291 lines
10 KiB
Python
291 lines
10 KiB
Python
import os
|
|
import tempfile
|
|
import pandas as pd
|
|
import plotly
|
|
from plotly.subplots import make_subplots
|
|
from plotly.graph_objs import Scatter, Layout, Bar, Figure
|
|
|
|
try:
|
|
from gc_wrapper.GC_Wrapper import GC_wrapper as GC
|
|
except ImportError:
|
|
pass
|
|
BASELINE_DAYS = 7
|
|
NORMALRANGE_DAYS = 60
|
|
TRAINING_STRESS = 'BikeStress'
|
|
|
|
HRV = 'RECOVERY_POINTS'
|
|
HR = 'HR'
|
|
HRV_BASE = 'HrvBaseline'
|
|
HR_BASE = 'HrBaseline'
|
|
HRV_NORMAL = 'HrvNormal'
|
|
HRV_STD = 'HrvStdDev'
|
|
HRV_CEILING = 'HrvNormalCeiling'
|
|
HRV_FLOOR = 'HrvNormalFloor'
|
|
HRV_CV = 'HrvCv'
|
|
HRV_VAR_BASE = 'HrvVarBase'
|
|
|
|
|
|
def plot_plotly():
|
|
lts_trace = Scatter(x=pmc_data['date'],
|
|
y=pmc_data['lts'],
|
|
name='Fitness (LTS)',
|
|
fill='tozeroy',
|
|
line=dict(color='#1f77b4'))
|
|
sts_trace = Scatter(x=pmc_data['date'],
|
|
y=pmc_data['sts'],
|
|
name='Fatigue (STS)',
|
|
fill='tozeroy',
|
|
line=dict(color='#FF6692'))
|
|
|
|
sb_trace = Scatter(x=pmc_data['date'], y=pmc_data['sb'], name='Form (TSB)')
|
|
|
|
hr_trace = Scatter(x=hrv_data['date'],
|
|
y=hrv_data[HR_BASE],
|
|
mode='lines',
|
|
name=f'{BASELINE_DAYS}-day HR Baseline')
|
|
|
|
hrv_ceiling_trace = Scatter(x=hrv_data['date'],
|
|
y=hrv_data[HRV_CEILING],
|
|
fill=None,
|
|
mode='lines',
|
|
name=f"{NORMALRANGE_DAYS}-day Top Normal",
|
|
line=dict(color='#b3f6d1', ))
|
|
hrv_floor_trace = Scatter(x=hrv_data['date'],
|
|
y=hrv_data[HRV_FLOOR],
|
|
fill='tonexty',
|
|
mode='lines',
|
|
name=f'{NORMALRANGE_DAYS}-day Bottom Normal',
|
|
line=dict(color='#b3f6d1', ))
|
|
|
|
hrv_base_trace = Scatter(x=hrv_data['date'],
|
|
y=hrv_data[HRV_BASE],
|
|
mode='lines',
|
|
name=f"{BASELINE_DAYS}-day Baseline",
|
|
line=dict(color='red', ))
|
|
|
|
hrv_trace = Bar(x=hrv_data['date'],
|
|
y=hrv_data[HRV],
|
|
name="Recovery Points",
|
|
marker=dict(color='gray', ))
|
|
|
|
hrv_cv_trace = Scatter(x=hrv_data['date'],
|
|
y=hrv_data[HRV_CV],
|
|
name='CV',
|
|
mode='lines',
|
|
line=dict(color='yellow'))
|
|
|
|
# session_rpe_trace = Bar(x=rpe['date'],
|
|
# y=rpe['Session_RPE'],
|
|
# name='RPE',
|
|
# marker=dict(color='lightgray', ))
|
|
rpe_trace = Bar(x=rpe['date'],
|
|
y=rpe['RPE'],
|
|
name='RPE',
|
|
marker=dict(color='red', ))
|
|
|
|
layout = Layout(
|
|
template='plotly_dark',
|
|
# paper_bgcolor='rgba(0,0,0,0)',
|
|
# plot_bgcolor='rgba(0,0,0,0)',
|
|
yaxis=dict(title="HRV Recovery Points", range=[5.5, 10]),
|
|
yaxis2=dict(title="Coeffient of Variation", range=[0, 20]),
|
|
yaxis3=dict(title=f'{TRAINING_STRESS}'),
|
|
yaxis4=dict(title='HRV (ln(RMSSD)'),
|
|
yaxis5=dict(title='HR (BPM)'),
|
|
legend=dict(orientation="h"))
|
|
|
|
fig = make_subplots(
|
|
4,
|
|
1,
|
|
subplot_titles=[
|
|
'HRV',
|
|
'Coefficient of Variaton',
|
|
'Stress',
|
|
'HRV vs. HR',
|
|
],
|
|
specs=[
|
|
[dict(secondary_y=False)],
|
|
[dict(secondary_y=False)],
|
|
[dict(secondary_y=False)],
|
|
[dict(secondary_y=True)],
|
|
