def create_streamline(x,
y,
u,
v,
density=1,
angle=math.pi / 9,
arrow_scale=.09,
**kwargs):
"""
Returns data for a streamline plot.
:param (list|ndarray) x: 1 dimensional, evenly spaced list or array
:param (list|ndarray) y: 1 dimensional, evenly spaced list or array
:param (ndarray) u: 2 dimensional array
:param (ndarray) v: 2 dimensional array
:param (float|int) 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
:param (angle in radians) angle: angle of arrowhead. Default = pi/9
:param (float in [0,1]) arrow_scale: value to scale length of arrowhead
Default = .09
:param kwargs: kwargs passed through plotly.graph_objs.Scatter
for more information on valid kwargs call
help(plotly.graph_objs.Scatter)
:rtype (dict): returns a representation of streamline figure.
Example 1: Plot simple streamline and increase arrow size
```
import plotly.plotly as py
from plotly.figure_factory import create_streamline
import numpy as np
import math
# Add data
x = np.linspace(-3, 3, 100)
y = np.linspace(-3, 3, 100)
Y, X = np.meshgrid(x, y)
u = -1 - X**2 + Y
v = 1 + X - Y**2
u = u.T # Transpose
v = v.T # Transpose
# Create streamline
fig = create_streamline(x, y, u, v, arrow_scale=.1)
# Plot
py.plot(fig, filename='streamline')
```
Example 2: from nbviewer.ipython.org/github/barbagroup/AeroPython
```
import plotly.plotly as py
from plotly.figure_factory import create_streamline
import numpy as np
import math
# Add data
N = 50
x_start, x_end = -2.0, 2.0
y_start, y_end = -1.0, 1.0
x = np.linspace(x_start, x_end, N)
y = np.linspace(y_start, y_end, N)
X, Y = np.meshgrid(x, y)
ss = 5.0
x_s, y_s = -1.0, 0.0
# Compute the velocity field on the mesh grid
u_s = ss/(2*np.pi) * (X-x_s)/((X-x_s)**2 + (Y-y_s)**2)
v_s = ss/(2*np.pi) * (Y-y_s)/((X-x_s)**2 + (Y-y_s)**2)
# Create streamline
fig = create_streamline(x, y, u_s, v_s, density=2, name='streamline')
# Add source point
point = Scatter(x=[x_s], y=[y_s], mode='markers',
marker=Marker(size=14), name='source point')
# Plot
fig['data'].append(point)
py.plot(fig, filename='streamline')
```
"""
utils.validate_equal_length(x, y)
utils.validate_equal_length(u, v)
validate_streamline(x, y)
utils.validate_positive_scalars(density=density, arrow_scale=arrow_scale)
streamline_x, streamline_y = _Streamline(x, y, u, v, density, angle,
arrow_scale).sum_streamlines()
arrow_x, arrow_y = _Streamline(x, y, u, v, density, angle,
arrow_scale).get_streamline_arrows()
streamline = graph_objs.Scatter(x=streamline_x + arrow_x,
y=streamline_y + arrow_y,
mode='lines',
**kwargs)
data = [streamline]
layout = graph_objs.Layout(hovermode='closest')
return graph_objs.Figure(data=data, layout=layout)
def create_quiver(x,
y,
u,
v,
scale=0.1,
arrow_scale=0.3,
angle=math.pi / 9,
scaleratio=None,
**kwargs):
"""
Returns data for a quiver plot.
:param (list|ndarray) x: x coordinates of the arrow locations
:param (list|ndarray) y: y coordinates of the arrow locations
:param (list|ndarray) u: x components of the arrow vectors
:param (list|ndarray) v: y components of the arrow vectors
:param (float in [0,1]) scale: scales size of the arrows(ideally to
avoid overlap). Default = .1
:param (float in [0,1]) arrow_scale: value multiplied to length of barb
to get length of arrowhead. Default = .3
:param (angle in radians) angle: angle of arrowhead. Default = pi/9
:param (positive float) scaleratio: the ratio between the scale of the y-axis
and the scale of the x-axis (scale_y / scale_x). Default = None, the
scale ratio is not fixed.
:param kwargs: kwargs passed through plotly.graph_objs.Scatter
for more information on valid kwargs call
help(plotly.graph_objs.Scatter)
:rtype (dict): returns a representation of quiver figure.
Example 1: Trivial Quiver
```
import plotly.plotly as py
from plotly.figure_factory import create_quiver
import math
# 1 Arrow from (0,0) to (1,1)
fig = create_quiver(x=[0], y=[0], u=[1], v=[1], scale=1)
py.plot(fig, filename='quiver')
```
Example 2: Quiver plot using meshgrid
```
import plotly.plotly as py
from plotly.figure_factory import create_quiver
import numpy as np
import math
# Add data
x,y = np.meshgrid(np.arange(0, 2, .2), np.arange(0, 2, .2))
u = np.cos(x)*y
v = np.sin(x)*y
#Create quiver
fig = create_quiver(x, y, u, v)
# Plot
py.plot(fig, filename='quiver')
```
Example 3: Styling the quiver plot
```
import plotly.plotly as py
from plotly.figure_factory import create_quiver
import numpy as np
import math
# Add data
x, y = np.meshgrid(np.arange(-np.pi, math.pi, .5),
np.arange(-math.pi, math.pi, .5))
u = np.cos(x)*y
v = np.sin(x)*y
# Create quiver
fig = create_quiver(x, y, u, v, scale=.2, arrow_scale=.3, angle=math.pi/6,
name='Wind Velocity', line=dict(width=1))
# Add title to layout
fig['layout'].update(title='Quiver Plot')
# Plot
py.plot(fig, filename='quiver')
```
Example 4: Forcing a fix scale ratio to maintain the arrow length
```
import plotly.plotly as py
from plotly.figure_factory import create_quiver
import numpy as np
# Add data
x,y = np.meshgrid(np.arange(0.5, 3.5, .5), np.arange(0.5, 4.5, .5))
u = x
v = y
angle = np.arctan(v / u)
norm = 0.25
u = norm * np.cos(angle)
v = norm * np.sin(angle)
# Create quiver with a fix scale ratio
fig = create_quiver(x, y, u, v, scale = 1, scaleratio = 0.5)
# Plot
py.plot(fig, filename='quiver')
```
"""
utils.validate_equal_length(x, y, u, v)
utils.validate_positive_scalars(arrow_scale=arrow_scale, scale=scale)
if scaleratio is None:
quiver_obj = _Quiver(x, y, u, v, scale, arrow_scale, angle)
else:
quiver_obj = _Quiver(x, y, u, v, scale, arrow_scale, angle, scaleratio)
barb_x, barb_y = quiver_obj.get_barbs()
arrow_x, arrow_y = quiver_obj.get_quiver_arrows()
quiver_plot = graph_objs.Scatter(x=barb_x + arrow_x,
y=barb_y + arrow_y,
mode="lines",
**kwargs)
data = [quiver_plot]
if scaleratio is None:
layout = graph_objs.Layout(hovermode="closest")
else:
layout = graph_objs.Layout(hovermode="closest",
yaxis=dict(scaleratio=scaleratio,
scaleanchor="x"))
return graph_objs.Figure(data=data, layout=layout)
def create_quiver(x, y, u, v, scale=.1, arrow_scale=.3,
angle=math.pi / 9, scaleratio=None, **kwargs):
"""
Returns data for a quiver plot.
:param (list|ndarray) x: x coordinates of the arrow locations
:param (list|ndarray) y: y coordinates of the arrow locations
:param (list|ndarray) u: x components of the arrow vectors
:param (list|ndarray) v: y components of the arrow vectors
:param (float in [0,1]) scale: scales size of the arrows(ideally to
avoid overlap). Default = .1
:param (float in [0,1]) arrow_scale: value multiplied to length of barb
to get length of arrowhead. Default = .3
:param (angle in radians) angle: angle of arrowhead. Default = pi/9
:param (positive float) scaleratio: the ratio between the scale of the y-axis
and the scale of the x-axis (scale_y / scale_x). Default = None, the
scale ratio is not fixed.
