Cleanup documentation.
This commit is contained in:
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@ -5,17 +5,20 @@ __author__ = 'Timothy Allen'
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__email__ = 'tim@treehouse.org.za'
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__license__ = 'MIT'
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''' Included are the Noto Sans and IcoGluco font sets.
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Noto Sans is licensed under the SIL Open Font License version 1.1
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''' Included are the OpenSans and IcoGluco font sets.
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IcoGluco contains fonts from Noto Sans, which is licensed under the
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SIL Open Font License version 1.1
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<http://scripts.sil.org/cms/scripts/page.php?site_id=nrsi&id=OFL>,
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IcoGluco contains fonts from Noto Sans, as well as
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green apple character from Vectors Market <https://www.flaticon.com/authors/vectors-market>,
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as well as a green apple character from
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Vectors Market <https://www.flaticon.com/authors/vectors-market>,
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licensed under Creative Commons BY 3.0, <http://creativecommons.org/licenses/by/3.0/>, and
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syringe and pushpin characters from FreePik, <http://www.freepik.com>,
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licensed under Creative Commons BY 3.0, <http://creativecommons.org/licenses/by/3.0/>
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licensed under Creative Commons BY 3.0, <http://creativecommons.org/licenses/by/3.0/>.
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'''
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# TODO: weekly graph with each day's figures as a different-coloured line
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# TODO: Split each type of charts into a separate function and offer a means
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# of selecting which charts to generate
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import argparse
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import csv
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@ -80,6 +83,10 @@ def main():
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for row in rows:
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row = parse_entry(row, args.icons)
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''' Fill in gaps that might exist in the data, in order to smooth the curves and fills '''
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''' We're using 8 minute gaps in order to have more accurate fills '''
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rows = fill_gaps(rows, interval=dt.timedelta(minutes=10))
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''' If we're on the default values for units, highs and lows, check that the average
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value is under 35 (assuming that average mmol/L < 35 and average mg/dL > 35) '''
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if args.units == UNIT_MMOLL and (args.high == DEFAULT_HIGH or args.low == DEFAULT_LOW):
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@ -92,16 +99,6 @@ def main():
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args.graph_max = GRAPH_MAX_MGDL
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args.graph_min = GRAPH_MIN_MGDL
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''' Fill in gaps that might exist in the data, in order to smooth the curves and fills '''
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''' We're using 8 minute gaps in order to have more accurate fills '''
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rows = fill_gaps(rows, interval=dt.timedelta(minutes=10))
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''' Calculate the days and weeks in which we are interested '''
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''' Note that trim_weeks should be adjusted based on the interval passed to fill_gaps() '''
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(days, weeks) = list_days_and_weeks(rows, trim_weeks=300)
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totalweeks = sum([len(weeks[y]) for y in weeks])
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totaldays = len(days)
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''' Set some defaults '''
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rcParams['font.size'] = 8
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rcParams['axes.titlesize'] = 12
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@ -116,15 +113,21 @@ def main():
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custom icons on IcoMoon, works around this. '''
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if args.icons:
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args.customfont = import_font('fonts/icogluco.ttf')
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#args.customfont = import_font('fonts/OpenSansEmoji.ttf') # Alternate working font
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#args.customfont = import_font('fonts/OpenSansEmoji.ttf') # Alternate font
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''' Calculate the days and weeks in which we are interested '''
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''' Note that trim_weeks should be adjusted based on the interval passed to fill_gaps() '''
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(days, weeks) = list_days_and_weeks(rows, trim_weeks=300)
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totalweeks = sum([len(weeks[y]) for y in weeks])
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totaldays = len(days)
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nrows = args.graphs_per_page
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ncols = 1
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plotnum = 1
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with FigurePDF(args.output_file) as pdf:
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''' Overall averages for all data by hour '''
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title = 'Overall Average Daily Glucose Summary'
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''' Overall averages for all data by hour of the day '''
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title = 'Overall Average Glucose Summary'
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data = {}
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for row in rows:
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@ -144,7 +147,7 @@ def main():
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'min' : intervals.get(i).get('min'),
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}
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''' Calculate the mean and median blood glucose levels for the day '''
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''' Calculate the mean and median blood glucose and HbA1c levels '''
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(g_mean, g_median, a_mean, a_median) = calculate_averages(data, args)
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figure = Figure(figsize=args.pagesize)
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@ -155,9 +158,10 @@ def main():
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figure.set_tight_layout({'pad':3})
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''' Draw the target range '''
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ax.axhspan(args.low, args.high, facecolor='#0072b2', edgecolor='#a8a8a8', alpha=0.2, zorder=5)
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ax.axhspan(args.low, args.high, facecolor='#0072b2', edgecolor='#a8a8a8', alpha=0.1, zorder=5)
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''' The maxmined curve of maximum and minimum values '''
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''' The maxmin curve (maximum and minimum values for each 15 minute
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period of the data set, by day) '''
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generate_plot(intervaldata,
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ax=ax,
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transforms={'spline':False, 'maxmin':True},
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@ -166,6 +170,8 @@ def main():
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alpha=0.5,
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)
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''' The graph with a bezier curve applied, and a boundary transform to change line colour
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above and below the target values '''
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generate_plot(data,
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ax=ax,
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transforms={'bezier':True, 'avga1c':a_median, \
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@ -178,7 +184,8 @@ def main():
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pdf.savefig(figure)
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ax.clear()
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''' Overall averages for a week by hour '''
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''' Overall averages for a week by hour of the dday '''
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cnt = 0
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for year in reversed(sorted(weeks.keys())):
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for week in reversed(sorted(weeks[year].keys())):
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@ -187,7 +194,7 @@ def main():
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monday = time + dt.timedelta(days=-time.weekday(), weeks=week-1)
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sunday = monday + dt.timedelta(days=6)
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period = monday.strftime('%A, %-d %B %Y') + ' to ' + sunday.strftime('%A, %-d %B %Y');
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title = 'Average Daily Glucose for ' + period
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title = 'Average Glucose for ' + period
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weekrows = []
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for row in rows:
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@ -204,6 +211,8 @@ def main():
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'comment' : row.get('comment'),
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}
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''' Calculate the maximum and minimum value for each 15-minute period
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of the day, across the week '''
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intervals = calculate_max_min(weekrows)
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intervaldata = {}
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for i in intervals:
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@ -213,7 +222,7 @@ def main():
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'min' : intervals.get(i).get('min'),
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}
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''' Calculate the mean and median blood glucose levels for the day '''
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''' Calculate the mean and median blood glucose levels for the week '''
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(g_mean, g_median, a_mean, a_median) = calculate_averages(data, args)
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if cnt % nrows == 0:
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@ -226,7 +235,7 @@ def main():
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figure.set_tight_layout({'pad':3})
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''' Draw the target range '''
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ax.axhspan(args.low, args.high, facecolor='#0072b2', edgecolor='#a8a8a8', alpha=0.2, zorder=5)
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ax.axhspan(args.low, args.high, facecolor='#0072b2', edgecolor='#a8a8a8', alpha=0.1, zorder=5)
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''' The maxmined curve of maximum and minimum values '''
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generate_plot(intervaldata,
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@ -237,6 +246,8 @@ def main():
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alpha=0.5,
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)
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''' The graph with a bezier curve applied, and a boundary transform to change line colour
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above and below the target values '''
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generate_plot(data,
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ax=ax,
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transforms={'bezier':True, \
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@ -280,19 +291,20 @@ def main():
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''' Draw the target range '''
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ax.axhspan(args.low, args.high, facecolor='#0072b2', edgecolor='#a8a8a8', alpha=0.2, zorder=5)
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''' Draw graph with a spline tranform and labels '''
