caslock/psychrochart

A Python 3 library to make psychrometric charts and overlay information on them.

Psychrochart

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).

Install

Get it from pypi or clone it if you want to run the tests.

pip install psychrochart

Features

• SI units (with temperatures in celsius for better readability).
• Easy style customization with a JSON template (colors, line styles and line widths).
• Psychrometric charts within temperature and humidity ratio ranges, for any pressure*, with:
  • Saturation line
  • Constant RH lines
  • Constant enthalpy lines
  • Constant wet-bulb temperature lines
  • Constant specific volume lines
  • Constant dry-bulb temperature lines (internal orthogonal grid, vertical)
  • Constant humidity ratio lines (internal orthogonal grid, horizontal)
• Plot legend for each family of lines
• Specify labels for each family of lines
• Overlay points, zones, arrows...
• Export SVG, PNG files

* 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.

Usage

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()

Chart customization

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.

Tests

To run the tests, clone the repository, poetry install it, and run poetry run pytest.

License

MIT license, so do with it as you like ;-)

Included styling examples

Default style:

ASHRAE Handbook black and white style:

ASHRAE Handbook black and white style (IP units):

Minimal style: