Article Outline
Example Python program colormap_calendar.py
Modules
- import pandas, pdb, os, csv, datetime, numpy, brewer2mpl
- import matplotlib.pyplot as plt
- import matplotlib.colorbar as cbar
- from matplotlib import rcParams
- import palettable
- from dateutil import rrule
- import matplotlib
- import calendar
Methods
- def set_matplotlib_params():
- def get_colors():
- def draw_calendar(ax,df,horz):
- def draw_daily_lines(ax,df,horz, num_weeks):
- def draw_month_boundary(ax,df,horz):
Code
Python example
import pandas, pdb, os, csv, datetime, numpy, brewer2mpl
import matplotlib.pyplot as plt
import matplotlib.colorbar as cbar
from matplotlib import rcParams
import palettable
from dateutil import rrule
import matplotlib
import calendar
def set_matplotlib_params():
"""
Set matplotlib defaults to nicer values
"""
# rcParams dict
rcParams['mathtext.default'] ='regular'
rcParams['axes.labelsize'] = 11
rcParams['xtick.labelsize'] = 11
rcParams['ytick.labelsize'] = 11
rcParams['legend.fontsize'] = 11
rcParams['font.family'] = 'sans-serif'
rcParams['font.serif'] = ['Helvetica']
rcParams['figure.figsize'] = 7.3, 4.2
###############################################################################
#
#
#
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def get_colors():
"""
Get palettable colors, which are nicer
"""
bmap=palettable.colorbrewer.sequential.BuPu_9.mpl_colors
return bmap
###############################################################################
#
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#
#
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def draw_calendar(ax,df,horz):
for i in range(len(df.index)):
if(df[col_name][i] > 0):
cur_wk = datetime.date(df.YEAR[i],df.MONTH[i],df.DAY[i]).isocalendar()[1]
cur_yr = datetime.date(df.YEAR[i],df.MONTH[i],df.DAY[i]).isocalendar()[0]
if((cur_yr < df.YEAR[i]) and (df.DAY[i]<7)):
cur_wk = 0
if(cur_yr>df.YEAR[i]):
cur_wk = 53
day_of_week = df.index[i].weekday()
#normalise each data point to val - note added a very small amount
#to data range, so that we never get exactly 1.0
val = float((df[col_name][i]-min_val)/float(max_val-min_val + 0.000001))
if(horz):
rect = matplotlib.patches.Rectangle((cur_wk,day_of_week), 1, 1, color = color_list[int(val*color_len)])
else:
rect = matplotlib.patches.Rectangle((day_of_week,cur_wk), 1, 1, color = color_list[int(val*color_len)],label='a')
ax.add_patch(rect)
###############################################################################
#
#
#
#
###############################################################################
def draw_daily_lines(ax,df,horz, num_weeks):
clr = 'w'
wth = 0.5
stl = '-'
# Draw calendar grid
for i in range(int(num_weeks)):
ax.plot([0,7],[i,i],color=clr,linestyle=stl,lw=wth)
for j in range(7):
ax.plot([j,j],[0,num_weeks],color=clr,linestyle=stl,lw=wth)
pass
###############################################################################
#
#
#
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def draw_month_boundary(ax,df,horz):
clr = 'w'
wth = 1.25
stl = '-'
month_seq = rrule.rrule(rrule.MONTHLY,dtstart=df.index[0],until=df.index[len(df.index)-1])
for mon in month_seq:
num_days = calendar.monthrange(mon.year,mon.month)[1]
cur_wk = datetime.date(mon.year,mon.month,num_days).isocalendar()[1]
cur_yr = datetime.date(mon.year,mon.month,num_days).isocalendar()[0]
day_of_week = datetime.date(mon.year,mon.month,num_days).weekday()
if(cur_yr == mon.year and (mon.month <> 12)):
if(horz):
ax.plot([cur_wk+1,cur_wk+1],[0,day_of_week+1],color=clr,linestyle=stl,lw=wth)
else:
ax.plot([0,day_of_week+1],[cur_wk+1,cur_wk+1],color=clr,linestyle=stl,lw=wth)
if (day_of_week != 6):
if(horz):
