**proxyC** computes proximity between rows or columns of
large matrices efficiently in C++. It is optimized for large sparse
matrices using the Armadillo and Intel TBB libraries. Among several
built-in similarity/distance measures, computation of correlation,
cosine similarity and Euclidean distance is particularly fast.

This code was originally written for **quanteda**
to compute similarity/distance between documents or features in large
corpora, but separated as a stand-alone package to make it available for
broader data scientific purposes.

`install.packages("proxyC")`

```
require(Matrix)
## Loading required package: Matrix
require(microbenchmark)
## Loading required package: microbenchmark
require(RcppParallel)
## Loading required package: RcppParallel
require(ggplot2)
## Loading required package: ggplot2
require(magrittr)
## Loading required package: magrittr
# Set number of threads
setThreadOptions(8)
# Make a matrix with 99% zeros
<- rsparsematrix(1000, 1000, 0.01) # 1,000 columns
sm1k <- rsparsematrix(1000, 10000, 0.01) # 10,000 columns
sm10k
# Convert to dense format
<- as.matrix(sm1k)
dm1k <- as.matrix(sm10k) dm10k
```

With sparse matrices, **proxyC** is roughly 10 to 100
times faster than **proxy**.

```
<- microbenchmark(
bm1 "proxy 1k" = proxy::simil(dm1k, method = "cosine"),
"proxyC 1k" = proxyC::simil(sm1k, margin = 2, method = "cosine"),
"proxy 10k" = proxy::simil(dm10k, method = "cosine"),
"proxyC 10k" = proxyC::simil(sm10k, margin = 2, method = "cosine"),
times = 10
)autoplot(bm1)
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
```

If `min_simil`

is used, **proxyC** becomes
even faster because small similarity scores are floored to zero.

```
<- microbenchmark(
bm2 "proxyC all" = proxyC::simil(sm1k, margin = 2, method = "cosine"),
"proxyC min_simil" = proxyC::simil(sm1k, margin = 2, method = "cosine", min_simil = 0.9),
times = 10
)autoplot(bm2)
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
```

Flooring by `min_simil`

makes the resulting object much
smaller.

```
::simil(sm10k, margin = 2, method = "cosine") %>%
proxyCobject.size() %>%
print(units = "MB")
## 763 Mb
::simil(sm10k, margin = 2, method = "cosine", min_simil = 0.9) %>%
proxyCobject.size() %>%
print(units = "MB")
## 0.2 Mb
```

If `rank`

is used, **proxyC** only returns
top-n values.

```
<- microbenchmark(
bm3 "proxyC rank" = proxyC::simil(sm1k, margin = 2, method = "correlation", rank = 10),
"proxyC all" = proxyC::simil(sm1k, margin = 2, method = "correlation"),
times = 10
)autoplot(bm3)
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
```