Program to output the wearing time and other statistics of a Cambridge N99 | FFP2 mask.
Project description
Cambridge Masks Stats
Application to output the wearing time and other statistics of a Cambridge N99 | FFP2 mask.
the program is in the alpha phase. this means that the api will probably change often. the code is written in such a way that the syntax in the console is maintained or at least only minimal changes are made. this description also only deals with the terminal. the api will be described in the documentation of the code, if this is necessary. it is tried to write the code in a way that it is easy to understand.
the application is intended exclusively for the pro version of the cambridge mask, which should be worn for a maximum of 340 hours. the minutes are calculated automatically for aqi_level higher than 2, so that the wear is displayed correctly.
if there is no entry in the csv for a day between the start and end date, the time carried is automatically set to 0 for that day. this means that for months that lie between the start and end month <count_d> also counts the days for which the mask was not worn or for which there is no entry in the csv file.
requirements
python version
Python >= 3.6
dependencies
numpy==1.21.2
pandas==1.3.2
python-dateutil==2.8.2
pytz==2021.1
six==1.16.0
pip installation (with dependencies)
pip install cambridge-mask-stats
csv file
the CSV file to import needs the following header:
date,id,model,aqi_level,minutes_worn
- date -> format yyyy-mm-dd
- id -> mask id. preferably consecutive numbering
- model -> mask model like 'The Churchill Pro'
- aqi_level -> from 1-5 according to the data in the manual (1 = aqi below 50, 2 = 50 - 100 ...)
- minutes_worn -> minutes worn on this date
execute
mask-stats <FILEPATH>
abbreviations in the output
- count_d -> days in the month for which data are available
- hrs -> hours (really worn)
- mean_min_d -> mean minutes daily
- pct -> percent | percentage (determined from sum_min_ratio)
- sum_hrs -> summary hours
- sum_min -> summary minutes
- *_ratio -> values under consideration of the ratio (aqi_level > 2)
example
masks-stats /home/w01fdev/Documents/masks.csv
output
******************* StatsMasks *******************
worn | wear hrs hrs_ratio pct
id model
1 The Admiral Pro 10 12 3.53
2 The Churchill Pro 15 27 7.94
***************** StatsDateRange *****************
worn | wear count_d mean_min_d mean_min_d_ratio sum_min sum_min_ratio sum_hrs sum_hrs_ratio pct
2020-08-31 1 58 58 58 58 0 0 0.28
2020-09-30 30 9 18 278 563 4 9 2.76
2020-10-31 31 39 56 1237 1759 20 29 8.62
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