如题，我现在安装的是0.7.32版taichi引擎，运行一年前大佬们写的代码时候会报错。一般来说把var改成field可以解决问题，但是vector就不知道怎么改了，会提示AttributeError: 'MatrixField' object has no attribute 'entries'。请问现在应该是用什么类型的变量
你好，可以贴一下出现错误的部分代码吗？
In general, the ti.Vector in old versions can be replaced by ti.Vector.field.
It will be easier to debug if you can post the codes here as @Richard mentioned. 
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比如说201课程第4讲的示例代码：
import taichi as ti
import numpy as np
import math
ti.init(arch=ti.gpu)
eps = 0.01
dt = 0.1
n_vortex = 4
n_tracer = 200000
pos = ti.Vector(2, ti.f32, shape=n_vortex)
new_pos = ti.Vector(2, ti.f32, shape=n_vortex)
vort = ti.var(ti.f32, shape=n_vortex)
tracer = ti.Vector(2, ti.f32, shape=n_tracer)
@ti.func
def compute_u_single(p, i):
r2 = (p - pos[i]).norm()**2
uv = ti.Vector([pos[i].y - p.y, p.x - pos[i].x])
return vort[i] * uv / (r2 * math.pi) * 0.5 * (1.0 - ti.exp(-r2 / eps**2))
@ti.func
def compute_u_full(p):
u = ti.Vector([0.0, 0.0])
for i in range(n_vortex):
u += compute_u_single(p, i)
return u
@ti.kernel
def integrate_vortex():
for i in range(n_vortex):
v = ti.Vector([0.0, 0.0])
for j in range(n_vortex):
if i != j:
v += compute_u_single(pos[i], j)
new_pos[i] = pos[i] + dt * v
for i in range(n_vortex):
pos[i] = new_pos[i]
@ti.kernel
def advect():
for i in range(n_tracer):
# Ralston's third-order method
p = tracer[i]
v1 = compute_u_full(p)
v2 = compute_u_full(p + v1 * dt * 0.5)
v3 = compute_u_full(p + v2 * dt * 0.75)
tracer[i] += (2 / 9 * v1 + 1 / 3 * v2 + 4 / 9 * v3) * dt
pos[0] = [0, 1]
pos[1] = [0, -1]
pos[2] = [0, 0.3]
pos[3] = [0, -0.3]
vort[0] = 1
vort[1] = -1
vort[2] = 1
vort[3] = -1
@ti.kernel
def init_tracers():
for i in range(n_tracer):
tracer[i] = [ti.random() - 0.5, ti.random() * 3 - 1.5]
init_tracers()
gui = ti.GUI("Vortex", (1024, 512), background_color=0xFFFFFF)
for T in range(1000):
for i in range(4): # substeps
advect()
integrate_vortex()
gui.circles(
tracer.to_numpy() * np.array([[0.05, 0.1]]) + np.array([[0.0, 0.5]]),
radius=0.5,
color=0x0)
gui.show()
这个在运行时会有这样的报错：
请问该怎么解决呢
如mzhang所说，将ti.Vector替换为ti.Vector.field即可，如下
import taichi as ti
import numpy as np
import math
ti.init(arch=ti.gpu)
eps = 0.01
dt = 0.1
n_vortex = 4
n_tracer = 200000
pos = ti.Vector.field(2, ti.f32, shape=n_vortex)
new_pos = ti.Vector.field(2, ti.f32, shape=n_vortex)
vort = ti.field(ti.f32, shape=n_vortex)
tracer = ti.Vector.field(2, ti.f32, shape=n_tracer)
@ti.func
def compute_u_single(p, i):
r2 = (p - pos[i]).norm()**2
uv = ti.Vector([pos[i].y - p.y, p.x - pos[i].x])
return vort[i] * uv / (r2 * math.pi) * 0.5 * (1.0 - ti.exp(-r2 / eps**2))
@ti.func
def compute_u_full(p):
u = ti.Vector([0.0, 0.0])
for i in range(n_vortex):
u += compute_u_single(p, i)
return u
@ti.kernel
def integrate_vortex():
for i in range(n_vortex):
v = ti.Vector([0.0, 0.0])
for j in range(n_vortex):
if i != j:
v += compute_u_single(pos[i], j)
new_pos[i] = pos[i] + dt * v
for i in range(n_vortex):
pos[i] = new_pos[i]
@ti.kernel
def advect():
for i in range(n_tracer):
# Ralston's third-order method
p = tracer[i]
v1 = compute_u_full(p)
v2 = compute_u_full(p + v1 * dt * 0.5)
v3 = compute_u_full(p + v2 * dt * 0.75)
tracer[i] += (2 / 9 * v1 + 1 / 3 * v2 + 4 / 9 * v3) * dt
pos[0] = [0, 1]
pos[1] = [0, -1]
pos[2] = [0, 0.3]
pos[3] = [0, -0.3]
vort[0] = 1
vort[1] = -1
vort[2] = 1
vort[3] = -1
@ti.kernel
def init_tracers():
for i in range(n_tracer):
tracer[i] = [ti.random() - 0.5, ti.random() * 3 - 1.5]
init_tracers()
gui = ti.GUI("Vortex", (1024, 512), background_color=0xFFFFFF)
for T in range(1000):
for i in range(4): # substeps
advect()
integrate_vortex()
gui.circles(
tracer.to_numpy() * np.array([[0.05, 0.1]]) + np.array([[0.0, 0.5]]),
radius=0.5,
color=0x0)
gui.show()
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解决了！感谢