def output(self, anim, plt, dataset, output):
"""
Generic output functions
"""
logger.info("Writing output...")
filename = "covid_{}.{}".format(dataset.lower(), output)
if output == "mp4":
writer = FFMpegFileWriter(fps=10, bitrate=1800)
anim.save(filename, writer=writer)
elif output == "gif":
writer = ImageMagickFileWriter()
anim.save(filename, writer=writer)
else:
plt.show()
def test_gif():
"""
GIF动态图：matplotlib只能对静态图进行绘制显示；动态图是由一帧一帧的画面组合的，由ImageMagick完成
动图绘制路线：初始化图像-> FuncAnimation() -> 不断改变原始曲线值
"""
from matplotlib.animation import FuncAnimation
from IPython.display import Image
from matplotlib.animation import ImageMagickFileWriter
writer = ImageMagickFileWriter()
fig, ax = plt.subplots()
xdata, ydata = [], []
ln, = ax.plot([], [], 'r-', animated=False)
# 生成数据(用于传入update函数)
def data_gen():
pass
# 初始化图像
def init():
ax.set_xlim(0, 2 * np.pi) # 设置x轴范围
ax.set_ylim(-1.1, 1.1)
return ln,
# 将更新后的数据添加到图像中
def update(data):
xdata.append(data)
ydata.append(np.sin(data))
ln.set_data(xdata, ydata) # 重新设置曲线的值
return ln,
# 核心方法入口
# 参数说明:
ani = FuncAnimation(
fig, # 画布
update, # 我们每个时刻要更新图形对象的函数
frames=np.linspace(0, 2 * np.pi,
50), # 相当于时刻t，要模拟多少帧图画，不同时刻的t相当于animat的参数
interval=50, # 刷新频率，毫秒
init_func=init, # 初始化函数，其返回值就是每次都要更新的对象
blit=True) # blit是一个非常重要的关键字，它告诉动画只重绘修改的部分，结合上面保存的时间,true会使动画显示得会非常非常快
# 需要安装ImageMagick
# ani.save('ming.gif', writer='imagemagick')
plt.show()
def init_writer(map_size):
metadata = dict(title='Natural selection', artist='Matplotlib', comment='')
writer = ImageMagickFileWriter(fps=7, metadata=metadata)
fig = plt.figure(figsize=(8, 8))
ax = fig.gca()
ax.set_xticks(np.arange(0, map_size[0] + 1, 1))
ax.set_yticks(np.arange(0, map_size[1] + 1, 1))
plt.grid()
plt.xlim(0, map_size[0])
plt.ylim(0, map_size[1])
graph_c, = plt.plot([], [],
color='firebrick',
marker="o",
linestyle="",
markersize=20)
graph_h, = plt.plot([], [],
color='dodgerblue',
marker="o",
linestyle="",
markersize=20)
graph_p, = plt.plot([], [],
color='green',
marker="D",
linestyle="",
markersize=10)
#a.set_color('red')
#a.set_marker
#a.set_label
return writer, fig, graph_h, graph_p, graph_c
right = 0.98 # the right side
hspace = 0.20 # height reserved for white space
wspace = 0.05 # width reserved for blank space
plt.subplots_adjust(left=left,
bottom=bottom,
right=right,
top=top,
wspace=wspace,
hspace=hspace)
tit = plt.title('1850')
#showdate = ax.text(0.5, 0.95, '1850', fontweight = 'bold', color = cset[0], bbox=dict(facecolor='lightsteelblue', edgecolor='black', boxstyle='round,pad=1'))
save = True
if save:
metadata = dict(title='Temperature anomaly (SPHINX lcb0 experiment)',
artist='Federico Fabiano')
writer = ImageMagickFileWriter(
fps=10, metadata=metadata) #, frame_size = (1200, 900))
with writer.saving(fig, cart + "Temp_anomaly_animation_flat.gif", 150):
for i, (year, col) in enumerate(zip(anni, cset)):
print(year)
animate(i)
writer.grab_frame()
else:
line_ani = animation.FuncAnimation(fig,
animate,
len(anni),
interval=100,
blit=False)
def animate(self,
outputType="screen",
color="random",
speed=10,
outDir="out",
type="line"):
if not os.path.exists(outDir): os.mkdir(outDir)
fname = os.path.join(
outDir, "knightPath-{}-{}".format(self.kn.shape[0],
self.kn.shape[1]))
knightAnimation = FuncAnimation(self.fig,
self._genLine,
fargs=(speed, color, type),
repeat=False,
frames=range(
-speed,
len(self.kn.history),
speed,
),
blit=False,
interval=10,
cache_frame_data=False)
if outputType == "screen":
plt.show()
elif outputType == "avi":
knightAnimation.save(
fname + ".avi",
writer=FFMpegFileWriter(fps=1,
bitrate=100000,
extra_args=['-vcodec', 'libx264']),
)
print("video file written to", fname + ".avi")
elif outputType == "mp4":
knightAnimation.save(
fname + ".mp4",
writer=FFMpegFileWriter(fps=1,
bitrate=100000,
extra_args=['-vcodec', 'libx264']),
)
print("MP4 video file written to", fname + ".mp4")
elif outputType == "gif":
knightPathAnim = FuncAnimation(self.fig,
self._genAllLines,
repeat=False,
frames=range(1),
blit=False,
interval=10,
cache_frame_data=False)
knightPathAnim.save(fname + '.gif',
writer=ImageMagickFileWriter(fps=1))
print("Image written to", fname + ".gif")
elif outputType == "animgif":
knightAnimation.save(fname + '.anim.gif',
writer=ImageMagickFileWriter(fps=1))
print("Animated gif written to", fname + ".anim.gif")
elif outputType == "html":
open(fname + ".html", "w").write(
self._genHtmlFrame(knightAnimation.to_html5_video(50.0)))
print("HTML file written to", fname + ".html")
else:
print("Unknown outputType '" + outputType + "'")
return
ax.set_zlim(0, 1)
ax.set_xlabel('Nodes Layer 1')
ax.set_ylabel('Nodes Layer 2')
ax.set_zlabel('Mean CV Score')
plt.savefig(str(i) + ".png")
plt.show()
###############################################################################
dir_name = os.path.abspath(os.path.dirname(__file__))
data_file = 'processed_data.csv'
file_path = os.path.join(dir_name, data_file)
data = pandas.read_csv(file_path)
encoder = preprocessing.LabelEncoder()
encoder.fit(data.iloc[:, -1])
data.iloc[:, -1] = encoder.transform(data.iloc[:, -1])
#Prep the features and labels
features = np.array(data.iloc[:, 1:78])
labels = np.array(data.iloc[:, -1])
min_max_scaler = preprocessing.MinMaxScaler()
features = min_max_scaler.fit_transform(features)
###############################################################################
anim = FuncAnimation(fig, update, frames=range(15), repeat=False)
if len(sys.argv) > 1 and sys.argv[1] == 'save':
anim.save('surf.gif', dpi=80, writer=ImageMagickFileWriter(fps=1))
else:
plt.show()
# _____________
# _____________
r = RandomApproachAnimation(shubert, Settings, 10**5, 10**3)
it = r.__iter__()
def animate(i):
try:
return it.__next__()
except:
return
# ___________
# SHOWING ANIMATION
# ___________
if (__name__ != '__main__'):
ani = FuncAnimation(r.fig, animate, repeat=False, interval=2)
