Copyright (c) 2022 Antmicro
A tool for rendering time series plots in multiple formats.
Example projects using the module:
The module supports following backends:
-
- requires plotext module only,
- renders plots to terminal, in txt format
-
- requires
bokehandnumpyfor HTML rendering, - renders images in interactive HTML, PNG and SVG formats,
- optionally requires Selenium and geckodriver for rendering PNG/SVG plots.
- requires
-
- requires
matplotlibmodule, - renders plots in SVG/JPG/PNG format.
- requires
To install base servis with plotext backend support, run:
pip install git+https://github.com/antmicro/servisTo install additional backends (bokeh, matplotlib), run:
pip install git+https://github.com/antmicro/servis#egg=servis[<backend-name>]For example:
pip install git+https://github.com/antmicro/servis#egg=servis[bokeh]To run Servis from terminal, use:
python -m servis -h
The tool accepts files with space-separated values, representing Y (and optionally X) values. It also accepts data from standard input.
For example, we can create a sample.txt file:
1 0
2 1
4 2
8 3
16 4
We can provide data in two ways:
cat sample.txt | python -m servis
or:
python -m servis sample.txt
It is possible to control the delimiter and plot type - check help (python -m servis -h) for details.
Example script:
import json
from servis import render_time_series_plot_with_histogram
with open("data1.json", "r") as data:
data = json.load(data)
xdata = data["xdata"]
ydata = data["ydata"]
tags = []
for tag in data["tags"]:
tags.append({
'name': tag[0],
'start': float(tag[1]),
'end': float(tag[2])
})
render_time_series_plot_with_histogram(
ydata,
xdata,
"Example plot",
"X axis",
"unit",
"Y axis",
"unit",
outpath="example_plots/singleplot",
outputext=["txt", "html", "png", "svg"],
tags=tags,
tagstype="double",
backend="matplotlib"
)To run the script from terminal:
python3 tests/test1.pyGenerated plot with PNG extension:
Example script:
import json
from servis import render_multiple_time_series_plot
with open("data2.json", "r") as data:
data = json.load(data)
xdata = data["xdata"]
ydata1 = data["ydata1"]
ydata2 = data["ydata2"]
tags = []
for tag in data["tags"]:
tags.append({
'name': tag[0],
'timestamp': float(tag[1])
})
render_multiple_time_series_plot(
[ydata1, ydata2],
[xdata]*2,
title="Example plot",
subtitles=["Plot1", "Plot2"],
xtitles=["X axis"]*2,
xunits=["unit"]*2,
ytitles=["Y axis"]*2,
yunits=["unit"]*2,
y_ranges=[(-5, 105)]*2,
outpath="example_plots/multipleplot",
outputext=["txt", "html"],
tags=[tags]*2,
tagstype="single",
backend="matplotlib",
is_x_timestamp=False,
setgradientcolors=True
)To run the script from terminal:
python3 tests/test2.pyGenerated TXT plot:
Example PNG double plot generated with bokeh:
Example script:
import json
from servis import render_multiple_time_series_plot
with open("data1.json", "r") as data:
data = json.load(data)
xdata0 = data["xdata"]
ydata0 = data["ydata"]
tags1 = []
for tag in data["tags"]:
tags1.append({
'name': tag[0],
'start': float(tag[1]),
'end': float(tag[2])
})
with open("data2.json", "r") as data:
data = json.load(data)
xdata1 = data["xdata"]
ydata1 = data["ydata1"]
ydata2 = data["ydata2"]
tags2 = []
for tag in data["tags"]:
tags2.append({
'name': tag[0],
'timestamp': float(tag[1])
})
COLORS = [
"#ab47bd", # purple
"#4051b5", # indigo
"#ef5552", # red
]
render_multiple_time_series_plot(
[[ydata0], [ydata1, ydata2]],
[[xdata0], [xdata1]*2],
title="Example plot",
subtitles=["Plot1", "Plot2"],
xtitles=["X axis"]*2,
xunits=["unit"]*2,
ytitles=["Y axis"]*2,
yunits=["unit"]*2,
outpath="example_plots/multifigures",
outputext=["png", "svg", "html", "txt"],
tags=[tags1, tags2],
tagstype=["double", "single"],
backend="matplotlib",
colormap=COLORS,
legend_labels=["Data1", "Data2", "Data3"]
)To run the script from terminal:
python3 tests/test3.pyExample PNG plot generated with matplotlib:
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