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Aggiunto lettura di più misure I,V per ogni riga di logger

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ddnthemc 2025-04-04 17:40:13 +02:00
parent 0dfeb02c83
commit de9f6d96fb
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176
load_data_from_multiple.py Normal file
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@ -0,0 +1,176 @@
#!/usr/bin/python
# -*- coding: utf-8 -*-
from openpyxl import load_workbook
from pathlib import Path
from my_folders import source_file_folder
from dataclasses import dataclass, asdict
import matplotlib.pyplot as plt
from itertools import islice
def batched(iterable, batch_size):
it = iter(iterable)
while _batch := list(islice(it, batch_size)):
yield _batch
@dataclass(frozen=True)
class Measure:
ts: float # time stamp
v: float
i: float
@dataclass
class RawMeasure:
ts: int
ch: int
v: float
@dataclass(frozen=True)
class DischargePoint(Measure):
c: float # Capacity
column_indexes = { # columns indexes that we want to import: None means try to find the column
'TimeStamp': 0,
'Ibatt': None,
'Vbatt': None,
}
def available_measurements(s_in: str):
"""
generates the series of RawMeasure contained in the s_in string
:param s_in:
:return:
"""
fields = s_in.strip().strip('\n').replace('VDC1', 'VDC 1').split()
for ts, ch, chn, value, unit in batched(fields, 5):
if ch != 'Ch' or not unit.endswith('DC'):
continue
yield RawMeasure(ts=int(ts), ch=int(chn), v=float(value))
def load_a_txt_file(path: Path, duts: dict[str, tuple[int, int]]) -> dict[str, list[Measure]]:
"""Returns a sorted list of Measures()"""
# 1742542808 Ch 101 4.6694100e-03 VDC 1742542808 Ch 102 3.6288222e+00 VDC
# 1742542838 Ch 101 4.6651780e-03 VDC 1742542838 Ch 102 3.6315371e+00 VDC
# 1743758985 Ch 101 2.2117630e-03 VDC 1743758985 Ch 102 2.9622319e+00 VDC1743758985 Ch 103 1.9700000e-03 VDC 1743758985 Ch 104 3.0066588e+00 VDC
# 1743759015 Ch 101 2.1362400e-03 VDC 1743759015 Ch 102 3.0225466e+00 VDC1743759015 Ch 103 1.9600170e-03 VDC 1743759015 Ch 104 3.0766279e+00 VDC
# 1743759046 Ch 101 2.1291870e-03 VDC 1743759046 Ch 102 3.0660180e+00 VDC1743759046 Ch 103 1.9516620e-03 VDC 1743759046 Ch 104 3.1234983e+00 VDC
# 1743759076 Ch 101 2.1232190e-03 VDC 1743759076 Ch 102 3.1013554e+00 VDC1743759076 Ch 103 1.9452600e-03 VDC 1743759076 Ch 104 3.1604323e+00 VDC
# 1743759106 Ch 101 2.1214820e-03 VDC 1743759106 Ch 102 3.1316431e+00 VDC1743759106 Ch 103 1.9383150e-03 VDC 1743759106 Ch 104 3.1913389e+00 VDC
# 0 1 2 3 4 5 6 7 8 9
discharges = {k: [] for k in duts.keys()}
with open(path, 'r') as fin:
for raw_line in fin:
if len(raw_line) < 10: # arbitrario per rimuovere linee sicuramente sbagliate
continue
if 'slv' in raw_line.lower():
continue
fields = raw_line.strip().strip('\n').split()
if len(fields) < 10:
continue # remove malformed lines
measures = {m.ch: m for m in available_measurements(raw_line)}
for dut, dsch_ptis in discharges.items():
chi, chv = duts[dut]
i = measures[chi]
v = measures[chv]
dsch_ptis.append(Measure(ts=i.ts, i=i.v / 0.010007, v=v.v))
for disc in discharges.values():
disc.sort(key=lambda x: x.ts)
return discharges
def compute_discharge(measures: list[Measure], initial_capacity: float = 0.0) -> list[DischargePoint]:
discharge_sequence = []
last_m = None
t0 = None
for m in measures:
if t0 is None:
t0 = m.ts
if last_m is not None:
initial_capacity += (m.i + last_m.i) * 0.5 * (m.ts - last_m.ts) / 3600.0
meas = asdict(m)
meas['ts'] -= t0
discharge_sequence.append(DischargePoint(c=initial_capacity, **meas))
last_m = m
return discharge_sequence
def show_a_discharge(discharge: list[DischargePoint], title='Title'):
out_name = f'{title}.png'
if '100_per' in title:
title = 'Battery Option: 100%'
elif '80_per' in title:
title = 'Battery Option: 80%'
else:
title = f'Battery Option: OFF ({title})'
how_many = 1
fig, axs_maybe = plt.subplots(how_many, 1, tight_layout=False, figsize=(7.85, 5.38))
# fig.suptitle(f'Recahrging Behavior', fontsize=20)
# fig, ax = plt.subplots(figsize=(11, 6))
if how_many == 1:
axs = (axs_maybe,)
else:
axs = axs_maybe
ax = axs[0]
ax.grid(True)
axr = ax.twinx()
