Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
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💹 Hackable charting lib for traders. You can draw literally ANYTHING on top of candlestick charts. [Not Maintained] | ||||||||||
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A better way to deploy Kubernetes Helm charts | ||||||||||
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Psychrochart | 74 | 4 months ago | 23 | November 12, 2019 | 12 | mit | Jupyter Notebook | |||
A Python 3 library to make psychrometric charts and overlay information on them. | ||||||||||
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HTML5 ES6 canvas candlestick chart with probability heatmap overlay. Built to display stock and currency forecasts. | ||||||||||
Chartjs Plugin Empty Overlay | 8 | 4 years ago | 4 | November 29, 2017 | 2 | other | JavaScript | |||
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A python 3 library to make psychrometric charts and overlay information on them.
It implements a useful collection of psychrometric equations for moisture and humid air calculations, and the generation of beautiful and high customizable psychrometric charts in SVG with matplotlib
.
Psychrometric calculations to make the chart data are done with PsychroLib
(summary paper in https://doi.org/10.21105/joss.01137).
Get it from pypi or clone it if you want to run the tests.
pip install psychrochart
* The ranges of temperature, humidity and pressure where this library should provide good results are within the normal environments for people to live in. Don't expect right results if doing other type of thermodynamic calculations. Over saturated water vapor states are not implemented.
from psychrochart import PsychroChart
# Load default style:
chart_default = PsychroChart()
axes = chart_default.plot()
axes.get_figure()
Called from a terminal (python psychrochart
), it plots and shows the default chart using the default matplotlib backend, equivalent to this python script:
from psychrochart import PsychroChart
import matplotlib.pyplot as plt
PsychroChart().plot(ax=plt.gca())
plt.show()
The default styling for charts is defined in JSON files that you can change, or you can pass a path of a file in JSON, or a dict, when you create the psychrometric chart object.
Included styles are: default
, ashrae
, interior
and minimal
.
from psychrochart import load_config, PsychroChart
# Load preconfigured styles:
chart_ashrae_style = PsychroChart('ashrae')
chart_ashrae_style.plot()
chart_minimal = PsychroChart('minimal')
chart_minimal.plot()
# Get a preconfigured style dict
dict_config = load_config('interior')
# Specify the styles JSON file:
chart_custom = PsychroChart('/path/to/json_file.json')
chart_custom.plot()
# Pass a dict with the changes wanted:
custom_style = {
"figure": {
"figsize": [12, 8],
"base_fontsize": 12,
"title": "My chart",
"x_label": None,
"y_label": None,
"partial_axis": False
},
"limits": {
"range_temp_c": [15, 30],
"range_humidity_g_kg": [0, 25],
"altitude_m": 900,
"step_temp": .5
},
"saturation": {"color": [0, .3, 1.], "linewidth": 2},
"constant_rh": {"color": [0.0, 0.498, 1.0, .7], "linewidth": 2.5,
"linestyle": ":"},
"chart_params": {
"with_constant_rh": True,
"constant_rh_curves": [25, 50, 75],
"constant_rh_labels": [25, 50, 75],
"with_constant_v": False,
"with_constant_h": False,
"with_constant_wet_temp": False,
"with_zones": False
}
}
chart_custom_2 = PsychroChart(custom_style)
chart_custom_2.plot()
The custom configuration does not need to include all fields, but only the fields you want to change.
To play with it and see the results, look at this notebook with usage examples.
To run the tests, clone the repository, poetry install
it, and run poetry run pytest
.
MIT license, so do with it as you like ;-)
Default style:
ASHRAE Handbook black and white style:
ASHRAE Handbook black and white style (IP units):
Minimal style: