partition stringclasses 3
values | func_name stringlengths 1 134 | docstring stringlengths 1 46.9k | path stringlengths 4 223 | original_string stringlengths 75 104k | code stringlengths 75 104k | docstring_tokens listlengths 1 1.97k | repo stringlengths 7 55 | language stringclasses 1
value | url stringlengths 87 315 | code_tokens listlengths 19 28.4k | sha stringlengths 40 40 |
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train | poa_components | r'''
Determine in-plane irradiance components.
Combines DNI with sky diffuse and ground-reflected irradiance to calculate
total, direct and diffuse irradiance components in the plane of array.
Parameters
----------
aoi : numeric
Angle of incidence of solar rays with respect to the modu... | pvlib/irradiance.py | def poa_components(aoi, dni, poa_sky_diffuse, poa_ground_diffuse):
r'''
Determine in-plane irradiance components.
Combines DNI with sky diffuse and ground-reflected irradiance to calculate
total, direct and diffuse irradiance components in the plane of array.
Parameters
----------
aoi : nu... | def poa_components(aoi, dni, poa_sky_diffuse, poa_ground_diffuse):
r'''
Determine in-plane irradiance components.
Combines DNI with sky diffuse and ground-reflected irradiance to calculate
total, direct and diffuse irradiance components in the plane of array.
Parameters
----------
aoi : nu... | [
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train | get_ground_diffuse | Estimate diffuse irradiance from ground reflections given
irradiance, albedo, and surface tilt
Function to determine the portion of irradiance on a tilted surface
due to ground reflections. Any of the inputs may be DataFrames or
scalars.
Parameters
----------
surface_tilt : numeric
... | pvlib/irradiance.py | def get_ground_diffuse(surface_tilt, ghi, albedo=.25, surface_type=None):
'''
Estimate diffuse irradiance from ground reflections given
irradiance, albedo, and surface tilt
Function to determine the portion of irradiance on a tilted surface
due to ground reflections. Any of the inputs may be DataFr... | def get_ground_diffuse(surface_tilt, ghi, albedo=.25, surface_type=None):
'''
Estimate diffuse irradiance from ground reflections given
irradiance, albedo, and surface tilt
Function to determine the portion of irradiance on a tilted surface
due to ground reflections. Any of the inputs may be DataFr... | [
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train | klucher | r'''
Determine diffuse irradiance from the sky on a tilted surface
using Klucher's 1979 model
.. math::
I_{d} = DHI \frac{1 + \cos\beta}{2} (1 + F' \sin^3(\beta/2))
(1 + F' \cos^2\theta\sin^3\theta_z)
where
.. math::
F' = 1 - (I_{d0} / GHI)
Klucher's 1979 model determi... | pvlib/irradiance.py | def klucher(surface_tilt, surface_azimuth, dhi, ghi, solar_zenith,
solar_azimuth):
r'''
Determine diffuse irradiance from the sky on a tilted surface
using Klucher's 1979 model
.. math::
I_{d} = DHI \frac{1 + \cos\beta}{2} (1 + F' \sin^3(\beta/2))
(1 + F' \cos^2\theta\sin^3\t... | def klucher(surface_tilt, surface_azimuth, dhi, ghi, solar_zenith,
solar_azimuth):
r'''
Determine diffuse irradiance from the sky on a tilted surface
using Klucher's 1979 model
.. math::
I_{d} = DHI \frac{1 + \cos\beta}{2} (1 + F' \sin^3(\beta/2))
(1 + F' \cos^2\theta\sin^3\t... | [
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train | haydavies | r'''
Determine diffuse irradiance from the sky on a tilted surface using
Hay & Davies' 1980 model
.. math::
I_{d} = DHI ( A R_b + (1 - A) (\frac{1 + \cos\beta}{2}) )
Hay and Davies' 1980 model determines the diffuse irradiance from
the sky (ground reflected irradiance is not included in th... | pvlib/irradiance.py | def haydavies(surface_tilt, surface_azimuth, dhi, dni, dni_extra,
solar_zenith=None, solar_azimuth=None, projection_ratio=None):
r'''
Determine diffuse irradiance from the sky on a tilted surface using
Hay & Davies' 1980 model
.. math::
I_{d} = DHI ( A R_b + (1 - A) (\frac{1 + \co... | def haydavies(surface_tilt, surface_azimuth, dhi, dni, dni_extra,
solar_zenith=None, solar_azimuth=None, projection_ratio=None):
r'''
Determine diffuse irradiance from the sky on a tilted surface using
Hay & Davies' 1980 model
.. math::
I_{d} = DHI ( A R_b + (1 - A) (\frac{1 + \co... | [
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train | reindl | r'''
Determine diffuse irradiance from the sky on a tilted surface using
Reindl's 1990 model
.. math::
I_{d} = DHI (A R_b + (1 - A) (\frac{1 + \cos\beta}{2})
(1 + \sqrt{\frac{I_{hb}}{I_h}} \sin^3(\beta/2)) )
Reindl's 1990 model determines the diffuse irradiance from the sky
(ground ... | pvlib/irradiance.py | def reindl(surface_tilt, surface_azimuth, dhi, dni, ghi, dni_extra,
solar_zenith, solar_azimuth):
r'''
Determine diffuse irradiance from the sky on a tilted surface using
Reindl's 1990 model
.. math::
I_{d} = DHI (A R_b + (1 - A) (\frac{1 + \cos\beta}{2})
(1 + \sqrt{\frac{I_{h... | def reindl(surface_tilt, surface_azimuth, dhi, dni, ghi, dni_extra,
solar_zenith, solar_azimuth):
r'''
Determine diffuse irradiance from the sky on a tilted surface using
Reindl's 1990 model
.. math::
I_{d} = DHI (A R_b + (1 - A) (\frac{1 + \cos\beta}{2})
(1 + \sqrt{\frac{I_{h... | [
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train | king | Determine diffuse irradiance from the sky on a tilted surface using
the King model.
King's model determines the diffuse irradiance from the sky (ground
reflected irradiance is not included in this algorithm) on a tilted
surface using the surface tilt angle, diffuse horizontal irradiance,
global hor... | pvlib/irradiance.py | def king(surface_tilt, dhi, ghi, solar_zenith):
'''
Determine diffuse irradiance from the sky on a tilted surface using
the King model.
King's model determines the diffuse irradiance from the sky (ground
reflected irradiance is not included in this algorithm) on a tilted
surface using the surfa... | def king(surface_tilt, dhi, ghi, solar_zenith):
'''
Determine diffuse irradiance from the sky on a tilted surface using
the King model.
King's model determines the diffuse irradiance from the sky (ground
reflected irradiance is not included in this algorithm) on a tilted
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train | perez | Determine diffuse irradiance from the sky on a tilted surface using
one of the Perez models.
Perez models determine the diffuse irradiance from the sky (ground
reflected irradiance is not included in this algorithm) on a tilted
surface using the surface tilt angle, surface azimuth angle, diffuse
ho... | pvlib/irradiance.py | def perez(surface_tilt, surface_azimuth, dhi, dni, dni_extra,
solar_zenith, solar_azimuth, airmass,
model='allsitescomposite1990', return_components=False):
'''
Determine diffuse irradiance from the sky on a tilted surface using
one of the Perez models.
Perez models determine the di... | def perez(surface_tilt, surface_azimuth, dhi, dni, dni_extra,
solar_zenith, solar_azimuth, airmass,
model='allsitescomposite1990', return_components=False):
'''
Determine diffuse irradiance from the sky on a tilted surface using
one of the Perez models.
Perez models determine the di... | [
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train | clearsky_index | Calculate the clearsky index.
The clearsky index is the ratio of global to clearsky global irradiance.
Negative and non-finite clearsky index values will be truncated to zero.
Parameters
----------
ghi : numeric
Global horizontal irradiance in W/m^2.
clearsky_ghi : numeric
Mod... | pvlib/irradiance.py | def clearsky_index(ghi, clearsky_ghi, max_clearsky_index=2.0):
"""
Calculate the clearsky index.
The clearsky index is the ratio of global to clearsky global irradiance.
Negative and non-finite clearsky index values will be truncated to zero.
Parameters
----------
ghi : numeric
Glo... | def clearsky_index(ghi, clearsky_ghi, max_clearsky_index=2.0):
"""
Calculate the clearsky index.
The clearsky index is the ratio of global to clearsky global irradiance.
Negative and non-finite clearsky index values will be truncated to zero.
Parameters
----------
ghi : numeric
Glo... | [
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train | clearness_index | Calculate the clearness index.
The clearness index is the ratio of global to extraterrestrial
irradiance on a horizontal plane.
Parameters
----------
ghi : numeric
Global horizontal irradiance in W/m^2.
solar_zenith : numeric
True (not refraction-corrected) solar zenith angle ... | pvlib/irradiance.py | def clearness_index(ghi, solar_zenith, extra_radiation, min_cos_zenith=0.065,
max_clearness_index=2.0):
"""
Calculate the clearness index.
The clearness index is the ratio of global to extraterrestrial
irradiance on a horizontal plane.
Parameters
----------
ghi : numeri... | def clearness_index(ghi, solar_zenith, extra_radiation, min_cos_zenith=0.065,
max_clearness_index=2.0):
"""
Calculate the clearness index.
The clearness index is the ratio of global to extraterrestrial
irradiance on a horizontal plane.
Parameters
----------
ghi : numeri... | [
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train | clearness_index_zenith_independent | Calculate the zenith angle independent clearness index.
Parameters
----------
clearness_index : numeric
Ratio of global to extraterrestrial irradiance on a horizontal
plane
airmass : numeric
Airmass
max_clearness_index : numeric, default 2.0
Maximum value of the cl... | pvlib/irradiance.py | def clearness_index_zenith_independent(clearness_index, airmass,
max_clearness_index=2.0):
"""
Calculate the zenith angle independent clearness index.
Parameters
----------
clearness_index : numeric
Ratio of global to extraterrestrial irradiance on a h... | def clearness_index_zenith_independent(clearness_index, airmass,
max_clearness_index=2.0):
"""
Calculate the zenith angle independent clearness index.
Parameters
----------
clearness_index : numeric
Ratio of global to extraterrestrial irradiance on a h... | [
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train | disc | Estimate Direct Normal Irradiance from Global Horizontal Irradiance
using the DISC model.
The DISC algorithm converts global horizontal irradiance to direct
normal irradiance through empirical relationships between the global
and direct clearness indices.
The pvlib implementation limits the clearn... | pvlib/irradiance.py | def disc(ghi, solar_zenith, datetime_or_doy, pressure=101325,
min_cos_zenith=0.065, max_zenith=87, max_airmass=12):
"""
Estimate Direct Normal Irradiance from Global Horizontal Irradiance
using the DISC model.
The DISC algorithm converts global horizontal irradiance to direct
normal irradi... | def disc(ghi, solar_zenith, datetime_or_doy, pressure=101325,
min_cos_zenith=0.065, max_zenith=87, max_airmass=12):
"""
Estimate Direct Normal Irradiance from Global Horizontal Irradiance
using the DISC model.
The DISC algorithm converts global horizontal irradiance to direct
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train | _disc_kn | Calculate Kn for `disc`
Parameters
----------
clearness_index : numeric
airmass : numeric
max_airmass : float
airmass > max_airmass is set to max_airmass before being used
in calculating Kn.
Returns
-------
Kn : numeric
am : numeric
airmass used in the calcu... | pvlib/irradiance.py | def _disc_kn(clearness_index, airmass, max_airmass=12):
"""
Calculate Kn for `disc`
Parameters
----------
clearness_index : numeric
airmass : numeric
max_airmass : float
airmass > max_airmass is set to max_airmass before being used
in calculating Kn.
Returns
-------... | def _disc_kn(clearness_index, airmass, max_airmass=12):
"""
Calculate Kn for `disc`
Parameters
----------
clearness_index : numeric
airmass : numeric
max_airmass : float
airmass > max_airmass is set to max_airmass before being used
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Returns
-------... | [
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train | dirint | Determine DNI from GHI using the DIRINT modification of the DISC
model.
Implements the modified DISC model known as "DIRINT" introduced in
[1]. DIRINT predicts direct normal irradiance (DNI) from measured
global horizontal irradiance (GHI). DIRINT improves upon the DISC
model by using time-series G... | pvlib/irradiance.py | def dirint(ghi, solar_zenith, times, pressure=101325., use_delta_kt_prime=True,
temp_dew=None, min_cos_zenith=0.065, max_zenith=87):
"""
Determine DNI from GHI using the DIRINT modification of the DISC
model.
Implements the modified DISC model known as "DIRINT" introduced in
[1]. DIRINT ... | def dirint(ghi, solar_zenith, times, pressure=101325., use_delta_kt_prime=True,
temp_dew=None, min_cos_zenith=0.065, max_zenith=87):
"""
Determine DNI from GHI using the DIRINT modification of the DISC
model.
Implements the modified DISC model known as "DIRINT" introduced in
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... | 2e844a595b820b43d1170269781fa66bd0ccc8a3 |
train | _dirint_from_dni_ktprime | Calculate DIRINT DNI from supplied DISC DNI and Kt'.
Supports :py:func:`gti_dirint` | pvlib/irradiance.py | def _dirint_from_dni_ktprime(dni, kt_prime, solar_zenith, use_delta_kt_prime,
temp_dew):
"""
Calculate DIRINT DNI from supplied DISC DNI and Kt'.
Supports :py:func:`gti_dirint`
"""
times = dni.index
delta_kt_prime = _delta_kt_prime_dirint(kt_prime, use_delta_kt_prim... | def _dirint_from_dni_ktprime(dni, kt_prime, solar_zenith, use_delta_kt_prime,
temp_dew):
"""
Calculate DIRINT DNI from supplied DISC DNI and Kt'.
Supports :py:func:`gti_dirint`
"""
times = dni.index
delta_kt_prime = _delta_kt_prime_dirint(kt_prime, use_delta_kt_prim... | [
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train | _delta_kt_prime_dirint | Calculate delta_kt_prime (Perez eqn 2 and eqn 3), or return a default value
for use with :py:func:`_dirint_bins`. | pvlib/irradiance.py | def _delta_kt_prime_dirint(kt_prime, use_delta_kt_prime, times):
"""
Calculate delta_kt_prime (Perez eqn 2 and eqn 3), or return a default value
for use with :py:func:`_dirint_bins`.
"""
if use_delta_kt_prime:
# Perez eqn 2
kt_next = kt_prime.shift(-1)
kt_previous = kt_prime.... | def _delta_kt_prime_dirint(kt_prime, use_delta_kt_prime, times):
"""
Calculate delta_kt_prime (Perez eqn 2 and eqn 3), or return a default value
for use with :py:func:`_dirint_bins`.
"""
if use_delta_kt_prime:
# Perez eqn 2
kt_next = kt_prime.shift(-1)
kt_previous = kt_prime.... | [
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train | _temp_dew_dirint | Calculate precipitable water from surface dew point temp (Perez eqn 4),
or return a default value for use with :py:func:`_dirint_bins`. | pvlib/irradiance.py | def _temp_dew_dirint(temp_dew, times):
"""
Calculate precipitable water from surface dew point temp (Perez eqn 4),
or return a default value for use with :py:func:`_dirint_bins`.
"""
if temp_dew is not None:
# Perez eqn 4
w = pd.Series(np.exp(0.07 * temp_dew - 0.075), index=times)
... | def _temp_dew_dirint(temp_dew, times):
"""
Calculate precipitable water from surface dew point temp (Perez eqn 4),
or return a default value for use with :py:func:`_dirint_bins`.
"""
if temp_dew is not None:
# Perez eqn 4
w = pd.Series(np.exp(0.07 * temp_dew - 0.075), index=times)
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train | _dirint_coeffs | Determine the DISC to DIRINT multiplier `dirint_coeffs`.
dni = disc_out['dni'] * dirint_coeffs
Parameters
----------
times : pd.DatetimeIndex
kt_prime : Zenith-independent clearness index
solar_zenith : Solar zenith angle
w : precipitable water estimated from surface dew-point temperature
... | pvlib/irradiance.py | def _dirint_coeffs(times, kt_prime, solar_zenith, w, delta_kt_prime):
"""
Determine the DISC to DIRINT multiplier `dirint_coeffs`.
dni = disc_out['dni'] * dirint_coeffs
Parameters
----------
times : pd.DatetimeIndex
kt_prime : Zenith-independent clearness index
solar_zenith : Solar zen... | def _dirint_coeffs(times, kt_prime, solar_zenith, w, delta_kt_prime):
"""
Determine the DISC to DIRINT multiplier `dirint_coeffs`.
dni = disc_out['dni'] * dirint_coeffs
Parameters
----------
times : pd.DatetimeIndex
kt_prime : Zenith-independent clearness index
solar_zenith : Solar zen... | [
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train | _dirint_bins | Determine the bins for the DIRINT coefficients.
Parameters
----------
times : pd.DatetimeIndex
kt_prime : Zenith-independent clearness index
zenith : Solar zenith angle
w : precipitable water estimated from surface dew-point temperature
delta_kt_prime : stability index
Returns
----... | pvlib/irradiance.py | def _dirint_bins(times, kt_prime, zenith, w, delta_kt_prime):
"""
Determine the bins for the DIRINT coefficients.
Parameters
----------
times : pd.DatetimeIndex
kt_prime : Zenith-independent clearness index
zenith : Solar zenith angle
w : precipitable water estimated from surface dew-po... | def _dirint_bins(times, kt_prime, zenith, w, delta_kt_prime):
"""
Determine the bins for the DIRINT coefficients.
Parameters
----------
times : pd.DatetimeIndex
kt_prime : Zenith-independent clearness index
zenith : Solar zenith angle
w : precipitable water estimated from surface dew-po... | [
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train | dirindex | Determine DNI from GHI using the DIRINDEX model, which is a modification of
the DIRINT model with information from a clear sky model.
DIRINDEX [1] improves upon the DIRINT model by taking into account
turbidity when used with the Ineichen clear sky model results.
The pvlib implementation limits the cl... | pvlib/irradiance.py | def dirindex(ghi, ghi_clearsky, dni_clearsky, zenith, times, pressure=101325.,
use_delta_kt_prime=True, temp_dew=None, min_cos_zenith=0.065,
max_zenith=87):
"""
Determine DNI from GHI using the DIRINDEX model, which is a modification of
the DIRINT model with information from a clea... | def dirindex(ghi, ghi_clearsky, dni_clearsky, zenith, times, pressure=101325.,
use_delta_kt_prime=True, temp_dew=None, min_cos_zenith=0.065,
max_zenith=87):
"""
Determine DNI from GHI using the DIRINDEX model, which is a modification of
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train | gti_dirint | Determine GHI, DNI, DHI from POA global using the GTI DIRINT model.
.. warning::
Model performance is poor for AOI greater than approximately
80 degrees `and` plane of array irradiance greater than
approximately 200 W/m^2.
Parameters
----------
poa_global : array-like
... | pvlib/irradiance.py | def gti_dirint(poa_global, aoi, solar_zenith, solar_azimuth, times,
surface_tilt, surface_azimuth, pressure=101325.,
use_delta_kt_prime=True, temp_dew=None, albedo=.25,
model='perez', model_perez='allsitescomposite1990',
calculate_gt_90=True, max_iterations=30... | def gti_dirint(poa_global, aoi, solar_zenith, solar_azimuth, times,
surface_tilt, surface_azimuth, pressure=101325.,
use_delta_kt_prime=True, temp_dew=None, albedo=.25,
model='perez', model_perez='allsitescomposite1990',
calculate_gt_90=True, max_iterations=30... | [
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train | _gti_dirint_lt_90 | GTI-DIRINT model for AOI < 90 degrees. See Marion 2015 Section 2.1.
See gti_dirint signature for parameter details. | pvlib/irradiance.py | def _gti_dirint_lt_90(poa_global, aoi, aoi_lt_90, solar_zenith, solar_azimuth,
times, surface_tilt, surface_azimuth, pressure=101325.,
use_delta_kt_prime=True, temp_dew=None, albedo=.25,
model='perez', model_perez='allsitescomposite1990',
... | def _gti_dirint_lt_90(poa_global, aoi, aoi_lt_90, solar_zenith, solar_azimuth,
times, surface_tilt, surface_azimuth, pressure=101325.,
use_delta_kt_prime=True, temp_dew=None, albedo=.25,
model='perez', model_perez='allsitescomposite1990',
... | [
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train | _gti_dirint_gte_90 | GTI-DIRINT model for AOI >= 90 degrees. See Marion 2015 Section 2.2.
See gti_dirint signature for parameter details. | pvlib/irradiance.py | def _gti_dirint_gte_90(poa_global, aoi, solar_zenith, solar_azimuth,
surface_tilt, times, kt_prime,
pressure=101325., temp_dew=None, albedo=.25):
"""
GTI-DIRINT model for AOI >= 90 degrees. See Marion 2015 Section 2.2.
See gti_dirint signature for parameter det... | def _gti_dirint_gte_90(poa_global, aoi, solar_zenith, solar_azimuth,
surface_tilt, times, kt_prime,
pressure=101325., temp_dew=None, albedo=.25):
"""
GTI-DIRINT model for AOI >= 90 degrees. See Marion 2015 Section 2.2.
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train | _gti_dirint_gte_90_kt_prime | Determine kt' values to be used in GTI-DIRINT AOI >= 90 deg case.
See Marion 2015 Section 2.2.
For AOI >= 90 deg: average of the kt_prime values for 65 < AOI < 80
in each day's morning and afternoon. Morning and afternoon are treated
separately.
For AOI < 90 deg: NaN.
See gti_dirint signature... | pvlib/irradiance.py | def _gti_dirint_gte_90_kt_prime(aoi, solar_zenith, solar_azimuth, times,
kt_prime):
"""
Determine kt' values to be used in GTI-DIRINT AOI >= 90 deg case.
See Marion 2015 Section 2.2.
For AOI >= 90 deg: average of the kt_prime values for 65 < AOI < 80
in each day's mo... | def _gti_dirint_gte_90_kt_prime(aoi, solar_zenith, solar_azimuth, times,
kt_prime):
"""
Determine kt' values to be used in GTI-DIRINT AOI >= 90 deg case.
See Marion 2015 Section 2.2.
For AOI >= 90 deg: average of the kt_prime values for 65 < AOI < 80
in each day's mo... | [
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train | erbs | r"""
Estimate DNI and DHI from GHI using the Erbs model.
The Erbs model [1]_ estimates the diffuse fraction DF from global
horizontal irradiance through an empirical relationship between DF
and the ratio of GHI to extraterrestrial irradiance, Kt. The
function uses the diffuse fraction to compute DH... | pvlib/irradiance.py | def erbs(ghi, zenith, datetime_or_doy, min_cos_zenith=0.065, max_zenith=87):
r"""
Estimate DNI and DHI from GHI using the Erbs model.
The Erbs model [1]_ estimates the diffuse fraction DF from global
horizontal irradiance through an empirical relationship between DF
and the ratio of GHI to extrater... | def erbs(ghi, zenith, datetime_or_doy, min_cos_zenith=0.065, max_zenith=87):
r"""
Estimate DNI and DHI from GHI using the Erbs model.
The Erbs model [1]_ estimates the diffuse fraction DF from global
horizontal irradiance through an empirical relationship between DF
and the ratio of GHI to extrater... | [
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train | liujordan | Determine DNI, DHI, GHI from extraterrestrial flux, transmittance,
and optical air mass number.
Liu and Jordan, 1960, developed a simplified direct radiation model.
DHI is from an empirical equation for diffuse radiation from Liu and
Jordan, 1960.
Parameters
----------
zenith: pd.Series
... | pvlib/irradiance.py | def liujordan(zenith, transmittance, airmass, dni_extra=1367.0):
'''
Determine DNI, DHI, GHI from extraterrestrial flux, transmittance,
and optical air mass number.
Liu and Jordan, 1960, developed a simplified direct radiation model.
DHI is from an empirical equation for diffuse radiation from Liu ... | def liujordan(zenith, transmittance, airmass, dni_extra=1367.0):
'''
Determine DNI, DHI, GHI from extraterrestrial flux, transmittance,
and optical air mass number.
Liu and Jordan, 1960, developed a simplified direct radiation model.
DHI is from an empirical equation for diffuse radiation from Liu ... | [
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train | _get_perez_coefficients | Find coefficients for the Perez model
Parameters
----------
perezmodel : string (optional, default='allsitescomposite1990')
a character string which selects the desired set of Perez
coefficients. If model is not provided as an input, the default,
'1990' will be used.
Al... | pvlib/irradiance.py | def _get_perez_coefficients(perezmodel):
'''
Find coefficients for the Perez model
Parameters
----------
perezmodel : string (optional, default='allsitescomposite1990')
a character string which selects the desired set of Perez
coefficients. If model is not provided as an input... | def _get_perez_coefficients(perezmodel):
'''
Find coefficients for the Perez model
Parameters
----------
perezmodel : string (optional, default='allsitescomposite1990')
a character string which selects the desired set of Perez
coefficients. If model is not provided as an input... | [
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train | _get_dirint_coeffs | A place to stash the dirint coefficients.
Returns
-------
np.array with shape ``(6, 6, 7, 5)``.
Ordering is ``[kt_prime_bin, zenith_bin, delta_kt_prime_bin, w_bin]`` | pvlib/irradiance.py | def _get_dirint_coeffs():
"""
A place to stash the dirint coefficients.
Returns
-------
np.array with shape ``(6, 6, 7, 5)``.
Ordering is ``[kt_prime_bin, zenith_bin, delta_kt_prime_bin, w_bin]``
"""
# To allow for maximum copy/paste from the MATLAB 1-indexed code,
# we create and ... | def _get_dirint_coeffs():
"""
A place to stash the dirint coefficients.
Returns
-------
np.array with shape ``(6, 6, 7, 5)``.
Ordering is ``[kt_prime_bin, zenith_bin, delta_kt_prime_bin, w_bin]``
"""
# To allow for maximum copy/paste from the MATLAB 1-indexed code,
# we create and ... | [
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train | dni | Determine DNI from GHI and DHI.
When calculating the DNI from GHI and DHI the calculated DNI may be
unreasonably high or negative for zenith angles close to 90 degrees
(sunrise/sunset transitions). This function identifies unreasonable DNI
values and sets them to NaN. If the clearsky DNI is given unrea... | pvlib/irradiance.py | def dni(ghi, dhi, zenith, clearsky_dni=None, clearsky_tolerance=1.1,
zenith_threshold_for_zero_dni=88.0,
zenith_threshold_for_clearsky_limit=80.0):
"""
Determine DNI from GHI and DHI.
When calculating the DNI from GHI and DHI the calculated DNI may be
unreasonably high or negative for z... | def dni(ghi, dhi, zenith, clearsky_dni=None, clearsky_tolerance=1.1,
zenith_threshold_for_zero_dni=88.0,
zenith_threshold_for_clearsky_limit=80.0):
"""
Determine DNI from GHI and DHI.
When calculating the DNI from GHI and DHI the calculated DNI may be
unreasonably high or negative for z... | [
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train | ineichen | Determine clear sky GHI, DNI, and DHI from Ineichen/Perez model.
Implements the Ineichen and Perez clear sky model for global
horizontal irradiance (GHI), direct normal irradiance (DNI), and
calculates the clear-sky diffuse horizontal (DHI) component as the
difference between GHI and DNI*cos(zenith) as... | pvlib/clearsky.py | def ineichen(apparent_zenith, airmass_absolute, linke_turbidity,
altitude=0, dni_extra=1364., perez_enhancement=False):
'''
Determine clear sky GHI, DNI, and DHI from Ineichen/Perez model.
Implements the Ineichen and Perez clear sky model for global
horizontal irradiance (GHI), direct norm... | def ineichen(apparent_zenith, airmass_absolute, linke_turbidity,
altitude=0, dni_extra=1364., perez_enhancement=False):
'''
Determine clear sky GHI, DNI, and DHI from Ineichen/Perez model.
Implements the Ineichen and Perez clear sky model for global
horizontal irradiance (GHI), direct norm... | [
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train | lookup_linke_turbidity | Look up the Linke Turibidity from the ``LinkeTurbidities.h5``
data file supplied with pvlib.
Parameters
----------
time : pandas.DatetimeIndex
latitude : float
longitude : float
filepath : None or string, default None
The path to the ``.h5`` file.
interp_turbidity : bool, de... | pvlib/clearsky.py | def lookup_linke_turbidity(time, latitude, longitude, filepath=None,
interp_turbidity=True):
"""
Look up the Linke Turibidity from the ``LinkeTurbidities.h5``
data file supplied with pvlib.
Parameters
----------
time : pandas.DatetimeIndex
latitude : float
l... | def lookup_linke_turbidity(time, latitude, longitude, filepath=None,
interp_turbidity=True):
"""
Look up the Linke Turibidity from the ``LinkeTurbidities.h5``
data file supplied with pvlib.
Parameters
----------
time : pandas.DatetimeIndex
latitude : float
l... | [
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train | _is_leap_year | Determine if a year is leap year.
Parameters
----------
year : numeric
Returns
-------
isleap : array of bools | pvlib/clearsky.py | def _is_leap_year(year):
"""Determine if a year is leap year.
Parameters
----------
year : numeric
Returns
-------
isleap : array of bools
"""
isleap = ((np.mod(year, 4) == 0) &
((np.mod(year, 100) != 0) | (np.mod(year, 400) == 0)))
return isleap | def _is_leap_year(year):
"""Determine if a year is leap year.
Parameters
----------
year : numeric
Returns
-------
isleap : array of bools
"""
isleap = ((np.mod(year, 4) == 0) &
((np.mod(year, 100) != 0) | (np.mod(year, 400) == 0)))
return isleap | [
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train | _interpolate_turbidity | Interpolated monthly Linke turbidity onto daily values.
Parameters
----------
lts : np.array
Monthly Linke turbidity values.
time : pd.DatetimeIndex
Times to be interpolated onto.
Returns
-------
linke_turbidity : pd.Series
The interpolated turbidity. | pvlib/clearsky.py | def _interpolate_turbidity(lts, time):
"""
Interpolated monthly Linke turbidity onto daily values.
Parameters
----------
lts : np.array
Monthly Linke turbidity values.
time : pd.DatetimeIndex
Times to be interpolated onto.
Returns
-------
linke_turbidity : pd.Series... | def _interpolate_turbidity(lts, time):
"""
Interpolated monthly Linke turbidity onto daily values.
Parameters
----------
lts : np.array
Monthly Linke turbidity values.
time : pd.DatetimeIndex
Times to be interpolated onto.
Returns
-------
linke_turbidity : pd.Series... | [
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train | _calendar_month_middles | List of middle day of each month, used by Linke turbidity lookup | pvlib/clearsky.py | def _calendar_month_middles(year):
"""List of middle day of each month, used by Linke turbidity lookup"""
# remove mdays[0] since January starts at mdays[1]
# make local copy of mdays since we need to change
# February for leap years
mdays = np.array(calendar.mdays[1:])
ydays = 365
# handle ... | def _calendar_month_middles(year):
"""List of middle day of each month, used by Linke turbidity lookup"""
# remove mdays[0] since January starts at mdays[1]
# make local copy of mdays since we need to change
# February for leap years
mdays = np.array(calendar.mdays[1:])
ydays = 365
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train | _linearly_scale | linearly scale input to output, used by Linke turbidity lookup | pvlib/clearsky.py | def _linearly_scale(inputmatrix, inputmin, inputmax, outputmin, outputmax):
"""linearly scale input to output, used by Linke turbidity lookup"""
inputrange = inputmax - inputmin
outputrange = outputmax - outputmin
delta = outputrange/inputrange # number of indices per input unit
inputmin = inputmin... | def _linearly_scale(inputmatrix, inputmin, inputmax, outputmin, outputmax):
"""linearly scale input to output, used by Linke turbidity lookup"""
inputrange = inputmax - inputmin
outputrange = outputmax - outputmin
delta = outputrange/inputrange # number of indices per input unit
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train | haurwitz | Determine clear sky GHI using the Haurwitz model.
Implements the Haurwitz clear sky model for global horizontal
irradiance (GHI) as presented in [1, 2]. A report on clear
sky models found the Haurwitz model to have the best performance
in terms of average monthly error among models which require only
... | pvlib/clearsky.py | def haurwitz(apparent_zenith):
'''
Determine clear sky GHI using the Haurwitz model.
Implements the Haurwitz clear sky model for global horizontal
irradiance (GHI) as presented in [1, 2]. A report on clear
sky models found the Haurwitz model to have the best performance
in terms of average mont... | def haurwitz(apparent_zenith):
'''
Determine clear sky GHI using the Haurwitz model.
Implements the Haurwitz clear sky model for global horizontal
irradiance (GHI) as presented in [1, 2]. A report on clear
sky models found the Haurwitz model to have the best performance
in terms of average mont... | [
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train | simplified_solis | Calculate the clear sky GHI, DNI, and DHI according to the
simplified Solis model [1]_.
Reference [1]_ describes the accuracy of the model as being 15, 20,
and 18 W/m^2 for the beam, global, and diffuse components. Reference
[2]_ provides comparisons with other clear sky models.
Parameters
---... | pvlib/clearsky.py | def simplified_solis(apparent_elevation, aod700=0.1, precipitable_water=1.,
pressure=101325., dni_extra=1364.):
"""
Calculate the clear sky GHI, DNI, and DHI according to the
simplified Solis model [1]_.
Reference [1]_ describes the accuracy of the model as being 15, 20,
and 18... | def simplified_solis(apparent_elevation, aod700=0.1, precipitable_water=1.,
pressure=101325., dni_extra=1364.):
"""
Calculate the clear sky GHI, DNI, and DHI according to the
simplified Solis model [1]_.
Reference [1]_ describes the accuracy of the model as being 15, 20,
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train | _calc_i0p | Calculate the "enhanced extraterrestrial irradiance". | pvlib/clearsky.py | def _calc_i0p(i0, w, aod700, p):
"""Calculate the "enhanced extraterrestrial irradiance"."""
p0 = 101325.
io0 = 1.08 * w**0.0051
i01 = 0.97 * w**0.032
i02 = 0.12 * w**0.56
i0p = i0 * (i02*aod700**2 + i01*aod700 + io0 + 0.071*np.log(p/p0))
return i0p | def _calc_i0p(i0, w, aod700, p):
"""Calculate the "enhanced extraterrestrial irradiance"."""
p0 = 101325.
io0 = 1.08 * w**0.0051
i01 = 0.97 * w**0.032
i02 = 0.12 * w**0.56
i0p = i0 * (i02*aod700**2 + i01*aod700 + io0 + 0.071*np.log(p/p0))
return i0p | [
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train | _calc_taub | Calculate the taub coefficient | pvlib/clearsky.py | def _calc_taub(w, aod700, p):
"""Calculate the taub coefficient"""
p0 = 101325.
tb1 = 1.82 + 0.056*np.log(w) + 0.0071*np.log(w)**2
tb0 = 0.33 + 0.045*np.log(w) + 0.0096*np.log(w)**2
tbp = 0.0089*w + 0.13
taub = tb1*aod700 + tb0 + tbp*np.log(p/p0)
return taub | def _calc_taub(w, aod700, p):
"""Calculate the taub coefficient"""
p0 = 101325.
tb1 = 1.82 + 0.056*np.log(w) + 0.0071*np.log(w)**2
tb0 = 0.33 + 0.045*np.log(w) + 0.0096*np.log(w)**2
tbp = 0.0089*w + 0.13
taub = tb1*aod700 + tb0 + tbp*np.log(p/p0)
return taub | [
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train | _calc_b | Calculate the b coefficient. | pvlib/clearsky.py | def _calc_b(w, aod700):
"""Calculate the b coefficient."""
b1 = 0.00925*aod700**2 + 0.0148*aod700 - 0.0172
b0 = -0.7565*aod700**2 + 0.5057*aod700 + 0.4557
b = b1 * np.log(w) + b0
return b | def _calc_b(w, aod700):
"""Calculate the b coefficient."""
b1 = 0.00925*aod700**2 + 0.0148*aod700 - 0.0172
b0 = -0.7565*aod700**2 + 0.5057*aod700 + 0.4557
b = b1 * np.log(w) + b0
return b | [
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train | _calc_taug | Calculate the taug coefficient | pvlib/clearsky.py | def _calc_taug(w, aod700, p):
"""Calculate the taug coefficient"""
p0 = 101325.
tg1 = 1.24 + 0.047*np.log(w) + 0.0061*np.log(w)**2
tg0 = 0.27 + 0.043*np.log(w) + 0.0090*np.log(w)**2
tgp = 0.0079*w + 0.1
taug = tg1*aod700 + tg0 + tgp*np.log(p/p0)
return taug | def _calc_taug(w, aod700, p):
"""Calculate the taug coefficient"""
p0 = 101325.
tg1 = 1.24 + 0.047*np.log(w) + 0.0061*np.log(w)**2
tg0 = 0.27 + 0.043*np.log(w) + 0.0090*np.log(w)**2
tgp = 0.0079*w + 0.1
taug = tg1*aod700 + tg0 + tgp*np.log(p/p0)
return taug | [
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train | _calc_g | Calculate the g coefficient. | pvlib/clearsky.py | def _calc_g(w, aod700):
"""Calculate the g coefficient."""
g = -0.0147*np.log(w) - 0.3079*aod700**2 + 0.2846*aod700 + 0.3798
return g | def _calc_g(w, aod700):
"""Calculate the g coefficient."""
g = -0.0147*np.log(w) - 0.3079*aod700**2 + 0.2846*aod700 + 0.3798
return g | [
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train | _calc_taud | Calculate the taud coefficient. | pvlib/clearsky.py | def _calc_taud(w, aod700, p):
"""Calculate the taud coefficient."""
# isscalar tests needed to ensure that the arrays will have the
# right shape in the tds calculation.
# there's probably a better way to do this.
if np.isscalar(w) and np.isscalar(aod700):
w = np.array([w])
aod700 ... | def _calc_taud(w, aod700, p):
"""Calculate the taud coefficient."""
# isscalar tests needed to ensure that the arrays will have the
# right shape in the tds calculation.
# there's probably a better way to do this.
if np.isscalar(w) and np.isscalar(aod700):
w = np.array([w])
aod700 ... | [
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train | _calc_d | Calculate the d coefficient. | pvlib/clearsky.py | def _calc_d(aod700, p):
"""Calculate the d coefficient."""
p0 = 101325.
dp = 1/(18 + 152*aod700)
d = -0.337*aod700**2 + 0.63*aod700 + 0.116 + dp*np.log(p/p0)
return d | def _calc_d(aod700, p):
"""Calculate the d coefficient."""
p0 = 101325.
dp = 1/(18 + 152*aod700)
d = -0.337*aod700**2 + 0.63*aod700 + 0.116 + dp*np.log(p/p0)
return d | [
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train | detect_clearsky | Detects clear sky times according to the algorithm developed by Reno
and Hansen for GHI measurements [1]. The algorithm was designed and
validated for analyzing GHI time series only. Users may attempt to
apply it to other types of time series data using different filter
settings, but should be skeptical... | pvlib/clearsky.py | def detect_clearsky(measured, clearsky, times, window_length,
mean_diff=75, max_diff=75,
lower_line_length=-5, upper_line_length=10,
var_diff=0.005, slope_dev=8, max_iterations=20,
return_components=False):
"""
Detects clear sky tim... | def detect_clearsky(measured, clearsky, times, window_length,
mean_diff=75, max_diff=75,
lower_line_length=-5, upper_line_length=10,
var_diff=0.005, slope_dev=8, max_iterations=20,
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train | bird | Bird Simple Clear Sky Broadband Solar Radiation Model
Based on NREL Excel implementation by Daryl R. Myers [1, 2].
Bird and Hulstrom define the zenith as the "angle between a line to
the sun and the local zenith". There is no distinction in the paper
between solar zenith and apparent (or refracted) ze... | pvlib/clearsky.py | def bird(zenith, airmass_relative, aod380, aod500, precipitable_water,
ozone=0.3, pressure=101325., dni_extra=1364., asymmetry=0.85,
albedo=0.2):
"""
Bird Simple Clear Sky Broadband Solar Radiation Model
Based on NREL Excel implementation by Daryl R. Myers [1, 2].
Bird and Hulstrom d... | def bird(zenith, airmass_relative, aod380, aod500, precipitable_water,
ozone=0.3, pressure=101325., dni_extra=1364., asymmetry=0.85,
albedo=0.2):
"""
Bird Simple Clear Sky Broadband Solar Radiation Model
Based on NREL Excel implementation by Daryl R. Myers [1, 2].
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train | read_surfrad | Read in a daily NOAA SURFRAD[1] file.
Parameters
----------
filename: str
Filepath or url.
map_variables: bool
When true, renames columns of the Dataframe to pvlib variable names
where applicable. See variable SURFRAD_COLUMNS.
Returns
-------
Tuple of the form (data... | pvlib/iotools/surfrad.py | def read_surfrad(filename, map_variables=True):
"""Read in a daily NOAA SURFRAD[1] file.
