本文整理汇总了Python中matplotlib.collections.LineCollection.set_antialiased方法的典型用法代码示例。如果您正苦于以下问题：Python LineCollection.set_antialiased方法的具体用法？Python LineCollection.set_antialiased怎么用？Python LineCollection.set_antialiased使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类matplotlib.collections.LineCollection的用法示例。
在下文中一共展示了LineCollection.set_antialiased方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: plot
# 需要导入模块: from matplotlib.collections import LineCollection [as 别名]
# 或者: from matplotlib.collections.LineCollection import set_antialiased [as 别名]
def plot(ax, x, y, time, sim_type):
assert(len(x) == len(y) == len(time))
l = len(time)
if use_hf_coloration:
time_to_grayscale = 0.8 / 23.6 # for HF coloring
else:
time_to_grayscale = 0.8 / time[l-1]
colors = []
for i in range(l-1):
if use_hf_coloration:
color = get_hf_color(time[i]) # time[] is really HF
else:
g = 0.8 - (time[i] * time_to_grayscale)**2.0
if sim_type == 'driven':
color = (g, 1.0, g, 0.8)
else:
color = (g, g, 1.0, 1.0)
colors.append(color)
points = zip(x,y)
segments = zip(points[:-1], points[1:])
lc = LineCollection(segments, colors=colors)
lc.set_alpha(1.0)
lc.set_linewidth(1.0)
lc.set_antialiased(True)
ax.add_collection(lc)
if use_hf_coloration:
end_points.append((x[l-1], y[l-1], get_hf_color(time[l-1])))
else:
end_points.append((x[l-1], y[l-1], COLOR[sim_type]))示例2: plotter
# 需要导入模块: from matplotlib.collections import LineCollection [as 别名]
# 或者: from matplotlib.collections.LineCollection import set_antialiased [as 别名]
def plotter(choice, numNeurons, numTimeSteps, maxNeurons, maxTimeSteps, reverse, numInputNeurons, colorNeurons, redStart, redEnd, greenStart, greenEnd, blueStart, blueEnd, eatNeuron, mateNeuron, fightNeuron, moveNeuron, yawNeuron, label, behaviorLabels, inputLabels):
rhythm_file = open_file(choice, "r")
line = next_line(rhythm_file)
line = next_line(rhythm_file)
figwidth = 12.0
figheight = 8.0
fig = pylab.figure(figsize=(figwidth,figheight))
ax = fig.add_subplot(111)
ax.set_xlim(0.5, maxTimeSteps+0.5)
ax.set_ylim(maxNeurons-0.5, -0.5)
pylab.title(label)
pylab.ylabel('Neuron Index')
pylab.xlabel('Time Step')
linewidth = 0.715 * fig.get_figwidth() * fig.get_dpi() / maxTimeSteps
for time in range(numTimeSteps):
x = []
y = []
colors = []
for neuron in range(numNeurons):
activ = line.split()
x.append(time+1)
y.append(neuron-0.5)
activation = float(activ[1])
if reverse:
activation = 1.0 - activation
if colorNeurons:
if neuron in range(redStart, redEnd+1):
colors.append((activation, activation*ALT_COLOR_MAX, activation*ALT_COLOR_MAX, 1.0))
elif neuron in range(greenStart, greenEnd+1):
colors.append((activation*ALT_COLOR_MAX, activation, activation*ALT_COLOR_MAX, 1.0))
elif neuron in range(blueStart, blueEnd+1):
colors.append((activation*ALT_COLOR_MAX, activation*ALT_COLOR_MAX, activation, 1.0))
elif neuron == eatNeuron:
colors.append((activation*ALT_COLOR_MAX, activation, activation*ALT_COLOR_MAX, 1.0))
elif neuron == mateNeuron:
colors.append((activation*ALT_COLOR_MAX, activation*ALT_COLOR_MAX, activation, 1.0))
elif neuron == fightNeuron:
colors.append((activation, activation*ALT_COLOR_MAX, activation*ALT_COLOR_MAX, 1.0))
elif neuron == yawNeuron:
colors.append((activation, activation, activation*ALT_COLOR_MAX, 1.0))
else:
colors.append((activation, activation, activation, 1.0))
else:
colors.append((activation, activation, activation, 1.0))
line = next_line(rhythm_file)
x.append(time+1)
y.append(neuron+0.5)
colors.append((activation, activation, activation, 1.0))
points = zip(x, y)
segments = zip(points[:-1], points[1:])
lc = LineCollection(segments, colors=colors)
lc.set_alpha(1.0)
lc.set_linewidth(linewidth)
lc.set_antialiased(False)
ax.add_collection(lc)
rhythm_file.close()
if behaviorLabels:
matplotlib.pyplot.text(maxTimeSteps+1.5, eatNeuron, "Eat", weight="ultralight", size="small", va="center")
matplotlib.pyplot.text(maxTimeSteps+1.5, mateNeuron, "Mate", weight="ultralight", size="small", va="center")
matplotlib.pyplot.text(maxTimeSteps+1.5, fightNeuron, "Fight", weight="ultralight", size="small", va="center")
matplotlib.pyplot.text(maxTimeSteps+1.5, moveNeuron, "Move", weight="ultralight", size="small", va="center")
matplotlib.pyplot.text(maxTimeSteps+1.5, yawNeuron, "Turn", weight="ultralight", size="small", va="center")
matplotlib.pyplot.text(maxTimeSteps+1.5, yawNeuron+1, "Light", weight="ultralight", size="small", va="center")
matplotlib.pyplot.text(maxTimeSteps+1.5, yawNeuron+2, "Focus", weight="ultralight", size="small", va="center")
if inputLabels:
matplotlib.pyplot.text(maxTimeSteps+1.5, 0, "Random", weight="ultralight", size="small", va="center")
matplotlib.pyplot.text(maxTimeSteps+1.5, 1, "Health", weight="ultralight", size="small", va="center")
for neuron in range(redStart, redEnd+1):
matplotlib.pyplot.text(maxTimeSteps+1.5, neuron, "R", weight="ultralight", size="small", va="center")
for neuron in range(greenStart, greenEnd+1):
matplotlib.pyplot.text(maxTimeSteps+1.5, neuron, "G", weight="ultralight", size="small", va="center")
for neuron in range(blueStart, blueEnd+1):
matplotlib.pyplot.text(maxTimeSteps+1.5, neuron, "B", weight="ultralight", size="small", va="center")