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generate_plot(data,
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ax=ax,
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transforms={'spline':True, 'label':True, 'avgglucose':g_median, 'avga1c':a_median},
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args=args,
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color=BLUE,
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)
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)
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''' For max higher than target high '''
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''' Fill the chart with colour when line is higher or lower than target range '''
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generate_plot(data,
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ax=ax,
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transforms={'spline':True, 'fill':True},
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args=args,
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)
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)
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''' Save the graph to the output PDF if we're at the end of the page '''
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if (cnt + 1) % nrows == 0 or (cnt + 1) == totaldays:
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@ -367,7 +379,7 @@ def generate_plot(data, ax=None, transforms={}, args=[], **plot_args):
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else:
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maxmin = False
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''' Process points to apply smoothing and other fixups '''
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''' Transform points to apply smoothing and other fixups '''
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for transform in transforms:
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if transform == 'linear' and transforms.get(transform) is True:
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''' Use SciPy's interp1d for linear transforming '''
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@ -379,10 +391,11 @@ def generate_plot(data, ax=None, transforms={}, args=[], **plot_args):
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elif transform == 'spline' and transforms.get(transform) is True:
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''' Use SciPy's UnivariateSpline for transforming (s is transforming factor) '''
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''' An s of 8 (mmol/L) or 200 (mg/dL) was chosen by experimentation! '''
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if args.units == UNIT_MMOLL:
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s = 8
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else:
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s = convert_glucose_unit(12, UNIT_MMOLL)
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s = 200
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if not maxmin:
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curve = interpolate.UnivariateSpline(x=x, y=y, k=3, s=s)
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y = curve(x)
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@ -399,7 +412,7 @@ def generate_plot(data, ax=None, transforms={}, args=[], **plot_args):
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''' The binomial calculation for the bezier curve overflows with arrays of 1020 or more elements,
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For large arrays, get a smaller slice of the full array.
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Do this by removing every nth element from the array '''
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Do this by removing every nth element from the array. '''
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n = 5
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while len(x) > 1000:
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x = np.delete(x, np.arange(0, len(x), n), axis=0)
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@ -409,21 +422,22 @@ def generate_plot(data, ax=None, transforms={}, args=[], **plot_args):
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curve = np.array([c for _, c in bezier(np.array([x,y]).T, 250)])
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(x, y) = (curve[:,0], curve[:,1])
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''' Add the mean or median glucose and A1c values '''
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''' Add the mean or median glucose and A1c values in an annotation box '''
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if transform == 'avgglucose' and isinstance(transforms.get(transform), (int, float)):
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if args.units == UNIT_MMOLL:
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gmtext = 'Median glucose: %.1f%s' % (round(transforms.get('avgglucose'), 1), args.units)
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else:
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gmtext = 'Median glucose: %.0f%s' % (round(transforms.get('avgglucose'), 1), args.units)
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ax.annotate(gmtext, fontsize=9, \
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xy=(0.95, 0.85), xycoords='axes fraction', verticalalignment='top', horizontalalignment='right', \
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zorder=40, bbox=dict(facecolor=GREEN, edgecolor='#009e73', alpha=0.7, pad=8), \
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)
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ax.annotate(gmtext, fontsize=9, xy=(0.95, 0.85),
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xycoords='axes fraction', verticalalignment='top', horizontalalignment='right',
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zorder=40, bbox=dict(facecolor=GREEN, edgecolor='#009e73', alpha=0.7, pad=8),
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)
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if transform == 'avga1c' and isinstance(transforms.get(transform), (int, float)):
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ax.annotate('Median HbA1c: %.1f%%' % round(transforms.get('avga1c'), 1), fontsize=9, \
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xy=(0.05, 0.85), xycoords='axes fraction', verticalalignment='top', horizontalalignment='left', \
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zorder=40, bbox=dict(facecolor=BOXYELLOW, edgecolor='#e69f00', alpha=0.7, pad=8), \
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ax.annotate('Median HbA1c: %.1f%%' % round(transforms.get('avga1c'), 1), fontsize=9,
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xy=(0.05, 0.85), xycoords='axes fraction',
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verticalalignment='top', horizontalalignment='left',
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zorder=40, bbox=dict(facecolor=BOXYELLOW, edgecolor='#e69f00', alpha=0.7, pad=8),
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)
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if args.units == UNIT_MMOLL:
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@ -434,14 +448,13 @@ def generate_plot(data, ax=None, transforms={}, args=[], **plot_args):
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if transform == 'label' and transforms.get(transform) is True and args.icons is True:
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for x_pos, y_pos, label in zip(x, y, z):
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if isinstance(label, dict) and len(label) > 0:
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symbol = ''
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symbol = '$'
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for key in label:
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''' In the included IcoGluco font use for args.customfont,
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\N{SYRINGE} is a straight syringe (from FreePik),
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\N{PUSHPIN} is a an angled syringe (from FreePik),
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\N{DAGGER} is unused,
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\N{GREEN APPLE} is an apple (from Vectors Market. '''
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\N{SYRINGE} is a straight syringe (modified from FreePik) for rotated labels,
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\N{PUSHPIN} is a an angled syringe (from FreePik) for horizontal labels,
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\N{DAGGER} is unused (reserved a different syringe icon),
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\N{GREEN APPLE} is an apple (from Vectors Market). '''
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if key == 'Insulin':
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if isinstance(label.get(key), str):
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symbol += '\N{SYRINGE}^{%s}' % label.get(key)
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@ -452,13 +465,9 @@ def generate_plot(data, ax=None, transforms={}, args=[], **plot_args):
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elif key == 'Food':
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symbol += '\N{GREEN APPLE}'
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symbol += '$'
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ax.annotate(
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symbol,
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xy=(x_pos, args.graph_max-y_offset),
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rotation=45,
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zorder=25,
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fontsize=10,
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fontproperties=args.customfont,
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ax.annotate(symbol, xy=(x_pos, args.graph_max-y_offset),
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rotation=45, zorder=25, fontsize=10,
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fontproperties=args.customfont,
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)
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''' Create a line coloured according to the list in transforms['color'] '''
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@ -493,8 +502,8 @@ def generate_plot(data, ax=None, transforms={}, args=[], **plot_args):
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def import_font(fontname):
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''' Turns a relative font path into a matplotlib font property. '''
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basedir = os.path.dirname(os.path.abspath(__file__))
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fontpath = os.path.join(basedir, fontname)
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basedir = os.path.dirname(os.path.abspath(__file__))
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fontpath = os.path.join(basedir, fontname)
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if not os.path.exists(fontpath):
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raise UserError("Font %s does not exist" % fontpath)
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prop = fm.FontProperties(fname=fontpath)
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@ -516,13 +525,13 @@ def parse_entry(data, icons, fmt='%Y-%m-%d %H:%M:%S'):
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'''
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if icons:
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''' Ignore comments that aren't relevant '''
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rrelevant = re.compile('(Food|Rapid-acting insulin|Long-acting insulin)(?: \((.*?)\))', flags=re.IGNORECASE)
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rduplicate = re.compile('^(I\$\^\{\d+\S?)(\}.*)$')
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rrelevant = re.compile('(Food|Rapid-acting insulin|Long-acting insulin)(?: \((.*?)\))', flags=re.IGNORECASE)
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rduplicate = re.compile('^(I\$\^\{\d+\S?)(\}.*)$')
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commentparts = {}
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for part in data.get('comment').split('; '):
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relevant = rrelevant.search(part)
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if relevant is not None:
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ctype = relevant.group(1)
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ctype = relevant.group(1)
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cvalue = relevant.group(2)
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''' Convert floating point-style strings (2.0) to integer-style strings (2) '''
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@ -828,6 +837,9 @@ def convert_glucose_unit(value, from_unit, to_unit=None):
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Raises:
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exceptions.InvalidGlucoseUnit: If the parameters are incorrect.
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Note that this is defined by the main glucometerutils package, from which
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this function is duplicated, and is not a valid exception for this script.
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So let's hope it doesn't get triggered!
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"""
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if from_unit not in VALID_UNITS:
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raise exceptions.InvalidGlucoseUnit(from_unit)
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