1 | from datetime import datetime, timedelta |
||
2 | import mysql.connector |
||
3 | import collections |
||
4 | from decimal import * |
||
5 | import config |
||
6 | import statistics |
||
7 | |||
8 | |||
9 | ######################################################################################################################## |
||
10 | # Aggregate hourly data by period |
||
11 | # rows_hourly: list of (start_datetime_utc, actual_value), should belong to one energy_category_id |
||
12 | # start_datetime_utc: start datetime in utc |
||
13 | # end_datetime_utc: end datetime in utc |
||
14 | # period_type: one of the following period types, 'hourly', 'daily', 'monthly' and 'yearly' |
||
15 | # Note: this procedure doesn't work with multiple energy categories |
||
16 | ######################################################################################################################## |
||
17 | def aggregate_hourly_data_by_period(rows_hourly, start_datetime_utc, end_datetime_utc, period_type): |
||
18 | # todo: validate parameters |
||
19 | start_datetime_utc = start_datetime_utc.replace(tzinfo=None) |
||
20 | end_datetime_utc = end_datetime_utc.replace(tzinfo=None) |
||
21 | |||
22 | if period_type == "hourly": |
||
23 | result_rows_hourly = list() |
||
24 | # todo: add config.working_day_start_time_local |
||
25 | # todo: add config.minutes_to_count |
||
26 | current_datetime_utc = start_datetime_utc.replace(minute=0, second=0, microsecond=0, tzinfo=None) |
||
27 | while current_datetime_utc <= end_datetime_utc: |
||
28 | subtotal = Decimal(0.0) |
||
29 | for row in rows_hourly: |
||
30 | if current_datetime_utc <= row[0] < current_datetime_utc + \ |
||
31 | timedelta(minutes=config.minutes_to_count): |
||
32 | subtotal += row[1] |
||
33 | result_rows_hourly.append((current_datetime_utc, subtotal)) |
||
34 | current_datetime_utc += timedelta(minutes=config.minutes_to_count) |
||
35 | |||
36 | return result_rows_hourly |
||
37 | |||
38 | elif period_type == "daily": |
||
39 | result_rows_daily = list() |
||
40 | # todo: add config.working_day_start_time_local |
||
41 | # todo: add config.minutes_to_count |
||
42 | # calculate the start datetime in utc of the first day in local |
||
43 | start_datetime_local = start_datetime_utc + timedelta(hours=int(config.utc_offset[1:3])) |
||
44 | current_datetime_utc = start_datetime_local.replace(hour=0) - timedelta(hours=int(config.utc_offset[1:3])) |
||
45 | while current_datetime_utc <= end_datetime_utc: |
||
46 | subtotal = Decimal(0.0) |
||
47 | for row in rows_hourly: |
||
48 | if current_datetime_utc <= row[0] < current_datetime_utc + timedelta(days=1): |
||
49 | subtotal += row[1] |
||
50 | result_rows_daily.append((current_datetime_utc, subtotal)) |
||
51 | current_datetime_utc += timedelta(days=1) |
||
52 | |||
53 | return result_rows_daily |
||
54 | |||
55 | elif period_type == "monthly": |
||
56 | result_rows_monthly = list() |
||
57 | # todo: add config.working_day_start_time_local |
||
58 | # todo: add config.minutes_to_count |
||
59 | # calculate the start datetime in utc of the first day in the first month in local |
||
60 | start_datetime_local = start_datetime_utc + timedelta(hours=int(config.utc_offset[1:3])) |
||
61 | current_datetime_utc = start_datetime_local.replace(day=1, hour=0) - timedelta(hours=int(config.utc_offset[1:3])) |
||
62 | |||
63 | while current_datetime_utc <= end_datetime_utc: |
||
64 | # calculate the next datetime in utc |
||
65 | View Code Duplication | if current_datetime_utc.month == 1: |
|
66 | temp_day = 28 |
||
67 | ny = current_datetime_utc.year |
||
68 | if (ny % 100 != 0 and ny % 4 == 0) or (ny % 100 == 0 and ny % 400 == 0): |
||
69 | temp_day = 29 |
||
70 | |||
71 | next_datetime_utc = datetime(year=current_datetime_utc.year, |
||
72 | month=current_datetime_utc.month + 1, |
||
73 | day=temp_day, |
||
74 | hour=current_datetime_utc.hour, |
||
75 | minute=current_datetime_utc.minute, |
||
76 | second=0, |
||
77 | microsecond=0, |
||
78 | tzinfo=None) |
||
79 | elif current_datetime_utc.month == 2: |
||
80 | next_datetime_utc = datetime(year=current_datetime_utc.year, |
||
81 | month=current_datetime_utc.month + 1, |
||
82 | day=31, |
||
83 | hour=current_datetime_utc.hour, |
||
84 | minute=current_datetime_utc.minute, |
||
85 | second=0, |
||
86 | microsecond=0, |
||
87 | tzinfo=None) |
||
88 | elif current_datetime_utc.month in [3, 5, 8, 10]: |
||
89 | next_datetime_utc = datetime(year=current_datetime_utc.year, |
||
90 | month=current_datetime_utc.month + 1, |
||
91 | day=30, |
||
92 | hour=current_datetime_utc.hour, |
||
93 | minute=current_datetime_utc.minute, |
||
94 | second=0, |
||
95 | microsecond=0, |
||
96 | tzinfo=None) |
||
97 | elif current_datetime_utc.month == 7: |
||
98 | next_datetime_utc = datetime(year=current_datetime_utc.year, |
||
99 | month=current_datetime_utc.month + 1, |
||
100 | day=31, |
||
101 | hour=current_datetime_utc.hour, |
||
102 | minute=current_datetime_utc.minute, |
||
103 | second=0, |
||
104 | microsecond=0, |
||
105 | tzinfo=None) |
||
106 | elif current_datetime_utc.month in [4, 6, 9, 11]: |
||
107 | next_datetime_utc = datetime(year=current_datetime_utc.year, |
||
108 | month=current_datetime_utc.month + 1, |
||
109 | day=31, |
||
110 | hour=current_datetime_utc.hour, |
||
111 | minute=current_datetime_utc.minute, |
||
112 | second=0, |
||
113 | microsecond=0, |
||
114 | tzinfo=None) |
||
115 | elif current_datetime_utc.month == 12: |
||
116 | next_datetime_utc = datetime(year=current_datetime_utc.year + 1, |
||
117 | month=1, |
||
118 | day=31, |
||
119 | hour=current_datetime_utc.hour, |
||
120 | minute=current_datetime_utc.minute, |
||
121 | second=0, |
||
122 | microsecond=0, |
||
123 | tzinfo=None) |
||
124 | |||
125 | subtotal = Decimal(0.0) |
||
126 | for row in rows_hourly: |
||
127 | if current_datetime_utc <= row[0] < next_datetime_utc: |
||
128 | subtotal += row[1] |
||
129 | |||
130 | result_rows_monthly.append((current_datetime_utc, subtotal)) |
||
131 | current_datetime_utc = next_datetime_utc |
||
132 | |||
133 | return result_rows_monthly |
||
134 | |||
135 | elif period_type == "yearly": |
||
136 | result_rows_yearly = list() |
||
137 | # todo: add config.working_day_start_time_local |
||
138 | # todo: add config.minutes_to_count |
||
139 | # calculate the start datetime in utc of the first day in the first month in local |
||
140 | start_datetime_local = start_datetime_utc + timedelta(hours=int(config.utc_offset[1:3])) |
||
141 | current_datetime_utc = start_datetime_local.replace(month=1, day=1, hour=0) - timedelta( |
||
142 | hours=int(config.utc_offset[1:3])) |
||
143 | |||
144 | while current_datetime_utc <= end_datetime_utc: |
||
145 | # calculate the next datetime in utc |
||
146 | # todo: timedelta of year |
||
147 | next_datetime_utc = datetime(year=current_datetime_utc.year + 2, |
||
148 | month=1, |
||
149 | day=1, |
||
150 | hour=current_datetime_utc.hour, |
||
151 | minute=current_datetime_utc.minute, |
||
152 | second=current_datetime_utc.second, |
||
153 | microsecond=current_datetime_utc.microsecond, |
||
154 | tzinfo=current_datetime_utc.tzinfo) - timedelta(days=1) |
||
155 | subtotal = Decimal(0.0) |
||
156 | for row in rows_hourly: |
||
157 | if current_datetime_utc <= row[0] < next_datetime_utc: |
||
158 | subtotal += row[1] |
||
159 | |||
160 | result_rows_yearly.append((current_datetime_utc, subtotal)) |
||
161 | current_datetime_utc = next_datetime_utc |
||
162 | return result_rows_yearly |
||
163 | |||
164 | |||
165 | ######################################################################################################################## |
||
166 | # Get tariffs by energy category |
||
167 | ######################################################################################################################## |
||
168 | View Code Duplication | def get_energy_category_tariffs(cost_center_id, energy_category_id, start_datetime_utc, end_datetime_utc): |
|
169 | # todo: validate parameters |
||
170 | if cost_center_id is None: |
||
171 | return dict() |
||
172 | |||
173 | start_datetime_utc = start_datetime_utc.replace(tzinfo=None) |
||
174 | end_datetime_utc = end_datetime_utc.replace(tzinfo=None) |
||
175 | |||
176 | # get timezone offset in minutes, this value will be returned to client |
||
177 | timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6]) |
||
178 | if config.utc_offset[0] == '-': |
||
179 | timezone_offset = -timezone_offset |
||
180 | |||
181 | tariff_dict = collections.OrderedDict() |
||
182 | |||
183 | cnx = None |
||
184 | cursor = None |
||
185 | try: |
||
186 | cnx = mysql.connector.connect(**config.myems_system_db) |
||
187 | cursor = cnx.cursor() |
||
188 | query_tariffs = (" SELECT t.id, t.valid_from_datetime_utc, t.valid_through_datetime_utc " |
||
189 | " FROM tbl_tariffs t, tbl_cost_centers_tariffs cct " |
||
190 | " WHERE t.energy_category_id = %s AND " |
||
191 | " t.id = cct.tariff_id AND " |
||
192 | " cct.cost_center_id = %s AND " |
||
193 | " t.valid_through_datetime_utc >= %s AND " |
||
194 | " t.valid_from_datetime_utc <= %s " |
||
195 | " ORDER BY t.valid_from_datetime_utc ") |
||
196 | cursor.execute(query_tariffs, (energy_category_id, cost_center_id, start_datetime_utc, end_datetime_utc,)) |
||
197 | rows_tariffs = cursor.fetchall() |
||
198 | except Exception as e: |
||
199 | print(str(e)) |
||
200 | if cnx: |
||
201 | cnx.disconnect() |
||
202 | if cursor: |
||
203 | cursor.close() |
||
204 | return dict() |
||
