In [62]:

    

import numpy as np


    

In [63]:

    

a = np.loadtxt(fname='inflammation-data/inflammation-01.csv', delimiter=',')
a.shape


    

    
Out[63]:





(60, 40)

In [64]:

    

b = np.loadtxt(fname='inflammation-data/inflammation-02.csv', delimiter=',')
b.shape


    

    
Out[64]:





(60, 40)

In [65]:

    

from plotly import __version__
from plotly.offline import download_plotlyjs, init_notebook_mode, iplot
import plotly.graph_objs as go
init_notebook_mode()


    

In [66]:

    

print(__version__)


    

    




1.9.5

In [67]:

    

p0 = a[0, :]
iplot([{"x": [i for i in range(0, len(p0))], "y": p0}])


    

In [68]:

    

data = []
for x in range(60):
    patient_data = a[x, :]
    trace = go.Scatter(
        name = "Patient " + str(x),
        x = [i for i in range(len(patient_data))],
        y = patient_data,
        mode = 'markers'
    )
    #[{"x": [i for i in range(len(patient_data))], "y": patient_data}]
    data.append(trace)

iplot(data)


    

In [69]:

    

data = []
for x in range(60):
    patient_data = a[x, :]
    trace = go.Scatter(
        name = "Patient " + str(x),
        x = [i for i in range(len(patient_data))],
        y = patient_data,
        mode = 'lines'
    )
    #[{"x": [i for i in range(len(patient_data))], "y": patient_data}]
    data.append(trace)

iplot(data)


    

In [70]:

    

means = []
for x in range(60):
    patient_data = a[x, :]
    means.append(patient_data.mean())

means = np.array(means)
mean = means.mean()
stdev = means.std()
print("Mean: ", str(mean))
print("Standard Deviation: ", str(stdev))

hist_data = [
    go.Histogram(
        x = means
    )]

hist_layout = go.Layout(
    title='Histogram of Patient 0-60 Inflammation Means',
    xaxis=dict(
        title='Mean Inflammation'
    ),
    yaxis=dict(
        title='Count'
    ),
    #barmode='overlay',
    bargap=0.25,
    bargroupgap=0.3
)

fig = go.Figure(data=hist_data, layout=hist_layout)
iplot(fig)


    

    




Mean:  6.14875
Standard Deviation:  0.42047654017






    

In [78]:

    

data = {"Low": [], "Mid-Low": [], "Mid-High": [], "High": []}
for x in range(60):
    patient_data = a[x, :]
    patient_mean = patient_data.mean()
    
    trace = go.Scatter(
        name = "Patient " + str(x),
        x = [i for i in range(len(patient_data))],
        y = patient_data,
        mode = 'lines'
    )
    if patient_mean < mean - stdev:
        data["Low"].append(trace)
    elif patient_mean > mean + stdev:
        data["High"].append(trace)
    else:
        if patient_mean <= mean:
            data["Mid-Low"].append(trace)
        else:
            data["Mid-High"].append(trace)

for plot in data:
    layout = go.Layout(
        title='Inflamation by Day for Patients with %s Mean' % plot,
        xaxis=dict(
            title='Day'
        ),
        yaxis=dict(
            title='Inflammation Score'
        )
    )
    figure = go.Figure(data=data[plot], layout=layout)
    iplot(figure)


    

In [ ]: