//+------------------------------------------------------------------+//| Computes the minimum value in array[] |//+------------------------------------------------------------------+doubleMathMin(constdouble &array[],constint start=0,constint count=WHOLE_ARRAY)
{
int size=ArraySize(array);
int data_count=0;
//--- set data countif(count==WHOLE_ARRAY)
data_count=size;
else
data_count=count;
//--- check data rangeif(data_count==0)
return(QNaN);
if(start+data_count>size)
return(QNaN);
//--- set indexesint ind1=start;
int ind2=ind1+data_count-1;
//--- first element by default, find minimumdouble min_value=array[ind1];
for(int i=ind1+1; i<=ind2; i++)
min_value=MathMin(min_value,array[i]);
//--- return minimum valuereturn(min_value);
}
//+------------------------------------------------------------------+//| Computes the maximum value in array[] |//+------------------------------------------------------------------+doubleMathMax(constdouble &array[],constint start=0,constint count=WHOLE_ARRAY)
{
int size=ArraySize(array);
int data_count=0;
//--- set data countif(count==WHOLE_ARRAY)
data_count=size;
else
data_count=count;
//--- check data rangeif(data_count==0)
return(QNaN);
if(start+data_count>size)
return(QNaN);
//--- set indexesint ind1=start;
int ind2=ind1+data_count-1;
//--- first element by default, find maximumdouble max_value=array[ind1];
for(int i=ind1+1; i<=ind2; i++)
max_value=MathMax(max_value,array[i]);
//--- return maximum valuereturn(max_value);
}
//+------------------------------------------------------------------+//| Computes the range of the values in array[] |//+------------------------------------------------------------------+double MathRange(constdouble &array[],constint start=0,constint count=WHOLE_ARRAY)
{
int size=ArraySize(array);
int data_count=0;
//--- set data countif(count==WHOLE_ARRAY)
data_count=size;
else
data_count=count;
//--- check data rangeif(data_count==0)
return(QNaN);
if(start+data_count>size)
return(QNaN);
//--- set indexesint ind1=start;
int ind2=ind1+data_count-1;
//--- default values, find minimum and maximum valuesdouble min_value=array[ind1];
double max_value=array[ind1];
for(int i=ind1+1; i<=ind2; i++)
{
double value=array[i];
min_value=MathMin(min_value,value);
max_value=MathMax(max_value,value);
}
//--- return rangereturn(max_value-min_value);
}
//+------------------------------------------------------------------+//| Computes the sum of the values in array[] |//+------------------------------------------------------------------+double MathSum(constdouble &array[],constint start=0,constint count=WHOLE_ARRAY)
{
int size=ArraySize(array);
int data_count=0;
//--- set data countif(count==WHOLE_ARRAY)
data_count=size;
else
data_count=count;
//--- check data rangeif(data_count==0)
return(QNaN);
if(start+data_count>size)
return(QNaN);
//--- set indexesint ind1=start;
int ind2=ind1+data_count-1;
//--- calculate sumdouble sum=0.0;
for(int i=ind1; i<=ind2; i++)
sum+=array[i];
//--- return sumreturn(sum);
}
//+------------------------------------------------------------------+//| Computes the standard deviation of the values in array[] |//+------------------------------------------------------------------+double MathStandardDeviation(constdouble &array[],constint start=0,constint count=WHOLE_ARRAY)
{
int size=ArraySize(array);
int data_count=0;
//--- set data countif(count==WHOLE_ARRAY)
