A Step-by-Step Guide To Accurately Detect Peaks and Valleys.

Our human brain is excellent in peak detection in relation to its context. What seems an easy task by eye can be a challenging task to automate by machines. In general, peaks and valleys indicate (significant) events such as sudden increases or decreases in price/volume, or sharp rises in demand. One of the challenges is the definition of a peak/valley which can differ across applications and domains. Other challenges can be more technical, such as a noisy signal that can result in many false positives or a single threshold that may not accurately detect local events. In this blog, I will describe how to accurately detect peaks and valleys in a 1-dimensional vector or a 2-dimensional array (image) without making assumptions about the peak shape. In addition, I will demonstrate how to handle noise in the signal. Analyses are performed using the findpeaks library, and hands-on examples are provided for experimenting. <a href="https://towardsdatascience.com/a-step-by-step-guide-to-accurately-detect-peaks-and-valleys-9abc49a2eac3">Click Here</a>