I have a pandas dataframe in the above format from which I’m trying to create a complex animation from offline in a VScode Jupyter notebook. I’ve been trying for a couple days now to animate it but can’t quite figure out the exact configuration needed for it to work, and now think I need to raise my hand and ask my help.
Part of my struggle is that it is producing a graphic (see below) but no error message that would hint at where to investigate next. I had this working in a much simpler animation but it has failed to scale appropriately. When I deconstruct the output of the animateDataSource it outputs a list of frames as expected. Any suggestions on how to improve the code would be appreciated. (I am around to answer follow up questions if that’s helpful.)
#imports
import pandas as pd
import numpy as np
import plotly.graph_objects as go
from plotly.offline import init_notebook_mode
init_notebook_mode(connected=False)
source = df
def frameMaker(i):
"""
returns x,y,z dict of currently indexed frame by vector component key
"""
scale = 2
current_dict = dict({
"x": [[source["X"][i], scale * source["X"][i+1]], [source["Y"][i], source["Y"][i]], [source["Z"][i], source["Z"][i]]],
"y": [[source["X"][i], source["X"][i]], [source["Y"][i], scale * source["Y"][i+1]], [source["Z"][i], source["Z"][i]]],
"z": [[source["X"][i], source["X"][i]], [source["Y"][i], source["Y"][i]], [source["Z"][i], scale * source["Z"][i+1]]]
})
return current_dict
def animateDataSource(time_series_source):
"""
Takes lists of x,y,z data and returns a list of plotly frames through the frameMaker function.
"""
list_of_frames = []
for k in range(time_series_source.shape[0]-1):
current_vector_data = frameMaker(k)
list_of_frames.append(
go.Frame(
data=[go.Scatter3d(
x = [time_series_source["X"][k]],
y = [time_series_source["Y"][k]],
z = [time_series_source["Z"][k]],
name = "target",
mode = "markers",
marker=dict(color="red",size=10,opacity=0.5)),
go.Scatter3d(
x=time_series_source["X"],
y=time_series_source["Y"],
z=time_series_source["Z"],
name="path",
mode="lines",
line=dict(color="black", width=1)),
go.Scatter3d(
x=current_vector_data["x"][0],
y=current_vector_data["x"][1],
z=current_vector_data["x"][2],
name = "x",
line=dict(color='blue',width=3)),
go.Scatter3d(
x=current_vector_data["y"][0],
y=current_vector_data["y"][1],
z=current_vector_data["y"][2],
name = "y",
line=dict(color='green',width=3)),
go.Scatter3d(
x=current_vector_data["z"][0],
y=current_vector_data["z"][1],
z=current_vector_data["z"][2],
name = "z",
line=dict(color='red',width=3))
]
)
)
return list_of_frames
vect = frameMaker(0)
plt = go.Figure(
data=[go.Scatter3d(
x=[df["X"].iloc[0]],
y=[df["Y"].iloc[0]],
z=[df["Z"].iloc[0]],
name="target",
mode="markers",
marker=dict(
color="red",
size=10,
opacity=0.5)),
go.Scatter3d(
x=df["X"].values,
y=df["Y"].values,
z=df["Z"].values,
name="path",
mode="lines",
line=dict(
color="black",
width=1)),
go.Scatter3d(
x = vect["x"][0],
y = vect["x"][1],
z = vect["x"][2],
name = "x",
mode = "lines",
line = dict(color='blue', width=3)),
go.Scatter3d(
x = vect["y"][0],
y = vect["y"][1],
z = vect["y"][2],
name = "y",
mode = "lines",
line = dict(color='green', width=3)),
go.Scatter3d(
x=vect["z"][0],
y=vect["z"][1],
z=vect["z"][2],
name = "z",
mode = "lines",
line = dict(color='red', width=3))],
layout =
go.Layout(
title = go.layout.Title(text="Movement"),
scene_aspectmode="cube",
scene = dict(
xaxis = dict(range=[-5,5], nticks=10, autorange=False),
yaxis = dict(range=[-5,5], nticks=10, autorange=False),
zaxis = dict(range=[-5,5], nticks=10, autorange=False)),
updatemenus=[dict(type="buttons",
buttons=[dict(label="Play",
method="animate",
args=[None])])]),
frames = animateDataSource(df)
)
plt.show()
Updated 2019-12-26:
Needs to be refactored a bit but I’ve updated the above with the framemaker def.