程序库: 日历 - 页 5

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BillionerClub #:

但在合并数组时，最终数组会出现排序错误，因为数组中最近的元素应该有更长的时间。

我没有注意到这样的情况。试着创建一个脚本来重现它。

 

关于交易、自动交易系统和交易策略测试的论坛

图书馆：日历

BillionerClub, 2022.11.04 07:43 pm.

   int totall = Calendar+=Calendar3;

for(int i=0;i<totall;i++)
  {
   Print(TimeToString(Calendar[i].time));
  }
合并前添加。 
Calendar.Save("Calendar.bin");
Calendar3.Save("Calendar3.bin");

并附上生成的 bin 文件。这样我就能复制了。

 
fxsaber #:
在合并之前添加。

并附上生成的 bin 文件。然后我就可以再做一次了。

附件 链接

 

如果不添加到 "事件 "类，您将无法重现该事件。

  ENUM_CALENDAR_EVENT_SECTOR Sector;
  ENUM_CALENDAR_EVENT_TYPE EventType;
  ENUM_CALENDAR_EVENT_SECTOR Sector;
  ENUM_CALENDAR_EVENT_UNIT Unit;
  ENUM_CALENDAR_EVENT_MULTIPLIER Multiplier;
  ENUM_CALENDAR_EVENT_TIMEMODE TimeMode;
  ENUM_CALENDAR_EVENT_TYPE EventType;
  STRING4 CurrencySymbol;

  EVENT( void ) : time(0), Importance(CALENDAR_IMPORTANCE_NONE), id(0), EventID(0),
                  Actual(LONG_MIN), Previous(LONG_MIN), Revised(LONG_MIN), Forecast(LONG_MIN),
                  Unit(CALENDAR_UNIT_NONE), Multiplier(CALENDAR_MULTIPLIER_NONE), TimeMode(CALENDAR_TIMEMODE_DATETIME ),Sector(CALENDAR_SECTOR_NONE),EventType(CALENDAR_TYPE_HOLIDAY)
  {
Calendar.Set(NULL,CALENDAR_IMPORTANCE_MODERATE,currentday,MaxTime);
Calendar3.SetHolydays(NULL,CALENDAR_TYPE_HOLIDAY,currentday,MaxTime);
  int SetHolydays( const string sCurrency = NULL, const ENUM_CALENDAR_EVENT_TYPE EventType = CALENDAR_TYPE_HOLIDAY,
           const datetime From = -1, const datetime To = -WEEK )
  {
    int Amount = 0;

    MqlCalendarValue Values[];

    if (::CalendarValueHistory(Values, (From >= 0) ? From : ::TimeTradeServer(), (To < 0) ? ::TimeTradeServer() - To : To, NULL, sCurrency))
    {
      const int Size = ::ArrayResize(this.Events, ::ArraySize(Values));

      for (int i = 0; i < Size; i++)
      {
        if (this.Events[Amount].Set(Values[i]) && (this.Events[Amount].EventType == EventType))
        {
          Amount++;
        }
      }
    }

    return(::ArrayResize(this.Events, Amount));
  }
  
 
BillionerClub #:

附件 链接

#include <fxsaber\Calendar\Calendar.mqh>

void OnStart()
{
  CALENDAR Calendar;
  
  Calendar.Load("Calendar.bin");

  Print(Calendar.ToString());
}


2022.11.04 17:00 USD 2 Baker Hughes US Oil Rig Count(baker-hughes-us-oil-rig-count), United States(US) |  |  | 610 | 
2022.11.04 17:00 USD 2 Baker Hughes US Total Rig Count(baker-hughes-us-total-rig-count), United States(US) |  |  | 768 | 
2022.11.08 AllDay EUR 2 Economic and Financial Affairs Council Meeting(economic-financial-affairs-council-meeting), European Union(EU) |  |  |  | 
2022.11.07 ≈02:00 CNY 2 Trade Balance USD(trade-balance-usd), China(CN) |  | $83.12 B | $84.74 B | 
2022.11.07 ≈02:00 CNY 2 Trade Balance(trade-balance), China(CN) |  | ¥565.34 B | ¥573.57 B |

原因是这样的。合并排序只有在两个日历都排序的情况下才会起作用。在这里，原始日历没有按时间排序。

 
fxsaber #:

原始日历不是按时间排序的。

原因是这样的。

#include <fxsaber\Calendar\Calendar.mqh>

void OnStart()
{
  CALENDAR Calendar;
  
  const int Size = Calendar.Set(NULL, CALENDAR_IMPORTANCE_NONE, 0, INT_MAX); // 用了整个日历。

  for (int i = 1; i < Size; i++)
    if (Calendar[i].time < Calendar[i - 1].time)
    {
      Print("----------");
      Print(Calendar[i - 1].ToString());
      Print(Calendar[i].ToString());
    }  
}


...............