Parameters
----------
filename: str
Filepath or url.
map_variables: bool
When true, renames columns of the Dataframe to pvlib variable names
where applicable. See variable SURFRAD_COLUMN... | def read_surfrad(filename, map_variables=True):
"""Read in a daily NOAA SURFRAD[1] file.
Parameters
----------
filename: str
Filepath or url.
map_variables: bool
When true, renames columns of the Dataframe to pvlib variable names
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train | format_index | Create UTC localized DatetimeIndex for the dataframe.
Parameters
----------
data: Dataframe
Must contain columns 'year', 'jday', 'hour' and
'minute'.
Return
------
data: Dataframe
Dataframe with a DatetimeIndex localized to UTC. | pvlib/iotools/surfrad.py | def format_index(data):
"""Create UTC localized DatetimeIndex for the dataframe.
Parameters
----------
data: Dataframe
Must contain columns 'year', 'jday', 'hour' and
'minute'.
Return
------
data: Dataframe
Dataframe with a DatetimeIndex localized to UTC.
"""
... | def format_index(data):
"""Create UTC localized DatetimeIndex for the dataframe.
Parameters
----------
data: Dataframe
Must contain columns 'year', 'jday', 'hour' and
'minute'.
Return
------
data: Dataframe
Dataframe with a DatetimeIndex localized to UTC.
"""
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train | warn_deprecated | Used to display deprecation in a standard way.
Parameters
----------
since : str
The release at which this API became deprecated.
message : str, optional
Override the default deprecation message. The format
specifier `%(name)s` may be used for the name of the function,
a... | pvlib/_deprecation.py | def warn_deprecated(
since, message='', name='', alternative='', pending=False,
obj_type='attribute', addendum='', removal=''):
"""
Used to display deprecation in a standard way.
Parameters
----------
since : str
The release at which this API became deprecated.
message : ... | def warn_deprecated(
since, message='', name='', alternative='', pending=False,
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"""
Used to display deprecation in a standard way.
Parameters
----------
since : str
The release at which this API became deprecated.
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train | deprecated | Decorator to mark a function or a class as deprecated.
Parameters
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since : str
The release at which this API became deprecated. This is
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message : str, optional
Override the default deprecation message. The format
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addendum='', removal=''):
"""
Decorator to mark a function or a class as deprecated.
Parameters
----------
since : str
The release at which this API became deprecated. This is
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"""
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The release at which this API became deprecated. This is
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train | map_midc_to_pvlib | A mapper function to rename Dataframe columns to their pvlib counterparts.
Parameters
----------
variable_map: Dictionary
A dictionary for mapping MIDC field name to pvlib name. See
VARIABLE_MAP for default value and description of how to construct
this argument.
field_name: str... | pvlib/iotools/midc.py | def map_midc_to_pvlib(variable_map, field_name):
"""A mapper function to rename Dataframe columns to their pvlib counterparts.
Parameters
----------
variable_map: Dictionary
A dictionary for mapping MIDC field name to pvlib name. See
VARIABLE_MAP for default value and description of how... | def map_midc_to_pvlib(variable_map, field_name):
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----------
variable_map: Dictionary
A dictionary for mapping MIDC field name to pvlib name. See
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train | format_index | Create DatetimeIndex for the Dataframe localized to the timezone provided
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Parameters
----------
data: Dataframe
Must contain 'DATE (MM/DD/YYYY)' column, second column must be labeled
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Re... | pvlib/iotools/midc.py | def format_index(data):
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Parameters
----------
data: Dataframe
Must contain 'DATE (MM/DD/YYYY)' column, second column must be labeled
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train | format_index_raw | Create DatetimeIndex for the Dataframe localized to the timezone provided
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Parameters
----------
data: Dataframe
Must contain columns 'Year' and 'DOY'. Timezone must be found as the
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data: Dat... | pvlib/iotools/midc.py | def format_index_raw(data):
"""Create DatetimeIndex for the Dataframe localized to the timezone provided
as the label of the third column.
Parameters
----------
data: Dataframe
Must contain columns 'Year' and 'DOY'. Timezone must be found as the
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data: Dataframe
Must contain columns 'Year' and 'DOY'. Timezone must be found as the
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train | read_midc | Read in National Renewable Energy Laboratory Measurement and
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Parameters
----------
filename: string
Filename or url of data to read.
variable_map: dictionary
Dictionary for mapping MIDC field names to pvlib names. See variable
`... | pvlib/iotools/midc.py | def read_midc(filename, variable_map=VARIABLE_MAP, raw_data=False):
"""Read in National Renewable Energy Laboratory Measurement and
Instrumentation Data Center [1]_ weather data.
Parameters
----------
filename: string
Filename or url of data to read.
variable_map: dictionary
Dic... | def read_midc(filename, variable_map=VARIABLE_MAP, raw_data=False):
"""Read in National Renewable Energy Laboratory Measurement and
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Parameters
----------
filename: string
Filename or url of data to read.
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train | read_midc_raw_data_from_nrel | Request and read MIDC data directly from the raw data api.
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----------
site: string
The MIDC station id.
start: datetime
Start date for requested data.
end: datetime
End date for requested data.
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-------
data:
Dataframe with DatetimeInde... | pvlib/iotools/midc.py | def read_midc_raw_data_from_nrel(site, start, end):
"""Request and read MIDC data directly from the raw data api.
Parameters
----------
site: string
The MIDC station id.
start: datetime
Start date for requested data.
end: datetime
End date for requested data.
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site: string
The MIDC station id.
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Start date for requested data.
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train | gueymard94_pw | r"""
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Calculates precipitable water (cm) from ambient air temperature (C)
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Calculates precipitable water (cm) from ambient air temperature (C)
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Estimates a spectral mismatch modifier M representing the effect on
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r"""
Spectral mismatch modifier based on precipitable water and absolute
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Estimates a spectral mismatch modifier M representing the effect on
... | def first_solar_spectral_correction(pw, airmass_absolute, module_type=None,
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Spectral mismatch modifier based on precipitable water and absolute
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train | kasten96_lt | Calculate Linke turbidity factor using Kasten pyrheliometric formula.
Note that broadband aerosol optical depth (AOD) can be approximated by AOD
measured at 700 nm according to Molineaux [4] . Bird and Hulstrom offer an
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train | angstrom_alpha | r"""
Calculate Angstrom alpha exponent.
Parameters
----------
aod1 : numeric
first aerosol optical depth
lambda1 : numeric
wavelength in nanometers corresponding to ``aod1``
aod2 : numeric
second aerosol optical depth
lambda2 : numeric
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r"""
Calculate Angstrom alpha exponent.
Parameters
----------
aod1 : numeric
first aerosol optical depth
lambda1 : numeric
wavelength in nanometers corresponding to ``aod1``
aod2 : numeric
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r"""
Calculate Angstrom alpha exponent.
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----------
aod1 : numeric
first aerosol optical depth
lambda1 : numeric
wavelength in nanometers corresponding to ``aod1``
aod2 : numeric
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train | localize_to_utc | Converts or localizes a time series to UTC.
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time : datetime.datetime, pandas.DatetimeIndex,
or pandas.Series/DataFrame with a DatetimeIndex.
location : pvlib.Location object
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-------
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Converts or localizes a time series to UTC.
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----------
time : datetime.datetime, pandas.DatetimeIndex,
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location : pvlib.Location object
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-------
pandas object loca... | def localize_to_utc(time, location):
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Converts or localizes a time series to UTC.
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----------
time : datetime.datetime, pandas.DatetimeIndex,
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location : pvlib.Location object
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train | datetime_to_djd | Converts a datetime to the Dublin Julian Day
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time : datetime.datetime
time to convert
Returns
-------
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time : datetime.datetime
time to convert
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time : datetime.datetime
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fractional days since 12/31/1899+0000
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train | djd_to_datetime | Converts a Dublin Julian Day float to a datetime.datetime object
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djd : float
fractional days since 12/31/1899+0000
tz : str, default 'UTC'
timezone to localize the result to
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Converts a Dublin Julian Day float to a datetime.datetime object
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----------
djd : float
fractional days since 12/31/1899+0000
tz : str, default 'UTC'
timezone to localize the result to
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-------
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djd : float
fractional days since 12/31/1899+0000
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timezone to localize the result to
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train | _doy_to_datetimeindex | Convert a day of year scalar or array to a pd.DatetimeIndex.