205 | |||
206 | if rows_tariffs is None or len(rows_tariffs) == 0: |
||
207 | if cursor: |
||
208 | cursor.close() |
||
209 | if cnx: |
||
210 | cnx.disconnect() |
||
211 | return dict() |
||
212 | |||
213 | for row in rows_tariffs: |
||
214 | tariff_dict[row[0]] = {'valid_from_datetime_utc': row[1], |
||
215 | 'valid_through_datetime_utc': row[2], |
||
216 | 'rates': list()} |
||
217 | |||
218 | try: |
||
219 | query_timeofuse_tariffs = (" SELECT tariff_id, start_time_of_day, end_time_of_day, price " |
||
220 | " FROM tbl_tariffs_timeofuses " |
||
221 | " WHERE tariff_id IN ( " + ', '.join(map(str, tariff_dict.keys())) + ")" |
||
222 | " ORDER BY tariff_id, start_time_of_day ") |
||
223 | cursor.execute(query_timeofuse_tariffs, ) |
||
224 | rows_timeofuse_tariffs = cursor.fetchall() |
||
225 | except Exception as e: |
||
226 | print(str(e)) |
||
227 | if cnx: |
||
228 | cnx.disconnect() |
||
229 | if cursor: |
||
230 | cursor.close() |
||
231 | return dict() |
||
232 | |||
233 | if cursor: |
||
234 | cursor.close() |
||
235 | if cnx: |
||
236 | cnx.disconnect() |
||
237 | |||
238 | if rows_timeofuse_tariffs is None or len(rows_timeofuse_tariffs) == 0: |
||
239 | return dict() |
||
240 | |||
241 | for row in rows_timeofuse_tariffs: |
||
242 | tariff_dict[row[0]]['rates'].append({'start_time_of_day': row[1], |
||
243 | 'end_time_of_day': row[2], |
||
244 | 'price': row[3]}) |
||
245 | |||
246 | result = dict() |
||
247 | for tariff_id, tariff_value in tariff_dict.items(): |
||
248 | current_datetime_utc = tariff_value['valid_from_datetime_utc'] |
||
249 | while current_datetime_utc < tariff_value['valid_through_datetime_utc']: |
||
250 | for rate in tariff_value['rates']: |
||
251 | current_datetime_local = current_datetime_utc + timedelta(minutes=timezone_offset) |
||
252 | seconds_since_midnight = (current_datetime_local - |
||
253 | current_datetime_local.replace(hour=0, |
||
254 | second=0, |
||
255 | microsecond=0, |
||
256 | tzinfo=None)).total_seconds() |
||
257 | if rate['start_time_of_day'].total_seconds() <= \ |
||
258 | seconds_since_midnight < rate['end_time_of_day'].total_seconds(): |
||
259 | result[current_datetime_utc] = rate['price'] |
||
260 | break |
||
261 | |||
262 | # start from the next time slot |
||
263 | current_datetime_utc += timedelta(minutes=config.minutes_to_count) |
||
264 | |||
265 | return {k: v for k, v in result.items() if start_datetime_utc <= k <= end_datetime_utc} |
||
266 | |||
267 | |||
268 | ######################################################################################################################## |
||
269 | # Get peak types of tariff by energy category |
||
270 | # peak types: toppeak, onpeak, midpeak, offpeak |
||
271 | ######################################################################################################################## |
||
272 | View Code Duplication | def get_energy_category_peak_types(cost_center_id, energy_category_id, start_datetime_utc, end_datetime_utc): |
|
273 | # todo: validate parameters |
||
274 | if cost_center_id is None: |
||
275 | return dict() |
||
276 | |||
277 | start_datetime_utc = start_datetime_utc.replace(tzinfo=None) |
||
278 | end_datetime_utc = end_datetime_utc.replace(tzinfo=None) |
||
279 | |||
280 | # get timezone offset in minutes, this value will be returned to client |
||
281 | timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6]) |
||
282 | if config.utc_offset[0] == '-': |
||
283 | timezone_offset = -timezone_offset |
||
284 | |||
285 | tariff_dict = collections.OrderedDict() |
||
286 | |||
287 | cnx = None |
||
288 | cursor = None |
||
289 | try: |
||
290 | cnx = mysql.connector.connect(**config.myems_system_db) |
||
291 | cursor = cnx.cursor() |
||
292 | query_tariffs = (" SELECT t.id, t.valid_from_datetime_utc, t.valid_through_datetime_utc " |
||
293 | " FROM tbl_tariffs t, tbl_cost_centers_tariffs cct " |
||
294 | " WHERE t.energy_category_id = %s AND " |
||
295 | " t.id = cct.tariff_id AND " |
||
296 | " cct.cost_center_id = %s AND " |
||
297 | " t.valid_through_datetime_utc >= %s AND " |
||
298 | " t.valid_from_datetime_utc <= %s " |
||
299 | " ORDER BY t.valid_from_datetime_utc ") |
||
300 | cursor.execute(query_tariffs, (energy_category_id, cost_center_id, start_datetime_utc, end_datetime_utc,)) |
||
301 | rows_tariffs = cursor.fetchall() |
||
302 | except Exception as e: |
||
303 | print(str(e)) |
||
304 | if cnx: |
||
305 | cnx.disconnect() |
||
306 | if cursor: |
||
307 | cursor.close() |
||
308 | return dict() |
||
309 | |||
310 | if rows_tariffs is None or len(rows_tariffs) == 0: |
||
311 | if cursor: |
||
312 | cursor.close() |
||
313 | if cnx: |
||
314 | cnx.disconnect() |
||
315 | return dict() |
||
316 | |||
317 | for row in rows_tariffs: |
