def testcase1():
## 2018-11-22,07:51,68.40,461,3.60,11.50,66.30,45.90,22.30,1542873060
data_peter = {
"measured": 72.80,
"calcweight": 70.65,
"unit": 'kg',
"impedance": 478,
"timestamp": str(datetime.today().strftime('%Y-%m-%d %H:%M:%S')),
"scantime": str(datetime.today().strftime('%Y-%m-%d %H:%M:%S'))
}
data_reni = {
"measured": 49.50,
"calcweight": 49.50,
"unit": 'kg',
"impedance": 495,
"timestamp": str(datetime.today().strftime('%Y-%m-%d %H:%M:%S')),
"scantime": str(datetime.today().strftime('%Y-%m-%d %H:%M:%S'))
}
data = data_peter
log.info('Calcluation based on data:{}'.format(data))
mCalc = calcdata.CalcData(data, True)
mi_data = mCalc.getData('string')
print(mi_data)
def testcase1():
variables_file = '../data/gewichtsdaten.csv'
reader = csv.DictReader(open(variables_file, 'r'), delimiter=',')
dict_list = []
for line in reader:
dict_list.append(line)
line_count = 0
for data in dict_list:
# simulate the impedance from the history values
# impedance = int((450 / 54) * float(data['wasser']))
impedance = int((175**2) / float(data['wasser']))
scaledata = {
"measured": float(data['gewicht']),
"calcweight": 70.65,
"unit": 'kg',
"impedance": impedance,
"timestamp": str(datetime.today().strftime('%Y-%m-%d %H:%M:%S')),
"scantime": str(datetime.today().strftime('%Y-%m-%d %H:%M:%S'))
}
mCalc = calcdata.CalcData(scaledata, True)
user = mCalc.getUserData()
mCalc.impedance = int((user['height']**2) / float(data['wasser']))
# get the data from the calculation
results = mCalc.getData('full', 'data')
log.info("Results: {}".format(results))
line_count += 1
print(f'Processed {line_count} lines.')
return line_count
def main():
dict_list = [] # list previous data
line_count = 0 # number of lines
scaledata = dict() # data object for the calc module
height = 175 # height for the user
try:
# file with the data from the previous scale
# datum,zeit,gewicht,knochen,fett,wasser,muskeln,bmi,timestamp
# 31.12.2013,12:35,77.90,3.70,21.00,59.20,40.60,25.40,1388493300
# ....
variables_file = '../data/peter.csv'
reader = csv.DictReader(open(variables_file, 'r'), delimiter=',')
# build the dict list
for line in reader:
dict_list.append(line)
for data in dict_list:
# calculate the impedance from the history values
impedance = (int(height)**2) / float(data['wasser'])
dt_object = datetime.fromtimestamp(int(data['timestamp']))
scaledata = {
"measured": float(data['gewicht']),
"calcweight": float(data['gewicht']) * 2.00,
"unit": 'kg',
"impedance": int(data['impedance']),
"timestamp": "{} {}:00".format(data['datum'], data['zeit']),
"scantime": "{} {}:00".format(data['datum'], data['zeit'])
}
log.info('Calcluation based on data:{}'.format(scaledata))
# initialize the calc module with the data from the csv file
mCalc = calcdata.CalcData(scaledata, True)
# get the userdata
mi_userdata = mCalc.getUserData()
# calculate all miscale data
log.info('Calcluation for user :{}, Date:{}'.format(
mi_userdata['name'], scaledata['timestamp']))
mi_data = mCalc.getData('alldata')
if mCalc.ready:
# publish data to influxdb
datasections = {"influxdb": True}
mCalc.publishdata(datasections)
line_count += 1
log.info(
'{} previous data found, transfer finished'.format(line_count))
except BaseException as e:
log.error(
f"Error {__name__}, {str(e)} line {sys.exc_info()[-1].tb_lineno}")
def doCalc(scaledata: dict = None,
useAge: bool = False,
useAthletic: bool = False):
mCalc = calcdata.CalcData(scaledata, useAge)
user = mCalc.getUserData()
mCalc.athletic = useAthletic
log.info(
"User: {}\t Athletic: {} \tAge: {} \tyears Weight: {}kg \tImpedance: {}"
.format(mCalc.user, mCalc.athletic, round(mCalc.age, 2), mCalc.weight,
mCalc.impedance))
results = mCalc.getData('full', 'data')
mCalc = None
return results
def updateInfluxDb():
log.debug("Start Update Influxdb data")
variables_file = '../data/peter.csv'
reader = csv.DictReader(open(variables_file, 'r'), delimiter=',')
dict_list = []
for line in reader:
dict_list.append(line)
line_count = 0
for data in dict_list:
# recalc the impedance and build the measurement data
scaledata = {
"measured": float(data['gewicht']),
"calcweight": float(data['gewicht']),
"unit": 'kg',
"impedance": data['impedance'],
"timestamp": data['datum'] + " " + data['zeit'],
"scantime": data['datum'] + " " + data['zeit']
}
log.info("Scale data: {}".format(scaledata))
# start the calculation modul
mCalc = calcdata.CalcData(scaledata, True)
# get the userdata
user = mCalc.getUserData()
# make the calulations
if mCalc.doCalc('full'):
# publish data to the influxDB
log.info("Update row{}, User{}".format(line_count, user['name']))
mCalc.publish2Influxdb()
mCalc.bodyScores2Influxdb()
line_count += 1
print(f'Processed {line_count} records to influxDB.')
