Reputation: 3744
I have the following graph whose data (the position and the color values) come from an external source:
import plotly.graph_objs as go
from plotly.offline import init_notebook_mode, iplot
data = go.Scatter({
'hoverinfo': 'text',
'marker': {'color': ['rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(30,136,229,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(30,136,229,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(101,103,181,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(101,103,181,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(101,103,181,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(101,103,181,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(101,103,181,1.0)', 'rgba(173,71,134,1.0)', 'rgba(101,103,181,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(101,103,181,1.0)', 'rgba(101,103,181,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(30,136,229,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(30,136,229,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(30,136,229,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(101,103,181,1.0)', 'rgba(101,103,181,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)'],
'line': {'color': ['rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(30,136,229,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(30,136,229,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(101,103,181,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(101,103,181,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(101,103,181,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(101,103,181,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(101,103,181,1.0)', 'rgba(173,71,134,1.0)', 'rgba(101,103,181,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(101,103,181,1.0)', 'rgba(101,103,181,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(30,136,229,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(30,136,229,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(30,136,229,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(101,103,181,1.0)', 'rgba(101,103,181,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)', 'rgba(245,39,87,1.0)', 'rgba(245,39,87,1.0)', 'rgba(173,71,134,1.0)'],
'width': 0},
'size': 4.0,
'symbol': 'circle'},
'mode': 'markers',
'name': '',
'text': 'some hover text',
'x': [-0.003959869034588337, 0.005061251576989889, 0.006703123915940523, 0.0019563836976885796, -0.0034903099294751883, 0.01550869271159172, 0.0034700739197432995, -0.0018220042111352086, 0.010076701641082764, 0.005893221125006676, 0.006880240514874458, 0.008371046744287014, -0.011258691549301147, 0.006205271929502487, 0.006518206559121609, 0.0006746328435838223, 0.003603707766160369, 0.006014757324010134, 0.00443321093916893, 0.003568103536963463, -0.003682805225253105, -0.00819386076182127, -0.004438681993633509, -0.005338573828339577, -0.003959869034588337, 0.009993263520300388, -0.003959869034588337, -0.0022754939272999763, -0.006901460234075785, 0.004212438594549894, 0.0055755432695150375, 0.00879394169896841, 0.00341446022503078, -0.003105803159996867, -0.0017424229299649596, -0.003959869034588337, 0.003894187044352293, 0.00497738691046834, 0.007604200392961502, -0.002378312638029456, -0.003682805225253105, 0.006995890289545059, -0.0009093930711969733, -0.006481392774730921, -0.0005934620276093483, 0.000962280435487628, -0.005434616934508085, 0.007020855322480202, 0.003565214341506362, 0.0007076506153680384, -0.0010657859966158867, -0.004246561788022518, 0.004018908832222223, 0.00341446022503078, 0.008702066726982594, 0.003824896179139614, 0.005599078722298145, 0.001925327000208199, 0.00950327143073082, -0.004803186748176813, -0.004064114764332771, 0.0020236200653016567, -0.00015490801888518035, 0.005108738783746958, -0.0018468756461516023, 0.0026262067258358, -0.0017437718342989683, 0.003807958448305726, 0.006813774351030588, -0.009644323959946632, -0.009730380959808826, -0.0022573473397642374, 0.0046448661014437675, -0.0024109657388180494, 0.008578626438975334, 0.016399644315242767, 0.0031808093190193176, -0.014735744334757328, -0.001668736687861383, -0.0010972967138513923, 0.006214889232069254, -0.004786754958331585, 0.00018462195293977857, -0.003240009071305394, -0.008156259544193745, -0.0032861116342246532, -0.005193014163523912, -0.005338573828339577, 0.006094215903431177, 0.004020459949970245, -0.002630046335980296, -0.00510041881352663, 0.0034949760884046555, 0.013181162998080254, 0.005493168719112873, -0.0038349907845258713, 0.0087448013946414, -0.00782866682857275, -0.002721679862588644, 0.007046200335025787],
