Article Outline
Python matplotlib example 'colormap calendar'
Functions in program:
def draw_month_boundary(ax,df,horz):def draw_daily_lines(ax,df,horz, num_weeks):def draw_calendar(ax,df,horz):def get_colors():def set_matplotlib_params():
Modules used in program:
import calendarimport matplotlibimport palettableimport matplotlib.colorbar as cbarimport matplotlib.pyplot as pltimport pandas, pdb, os, csv, datetime, numpy, brewer2mpl
python colormap calendar
Python matplotlib example: colormap calendar
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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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)
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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()
Python links
- Learn Python: https://pythonbasics.org/
- Python Tutorial: https://pythonprogramminglanguage.com