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csv_plotter v4.py
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csv_plotter v4.py
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from re import X
from turtle import color, width
import matplotlib.pyplot as plt
import csv
from matplotlib.patches import Ellipse, Rectangle
import numpy as np
def readCSV (path):
data = []
header = [] # removes first line of file
filename = path
with open(filename) as csvfile:
csvreader = csv.reader(csvfile)
header = next(csvreader) # removes first line of file
for datapoint in csvreader:
values = [float(value) for value in datapoint]
data.append(values)
return data
def magnitudeBode(dataList, dataLabel,col, col2=-1):
#Figure size (x,y) in inches. Move Legend if changed drasticly to avoid clipping
fig = plt.figure(1, figsize=(14.5, 6.5))
#number of rows/cols of subplots
ax = fig.add_subplot(1, 1, 1)
#plt.minorticks_on()
#max num ticks in axis
max_yticks = 15
max_xticks = 10 #irrelevant due to log scale
yloc = plt.MaxNLocator(max_yticks)
xloc = plt.MaxNLocator(max_xticks)
ax.yaxis.set_major_locator(yloc)
ax.xaxis.set_major_locator(xloc)
ax.tick_params(which='major', length=8)
ax.tick_params(which='minor', length=6)
ax.tick_params(which='both', width=1)
#ax.yaxis.set_minor_locator(AutoMinorLocator())
#Use log scale
#ax.set_xscale('log')
# ax.set_yscale('log')
#plt.title('Bode diagram demping')
plt.grid(True)
#ax.xaxis.minorTicks()
ax.xaxis.grid(b=True, which='minor', linestyle=(0, (1,3)))
#plot data
for i in range (0,len(dataList)):
time = [p[0] for p in dataList[i]]
if col2!=-1:
trace1 = [p[col2] for p in dataList[i]]
plt.plot(time, trace1, "-")
trace1 = [p[col] for p in dataList[i]]
plt.plot(time, trace1, "-", alpha=0.8,label = dataLabel[i])
#labels
plt.xlabel("Frekvens [Hz]")
plt.ylabel("Demping [dB]")
#Final touch
# ellipse = Ellipse(xy=(580, -24), width=900, height=10,
# edgecolor='r', fc='None', lw=2)
# ax.add_patch(ellipse)
#ypoints = [(0,580),(-44,580)]
#plt.plot(ypoints, linestyle = 'dotted')
plt.axvline(x=5650, ymin=-0.95, ymax=0.95, linestyle = (0,(5,1)), color = 'tab:orange',label='$f_0 = 5650$ Hz')
plt.axvline(x=11300, ymin=-0.95, ymax=0.95, linestyle = (0,(5,1)), color = 'tab:green',label='$f_1 = 11300$ Hz')
plt.axvline(x=16950, ymin=-0.95, ymax=0.95, linestyle = (0,(5,1)), color = 'tab:red',label='$f_2 = 16950$ Hz')
#legend. Source: https://stackoverflow.com/questions/4700614/how-to-put-the-legend-outside-the-plot-in-matplotlib
plt.legend(bbox_to_anchor=(0.5, -0.15), loc="upper center",fancybox=True, ncol=8, borderaxespad=0)
plt.tight_layout(rect=[0,0,1,0.98])
plt.show()
def magnitudeSpektrum(dataList, dataLabel,col, col2=-1):
#Figure size (x,y) in inches. Move Legend if changed drasticly to avoid clipping
fig = plt.figure(1, figsize=(14.5, 6.5))
#number of rows/cols of subplots
ax = fig.add_subplot(1, 1, 1)
#max num ticks in axis
max_yticks = 20
max_xticks = 10 #irrelevant due to log scale
yloc = plt.MaxNLocator(max_yticks)
xloc = plt.MaxNLocator(max_xticks)
ax.yaxis.set_major_locator(yloc)
ax.xaxis.set_major_locator(xloc)
#Use log scale
#ax.set_xscale('log')
#ax.set_yscale('log')
#plot data
time = [p[0] for p in dataList[0]]
trace1 = [p[col] for p in dataList[0]]
plt.plot(time, trace1, "-", alpha=1)
#plt.plot(time, trace1, "-", alpha=0.8)
print (len(dataList))
for i in range (2,len(dataList)):
if col2!=-1 :
trace1 = [p[col2] for p in dataList[i]]
plt.plot(time, trace1, "-", alpha=1)
#plt.plot(time, trace1, "-")
#labels
plt.xlabel("Frekvens [Hz]")
plt.ylabel(r"Magnitude (Peak Hold Cont.) [dB$\tilde{V}$]")
#legend. Source: https://stackoverflow.com/questions/4700614/how-to-put-the-legend-outside-the-plot-in-matplotlib
plt.legend(dataLabel, bbox_to_anchor=(0.5, -0.15), loc="upper center",fancybox=True, ncol=8, borderaxespad=0)
plt.tight_layout(rect=[0,0,1,0.98])
#ellipse = Ellipse(xy=(580, -24), width=900, height=10, edgecolor='r', fc='None', lw=2)
#ax.add_patch(ellipse)
#add rectangle
# plt.gca().add_patch(Rectangle((250,-100),1000,80,edgecolor='red',facecolor='none',lw=2))
#Final touch
