Streamline Plots in Plotly using Python

A Plotly is a Python library that is used to design graphs, especially interactive graphs. It can plot various graphs and charts like histogram, barplot, boxplot, spreadplot, and many more. It is mainly used in data analysis as well as financial analysis. plotly is an interactive visualization library.

Streamline Plots in Plotly

In plotly, streamline plots are based on the representation on a 2-D vector field which is explained as velocity fields, which are consist of closed curves that are tangent to the velocity field. Streamlining is the fastest technique and more efficient for getting the data. Velocity values are interpolated when determining the streamlines. Streamlines are initialized on the boundary of the x-y domain.

Syntax: create_streamline(x, y, u, v, density=1, angle=0.3490658503988659, arrow_scale=0.09)

Parameters:

x: 1 dimensional, evenly spaced list or array



y: 1 dimensional, evenly spaced list or array

u: 2 dimensional array

v: 2 dimensional array

density: controls the density of streamlines in plot. This is multiplied by 30 to scale similiarly to other available streamline functions such as matplotlib. Default = 1

angle: angle of arrowhead. Default = pi/9

arrow_scale: value to scale length of arrowhead Default = .09

Example:

Python3



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import plotly.figure_factory as ff
import numpy as np
  
x = np.linspace(-1, 1, 10)
y = np.linspace(-1, 1, 10)
Y, X = np.meshgrid(x, y)
u = 1 - X**2 + Y
v = -1 + X - Y**2
  
# Create streamline figure
fig = ff.create_streamline(x, y, u, v, arrow_scale=.1)
fig.show()

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Output:

Plotting the Source Point

The source point can be plot using the scatterplot() method of the graph_objects class. In this, the streamline plot and the position of the marker in the scatterplot are tweaked in such a way that it seems that all the stream is originating from a particular source.

Example:

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import plotly.figure_factory as ff
import plotly.graph_objects as go
import numpy as np
  
x = np.linspace(-1, 2, 50)
y = np.linspace(-1, 1, 50)
Y, X = np.meshgrid(x, y)
u = np.cos(X)*Y
v = np.cos(y)*X
  
# Source for x and y coordinate
# of scatter plot
X, Y = 0, 0
  
# Create streamline figure
fig = ff.create_streamline(x, y, u, v, arrow_scale=.1)
  
fig.add_trace(go.Scatter(x=[X], y=[Y],
                          mode='markers',
                          marker_size=15,
                        ))
  
fig.show()

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Output:


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