Skip to main content

loggertools: a Python port of the Control File Functions of Loggertools, the Logger Tools Software of Olaf Kolle, MPI-BGC Jena, (c) 2012.

Project description

A Python port of the Control File Functions of the Logger Tools Software of Olaf Kolle, MPI-BGC Jena, (c) 2012.

Zenodo DOI PyPI version Conda version License Build status

About loggertools

loggertools is a Python port of the Control File Functions of the Logger Tools Software of Olaf Kolle, MPI-BGC Jena, (c) 2012.

From the Logger Tools Software manual: “The functions range from simple mathematic operations to more complex and special procedures including functions for checking data. Most of the functions have the following appearance: y = f(x, p1, p2, …, pn) where y is the variable in which the result of the function f is stored, x is the input variable of the function and p1 to pn are parameters (numbers) of the function. An output variable (result of a function) may be the same as an input variable. Some functions need more than one input variable, some functions do not need any parameter and some functions (mean, mini, maxi) may have a variable number of input variables.”

The complete documentation of loggertools is available at:

https://mcuntz.github.io/loggertools/

and the API can be found here:

https://mcuntz.github.io/loggertools/html/loggertools.html

Installation

The easiest way to install is via pip:

pip install loggertools

or via conda:

conda install -c conda-forge loggertools
Requirements

License

loggertools is distributed under the MIT License. See the LICENSE file for details.

Copyright (c) 2014-2023 Matthias Cuntz, Olaf Kolle

The project structure of loggertools has borrowed heavily from welltestpy by Sebastian Müller.

Logger Tool Functions

Some functions are renamed compared to the original logger tools:

chs -> varchs

add -> varadd

sub -> varsub

mul -> varmul

div -> vardiv

sqr -> varsqr / varsqrt

exp -> varexp

log -> varlog

pot -> varpot

Not all functions are implemented (yet). Missing functions are:

varset

met_torad

met_psy_rh

met_dpt_rh

write

Some functions are slightly enhanced, which is reflected in the documentation of the indidual functions.

All functions have an additional keyword undef, which defaults to -9999.: elements are excluded from the calculations if any of the inputs equals undef.

Only bit_test and the if-statements ifeq, ifne, ifle, ifge, iflt, igt do not have the undef keyword.

The Logger Tools control functions implemented are:

  1. Assignment

    # not implemented

  2. Change sign

    y = varchs(a) means y = -a, where a is a variable or a number.

    def varchs(var1, undef=-9999.):

  3. Addition

    y = varadd(a, b) means y = a + b, where a and b are ndarray or float.

    def varadd(var1, var2, undef=-9999.):

  4. Subtraction

    y = varsub(a, b) means y = a - b, where a and b are ndarray or float.

    def varsub(var1, var2, undef=-9999.):

  5. Multiplication

    y = varmul(a, b) means y = a * b, where a and b are ndarray or float.

    def varmul(var1, var2, undef=-9999.):

  6. Division

    y = vardiv(a, b) means y = a / b, where a and b are ndarray or float.

    def vardiv(var1, var2, undef=-9999.):

  7. Square root

    y = varsqr(a) means y = sqrt(a), where a is a variable or a number.

    y = varsqrt(a) means y = sqrt(a), where a is a variable or a number.

    def varsqr(var1, undef=-9999.):

    def varsqrt(var1, undef=-9999.):

  8. Exponentiation of e

    y = varexp(a) means y = exp(a), where a is a variable or a number.

    def varexp(var1, undef=-9999.):

  9. Natural logarithm

    y = varlog(a) means y = ln(a), where a is a variable or a number.

    def varlog(var1, undef=-9999.):

  10. Exponentiation

    y = varpot(a, b) means y = a**b, where a and b are ndarray or float.

    def varpot(var1, var2, undef=-9999.):

  11. Apply linear function

    y = lin(x, a0, a1) means y = a0 + a1 * x, where a0 and a1 are ndarray or float.

