query: Efficiently convert a vector of bin counts to a vector of bin indices
positive_passages.docid: 151766
positive_passages.text: Inverse of numpy's bincount function
negative_passages.docid: 19013
negative_passages.text: What is a good algorithm for estimating the median of a huge read-once data set?
negative_passages.docid: 123622
negative_passages.text: Generate correlated random numbers from binomial distributions
negative_passages.docid: 4618
negative_passages.text: Can counting byte matches between two strings be optimized using SIMD?
negative_passages.docid: 53377
negative_passages.text: Fast matrix transposition in Python
negative_passages.docid: 126544
negative_passages.text: Constructing N-dimensional vectors out of point distances
negative_passages.docid: 135247
negative_passages.text: Extracting numbers from vectors of strings
negative_passages.docid: 39159
negative_passages.text: Finding unit tangent, normal, and binormal vectors for a given r(t)
negative_passages.docid: 48695
negative_passages.text: get index of the histogram bin in R
negative_passages.docid: 152852
negative_passages.text: How do I represent and work with n-bit vectors in Python?
negative_passages.docid: 112343
negative_passages.text: vectorized array creation from a list of start/end indices
negative_passages.docid: 1050
negative_passages.text: Counting inversions in an array
negative_passages.docid: 140081
negative_passages.text: Fast and memory efficient moving average calculation
negative_passages.docid: 127708
negative_passages.text: Rolling analysis with out-of sample
negative_passages.docid: 78266
negative_passages.text: R fill vector efficiently
negative_passages.docid: 116827
negative_passages.text: Replace matrix @ vector list comprehensions with something more efficient
negative_passages.docid: 100371
negative_passages.text: Creating a histogram using aggregated data