ES-Alexander

import numpy as np

try:
    # If available, import numba to enable compiling the functions for extra speed
    from numba import njit, boolean

except ImportError:
    print("Numba compilation not available - falling back to pure Python.")

    def njit(func, *args, **kwargs):

ES-Alexander

from fullcontrol.visualize.tube_mesh import FlowTubeMesh, go, np

# Display parameters
COLOURS = '#666' # 'black' / '#C0FFEE' / None
SHOW = True # if False, saves animation frames instead

# Geometry parameters
np.random.seed(sum(b'gcode'))
SEGMENTS_PER_CURVE = 31
BASE_THICKNESS = 0.6 # 0.2

ES-Alexander

# relevant types
from collections.abc import Sequence
from numbers import Real
import pathlib
# functionality
from itertools import chain, pairwise
import plotly.graph_objects as go
import numpy as np

ES-Alexander

''' Written in response to u/thisisjusttofindajob's Reddit post 

https://www.reddit.com/r/learnpython/comments/xnq9bv/how_to_render_objects_randomly_in_time/

about random timings with an average frequency.
'''

from time import perf_counter
import random

ES-Alexander

'''
Cleans up a drawing, and creates grey, blue, and red variants.
Blue and red are saved with a transparent background.
Grey is saved as single channel.

Author: ES-Alexander
License: MIT (a.k.a. free use, but not my problem if it doesn't work for you)

Created in response to:
  https://www.reddit.com/r/opencv/comments/wmyuyh/question_remove_paper_background_from_sketches/

ES-Alexander

''' Mandelbulb.py

Adapted from
 https://github.com/AstroKriel/Mandelbulb/blob/main/python/main.py

EXAMPLE OUTPUT:
 https://youtube.com/shorts/f8ek83Z9SFo

Original author: AstroKriel
   - Mandelbulb raymarcher

ES-Alexander

#!/usr/bin/env python3

from pymavlink import mavutil, mavlink

class CourseAverager:
    MSG_TYPE = 'GLOBAL_POSITION_INT'
    
    def __init__(self, mavlink_connection, request_rate=1, decay_rate=0.95, initial_course=(0, 0)):
        self.master = mavlink_connection
        self.request_message(request_rate)

ES-Alexander

from scipy.spatial import KDTree
import matplotlib.pyplot as plt
import numpy as np

# SETUP
points = np.array([[1,2],[5,9],[-8,-2],[5,-5],[-4,-1]])
xmin, xmax, ymin, ymax = -10, 10, -10, 10
x_resolution = y_resolution = 300
pixel_size = max((xmax-xmin)/x_resolution, (ymax-ymin)/y_resolution)
radius = 3

ES-Alexander

from pathlib import Path
from scipy.io import wavfile
from scipy.fft import fft, fftfreq
import matplotlib.pyplot as plt
import numpy as np

path = Path('.') # path to whale song files

files = list(path.glob('*.wav'))

ES-Alexander

#!/usr/bin/env python3

from itertools import combinations_with_replacement
from typing import List, Tuple, Generator

VALID_E_SERIES = (3, 6, 12, 24, 48, 96, 192)

def E(m: int) -> Generator[float, None, None]:
    """ A generator of IEEE E-series values.