Add font icons sets for labels.

glucometer_graphs.py

@@ -19,10 +19,14 @@ from matplotlib.backends.backend_pdf import PdfPages as FigurePDF
 from matplotlib.collections import LineCollection
 from matplotlib.colors import ListedColormap, BoundaryNorm
 from matplotlib import dates as mdates
+from matplotlib import font_manager as fm
+from matplotlib import image
 from matplotlib.patches import Circle, PathPatch
 from matplotlib.path import Path
 from matplotlib import ticker as mticker
+from matplotlib.offsetbox import (OffsetImage, AnnotationBbox)
 import numpy as np
+import os
 import re
 from scipy import interpolate
 from scipy.special import binom
@@ -72,7 +76,7 @@ def main():
   # If we're on the default values for units, highs and lows, check that the average
   # value is under 35 (assuming that average mmol/L < 35 and average mg/dL > 35)
   if args.units == UNIT_MMOLL and (args.high == DEFAULT_HIGH or args.low == DEFAULT_LOW):
-    mean = round(np.mean([l['value'] for l in rows]), 1)
+    mean = round(np.mean([l.get('value') for l in rows]), 1)
     if mean > 35:
       args.units = UNIT_MGDL
       args.high  = convert_glucose_unit(args.high, UNIT_MMOLL)
@@ -96,11 +100,12 @@ def main():
   rcParams['axes.titlesize'] = 12
   rcParams['font.family'] = 'sans-serif'
   rcParams['font.sans-serif'] = ['Calibri','Verdana','Geneva','Arial','Helvetica','DejaVu Sans','Bitstream Vera Sans','sans-serif']
-  ''' Misuse the mathtext "mathcal" definition for the Unicode characters in Symbola '''
-  rcParams['mathtext.fontset'] = 'custom'
-  rcParams['mathtext.cal'] = 'Symbola'
   rcParams['mathtext.default'] = 'regular'
 
+  # Load custom fonts for the icon sets
+  if args.icons:
+    args.customfont = import_font('fonts/icogluco.ttf') # Works
+    #args.customfont = import_font('fonts/OpenSansEmoji.ttf') # Alternate working font
 
   nrows = args.graphs_per_page
   ncols = 1
@@ -311,9 +316,6 @@ def generate_plot(data, ax=None, transforms={}, args=[], **plot_args):
   ''' Don't convert z to a numpy array if it has text in it '''
   if len(z) > 0 and isinstance(z[0], (int, float)):
     z = np.asarray(z)
-  else:
-    z = np.asarray(z, dtype='unicode_')
-
 
   ''' Calculations the axis limits '''
   firstminute = mdates.num2date(x[0]).replace(hour=0, minute=0, second=0, microsecond=0)
@@ -351,21 +353,21 @@ def generate_plot(data, ax=None, transforms={}, args=[], **plot_args):
   ax.yaxis.set_ticks_position('none')
 
 
-  if 'maxmin' in transforms and transforms['maxmin'] is True:
+  if 'maxmin' in transforms and transforms.get('maxmin') is True:
     maxmin = True
   else:
     maxmin = False
 
   ''' Process points to apply smoothing and other fixups '''
   for transform in transforms:
-    if transform == 'linear' and transforms[transform] is True:
+    if transform == 'linear' and transforms.get(transform) is True:
       ''' Use SciPy's interp1d for linear transforming '''
       if not maxmin:
         f = interpolate.interp1d(x, y, kind='linear')
         x = np.linspace(x.min(), x.max(), 50) # 50 is number of points to make between x.max & x.min
         y = f(x)
 
-    elif transform == 'spline' and transforms[transform] is True:
+    elif transform == 'spline' and transforms.get(transform) is True:
       ''' Use SciPy's UnivariateSpline for transforming (s is transforming factor) '''
       if args.units == UNIT_MMOLL:
         s = 8
@@ -375,7 +377,7 @@ def generate_plot(data, ax=None, transforms={}, args=[], **plot_args):
         curve = interpolate.UnivariateSpline(x=x, y=y, k=3, s=s)
         y = curve(x)
 
