def on_epoch_begin(self, epoch, logs={}):
self.target = self.params['samples']
self.progbar = ProgBar.Progbar(target=self.target,
newline_on_end=False)
self.seen = 0
self.progbar.last_run = 0
return
def BasicGraphs(GraphPath, Data):
"""Creates basic graphs
Creates graphs of the energy production
Only creates the graphs if they don't already exist
Creates:
Production graph of entire period
Monthly and Daily graphs of production
Parameters
----------
GraphPath : str
Path to save the graphs.
Data : array-like
The data to graph.
"""
pcount = 0
toCreate = 0
if not os.path.isfile(GraphPath + 'Monthly/Share2018-3.png'):
MonthGraphs = 60
else:
MonthGraphs = 0
if not os.path.isdir(GraphPath + 'Daily/'):
os.makedirs(GraphPath + 'Daily')
if not os.listdir(GraphPath + 'Daily'):
DayGraphs = 150
else:
DayGraphs = 0
if not os.path.isfile(GraphPath + 'Diesel.png'):
toCreate += 1
if not os.path.isfile(GraphPath + 'Wind.png'):
toCreate += 1
if not os.path.isfile(GraphPath + 'Water.png'):
toCreate += 1
if not os.path.isfile(GraphPath + 'Total.png'):
toCreate += 1
toCreate += MonthGraphs
toCreate += DayGraphs
#toCreate += 1
progbar = ProgBar.Progbar(target=toCreate,
newline_on_end=False,
text_description='Creating overview graphs: ')
years = mdates.YearLocator() # every year
months = mdates.MonthLocator() # every month
yearsFmt = mdates.DateFormatter('%Y')
plt.rcParams["figure.figsize"] = [16, 9]
if not os.path.isfile(GraphPath + 'Diesel.png'):
pcount += 1
#print('Creating diesel overview graph')
fig, ax = plt.subplots()
ax.plot(Data.index, Data.Diesel, color=Color1)
# format the ticks
ax.xaxis.set_major_locator(years)
ax.xaxis.set_major_formatter(yearsFmt)
ax.xaxis.set_minor_locator(months)
# round to nearest years...
datemin = np.datetime64(Data.index[0], 'Y')
datemax = np.datetime64(Data.index[-1], 'Y') + np.timedelta64(1, 'Y')
ax.set_xlim(datemin, datemax)
plt.title('Timeseries')
plt.xlabel('Time [date]')
plt.ylabel('Diesel production [% of total]')
ax.grid(which='major', alpha=1, color='black')
ax.grid(which='minor', alpha=0.05, color='black')
fig.autofmt_xdate()
plt.savefig(GraphPath + 'Diesel.png')
plt.close(fig)
progbar.update(pcount)
if not os.path.isfile(GraphPath + 'Wind.png'):
pcount += 1
#print('Creating Wind overview graph')
fig, ax = plt.subplots()
ax.plot(Data.index, Data.Wind, color=Color1)
# format the ticks
ax.xaxis.set_major_locator(years)
ax.xaxis.set_major_formatter(yearsFmt)
ax.xaxis.set_minor_locator(months)
# round to nearest years...
datemin = np.datetime64(Data.index[0], 'Y')
datemax = np.datetime64(Data.index[-1], 'Y')\
+ np.timedelta64(1, 'Y')
ax.set_xlim(datemin, datemax)
plt.title('Timeseries')
plt.xlabel('Time [date]')
plt.ylabel('Wind production [% of total]')
ax.grid(which='major', alpha=1, color='black')
ax.grid(which='minor', alpha=0.05, color='black')
fig.autofmt_xdate()
plt.savefig(GraphPath + 'Wind.png')
plt.close(fig)
progbar.update(pcount)
if not os.path.isfile(GraphPath + 'Water.png'):
pcount += 1
#print('Creating Water overview graph')
fig, ax = plt.subplots()
ax.plot(Data.index, Data.Water, color=Color1)
# format the ticks
ax.xaxis.set_major_locator(years)
ax.xaxis.set_major_formatter(yearsFmt)
ax.xaxis.set_minor_locator(months)