:param kwargs: kwargs passed through plotly.graph_objs.Scatter
for more information on valid kwargs call
help(plotly.graph_objs.Scatter)
:rtype (dict): returns a representation of quiver figure.
Example 1: Trivial Quiver
```
import plotly.plotly as py
from plotly.figure_factory import create_quiver
import math
# 1 Arrow from (0,0) to (1,1)
fig = create_quiver(x=[0], y=[0], u=[1], v=[1], scale=1)
py.plot(fig, filename='quiver')
```
Example 2: Quiver plot using meshgrid
```
import plotly.plotly as py
from plotly.figure_factory import create_quiver
import numpy as np
import math
# Add data
x,y = np.meshgrid(np.arange(0, 2, .2), np.arange(0, 2, .2))
u = np.cos(x)*y
v = np.sin(x)*y
#Create quiver
fig = create_quiver(x, y, u, v)
# Plot
py.plot(fig, filename='quiver')
```
Example 3: Styling the quiver plot
```
import plotly.plotly as py
from plotly.figure_factory import create_quiver
import numpy as np
import math
# Add data
x, y = np.meshgrid(np.arange(-np.pi, math.pi, .5),
np.arange(-math.pi, math.pi, .5))
u = np.cos(x)*y
v = np.sin(x)*y
# Create quiver
fig = create_quiver(x, y, u, v, scale=.2, arrow_scale=.3, angle=math.pi/6,
name='Wind Velocity', line=dict(width=1))
# Add title to layout
fig['layout'].update(title='Quiver Plot')
# Plot
py.plot(fig, filename='quiver')
```
Example 4: Forcing a fix scale ratio to maintain the arrow length
```
import plotly.plotly as py
from plotly.figure_factory import create_quiver
import numpy as np
# Add data
x,y = np.meshgrid(np.arange(0.5, 3.5, .5), np.arange(0.5, 4.5, .5))
u = x
v = y
angle = np.arctan(v / u)
norm = 0.25
u = norm * np.cos(angle)
v = norm * np.sin(angle)
# Create quiver with a fix scale ratio
fig = create_quiver(x, y, u, v, scale = 1, scaleratio = 0.5)
# Plot
py.plot(fig, filename='quiver')
```
"""
utils.validate_equal_length(x, y, u, v)
utils.validate_positive_scalars(arrow_scale=arrow_scale, scale=scale)
if scaleratio is None:
quiver_obj = _Quiver(x, y, u, v, scale, arrow_scale, angle)
else:
quiver_obj = _Quiver(x, y, u, v, scale, arrow_scale, angle, scaleratio)
barb_x, barb_y = quiver_obj.get_barbs()
arrow_x, arrow_y = quiver_obj.get_quiver_arrows()
quiver_plot = graph_objs.Scatter(x=barb_x + arrow_x,
y=barb_y + arrow_y,
mode='lines', **kwargs)
data = [quiver_plot]
if scaleratio is None:
layout = graph_objs.Layout(hovermode='closest')
else:
layout = graph_objs.Layout(
hovermode='closest',
yaxis=dict(
scaleratio = scaleratio,
scaleanchor = "x"
)
)
return graph_objs.Figure(data=data, layout=layout)
def create_quiver(x,
y,
u,
v,
scale=.1,
arrow_scale=.3,
angle=math.pi / 9,
**kwargs):
"""
Returns data for a quiver plot.
:param (list|ndarray) x: x coordinates of the arrow locations
:param (list|ndarray) y: y coordinates of the arrow locations
:param (list|ndarray) u: x components of the arrow vectors
:param (list|ndarray) v: y components of the arrow vectors
:param (float in [0,1]) scale: scales size of the arrows(ideally to
avoid overlap). Default = .1
:param (float in [0,1]) arrow_scale: value multiplied to length of barb
to get length of arrowhead. Default = .3
:param (angle in radians) angle: angle of arrowhead. Default = pi/9
:param kwargs: kwargs passed through plotly.graph_objs.Scatter
for more information on valid kwargs call
help(plotly.graph_objs.Scatter)
:rtype (dict): returns a representation of quiver figure.
