Download and run the attached program. For input you can use the temperature data files provided previously. When the program runs it puts up a window. Click the Browse button and open a temperature data file to plot. The purple curve is a smoothed version of the daily data points. The smoothing can be changed by entering a different number into the smoothing box and clicking the Plot button. The sensitivity of the peak finding can be changed by changing the Peak size and clicking Plot.

The program contains a function named find_local_min_max(y, delta) that finds the peaks/valleys. Write a new function named find_local_min_max2(y, delta) that counts a point as a peak if it is bigger than the points within delta distance before or after it. If delta = 2, the y[9] is a peak if it is bigger than y[8]m y[7], y[10] and y[11]. Use a similar strategy to find valleys. Think about how to handle points near the beginning and end of the data. Can you think of any flaws with this peak/valley algorithm. Write a version of the program that replaces the call to the original peak/valley finder with a call to your function. Run both programs and compare the results.

ATTACHED PROGRAM BELOW

Created on Thu Oct 13 08:31:01 2016

Reads temperarure data from input text file,

plots raw data, smoothed data and uses hysteresis based method

to find local temperature min/max.

@author: rutkowsk

"""

from tkinter import *

from tkinter.filedialog import *

#import numpy as np

import matplotlib

matplotlib.use('TkAgg')

from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2TkAgg

import matplotlib.pyplot as plt

#================================================================

# smooth data by averaging with neighbor points

def smooth(x):

y = []

y.append((x[0] + x[1])/2)

for i in range(1,len(x) - 1):

y.append((x[i-1] + x[i] + x[i+1])/3)

y.append((x[-1] + x[-2])/2)

return y

#================================================================

# find peaks using hysteresis

def find_local_min_max(y, delta):

y_lo = y[0] - delta

y_hi = y[0] + delta

hi_list = []

lo_list = []

direction = None

for i in range(len(y)):

if y[i] > y_hi:

y_hi = y[i]

y_lo = y_hi - 2*delta

if direction == 'down':

lo_list.append(i_last)

direction = 'up'

i_last = i

elif y[i] < y_lo:

y_lo = y[i]

y_hi = y_lo + 2*delta

if direction == 'up':

hi_list.append(i_last)

direction = 'down'

i_last = i

return lo_list, hi_list

#================================================================

# get input data from file

def get_data(fname):

f_in = open(fname, "r")

temp = []

prev_temp = 0

for s in f_in.readlines():

curr_temp = float(s.split()[3])

if curr_temp > -99: # fix -99 missing data marker

prev_temp = curr_temp

else:

curr_temp = prev_temp

temp.append(curr_temp)

return temp

#================================================================

# set plot parameters

def set_plot_params(plt):

#plt.ion() # interactive mode on

plt.rcParams["figure.figsize"] = (14, 7)

plt.rcParams['axes.facecolor'] = 'ivory'

plt.rcParams['figure.facecolor'] = 'powderblue'

plt.rcParams['figure.titlesize'] = 'large'

#================================================================

# plot raw data, smoothed data, peaks/valleys

def plot_data(x, y, hyst, smooth_count):

plt.clf()

plt.xlim(0, len(y) - 1)

plt.title(inputFileName.get())

plt.xlabel("Day Number")

plt.ylabel("Temperature Degrees F")

#--------------------------------------------

# plot original data

plt.plot(x, y, color='g', label='Raw Data')

#--------------------------------------------

# find/plot peaks/valleys

lo_plist, hi_plist = find_local_min_max(y, hyst)

peaky = [y[i] for i in hi_plist] # local highs

plt.plot(hi_plist, peaky, 'rs', label='Local Highs')

peaky = [y[i] for i in lo_plist] # local lows

plt.plot(lo_plist, peaky, 'bs', label='Local Lows')

#--------------------------------------------

# smooth data

s2 = smooth(y) # smooth data

for i in range(smooth_count):

s2 = smooth(s2)

plt.plot(x, s2, color='m', label ='Smoothed Data', linewidth = 3.0)

#--------------------------------------------

# setup the legend

plt.legend();

legend = plt.legend()

fr = legend.get_frame()

fr.set_facecolor('wheat')

fr.set_edgecolor('black')

#plt.show()

canvas.show()

#================================================================

# GUI

#================================================================

root = Tk()

root.title('Simple Plot')

# a tk.DrawingArea

set_plot_params(plt)

canvas = FigureCanvasTkAgg(plt.figure(), master=root)

canvas.show()

canvas.get_tk_widget().pack(side=TOP, fill=BOTH, expand=1)

# data file

row = Frame(root)

row.pack(side=TOP, fill=X, padx=5, pady=5)

Label(row, text = 'Input File').pack(side=LEFT, expand=NO, fill=X, padx=15)

inputFileName = StringVar()

Entry(row, textvariable = inputFileName).pack(side=LEFT, expand=YES, fill=X, padx=15)

# event handler

def browseInput():

inputFileName.set(askopenfilename(title="Select input file", filetypes=[("*.TXT", "*.txt")]))

temp = get_data(inputFileName.get())

plot_data(range(len(temp)), temp, hyster.get(), smooth_iter.get())

#canvas.show()

# browse input button

Button(row, fg ="blue" , text = "Browse", width = 10, command = browseInput).pack(side=LEFT, expand=NO, fill=X, padx=15)

# smoothing/peak finding parameters

row = Frame(root)

row.pack(side=TOP, fill=X, padx=5, pady=5)

Label(row, text = 'Smoothing').pack(side=LEFT, expand=NO, fill=X, padx=15)

smooth_iter = IntVar()

smooth_iter.set(100)

Entry(row, textvariable = smooth_iter).pack(side=LEFT, expand=YES, fill=X, padx=15)

Label(row, text = 'Peak Size').pack(side=LEFT, expand=NO, fill=X, padx=15)

hyster = DoubleVar()

hyster.set(5.0)

Entry(row, textvariable = hyster).pack(side=LEFT, expand=YES, fill=X, padx=15)

# event handler

def new_plot():

temp = get_data(inputFileName.get())

plot_data(range(len(temp)), temp, hyster.get(), smooth_iter.get())

#canvas.show()

# plot button

Button(row, fg ="blue" , text = "Plot", width = 10, command = new_plot).pack(side=LEFT, expand=NO, fill=X, padx=15)

#set_plot_params()

root.mainloop()