plt.show()
# ___________
# SAVING TO GIF
# ___________
else:
ani = FuncAnimation(r.fig, animate, repeat=False, interval=10, frames=5)
ani.save('line.gif', writer=ImageMagickFileWriter())
def generate_animation(file1, file2):
df, file_x, file_y = animate_data(file1, file2)
years = df['Year'].unique().tolist()
fig, ax = plt.subplots(figsize=(8, 8))
ax.set_xlim(df[file_x].min() - .3, df[file_x].max() + .3)
ax.set_ylim(df[file_y].min() - 2, df[file_y].max() + 2)
# set the regions' colors
colors = {
'Latin America & Caribbean': '#2CA02C',
'South Asia': '#8C564B',
'Sub-Saharan Africa': '#E377C2',
'Europe & Central Asia': '#FF7F0E',
'Middle East & North Africa': '#D62728',
'East Asia & Pacific': '#1F77B4',
'North America': '#9467BD'
}
# create one scatterplot per region
# I need to do like this to have all the regions
# showing up in the legend
scats = []
groups = df.groupby('Region')
for name, grp in groups:
scat = ax.scatter([], [],
marker='o',
color=colors[name],
label=name,
edgecolor='silver',
alpha=.6)
scats.append(scat)
# add the year in the middle of the scatter plot
# for now, the text is empty (''). Il will be filled
# in each frame
year_label = ax.text(4.5,
50,
'',
va='baseline',
ha='right',
alpha=.3,
size=12,
fontdict={'weight': 'bold'})
# decorate the visualization
ax.spines['bottom'].set_color('silver')
ax.spines['top'].set_color('silver')
ax.spines['right'].set_color('silver')
ax.spines['left'].set_color('silver')
ax.tick_params(labelcolor='silver', color='silver')
ax.set_xlabel(file_x, color='silver')
ax.set_ylabel(file_y, color='silver')
ax.legend(loc=1, fontsize=7)
# set the initial state
def init():
for scat in scats:
scat.set_offsets([])
return scats,
# function that will update the figure with new data
def update(year):
# I need to update all scatterplots one by one
# and return a list of updated plots
for scat, (name, data) in zip(scats, groups):
# get the data for the current year
sample = data[data['Year'] == year]
# set the x and y values
scat.set_offsets(sample[[file_x, file_y]])
# update the size of the markers with the population
# of the current year
scat.set_sizes(np.sqrt(sample['Population'] / 10000) * 5)
year_label.set_text(year)
return scats,
# generate the animation
ani = animation.FuncAnimation(fig,
update,
init_func=init,
frames=years,
interval=50,
repeat=False)
writer = ImageMagickFileWriter()
ani.save('predicted_images/analysis.gif', writer=writer)
#animate_data('CO2.csv','gdp.csv')
# plt.show()
plt.close()
def makeMovie(data, ind):
m = int(data[-1, 0])
start = np.searchsorted(data[:, 0], ind)
if ind == m:
end = data.shape[0] - 1
else:
end = np.searchsorted(data[:, 0], ind + 1) - 1
# if data[start,-1]==1: return
data = data[start:end + 1]
# x_e=data[:,3]-data[0,3]
x_e = data[:, 3]
y_e = data[:, 2]
# x_f=data[:,7]-data[0,3]
x_f = data[:, 7]
y_f = data[:, 6]
# x_ft=data[:,11]-data[0,3]
x_ft = data[:, 11]