    def lin(var1, a, b, undef=-9999.):

  12. Apply 2nd order function

    y = quad(x, a0, a1, a2) means y = a0 + a1 * x + a2 * x**2, where a0, a1 and a2 are ndarray or float.

    def quad(var1, a, b, c, undef=-9999.):

  13. Apply 3rd order function

    y = cubic(x, a0, a1, a2, a3) means y = a0 + a1 * x + a2 * x**2 + a3 * x**3, where a0, a1, a2 and a3 are ndarray or float.

    def cubic(var1, a, b, c, d, undef=-9999.):

  14. Calculate fraction of day from hours, minutes and seconds

    y = hms(h, m, s) means y = (h + m/60 + s/3600)/24, where h, m and s (hours, minutes and seconds) are ndarray or float.

    def hms(h, m, s, undef=-9999.):

  15. Bitwise test

    y = bit_test(x, b, start=0) means y = 1 if bit b is set in x otherwise y = 0.

    Returns a list of b is an array.

    Counting of b starts at start.

    For the behaviour of the original logger tools, set start=1.

    Negative b are not implemented.

    def bit_test(var1, var2, start=0):

  16. Replacement of underflows by new value

    y = setlow(x, lo, ln=None) means IF (x > lo) THEN y = ln ELSE y = x, where lo and ln are ndarray or float.

    ln is optional. If not given lo will be used.

    This function may be used to adjust small negative values of short wave radiation during nighttime to zero values.

    def setlow(dat, low, islow=None, undef=-9999.):

  17. Replacement of overflows by new value

    y = sethigh(x, lo, ln=None) means IF (x < lo) THEN y = ln ELSE y = x, where lo and ln are ndarray or float.

    ln is optional. If not given lo will be used.

    This function may be used to adjust relative humidity values of a little bit more than 100% to 100%.

    def sethigh(dat, high, ishigh=None, undef=-9999.):

  18. Replacement of underflows or overflows by the undef

    y = limits(x, ll, lh) means IF (x > ll) OR (x < lh) THEN y = undef ELSE y = x, where ll and lh are ndarray or float.

    This function may be used to check values lying in between certain limits. If one of the limits is exceeded the value is set to undef.

    def limits(dat, mini, maxi, undef=-9999.):

  19. Calculation of mean value

    y = mean(x1, x2, …, xn) means y = (x1 + x2 + … + xn) / n, where x1, x2, …, xn are ndarray or float.

    def mean(var1, axis=None, undef=-9999.):

  20. Calculation of minimum value

    y = mini(x1, x2, …, xn) means y = min(x1, x2, …, xn), where x1, x2, …, xn are ndarray or float.

    def mini(var1, axis=None, undef=-9999.):

  21. Calculation of maximum value

    y = maxi(x1, x2, …, xn) means y = max(x1, x2, …, xn), where x1, x2, …, xn are ndarray or float.

    def maxi(var1, axis=None, undef=-9999.):

  22. Calculation of total radiation from net radiometer

    # no implemented

  23. Calculation of long wave radiation from net radiometer

    y = met_lwrad(x, Tp) where x is the output voltage of the net radiometer in mV, Tp is the temperature of the net radiometer body in degC.

    The total radiation in W m-2 is calculated according to the following formula:

    y = x * fl + sigma * (Tp + 273.16)**4

    where sigma = 5.67051 * 10**8 W m-2 K-4 is the Stephan-Boltzmann-Constant and fl is the factor for long wave radiation (reciprocal value of sensitivity) in W m-2 per mV.

    The function assumes that fl was already applied before.

    All parameters may be ndarray or float.

    # assumes that dat was already multiplied with calibration factor def met_lwrad(dat, tpyr, undef=-9999.):

  24. Calculation of radiation temperature from long wave radiation

    y = met_trad(Rl, epsilon) where Rl is the long wave radiation in W m-2, epsilon is the long wave emissivity of the surface (between 0 and 1).

