Fitting the Principle of Constancy and Change
In the movement of the stars and the transformation of all things, natural regularities display a dual character: on the one hand there are recurring cycles that remain constant from year to year; on the other hand there are climate anomalies and varying factors that differ each year. One of the core ideas in Chinese medical models of time and space is therefore the principle of constancy and change. When constructing a model, this principle requires a constant main axis (constancy) representing the basic order—a baseline—together with a deviation that captures dynamic disturbance. Only by combining the two can complex phenomena be fitted adequately. This closely resembles the way nonlinear signals are handled in modern data science. If one looks only at “constancy,” the model becomes rigid and cannot explain anomalies such as a warm winter or a cold spring. If one looks only at “change,” the model falls into disorder. Through the superposition of host qi (constancy) and guest qi (change), the ancients attempted to use an orderly equation-like framework to calculate the complex physiological effects of dynamic meteorological variation.