y_ft = data[:, 10]
# x_rt=data[:,15]-data[0,3]
x_rt = data[:, 15]
y_rt = data[:, 14]
x_rt1 = data[:, 20]
y_rt1 = data[:, 19]
xMin = min(x_e)
xMax = max(x_e)
# x_f_min=min(x_f[x_f!=0])
# if x_f[x_f!=0].shape[0]!=0: xMin=min(xMin, min(x_f[x_f!=0]))
# if x_ft[x_ft!=0].shape[0]!=0: xMin=min(xMin, min(x_ft[x_ft!=0]))
# if x_rt[x_rt!=0].shape[0]!=0: xMin=min(xMin, min(x_rt[x_rt!=0]))
xMin = int(
min(min(min(min(x_e), min(x_f)), min(min(x_ft), min(x_rt))),
min(x_rt1))) - 5
xMax = int(
max(max(max(max(x_e), max(x_f)), max(max(x_ft), max(x_rt))),
max(x_rt1))) + 5
# x_e-=xMin
# x_f-=xMin
# x_ft-=xMin
# x_rt-=xMin
# xMax=int(xMax-xMin+5)
# xMin=-5
# laneLowerBound=(int(max(y_e)/widthLane)+1)*widthLane
laneLowerBound = widthLane
# laneUpperBound=int(min(y_e)/widthLane)*widthLane
laneUpperBound = -widthLane
# if laneLowerBound>=widthLane*7:
# laneUpperBound=widthLane*5
# laneLowerBound=widthLane*7
# for ramp
laneDivision = laneUpperBound + widthLane
print('ub', laneUpperBound, 'lb', laneLowerBound, 'ld', laneDivision)
fig = plt.figure()
plt.axis('scaled')
ax = fig.add_subplot(111)
ax.set_xlim(xMin, xMax)
ax.set_ylim(laneUpperBound - 2, laneLowerBound + 2)
plt.gca().invert_yaxis()
# (x,y) bottom and left corner coordinates
patch_e = patches.Rectangle(
(x_e[0] - lengthCar / 2., y_e[0] - widthCar / 2.),
lengthCar,
widthCar,
fc='r')
patch_f = patches.Rectangle(
(x_f[0] - lengthCar / 2., y_f[0] - widthCar / 2.),
lengthCar,
widthCar,
fc='b')
patch_ft = patches.Rectangle(
(x_ft[0] - lengthCar / 2., y_ft[0] - widthCar / 2.),
lengthCar,
widthCar,
fc='b')
patch_rt = patches.Rectangle(
(x_rt[0] - lengthCar / 2., y_rt[0] - widthCar / 2.),
lengthCar,
widthCar,
fc='b')
patch_rt1 = patches.Rectangle(
(x_rt1[0] - lengthCar / 2., y_rt1[0] - widthCar / 2.),
lengthCar,
widthCar,
fc='b')
def init():
ax.add_patch(patch_e)
ax.plot(np.arange(xMin, xMax, 1),
laneLowerBound * np.ones(xMax - xMin))
ax.plot(np.arange(xMin, xMax, 1),
laneUpperBound * np.ones(xMax - xMin))
ax.plot(np.arange(xMin, xMax, 1),
laneDivision * np.ones(xMax - xMin),
linestyle='--')
return patch_e,
def animate(i):
patch_e.set_xy([x_e[i] - lengthCar / 2., y_e[i] - widthCar / 2.])
if y_f[i] == 0.:
# front obstacle does not exist, -100 to remove it out the animation y limit
patch_f.set_xy(
[x_f[i] - lengthCar / 2., y_f[i] - widthCar / 2. - 100.])
else:
patch_f.set_xy(
[x_f[i] - lengthCar / 2., y_f[i] - widthCar / 2.])
ax.add_patch(patch_f)
if y_ft[i] == 0.:
patch_ft.set_xy(
[x_ft[i] - lengthCar / 2., y_ft[i] - widthCar / 2. - 100.])
else:
patch_ft.set_xy(
[x_ft[i] - lengthCar / 2., y_ft[i] - widthCar / 2.])
ax.add_patch(patch_ft)
if y_rt[i] == 0.:
patch_rt.set_xy(
[x_rt[i] - lengthCar / 2., y_rt[i] - widthCar / 2. - 100.])
else:
patch_rt.set_xy(
[x_rt[i] - lengthCar / 2., y_rt[i] - widthCar / 2.])
ax.add_patch(patch_rt)
if y_rt1[i] == 0.:
patch_rt1.set_xy([
x_rt1[i] - lengthCar / 2., y_rt1[i] - widthCar / 2. - 100.