'xaxis': 'x',
'y': [-0.22, -0.12, -0.06, -0.06, 0.1, 0.01, -0.09, 0.07, -0.03, 0.0, 0.11, -0.07, 0.02, 0.13, -0.12, -0.09, 0.12, 0.01, -0.11, 0.1, -0.01, 0.02, -0.11, -0.05, 0.06, 0.02, 0.0, -0.11, 0.05, 0.08, -0.07, -0.03, 0.05, -0.1, -0.06, -0.04, -0.05, 0.15, -0.11, -0.12, 0.3, 0.05, 0.05, 0.0, -0.04, 0.02, -0.12, 0.17, 0.13, -0.01, 0.08, 0.02, 0.04, 0.0, -0.06, 0.04, -0.1, 0.02, 0.05, -0.04, 0.35, 0.05, -0.1, -0.05, -0.02, -0.03, 0.0, 0.02, -0.14, 0.04, 0.03, 0.1, 0.01, 0.15, -0.09, 0.01, -0.02, -0.01, -0.14, -0.08, -0.01, -0.06, 0.09, 0.03, -0.04, -0.05, -0.08, 0.0, 0.05, -0.01, -0.07, -0.1, -0.12, 0.01, 0.01, 0.15, -0.02, 0.04, -0.16, -0.07],
'yaxis': 'y'
})
layout=go.Layout(title="Some Plot", xaxis={'title':'x-axis label'})
init_notebook_mode(connected=True)
fig = go.Figure(data=[data], layout=layout)
iplot(fig)
Now, I want to add a colorbar to the right of the figure to give an indication of what the colors mean. For that, I took the color dictionary that resembles the colors in the plot, converted them to a colormap using matplotlib functions, and converted them to a plotly-compatible colormap as shown in the example here:
from matplotlib.colors import LinearSegmentedColormap
import matplotlib
import numpy as np
cdict = {
'red': ((0.0, 0.12, 0.12),
(1.0, 0.96, 0.96)),
'green': ((0.0, 0.53, 0.53),
(1.0, 0.15, 0.15)),
'blue': ((0.0, 0.90, 0.90),
(1.0, 0.34, 0.34)),
'alpha': ((0.0, 1, 1),
(0.5, 1, 1),
(1.0, 1, 1))
}
red_blue = LinearSegmentedColormap('RedBlue', cdict)
def matplotlib_to_plotly(cmap, pl_entries):
h = 1.0/(pl_entries-1)
pl_colorscale = []
for k in range(pl_entries):
C = list(map(np.uint8, np.array(cmap(k*h)[:3])*255))
pl_colorscale.append([k*h, 'rgb'+str((C[0], C[1], C[2]))])
return pl_colorscale
red_blue = matplotlib_to_plotly(red_blue, 255)
If I had access to the actual values used to color the data points, I could have used them to draw the colorbar like so: data['marker'] = dict(color=actual_color_values, colorscale=red_blue)
So, I tried taking the y-values from the data
part of the figure itself, to see if those were used to color the dots. But apparently not, because the resulting figure has different colors of the data points than the original one:
y = data['y']
data['marker'] = dict(color=y, colorscale=red_blue, colorbar=dict(thickness=10))
fig = go.Figure(data=[data], layout=layout)
iplot(fig)
Then I tried assigning the color values with the values of data['marker']['color']
. But this produces a blank colorbar with wrong colorbar limits:
y = data['marker']['color']
data['marker'] = dict(color=y, colorscale=red_blue, colorbar=dict(thickness=10))
fig = go.Figure(data=[data], layout=layout)
iplot(fig)
So I tried another way. I made a dummy trace using this colormap to display the colorbar with the min and max values of x and y by eyeballing from the original plot:
min_x = -0.015
max_x = 0.015
min_y = -0.3
max_y = 0.3
dummy_trace=go.Scatter(x=[min_x, max_x],
y=[min_y, max_y],
mode='markers',
marker=dict(
size=(max(y)-min(y))/100,
color=[min(y), max(y)],
colorscale=red_blue,
colorbar=dict(thickness=10),
showscale=True
),
hoverinfo='none'
)
layout = dict(xaxis=dict(visible=False), yaxis=dict(visible=False))
fig = go.Figure([dummy_trace], layout)
iplot(fig)
Now if I can somehow just display this colorbar alongside the actual plot, it'll do it. Is there any way to do that? And, if possible I would also like to remove the numbers from the colorbar, and display just High at the top of it and Low at the bottom of it, because as we have seen above, the min and max y-values are not the min and max of the actual values used to color the data points.
Upvotes: 13
Views: 13788
Reputation: 3744
I found the way to add the dummy trace to the figure object; it is with the add_trace
function. And the way to remove the numbers from the colorbar is to replace the tickvals
and ticktext
parameters in the colorbar
field of the dummy trace with the desired values.
colorbar_trace = go.Scatter(x=[None],
y=[None],
mode='markers',
marker=dict(
colorscale=red_blue,
showscale=True,
cmin=-5,
cmax=5,
colorbar=dict(thickness=5, tickvals=[-5, 5], ticktext=['Low', 'High'], outlinewidth=0)
),
hoverinfo='none'
)
fig['layout']['showlegend'] = False
fig.add_trace(colorbar_trace)
iplot(fig)
Since I want only 2 values in the colorbar (High
and Low
), I specify 2 values in tickvals; if, say, I specified 3 values in the colorbar
dictionary with tickvals=[-5, 0, 5], ticktext=['Low', 'Medium', 'High']
, it would look like this:
Upvotes: 18