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Coming Soon!! SuperAlign accepts matplotlib figures to be logged. These figures are converted to images before registering.

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Logging inside the model decorator

Using log method, matplotlib figures are added to a model version: 
from pureml.decorators import model
import pureml

@model('sales forecast')
def train_model():
    #model = model training code
    ....

    fig = #matplotlib figure object
    pureml.log(figure={'cnf_matrix':fig})

    ...
    return model
When log method is invoked inside the model decorator, the figures are added to the version of the model that is registered by the decorator.

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Logging outside the model decorator

Logging can be done outside the model decorator in the following ways: 
pureml.log(figure={'cnf_matrix':fig},
           label='sales forecast')
By default, log method adds the figure to the latest version of the model. It can be added to a particular version of a model by providing version parameter as the following: 
pureml.log(figure={'cnf_matrix':fig},
           label='sales forecast:v3')
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