Data visualization Custom python and R scripts were developed for data visualization, using the following packages: scipy [51], pandas [52], numpy [53], seaborn [54], python [55], jupyter notebook [56], statsmo
A fourth-order Runge-Kutta method, with an adaptive timestep, in the Python library SciPy is used to solve the ordinary differential equations dx/dt=u(x(t),y(t),t), which describe the motion of the markers. A user-defined maximum timestep, Δtmax=0.01, is used in the numerical ...
Three-dimensional deformable surfaces provide essential geometric information for individuals to visually sense each other and further interact with each other in a social interaction context. However, the 3D surface information has not been captured by most existing laboratory animal motion capture methodol...
The python package scipy (ver 1.4.1) was used throughout all the statistical analyses. 3. Results 3.1. Compositions of the shapes and polymers of meso/microplastic particles The total number and mass of the MMP particles were 4390 and 676 mg, respectively. The size distributions indicated that...
If 90% or more of the polygon is within the path/row or the area of intersection between adjacent path/rows, the polygon is treated as contained by the path/row. Large wetland polygons that cover multiple path-rows or small wetland polygons that fall on boundaries often inter- sect more...