# ax.set_xlim(0.0, 125)
mins = []
vbatt = []
ibatt = []
caps = []
for dp in discharge:
mins.append(dp.ts/60.0)
vbatt.append(dp.v)
ibatt.append(dp.i * 1000.0)
caps.append(dp.c * 1000.0)
ax.plot(mins, vbatt, color='g', lw=3, alpha=0.5, label='Battery Voltage')
axr.plot(mins, caps, color='b', lw=3, alpha=0.5, label='Accumulated Capacity')
axr.plot(mins, ibatt, color='r', lw=3, alpha=0.5, label='Charging Current')
ax.set_xlim(0, None)
ax.set_ylim(3.0, 4.3)
axr.set_ylim(0, None)
axr.set_ylabel('Capacity [mAh] / Current [mA]')
ax.set_xlabel('time [minutes]')
ax.set_ylabel('Cell Voltage [V]')
ax.set_title(title)
axr.legend(loc='center right')
ax.legend(loc='upper left')
txt = f'Total Capacity: {caps[-1]:.1f} mAh'
print(txt)
axr.text(mins[-1], caps[-1] - 150, txt, ha='right', fontsize=10, bbox={'facecolor': 'cyan', 'alpha': 0.7, 'pad': 5})
# fig.tight_layout()
fig.savefig(out_name, dpi=300)
plt.close()
DUTS = {
'SLV15': (101, 102),
'SLV19': (103, 104),
}
if __name__ == '__main__':
for f in source_file_folder.iterdir():
if f.stem != 'log_2025_04_04_09':
continue
if f.is_file():
if f.suffix.lower() == '.xlsx':
print('skipping ', f)
elif f.suffix.lower() == '.txt':
print(f)
measured_data = load_a_txt_file(f, DUTS)
# print(measured_data)
else:
continue
for name, discharge_points in measured_data.items():
discharge = compute_discharge(discharge_points)
stem_under = f.stem.replace(' ', '_')
show_a_discharge(discharge, title=f'{name}_{stem_under}')

63
load_data_from_xlsx.py
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@ -5,6 +5,12 @@ from pathlib import Path
from my_folders import source_file_folder
from dataclasses import dataclass, asdict
import matplotlib.pyplot as plt
from itertools import islice
def batched(iterable, batch_size):
it = iter(iterable)
while _batch := list(islice(it, batch_size)):
yield _batch
@dataclass(frozen=True)
@ -14,6 +20,13 @@ class Measure:
i: float
@dataclass
class RawMeasure:
ts: int
ch: int
v: float
@dataclass(frozen=True)
class DischargePoint(Measure):
c: float # Capacity
@ -66,12 +79,60 @@ def load_a_txt_file(path: Path) -> list[Measure]:
# 1742542808 Ch 101 4.6694100e-03 VDC 1742542808 Ch 102 3.6288222e+00 VDC
# 1742542838 Ch 101 4.6651780e-03 VDC 1742542838 Ch 102 3.6315371e+00 VDC
#
# 0 1 2 3 4 5 6 7 8 9
discharge = []
with open(path, 'r') as fin:
for raw_line in fin:
if len(raw_line) < 10: # arbitrario per rimuovere linee sicuramente sbagliate
continue
if 'slv' in raw_line.lower():
continue
fields = raw_line.strip().strip('\n').split()
if len(fields) < 10:
continue # remove malformed lines
ts = int(fields[0])
v = float(fields[8])
i = float(fields[3])
if None not in (ts, v, i):
i /= 0.010007
measure = Measure(ts=ts, v=v, i=i)
# print(measure)
discharge.append(measure)
discharge.sort(key=lambda x: x.ts)
return discharge
def available_measurements(s_in: str):
"""
generates the series of RawMeasure contained in the s_in string
:param s_in:
:return:
"""
fields = s_in.strip().strip('\n').replace('VDC1', 'VDC 1').split()
for batch in batched(fields, 5):
ts, ch, chn, value, unit = batch.split()
if ch != 'Ch' or not unit.endswith('DC'):
continue
yield RawMeasure(ts=int(ts), ch=int(chn), v=float(value))
def load_a_txt_file_4(path: Path) -> list[Measure]:
"""Returns a sorted list of Measures()"""
# 1742542808 Ch 101 4.6694100e-03 VDC 1742542808 Ch 102 3.6288222e+00 VDC
# 1742542838 Ch 101 4.6651780e-03 VDC 1742542838 Ch 102 3.6315371e+00 VDC
# 1743758985 Ch 101 2.2117630e-03 VDC 1743758985 Ch 102 2.9622319e+00 VDC1743758985 Ch 103 1.9700000e-03 VDC 1743758985 Ch 104 3.0066588e+00 VDC
# 0 1 2 3 4 5 6 7 8 9
discharge = []
with open(path, 'r') as fin:
for raw_line in fin:
if len(raw_line) < 10: # arbitrario per rimuovere linee sicuramente sbagliate
continue
if 'slv' in raw_line.lower():
continue
fields = raw_line.strip().strip('\n').split()
if len(fields) < 10:
continue # remove malformed lines
@ -155,6 +216,8 @@ def show_a_discharge(discharge: list[DischargePoint], title='Title'):
if __name__ == '__main__':
for f in source_file_folder.iterdir():
if f.stem != 'log_2025_04_04_09':
continue
if f.is_file():
if f.suffix.lower() == '.xlsx':
print(f)