2022.11.01 AllDay EUR 0 День всех святых(all-saints-day), Италия(IT) |  |  |  | 
2022.10.31 04:00 SGD 1 Объём банковского кредитования(bank-loans), Сингапур(SG) | R$838.81 B | R$846.787 B | R$842.813 B | 
----------
2022.11.02 AllDay BRL 0 День поминовения усопших(all-souls-day), Бразилия(BR) |  |  |  | 
2022.11.01 05:30 AUD 2 Заявление Резервного Банка Австралии по процентной ставке(rba-rate-statement), Австралия(AU) |  |  |  | 
----------
2022.11.03 AllDay JPY 0 День культуры(culture-day), Япония(JP) |  |  |  | 
2022.11.02 09:00 EUR 1 Объем экспорта м/м(exports-mm), Германия(DE) | -0.5% | -0.7% | 1.6% | 2.9%
----------
2022.11.07 AllDay EUR 2 Заседание Еврогруппы(eurogroup-meeting), Европейский Союз(EU) |  |  |  | 
2022.11.04 07:00 SGD 2 Розничные продажи м/м(retail-sales-mm), Сингапур(SG) | 3.3% | 0.3% | -1.3% | -1.2%
----------
2022.11.08 AllDay EUR 2 Заседание совета по экономическим и финансовым вопросам(economic-financial-affairs-council-meeting), Европейский Союз(EU) |  |  |  | 
2022.11.07 ≈04:00 CNY 2 Торговый баланс USD(trade-balance-usd), Китай(CN) |  | $83.12 B | $84.74 B | 
----------
2022.11.11 AllDay EUR 2 Заседание совета по экономическим и финансовым вопросам(economic-financial-affairs-council-meeting), Европейский Союз(EU) |  |  |  | 
2022.11.10 09:00 NOK 2 Индекс потребительских цен м/м(cpi-mm), Норвегия(NO) |  | 0.5% | 1.4% | 

............
ZY错误报告。 @BillionerClub，感谢您的提示！
 
fxsaber #:

原始日历不是按时间排序的。

修复选项。

  int Set( const string sCurrency = NULL, const ENUM_CALENDAR_EVENT_IMPORTANCE MinImportance = CALENDAR_IMPORTANCE_HIGH,
           const datetime From = -1, const datetime To = -WEEK )
  {
    int Amount = 0;

    MqlCalendarValue Values[];
    
    if (::CalendarValueHistory(Values, (From >= 0) ? From : ::TimeTradeServer(), (To < 0) ? ::TimeTradeServer() - To : To, NULL, sCurrency))
    {      
      //https://www.mql5.com/ru/forum/434546/page11#comment_43037160
      if (::TerminalInfoInteger(TERMINAL_BUILD) < 3481)) // 详细说明他们将在何处解决问题。
        ArraySortStruct2(Values, time); //https://www.mql5.com/ru/forum/170952/page222#comment_40289584
      
      const int Size = ::ArrayResize(this.Events, ::ArraySize(Values));

      for (int i = 0; i < Size; i++)
        if (this.Events[Amount].Set(Values[i]) && (this.Events[Amount].Importance >= MinImportance))
          Amount++;
    }

    return(::ArrayResize(this.Events, Amount));
  }


在全局范围内写入。

ArraySortStruct2_Define(time) //https://www.mql5.com/ru/forum/170952/page222#comment_40289584
 
fxsaber #:


原因是这样的。合并排序只有在两个日历都排序的情况下才会起作用。在这里，源日历没有按时间排序。

谢谢。如果没有你，我永远也想不明白 )) 一切看起来都太正确了，而且通过了所有检查。

 

请帮助了解这些日历是否正确。

我把已知的工资单 和几份日历进行了比较。在新闻发布时，它们似乎是一致的。

// 输出非农就业数据。

#include <fxsaber\Calendar\Calendar.mqh> //https://www.mql5.com/zh/code/32430

void OnStart()
{
  CALENDAR Calendar;
  
  Calendar.Set(840030016); // 非农就业人数（非农就业人数），美国（US）
  Calendar.FilterByTime(D'2019.01.01', D'2023.01.01');
  
  for (int i = Calendar.GetAmount() - 1; i >= 0; i--)
    Print(Calendar[i].ToString());
}


