-
Notifications
You must be signed in to change notification settings - Fork 1
/
vol_plot.py
119 lines (112 loc) · 3.84 KB
/
vol_plot.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
#!/usr/bin/env python
# coding: utf-8
# In[ ]:
def vol_plot(x):
import os #TO control directories
import nibabel as nib # read and save medical images
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import plotly
import plotly.express as px
from ipywidgets import interact, interactive, fixed, interact_manual
import ipywidgets as widgets
from skimage import io #用于读取保存或显示图片或者视频
import timeit #compute time, useage: timeit.timeit()
import math
import time
import warnings
import numpy as np
import nipype.interfaces.fsl as fsl #topup
from nipype.interfaces.fsl import TOPUP
from nipype.interfaces.fsl import ApplyTOPUP
from nipype.interfaces.fsl import Eddy
from nipype.testing import anatfile
from dipy.denoise.localpca import mppca #denoising
from dipy.io import read_bvals_bvecs
from dipy.core.gradients import gradient_table
from dipy.reconst.dti import TensorModel
from dipy.reconst.dti import fractional_anisotropy
from dipy.reconst.dti import color_fa
import dipy.reconst.dki as dki
"to create 3D MRI figure with slider"
vol = x
colormax = vol.max()#获取最大array中的最大值,最后代表cmax
volume = vol.T
len(volume)
r, c = volume[math.floor(len(volume)/2)].shape
# Define frames
import plotly.graph_objects as go
nb_frames = len(volume)-1
fig = go.Figure(frames=[go.Frame(
data=go.Surface(
z=(len(volume)-1 - k ) * np.ones((r, c)),
surfacecolor=volume[len(volume)-1 - k],
cmin=0, cmax=colormax
),
name=str(k) # name the frame for the animation to behave properly
)
for k in range(nb_frames)])
# Add data to be displayed before animation starts
fig.add_trace(go.Surface(
z=(len(volume)-1) * np.ones((r, c)),
surfacecolor=volume[len(volume)-1],#np.flipud(volume[30]),
colorscale='gray',
cmin=0, cmax=colormax,
colorbar=dict(thickness=20, ticklen=4)
))
def frame_args(duration):
return {
"frame": {"duration": 500},# Duration can be used to change animate speed
"mode": "immediate",
"fromcurrent": True,
"transition": {"duration": 500, "easing": "linear"},
}
sliders = [
{
"pad": {"b": 10, "t": 60},
"len": 0.9,
"x": 0.1,
"y": 0,
"steps": [
{
"args": [[f.name], frame_args(0)],
"label": str(k),
"method": "animate",
}
for k, f in enumerate(fig.frames)
],
}
]
# Layout
fig.update_layout(
title='Slices in volumetric data',
width=600,
height=600,
scene=dict(
zaxis=dict(range=[-1, len(volume)-1], autorange=False),
aspectratio=dict(x=1, y=1, z=1),
),
updatemenus = [
{
"buttons": [
{
"args": [None, frame_args(50)],
"label": "▶", # play symbol
"method": "animate",
},
{
"args": [[None], frame_args(0)],
"label": "◼", # pause symbol
"method": "animate",
},
],
"direction": "left",
"pad": {"r": 10, "t": 70},
"type": "buttons",
"x": 0.1,
"y": 0,
}
],
sliders=sliders
)
fig.show()