_abs > 0.05:
patch.set_linestyle('dotted')
# ax.add_artist(patch)
patches.append(patch)
# FIXME edgecolor is always printed
elif method == 'circle':
patch = Circle((x, y), radius=d_abs * self.shrink / 2.)
if self.edgecolor:
patch.set_edgecolor(self.edgecolor)
# patch.set_facecolor(cmap(d_abs))
colors.append(datum)
if d_abs > 0.05:
patch.set_linestyle('dotted')
# ax.add_artist(patch)
patches.append(patch)
elif method in ['number', 'text']:
if d < 0:
edgecolor = self.cm(-1.0)
elif d >= 0:
edgecolor = self.cm(1.0)
d_str = "{:.2f}".format(d).replace("0.",
".").replace(".00", "")
ax.text(x,
y,
d_str,
color=edgecolor,
fontsize=self.fontsize,
horizontalalignment='center',
weight='bold',
alpha=max(0.5, d_abs),
withdash=False)
elif method == 'pie':
S = 360 * d_abs
patch = [
Wedge((x, y), 1 * self.shrink / 2., -90, S - 90),
Wedge((x, y), 1 * self.shrink / 2., S - 90, 360 - 90),
]
# patch[0].set_facecolor(cmap(d_abs))
# patch[1].set_facecolor('white')
colors.append(datum)
colors.append(0.5)
if self.edgecolor:
patch[0].set_edgecolor(self.edgecolor)
patch[1].set_edgecolor(self.edgecolor)
# ax.add_artist(patch[0])
# ax.add_artist(patch[1])
patches.append(patch[0])
patches.append(patch[1])
else:
raise ValueError(
'Method for the symbols is not known. Use e.g, square, circle'
)
if self.binarise_color:
colors = [1 if color > 0.5 else -1 for color in colors]
if len(patches):
col1 = PatchCollection(patches,
array=np.array(colors),
cmap=self.cm)
ax.add_collection(col1)
self.collection = col1
def plot_span_circle(fig: plt.Figure, ax: plt.Axes, R: PlanarTriangle,
P: Triangle, i: int) -> None:
c, r = get_span_circle(R, P, i)
circle = Circle(c, r, linestyle="--", fill=None)
ax.add_patch(circle)
def __init__(self, instance, schedule, duration):
with open(instance) as map_file:
map_data = yaml.load(map_file, Loader=yaml.SafeLoader)
aspect = (map_data["map"]["dimensions"][0] +
2) / (map_data["map"]["dimensions"][1] + 2)
self.fig, self.ax = plt.subplots(frameon=False,
figsize=(4 * aspect, 4))
self.ax.set_aspect('equal')
plt.axis('off')
self.fig.subplots_adjust(left=0,
right=1,
bottom=0,
top=1,
wspace=None,
hspace=None)
xmin = -1
ymin = -1
xmax = map_data["map"]["dimensions"][0] + 1
ymax = map_data["map"]["dimensions"][1] + 1
plt.xlim(xmin, xmax)
plt.ylim(ymin, ymax)
for o in map_data["map"]["obstacles"]:
self.ax.add_patch(
Rectangle(o, 1.0, 1.0, facecolor='gray', alpha=0.5))
for x in range(-1, map_data["map"]["dimensions"][0] + 1):
self.ax.add_patch(
Rectangle([x, -1], 1.0, 1.0, facecolor='gray', alpha=0.5))
self.ax.add_patch(
Rectangle([x, map_data["map"]["dimensions"][1]],
1.0,
1.0,
facecolor='gray',
alpha=0.5))
for y in range(map_data["map"]["dimensions"][1]):
self.ax.add_patch(
Rectangle([-1, y], 1.0, 1.0, facecolor='gray', alpha=0.5))
self.ax.add_patch(
Rectangle([map_data["map"]["dimensions"][0], y],
1.0,
1.0,
facecolor='gray',
alpha=0.5))
self.data = np.load(schedule)
self.num_agents = len(map_data["agents"])
self.dt = self.data[1, 0] - self.data[0, 0]
self.colors = []
self.robots = []
for i in range(self.num_agents):
# plot trajectory
# line = self.ax.plot(self.data[:,1+i*4], self.data[:,1+i*4+1],alpha=0.5,linewidth=2,linestyle='dashed')
line = self.ax.plot(self.data[0:0, 1 + i * 4],
self.data[0:0, 1 + i * 4 + 1],
alpha=0.5,
linewidth=2,
linestyle='dashed')
color = line[0].get_color()
self.colors.append(color)
# plot start and goal
start = np.array(map_data["agents"][i]["start"])
goal = np.array(map_data["agents"][i]["goal"])
self.robots.append(
Circle(start + np.array([0.5, 0.5]),
0.15,
alpha=0.5,
color=color))
self.ax.add_patch(self.robots[-1])
self.ax.add_patch(
Rectangle(goal + np.array([0.3, 0.3]),
0.4,
0.4,
alpha=0.5,
color=color))
if duration < 0:
duration = int(self.data[-1, 0])