    The radiation temperature in degC is calculated according to the following formula:

    y = sqrt4(Rl / (sigma * epsilon)) - 273.16

    where sigma = 5.67051 * 10**8 W m-2 K-4 is the Stephan-Boltzmann-Constant.

    Both parameters may be ndarray or float.

    def met_trad(dat, eps, undef=-9999.):

  25. Calculation of albedo from short wave downward and upward radiation

    y = met_alb(Rsd, Rsu) where Rsd is the short wave downward radiation in Wm-2, Rsu is the short wave upward radiation in Wm-2,

    The albedo in % is calculated according to the following formula:

    y = 100 * ( Rsu / Rsd )

    If Rsd > 50 W m-2 or Rsu > 10 W m-2 the result is undef.

    Both parameters may be ndarray or float.

    def met_alb(swd, swu, swdmin=50., swumin=10., undef=-9999.):

  26. Calculation of albedo from short wave downward and upward radiation with limits

    y = met_albl(Rsd, Rsu, Rsd_limit, Rsu_limit) where Rsd is the short wave downward radiation in Wm-2, Rsu is the short wave upward radiation in Wm-2, Rsd_limit is the short wave downward radiation limit in Wm-2, Rsu_limit is the short wave upward radiation limit in Wm-2,

    The albedo in % is calculated according to the following formula:

    y = 100 * ( Rsu / Rsd )

    If Rsd > Rsd_limit or Rsu > Rsu_limit the result is undef.

    All four parameters may be ndarray or float.

    def met_albl(swd, swu, swdmin, swumin, undef=-9999.):

  27. Calculation of saturation water vapour pressure

    y = met_vpmax(T) where T is the air temperature in degC.

    The saturation water vapour pressure in mbar (hPa) is calculated according to the following formula:

    y = 6.1078 * exp(17.08085 * T / (234.175 + T))

    The parameter may be a variable or a number.

    def met_vpmax(temp, undef=-9999.):

  28. Calculation of actual water vapour pressure

    y = met_vpact(T, rh) where T is the air temperature in degC, rh is the relative humidity in %.

    The actual water vapour pressure in mbar (hPa) is calculated according to the following formulas:

    Es = 6.1078*exp(17.08085*T/ (234.175 + T))

    y = Es * rh/100

    Both parameters may be ndarray or float.

    def met_vpact(temp, rh, undef=-9999.):

  29. Calculation of water vapour pressure deficit

    y = met_vpdef(T, rh) where T is the air temperature in degC, rh is the relative humidity in %.

    The water vapour pressure deficit in mbar (hPa) is calculated according to the following formulas:

    Es = 6.1078*exp(17.08085*T/ (234.175 + T))

    E = Es * rh/100

    y = Es - E

    Both parameters may be ndarray or float.

    def met_vpdef(temp, rh, undef=-9999.):

  30. Calculation of specific humidity

    y = met_sh(T, rh, p) where T is the air temperature in degC, rh is the relative humidity in %, p is the air pressure in mbar (hPa).

    The specific humidity in g kg-1 is calculated according to the following formulas:

    Es = 6.1078*exp(17.08085*T/ (234.175 + T))

    E = Es * rh/100

    y = 622 * E/(p-0.378*E)

    All parameters may be ndarray or float.

    def met_sh(temp, rh, p, undef=-9999.):

  31. Calculation of potential temperature

    y = met_tpot(T, p) where T is the air temperature in degC, p is the air pressure in mbar (hPa).

    The potential temperature in K is calculated according to the following formula:

    y = (T + 273.16) * (1000/p)**0.286

    Both parameters may be ndarray or float.

    def met_tpot(temp, p, undef=-9999.):

  32. Calculation of air density

    y = met_rho(T, rh, p) where T is the air temperature in degC, rh is the relative humidity in %, p is the air pressure in mbar (hPa).