data_count=size;
else
data_count=count;
//--- check data rangeif(data_count<=1)
return(QNaN);
if(start+data_count>size)
return(QNaN);
//--- set indexesint ind1=start;
int ind2=ind1+data_count-1;
//--- calculate meandouble mean=0.0;
for(int i=ind1; i<=ind2; i++)
mean+=array[i];
//--- average mean
mean=mean/data_count;
//--- calculate standard deviation double sdev=0;
for(int i=ind1; i<=ind2; i++)
sdev+=MathPow(array[i]-mean,2);
//--- return standard deviationreturnMathSqrt(sdev/(data_count-1));
}
//+------------------------------------------------------------------+//| Computes the average absolute deviation of the values in array[] |//+------------------------------------------------------------------+double MathAverageDeviation(constdouble &array[],constint start=0,constint count=WHOLE_ARRAY)
{
int size=ArraySize(array);
int data_count=0;
//--- set data countif(count==WHOLE_ARRAY)
data_count=size;
else
data_count=count;
//--- check data rangeif(data_count<=1)
return(QNaN);
if(start+data_count>size)
return(QNaN);
//--- set indexesint ind1=start;
int ind2=ind1+data_count-1;
//--- calculate meandouble mean=0.0;
for(int i=ind1; i<=ind2; i++)
mean+=array[i];
mean=mean/data_count;
//--- calculate average deviationdouble adev=0;
for(int i=ind1; i<=ind2; i++)
adev+=MathAbs(array[i]-mean);
adev=adev/data_count;
//--- return average deviationreturn(adev);
}
//+------------------------------------------------------------------+//| Computes the median value of the values in array[] |//+------------------------------------------------------------------+double MathMedian(double &array[],constint start=0,constint count=WHOLE_ARRAY)
{
int size=ArraySize(array);
int data_count=0;
//--- set data countif(count==WHOLE_ARRAY)
data_count=size;
else
data_count=count;
//--- check data rangeif(data_count==0)
return(QNaN);
if(start+data_count>size)
return(QNaN);
//--- set indexesint ind1=start;
int ind2=ind1+data_count-1;
//--- prepare sorted valuesdouble sorted_values[];
ArrayCopy(sorted_values,array,0,start,count);
ArraySort(sorted_values);
//--- calculate median for odd and even cases//--- data_count=oddif(data_count%2==1)
return(sorted_values[data_count/2]);
else//--- data_count=evenreturn(0.5*(sorted_values[(data_count-1)/2]+sorted_values[(data_count+1)/2]));
}
//+------------------------------------------------------------------+//| Computes the mean value of the values in array[] |//+------------------------------------------------------------------+double MathMean(constdouble &array[],constint start=0,constint count=WHOLE_ARRAY)
{
int size=ArraySize(array);
int data_count=0;
//--- set data countif(count==WHOLE_ARRAY)
data_count=size;
else
data_count=count;
//--- check data rangeif(data_count<1)
return(QNaN); // need at least 1 observationif(start+data_count>size)
return(QNaN);
//--- set indexesint ind1=start;
int ind2=ind1+data_count-1;
//--- calculate meandouble mean=0.0;
for(int i=ind1; i<=ind2; i++)
mean+=array[i];
mean=mean/data_count;
//--- return meanreturn(mean);
}
//+------------------------------------------------------------------+//| Computes the variance of the values in array[] |//+------------------------------------------------------------------+double MathVariance(constdouble &array[],constint start=0,constint count=WHOLE_ARRAY)
{
int size=ArraySize(array);
int data_count=0;
//--- set data countif(count==WHOLE_ARRAY)
data_count=size;