Parameters
----------
doy : numeric
Contains days of the year
Returns
-------
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Parameters
----------
doy : numeric
Contains days of the year
Returns
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pd.DatetimeIndex
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doy : numeric
Contains days of the year
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pd.DatetimeIndex
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train | _build_kwargs | Parameters
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keys : iterable
Typically a list of strings.
adict : dict-like
A dictionary from which to attempt to pull each key.
Returns
-------
kwargs : dict
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A vectorized version of Newton, Halley, and secant methods for arrays. Do
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train | _golden_sect_DataFrame | Vectorized golden section search for finding MPP from a dataframe
timeseries.
Parameters
----------
params : dict
Dictionary containing scalars or arrays
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Each row should represent an independent optimization.
VL: float
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"""
Vectorized golden section search for finding MPP from a dataframe
timeseries.
Parameters
----------
params : dict
Dictionary containing scalars or arrays
of inputs to the function to be optimized.
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Vectorized golden section search for finding MPP from a dataframe
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params : dict
Dictionary containing scalars or arrays
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train | singleaxis | Determine the rotation angle of a single axis tracker using the
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angle. backtracking may be specified, and if so, a ground coverage
ratio is required.
Rotation angle is determined in a panel-oriented coordinate system.
The tracker azimu... | pvlib/tracking.py | def singleaxis(apparent_zenith, apparent_azimuth,
axis_tilt=0, axis_azimuth=0, max_angle=90,
backtrack=True, gcr=2.0/7.0):
"""
Determine the rotation angle of a single axis tracker using the
equations in [1] when given a particular sun zenith and azimuth
angle. backtracking... | def singleaxis(apparent_zenith, apparent_azimuth,
axis_tilt=0, axis_azimuth=0, max_angle=90,
backtrack=True, gcr=2.0/7.0):
"""
Determine the rotation angle of a single axis tracker using the
equations in [1] when given a particular sun zenith and azimuth
angle. backtracking... | [
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train | SingleAxisTracker.singleaxis | Get tracking data. See :py:func:`pvlib.tracking.singleaxis` more
detail.
Parameters
----------
apparent_zenith : float, 1d array, or Series
Solar apparent zenith angles in decimal degrees.
apparent_azimuth : float, 1d array, or Series
Solar apparent azim... | pvlib/tracking.py | def singleaxis(self, apparent_zenith, apparent_azimuth):
"""
Get tracking data. See :py:func:`pvlib.tracking.singleaxis` more
detail.
Parameters
----------
apparent_zenith : float, 1d array, or Series
Solar apparent zenith angles in decimal degrees.
... | def singleaxis(self, apparent_zenith, apparent_azimuth):
"""
Get tracking data. See :py:func:`pvlib.tracking.singleaxis` more
detail.
Parameters
----------
apparent_zenith : float, 1d array, or Series
Solar apparent zenith angles in decimal degrees.
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train | SingleAxisTracker.get_irradiance | Uses the :func:`irradiance.get_total_irradiance` function to
calculate the plane of array irradiance components on a tilted
surface defined by the input data and ``self.albedo``.
For a given set of solar zenith and azimuth angles, the
surface tilt and azimuth parameters are typically de... | pvlib/tracking.py | def get_irradiance(self, surface_tilt, surface_azimuth,
solar_zenith, solar_azimuth, dni, ghi, dhi,
dni_extra=None, airmass=None, model='haydavies',
**kwargs):
"""
Uses the :func:`irradiance.get_total_irradiance` function to
ca... | def get_irradiance(self, surface_tilt, surface_azimuth,
solar_zenith, solar_azimuth, dni, ghi, dhi,
dni_extra=None, airmass=None, model='haydavies',
**kwargs):
"""
Uses the :func:`irradiance.get_total_irradiance` function to
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train | read_srml | Read University of Oregon SRML[1] 1min .tsv file into pandas dataframe.
Parameters
----------
filename: str
filepath or url to read for the tsv file.
Returns
-------
data: Dataframe
A dataframe with datetime index and all of the variables listed
in the `VARIABLE_MAP` di... | pvlib/iotools/srml.py | def read_srml(filename):
"""
Read University of Oregon SRML[1] 1min .tsv file into pandas dataframe.
Parameters
----------
filename: str
filepath or url to read for the tsv file.
Returns
-------
data: Dataframe
A dataframe with datetime index and all of the variables li... | def read_srml(filename):
"""
Read University of Oregon SRML[1] 1min .tsv file into pandas dataframe.
Parameters
----------
filename: str
filepath or url to read for the tsv file.
Returns
-------
data: Dataframe
A dataframe with datetime index and all of the variables li... | [
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train | map_columns | Map data element numbers to pvlib names.
Parameters
----------
col: str
Column label to be mapped.
Returns
-------
str
The pvlib label if it was found in the mapping,
else the original label. | pvlib/iotools/srml.py | def map_columns(col):
"""Map data element numbers to pvlib names.
Parameters
----------
col: str
Column label to be mapped.
Returns
-------
str
The pvlib label if it was found in the mapping,
else the original label.
"""
if col.startswith('7'):
# spe... | def map_columns(col):
"""Map data element numbers to pvlib names.
Parameters
----------
col: str
Column label to be mapped.
Returns
-------
str
The pvlib label if it was found in the mapping,
else the original label.
"""
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train | format_index | Create a datetime index from day of year, and time columns.
Parameters
----------
df: pd.Dataframe
The srml data to reindex.
Returns
-------
df: pd.Dataframe
The Dataframe with a DatetimeIndex localized to 'Etc/GMT+8'. | pvlib/iotools/srml.py | def format_index(df):
"""Create a datetime index from day of year, and time columns.
Parameters
----------
df: pd.Dataframe
The srml data to reindex.
Returns
-------
df: pd.Dataframe
The Dataframe with a DatetimeIndex localized to 'Etc/GMT+8'.
"""
# Name of the seco... | def format_index(df):
"""Create a datetime index from day of year, and time columns.
Parameters
----------
df: pd.Dataframe
The srml data to reindex.
Returns
-------
df: pd.Dataframe
The Dataframe with a DatetimeIndex localized to 'Etc/GMT+8'.
"""
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train | read_srml_month_from_solardat | Request a month of SRML[1] data from solardat and read it into
a Dataframe.
Parameters
----------
station: str
The name of the SRML station to request.
year: int
Year to request data for
month: int
Month to request data for.
filetype: string
SRML file type to... | pvlib/iotools/srml.py | def read_srml_month_from_solardat(station, year, month, filetype='PO'):
"""Request a month of SRML[1] data from solardat and read it into
a Dataframe.
Parameters
----------
station: str
The name of the SRML station to request.
year: int
Year to request data for
month: int
... | def read_srml_month_from_solardat(station, year, month, filetype='PO'):
"""Request a month of SRML[1] data from solardat and read it into
a Dataframe.
Parameters
----------
station: str
The name of the SRML station to request.
year: int
Year to request data for
month: int
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train | get_ecmwf_macc | Download data from ECMWF MACC Reanalysis API.
Parameters
----------
filename : str
full path of file where to save data, ``.nc`` appended if not given
params : str or sequence of str
keynames of parameter[s] to download
startdate : datetime.datetime or datetime.date
UTC date... | pvlib/iotools/ecmwf_macc.py | def get_ecmwf_macc(filename, params, startdate, stopdate, lookup_params=True,
server=None, target=_ecmwf):
"""
Download data from ECMWF MACC Reanalysis API.
Parameters
----------
filename : str
full path of file where to save data, ``.nc`` appended if not given
params... | def get_ecmwf_macc(filename, params, startdate, stopdate, lookup_params=True,
server=None, target=_ecmwf):
"""
Download data from ECMWF MACC Reanalysis API.
Parameters
----------
filename : str
full path of file where to save data, ``.nc`` appended if not given
params... | [
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train | read_ecmwf_macc | Read data from ECMWF MACC reanalysis netCDF4 file.
Parameters
----------
filename : string
full path to netCDF4 data file.
latitude : float
latitude in degrees
longitude : float
longitude in degrees
utc_time_range : sequence of datetime.datetime
pair of start and... | pvlib/iotools/ecmwf_macc.py | def read_ecmwf_macc(filename, latitude, longitude, utc_time_range=None):
"""
Read data from ECMWF MACC reanalysis netCDF4 file.
Parameters
----------
filename : string
full path to netCDF4 data file.
latitude : float
latitude in degrees
longitude : float
longitude in... | def read_ecmwf_macc(filename, latitude, longitude, utc_time_range=None):
"""
Read data from ECMWF MACC reanalysis netCDF4 file.