# [dict(secondary_y=True)],
|
|
],
|
|
# horizontal_spacing=0.2,
|
|
# vertical_spacing=0.2
|
|
)
|
|
fig.update_layout(template='plotly_dark')
|
|
fig.add_trace(hrv_trace, 1, 1)
|
|
fig.add_trace(hrv_ceiling_trace, 1, 1)
|
|
fig.add_trace(hrv_floor_trace, 1, 1)
|
|
fig.add_trace(hrv_base_trace, 1, 1)
|
|
# fig.add_trace(sb_trace, 1, 1, secondary_y=True)
|
|
fig.add_trace(hrv_cv_trace, 2, 1)
|
|
fig.add_trace(sts_trace, 3, 1)
|
|
fig.add_trace(lts_trace, 3, 1)
|
|
fig.add_trace(hr_trace, 4, 1, secondary_y=True)
|
|
fig.add_trace(hrv_base_trace, 4, 1)
|
|
# fig.add_trace(session_rpe_trace, 2, 2)
|
|
# fig.add_trace(rpe_trace, 5, 1)
|
|
fig.update_layout(layout)
|
|
fig.update_layout(
|
|
dict(
|
|
yaxis=dict(showline=True, mirror=True, ticks='inside'),
|
|
yaxis2=dict(showline=True, mirror=True, ticks='inside'),
|
|
yaxis3=dict(showline=True, mirror=True, ticks='inside'),
|
|
yaxis4=dict(showline=True, mirror=True, ticks='inside'),
|
|
yaxis5=dict(showline=True, mirror=True, ticks='inside'),
|
|
yaxis6=dict(showline=True, mirror=True, ticks='inside'),
|
|
yaxis7=dict(showline=True, mirror=True, ticks='inside'),
|
|
yaxis8=dict(showline=True, mirror=True, ticks='inside'),
|
|
xaxis=dict(showline=True, mirror=True, ticks='inside'),
|
|
xaxis2=dict(showline=True, mirror=True, ticks='inside'),
|
|
xaxis3=dict(showline=True, mirror=True, ticks='inside'),
|
|
xaxis4=dict(showline=True, mirror=True, ticks='inside'),
|
|
xaxis5=dict(showline=True, mirror=True, ticks='inside'),
|
|
xaxis6=dict(showline=True, mirror=True, ticks='inside'),
|
|
xaxis7=dict(showline=True, mirror=True, ticks='inside'),
|
|
xaxis8=dict(showline=True, mirror=True, ticks='inside'),
|
|
))
|
|
fig.update_xaxes(showline=True,
|
|
linewidth=1,
|
|
linecolor='black',
|
|
mirror=True)
|
|
fig.update_yaxes(showline=True,
|
|
linewidth=1,
|
|
linecolor='black',
|
|
mirror=True)
|
|
|
|
f = plotly.offline.plot(fig,
|
|
auto_open=False,
|
|
filename=tempfile.gettempdir() + "/temp-plot.html")
|
|
|
|
GC.webpage("file://" + f)
|
|
|
|
|
|
def plot_native():
|
|
GC.setChart(type=GC.CHART_LINE,
|
|
orientation=GC_VERTICAL,
|
|
legpos=GC_ALIGN_RIGHT,
|
|
stack=False,
|
|
animate=True)
|
|
hrv_data['date_internal'] = (hrv_data['date'] -
|
|
pd.to_datetime('1900-01-01').date()).dt.days
|
|
xx = hrv_data['date_internal']
|
|
settings = dict(symbol=GC_SYMBOL_CIRCLE,
|
|
line=GC_LINE_NONE,
|
|
color='gray',
|
|
opacity=20,
|
|
xaxis='Date',
|
|
yaxis='lnRMSSD',
|
|
size=3,
|
|
opengl=False)
|
|
GC.addCurve(name='Measurement', x=xx, y=hrv_data[HRV], **settings)
|
|
settings = dict(symbol=GC_SYMBOL_NONE,
|
|
line=GC_LINE_SOLID,
|
|
color='red',
|
|
opacity=100,
|
|
xaxis='Date',
|
|
yaxis='lnRMSSD',
|
|
size=3,
|
|
opengl=False)
|
|
settings['color'] = 'green'
|
|
settings['opacity'] = 100
|
|
settings['line'] = GC_LINE_DASH
|
|
GC.addCurve(name='Normal Top', x=xx, y=hrv_data[HRV_CEILING], **settings)
|
|
GC.addCurve(name='Normal Bot', x=xx, y=hrv_data[HRV_FLOOR], **settings)
|
|
|
|
