
__author__ = 'Lothilius'

import csv
import sys
import numpy as np
import matplotlib.pyplot as plt
import skimage as ski
import pylab

from skimage import data, filter
from skimage.color import rgb2gray
from skimage.transform import hough_circle
from skimage.feature import peak_local_max
from skimage.draw import circle_perimeter


#Pull data from CSV file
def arrayFromFile(filename):
    """Given an external file containing numbers,
            create an array from those numbers."""
    dataArray = []
    with open(filename, 'r+') as csvfile:
        spamreader = csv.reader(csvfile, delimiter=',', quotechar='"')
        for row in spamreader:
            dataArray.append(row)
    return dataArray[1565]

#Reduce data to a few peak points
def peaks(data):
    opStack = MyQue.Stack()
    indx = MyQue.Stack()
    i = 0
    last = 0
    lasti = 0
    vlast = 0

    for pixel in data[1565]:
        if len(pixel) == 2:
            pixel = pixel.replace("0.","0")
        if opStack.isEmpty():
            opStack.push(pixel)
            indx.push(i)
            i = i + 1
        elif last > pixel:
            if vlast <= last and last != opStack.peek() and i - indx.peek() <= 3:
                indx.push(lasti)
                opStack.push(last)
                i = i + 1
            else:
                i = i + 1
        elif last < pixel: #and i - indx.peek() >= 10:
            if i - indx.peek() <= 10:
                indx.pop()
                opStack.pop()
                indx.push(i)
                opStack.push(pixel)
                i = i + 1
            else:
                indx.push(i)
                opStack.push(pixel)
                i = i + 1
        else:
            i = i + 1
        last = pixel
        lasti = i
        vlast = last

    thePeaks = [0]*4752
    for i, d in zip(indx, opStack):
        thePeaks[i] = d

    return thePeaks

# Return Radius given two peaks on the same ring
def radius(peakL, peakR):
   rad = (peakR - peakL)
   return rad

#write an array to a file.
def arrayTofile(dataArray, fileNum):
    fileName = "/Users/admin/Dropbox/School/Spring-2014/PHY-474/Labs/Zeeman/play_data/dataManipulation/ImageData"+fileNum+"_a.csv"
    print(fileName)
    with open(fileName, 'w+', newline='') as csvfile:
        linewriter = csv.writer(csvfile, delimiter= ",")
        for each in dataArray:
            linewriter.writerow([each])
    print("done")

#Create file from array with finaldata.csv as the name and append.
def dataTofile(dataArray):
    fileName = "Finaldata2.csv"
    with open(fileName, 'a', newline='') as csvfile:
        linewriter = csv.writer(csvfile, delimiter= ",")
        linewriter.writerow(dataArray)

#Create array of data for creating the Delta enregy function.
def dataArray(peakL1, peakR1, peakL2, peakI, peakO):
    rad1 = radius(peakL1,peakR1) / 2
    halfPoint = peakL1 + rad1
    rad2 = radius(peakL2, halfPoint)
    radI = radius(peakI, halfPoint)
    radO = radius(peakO, halfPoint)
    radArray = [rad1, rad2, radI, radO]
    return radArray

#Ternary Search
def ternarySearch(f, left, right, absolutePrecision):
    #left and right are the current bounds; the maximum is between them
    if (right - left) < absolutePrecision:
        return (left + right)/2

    leftThird = (2*left + right)/3
    rightThird = (left + 2*right)/3

    if f[leftThird] < f[rightThird]:
        return ternarySearch(f, leftThird, right, absolutePrecision)
    else:
        return ternarySearch(f, left, rightThird, absolutePrecision)


#Processes jpg file
def jpg_to_array(file_path, file_name):
    full_path = file_path + file_name
    image = data.load(full_path)
    #plt.imshow(image)
    #plt.show()
    return image

#Remove all but one color
def strip_color(image_rgb1, color_of_interest):
    image_rgb = ski.img_as_float(image_rgb1)

    if color_of_interest == 0:
        colorow = np.array([[1.0, 0, 0]] * len(image_rgb[0]))
    elif color_of_interest == 1:
        colorow = np.array([[0, 1.0, 0]] * len(image_rgb[0]))
    elif color_of_interest == 2:
        colorow = np.array([[0, 0, 1.0]] * len(image_rgb[0]))

    image_proc = np.array([colorow] * len(image_rgb))

    image_proc = image_proc * image_rgb
    image_proc = rgb2gray(image_proc)

    #np.array(image_proc)
    plt.imshow(image_proc)
    plt.show()
    return image_proc

#plot data
def plotevents(datalist):
    x = range(0, len(datalist))
    x = np.array(x)
    y = datalist

    plt.plot(y)
    #fig, ax = plt.subplots()
    #plt.scatter(x,y,s=20, marker='.', c='blue')

    plt.show()
    return "done"


def main():
    file_name = raw_input("Type in file name: ")
    #data = arrayFromFile(inputFileDer+fileNum)
    image = jpg_to_array(inputFileDer, file_name)

    color_of_interest = raw_input("What color is of interest? ")

    if ('Green' in color_of_interest) or ('green' in color_of_interest):
        color_of_interest = 1
        image = strip_color(image, color_of_interest)
        plotevents(image[1622])
        print('The red and blue have been stripped from image.')


    peakL1 = int(raw_input("Type in potential n peak pixel bin: "))
    peakPrec = int(raw_input("Type in precision: "))
    peakL1 = ternarySearch(data, peakL1-15, peakL1+15, peakPrec)
    print(peakL1)


main()
@@ -4243,28 +4243,89 @@
     
-#np.array(image_proc
+rings = ski.filter.sobel(image_proc)%0A%0A    img = get_radius(image_proc, image_rgb1
 )%0A  
@@ -4339,25 +4339,19 @@
 mshow(im
-age_proc)
+g)%0A
 %0A    plt

Include call to edge detector function