else:
duration = int(duration)
self.anim = animation.FuncAnimation(self.fig,
self.animate_func,
init_func=self.init_func,
frames=duration * 10,
interval=100,
blit=True)
def animate(self):
if self.is_sim_mode == True:
if MathsCalculations.CalcRange(
self, MathsCalculations.GetVelocity(self),
MathsCalculations.GetAngleOfProjection(self),
MathsCalculations.GetElevation(
self)) > MathsCalculations.CalcMaxHeight(
self, MathsCalculations.GetVelocity(self),
MathsCalculations.GetAngleOfProjection(self),
MathsCalculations.GetElevation(self)):
limit = MathsCalculations.CalcRange(
self, MathsCalculations.GetVelocity(self),
MathsCalculations.GetAngleOfProjection(self),
MathsCalculations.GetElevation(self))
else:
limit = MathsCalculations.CalcMaxHeight(
self, MathsCalculations.GetVelocity(self),
MathsCalculations.GetAngleOfProjection(self),
MathsCalculations.GetElevation(self))
try:
self.cl = self.figure_sm.clf()
self.ax = self.figure_sm.add_subplot()
self.circle = Circle((0, 0), 0.3)
self.ax.add_artist(self.circle)
self.ax.set_xlim([0, limit + (limit * 0.1)])
self.ax.set_ylim([0, limit + (limit * 0.1)])
self.animation1 = animation.FuncAnimation(
self.figure_sm,
self.animate_loop_sm,
frames=np.arange(
0,
MathsCalculations.CalcTimeTaken(
self, float(self.veloinp_sm.text()),
float(self.anglespin_sm.text()),
float(self.elevinp_sm.text())), 0.01),
interval=10,
repeat=False)
self.animation2 = animation.FuncAnimation(
self.figure_sm,
self.animate_trailloop_sm,
frames=np.arange(
0,
MathsCalculations.CalcTimeTaken(
self, float(self.veloinp_sm.text()),
float(self.anglespin_sm.text()),
float(self.elevinp_sm.text())), 0.01),
interval=10,
repeat=False)
self.canvas_sm.draw()
except:
print("Error")
else:
try:
self.cl = self.figure_qm.clf()
self.ax = self.figure_qm.add_subplot()
self.circle = Circle((0, 0), 0.5)
self.ax.add_artist(self.circle)
self.ax.set_xlim([0, limit] + (limit * 0.1))
self.ax.set_ylim([0, limit] + (limit * 0.1))
self.animation = animation.FuncAnimation(
self.figure_qm,
self.animate_loop_qm,
frames=np.arange(
0,
MathsCalculations.CalcTimeTaken(
self, float(self.veloinp_qm.text()),
float(self.angleinp_qm.text()),
float(self.elevinp_qm.text())), 0.01),
interval=10,
repeat=False)
self.canvas_qm.draw()
except:
print("Error")
start_points=seed.T)
ax2.streamplot(x,
z,
Vx,
Vz - u,
color=color,
linewidth=1,
cmap='afmhot',
density=5,
arrowstyle='-|>',
arrowsize=1.0,
minlength=0.4,
start_points=seed.T)
for ax in (ax1, ax2):
# Add filled circle for sphere
ax.add_patch(Circle((0, 0), a, color='C0', zorder=2))
ax.set_xlabel('$x$')
ax.set_ylabel('$z$')
ax.set_aspect('equal')
ax.set_xlim(-0.7 * xlim, 0.7 * xlim)
ax.set_ylim(-0.7 * zlim, 0.7 * zlim)
fig.tight_layout()
fig.savefig('./figures/stokesFlowStream.pdf')
fig.show()
"""
Introduction to Python for Science & Engineering
by David J. Pine
Code last edited: 2018-09-15
Streamplot example using matplotlib
"""
data = np.array(data)
xys = data[:, :2]
sphere1s = data[:, 2:5]
sphere2s = data[:, 5:8]
point1s = data[:, 8:10]
point2s = data[:, 10:12]
color2 = '#d6191b'
patches_circle = []
for xy, sphere1, sphere2, point1, point2 in zip(
xys, sphere1s, sphere2s, point1s, point2s):
xc = xy[0] + sphere2[0] - sphere1[0]
yc = xy[1] + sphere2[1] - sphere1[1]
r = sqrt(sphere1[2] * sphere1[2] + sphere2[2] * sphere2[2])
if invert_yaxis:
circle = Circle((xc, -yc), r, color=color2)
patches_circle.append(circle)
else:
circle = Circle((xc, yc), r, color=color2)
patches_circle.append(circle)
xc = xy[0] + point2[0] - sphere1[0]
yc = xy[1] + point2[1] - sphere1[1]
r = sphere1[2]
if invert_yaxis:
circle = Circle((xc, -yc), r, color=color2)
patches_circle.append(circle)
else:
circle = Circle((xc, yc), r, color=color2)
patches_circle.append(circle)