||
318 | tariff_dict[row[0]] = {'valid_from_datetime_utc': row[1], |
||
319 | 'valid_through_datetime_utc': row[2], |
||
320 | 'rates': list()} |
||
321 | |||
322 | try: |
||
323 | query_timeofuse_tariffs = (" SELECT tariff_id, start_time_of_day, end_time_of_day, peak_type " |
||
324 | " FROM tbl_tariffs_timeofuses " |
||
325 | " WHERE tariff_id IN ( " + ', '.join(map(str, tariff_dict.keys())) + ")" |
||
326 | " ORDER BY tariff_id, start_time_of_day ") |
||
327 | cursor.execute(query_timeofuse_tariffs, ) |
||
328 | rows_timeofuse_tariffs = cursor.fetchall() |
||
329 | except Exception as e: |
||
330 | print(str(e)) |
||
331 | if cnx: |
||
332 | cnx.disconnect() |
||
333 | if cursor: |
||
334 | cursor.close() |
||
335 | return dict() |
||
336 | |||
337 | if cursor: |
||
338 | cursor.close() |
||
339 | if cnx: |
||
340 | cnx.disconnect() |
||
341 | |||
342 | if rows_timeofuse_tariffs is None or len(rows_timeofuse_tariffs) == 0: |
||
343 | return dict() |
||
344 | |||
345 | for row in rows_timeofuse_tariffs: |
||
346 | tariff_dict[row[0]]['rates'].append({'start_time_of_day': row[1], |
||
347 | 'end_time_of_day': row[2], |
||
348 | 'peak_type': row[3]}) |
||
349 | |||
350 | result = dict() |
||
351 | for tariff_id, tariff_value in tariff_dict.items(): |
||
352 | current_datetime_utc = tariff_value['valid_from_datetime_utc'] |
||
353 | while current_datetime_utc < tariff_value['valid_through_datetime_utc']: |
||
354 | for rate in tariff_value['rates']: |
||
355 | current_datetime_local = current_datetime_utc + timedelta(minutes=timezone_offset) |
||
356 | seconds_since_midnight = (current_datetime_local - |
||
357 | current_datetime_local.replace(hour=0, |
||
358 | second=0, |
||
359 | microsecond=0, |
||
360 | tzinfo=None)).total_seconds() |
||
361 | if rate['start_time_of_day'].total_seconds() <= \ |
||
362 | seconds_since_midnight < rate['end_time_of_day'].total_seconds(): |
||
363 | result[current_datetime_utc] = rate['peak_type'] |
||
364 | break |
||
365 | |||
366 | # start from the next time slot |
||
367 | current_datetime_utc += timedelta(minutes=config.minutes_to_count) |
||
368 | |||
369 | return {k: v for k, v in result.items() if start_datetime_utc <= k <= end_datetime_utc} |
||
370 | |||
371 | |||
372 | ######################################################################################################################## |
||
373 | # Averaging calculator of hourly data by period |
||
374 | # rows_hourly: list of (start_datetime_utc, actual_value), should belong to one energy_category_id |
||
375 | # start_datetime_utc: start datetime in utc |
||
376 | # end_datetime_utc: end datetime in utc |
||
377 | # period_type: one of the following period types, 'hourly', 'daily', 'monthly' and 'yearly' |
||
378 | # Returns: periodically data of average and maximum |
||
379 | # Note: this procedure doesn't work with multiple energy categories |
||
380 | ######################################################################################################################## |
||
381 | def averaging_hourly_data_by_period(rows_hourly, start_datetime_utc, end_datetime_utc, period_type): |
||
382 | # todo: validate parameters |
||
383 | start_datetime_utc = start_datetime_utc.replace(tzinfo=None) |
||
384 | end_datetime_utc = end_datetime_utc.replace(tzinfo=None) |
||
385 | |||
386 | if period_type == "hourly": |
||
387 | result_rows_hourly = list() |
||
388 | # todo: add config.working_day_start_time_local |
||
389 | # todo: add config.minutes_to_count |
||
390 | total = Decimal(0.0) |
||
391 | maximum = None |
||
392 | counter = 0 |
||
393 | current_datetime_utc = start_datetime_utc.replace(minute=0, second=0, microsecond=0, tzinfo=None) |
||
394 | View Code Duplication | while current_datetime_utc <= end_datetime_utc: |
|
395 | sub_total = Decimal(0.0) |
||
396 | sub_maximum = None |
||
397 | sub_counter = 0 |
||
398 | for row in rows_hourly: |
||
399 | if current_datetime_utc <= row[0] < current_datetime_utc + \ |
||
400 | timedelta(minutes=config.minutes_to_count): |
||
401 | sub_total += row[1] |
||
402 | if sub_maximum is None: |
||
403 | sub_maximum = row[1] |
||
404 | elif sub_maximum < row[1]: |
||
405 | sub_maximum = row[1] |
||
406 | sub_counter += 1 |
||
407 | |||
408 | sub_average = (sub_total / sub_counter) if sub_counter > 0 else None |
||
409 | result_rows_hourly.append((current_datetime_utc, sub_average, sub_maximum)) |
||
410 | |||
411 | total += sub_total |
||
412 | counter += sub_counter |
||
413 | if sub_maximum is None: |
||
414 | pass |
||
415 | elif maximum is None: |
||
416 | maximum = sub_maximum |
||
417 | elif maximum < sub_maximum: |
||
418 | maximum = sub_maximum |
||
419 | |||
420 | current_datetime_utc += timedelta(minutes=config.minutes_to_count) |
