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I am trying to annotate my subplots inside a for loop. Each subplot will have RMS value printed on the plot. I tried to do it the following way:

from plotly import tools
figg = tools.make_subplots(rows=4, cols=1)

fake_date = {"X":   np.arange(1, 101, 0.5), "Y": np.sin(x), "Z": [x + 1 for x in range(10)] * 20}
fake_date = pd.DataFrame(fake_date)
fake_date.sort_values("Z")

unique_ids = fake_date['Z'].unique()
train_id, test_id = np.split(np.random.permutation(unique_ids), [int(.6 * len(unique_ids))])


for i, j in enumerate(test_id):

    x_test = fake_date[fake_date['Z'].isin([test_id[i]])] 
    y_test = fake_date[fake_date['Z'].isin([test_id[i]])]


    # Evaluate 
    rms_test = 0.04
    r_test = 0.9



    Real = {'type' : 'scatter',
                     'x' : x_test.X,
                     'y' : x_test.Y,
                "mode" : 'lines+markers', 
                "name" : 'Real'}




    figg.append_trace(Real, i+1, 1)


figg['layout'].update( annotations=[dict(x = 10,y = 0.2,  text= rms_test, xref= "x1",yref="y1")]  )
figg['layout'].update(height=1800, width=600, title='Testing')
pyo.iplot(figg)

This does not work, although the answer given here seems to work for others. Can anyone point out what wrong am I doing? I generated fake date for reproducibility

owise
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1 Answers1

2

I am not sure where to exactly place the RMS value, but below is a sample code which will help you achieve what you want.

We create an array annotation_arr where we store the annotations using the for loop.

We need to set the xval and yval for each of the individual axes. Remember, first axis will be x, second will be x2 so, I have written a ternary condition for that, please checkout the below code and let me know if there is any issues!

import plotly.graph_objs as go
from plotly.offline import download_plotlyjs,init_notebook_mode,plot,iplot
from plotly import tools
import numpy as np
import pandas as pd
init_notebook_mode(connected=True)
rows = 4
figg = tools.make_subplots(rows=rows, cols=1)

fake_date = {"X":   np.arange(0, 100, 0.5), "Y": [np.sin(x) for x in range(200)], "Z": [x + 1 for x in range(10)] * 20}
fake_date = pd.DataFrame(fake_date)
fake_date.sort_values("Z")

unique_ids = fake_date['Z'].unique()
train_id, test_id = np.split(np.random.permutation(unique_ids), [int(.6 * len(unique_ids))])
top = 0
annotation_arr = []
for i, j in enumerate(test_id):

    x_test = fake_date[fake_date['Z'].isin([test_id[i]])] 
    y_test = fake_date[fake_date['Z'].isin([test_id[i]])]


    # Evaluate 
    rms_test = 0.04
    r_test = 0.9



    Real = {'type' : 'scatter',
                     'x' : x_test.X,
                     'y' : x_test.Y,
                "mode" : 'lines+markers', 
                "name" : 'Real'}


    top = top + 1/rows
    i_val = "" if i == 0 else i + 1
    annotation_arr.append(dict(x = r_test,y = top,  text= rms_test, xref= "x"+str(i_val),yref="y"+str(i_val)))
    figg.append_trace(Real, i+1, 1)


figg['layout'].update( annotations=annotation_arr  )
figg['layout'].update(height=1800, width=600, title='Testing')
iplot(figg)
Naren Murali
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