-    elif transform == 'bezier' and transforms[transform] is True:
+    elif transform == 'bezier' and transforms.get(transform) is True:
       ''' Create bezier function for transforming (s is transforming factor) '''
       def bezier(points, s=100):
         n = len(points)
@@ -398,18 +400,18 @@ def generate_plot(data, ax=None, transforms={}, args=[], **plot_args):
         (x, y) = (curve[:,0], curve[:,1])
 
     ''' Add the mean or median glucose and A1c values '''
-    if transform == 'avgglucose' and isinstance(transforms[transform], (int, float)):
+    if transform == 'avgglucose' and isinstance(transforms.get(transform), (int, float)):
       if args.units == UNIT_MMOLL:
-        gmtext = 'Median glucose: %.1f%s' % (round(transforms['avgglucose'], 1), args.units)
+        gmtext = 'Median glucose: %.1f%s' % (round(transforms.get('avgglucose'), 1), args.units)
       else:
-        gmtext = 'Median glucose: %.0f%s' % (round(transforms['avgglucose'], 1), args.units)
+        gmtext = 'Median glucose: %.0f%s' % (round(transforms.get('avgglucose'), 1), args.units)
 
       ax.annotate(gmtext, fontsize=9, \
           xy=(0.95, 0.85), xycoords='axes fraction', verticalalignment='top', horizontalalignment='right', \
           zorder=40, bbox=dict(facecolor=GREEN, edgecolor='#009e73', alpha=0.7, pad=8), \
       )
-    if transform == 'avga1c' and isinstance(transforms[transform], (int, float)):
+    if transform == 'avga1c' and isinstance(transforms.get(transform), (int, float)):
-      ax.annotate('Median HbA1c: %.1f%%' % round(transforms['avga1c'], 1), fontsize=9, \
+      ax.annotate('Median HbA1c: %.1f%%' % round(transforms.get('avga1c'), 1), fontsize=9, \
           xy=(0.05, 0.85), xycoords='axes fraction', verticalalignment='top', horizontalalignment='left', \
           zorder=40, bbox=dict(facecolor=BOXYELLOW, edgecolor='#e69f00', alpha=0.7, pad=8), \
           )
@@ -422,21 +424,56 @@ def generate_plot(data, ax=None, transforms={}, args=[], **plot_args):
     else:
       y_offset = convert_glucose_unit(6, UNIT_MMOLL)
 
-    if transform == 'label' and transforms[transform] is True:
+    if transform == 'label' and transforms.get(transform) is True and args.icons is True:
       for x_pos, y_pos, label in zip(x, y, z):
-        if len(label) > 0:
+        if isinstance(label, dict) and len(label) > 0:
-          #print(label)
+          symbol = ''
+          symbol = '$'
+          for key in label:
+            ''' In the included IcoGluco font use for args.customfont, 
+                \N{SYRINGE} is a straight syringe (from FreePik),
+                \N{PUSHPIN} is a an angled syringe (from FreePik),
+                \N{DAGGER} is unused,
+                \N{GREEN APPLE} is an apple (from Vectors Market. '''
+            if key == 'Insulin':
+              if isinstance(label.get(key), str):
+                symbol += '\N{SYRINGE}^{%s}' % label.get(key)
+                #symbol += '\N{PUSHPIN}^{%s}' % label.get(key)
+                #symbol += '\N{SYRINGE}'
+              else:
+                symbol += '\N{SYRINGE}'
+            elif key == 'Food':
+              symbol += '\N{GREEN APPLE}'
+          symbol += '$'
+          print(symbol)
           ax.annotate(
-            label,
+            symbol,
             xy=(x_pos, args.graph_max-y_offset),
             rotation=45,
             zorder=25,
+            fontsize=10,
+            fontproperties=args.customfont,
             )
+        '''
+        if len(label) > 0:
+          if re.sub('F', '', label):
+            imagebox = OffsetImage(apple, axes=ax, zoom=.1, filternorm=None)
+          elif re.sub('I', '', label):
+            imagebox = OffsetImage(syringe, axes=ax, zoom=.1)
+          ab = AnnotationBbox(
+            imagebox,
+            xy=(x_pos, args.graph_max-y_offset),
+            frameon=False,
+            )
+          ab.zorder = 25
+          ax.add_artist(ab)
+        '''
+
 
