Package: psychrochart
PsychrochartA python 3 library to makepsychrometric chartsand 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 customizablepsychrometric charts in SVGwithmatplotlib.Psychrometric calculations to make the chart data are done withPsychroLib(summary paper inhttps://doi.org/10.21105/joss.01137).InstallGet itfrom pypiorclone itif you want to run the tests.pipinstallpsychrochartFeaturesSIunits (with temperatures in celsius for better readability), withpartialcompatibility with IP system (imperial units)Easy style customization based onpydanticmodels and config presets for full customization ofchart limits, included lines and labels, colors, line styles, line widths, etc..Psychrometric charts within temperature and humidity ratio ranges, for any pressure*, with:Saturation lineConstant RH linesConstant enthalpy linesConstant wet-bulb temperature linesConstant specific volume linesConstant dry-bulb temperature lines(internal orthogonal grid, vertical)Constant humidity ratio lines(internal orthogonal grid, horizontal)Plot legend for each family of lines, labeled zones and annotationsSpecify labels for each family of linesOverlay points, arrows,data-series(numpy arrays or pandas series), and convex hulls around pointsDefine multiple kinds ofzones limited by psychrometric values:'dbt-rh' for areas between dry-bulb temperature and relative humidity values,'enthalpy-rh' for areas between constant enthalpy and relative humidity values'volume-rh' for areas between constant volume and relative humidity values'dbt-wmax' for an area between dry-bulb temperature and water vapor content values (:= a rectangle cut by the saturation line),'xy-points' to define arbitrary closed paths in plot coordinates (dbt, abs humidity)Export as SVG, PNG files, or generate dynamic SVGs with extra CSS and  withchart.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 ⚠️UsagefrompsychrochartimportPsychroChart# Load default style:chart_default=PsychroChart.create()# customize anythingchart_default.limits.range_temp_c=(15.0,35.0)chart_default.limits.range_humidity_g_kg=(5,25)chart_default.config.saturation.linewidth=1chart_default.config.constant_wet_temp.color="darkblue"# plotaxes=chart_default.plot()axes.get_figure()# or store on diskchart_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:frompsychrochartimportPsychroChartimportmatplotlib.pyplotaspltPsychroChart.create().plot(ax=plt.gca())plt.show()Chart customizationThe 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, andminimal.frompathlibimportPathfrompsychrochartimportload_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 itchart_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=3000custom_chart=PsychroChart.create(chart_config)custom_chart.save("custom-chart.svg")# serialize the config for future usesassertchart_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 psychrochartPath('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 thisnotebook with usage examples.Development and testingTo run the tests, clone the repository,poetry installit, and runpoetry run pytest.Runpoetry run pre-commit run --all-filesto apply linters for changes in the code 😜.LicenseMIT license, so do with it as you like ;-)Included styling examplesDefault style:ASHRAE Handbook black and white style: (preset:ashrae)ASHRAE Handbook black and white style (IP units): (preset:ashrae_ip)Minimal style: (preset:minimal)