    The air density in kg m-3 is calculated according to the following formulas:

    Es = 6.1078*exp(17.08085*T/ (234.175 + T))

    E = Es * rh/100

    sh = 622 * E/(p-0.378*E)

    Tv = ((T + 273.16) * (1 + 0.000608 * sh)) - 273.16

    y = p * 100 / (287.05 * (Tv + 273.16))

    All parameters may be ndarray or float.

    def met_rho(temp, rh, p, undef=-9999.):

  33. Calculation of dew point temperature

    y = met_dpt(T, rh) where T is the air temperature in degC, rh is the relative humidity in %.

    The dew point temperature in degC is calculated according to the following formulas:

    Es = 6.1078*exp(17.08085*T/(234.175 + T))

    E = Es * rh/100

    y = 234.175 * ln(E/6.1078)/(17.08085 - ln(E/6.1078))

    Both parameters may be ndarray or float.

    def met_dpt(temp, rh, undef=-9999.):

  34. Calculation of water vapour concentration

    y = met_h2oc(T, rh, p) where T is the air temperature in degC, rh is the relative humidity in %, p is the air pressure in mbar (hPa).

    The water vapour concentration in mmol mol-1 is calculated according to the following formulas:

    Es = 6.1078*exp(17.08085*T/ (234.175 + T))

    E = Es * rh/100

    y = 0.1 * E /(0.001*p*100*0.001)

    All parameters may be ndarray or float.

    def met_h2oc(temp, rh, p, undef=-9999.):

  35. Calculation of relative humidity from dry and wet bulb temperature

    # not implemented

  36. Calculation of relative humidity from dew point temperature

    # not implemented

  37. Calculation of relative humidity from water vapour concentration

    y = met_h2oc_rh(T, [H2O], p) where T is the air temperature in degC, [H2O] is the water vapour concentration in mmolmol-1, p is the air pressure in mbar (hPa).

    The relative humidity in % is calculated according to the following formulas:

    Es = 6.1078*exp(17.08085*T/(234.175 + T))

    E = 10 * [H2O] * 0.001 * p * 100 * 0.001

    y = 100 * E / Es

    All parameters may be ndarray or float.

    def met_h2oc_rh(temp, h, p, undef=-9999.):

  38. Rotation of wind direction

    y = met_wdrot(wd, a) where wd is the wind direction in degree, a is the rotation angle in degree (positive is clockwise).

    The rotated wind direction is calculated according to the following formulas:

    y = wd + a

    IF y > 0 THEN y = y + 360

    IF y >= 360 THEN y = y - 360

    Both parameters may be ndarray or float.

    def met_wdrot(wd, a, undef=-9999.):

  39. Rotation of u-component of wind vector

    y = met_urot(u, v, a) where u is the u-component of the wind vector, v is the v-component of the wind vector, a is the rotation angle in degree (positive is clockwise).

    The rotated u-component is calculated according to the following formula:

    y = u * cos (a) + v * sin (a)

    All three parameters may be ndarray or float.

    def met_urot(u, v, a, undef=-9999.):

  40. Rotation of v-component of wind vector

    y = met_vrot(u, v, a) where u is the u-component of the wind vector, v is the v-component of the wind vector, a is the rotation angle in degree (positive is clockwise).

    The rotated v-component is calculated according to the following formula:

    y = -u * sin (a) + v * cos (a)

    All three parameters may be ndarray or float.

    def met_vrot(u, v, a, undef=-9999.):

  41. Calculation of wind velocity from u- and v-component of wind vector

    y = met_uv_wv(u, v) where u is the u-component of the wind vector, v is the v-component of the wind vector.

