Here is some sample C++ code extracted from a current throwaway project using openCV 3.4.1. Hope this helps.

```
// input floating point image fdata of size nrows x ncols
cv::Mat fdata = cv::Mat::zeros(nrows,ncols,CV_32FC1);
// load data into fdata here
// set up to find maximum and minimum values
double minv, maxv;
cv::minMaxIdx(fdata,&minv,&maxv);
// mask is from thresholding all data above 31 counts
cv::Mat mask8 = cv::Mat::zeros(nrows,ncols,CV_8UC1);
// mask8 values are 0 or 255
cv::threshold(fdata,mask8,31,255,cv::THRESH_BINARY);
// size of histogram to create
int hist_sz = 10;
// create "tree" of pointers for binning histogram, contains max and min values
float rngs[2];
rngs[0] = static_cast<float>(minv);
rngs[1] = static_cast<float>(maxv);
const float* prng = { &rngs[0] };
const float** ranges = { &prng };
// print out values to see if tree is correct so that histogram function will not assert an error
std::cout << "ranges[0]=" << ranges[0] << " ranges[0][0]=" << ranges[0][0] <<
" ranges[0][1]=" << ranges[0][1] << std::endl;
// compute histogram on first channel
int chan = 0;
cv::MatND hist;
cv::calcHist(&fdata,1,&chan,mask8,hist,1,&hist_sz,ranges,true,false);
// histogram now only contains data counted from pixels with mask8 > 0
// note that histogram is of type float and is a cv::Mat vector with 10 rows and 1 column
```

Do you want to use mask? mask is used to find histogram of a specific region of image. If you want to find histogram of full image, just ignore it.