settings['color'] = 'red'
|
|
settings['line'] = GC_LINE_SOLID
|
|
GC.addCurve(name='HRV', x=xx, y=hrv_data[HRV_BASE], **settings)
|
|
|
|
settings['color'] = 'yellow'
|
|
settings['opacity'] = 100
|
|
settings['line'] = GC_LINE_SOLID
|
|
settings['yaxis'] = 'Coefficient of Variation'
|
|
settings['xaxis'] = 'Date2'
|
|
GC.addCurve(name='Variation', x=xx, y=hrv_data[HRV_CV], **settings)
|
|
|
|
GC.setAxis('Date', type=GC.AXIS_DATE)
|
|
GC.setAxis('Date2', type=GC.AXIS_DATE)
|
|
GC.setAxis('Coefficient of Variation',
|
|
type=GC.AXIS_CONTINUOUS,
|
|
min=0,
|
|
max=25)
|
|
GC.setAxis('lnRMSSD',
|
|
type=GC.AXIS_CONTINUOUS,
|
|
min=4.0,
|
|
max=10.0,
|
|
color='red')
|
|
|
|
|
|
def get_hrv_measures():
|
|
history = pd.DataFrame(GC.seasonMeasures(
|
|
all=True, group='Hrv')).query(f'{HRV} != 0.0')
|
|
selection = pd.DataFrame(GC.seasonMeasures(
|
|
all=False, group='Hrv')).query(f'{HRV} != 0.0')
|
|
return history, selection
|
|
|
|
|
|
def compute_hrv_trends(df: pd.DataFrame):
|
|
df[HRV_BASE] = df[HRV].rolling(window=BASELINE_DAYS,
|
|
min_periods=BASELINE_DAYS // 2).mean()
|
|
df[HRV_NORMAL] = df[HRV].rolling(window=NORMALRANGE_DAYS,
|
|
min_periods=NORMALRANGE_DAYS // 2).mean()
|
|
df[HRV_STD] = df[HRV].rolling(window=NORMALRANGE_DAYS,
|
|
min_periods=NORMALRANGE_DAYS // 2).std()
|
|
df[HRV_CEILING] = df[HRV_NORMAL] + 0.75 * df[HRV_STD]
|
|
df[HRV_FLOOR] = df[HRV_NORMAL] - 0.75 * df[HRV_STD]
|
|
|
|
df[HR_BASE] = df[HR].rolling(window=BASELINE_DAYS,
|
|
min_periods=BASELINE_DAYS // 2).mean()
|
|
df[HRV_VAR_BASE] = df[HRV].rolling(window=BASELINE_DAYS,
|
|
min_periods=BASELINE_DAYS // 2).std()
|
|
df[HRV_CV] = df[HRV_VAR_BASE] / df[HRV_BASE] * 100.0
|
|
return df
|
|
|
|
|
|
def get_pmc_data(t1):
|
|
df = pd.DataFrame(GC.seasonPmc(all=True, metric=TRAINING_STRESS))
|
|
tmp = pd.DataFrame(GC.seasonPmc(all=False, metric=TRAINING_STRESS))
|
|
t0 = tmp.iloc[0]['date']
|
|
return crop(df, t0, t1)
|
|
|
|
|
|
def get_stress():
|
|
df = pd.DataFrame(GC.seasonMetrics())[['date', TRAINING_STRESS]]
|
|
data = df.groupby('date')[TRAINING_STRESS].sum()
|
|
df = pd.DataFrame({'date': data.index, TRAINING_STRESS: data.values})
|
|
return df
|
|
|
|
|
|
def get_rpe():
|
|
df = pd.DataFrame(GC.seasonMetrics())[['date', 'RPE']]
|
|
# df = df.loc[df['RPE'].dtype.kind in 'iufc']
|
|
# df = df.query('RPE != 0.0')
|
|
df['RPE'] = df['RPE'].replace('', '0').astype(int)
|
|
data = df.groupby('date', as_index=False).mean()
|
|
return data
|
|
|
|
|
|
def crop(df: pd.DataFrame, t0, t1):
|
|
df = df.loc[df['date'] >= t0]
|
|
return df.loc[df['date'] <= t1]
|
|
|
|
|
|
try:
|
|
os.remove(tempfile.gettempdir() + "/hrv_trends.html")
|
|
except:
|
|
pass
|
|
|
|
history, selection = get_hrv_measures()
|
|
compute_hrv_trends(history)
|
|
t0 = selection.iloc[0]['date']
|
|
t1 = selection.iloc[-1]['date']
|
|
hrv_data = crop(history, t0, t1)
|
|
|
|
rpe = get_rpe()
|
|
stress = get_stress()
|
|
pmc_data = get_pmc_data(stress.iloc[-1]['date'])
|
|
|
|
plot_native()
|
|
plot_plotly()
|