])
else:
patch_rt1.set_xy(
[x_rt1[i] - lengthCar / 2., y_rt1[i] - widthCar / 2.])
ax.add_patch(patch_rt1)
return patch_e, patch_f, patch_ft, patch_rt, patch_rt1
anim = animation.FuncAnimation(fig,
animate,
init_func=init,
frames=x_e.shape[0],
interval=100,
blit=True)
writer = ImageMagickFileWriter(fps=15, bitrate=3000)
anim.save('lc_id' + str(ind) + '.gif', writer=writer)
def makeMovie(data, ind, dir):
start = np.searchsorted(data[:, 0], ind)
end = np.searchsorted(data[:, 0], ind + 1) - 1
# if data[start,-1]==1: return
data = data[start:end + 1]
x_e = data[:, 3]
y_e = data[:, 2]
x_f = data[:, 7]
y_f = data[:, 6]
x_ft = data[:, 11]
y_ft = data[:, 10]
x_rt = data[:, 15]
y_rt = data[:, 14]
xMin = min(x_e)
xMax = max(x_e)
xMin = int(min(min(min(x_e), min(x_f)), min(min(x_ft), min(x_rt)))) - 5
xMax = int(max(max(max(x_e), max(x_f)), max(max(x_ft), max(x_rt)))) + 5
laneLowerBound = widthLane
laneUpperBound = -widthLane
# for ramp
laneDivision = laneUpperBound + widthLane
fig = plt.figure()
plt.axis('scaled')
ax = fig.add_subplot(111)
ax.set_xlim(xMin, xMax)
ax.set_ylim(laneUpperBound - 2, laneLowerBound + 2)
plt.gca().invert_yaxis()
# (x,y) bottom and left corner coordinates
patch_e = patches.Rectangle(
(x_e[0] - lengthCar / 2., y_e[0] - widthCar / 2.),
lengthCar,
widthCar,
fc='r')
patch_f = patches.Rectangle(
(x_f[0] - lengthCar / 2., y_f[0] - widthCar / 2.),
lengthCar,
widthCar,
fc='b')
patch_ft = patches.Rectangle(
(x_ft[0] - lengthCar / 2., y_ft[0] - widthCar / 2.),
lengthCar,
widthCar,
fc='b')
patch_rt = patches.Rectangle(
(x_rt[0] - lengthCar / 2., y_rt[0] - widthCar / 2.),
lengthCar,
widthCar,
fc='b')
def init():
ax.add_patch(patch_e)
ax.plot(np.arange(xMin, xMax, 1),
laneLowerBound * np.ones(xMax - xMin))
ax.plot(np.arange(xMin, xMax, 1),
laneUpperBound * np.ones(xMax - xMin))
ax.plot(np.arange(xMin, xMax, 1),
laneDivision * np.ones(xMax - xMin),
linestyle='--')
return patch_e,
def animate(i):
patch_e.set_xy([x_e[i] - lengthCar / 2., y_e[i] - widthCar / 2.])
if y_f[i] == 0.:
# front obstacle does not exist, -100 to remove it out the animation y limit
patch_f.set_xy(
[x_f[i] - lengthCar / 2., y_f[i] - widthCar / 2. - 100.])
else:
patch_f.set_xy(
[x_f[i] - lengthCar / 2., y_f[i] - widthCar / 2.])
ax.add_patch(patch_f)
if y_ft[i] == 0.:
patch_ft.set_xy(
[x_ft[i] - lengthCar / 2., y_ft[i] - widthCar / 2. - 100.])
else:
patch_ft.set_xy(
[x_ft[i] - lengthCar / 2., y_ft[i] - widthCar / 2.])
ax.add_patch(patch_ft)
if y_rt[i] == 0.:
patch_rt.set_xy(
[x_rt[i] - lengthCar / 2., y_rt[i] - widthCar / 2. - 100.])
else:
patch_rt.set_xy(
[x_rt[i] - lengthCar / 2., y_rt[i] - widthCar / 2.])
ax.add_patch(patch_rt)
return patch_e, patch_f, patch_ft, patch_rt
anim = animation.FuncAnimation(fig,
animate,
init_func=init,
frames=x_e.shape[0],
interval=100,
blit=True)
writer = ImageMagickFileWriter(fps=15, bitrate=3000)
anim.save(dir + 'lc_id' + str(ind) + '.gif', writer=writer)