||
421 | |||
422 | average = total / counter if counter > 0 else None |
||
423 | return result_rows_hourly, average, maximum |
||
424 | |||
425 | elif period_type == "daily": |
||
426 | result_rows_daily = list() |
||
427 | # todo: add config.working_day_start_time_local |
||
428 | # todo: add config.minutes_to_count |
||
429 | total = Decimal(0.0) |
||
430 | maximum = None |
||
431 | counter = 0 |
||
432 | # calculate the start datetime in utc of the first day in local |
||
433 | start_datetime_local = start_datetime_utc + timedelta(hours=int(config.utc_offset[1:3])) |
||
434 | current_datetime_utc = start_datetime_local.replace(hour=0) - timedelta(hours=int(config.utc_offset[1:3])) |
||
435 | View Code Duplication | while current_datetime_utc <= end_datetime_utc: |
|
436 | sub_total = Decimal(0.0) |
||
437 | sub_maximum = None |
||
438 | sub_counter = 0 |
||
439 | for row in rows_hourly: |
||
440 | if current_datetime_utc <= row[0] < current_datetime_utc + timedelta(days=1): |
||
441 | sub_total += row[1] |
||
442 | if sub_maximum is None: |
||
443 | sub_maximum = row[1] |
||
444 | elif sub_maximum < row[1]: |
||
445 | sub_maximum = row[1] |
||
446 | sub_counter += 1 |
||
447 | |||
448 | sub_average = (sub_total / sub_counter) if sub_counter > 0 else None |
||
449 | result_rows_daily.append((current_datetime_utc, sub_average, sub_maximum)) |
||
450 | total += sub_total |
||
451 | counter += sub_counter |
||
452 | if sub_maximum is None: |
||
453 | pass |
||
454 | elif maximum is None: |
||
455 | maximum = sub_maximum |
||
456 | elif maximum < sub_maximum: |
||
457 | maximum = sub_maximum |
||
458 | current_datetime_utc += timedelta(days=1) |
||
459 | |||
460 | return result_rows_daily, average, maximum |
||
0 ignored issues
–
show
Comprehensibility
Best Practice
introduced
by
![]() |
|||
461 | |||
462 | elif period_type == "monthly": |
||
463 | result_rows_monthly = list() |
||
464 | # todo: add config.working_day_start_time_local |
||
465 | # todo: add config.minutes_to_count |
||
466 | total = Decimal(0.0) |
||
467 | maximum = None |
||
468 | counter = 0 |
||
469 | # calculate the start datetime in utc of the first day in the first month in local |
||
470 | start_datetime_local = start_datetime_utc + timedelta(hours=int(config.utc_offset[1:3])) |
||
471 | current_datetime_utc = start_datetime_local.replace(day=1, hour=0) - timedelta(hours=int(config.utc_offset[1:3])) |
||
472 | |||
473 | while current_datetime_utc <= end_datetime_utc: |
||
474 | # calculate the next datetime in utc |
||
475 | View Code Duplication | if current_datetime_utc.month == 1: |
|
476 | temp_day = 28 |
||
477 | ny = current_datetime_utc.year |
||
478 | if (ny % 100 != 0 and ny % 4 == 0) or (ny % 100 == 0 and ny % 400 == 0): |
||
479 | temp_day = 29 |
||
480 | |||
481 | next_datetime_utc = datetime(year=current_datetime_utc.year, |
||
482 | month=current_datetime_utc.month + 1, |
||
483 | day=temp_day, |
||
484 | hour=current_datetime_utc.hour, |
||
485 | minute=current_datetime_utc.minute, |
||
486 | second=0, |
||
487 | microsecond=0, |
||
488 | tzinfo=None) |
||
489 | elif current_datetime_utc.month == 2: |
||
490 | next_datetime_utc = datetime(year=current_datetime_utc.year, |
||
491 | month=current_datetime_utc.month + 1, |
||
492 | day=31, |
||
493 | hour=current_datetime_utc.hour, |
||
494 | minute=current_datetime_utc.minute, |
||
495 | second=0, |
||
496 | microsecond=0, |
||
497 | tzinfo=None) |
||
498 | elif current_datetime_utc.month in [3, 5, 8, 10]: |
||
499 | next_datetime_utc = datetime(year=current_datetime_utc.year, |
||
500 | month=current_datetime_utc.month + 1, |
||
501 | day=30, |
||
502 | hour=current_datetime_utc.hour, |
||
503 | minute=current_datetime_utc.minute, |
||
504 | second=0, |
||
505 | microsecond=0, |
||
506 | tzinfo=None) |
||
507 | elif current_datetime_utc.month == 7: |
||
508 | next_datetime_utc = datetime(year=current_datetime_utc.year, |
||
509 | month=current_datetime_utc.month + 1, |
||
510 | day=31, |
||
511 | hour=current_datetime_utc.hour, |
||
512 | minute=current_datetime_utc.minute, |
||
513 | second=0, |
||
514 | microsecond=0, |
||
515 | tzinfo=None) |
||
516 | elif current_datetime_utc.month in [4, 6, 9, 11]: |
||
517 | next_datetime_utc = datetime(year=current_datetime_utc.year, |
||
518 | month=current_datetime_utc.month + 1, |
||
519 | day=31, |
||
520 | hour=current_datetime_utc.hour, |
||
521 | minute=current_datetime_utc.minute, |
||
522 | second=0, |
||
523 | microsecond=0, |
||
524 | tzinfo=None) |
||
525 | elif current_datetime_utc.month == 12: |
||
526 | next_datetime_utc = datetime(year=current_datetime_utc.year + 1, |
||
527 | month=1, |
||
528 | day=31, |
||
529 | hour=current_datetime_utc.hour, |
||
530 | minute=current_datetime_utc.minute, |
||
531 | second=0, |
||
532 | microsecond=0, |
||
533 | tzinfo=None) |
||
534 | |||
535 | sub_total = Decimal(0.0) |
||
536 | sub_maximum = None |
||
537 | sub_counter = 0 |
||
538 | for row in rows_hourly: |
||
539 | if current_datetime_utc <= row[0] < next_datetime_utc: |
||
540 | sub_total += row[1] |
||
541 | if sub_maximum is None: |
||
542 | sub_maximum = row[1] |
||
543 | elif sub_maximum < row[1]: |
||
544 | sub_maximum = row[1] |
||
545 | sub_counter += 1 |
||
546 | |||
547 | sub_average = (sub_total / sub_counter) if sub_counter > 0 else None |
||
548 | result_rows_monthly.append((current_datetime_utc, sub_average, sub_maximum)) |
||
549 | total += sub_total |
||
550 | counter += sub_counter |
||
551 | if sub_maximum is None: |
||
552 | pass |
||
553 | elif maximum is None: |
||
554 | maximum = sub_maximum |
||
555 | elif maximum < sub_maximum: |
||
556 | maximum = sub_maximum |
||
557 | current_datetime_utc = next_datetime_utc |
||
558 | |||
559 | average = total / counter if counter > 0 else None |
||
560 | return result_rows_monthly, average, maximum |
||
561 | |||
562 | elif period_type == "yearly": |
||
563 | result_rows_yearly = list() |
||
564 | # todo: add config.working_day_start_time_local |
||
565 | # todo: add config.minutes_to_count |
||
566 | total = Decimal(0.0) |
||
567 | maximum = None |
||
568 | counter = 0 |
||
569 | # calculate the start datetime in utc of the first day in the first month in local |
||
570 | start_datetime_local = start_datetime_utc + timedelta(hours=int(config.utc_offset[1:3])) |
||
571 | current_datetime_utc = start_datetime_local.replace(month=1, day=1, hour=0) - timedelta( |
||
572 | hours=int(config.utc_offset[1:3])) |
||
573 | |||
574 | while current_datetime_utc <= end_datetime_utc: |
||
575 | # calculate the next datetime in utc |
||
576 | # todo: timedelta of year |
||
577 | next_datetime_utc = datetime(year=current_datetime_utc.year + 2, |
||
578 | month=1, |
||
579 | day=1, |
||
580 | hour=current_datetime_utc.hour, |
||
581 | minute=current_datetime_utc.minute, |
||
582 | second=current_datetime_utc.second, |
||
583 | microsecond=current_datetime_utc.microsecond, |
||
584 | tzinfo=current_datetime_utc.tzinfo) - timedelta(days=1) |
||
585 | sub_total = Decimal(0.0) |
||
586 | sub_maximum = None |
||
587 | sub_counter = 0 |
||
588 | for row in rows_hourly: |
||
589 | if current_datetime_utc <= row[0] < next_datetime_utc: |
||
590 | sub_total += row[1] |
||
591 | if sub_maximum is None: |
||
592 | sub_maximum = row[1] |
||
593 | elif sub_maximum < row[1]: |
||
594 | sub_maximum = row[1] |
||
595 | sub_counter += 1 |
||
596 | |||
597 | sub_average = (sub_total / sub_counter) if sub_counter > 0 else None |
||
598 | result_rows_yearly.append((current_datetime_utc, sub_average, sub_maximum)) |
||
599 | total += sub_total |
||
600 | counter += sub_counter |
||
601 | if sub_maximum is None: |
||
602 | pass |
||
603 | elif maximum is None: |
||
604 | maximum = sub_maximum |
||
605 | elif maximum < sub_maximum: |
||
606 | maximum = sub_maximum |
||
607 | current_datetime_utc = next_datetime_utc |
||
608 | |||
609 | average = total / counter if counter > 0 else None |
||
610 | return result_rows_yearly, average, maximum |
||
611 | |||
612 | |||
613 | ######################################################################################################################## |
||
614 | # Statistics calculator of hourly data by period |
||
615 | # rows_hourly: list of (start_datetime_utc, actual_value), should belong to one energy_category_id |
||
616 | # start_datetime_utc: start datetime in utc |
||
617 | # end_datetime_utc: end datetime in utc |
||
618 | # period_type: one of the following period types, 'hourly', 'daily', 'monthly' and 'yearly' |
||
619 | # Returns: periodically data of values and statistics of mean, median, minimum, maximum, stdev and variance |
||
620 | # Note: this procedure doesn't work with multiple energy categories |
||
621 | ######################################################################################################################## |
||
622 | def statistics_hourly_data_by_period(rows_hourly, start_datetime_utc, end_datetime_utc, period_type): |
||
623 | # todo: validate parameters |
||
624 | start_datetime_utc = start_datetime_utc.replace(tzinfo=None) |
||
625 | end_datetime_utc = end_datetime_utc.replace(tzinfo=None) |
||
626 | |||
627 | if period_type == "hourly": |
||
628 | result_rows_hourly = list() |
||
629 | sample_data = list() |
||
630 | # todo: add config.working_day_start_time_local |
||
631 | # todo: add config.minutes_to_count |
||
632 | counter = 0 |
||
633 | mean = None |
||
634 | median = None |
||
635 | minimum = None |
||
636 | maximum = None |
||
637 | stdev = None |
||
638 | variance = None |
||
639 | current_datetime_utc = start_datetime_utc.replace(minute=0, second=0, microsecond=0, tzinfo=None) |
||
640 | View Code Duplication | while current_datetime_utc <= end_datetime_utc: |
|
641 | sub_total = Decimal(0.0) |
||
642 | for row in rows_hourly: |
||
643 | if current_datetime_utc <= row[0] < current_datetime_utc + \ |
||
644 | timedelta(minutes=config.minutes_to_count): |
||
645 | sub_total += row[1] |
||
646 | |||
647 | result_rows_hourly.append((current_datetime_utc, sub_total)) |
||
648 | sample_data.append(sub_total) |
||
649 | |||
650 | counter += 1 |
||
651 | if minimum is None: |
||
652 | minimum = sub_total |
||
653 | elif minimum > sub_total: |
||
654 | minimum = sub_total |
||
655 | |||
656 | if maximum is None: |
||
657 | maximum = sub_total |
||
658 | elif maximum < sub_total: |
||
659 | maximum = sub_total |
||
660 | |||
661 | current_datetime_utc += timedelta(minutes=config.minutes_to_count) |
||
662 | |||
663 | if len(sample_data) > 1: |
||
664 | mean = statistics.mean(sample_data) |
||
665 | median = statistics.median(sample_data) |
||
666 | stdev = statistics.stdev(sample_data) |
||
667 | variance = statistics.variance(sample_data) |
||
668 | |||
669 | return result_rows_hourly, mean, median, minimum, maximum, stdev, variance |
||
670 | |||
671 | elif period_type == "daily": |
||
672 | result_rows_daily = list() |
||
673 | sample_data = list() |
||
674 | # todo: add config.working_day_start_time_local |
||
675 | # todo: add config.minutes_to_count |
||
676 | counter = 0 |
||
677 | mean = None |
||
678 | median = None |
||
679 | minimum = None |
||
680 | maximum = None |
||
681 | stdev = None |
||
682 | variance = None |
||
683 | # calculate the start datetime in utc of the first day in local |
||
684 | start_datetime_local = start_datetime_utc + timedelta(hours=int(config.utc_offset[1:3])) |
||
685 | current_datetime_utc = start_datetime_local.replace(hour=0) - timedelta(hours=int(config.utc_offset[1:3])) |
||
686 | View Code Duplication | while current_datetime_utc <= end_datetime_utc: |
|
687 | sub_total = Decimal(0.0) |
||
688 | for row in rows_hourly: |
||
689 | if current_datetime_utc <= row[0] < current_datetime_utc + timedelta(days=1): |
||
690 | sub_total += row[1] |
||
691 | |||
692 | result_rows_daily.append((current_datetime_utc, sub_total)) |
||
693 | sample_data.append(sub_total) |
||
694 | |||
695 | counter += 1 |
||
696 | if minimum is None: |
||
697 | minimum = sub_total |
||
698 | elif minimum > sub_total: |
||
699 | minimum = sub_total |
||
700 | |||
701 | if maximum is None: |
||
702 | maximum = sub_total |
||
703 | elif maximum < sub_total: |
||
704 | maximum = sub_total |
||
705 | current_datetime_utc += timedelta(days=1) |
||
706 | |||
707 | if len(sample_data) > 1: |
||
708 | mean = statistics.mean(sample_data) |
||
709 | median = statistics.median(sample_data) |
||
710 | stdev = statistics.stdev(sample_data) |
||
711 | variance = statistics.variance(sample_data) |
||
712 | |||
713 | return result_rows_daily, mean, median, minimum, maximum, stdev, variance |
||
714 | |||
715 | elif period_type == "monthly": |
||
716 | result_rows_monthly = list() |
||
717 | sample_data = list() |
||
718 | # todo: add config.working_day_start_time_local |
||
719 | # todo: add config.minutes_to_count |
||
720 | counter = 0 |
||
721 | mean = None |
||
722 | median = None |
||
723 | minimum = None |
||
724 | maximum = None |
||
725 | stdev = None |
||
726 | variance = None |
||
727 | # calculate the start datetime in utc of the first day in the first month in local |
||
728 | start_datetime_local = start_datetime_utc + timedelta(hours=int(config.utc_offset[1:3])) |
||
729 | current_datetime_utc = start_datetime_local.replace(day=1, hour=0) - timedelta(hours=int(config.utc_offset[1:3])) |
||
730 | |||
731 | while current_datetime_utc <= end_datetime_utc: |
||
732 | # calculate the next datetime in utc |
||
733 | View Code Duplication | if current_datetime_utc.month == 1: |
|
734 | temp_day = 28 |
||
735 | ny = current_datetime_utc.year |
||
736 | if (ny % 100 != 0 and ny % 4 == 0) or (ny % 100 == 0 and ny % 400 == 0): |
||
737 | temp_day = 29 |
||
738 | |||
739 | next_datetime_utc = datetime(year=current_datetime_utc.year, |
||
740 | month=current_datetime_utc.month + 1, |
||
741 | day=temp_day, |
||
742 | hour=current_datetime_utc.hour, |
||
743 | minute=current_datetime_utc.minute, |
||
744 | second=0, |
||
745 | microsecond=0, |
||
746 | tzinfo=None) |
||
747 | elif current_datetime_utc.month == 2: |
||
748 | next_datetime_utc = datetime(year=current_datetime_utc.year, |
||
749 | month=current_datetime_utc.month + 1, |
||
750 | day=31, |
||
751 | hour=current_datetime_utc.hour, |
||
752 | minute=current_datetime_utc.minute, |
||
753 | second=0, |
||
754 | microsecond=0, |
||
755 | tzinfo=None) |
||
756 | elif current_datetime_utc.month in [3, 5, 8, 10]: |
||
757 | next_datetime_utc = datetime(year=current_datetime_utc.year, |
||
758 | month=current_datetime_utc.month + 1, |
||
759 | day=30, |
||
760 | hour=current_datetime_utc.hour, |
||
761 | minute=current_datetime_utc.minute, |
||
762 | second=0, |
||
763 | microsecond=0, |
||
764 | tzinfo=None) |
||
765 | elif current_datetime_utc.month == 7: |
||
766 | next_datetime_utc = datetime(year=current_datetime_utc.year, |
||
767 | month=current_datetime_utc.month + 1, |
||
768 | day=31, |
||
769 | hour=current_datetime_utc.hour, |
||
770 | minute=current_datetime_utc.minute, |
||
771 | second=0, |
||
772 | microsecond=0, |
||
773 | tzinfo=None) |
||
774 | elif current_datetime_utc.month in [4, 6, 9, 11]: |
||
775 | next_datetime_utc = datetime(year=current_datetime_utc.year, |
||
776 | month=current_datetime_utc.month + 1, |
||
777 | day=31, |
||
778 | hour=current_datetime_utc.hour, |
||
779 | minute=current_datetime_utc.minute, |
||
780 | second=0, |
||
781 | microsecond=0, |
||
782 | tzinfo=None) |
||
783 | elif current_datetime_utc.month == 12: |
||
784 | next_datetime_utc = datetime(year=current_datetime_utc.year + 1, |
||
785 | month=1, |
||
786 | day=31, |
||
787 | hour=current_datetime_utc.hour, |
||
788 | minute=current_datetime_utc.minute, |
||
789 | second=0, |
||
790 | microsecond=0, |
||
791 | tzinfo=None) |
||
792 | |||
793 | sub_total = Decimal(0.0) |
||
794 | for row in rows_hourly: |
||
795 | if current_datetime_utc <= row[0] < next_datetime_utc: |
||
796 | sub_total += row[1] |
||
797 | |||
798 | result_rows_monthly.append((current_datetime_utc, sub_total)) |
||
799 | sample_data.append(sub_total) |
||
800 | |||
801 | counter += 1 |
||
802 | if minimum is None: |
||
803 | minimum = sub_total |
||
804 | elif minimum > sub_total: |
||
805 | minimum = sub_total |
||
806 | |||
807 | if maximum is None: |
||
808 | maximum = sub_total |
||
809 | elif maximum < sub_total: |
||
810 | maximum = sub_total |
||
811 | current_datetime_utc = next_datetime_utc |
||
812 | |||
813 | if len(sample_data) > 1: |
||
814 | mean = statistics.mean(sample_data) |
||
815 | median = statistics.median(sample_data) |
||
816 | stdev = statistics.stdev(sample_data) |
||
817 | variance = statistics.variance(sample_data) |
||
818 | |||
819 | return result_rows_monthly, mean, median, minimum, maximum, stdev, variance |
||
820 | |||
821 | elif period_type == "yearly": |
||
822 | result_rows_yearly = list() |
||
823 | sample_data = list() |
||
824 | # todo: add config.working_day_start_time_local |
||
825 | # todo: add config.minutes_to_count |
||
826 | mean = None |
||
827 | median = None |
||
828 | minimum = None |
||
829 | maximum = None |
||
830 | stdev = None |
||
831 | variance = None |
||
832 | # calculate the start datetime in utc of the first day in the first month in local |
||
833 | start_datetime_local = start_datetime_utc + timedelta(hours=int(config.utc_offset[1:3])) |
||
834 | current_datetime_utc = start_datetime_local.replace(month=1, day=1, hour=0) - timedelta( |
||
835 | hours=int(config.utc_offset[1:3])) |
||
836 | |||
837 | while current_datetime_utc <= end_datetime_utc: |
||
838 | # calculate the next datetime in utc |
||
839 | # todo: timedelta of year |
||
840 | next_datetime_utc = datetime(year=current_datetime_utc.year + 2, |
||
841 | month=1, |
||
842 | day=1, |
||
843 | hour=current_datetime_utc.hour, |
||
844 | minute=current_datetime_utc.minute, |
||
845 | second=current_datetime_utc.second, |
||
846 | microsecond=current_datetime_utc.microsecond, |
||
847 | tzinfo=current_datetime_utc.tzinfo) - timedelta(days=1) |
||
848 | sub_total = Decimal(0.0) |
||
849 | for row in rows_hourly: |
||
850 | if current_datetime_utc <= row[0] < next_datetime_utc: |
||
851 | sub_total += row[1] |
||
852 | |||
853 | result_rows_yearly.append((current_datetime_utc, sub_total)) |
||
854 | sample_data.append(sub_total) |
||
855 | |||
856 | if minimum is None: |
||
857 | minimum = sub_total |
||
858 | elif minimum > sub_total: |
||
859 | minimum = sub_total |
||
860 | if maximum is None: |
||
861 | maximum = sub_total |
||
862 | elif maximum < sub_total: |
||
863 | maximum = sub_total |
||
864 | |||
865 | current_datetime_utc = next_datetime_utc |
||
866 | |||
867 | if len(sample_data) > 1: |
||
868 | mean = statistics.mean(sample_data) |
||
869 | median = statistics.median(sample_data) |
||
870 | stdev = statistics.stdev(sample_data) |
||
871 | variance = statistics.variance(sample_data) |
||
872 | |||
873 | return result_rows_yearly, mean, median, minimum, maximum, stdev, variance |
||
874 |