1
pip3 install nominal jupyterlab pandas plotly ipywidgets

1
from dateutil import parser
2
import datetime
3
import pandas as pd
4
import numpy as np
5
6
dataset_name = "1h_5ms"
7
start = parser.isoparse("2024-10-22T00:00:00Z")
8
end = parser.isoparse("2024-10-22T01:00:00Z")
9
resolution = datetime.timedelta(milliseconds=5)
10
11
dt = end - start
12
n = int((dt.total_seconds() * 1e6 + dt.microseconds) / resolution.microseconds)
13
14
np.random.seed(2)
15
cols = ["value"]
16
17
# Generate a fake signal
18
signal = np.random.normal(0, 0.3, size=n).cumsum() + 50
19
20
# Generate many noisy samples from the signal
21
noise = lambda var, bias, n: np.random.normal(bias, var, n)
22
23
data = {c: signal + noise(1, 10*(np.random.random() - 0.5), n) for c in cols}
24
25
# Pick a few samples from the first line and really blow them out
26
locs = np.random.choice(n, 10)
27
data["value"][locs] *= 2
28
29
data["Time"] = [(start + resolution * i).isoformat() for i in range(n)]
30
31
df_gen = pd.DataFrame(data)
32
df_gen

1
import nominal.nominal as nm
2
3
nm.set_token(
4
    base_url = 'https://api.gov.nominal.io/api',
5
    token = '* * *' # Replace with your Access Token from 
6
                    # https://app.gov.nominal.io/settings/user?tab=tokens
7
)

1
dataset = nm.upload_pandas(df_gen, dataset_name, "Time", timestamp_type="iso_8601")
2
dataset

1
channel = dataset.get_channel("value")
2
df_decimated = channel.get_decimated(start, end, buckets=2000)
3
df_decimated

1
import plotly.graph_objects as go
2
3
if "value" in df_decimated.columns:
4
    # range had less than 1000 points
5
    fig = go.Figure([
6
        go.Scatter(
7
            x=df_decimated.index,
8
            y=df_decimated["value"],
9
            mode="lines",
10
            # line=dict(width=0),
11
            showlegend=False,
12
            # line_shape="vh"
13
        ),
14
    ])
15
else:
16
    fig = go.Figure([
17
        go.Scatter(
18
            x=df_decimated.index,
19
            y=df_decimated["max"],
20
            mode="lines",
21
            line=dict(width=0),
22
            showlegend=False,
23
            line_shape="vh"
24
        ),
25
        go.Scatter(
26
            x=df_decimated.index,
27
            y=df_decimated["min"],
28
            mode="lines",
29
            fill="tonexty",
30
            fillcolor="blue",
31
            line=dict(width=0),
32
            showlegend=False,
33
            line_shape="vh"
34
        )
35
    ])
36
37
fig.update_layout(
38
    xaxis_title="Time",
39
    yaxis_title="Value"
40
)
41
42
fig.show()

1
def on_range_change(layout, range_x):
2
    start = parser.isoparse(range_x[0]+"Z")
3
    end = parser.isoparse(range_x[1]+"Z")
4
5
    df = channel.get_decimated(start, end, buckets=2000)
6
7
    # Create a new figure with the new data
8
    fig = make_fig(df)
9
    fig.update_layout(xaxis={"range": range_x})
10
11
    # Update the existing figure widget with the new figure
12
    fig_widget.layout = fig.layout
13
    fig_widget.layout.on_change(on_range_change, "xaxis.range")
14
    fig_widget.data = []
15
    fig_widget.add_traces(fig.data)
16
17
def make_fig(df):
18
    if "value" in df.columns:
19
        # range had less than 1000 points
20
        fig = go.Figure([
21
            go.Scatter(
22
                x=df.index,
23
                y=df["value"],
24
                mode="lines",
25
                showlegend=False,
26
            ),
27
        ])
28
    else:
29
        fig = go.Figure([
30
            go.Scatter(
31
                x=df.index,
32
                y=df["max"],
33
                mode="lines",
34
                line=dict(width=0),
35
                showlegend=False,
36
                line_shape="vh"
37
            ),
38
            go.Scatter(
39
                x=df.index,
40
                y=df["min"],
41
                mode="lines",
42
                fill="tonexty",
43
                fillcolor="blue",
44
                line=dict(width=0),
45
                showlegend=False,
46
                line_shape="vh"
47
            )
48
        ])
49
50
    fig.update_layout(
51
        xaxis_title="Time",
52
        yaxis_title="Value",
53
    )
54
    return fig
55
56
fig_range = make_fig(channel.get_decimated(start, end, buckets=2000))
57
fig_widget = go.FigureWidget(fig_range)
58
59
fig_widget.layout.on_change(on_range_change, "xaxis.range")
60
61
fig_widget