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6 Commits
dev ... main

Author SHA1 Message Date
matthias@arch
6ab6aba43b fix name 2023-08-30 18:36:25 +02:00
matthias@arch
6a8c05eec0 fix backend section 2023-08-30 18:35:20 +02:00
matthias@arch
8621a18169 updated readme 2023-08-30 18:06:34 +02:00
matthias@arch
d479830a76 fix pip installation 2023-08-17 10:54:09 +02:00
matthias@arch
849730be09 Merge remote-tracking branch 'origin/dev' 2023-08-17 01:29:54 +02:00
matthias@arch
a672ab3dc2 merge 2023-08-17 01:19:03 +02:00
5 changed files with 45 additions and 28 deletions

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@ -1,2 +0,0 @@
include regina/package-data/*
include regina/sql/*.sql

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@ -66,7 +66,7 @@ from m_teng.utility.data import load_dataframe
from m_teng.utility import file_io
from m_teng.update_funcs import _Monitor, _ModelPredict, _update_print
config_path = path.expanduser("~/.config/k-teng.json")
config_path = path.expanduser("~/.config/m-teng.json")
_runtime_vars = {
"last-measurement": ""
@ -75,7 +75,7 @@ _runtime_vars = {
settings = {
"datadir": path.expanduser("~/data"),
"name": "measurement",
"interval": 0.05,
"interval": 0.02,
"beep": True,
}

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@ -1,12 +1,13 @@
import pandas as pd
import numpy as np
from os import path
import matplotlib.pyplot
import matplotlib.pyplot as plt
def buffer2dataframe(buffer):
df = pd.DataFrame(buffer)
df.colums = ["Time [s]", "Voltage [V]"]
return df
# deprecated
# def buffer2dataframe(buffer):
# df = pd.DataFrame(buffer)
# df.colums = ["Time [s]", "Voltage [V]"]
# return df
def buffers2dataframe(ibuffer, vbuffer):
"""
@ -32,22 +33,37 @@ def load_dataframe(p:str):
df = pd.read_pickle(p)
return df
def plot(data):
def plot(data: str or pd.DataFrame or np.ndarray, title="", U=True, I=False):
"""
Plot recorded data
@param data: filepath, dataframe or numpy array
"""
if type(data) == str:
data = load_dataframe(data)
if type(data) == pd.Dataframe:
data = data.to_numpy()
fig1, (vax, iax) = plt.subplots(2, 1, figsize=(8, 5))
# todo
_data = load_dataframe(data).to_numpy()
elif type(data) == pd.DataFrame:
_data = data.to_numpy()
else:
_data = data
print(_data[0])
plt.ion()
fig, ax = plt.subplots()
ax.set_xlabel("t [s]")
vax = ax
iax = ax
if U and I:
iax = ax.twinx()
if U:
vax = ax
vax.set_ylabel("U [V]")
vax.plot(_data[:,0], _data[:,2], color="blue", label="voltage")
if I:
iax.set_ylabel("I [A]")
iax.plot(_data[:,0], _data[:,1], color="orange", label="current")
if U and I:
plt.legend()
return fig
vline, = vax.plot(index, vdata, color="m")
vax.set_ylabel("Voltage [V]")
vax.grid(True)
vax.plot()
iline, = iax.plot(index, idata, color="m")
iax.set_ylabel("Current [A]")
iax.grid(True)

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@ -20,6 +20,7 @@ classifiers = [
dependencies = [
"matplotlib>=3.6",
"numpy",
"pandas",
]
[project.optional-dependencies]

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@ -1,6 +1,8 @@
# m-TENG
Helper scripts and shell for measuring **T**ribo**e**lectric **N**ano**g**enerator-based sensor output with a Keithley 2600B SMU or an Arduino
This project was written for my bachelor's thesis.
## Features
### Interactive (shell) mode
@ -33,7 +35,7 @@ Helper scripts and shell for measuring **T**ribo**e**lectric **N**ano**g**enerat
## Shell mode
It is recommended to run the shell with ipython:
```shell
ipython -i k_teng_interactive.py -- -*X*
ipython -i m_teng_interactive.py -- -*X*
```
Substitute *X* for `-k` for keithley backend, `-a` for arduino backend or `-t` for testing backend.