python-iqm

Interquartile Mean pure-Python module. It contains two classes:

DictIQM
MovingIQM

DictIQM

This class is efficient for datasets in which many numbers are repeated. It should not be used for large datasets with a uniform distribution. The trade-off between accuracy and memory usage can be manged with its round_digits argument.

Usage

from iqm import DictIQM
import sys

diqm = DictIQM(round_digits=-1, tenth_precise=True)
for line in open("source1_numbers_list.txt", "r"):
    diqm("source1", line)

print "# {:12,.2f}    Dict IQM".format(diqm.report("source1"))

MovingIQM

This class sacrifices accuracy for speed and low memory usage.

Usage

from iqm import MovingIQM
import sys

miqm = MovingIQM(1000)
for line in open("source1_numbers_list.txt", "r"):
    miqm("source1", line)

print "# {:12,.2f}    Moving IQM".format(miqm.report("source1"))

License

See LICENSE.txt (MIT License).

Release files for python-iqm 0.2.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for python-iqm 0.2.1
File	Size	Uploaded
python-iqm-0.2.1.tar.gz	4.4 kB	Oct 18, 2013	Details

Release files / python-iqm-0.2.1.tar.gz

Download URL	python-iqm-0.2.1.tar.gz
Size	4.4 kB
Tags	Source
SHA-256 checksum How to use checksums	`a50764f03c22482b61a597195c5fe942d2cbb01ff117e08fca89a4b51131f782`
BLAKE2b-256 checksum How to use checksums	`4fbb1e861cb154f88c883b114d827975e76ff53d512ddc2f45bc7a46d4cc4082`
Upload date	Oct 18, 2013
Uploaded using Trusted Publishing? What is trusted publishing?	No