Example 1: Trivial Quiver
```
import plotly.plotly as py
from plotly.figure_factory import create_quiver
import math
# 1 Arrow from (0,0) to (1,1)
fig = create_quiver(x=[0], y=[0], u=[1], v=[1], scale=1)
py.plot(fig, filename='quiver')
```
Example 2: Quiver plot using meshgrid
```
import plotly.plotly as py
from plotly.figure_factory import create_quiver
import numpy as np
import math
# Add data
x,y = np.meshgrid(np.arange(0, 2, .2), np.arange(0, 2, .2))
u = np.cos(x)*y
v = np.sin(x)*y
#Create quiver
fig = create_quiver(x, y, u, v)
# Plot
py.plot(fig, filename='quiver')
```
Example 3: Styling the quiver plot
```
import plotly.plotly as py
from plotly.figure_factory import create_quiver
import numpy as np
import math
# Add data
x, y = np.meshgrid(np.arange(-np.pi, math.pi, .5),
np.arange(-math.pi, math.pi, .5))
u = np.cos(x)*y
v = np.sin(x)*y
# Create quiver
fig = create_quiver(x, y, u, v, scale=.2, arrow_scale=.3, angle=math.pi/6,
name='Wind Velocity', line=Line(width=1))
# Add title to layout
fig['layout'].update(title='Quiver Plot')
# Plot
py.plot(fig, filename='quiver')
```
"""
utils.validate_equal_length(x, y, u, v)
utils.validate_positive_scalars(arrow_scale=arrow_scale, scale=scale)
barb_x, barb_y = _Quiver(x, y, u, v, scale, arrow_scale, angle).get_barbs()
arrow_x, arrow_y = _Quiver(x, y, u, v, scale, arrow_scale,
angle).get_quiver_arrows()
quiver = graph_objs.Scatter(x=barb_x + arrow_x,
y=barb_y + arrow_y,
mode='lines',
**kwargs)
data = [quiver]
layout = graph_objs.Layout(hovermode='closest')
return graph_objs.Figure(data=data, layout=layout)
def create_streamline(x, y, u, v, density=1, angle=math.pi / 9,
arrow_scale=.09, **kwargs):
"""
Returns data for a streamline plot.
:param (list|ndarray) x: 1 dimensional, evenly spaced list or array
:param (list|ndarray) y: 1 dimensional, evenly spaced list or array
:param (ndarray) u: 2 dimensional array
:param (ndarray) v: 2 dimensional array
:param (float|int) 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
:param (angle in radians) angle: angle of arrowhead. Default = pi/9
:param (float in [0,1]) arrow_scale: value to scale length of arrowhead
Default = .09
:param kwargs: kwargs passed through plotly.graph_objs.Scatter
for more information on valid kwargs call
help(plotly.graph_objs.Scatter)
:rtype (dict): returns a representation of streamline figure.