return line_count
def checkData():
scaledata = {
"measured": 68.50,
"calcweight": 70.65,
"unit": 'kg',
"impedance": 543,
"timestamp": str(datetime.today().strftime('%Y-%m-%d %H:%M:%S')),
"scantime": str(datetime.today().strftime('%Y-%m-%d %H:%M:%S'))
}
log.info("Calcdata: {}".format(scaledata))
mCalc = calcdata.CalcData(scaledata, True)
user = mCalc.getUserData()
# get the data from the calculation
results = mCalc.getData('full', 'data')
log.info("Results: {}".format(results))
mCalc.__savedata__()
def doCalc(scaledata, data) -> dict:
mCalc = calcdata.CalcData(scaledata, True)
user = mCalc.getUserData()
mCalc.impedance = (int(user['height'])**2) / float(data['wasser'])
# get the data from the calculation
result = mCalc.getData('full', 'data')
useAthletic = result['athletic']
useAthletic = False
# try to rescale the calculated values
if useAthletic:
#result['fat'] = round(result['fat'] - 8.34, 2)
result['fat'] = round(result['fat'] * 0.6225, 2)
result['bone'] = round(result['bone'] * 1.302, 2)
result['water'] = round(result['water'] * 1.033, 2)
result['muscle'] = round(result['muscle'] * 0.852, 2)
result['visceral'] = round(result['visceral'] * 0.475, 2)
# Körperfettanteil + Knochenmasse + Muskelmasse = 100 % der Körperzusammensetzung
result['check'] = round(float(result['fat']) + float(result['bone']) + float(result['muscle']) + float(result['water']), 2)
return result
def testcase2():
xmax = 600
ymax = 10
data = dict()
data['fat'] = dict()
data['visceral'] = dict()
data['muscle'] = dict()
data['bone'] = dict()
data['water'] = dict()
for impedance in range(450, 600):
miscale_peter = {
"measured": 70.65,
"calcweight": 70.65,
"unit": 'kg',
"impedance": impedance,
"timestamp": str(datetime.today().strftime('%Y-%m-%d %H:%M:%S')),
"scantime": str(datetime.today().strftime('%Y-%m-%d %H:%M:%S'))
}
miscale_reni = {
"measured": 50.65,
"calcweight": 50.65,
"unit": 'kg',
"impedance": impedance,
"timestamp": str(datetime.today().strftime('%Y-%m-%d %H:%M:%S')),
"scantime": str(datetime.today().strftime('%Y-%m-%d %H:%M:%S'))
}
mCalc = calcdata.CalcData(miscale_peter)
result = mCalc.getData('full', 'data')
y = result['fat']
# if y>ymax: ymax = y+0.10
data['fat'][impedance] = y
y = result['visceral']
# if y>ymax: ymax = y+0.10
data['visceral'][impedance] = y
y = result['muscle']
# if y>ymax: ymax = y+0.10
data['muscle'][impedance] = y
y = result['water']
# if y>ymax: ymax = y+0.10
data['water'][impedance] = y
y = result['bone']
# if y>ymax: ymax = y+0.10
data['bone'][impedance] = y
# draw the grid
fig, ax = plt.subplots(1, figsize=(8, 6))
plt.suptitle("Testcase Body Calculator Impedance {}".format(
result['timestamp']),
fontsize=12)
plt.title("Result for User {} ({}), Years:{}, Weight:{}{}, ".format(
result['user'], result['sex'], result['age'], result['measured'],
result['unit'], result['timestamp']),
fontsize=10)
# Show the major grid lines with dark grey lines
ax.minorticks_on()
ax.grid(b=True, which='major', color='#666666', linestyle='-', alpha=0.75)
# Show the minor grid lines with very faint and almost transparent grey lines
ax.minorticks_on()
ax.grid(b=True, which='minor', color='#999999', linestyle='-', alpha=0.1)
# primary y:
ax.plot(*zip(*sorted(data['fat'].items())), label='1-fat', color="red")
ax.plot(*zip(*sorted(data['visceral'].items())),
label='2-visceral',
color="orange")
ax.plot(*zip(*sorted(data['bone'].items())), label='5-bone', color="lime")
ax.set_ylabel("1-fat, 2-visceral, 5-Bone %")
ax.set_xlabel("Impedance (Ω)")
# secondary y:
ax2 = ax.twinx()
ax2.plot(*zip(*sorted(data['muscle'].items())),
label='3-muscle',
color="green")
ax2.plot(*zip(*sorted(data['water'].items())),
label='4-water',
color="blue")
ax2.set_ylabel("3-Muscle, 4-Water %")
# add legend
lines_1, labels_1 = ax.get_legend_handles_labels()
lines_2, labels_2 = ax2.get_legend_handles_labels()
lines = lines_1 + lines_2
labels = labels_1 + labels_2
ax.legend(lines, labels, loc="center left")
plt.savefig("impedance.png", dpi=600)
plt.show()