     ''' Create a line coloured according to the list in transforms['color'] '''
     if transform == 'boundaries' and 'color' in transforms:
-      cmap = ListedColormap(transforms['color'])
+      cmap = ListedColormap(transforms.get('color'))
-      norm = BoundaryNorm(transforms['boundaries'], cmap.N)
+      norm = BoundaryNorm(transforms.get('boundaries'), cmap.N)
       ''' create an array of points on the plot, and split into segments '''
       p = np.array([x, y]).T.reshape(-1, 1, 2)
       segments = np.concatenate([p[:-1], p[1:]], axis=1)
@@ -448,7 +485,7 @@ def generate_plot(data, ax=None, transforms={}, args=[], **plot_args):
   if 'boundaries' in transforms and 'color' in transforms:
     ax.add_collection(lc)
 
-  elif 'fill' in transforms and transforms['fill'] is True:
+  elif 'fill' in transforms and transforms.get('fill') is True:
     z = np.clip(y, None, args.high)
     ax.fill_between(x, y, z, interpolate=True, facecolor=YELLOW, alpha=0.7, zorder=12, **plot_args)
 
@@ -463,6 +500,23 @@ def generate_plot(data, ax=None, transforms={}, args=[], **plot_args):
 
   return ax
 
+def import_icon(filename):
+  basedir   = os.path.dirname(os.path.abspath(__file__))
+  filepath  = os.path.join(basedir, filename)
+  if not os.path.exists(filepath):
+    raise UserError("Image %s does not exist" % filepath)
+  icon = image.imread(filepath, format='png')
+  return icon
+
+def import_font(fontname):
+  basedir   = os.path.dirname(os.path.abspath(__file__))
+  fontdir   = os.path.join(basedir, 'fonts')
+  fontpath  = os.path.join(fontdir, fontname)
+  if not os.path.exists(fontpath):
+    raise UserError("Font %s does not exist" % fontpath)
+  prop = fm.FontProperties(fname=fontpath)
+  return prop
+
 def parse_entry(data, icons, fmt='%Y-%m-%d %H:%M:%S'):
   ''' Parse a row to create the icons and modify the timestamp
 
@@ -478,17 +532,24 @@ def parse_entry(data, icons, fmt='%Y-%m-%d %H:%M:%S'):
       ValueError if an incorrectly-formatted date exists in data['timestamp']
   '''
   if icons:
-    # Ignore comments that aren't relevant
+    ''' Ignore comments that aren't relevant '''
     rrelevant     = re.compile('(Food|Rapid-acting insulin|Long-acting insulin)(?: \((.*?)\))', flags=re.IGNORECASE)
-    rduplicate    = re.compile('.*?(\N{SYRINGE})')
+    rduplicate    = re.compile('^(I\$\^\{\d+\S?)(\}.*)$')
-    comment_parts = []
+    commentparts = {}
-    for comment_part in data.get('comment').split('; '):
+    for part in data.get('comment').split('; '):
-      relevant   = rrelevant.search(comment_part)
+      relevant   = rrelevant.search(part)
       if relevant is not None:
         ctype = relevant.group(1)
         cvalue = relevant.group(2)
 
