alexlib

import napari
import numpy as np


def _circle(r, theta):
    x = r*np.cos(theta)
    y = r*np.sin(theta)
    return x, y

def _sphere(r, theta, psi):

alexlib

import numpy as np
import numba
import xarray as xr

@numba.jit(nopython=True)
def lowess_1d(y, x, alpha=2. / 3., it=10):
    """lowess(x, y, f=2./3., iter=3) -> yest
    Lowess smoother: Robust locally weighted regression.
    The lowess function fits a nonparametric regression curve to a scatterplot.
    The arrays x and y contain an equal number of elements; each pair

alexlib

alexlib

# Example animations using matplotlib's FuncAnimation
# Ken Hughes. August 2019

# For more detail, see
#https://brushingupscience.com/2019/08/01/elaborate-matplotlib-animations/

# Examples include
#   - quiver plot with variable positions and directions
#   - 3D contour plot
#   - line plot on a polar projection

alexlib

# Example animations using matplotlib's FuncAnimation
# Ken Hughes. 18 June 2016.

# For more detail, see
# https://brushingupscience.wordpress.com/2016/06/21/matplotlib-animations-the-easy-way/

# Examples include
#    - line plot
#    - pcolor plot
#    - scatter plot

alexlib

import gcsfs
import pyarrow

def read_parquet(gs_directory_path, to_pandas=True):
    """
    Reads multiple (partitioned) parquet files from a GS directory
    e.g. 'gs://<bucket>/<directory>' (without ending /)
    """
    gs = gcsfs.GCSFileSystem()
    arrow_df = pyarrow.parquet.ParquetDataset(gs_directory_path, filesystem=gs)

alexlib

alexlib

alexlib

alexlib

Python version of the MATLAB code in this Stack Overflow post: http://stackoverflow.com/a/18648210/97160

The example shows how to determine the best-fit plane/surface (1st or higher order polynomial) over a set of three-dimensional points.

Implemented in Python + NumPy + SciPy + matplotlib.