A Python 3 library to make psychrometric charts and overlay information on them.
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
chart.make_svg(...)
NOTE: 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. This library is intended for HVAC applications only ⚠️
from psychrochart import PsychroChart
# Load default style:
chart_default = PsychroChart.create()
# customize anything
chart_default.limits.range_temp_c = (15.0, 35.0)
chart_default.limits.range_humidity_g_kg = (5, 25)
chart_default.config.saturation.linewidth = 1
chart_default.config.constant_wet_temp.color = "darkblue"
# plot
axes = chart_default.plot()
axes.get_figure()
# or store on disk
chart_default.save("my-custom-chart.svg")
Called from the 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.create().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
, ashrae_ip
(adjusted for IP units), interior
, and minimal
.
from pathlib import Path
from psychrochart import load_config, PsychroChart
# Load preconfigured styles:
chart_ashrae_style = PsychroChart.create('ashrae')
chart_ashrae_style.plot()
chart_minimal = PsychroChart.create('minimal')
chart_minimal.plot()
# Get a preconfigured style model and customize it
chart_config = load_config('interior')
chart_config.limits.range_temp_c = (18.0, 32.0)
chart_config.limits.range_humidity_g_kg = (1.0, 40.0)
chart_config.limits.altitude_m = 3000
custom_chart = PsychroChart.create(chart_config)
custom_chart.save("custom-chart.svg")
# serialize the config for future uses
assert chart_config.json() == custom_chart.config.json()
Path('path/to/chart_config_file.json').write_text(chart_config.json())
custom_chart_bis = PsychroChart.create('path/to/chart_config_file.json')
# or even the full psychrochart
Path('path/to/chart_file.json').write_text(custom_chart.json())
custom_chart_bis_2 = PsychroChart.parse_file('path/to/chart_file.json')
# Specify the styles JSON file:
chart_custom = PsychroChart.create('/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
},
"constant_v_annotation": {
"color":[0.2, 0.2, 0.2],
"fontsize":7,
"bbox": dict(boxstyle="square,pad=-0.2", color=[1, 1, 1, 0.9], lw=0.5)
},
"constant_h_annotation": {
"color":[0.2, 0.2, 0.2],
"fontsize":6,
"bbox": dict(boxstyle="square,pad=-0.1", color=[1, 1, 1, 0.9], lw=0.5)
},
"constant_wet_temp_annotation": {
"color":[0.2, 0.2, 0.2],
"fontsize":7,
"bbox": dict(boxstyle="square,pad=0", color=[1, 1, 1, 0.9], lw=0.5)
},
"constant_rh_annotation": {
"color":[0.2, 0.2, 0.2],
"fontsize":7,
"bbox": dict(boxstyle="square,pad=0", color=[1, 1, 1, 0.9], lw=0.5)
}
}
chart_custom_2 = PsychroChart.create(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
.
Run poetry run pre-commit run --all-files
to apply linters for changes in the code 😜.
MIT license, so do with it as you like ;-)
Default style:
ASHRAE Handbook black and white style: (preset: ashrae
)
ASHRAE Handbook black and white style (IP units): (preset: ashrae_ip
)
Minimal style: (preset: minimal
)