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fixing some tests

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This commit is contained in:
Sander Roosendaal
2024-04-16 15:47:03 +02:00
parent 0936d4cecc
commit eec03965c8
5 changed files with 29 additions and 226 deletions
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244
rowers/interactiveplots.py
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@@ -1731,35 +1731,35 @@ def interactive_flexchart_stacked(id, r, xparam='time',
try:
tseconds = rowdata['time']
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
return '', 'No time data - cannot make flex plot'
try:
rowdata = rowdata.with_columns(x1=pl.col(xparam))
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
rowdata = rowdata.with_columns(x1=pl.lit(0))
try:
rowdata = rowdata.with_columns(y1=pl.col(yparam1))
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
rowdata = rowdata.with_columns(y1=pl.col("time"))
rowdata = rowdata.with_columns((pl.col("y1")).alias(yparam1))
try:
rowdata = rowdata.with_columns(y2=pl.col(yparam2))
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
rowdata = rowdata.with_columns(y2=pl.col("time"))
rowdata = rowdata.with_columns((pl.col("y2")).alias(yparam2))
try:
rowdata = rowdata.with_columns(y1=pl.col(yparam3))
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
rowdata = rowdata.with_columns(y3=pl.col("time"))
rowdata = rowdata.with_columns((pl.col("y3")).alias(yparam3))
try:
rowdata = rowdata.with_columns(y4=pl.col(yparam1))
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
rowdata = rowdata.with_columns(y4=pl.col("time"))
rowdata = rowdata.with_columns((pl.col("y4")).alias(yparam4))
@@ -1800,8 +1800,8 @@ def interactive_flex_chart2(id, r, promember=0,
columns = [name for name, d in metrics.rowingmetrics]
columns_basic = [name for name, d in metrics.rowingmetrics if d['group'] == 'basic']
columns = columns + ['spm', 'driveenergy', 'distance']
columns_basic = columns_basic + ['spm', 'driveenergy', 'distance']
columns = columns + ['spm', 'driveenergy', 'distance','workoutstate']
columns_basic = columns_basic + ['spm', 'driveenergy', 'distance','workoutstate']
datadf = pd.DataFrame()
if promember:
@@ -1838,24 +1838,24 @@ def interactive_flex_chart2(id, r, promember=0,
workstrokesonly = False
try:
_ = rowdata[yparam2]
except (KeyError, TypeError): # pragma: no cover
except (KeyError, TypeError, ColumnNotFoundError): # pragma: no cover
yparam2 = 'None'
try:
_ = rowdata[yparam1]
except (TypeError, KeyError): # pragma: no cover
except (TypeError, KeyError, ColumnNotFoundError): # pragma: no cover
yparam1 = 'None'
# test if we have drive energy
try:
_ = rowdata['driveenergy'].mean()
except (KeyError, TypeError):
except (KeyError, TypeError, ColumnNotFoundError):
rowdata = rowdata.with_columns(driveenergy=pl.lit(500))
# test if we have power
try:
_ = rowdata['power'].mean()
except (KeyError, TypeError):
except (KeyError, TypeError, ColumnNotFoundError):
rowdata = rowdata.with_columns(power=pl.lit(50))
# replace nans
@@ -1870,22 +1870,22 @@ def interactive_flex_chart2(id, r, promember=0,
if workstrokesonly: # pragma: no cover
try:
rowdata = rowdata.filter(~pl.col("workoutstate").is_in(workoutstatesrest))
except KeyError:
except (KeyError, ColumnNotFoundError):
pass
try:
tseconds = rowdata['time']
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
return '', 'No time data - cannot make flex plot', workstrokesonly
try:
rowdata = rowdata.with_columns(x1 = pl.col(xparam))
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
rowdata = rowdata.with_columns(x1 = pl.col("time"))
try:
rowdata = rowdata.with_columns(y1 = pl.col(yparam1))
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
rowdata = rowdata.with_columns(y1 = pl.col("time"))
rowdata = rowdata.with_columns(yparam1 = pl.col("y1"))
@@ -1893,7 +1893,7 @@ def interactive_flex_chart2(id, r, promember=0,
if yparam2 != 'None':
try:
rowdata = rowdata.with_columns(y2 = pl.col(yparam2))
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
rowdata = rowdata.with_columns(y2 = pl.col("time"))
rowdata = rowdata.with_columns(yparam2 = pl.col("y2"))
@@ -1916,18 +1916,18 @@ def interactive_flex_chart2(id, r, promember=0,
try:
rowdata = rowdata.with_columns((pl.lit(axlabels[xparam])).alias("xname"))
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
rowdata = rowdata.with_columns((pl.lit(xparam)).alias("xname"))
try:
rowdata = rowdata.with_columns((pl.lit(axlabels[yparam1])).alias("yname1"))
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
rowdata = rowdata.with_columns((pl.lit(yparam1)).alias("yname1"))
if yparam2 != 'None':
try:
rowdata = rowdata.with_columns((pl.lit(axlabels[yparam2])).alias("yname2"))
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
rowdata = rowdata.with_columns((pl.lit(yparam2)).alias("yname2"))
else: # pragma: no cover
@@ -2185,210 +2185,6 @@ def interactive_multiple_compare_chart(ids, xparam, yparam, plottype='line',
script, div = get_chart("/compare", chart_data)
return script, div, message, errormessage
if xparam != 'distance' and xparam != 'time' and xparam != 'cumdist': # pragma: no cover
xaxmax = yaxmaxima[xparam]
xaxmin = yaxminima[xparam]
elif xparam == 'time' and not startenddict:
xaxmax = tseconds.max()
xaxmin = tseconds.min()
elif xparam == 'time' and startenddict: # pragma: no cover
deltas = [pair[1]-pair[0] for key, pair in startenddict.items()]
xaxmin = 0
xaxmax = pd.Series(deltas).max()*1000.
if xaxmax == 0:
xaxmax = tseconds.max()
else:
xaxmax = datadf['distance'].max()
xaxmin = datadf['distance'].min()
if yparam == 'distance': # pragma: no cover
yaxmin = datadf['distance'].min()
yaxmax = datadf['distance'].max()
elif yparam == 'cumdist': # pragma: no cover
yaxmin = datadf['cumdist'].min()
yaxmax = datadf['cumdist'].max()
else:
yaxmin = yaxminima[yparam]
yaxmax = yaxmaxima[yparam]
x_axis_type = 'linear'
y_axis_type = 'linear'
# Add hover to this comma-separated string and see what changes
if (promember == 1):
TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,crosshair'
else: # pragma: no cover
TOOLS = 'pan,box_zoom,wheel_zoom,reset,tap,crosshair'
if yparam == 'pace':
y_axis_type = 'datetime'
yaxmax = 90.*1e3
yaxmin = 150.*1e3
if xparam == 'time':
x_axis_type = 'datetime'
plot = figure(x_axis_type=x_axis_type, y_axis_type=y_axis_type,
tools=TOOLS,
toolbar_location="above",
width=920, height=500,
toolbar_sticky=False)
# add watermark
watermarkurl = "/static/img/logo7.png"
watermarkrange = Range1d(start=0, end=1)
watermarkalpha = 0.6
watermarkw = 184
watermarkh = 35
plot.extra_y_ranges = {"watermark": watermarkrange}
plot.extra_x_ranges = {"watermark": watermarkrange}
#plot.sizing_mode = 'stretch_both'
plot.image_url([watermarkurl], 0.05, 0.9,
watermarkw, watermarkh,
global_alpha=watermarkalpha,
w_units='screen',
h_units='screen',
anchor='top_left',
dilate=True,
x_range_name="watermark",
y_range_name="watermark",
)
colors = itertools.cycle(palette)
cntr = 0
l1 = []
try:
items = itertools.izip(ids, colors)
except AttributeError:
items = zip(ids, colors)
for id, color in items:
group = datadf[datadf['workoutid'] == int(id)].copy()
try:
startsecond, endsecond = startenddict[id]
except KeyError:
startsecond = 0
endsecond = 0
group.sort_values(by='time', ascending=True, inplace=True)
if endsecond > 0:
group['time'] = group['time'] - 1.e3*startsecond
mask = group['time'] < 0
group.mask(mask, inplace=True)
mask = group['time'] > 1.e3*(endsecond-startsecond)
group.mask(mask, inplace=True)
if xparam == 'cumdist':
group['cumdist'] = group['cumdist'] - group['cumdist'].min()
res = make_cumvalues(group[xparam])
group[xparam] = res[0]
elif xparam == 'distance':
group['distance'] = group['distance'] - group['distance'].min()
try:
group['x'] = group[xparam]
except KeyError: # pragma: no cover
group['x'] = group['time']
errormessage = xparam+' has no values. Plot invalid'
try:
group['y'] = group[yparam]
except KeyError:
group['y'] = 0.0*group['x']
ymean = group['y'].mean()
f = group['time'].diff().mean()
if f != 0 and not np.isnan(f):
windowsize = 2 * (int(20000./(f))) + 1
else:
windowsize = 1
if windowsize > 3 and windowsize < len(group['y']):
try:
group['y'] = savgol_filter(group['y'], windowsize, 3)
except ValueError: # pragma: no cover
pass
ylabel = Label(x=100, y=60+nrworkouts*20-20*cntr,
x_units='screen', y_units='screen',
text=axlabels[yparam] +
": {ymean:6.2f}".format(ymean=ymean),
background_fill_alpha=.7,
background_fill_color='white',
text_color=color,
)
if yparam != 'time' and yparam != 'pace':
plot.add_layout(ylabel)
source = ColumnDataSource(
group
)
TIPS = OrderedDict([
('time', '@ftime'),
('pace', '@fpace'),
('hr', '@hr'),
('spm', '@spm{1.1}'),
('distance', '@distance{5}'),
])
hover = plot.select(type=HoverTool)
hover.tooltips = TIPS
if labeldict:
try:
legend_label = labeldict[id]
except KeyError: # pragma: no cover
legend_label = str(id)
else: # pragma: no cover
legend_label = str(id)
if plottype == 'line':
l1.append(plot.line('x', 'y', source=source, color=color,
legend_label=legend_label, line_width=2))
else:
l1.append(plot.scatter('x', 'y', source=source, color=color, legend_label=legend_label,
fill_alpha=0.4, line_color=None))
plot.add_tools(HoverTool(renderers=[l1[cntr]], tooltips=TIPS))
cntr += 1
plot.legend.location = 'top_right'
plot.xaxis.axis_label = axlabels[xparam]
plot.yaxis.axis_label = axlabels[yparam]
if (xparam != 'time') and (xparam != 'distance') and (xparam != 'cumdist'): # pragma: no cover
xrange1 = Range1d(start=yaxminima[xparam], end=yaxmaxima[xparam])
plot.x_range = xrange1
yrange1 = Range1d(start=yaxmin, end=yaxmax)
plot.y_range = yrange1
if xparam == 'time':
xrange1 = Range1d(start=xaxmin, end=xaxmax)
plot.x_range = xrange1
plot.xaxis[0].formatter = DatetimeTickFormatter(
hours=["%H"],
minutes=["%M"],
seconds=["%S"],
days=["0"],
months=[""],
years=[""]
)
if yparam == 'pace':
plot.yaxis[0].formatter = DatetimeTickFormatter(
seconds=["%S"],
minutes=["%M"]
)
script, div = components(plot)
return [script, div, message, errormessage]
def get_zones_report(rower, startdate, enddate, trainingzones='hr', date_agg='week',
yaxis='time'):

