Craig Versek cversek

## basic_socket_server.py
import time, socket


doc = """
<!DOCTYPE html>
<html>
    <head> <title>ESP8266 Pins</title> </head>
    <body> <h1>ESP8266 Pins</h1>
        <table border="1"> <tr><th>Pin</th><th>Value</th></tr> s </table>

## README.md

      
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                cversek
                / README.md
            
            
              Created
              June 10, 2016 02:12
            
              
                These are simple pygame based pendulum physics simulations.
              
          
    auth: Craig Wm. Versek (cversek@gmail.com)
dates: gist created 2016/06/09 based directly from code written circa 2008 while I was a PhD candidate at UMass Amherst
These are simple pygame based pendulum physics simulations that started with a simple idea: perform the numerical integration (the "physics") within an infinite generator loop, supplying the parameters to the graphics rendering code on demand.  The thought was to separate the number crunching from the application at large and simplify its organization and portability.  The code can be configured to use one of a few numerical integration methods by swapping generators with the same interface. pygame is the only dependency that needs to be installed.
phys_gen.py illustrates the basic concept with no bells & whistles (nor graphics).
pendulum.py is a pygame driven simple pendulum interactive simulation -- try clicking and dragging the bob. Can use Heun, Steormer_Verlet, or RK4 methods.
doubled_pedulum.py has two double pendula running in

  
## cmap_gaussianHSV.py
import numpy as np
import matplotlib

def make_cmap_guassianHSV( num_segs     = 100, #number of segments
                           bandwidth    = 0.25,
                           red_center   = 1.00,
                           green_center = 0.75,
                           blue_center  = 0.50,
                           name = "gaussianHSV"
                         ):

## jeffs_HSV_colormap_demo.py
from pylab import *
cdict = {
'red'  :  ((0.00, 0.00, 0.00),
           (0.20, 0.00, 0.00),
           (0.40, 0.00, 0.00),
           (0.60, 0.00, 0.00),
           (0.80, 1.00, 1.00),
           (1.00, 1.00, 1.00)),
'green':  ((0.00, 0.00, 0.00),
           (0.20, 0.00, 0.00),

## stuporblue_ndvi.py
################################################################################
# this is code to compute NDVI from Blue (Visible channel) and Red (Infrared)
# such as pictures taken with "SuperBlue" camera
from PIL import Image
import numpy

img = Image.open("IMG_0512.JPG")
imgR, imgG, imgB = img.split() #get channels
#convert to double precision floating point..is this overkill? probably, could try 'float32' or 'float16'
arrR = numpy.asarray(imgR).astype('float64')
	import time, socket



	doc = """
	<!DOCTYPE html>
	<html>
	<head> <title>ESP8266 Pins</title> </head>
	<body> <h1>ESP8266 Pins</h1>
	<table border="1"> <tr><th>Pin</th><th>Value</th></tr> s </table>
	import numpy as np
	import matplotlib

	def make_cmap_guassianHSV( num_segs = 100, #number of segments
	bandwidth = 0.25,
	red_center = 1.00,
	green_center = 0.75,
	blue_center = 0.50,
	name = "gaussianHSV"
	):
	from pylab import *
	cdict = {
	'red' : ((0.00, 0.00, 0.00),
	(0.20, 0.00, 0.00),
	(0.40, 0.00, 0.00),
	(0.60, 0.00, 0.00),
	(0.80, 1.00, 1.00),
	(1.00, 1.00, 1.00)),
	'green': ((0.00, 0.00, 0.00),
	(0.20, 0.00, 0.00),
	################################################################################
	# this is code to compute NDVI from Blue (Visible channel) and Red (Infrared)
	# such as pictures taken with "SuperBlue" camera
	from PIL import Image
	import numpy

	img = Image.open("IMG_0512.JPG")
	imgR, imgG, imgB = img.split() #get channels
	#convert to double precision floating point..is this overkill? probably, could try 'float32' or 'float16'
	arrR = numpy.asarray(imgR).astype('float64')