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add plotting scripts for continous data

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juliangaal 2019-04-23 21:29:58 +02:00
parent b59fff66d9
commit cbf974f6f8
2 changed files with 139 additions and 0 deletions
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59
viz/plot.py Normal file
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#!/usr/bin/env python3
import sys
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
def plot(filename: str, filename_2: str, num_data_points: int):
df_1 = pd.read_csv(filename, delimiter = ',', names=['roll', 'pitch'])
df_2 = pd.read_csv(filename_2, delimiter = ',', names=['roll', 'pitch'])
n = num_data_points
y = df_1['roll'].to_list()
x = np.linspace(0, n, n)
plt.plot(x, y[:n], label='roll raw: var ' + str(np.var(y)), color='black')
var_1 = np.var(y)
y = df_2['roll'].to_list()
x = np.linspace(0, n, n)
plt.plot(x, y[:n], label='roll calibrated: var ' + str(np.var(y)), color='red')
var_2 = np.var(y)
plt.ylim([-0.1, 0.1])
plt.legend()
plt.show()
if var_1 < var_2:
print("Variance of {} is smaller: {}".format(filename, var_1))
else:
print("Variance of {} is smaller: {}".format(filename_2, var_2))
y = df_1['pitch'].to_list()
x = np.linspace(0, n, n)
plt.plot(x, y[:n], label='pitch raw: var ' + str(np.var(y)), color='black')
var_1 = np.var(y)
y = df_2['pitch'].to_list()
x = np.linspace(0, n, n)
plt.plot(x, y[:n], label='pitch calibrated: var ' + str(np.var(y)), color='red')
var_2 = np.var(y)
plt.ylim([-0.1, 0.1])
plt.legend()
plt.show()
if var_1 < var_2:
print("Variance of {} is smaller: {}".format(filename, var_1))
else:
print("Variance of {} is smaller: {}".format(filename_2, var_2))
file_1 = sys.argv[1]
file_1 = sys.argv[1]
file_2 = sys.argv[2]
n = int(sys.argv[3])
plot(file_1, file_2, n)

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viz/plot_rot.py Normal file
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#!/usr/bin/env python3
import sys
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
def plot(filename: str, filename_2: str, num_data_points: int):
df_1 = pd.read_csv(filename, delimiter = ',', names=['x', 'y', 'z'])
df_2 = pd.read_csv(filename_2, delimiter = ',', names=['x', 'y', 'z'])
n = num_data_points
y = df_1['x'].to_list()
x = np.linspace(0, n, n)
plt.plot(x, y[:n], label='x raw: var ' + str(np.var(y)), color='black')
var_1 = np.var(y)
y = df_2['x'].to_list()
x = np.linspace(0, n, n)
plt.plot(x, y[:n], label='x calib: var ' + str(np.var(y)), color='red')
var_2 = np.var(y)
plt.ylim([-0.1, 0.1])
plt.legend()
plt.show()
if var_1 < var_2:
print("Variance of {} is smaller: {}".format(filename, var_1))
else:
print("Variance of {} is smaller: {}".format(filename_2, var_2))
y = df_1['y'].to_list()
x = np.linspace(0, n, n)
plt.plot(x, y[:n], label='y raw: var ' + str(np.var(y)), color='black')
var_1 = np.var(y)
y = df_2['y'].to_list()
x = np.linspace(0, n, n)
plt.plot(x, y[:n], label='y calib: var ' + str(np.var(y)), color='red')
var_2 = np.var(y)
plt.ylim([-0.1, 0.1])
plt.legend()
plt.show()
if var_1 < var_2:
print("Variance of {} is smaller: {}".format(filename, var_1))
else:
print("Variance of {} is smaller: {}".format(filename_2, var_2))
y = df_1['z'].to_list()
x = np.linspace(0, n, n)
plt.plot(x, y[:n], label='z raw: var ' + str(np.var(y)), color='black')
var_1 = np.var(y)
y = df_2['z'].to_list()
x = np.linspace(0, n, n)
plt.plot(x, y[:n], label='z calib: var ' + str(np.var(y)), color='red')
var_2 = np.var(y)
plt.ylim([-0.1, 0.1])
plt.legend()
plt.show()
if var_1 < var_2:
print("Variance of {} is smaller: {}".format(filename, var_1))
else:
print("Variance of {} is smaller: {}".format(filename_2, var_2))
file_1 = sys.argv[1]
file_1 = sys.argv[1]
file_1 = sys.argv[1]
file_2 = sys.argv[2]
n = int(sys.argv[3])
plot(file_1, file_2, n)