#plt.title('Spektrum diagram')
plt.grid(True)
plt.show()
def phase(dataList, dataLabel,col):
#Figure size (x,y) in inches. Move Legend if changed drasticly
fig = plt.figure(1, figsize=(14.5, 6.5))
#number of rows/cols of subplots
ax = fig.add_subplot(1, 1, 1)
#max num ticks in axis
max_yticks = 20
max_xticks = 20 #irrelevant due to log scale
yloc = plt.MaxNLocator(max_yticks)
xloc = plt.MaxNLocator(max_xticks)
ax.yaxis.set_major_locator(yloc)
ax.xaxis.set_major_locator(xloc)
#Use log scale
ax.set_xscale('log')
# ax.set_yscale('log')
#plot data
for i in range (0,len(dataList)):
time = [p[0] for p in dataList[i]]
measurement = [p[col] for p in dataList[i]]
plt.plot(time, measurement, "-")
#labels
plt.xlabel("Frekvens [Hz]")
plt.ylabel("Fase [grader]")
#Legend
plt.legend(dataLabel, bbox_to_anchor=(0.5, -0.1), loc="upper center",fancybox=True, ncol=8, borderaxespad=0)
plt.tight_layout(rect=[0,0,1,0.98])
#Final touch
plt.grid(True)
plt.title('Bode diagram fase')
plt.show()
def bodeDiagram(fileList,dataLabel):
if len(fileList)!=len(dataLabel):
print("\n\nMissing labels for grafs\n\n")
dataList= []
for i in range (0,len(fileList)):
dataList.append(readCSV(fileList[i]))
magnitudeBode(dataList, dataLabel,2)
phase(dataList, dataLabel,3)
def spektrumDiagram(fileList,dataLabel):
if len(fileList)!=len(dataLabel):
print("\n\nMissing labels for grafs\n\n")
dataList= []
for i in range (0,len(fileList)):
dataList.append(readCSV(fileList[i]))
magnitudeSpektrum(dataList, dataLabel,1,1)
# xyPlot(dataList, dataLabel,1,3)
def xyPlot(dataList, dataLabel,col, col2=-1):
#Figure size (x,y) in inches. Move Legend if changed drasticly to avoid clipping
fig = plt.figure(1, figsize=(7, 6.5))
#number of rows/cols of subplots
ax = fig.add_subplot(1, 1, 1)
#max num ticks in axis
max_yticks = 20
max_xticks = 10 #irrelevant due to log scale
yloc = plt.MaxNLocator(max_yticks)
xloc = plt.MaxNLocator(max_xticks)
ax.yaxis.set_major_locator(yloc)
ax.xaxis.set_major_locator(xloc)
#Use log scale
#ax.set_xscale('log')
#ax.set_yscale('log')
#plot data
# time = [p[0] for p in dataList[0]]
# trace1 = [p[1] for p in dataList[0]]
# trace2 = [p[2] for p in dataList[0]]
# plt.plot(trace2, trace1, ".", alpha=1)
#plt.plot(time, trace1, "-", alpha=0.8)
for i in range (0,len(dataList)):
if col2!=-1:
trace1 = [p[1]*1000 for p in dataList[i]]
trace2 = [p[2] for p in dataList[i]]
plt.plot(trace1, trace2, ".", alpha=0.7)
#plt.plot(time, trace1, "-")
#labels
plt.xlabel("y(t) [mV]")
plt.ylabel("Spolespenning [V]")
#legend. Source: https://stackoverflow.com/questions/4700614/how-to-put-the-legend-outside-the-plot-in-matplotlib
plt.legend(dataLabel, bbox_to_anchor=(0.5, -0.15), loc="upper center",fancybox=True, ncol=3, borderaxespad=0)
plt.tight_layout(rect=[0,0,1,0.98])
#ellipse = Ellipse(xy=(580, -24), width=900, height=10, edgecolor='r', fc='None', lw=2)
#ax.add_patch(ellipse)
#add rectangle
# plt.gca().add_patch(Rectangle((250,-100),1000,80,edgecolor='red',facecolor='none',lw=2))
#Final touch
#plt.title('Spektrum diagram')
plt.grid(True)
plt.show()
def faseDiagram(fileList,dataLabel):
if len(fileList)!=len(dataLabel):
print("\n\nMissing labels for grafs\n\n")
dataList= []
for i in range (0,len(fileList)):
dataList.append(readCSV(fileList[i]))
xyPlot(dataList, dataLabel,1,2)
#phase(dataList, dataLabel,2)
plt.rcParams.update({'font.size': 16})
dataLabel = ["C = 3.938 nF","C = 3.127 nF"]
bodefiles = ["D4 bode 3.9nF.csv","D4 bode 3.1nF.csv"]
# bodeDiagram(bodefiles, dataLabel)
spektrumFiles = ["D4 spektrum Peak hold 35 kHz R=.7.csv","D4 spektrum Peak hold 35 kHz R=.7.csv","D4 spektrum Peak hold 35 kHz R=304.csv","D4 spektrum Peak hold 35 kHz R=718.csv","D4 spektrum Peak hold 35 kHz R=5k.csv","D4 spektrum Peak hold 35 kHz R=10.2k.csv"]
dataLabel = ["$R_2$ = 0,7$\Omega$","$R_2$ = 304$\Omega$","$R_2$ = 718$\Omega$","$R_2$ = 5k$\Omega$","$R_2$ = 10,2k$\Omega$"]
# spektrumDiagram(spektrumFiles,dataLabel)
faseFiles= ["D4 skop R=.7.csv","D4 skop R=304.csv","D4 skop R=718.csv","D4 skop R=5k.csv","D4 skop R=10.2k.csv"]
dataLabel.reverse()
faseFiles.reverse()
faseDiagram(faseFiles,dataLabel)