foundryts.functions.unit_conversion

foundryts.functions.unit_conversion(from_unit, to_unit)

Returns a function that converts all values in a single time series from the specified unit value to the specified unit.

The unit passed can either be a value from Unit or a valid Alias from the list of available units and conversions below:

Length

Unit	Alias	Names
m	meter	Meter
cm	centimeter	Centimeter
mm	millimeter	Millimeter
μm	micron, micrometer	Micrometer
nm	nanometer	Nanometer
angstrom		Angstrom
km	kilometer	Kilometer
in	inch	Inch
ft	foot	Foot
yd	yard	Yard
mi	mile	Mile

Temperature Units

Unit	Alias	Names
°C	Celsius	Celsius
K	kelvin	Kelvin
°F	Fahrenheit	Fahrenheit
°R	°Ra, rankine	Rankine

Pressure Units

Unit	Alias	Names
Pa	n/m2, pascal	Pascal
hPa	hectopascal	Hectopascal
kPa	kPaa, kilopascal	Kilopascal
kPag		Kilopascal gauge
atm		Atmosphere
bar	bara	Bar
barg		Bar gauge
fth2o		Foot of Water Column
inh2o		Inches of water
inhg		Inch of Mercury
Torr	mmhg	Torr (mmhg)
mTorr		Millitorr
psi	psia	Pound-force per square inch
psig		Pound-force per square inch gauge

Time Units

Unit	Alias	Names
s	second	Second
ms	millisecond	Millisecond
μs	microsecond	Microsecond
ns	nanosecond	Nanosecond
min	minute	Minute
hr	hour	Hour

Mass Units

Unit	Alias	Names
kg	kilogram	Kilogram
g	gram	Gram
lb	pound	Pound

Contact your service administrator to access and extend the list of units and conversions for your deployment.

Parameters:
- from_unit (str) – Original unit to convert values from.
- to_unit (str) – Desired unit to convert values to.
Returns: A function that accepts a single time series as input and returns the time series with values converted to the specified unit.
Return type: (FunctionNode) -> FunctionNode

Dataframe schema

Column name	Type	Description
timestamp	pandas.Timestamp	Timestamp of the point
value	float	Value of the point

Note

This function is only applicable to numeric series.

Examples

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>>> series = F.points(
...     (1, 8.0),
...     (101, 4.0),
...     (200, 2.0),
...     (201, 1.0),
...     (299, 35.0),
...     (300, 16.0),
...     (1000, 64.0),
...     name="series",
... )
>>> series.to_pandas()
                      timestamp  value
0 1970-01-01 00:00:00.000000001    8.0
1 1970-01-01 00:00:00.000000101    4.0
2 1970-01-01 00:00:00.000000200    2.0
3 1970-01-01 00:00:00.000000201    1.0
4 1970-01-01 00:00:00.000000299   35.0
5 1970-01-01 00:00:00.000000300   16.0
6 1970-01-01 00:00:00.000001000   64.0

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>>> unit_converted = F.unit_conversion("m", "mm")(series)
>>> unit_converted.to_pandas()
                      timestamp    value
0 1970-01-01 00:00:00.000000001   8000.0
1 1970-01-01 00:00:00.000000101   4000.0
2 1970-01-01 00:00:00.000000200   2000.0
3 1970-01-01 00:00:00.000000201   1000.0
4 1970-01-01 00:00:00.000000299  35000.0
5 1970-01-01 00:00:00.000000300  16000.0
6 1970-01-01 00:00:00.000001000  64000.0

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