# round to nearest years...
datemin = np.datetime64(Data.index[0], 'Y')
datemax = np.datetime64(Data.index[-1], 'Y')\
+ np.timedelta64(1, 'Y')
ax.set_xlim(datemin, datemax)
plt.title('Timeseries')
plt.xlabel('Time [date]')
plt.ylabel('Water production [% of total]')
ax.grid(which='major', alpha=1, color='black')
ax.grid(which='minor', alpha=0.05, color='black')
fig.autofmt_xdate()
plt.savefig(GraphPath + 'Water.png')
plt.close(fig)
progbar.update(pcount)
if not os.path.isfile(GraphPath + 'Total.png'):
pcount += 1
#print('Creating Total overview graph')
fig, ax = plt.subplots()
ax.plot(Data.index, Data.Total, color=Color1)
# format the ticks
ax.xaxis.set_major_locator(years)
ax.xaxis.set_major_formatter(yearsFmt)
ax.xaxis.set_minor_locator(months)
# round to nearest years...
datemin = np.datetime64(Data.index[0], 'Y')
datemax = np.datetime64(Data.index[-1], 'Y')\
+ np.timedelta64(1, 'Y')
ax.set_xlim(datemin, datemax)
plt.title('Timeseries')
plt.xlabel('Time [date]')
plt.ylabel('Total production [%]')
ax.grid(which='major', alpha=1, color='black')
ax.grid(which='minor', alpha=0.05, color='black')
fig.autofmt_xdate()
plt.savefig(GraphPath + 'Total.png')
plt.close(fig)
progbar.update(pcount)
majorTick = mdates.DayLocator(interval=7) # every month
majorFmt = mdates.DateFormatter('%d/%m')
minorTick = mdates.DayLocator() # every day
if not os.path.isdir(GraphPath + 'Monthly'):
#print('Monthly folder not found, creating it')
os.makedirs(GraphPath + 'Monthly')
if not os.path.isfile(GraphPath + 'Monthly/Share2018-3.png'):
progbar = ProgBar.Progbar(target=toCreate,
newline_on_end=False,
text_description='Creating monthly graphs: ')
month = 3
year = 3
done = False
count = 0
#print('Creating Monthly share graph [%]')
while not done:
pcount += 1
#if count % 6 == 0:
# print('\u220E', end='', flush=True)
StartPoint = Data.index.get_loc\
('201'+str(year)+'-'+str(month)+'-'+'01 00:00',method='nearest')
EndPoint = Data['201' + str(year) + '-' + str(month)].shape[0]
fig, ax = plt.subplots()
ax.plot(Data.index[StartPoint:StartPoint + EndPoint],
Data.Diesel['201' + str(year) + '-' + str(month)])
# format the ticks
ax.xaxis.set_major_locator(majorTick)
ax.xaxis.set_major_formatter(majorFmt)
ax.xaxis.set_minor_locator(minorTick)
datemin = np.datetime64(Data.index[StartPoint],
'm') # round to nearest years...
datemax = np.datetime64(Data.index[StartPoint + EndPoint - 1], 'm')
ax.set_xlim(datemin, datemax)
ax.grid(which='major', alpha=1, color='black')
ax.grid(which='minor', alpha=0.05, color='black')
fig.autofmt_xdate()
Diesel = Data.Diesel['201' + str(year) + '-' + str(month)]
Water = Data.Water['201' + str(year) + '-' + str(month)] + Diesel
Wind = Data.Wind['201' + str(year) + '-' + str(month)] + Water
plt.plot(Water, color=Color2)
plt.plot(Wind, color=Color3)
plt.fill_between(Wind.index,
Wind,
Water,
facecolor=Color3,
alpha=1)
plt.fill_between(Water.index,
Water,
Diesel,
facecolor=Color2,
alpha=1)
plt.fill_between(Diesel.index,
Diesel,
0,
facecolor=Color1,
alpha=1)
plt.title('201' + str(year) + ' - ' + monthDict[month])
plt.ylim([-1, 105])
plt.xlabel('Time [date]')
plt.ylabel('Total production [%]')
plt.legend(['Diesel', 'Water', 'Wind'])
plt.savefig(GraphPath + 'Monthly/' + 'Share201' + str(year) + '-' +
str(month) + '.png')
plt.close(fig)
progbar.update(pcount)