Example 1: Plot simple streamline and increase arrow size
```
import plotly.plotly as py
from plotly.figure_factory import create_streamline
import numpy as np
import math
# Add data
x = np.linspace(-3, 3, 100)
y = np.linspace(-3, 3, 100)
Y, X = np.meshgrid(x, y)
u = -1 - X**2 + Y
v = 1 + X - Y**2
u = u.T # Transpose
v = v.T # Transpose
# Create streamline
fig = create_streamline(x, y, u, v, arrow_scale=.1)
# Plot
py.plot(fig, filename='streamline')
```
Example 2: from nbviewer.ipython.org/github/barbagroup/AeroPython
```
import plotly.plotly as py
from plotly.figure_factory import create_streamline
import numpy as np
import math
# Add data
N = 50
x_start, x_end = -2.0, 2.0
y_start, y_end = -1.0, 1.0
x = np.linspace(x_start, x_end, N)
y = np.linspace(y_start, y_end, N)
X, Y = np.meshgrid(x, y)
ss = 5.0
x_s, y_s = -1.0, 0.0
# Compute the velocity field on the mesh grid
u_s = ss/(2*np.pi) * (X-x_s)/((X-x_s)**2 + (Y-y_s)**2)
v_s = ss/(2*np.pi) * (Y-y_s)/((X-x_s)**2 + (Y-y_s)**2)
# Create streamline
fig = create_streamline(x, y, u_s, v_s, density=2, name='streamline')
# Add source point
point = Scatter(x=[x_s], y=[y_s], mode='markers',
marker=Marker(size=14), name='source point')
# Plot
fig['data'].append(point)
py.plot(fig, filename='streamline')
```
"""
utils.validate_equal_length(x, y)
utils.validate_equal_length(u, v)
validate_streamline(x, y)
utils.validate_positive_scalars(density=density, arrow_scale=arrow_scale)
streamline_x, streamline_y = _Streamline(x, y, u, v,
density, angle,
arrow_scale).sum_streamlines()
arrow_x, arrow_y = _Streamline(x, y, u, v,
density, angle,
arrow_scale).get_streamline_arrows()
streamline = graph_objs.Scatter(x=streamline_x + arrow_x,
y=streamline_y + arrow_y,
mode='lines', **kwargs)
data = [streamline]
layout = graph_objs.Layout(hovermode='closest')
return graph_objs.Figure(data=data, layout=layout)
def create_streamline(x,
y,
u,
v,
density=1,
angle=math.pi / 9,
arrow_scale=0.09,
**kwargs):
"""
Returns data for a streamline plot.
:param (list|ndarray) x: 1 dimensional, evenly spaced list or array
:param (list|ndarray) y: 1 dimensional, evenly spaced list or array
:param (ndarray) u: 2 dimensional array
:param (ndarray) v: 2 dimensional array
:param (float|int) 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
:param (angle in radians) angle: angle of arrowhead. Default = pi/9
:param (float in [0,1]) arrow_scale: value to scale length of arrowhead
Default = .09
:param kwargs: kwargs passed through plotly.graph_objs.Scatter
for more information on valid kwargs call
help(plotly.graph_objs.Scatter)
:rtype (dict): returns a representation of streamline figure.
Example 1: Plot simple streamline and increase arrow size
>>> from plotly.figure_factory import create_streamline
>>> import plotly.graph_objects as go
>>> import numpy as np
>>> import math
>>> # Add data
>>> x = np.linspace(-3, 3, 100)
>>> y = np.linspace(-3, 3, 100)
>>> Y, X = np.meshgrid(x, y)
>>> u = -1 - X**2 + Y
>>> v = 1 + X - Y**2
>>> u = u.T # Transpose
>>> v = v.T # Transpose
>>> # Create streamline
>>> fig = create_streamline(x, y, u, v, arrow_scale=.1)
>>> fig.show()
Example 2: from nbviewer.ipython.org/github/barbagroup/AeroPython
>>> from plotly.figure_factory import create_streamline
>>> import numpy as np
>>> import math
>>> # Add data
>>> N = 50
>>> x_start, x_end = -2.0, 2.0
>>> y_start, y_end = -1.0, 1.0
>>> x = np.linspace(x_start, x_end, N)
>>> y = np.linspace(y_start, y_end, N)
>>> X, Y = np.meshgrid(x, y)