ax.plot([cur_wk+1,cur_wk],[day_of_week+1,day_of_week+1],color=clr,linestyle=stl,lw=wth) # Parallel to X-Axis
ax.plot([cur_wk,cur_wk],[day_of_week+1,7],color=clr,linestyle=stl,lw=wth)
else:
ax.plot([day_of_week+1,day_of_week+1],[cur_wk+1,cur_wk],color=clr,linestyle=stl,lw=wth) # Parallel to Y-axis
ax.plot([day_of_week+1,7],[cur_wk,cur_wk],color=clr,linestyle=stl,lw=wth)
if __name__ == '__main__':
col_name = 'NMN'
horz = False
df = pandas.read_csv('94.DGN',skiprows=10,delim_whitespace=True,usecols=['Y','M','D','BIOM','NMN','DN'])
df.rename(columns={'Y':'YEAR','M':'MONTH','D':'DAY'}, inplace=True)
df['datetime'] = df[['YEAR', 'MONTH', 'DAY']].apply(lambda s : datetime.datetime(*s),axis=1)
df = df.set_index('datetime')
num_yrs = len(df['YEAR'].unique())
max_val = max(df[col_name])
min_val = min(df[col_name])
color_list = get_colors()
color_len = len(color_list)
# Draw blank figure
fig = plt.figure()
set_matplotlib_params()
plt.subplots_adjust(hspace=0.3)
#plt.axis('off')
plt.axes().set_aspect('equal')
idx = 0
for i in df['YEAR'].unique():
sub_df = df[df['YEAR']==i]
start_date = sub_df.index[0]
end_date = sub_df.index[len(sub_df.index)-1]
diff = end_date - start_date
diff = numpy.timedelta64(diff)
num_weeks = numpy.ceil(diff/(numpy.timedelta64(1,'W')))+2
if(horz):
ax = plt.subplot2grid((num_yrs,4),(1,idx),colspan=2,rowspan=1)
else:
ax = plt.subplot2grid((4,num_yrs),(1,idx),rowspan=2,colspan=1)
ax.xaxis.tick_top()
ax.axes.get_xaxis().set_ticks([])
ax.axes.get_yaxis().set_ticks([])
ax.axis('off')
ax.set_title(str(i),fontsize=12)
if (horz):
plt.xlim(0,num_weeks)
plt.ylim(0,7)
else:
plt.xlim(0,7)
plt.ylim(num_weeks,0)
if(i == max(df['YEAR'].unique())):
plt.text(8,3,'Jan',fontsize=10)
plt.text(8,8,'Feb',fontsize=10)
plt.text(8,12,'Mar',fontsize=10)
plt.text(8,16,'Apr',fontsize=10)
plt.text(8,21,'May',fontsize=10)
plt.text(8,25,'Jun',fontsize=10)
plt.text(8,29,'Jul',fontsize=10)
plt.text(8,34,'Aug',fontsize=10)
plt.text(8,38,'Sept',fontsize=10)
plt.text(8,42,'Oct',fontsize=10)
plt.text(8,47,'Nov',fontsize=10)
plt.text(8,51,'Dec',fontsize=10)
draw_calendar(ax,sub_df,horz)
draw_daily_lines(ax,sub_df,horz, num_weeks)
draw_month_boundary(ax,sub_df,horz)
print idx, i
idx += 1
# plot an overall colorbar type legend
ax_colorbar = plt.subplot2grid((4,num_yrs), (3,0),rowspan=1,colspan=num_yrs)
mappableObject = matplotlib.cm.ScalarMappable(cmap = palettable.colorbrewer.sequential.BuPu_9.mpl_colormap)
mappableObject.set_array(numpy.array(df[col_name]))
col_bar = fig.colorbar(mappableObject, cax = ax_colorbar, orientation = 'horizontal', boundaries = numpy.arange(min_val,max_val,(max_val-min_val)/10))
# You can change the boundaries kwarg to either make the scale look less boxy (increase 10)
# or to get different values on the tick marks, or even omit it altogether to let
col_bar.set_label(col_name)
ax_colorbar.set_title(col_name + ' color mapping')
#print min_val
#print max_val
#plt.gca().legend(loc="upper right")
#draw the top overall graph
ax0 = plt.subplot2grid((4,num_yrs), (0,0),rowspan=1,colspan=num_yrs)
x_axis = numpy.arange(0.325,num_yrs+1,1.1)
bar_val = df[col_name].groupby(df['YEAR']).mean()
err_val = df[col_name].groupby(df['YEAR']).std()
ax0.bar(x_axis,bar_val,yerr=err_val,linewidth=0,width=0.25,color='g',
error_kw=dict(ecolor='gray', lw=1))
ax0.axes.get_xaxis().set_ticks([])
ax0.spines['top'].set_visible(False)
ax0.spines['right'].set_visible(False)
plt.ylabel(col_name)
ax0.axes.get_yaxis().set_ticks([])
#plt.tight_layout()
plt.savefig('aaa.png',dpi=900,frameon=False)
#plt.show()
plt.close()Useful Links
- Articles: https://python-commandments.org/
- Python shell: https://bsdnerds.org/learn-python/
- Tutorial: https://pythonprogramminglanguage.com/