if month == 12:
month = 1
year = year + 1
else:
month = month + 1
if year == 8 and month == 4:
done = True
#print('')
"""
If not created, create "random" graphs of single days
This can help see the flow of a day
"""
years = mdates.YearLocator() # every year
months = mdates.MonthLocator() # every month
hours = mdates.HourLocator() # every hour
hoursM = mdates.HourLocator(interval=3) # every 3rd hour
yearsFmt = mdates.DateFormatter('%d')
hoursFmt = mdates.DateFormatter('%H:%M')
if not os.listdir(GraphPath + 'Daily'):
progbar = ProgBar.Progbar(target=toCreate,
newline_on_end=False,
text_description='Creating daily graphs: ')
#widgets = ['Creating daily share graph: ', progressbar.Percentage(),
# ' ',progressbar.Bar(marker='∎',left='[',right=']'),
# ' ', progressbar.AdaptiveETA()]
#pbar = progressbar.ProgressBar(widgets=widgets, maxval=150)
#pbar.start()
#print('')
#print('Creating Daily share graph [%]')
for count in range(0, DayGraphs):
#if count % 5 == 0:
# print('\u220E', end='', flush=True)
#pbar.update(count+1)
pcount += 1
year = np.random.randint(3, 7 + 1)
if year == 3:
month = np.random.randint(3, 12 + 1)
elif year == 8:
month = np.random.randint(1, 3 + 1)
else:
month = np.random.randint(1, 12 + 1)
if year == 3 and month == 3:
day = np.random.randint(5, 31 + 1)
elif month == 2:
day = np.random.randint(1, 28 + 1)
elif month == 4 or month == 6 or month == 9 or month == 11:
day = np.random.randint(1, 30 + 1)
else:
day = np.random.randint(1, 31 + 1)
StartPoint = Data.index.get_loc('201' + str(year) + '-' +
str(month) + '-' + str(day) +
' 00:00',
method='nearest')
EndPoint = Data['201' + str(year) + '-' + str(month) + '-' +
str(day)].shape[0]
fig, ax = plt.subplots()
ax.plot(
Data.index[StartPoint:StartPoint + EndPoint],
Data.Diesel['201' + str(year) + '-' + str(month) + '-' +
str(day)])
# format the ticks
ax.xaxis.set_major_locator(hoursM)
ax.xaxis.set_major_formatter(hoursFmt)
ax.xaxis.set_minor_locator(hours)
# round to nearest years...
datemin = np.datetime64(Data.index[StartPoint], 'm')
datemax = np.datetime64(Data.index[StartPoint + EndPoint - 1], 'm')
# + np.timedelta64(1, 'D')
ax.set_xlim(datemin, datemax)
ax.grid(which='major', alpha=1, color='black')
ax.grid(which='minor', alpha=0.05, color='black')
fig.autofmt_xdate()
Diesel = Data.Diesel['201' + str(year) + '-' + str(month) + ' - ' +
str(day)]
Water = Data.Water['201' + str(year) + '-' + str(month) + ' - ' +
str(day)] + Diesel
Wind = Data.Wind['201' + str(year) + '-' + str(month) + ' - ' +
str(day)] + Water
#plt.plot(Diesel,color=Color1)
plt.plot(Water, color=Color2)
plt.plot(Wind, color=Color3)
plt.fill_between(Wind.index,
Wind,
Water,
facecolor=Color3,
alpha=1)
plt.fill_between(Water.index,
Water,
Diesel,
facecolor=Color2,
alpha=1)
plt.fill_between(Diesel.index,
Diesel,
0,
facecolor=Color1,
alpha=1)
plt.title('201' + str(year) + ' - ' + monthDict[month] + ' - ' +
str(day))
plt.ylim([-1, 105])
plt.xlabel('Time [date]')
plt.ylabel('Total production [%]')
plt.legend(['Diesel', 'Water', 'Wind'])
plt.savefig(GraphPath + 'Daily/' + 'Share201' + str(year) + '-' +
str(month) + '-' + str(day) + '.png')
plt.close(fig)
progbar.update(pcount)
#pbar.finish()
progbar = ProgBar.Progbar(target=toCreate,
newline_on_end=False,
text_description='Done: ')
if toCreate > 0:
progbar.update(pcount)