6
rowers/tests/mocks.py
View File

@@ -38,6 +38,7 @@ from nose.tools import assert_true
from mock import Mock, patch
#from minimocktest import MockTestCase
import pandas as pd
import polars as pl
import arrow
from django.http import HttpResponseRedirect
@@ -335,6 +336,11 @@ def mocked_getsmallrowdata_db(*args, **kwargs):
return df
def mocked_getsmallrowdata_pl(*args, **kwargs):
df = pl.read_csv('rowers/tests/testdata/colsfromdb.csv')
return df
def mocked_getsmallrowdata_db_updatecp(*args, **kwargs): # pragma: no cover
df = pd.read_csv('rowers/tests/testdata/colsfromdb.csv')

1
rowers/tests/statements.py
View File

@@ -65,6 +65,7 @@ from nose.tools import assert_true
from mock import Mock, patch
#from minimocktest import MockTestCase
import pandas as pd
import polars as pl
import rowers.c2stuff as c2stuff
import rowers.rojabo_stuff as rojabo_stuff

4
rowers/tests/test_unit_tests.py
View File

@@ -735,9 +735,9 @@ class InteractivePlotTests(TestCase):
self.assertFalse(len(div)==0)
@patch('rowers.dataprep.create_engine')
@patch('rowers.dataprep.getsmallrowdata_db', side_effect=mocked_getsmallrowdata_db)
@patch('rowers.dataprep.getsmallrowdata_pl', side_effect=mocked_getsmallrowdata_pl)
def test_interactive_flexchart_stacked(self, mocked_sqlalchemy,
mocked_getsmallrowdata_db):
mocked_getsmallrowdata_pl):
workout = Workout.objects.filter(user=self.r,workouttype__in=mytypes.rowtypes)[0]
id = workout.id

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rowers/tests/testdata/testdata.tcx.gz vendored
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