from oil.utils.utils import export
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.animation as animation
import numpy as np

@export
class Animation(object):
    def __init__(self, qt,body=None):
        """ [qt (T,n,d)"""
        self.qt = qt.data.numpy()
        T,n,d = qt.shape
        assert d in (2,3), "too many dimensions for animation"
        self.fig = plt.figure()
        self.ax = self.fig.add_axes([0, 0, 1, 1],projection='3d') if d==3 else self.fig.add_axes([0, 0, 1, 1])

        #self.ax.axis('equal')
        xyzmin = self.qt.min(0).min(0)#.min(dim=0)[0].min(dim=0)[0]
        xyzmax = self.qt.max(0).max(0)#.max(dim=0)[0].max(dim=0)[0]
        delta = xyzmax-xyzmin
        lower = xyzmin-.1*delta; upper = xyzmax+.1*delta
        self.ax.set_xlim((min(lower),max(upper)))
        self.ax.set_ylim((min(lower),max(upper)))
        if d==3: self.ax.set_zlim((min(lower),max(upper)))
        if d!=3: self.ax.set_aspect("equal")
        #elf.ax.auto_scale_xyz()
        empty = d*[[]]
        self.colors = np.random.choice([f"C{i}" for i in range(10)],size=n,replace=False)
        self.objects = {
            'pts':sum([self.ax.plot(*empty, "o", ms=6,color=self.colors[i]) for i in range(n)], []),
            'traj_lines':sum([self.ax.plot(*empty, "-",color=self.colors[i]) for i in range(n)], []),
        }

    def init(self):
        empty = 2*[[]]
        for obj in self.objects.values():
            for elem in obj:
                elem.set_data(*empty)
                if self.qt.shape[-1]==3: elem.set_3d_properties([])
        return sum(self.objects.values(),[])

    def update(self, i=0):
        T,n,d = self.qt.shape
        trail_len = 150
        for j in range(n):
            # trails
            xyz = self.qt[max(i - trail_len,0): i + 1,j,:]
            #chunks = xyz.shape[0]//10
            #xyz_chunks = torch.chunk(xyz,chunks)
            #for i,xyz in enumerate(xyz_chunks):
            self.objects['traj_lines'][j].set_data(*xyz[...,:2].T)
            if d==3: self.objects['traj_lines'][j].set_3d_properties(xyz[...,2].T)
            self.objects['pts'][j].set_data(*xyz[-1:,...,:2].T)
            if d==3: self.objects['pts'][j].set_3d_properties(xyz[-1:,...,2].T)
        #self.fig.canvas.draw()
        return sum(self.objects.values(),[])

    def animate(self):
        return self._animate().to_html5_video()

    def _animate(self):
        return animation.FuncAnimation(self.fig,self.update,frames=self.qt.shape[0],
                    interval=33,init_func=self.init,blit=True,)

from oil.utils.utils import export
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.animation as animation
import numpy as np

@export
class Animation(object):
    def __init__(self, qt,body=None):
        """ [qt (T,n,d)"""
        self.qt = qt.data.numpy()
        T,n,d = qt.shape
        assert d in (2,3), "too many dimensions for animation"
        self.fig = plt.figure()
        self.ax = self.fig.add_axes([0, 0, 1, 1],projection='3d') if d==3 else self.fig.add_axes([0, 0, 1, 1])

        #self.ax.axis('equal')
        xyzmin = self.qt.min(0).min(0)#.min(dim=0)[0].min(dim=0)[0]
        xyzmax = self.qt.max(0).max(0)#.max(dim=0)[0].max(dim=0)[0]
        delta = xyzmax-xyzmin
        lower = xyzmin-.1*delta; upper = xyzmax+.1*delta
        self.ax.set_xlim((min(lower),max(upper)))
        self.ax.set_ylim((min(lower),max(upper)))
        if d==3: self.ax.set_zlim((min(lower),max(upper)))
        if d!=3: self.ax.set_aspect("equal")
        #elf.ax.auto_scale_xyz()
        empty = d*[[]]
        self.colors = np.random.choice([f"C{i}" for i in range(10)],size=n,replace=False)
        self.objects = {
            'pts':sum([self.ax.plot(*empty, "o", ms=6,color=self.colors[i]) for i in range(n)], []),
            'traj_lines':sum([self.ax.plot(*empty, "-",color=self.colors[i]) for i in range(n)], []),
        }

    def init(self):
        empty = 2*[[]]
        for obj in self.objects.values():
            for elem in obj:
                elem.set_data(*empty)
                if self.qt.shape[-1]==3: elem.set_3d_properties([])
        return sum(self.objects.values(),[])

    def update(self, i=0):
        T,n,d = self.qt.shape
        trail_len = 150
        for j in range(n):
            # trails
            xyz = self.qt[max(i - trail_len,0): i + 1,j,:]
            #chunks = xyz.shape[0]//10
            #xyz_chunks = torch.chunk(xyz,chunks)
            #for i,xyz in enumerate(xyz_chunks):
            self.objects['traj_lines'][j].set_data(*xyz[...,:2].T)
            if d==3: self.objects['traj_lines'][j].set_3d_properties(xyz[...,2].T)
            self.objects['pts'][j].set_data(*xyz[-1:,...,:2].T)
            if d==3: self.objects['pts'][j].set_3d_properties(xyz[-1:,...,2].T)
        #self.fig.canvas.draw()
        return sum(self.objects.values(),[])

    def animate(self):
        return self._animate().to_html5_video()

    def _animate(self):
        return animation.FuncAnimation(self.fig,self.update,frames=self.qt.shape[0],
                    interval=33,init_func=self.init,blit=True,)

[qt (T,n,d) #self.ax.axis('equal') #.min(dim=0)[0].min(dim=0)[0] #.max(dim=0)[0].max(dim=0)[0] #elf.ax.auto_scale_xyz() # trails #chunks = xyz.shape[0]//10 #xyz_chunks = torch.chunk(xyz,chunks) #for i,xyz in enumerate(xyz_chunks): #self.fig.canvas.draw()