    The horizontal wind velocity is calculated according to the following formula:

    y = sqrt(u**2 + v**2)

    Both parameters may be ndarray or float.

    def met_uv_wv(u, v, undef=-9999.):

  42. Calculation of wind direction from u- and v-component of wind vector

    y = met_uv_wd(u, v) where u is the u-component of the wind vector, v is the v-component of the wind vector.

    The horizontal wind velocity is calculated according to the following formulas:

    IF u = 0 AND v = 0 THEN y = 0

    IF u = 0 AND v > 0 THEN y = 360

    IF u = 0 AND v < 0 THEN y = 180

    IF u < 0 THEN y = 270 - arctan(v/u)

    IF u > 0 THEN y = 90 - arctan(v/u)

    Both parameters may be ndarray or float.

    def met_uv_wd(u, v, undef=-9999.):

  43. Calculation of u-component of wind vector from wind velocity and wind direction

    y = met_wvwd_u(wv, wd) where wv is the horizontal wind velocity, wd is the horizontal wind direction.

    The u-component of the wind vector is calculated according to the following formula:

    y = -wv * sin (wd)

    Both parameters may be ndarray or float.

    def met_wvwd_u(wv, wd, undef=-9999.):

  44. Calculation of v-component of wind vector from wind velocity and wind direction

    y = met_wvwd_v(wv, wd) where wv is the horizontal wind velocity, wd is the horizontal wind direction.

    The v-component of the wind vector is calculated according to the following formula:

    y = -wv * cos (wd)

    Both parameters may be ndarray or float.

    def met_wvwd_v(wv, wd, undef=-9999.):

  45. If-statements

    y = ifeq(x, a0, a1, a2) means IF x == a0 THEN y = a1 ELSE y = a2

    y = ifne(x, a0, a1, a2) means IF x != a0 THEN y = a1 ELSE y = a2

    y = ifle(x, a0, a1, a2) means IF x <= a0 THEN y = a1 ELSE y = a2

    y = ifge(x, a0, a1, a2) means IF x >= a0 THEN y = a1 ELSE y = a2

    y = iflt(x, a0, a1, a2) means IF x > a0 THEN y = a1 ELSE y = a2

    y = ifgt(x, a0, a1, a2) means IF x < a0 THEN y = a1 ELSE y = a2

    All parameters may be ndarray or float.

    def ifeq(var1, iif, ithen, ielse):

    def ifne(var1, iif, ithen, ielse):

    def ifle(var1, iif, ithen, ielse):

    def ifge(var1, iif, ithen, ielse):

    def iflt(var1, iif, ithen, ielse):

    def ifgt(var1, iif, ithen, ielse):

  46. Write variables to a file

    # not implemented

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

loggertools-1.0.tar.gz (388.8 kB view details)

Uploaded Source

Built Distribution

loggertools-1.0-py3-none-any.whl (17.1 kB view details)

Uploaded Python 3

File details

Details for the file loggertools-1.0.tar.gz.

File metadata

  • Download URL: loggertools-1.0.tar.gz
  • Upload date:
  • Size: 388.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.2

File hashes

Hashes for loggertools-1.0.tar.gz
Algorithm Hash digest
SHA256 ab167a31c8b0f6f0de7eaabf87714193411286f122d9651e4fc90f7825f28f26
MD5 2fb415772cf1f21cc35f390c9169897a
BLAKE2b-256 0d6d87a6b0c2814953bbfe0039d644fbc890489d7f5d69196ba2a317a4c00f0b

See more details on using hashes here.

File details

Details for the file loggertools-1.0-py3-none-any.whl.

File metadata

  • Download URL: loggertools-1.0-py3-none-any.whl
  • Upload date:
  • Size: 17.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.2

File hashes

Hashes for loggertools-1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 59224dabbc19ba01ca31a129668484cd9075c6bf94898873261c049ee525ada6
MD5 b0819932f498cb7b916656439f20db41
BLAKE2b-256 68208fb3c8b50bc06594fa34483f39598d8bd8674073087f800efcb65292f82f

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page