else
data_count=count;
//--- check data rangeif(data_count<2)
return(QNaN); // need at least 2 observationsif(start+data_count>size)
return(QNaN);
//--- set indexesint ind1=start;
int ind2=ind1+data_count-1;
//--- calculate meandouble mean=0.0;
for(int i=ind1; i<=ind2; i++)
mean+=array[i];
mean=mean/data_count;
//--- calculate variancedouble variance=0;
for(int i=ind1; i<=ind2; i++)
variance+=MathPow(array[i]-mean,2);
variance=variance/(data_count-1);
//--- return variancereturn(variance);
}
//+------------------------------------------------------------------+//| Computes the skewness of the values in array[] |//+------------------------------------------------------------------+double MathSkewness(constdouble &array[],constint start=0,constint count=WHOLE_ARRAY)
{
int size=ArraySize(array);
int data_count=0;
//--- set data countif(count==WHOLE_ARRAY)
data_count=size;
else
data_count=count;
//--- check data rangeif(data_count<3)
return(QNaN); // need at least 3 observationsif(start+data_count>size)
return(QNaN);
//--- set indexesint ind1=start;
int ind2=ind1+data_count-1;
//--- calculate meandouble mean=0.0;
for(int i=ind1; i<=ind2; i++)
mean+=array[i];
mean=mean/data_count;
//--- calculate variance and skewnessdouble variance=0;
double skewness=0;
for(int i=ind1; i<=ind2; i++)
{
double sqr_dev=MathPow(array[i]-mean,2);
skewness+=sqr_dev*(array[i]-mean);
variance+=sqr_dev;
}
variance=(variance)/(data_count-1);
double v3=MathPow(MathSqrt(variance),3);
//---if(v3!=0)
{
skewness=skewness/(data_count*v3);
//--- return skewnessreturn(skewness);
}
elsereturn(QNaN);
}
//+------------------------------------------------------------------+//| Computes the kurtosis of the values in array[] |//+------------------------------------------------------------------+double MathKurtosis(constdouble &array[],constint start=0,constint count=WHOLE_ARRAY)
{
int size=ArraySize(array);
int data_count=0;
//--- set data countif(count==WHOLE_ARRAY)
data_count=size;
else
data_count=count;
//--- check data rangeif(data_count<4)
return(QNaN); // need at least 4 observationsif(start+data_count>size)
return(QNaN);
//--- set indexesint ind1=start;
int ind2=ind1+data_count-1;
//--- calculate meandouble mean=0.0;
for(int i=ind1; i<=ind2; i++)
mean+=array[i];
mean=mean/data_count;
//--- calculate variance and kurtosisdouble variance=0;
double kurtosis=0;
for(int i=ind1; i<=ind2; i++)
{
double sqr_dev=MathPow(array[i]-mean,2);
variance+=sqr_dev;
kurtosis+=sqr_dev*sqr_dev;
}
//--- calculate variance
variance=(variance)/(data_count-1);
double v4=MathPow(MathSqrt(variance),4);
if(v4!=0)
{
//--- calculate kurtosis
kurtosis=kurtosis/(data_count*v4);
kurtosis-=3;
//--- return kurtosisreturn(kurtosis);
}
elsereturn(QNaN);
}
可能已经做过了,但让我问一下。
为什么POSITION_COMMISSION 没有突出显示,也没有出现在帮助中?
这个常数不再有意义,但不幸的是我们不能拒绝它。这就是为什么它在编译器中没有被点亮的原因
我没有看到有什么矛盾。
与什么相抵触?
我在测试器中显示了一个负的余额。另外,股权也在不断地跌破零。我不得不假设这是一个错误。
我什么都不明白,MT5版本1545。在以前的版本中,Math.mqh列表中有一些函数。
而现在它们不在这个列表中,我在其他数学目录列表中寻找,但我在那里也没有找到这些功能。
它们到底是被删除了,还是被意外地删除了?
检查到MT5的1554版本,同样的情况,这些功能已经不存在了。
既然你有整套的数学函数,为什么还需要它们呢?
在你回答之前,请将其与我在列表中发布的那些进行比较。顺便说一下,这些函数在标准库 帮助中列出,所以更有可能是有人不小心把它们删掉了。
在你回答之前,请将其与我在列表中发布的那些进行比较。顺便说一下,这些函数在标准库 帮助中列出,所以更有可能是有人不小心把它们删掉了。
来自servicedesk的回答,标准库中的数据函数已经被特意删除,问题已经解决。帮助也应该被拿来排队,因为有时会浪费时间去寻找已经不在功能中的东西。
这怎么可能呢?我在btc-e.com公司的一个服务器上开了一个模拟账户,但它却在另一家公司的一个完全不同的服务器上开的!
![](https://c.mql5.com/3/121/2017-03-19_22-13-55__1.png)