Before, chart customize was done by creating a new Psychrochart object based on some modified chart configuration,
so creating custom plots, or even changing chart limits, was challenging 😓
Now, when chart.config changes, any call to chart.save(), chart.make_svg(), or chart.plot()
will regenerate the chart data (limits, enabled curves, styling, etc.) before plotting, with only the visible curves inside limits,
(no more 0-size artifacts in SVGs, and most errors because some var is out of range should be gone now 🤞)
Changes
♻️ Update example notebook with API changes, and using chart.make_svg() as the recommended method to generate SVGs
🔇 Call to SetUnitSystem only if not already configured
🐛 tests: Fix running pytest on single tests
💄 Parse colors into RGBA values, so "red", "#FF0000", "#FF0000FF" produce the same float repr [1., 0., 0., 1.]
🐛 Fix #15 (avoid calls to GetRelHumFromTWetBulb if wb_t > db_t)
🏗️ Add mutation control for configuration models, and use it to check if there is any config change before creating a chart, triggering a chart-data regeneration if necessary
🔧 Add new field ChartFigure.dpi to chart config, for easy customization of matplotlib Figure DPI
⚡️ Delimit enthalpy and volume lines calculations to only the lines inside chart limits, avoiding extra calculations and potential errors with variables out of range
⚡️ Delimit constant RH lines calculations to only the visible lines inside the chart, and define .rh_labels as list[int]
⚡️ Delimit constant WBT lines calculations, with minor refactor on 'make_constant_wet_bulb_temperature_lines' method
⚡️ Set initial dbt-min for sat curve crossing x-axis plot, to avoid generation of hidden curves under x-axis
🔥 Remove old hidden trick to use Agg backend
🐛 Fix min wbt estimation around 0ºC
🐛 Fix #22 (convergence errors in iterator solver for enthalpy lines), by allowing a smaller minimal step increment, avoiding oscillation around objective
Before, chart customize was done by creating a new
Psychrochartobject based on some modified chart configuration, so creating custom plots, or even changing chart limits, was challenging 😓Now, when
chart.configchanges, any call tochart.save(),chart.make_svg(), orchart.plot()will regenerate the chart data (limits, enabled curves, styling, etc.) before plotting, with only the visible curves inside limits, (no more 0-size artifacts in SVGs, and most errors because some var is out of range should be gone now 🤞)Changes
chart.make_svg()as the recommended method to generate SVGsChartFigure.dpito chart config, for easy customization of matplotlib Figure DPI.rh_labelsas list[int]