>>> ss = 5.0
>>> x_s, y_s = -1.0, 0.0
>>> # Compute the velocity field on the mesh grid
>>> u_s = ss/(2*np.pi) * (X-x_s)/((X-x_s)**2 + (Y-y_s)**2)
>>> v_s = ss/(2*np.pi) * (Y-y_s)/((X-x_s)**2 + (Y-y_s)**2)
>>> # Create streamline
>>> fig = create_streamline(x, y, u_s, v_s, density=2, name='streamline')
>>> # Add source point
>>> point = go.Scatter(x=[x_s], y=[y_s], mode='markers',
... marker_size=14, name='source point')
>>> fig.add_trace(point) # doctest: +SKIP
>>> fig.show()
"""
utils.validate_equal_length(x, y)
utils.validate_equal_length(u, v)
validate_streamline(x, y)
utils.validate_positive_scalars(density=density, arrow_scale=arrow_scale)
streamline_x, streamline_y = _Streamline(x, y, u, v, density, angle,
arrow_scale).sum_streamlines()
arrow_x, arrow_y = _Streamline(x, y, u, v, density, angle,
arrow_scale).get_streamline_arrows()
streamline = graph_objs.Scatter(x=streamline_x + arrow_x,
y=streamline_y + arrow_y,
mode="lines",
**kwargs)
data = [streamline]
layout = graph_objs.Layout(hovermode="closest")
return graph_objs.Figure(data=data, layout=layout)
def create_quiver(x, y, u, v, scale=.1, arrow_scale=.3,
angle=math.pi / 9, **kwargs):
"""
Returns data for a quiver plot.
:param (list|ndarray) x: x coordinates of the arrow locations
:param (list|ndarray) y: y coordinates of the arrow locations
:param (list|ndarray) u: x components of the arrow vectors
:param (list|ndarray) v: y components of the arrow vectors
:param (float in [0,1]) scale: scales size of the arrows(ideally to
avoid overlap). Default = .1
:param (float in [0,1]) arrow_scale: value multiplied to length of barb
to get length of arrowhead. Default = .3
:param (angle in radians) angle: angle of arrowhead. Default = pi/9
:param kwargs: kwargs passed through plotly.graph_objs.Scatter
for more information on valid kwargs call
help(plotly.graph_objs.Scatter)
:rtype (dict): returns a representation of quiver figure.
Example 1: Trivial Quiver
```
import plotly.plotly as py
from plotly.figure_factory import create_quiver
import math
# 1 Arrow from (0,0) to (1,1)
fig = create_quiver(x=[0], y=[0], u=[1], v=[1], scale=1)
py.plot(fig, filename='quiver')
```
Example 2: Quiver plot using meshgrid
```
import plotly.plotly as py
from plotly.figure_factory import create_quiver
import numpy as np
import math
# Add data
x,y = np.meshgrid(np.arange(0, 2, .2), np.arange(0, 2, .2))
u = np.cos(x)*y
v = np.sin(x)*y
#Create quiver
fig = create_quiver(x, y, u, v)
# Plot
py.plot(fig, filename='quiver')
```
Example 3: Styling the quiver plot
```
import plotly.plotly as py
from plotly.figure_factory import create_quiver
import numpy as np
import math
# Add data
x, y = np.meshgrid(np.arange(-np.pi, math.pi, .5),
np.arange(-math.pi, math.pi, .5))
u = np.cos(x)*y
v = np.sin(x)*y
# Create quiver
fig = create_quiver(x, y, u, v, scale=.2, arrow_scale=.3, angle=math.pi/6,
name='Wind Velocity', line=Line(width=1))
# Add title to layout
fig['layout'].update(title='Quiver Plot')
# Plot
py.plot(fig, filename='quiver')
```
"""
utils.validate_equal_length(x, y, u, v)
utils.validate_positive_scalars(arrow_scale=arrow_scale, scale=scale)
barb_x, barb_y = _Quiver(x, y, u, v, scale,
arrow_scale, angle).get_barbs()
arrow_x, arrow_y = _Quiver(x, y, u, v, scale,
arrow_scale, angle).get_quiver_arrows()
quiver = graph_objs.Scatter(x=barb_x + arrow_x,
y=barb_y + arrow_y,
mode='lines', **kwargs)
data = [quiver]
layout = graph_objs.Layout(hovermode='closest')
return graph_objs.Figure(data=data, layout=layout)
