def plot(self, precision=1, title=False, saving=False):
"""
Displays the data from the CSV file as a graph.
:param precision: Allows to take only a part of the data in the file. This value MUST BE positive
:type precision: int
:param title: Know of the plot must have a title or not
:type title: bool
:return: Create a plot
"""
# Create the arguments of plotSignals function (see plotsTest.py > plotSignal)
x, signals = self.makeSignals(precision)[:-2]
x_axis_name = self.getAxisNames()[0] + " [" + self.getAxisUnits(
)[0] + "]"
y_axis_name = self.getAxisNames()[1] + " [" + self.getAxisUnits(
)[1] + "]"
# Use of plot function
plot_signals(x,
signals,
self.getSignalsNames(),
x_label=x_axis_name,
y_label=y_axis_name,
title=title,
saving=saving)
def compareSignals(self, *args, title=False, saving=False):
"""
:param args:
:type args: Signal
:return:
"""
signals_names = [self.getName()]
signals = [self.getY()]
for arg in args:
if len(arg.getY()) == len(self.getX()):
signals_names.append(arg.getName())
signals.append(arg.getY())
else:
msg = "Signal {} have not a length of {}, comparaison can not be done. This signal is ignored". \
format(arg.getName(), len(self.getX()))
print(warningText(msg))
continue
plot_signals(self.getX(), signals, signals_names, x_label=self.getAxisLabels()[0],
y_label=self.getAxisLabels()[1], title=title, saving=saving)
def autoCompareSignal(self):
msg = "An equation and a value of y have been given. Here is the comparison of the 2."
plot_signals(self.getX(), [self.getY(), self.getF(self.getX())], ['Y list', 'Function'],
x_label=self.getAxisLabels()[0], y_label=self.getAxisLabels()[1])
print(warningText(msg))
def plot(self, title=False, saving=False):
plot_signals(self.getX(), [self.getY()], [self.getName()], x_label=self.getAxisLabels()[0],
y_label=self.getAxisLabels()[1], title=title, saving=saving)
import numpy as np
from main.model.functions import *
from main.plots import plot_signals
if __name__ == '__main__':
# Détection
VL = detection_b_const(time, -1 / 4, 100)
VL_list = []
VL_list.append(VL[0])
plot_signals(time,
VL_list, ['$V_L$'],
x_label="Temps [s]",
y_label="Tension [mV]")
# Amplificateur
VL = VL[0] / 1000
VAMP = amplification(time, VL)
plot_signals(time,
VAMP, ['$V_{amp}$', '$V_L$'],
x_label="Temps [ms]",
y_label="Tension [V]")
sin1 = lambda t: 0.2 * np.sin(20 * t)
VAMP_bis = amplification(time, sin1(time))
plot_signals(time,
VAMP_bis, ['$V_{amp}$', '$V_L$'],
x_label="Temps [ms]",
y_label="Tension [V]")
# Filter
VF = filter(np.linspace(0, 0.1, steps),