2022.12.02 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 263 K | -30 K | 261 K | 284 K
2022.11.04 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 261 K | -97 K | 263 K | 315 K
2022.10.07 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 263 K | 33 K | 315 K | 
2022.09.02 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 315 K | 156 K | 528 K | 526 K
2022.08.05 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 528 K | -19 K | 372 K | 398 K
2022.07.08 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 372 K | -229 K | 390 K | 384 K
2022.06.03 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 390 K | -19 K | 428 K | 436 K
2022.05.06 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 428 K | 317 K | 431 K | 428 K
2022.04.01 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 431 K | 80 K | 678 K | 750 K
2022.03.04 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 678 K | -413 K | 467 K | 481 K
2022.02.04 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 467 K | -192 K | 199 K | 510 K
2022.01.07 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 199 K | 379 K | 210 K | 249 K
2021.12.03 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 210 K | 330 K | 531 K | 546 K
2021.11.05 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 531 K | -54 K | 194 K | 312 K
2021.10.08 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 194 K | -302 K | 235 K | 366 K
2021.09.03 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 235 K | 23 K | 943 K | 1053 K
2021.08.06 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 943 K | 381 K | 850 K | 938 K
2021.07.02 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 850 K | 3 K | 559 K | 583 K
2021.06.04 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 559 K | -396 K | 266 K | 278 K
2021.05.07 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 266 K | -1 K | 916 K | 770 K
2021.04.02 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 916 K | 409 K | 379 K | 468 K
2021.03.05 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 379 K | -137 K | 49 K | 166 K
2021.02.05 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 49 K | -497 K | -140 K | -227 K
2021.01.08 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | -140 K | 207 K | 245 K | 336 K
2020.12.04 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 245 K | 528 K | 638 K | 610 K
2020.11.06 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 638 K | -76324 K | 661 K | 672 K
2020.10.02 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 661 K | 78356 K | 1371 K | 1489 K
2020.09.04 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 1371 K | -74433 K | 1763 K | 1734 K
2020.08.07 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 1763 K | 4511 K | 4800 K | 4791 K
2020.07.02 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 4800 K | -12034 K | 2509 K | 2699 K
2020.06.05 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 2509 K | -10000 K | -20500 K | -20687 K
2020.05.08 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | -20500 K | 139 K | -701 K | -870 K
2020.04.03 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | -701 K | 163 K | 273 K | 275 K
2020.03.06 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 273 K | 161 K | 225 K | 273 K
2020.02.07 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 225 K | 161 K | 145 K | 147 K
2020.01.10 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 145 K | 168 K | 266 K | 256 K
2019.12.06 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 266 K | 168 K | 128 K | 156 K
2019.11.01 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 128 K | 172 K | 136 K | 180 K
2019.10.04 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 136 K | 174 K | 130 K | 168 K
2019.09.06 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 130 K | 177 K | 164 K | 159 K
2019.08.02 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 164 K | 178 K | 224 K | 193 K
2019.07.05 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 224 K | 176 K | 75 K | 72 K
2019.06.07 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 75 K | 170 K | 263 K | 224 K
2019.05.03 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 263 K | 167 K | 196 K | 189 K
2019.04.05 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 196 K | 176 K | 20 K | 33 K
2019.03.08 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 20 K | 173 K | 304 K | 311 K
2019.02.01 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 304 K | 168 K | 312 K | 222 K
2019.01.04 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 312 K | 170 K | 155 K | 176 K

表格日历数据与价格数据不匹配。脚本以经纪商的时区显示数据，因此您可以在任何交易服务器上进行比较。

forexfactori 和投资日历显示的数据似乎与 MQL5 相同。

还有谁的价格数据与日历日期不一致？


ZЫ 如果日历会说谎，那么市场顾问 如何在回溯测试中绕过新闻？

Изменение числа занятых в несельскохозяйственном секторе - экономический индикатор США
Изменение числа занятых в несельскохозяйственном секторе - экономический индикатор США
  • www.mql5.com
Изменение числа занятых в несельскохозяйственном секторе (Nonfarm Payrolls) — показатель, отражающий количество новых рабочих мест, созданных в отчетном месяце, во всех отраслях экономики США, кроме
 
fxsaber #:

如果日历会说谎，那么市场顾问如何在回溯测试中绕过新闻？

看起来它们确实会撒谎。自动发现差异。

// 比较日历中的非农就业日期和历史价格。在美元货币对上运行。

#include <fxsaber\Calendar\Calendar.mqh> //https://www.mql5.com/zh/code/32430

// 时间条大小。
double GetBarSize( const datetime Time )
{
  MqlRates Rates[];
  
  return(CopyRates(_Symbol, PERIOD_M1, iBarShift(_Symbol, PERIOD_M1, Time), 1, Rates) != 1 ? 0 : Rates[0].high - Rates[0].low);
}

// 最大条形的时间（按数组中的时间）。
datetime GetMaxBarSizeTime( const datetime &Times[] )
{
  double Values[];
  
  for (int i = ArrayResize(Values, ArraySize(Times)) - 1; i >= 0; i--)
    Values[i] = GetBarSize(Times[i]);
  
  return(Times[ArrayMaximum(Values)]);
}

// 最有可能出现价格数据新闻的时间（反应强烈）。
datetime ChartNewsTime( const datetime &Time )
{
  datetime Times[3];
      
  Times[0] = Time;
  Times[1] = Times[0] - 3600;
  Times[2] = Times[0] + 3600;
  
  return(GetMaxBarSizeTime(Times));
}

void OnStart()
{
  CALENDAR Calendar;
  
  Calendar.Set(840030016); // 非农就业人数（非农就业人数），美国（US）
  Calendar.FilterByTime(D'2019.01.01', D'2023.01.01');
  
  for (int i = Calendar.GetAmount() - 1; i >= 0; i--)
  {
    const EVENT Event = Calendar[i];    
    const datetime ChartNews = ChartNewsTime(Event.time);
    
    if (Event.time != ChartNews)    
      Print(TimeToString(ChartNews) + " != " + Event.ToString());
  }
}


下面每一行中的差异。

2022.10.07 15:30 != 2022.10.07 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 263 K | 33 K | 315 K | 
2022.09.02 15:30 != 2022.09.02 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 315 K | 156 K | 528 K | 526 K
2022.08.05 15:30 != 2022.08.05 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 528 K | -19 K | 372 K | 398 K
2022.07.08 15:30 != 2022.07.08 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 372 K | -229 K | 390 K | 384 K
2022.06.03 15:30 != 2022.06.03 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 390 K | -19 K | 428 K | 436 K
2022.05.06 15:30 != 2022.05.06 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 428 K | 317 K | 431 K | 428 K
2022.04.01 15:30 != 2022.04.01 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 431 K | 80 K | 678 K | 750 K
2021.10.08 15:30 != 2021.10.08 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 194 K | -302 K | 235 K | 366 K
2021.09.03 15:30 != 2021.09.03 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 235 K | 23 K | 943 K | 1053 K
2021.08.06 15:30 != 2021.08.06 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 943 K | 381 K | 850 K | 938 K
2021.07.02 15:30 != 2021.07.02 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 850 K | 3 K | 559 K | 583 K
2021.06.04 15:30 != 2021.06.04 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 559 K | -396 K | 266 K | 278 K
2021.05.07 15:30 != 2021.05.07 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 266 K | -1 K | 916 K | 770 K
2021.04.02 15:30 != 2021.04.02 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 916 K | 409 K | 379 K | 468 K
2020.10.02 15:30 != 2020.10.02 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 661 K | 78356 K | 1371 K | 1489 K
2020.09.04 15:30 != 2020.09.04 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 1371 K | -74433 K | 1763 K | 1734 K
2020.08.07 15:30 != 2020.08.07 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 1763 K | 4511 K | 4800 K | 4791 K
2020.07.02 15:30 != 2020.07.02 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 4800 K | -12034 K | 2509 K | 2699 K
2020.06.05 15:30 != 2020.06.05 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 2509 K | -10000 K | -20500 K | -20687 K
2020.05.08 15:30 != 2020.05.08 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | -20500 K | 139 K | -701 K | -870 K
2020.04.03 15:30 != 2020.04.03 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | -701 K | 163 K | 273 K | 275 K
2019.10.04 15:30 != 2019.10.04 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 136 K | 174 K | 130 K | 168 K
2019.09.06 15:30 != 2019.09.06 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 130 K | 177 K | 164 K | 159 K
2019.08.02 15:30 != 2019.08.02 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 164 K | 178 K | 224 K | 193 K
2019.07.05 15:30 != 2019.07.05 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 224 K | 176 K | 75 K | 72 K
2019.06.07 15:30 != 2019.06.07 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 75 K | 170 K | 263 K | 224 K
2019.05.03 15:30 != 2019.05.03 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 263 K | 167 K | 196 K | 189 K
2019.04.05 15:30 != 2019.04.05 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 196 K | 176 K | 20 K | 33 K

左边是新闻对价格反应的时间，右边是日历。


看来我们应该在日历日期上做一个自动校正器。

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