Plotly 3D表面流式传输

Question

我想用Plotly的流式API生成3D表面，但我在实际的Python代码中没有收到任何错误，但是我在Plotly上收到了“糟糕！发生错误时载入此图的数据”。这里是我的代码：

import plotly.plotly as py 
import plotly.tools as tls 
import plotly.graph_objs as go 
from random import uniform 
import pandas as pd 
import time 

tls.set_credentials_file(username='', api_key='') 

stream_id = tls.get_credentials_file()['stream_ids'] 
token = stream_id[-1] 

stream_id = dict(token=token) 

z = [] 

surface = go.Surface(z=z, stream=stream_id) 
data = [surface] 
layout = go.Layout(
    title='Test', 
    autosize=False, 
    width=500, 
    height=500, 
    margin=dict(
     l=65, 
     r=50, 
     b=65, 
     t=90 
    ) 
) 
fig = go.Figure(data=data, layout=layout) 
plot_url = py.iplot(fig, filename='elevations-3d-surface', auto_open=True) 

s = py.Stream(stream_id=token) 
s.open() 

matrices = [] 
for p in range(5): 
    matrix = [] 
    for x in range(25): 
     row = [] 
     for y in range(25): 
      row.append(uniform(25, 100)) 
     matrix.append(row) 
    test = pd.DataFrame(matrix) 
    print(test) 
    matrices.append(matrix) 
print(pd.DataFrame(matrices[1])) 

i = 0 
while True: 
    step = 3 
    z = matrices[i] 
    s.write(go.Surface(z=z)) 
    time.sleep(step) 
    i += 1 
    if i == len(matrices): 
     i = 0 
    print(i) 
    # print(pd.DataFrame(z)) 
s.close() 

Answer 1

得到它的工作，这是我的最终代码：

import plotly.plotly as py 
import plotly.tools as tls 
import plotly.graph_objs as go 
import scipy.ndimage as ndimage 
from random import uniform 
import pandas as pd 
import numpy as np 
import time 

tls.set_credentials_file(username='', api_key='') 

stream_id = tls.get_credentials_file()['stream_ids'] 
token = stream_id[-1] 

stream_id = dict(token=token) 

z_init = np.zeros(100).reshape((10, 10)) 
z = z_init 

surface = go.Surface(z=z, stream=stream_id) 
data = [surface] 
layout = go.Layout(
    title='Test', 
    autosize=False, 
    width=500, 
    height=500, 
    margin=dict(
     l=65, 
     r=50, 
     b=65, 
     t=90 
    ) 
) 
fig = go.Figure(data=data, layout=layout) 
plot_url = py.iplot(fig, filename='', auto_open=True) 

s = py.Stream(stream_id=token) 
s.open() 

arr_width = 25 
arr_length = 25 

matrices = [] 
for p in range(100): 
    matrix = [] 
    for x in range(arr_width): 
     row = [] 
     for y in range(arr_length): 
      row.append(uniform(-1, 1)) 
     matrix.append(row) 
    matrices.append(matrix) 

################################################################## 

# given 2 arrays arr1, arr2, number of steps between arrays, and order of interpolation 
# numpoints = 10 
# order = 2 
# arr1 = matrices[1] 
# arr2 = matrices[2] 


def interp(arr1, arr2, numpoints, order): 

    # rejoin arr1, arr2 into a single array of shape (2, 10, 10) 
    arr = np.r_['0, 3', arr1, arr2] 

    # define the grid coordinates where you want to interpolate 
    X, Y = np.meshgrid(np.arange(arr_width), np.arange(arr_length)) 

    k = 0 
    interp_arr_vec = [] 
    while k <= 1: 
     coordinates = np.ones((arr_width, arr_length))*k, X, Y 
     # given arr interpolate at coordinates 
     interp_arr = ndimage.map_coordinates(arr, coordinates, order=order).T 
     interp_arr_vec.append(interp_arr) 

     step = 1/numpoints 
     k += step 

    return interp_arr_vec 

################################################################## 

sleep_time = .1 

i = 0 
while True: 

    between_test = interp(matrices[i], matrices[i+1], 200, 3) 

    r = 0 
    for r in range(len(between_test)): 
     s.write(go.Surface(z=between_test[r])) 
     time.sleep(sleep_time) 

    i += 1 
    print('i = ', i) 
    time.sleep(3) 

    if i == len(matrices): 
     i = 0 

s.close()