-        cvalue = re.sub('(\d+)(\.\d+)?', '\g<1>', cvalue)
+        #cvalue = re.sub('(\d+)(\.\d+)?', '\g<1>', cvalue)
+        ''' Convert floating point-style strings (2.0) to integer-style strings (2) '''
+        try:
+          cvalue = int(float(cvalue))
+        except:
+          pass
+        cvalue = str(cvalue)
+
         if re.search('Rapid', ctype) is not None:
           cvalue += 'R'
         if re.search('Long', ctype) is not None:
@@ -498,22 +559,20 @@ def parse_entry(data, icons, fmt='%Y-%m-%d %H:%M:%S'):
         # unicode chacters that lack proper glyph names are massed together and printed
         # as the same character
         # XXX Alternatives include replacing the glyph with an image, or a Path
-        ctype = re.sub('Food', '$\mathcal{\N{GREEN APPLE}}$', ctype, flags=re.IGNORECASE)
+        #ctype = re.sub('Food', '$\mathcal{\N{GREEN APPLE}}$', ctype, flags=re.IGNORECASE)
-        ctype = re.sub('Rapid-acting insulin', '$\mathcal{\N{SYRINGE}}^\mathrm{'+cvalue+'}$', ctype, flags=re.IGNORECASE)
+        #ctype = re.sub('Rapid-acting insulin', '$\mathcal{\N{SYRINGE}}^\mathrm{'+cvalue+'}$', ctype, flags=re.IGNORECASE)
-        ctype = re.sub('Long-acting insulin', '$\mathcal{\N{SYRINGE}}^\mathrm{'+cvalue+'}$', ctype, flags=re.IGNORECASE)
+        #ctype = re.sub('Long-acting insulin',  '$\mathcal{\N{SYRINGE}}^\mathrm{'+cvalue+'}$', ctype, flags=re.IGNORECASE)
-        #ctype = re.sub('Rapid-acting insulin', '$\mathcal{💉}$', ctype, flags=re.IGNORECASE)
+        ctype = re.sub('Rapid-acting insulin', 'Insulin', ctype, flags=re.IGNORECASE)
-        #ctype = re.sub('Long-acting insulin', '$\mathcal{💉}$', ctype, flags=re.IGNORECASE)
+        ctype = re.sub('Long-acting insulin',  'Insulin', ctype, flags=re.IGNORECASE)
 
-        idx = [i for i, x in enumerate(comment_parts) if rduplicate.search(x)]
+        if ctype in commentparts:
-        if idx:
+          commentparts[ctype] = commentparts[ctype] + '/' + cvalue
-          comment_parts[idx[0]] = re.sub('^(.*?\d+\S?)(.*)$', '\g<1>/'+cvalue+'\g<2>', comment_parts[idx[0]])
         else:
-          comment_parts.append(ctype)
+          commentparts[ctype] = cvalue
 
-    comment = ''.join(comment_parts)
+    data['comment'] = commentparts
-    data['comment'] = comment
   else:
-    data['comment'] = ''
+    data['comment'] = {}
 
   ''' Convert timestamp to ISO8601 (by default, at least), and store datetime object '''
   try:
@@ -655,14 +714,14 @@ def fill_gaps(rows, interval, maxinterval=dt.timedelta(days=1)):
       continue
 
     ''' If the next row has a time gap, create new rows to insert '''
-    if rows[i+1]['date'] - rows[i]['date'] > interval and \
+    if rows[i+1].get('date') - rows[i].get('date') > interval and \
-       rows[i+1]['date'] - rows[i]['date'] < maxinterval:
+       rows[i+1].get('date') - rows[i].get('date') < maxinterval:
 
-      n     = (rows[i+1]['date'] - rows[i]['date'])//interval
+      n     = (rows[i+1].get('date') - rows[i].get('date'))//interval
-      start = mdates.date2num(rows[i]['date'])
+      start = mdates.date2num(rows[i].get('date'))
-      end   = mdates.date2num(rows[i+1]['date'])
+      end   = mdates.date2num(rows[i+1].get('date'))
-      lower = rows[i]['value']
+      lower = rows[i].get('value')
-      upper = rows[i+1]['value']
+      upper = rows[i+1].get('value')
 
       ''' Calculate an range for each interval, assuming a straight line between the start and
           end of the gap.