graphing.py

"""

Creates a historgram for (a) given pixel(s) gradient magnitude taking the pixel location, the temp threshold to skip anything below and the bin resolution

"""
import numpy as np
import matplotlib.pyplot as plt
import math


def plotHistogram(temp_file, pixel, threshold=200, binCount=5, spacing=1):
    temp_data = np.load(temp_file, allow_pickle=True)

    frame_count = temp_data.shape[0]
    pixel_grad_mag = []
    pixel_grad_dir = []

    for i in range(frame_count):
        temp = temp_data[i].copy()
        gradientx, gradienty = np.gradient(temp, spacing)
        if temp[pixel] > threshold:
            pixel_grad_mag.append(
                math.sqrt((gradientx[pixel]**2) + (gradienty[pixel]**2)))
            if gradientx[pixel] == 0:
                if gradienty[pixel] > 0:
                    pixel_grad_dir.append(90)
                elif gradienty[pixel] < 0:
                    pixel_grad_dir.append(-90)
                else:
                    pixel_grad_dir.append(0)
            else:
                pixel_grad_dir.append(
                    (180 / math.pi) *
                    math.atan(gradienty[pixel] / gradientx[pixel]))

    n, bins, patches = plt.hist(pixel_grad_dir,
                                binCount,
                                facecolor='blue',
                                alpha=.5)
    plt.xlabel('Gradient Angle')
    plt.ylabel('Frequency')
    plt.show()


def plotLine(temp_file, pixel, startFrame: int, endFrame: int):
    temp_data = np.load(temp_file, allow_pickle=True)
    if endFrame is -1:
        endFrame = temp_data.shape[0] - 1

    frame = np.arange(int(startFrame), int(endFrame))
    pixelTempHistory = temp_data[frame, int(pixel[0]), int(pixel[1])]

    plt.plot(frame, pixelTempHistory)
    plt.show()