Parameters
----------
filename : string
full path to netCDF4 data file.
latitude : float
latitude in degrees
longitude : float
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train | ECMWF_MACC.get_nearest_indices | Get nearest indices to (latitude, longitude).
Parmaeters
----------
latitude : float
Latitude in degrees
longitude : float
Longitude in degrees
Returns
-------
idx_lat : int
index of nearest latitude
idx_lon : int
... | pvlib/iotools/ecmwf_macc.py | def get_nearest_indices(self, latitude, longitude):
"""
Get nearest indices to (latitude, longitude).
Parmaeters
----------
latitude : float
Latitude in degrees
longitude : float
Longitude in degrees
Returns
-------
idx_la... | def get_nearest_indices(self, latitude, longitude):
"""
Get nearest indices to (latitude, longitude).
Parmaeters
----------
latitude : float
Latitude in degrees
longitude : float
Longitude in degrees
Returns
-------
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train | ECMWF_MACC.interp_data | Interpolate ``param`` values to ``utc_time`` using indices nearest to
(``latitude, longitude``).
Parmaeters
----------
latitude : float
Latitude in degrees
longitude : float
Longitude in degrees
utc_time : datetime.datetime or datetime.date
... | pvlib/iotools/ecmwf_macc.py | def interp_data(self, latitude, longitude, utc_time, param):
"""
Interpolate ``param`` values to ``utc_time`` using indices nearest to
(``latitude, longitude``).
Parmaeters
----------
latitude : float
Latitude in degrees
longitude : float
... | def interp_data(self, latitude, longitude, utc_time, param):
"""
Interpolate ``param`` values to ``utc_time`` using indices nearest to
(``latitude, longitude``).
Parmaeters
----------
latitude : float
Latitude in degrees
longitude : float
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train | read_solrad | Read NOAA SOLRAD [1]_ [2]_ fixed-width file into pandas dataframe.
Parameters
----------
filename: str
filepath or url to read for the fixed-width file.
Returns
-------
data: Dataframe
A dataframe with DatetimeIndex and all of the variables in the
file.
Notes
-... | pvlib/iotools/solrad.py | def read_solrad(filename):
"""
Read NOAA SOLRAD [1]_ [2]_ fixed-width file into pandas dataframe.
Parameters
----------
filename: str
filepath or url to read for the fixed-width file.
Returns
-------
data: Dataframe
A dataframe with DatetimeIndex and all of the variable... | def read_solrad(filename):
"""
Read NOAA SOLRAD [1]_ [2]_ fixed-width file into pandas dataframe.
Parameters
----------
filename: str
filepath or url to read for the fixed-width file.
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-------
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train | read_crn | Read NOAA USCRN [1]_ [2]_ fixed-width file into pandas dataframe.
Parameters
----------
filename: str
filepath or url to read for the fixed-width file.
Returns
-------
data: Dataframe
A dataframe with DatetimeIndex and all of the variables in the
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Notes
--... | pvlib/iotools/crn.py | def read_crn(filename):
"""
Read NOAA USCRN [1]_ [2]_ fixed-width file into pandas dataframe.
Parameters
----------
filename: str
filepath or url to read for the fixed-width file.
Returns
-------
data: Dataframe
A dataframe with DatetimeIndex and all of the variables in... | def read_crn(filename):
"""
Read NOAA USCRN [1]_ [2]_ fixed-width file into pandas dataframe.
Parameters
----------
filename: str
filepath or url to read for the fixed-width file.
Returns
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train | read_epw | Read an EPW file in to a pandas dataframe.
Note that values contained in the metadata dictionary are unchanged
from the EPW file.
EPW files are commonly used by building simulation professionals
and are widely available on the web. For example via:
https://energyplus.net/weather , http://climate.o... | pvlib/iotools/epw.py | def read_epw(filename, coerce_year=None):
'''
Read an EPW file in to a pandas dataframe.
Note that values contained in the metadata dictionary are unchanged
from the EPW file.
EPW files are commonly used by building simulation professionals
and are widely available on the web. For example via:... | def read_epw(filename, coerce_year=None):
'''
Read an EPW file in to a pandas dataframe.
Note that values contained in the metadata dictionary are unchanged
from the EPW file.
EPW files are commonly used by building simulation professionals
and are widely available on the web. For example via:... | [
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train | Location.from_tmy | Create an object based on a metadata
dictionary from tmy2 or tmy3 data readers.
Parameters
----------
tmy_metadata : dict
Returned from tmy.readtmy2 or tmy.readtmy3
tmy_data : None or DataFrame, default None
Optionally attach the TMY data to this object.
... | pvlib/location.py | def from_tmy(cls, tmy_metadata, tmy_data=None, **kwargs):
"""
Create an object based on a metadata
dictionary from tmy2 or tmy3 data readers.
Parameters
----------
tmy_metadata : dict
Returned from tmy.readtmy2 or tmy.readtmy3
tmy_data : None or DataF... | def from_tmy(cls, tmy_metadata, tmy_data=None, **kwargs):
"""
Create an object based on a metadata
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Parameters
----------
tmy_metadata : dict
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train | Location.get_solarposition | Uses the :py:func:`solarposition.get_solarposition` function
to calculate the solar zenith, azimuth, etc. at this location.
Parameters
----------
times : DatetimeIndex
pressure : None, float, or array-like, default None
If None, pressure will be calculated using
... | pvlib/location.py | def get_solarposition(self, times, pressure=None, temperature=12,
**kwargs):
"""
Uses the :py:func:`solarposition.get_solarposition` function
to calculate the solar zenith, azimuth, etc. at this location.
Parameters
----------
times : DatetimeIn... | def get_solarposition(self, times, pressure=None, temperature=12,
**kwargs):
"""
Uses the :py:func:`solarposition.get_solarposition` function
to calculate the solar zenith, azimuth, etc. at this location.
Parameters
----------
times : DatetimeIn... | [
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train | Location.get_clearsky | Calculate the clear sky estimates of GHI, DNI, and/or DHI
at this location.
Parameters
----------
times: DatetimeIndex
model: str, default 'ineichen'
The clear sky model to use. Must be one of
'ineichen', 'haurwitz', 'simplified_solis'.
solar_posi... | pvlib/location.py | def get_clearsky(self, times, model='ineichen', solar_position=None,
dni_extra=None, **kwargs):
"""
Calculate the clear sky estimates of GHI, DNI, and/or DHI
at this location.
Parameters
----------
times: DatetimeIndex
model: str, default 'in... | def get_clearsky(self, times, model='ineichen', solar_position=None,
dni_extra=None, **kwargs):
"""
Calculate the clear sky estimates of GHI, DNI, and/or DHI
at this location.
Parameters
----------
times: DatetimeIndex
model: str, default 'in... | [
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train | Location.get_airmass | Calculate the relative and absolute airmass.
Automatically chooses zenith or apparant zenith
depending on the selected model.
Parameters
----------
times : None or DatetimeIndex, default None
Only used if solar_position is not provided.
solar_position : None... | pvlib/location.py | def get_airmass(self, times=None, solar_position=None,
model='kastenyoung1989'):
"""
Calculate the relative and absolute airmass.
Automatically chooses zenith or apparant zenith
depending on the selected model.
Parameters
----------
times : N... | def get_airmass(self, times=None, solar_position=None,
model='kastenyoung1989'):
"""
Calculate the relative and absolute airmass.
Automatically chooses zenith or apparant zenith
depending on the selected model.
Parameters
----------
times : N... | [
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train | Location.get_sun_rise_set_transit | Calculate sunrise, sunset and transit times.
Parameters
----------
times : DatetimeIndex
Must be localized to the Location
method : str, default 'pyephem'
'pyephem', 'spa', or 'geometric'
kwargs are passed to the relevant functions. See
solarposi... | pvlib/location.py | def get_sun_rise_set_transit(self, times, method='pyephem', **kwargs):
"""
Calculate sunrise, sunset and transit times.
Parameters
----------
times : DatetimeIndex
Must be localized to the Location
method : str, default 'pyephem'
'pyephem', 'spa',... | def get_sun_rise_set_transit(self, times, method='pyephem', **kwargs):
"""
Calculate sunrise, sunset and transit times.
Parameters
----------
times : DatetimeIndex
Must be localized to the Location
method : str, default 'pyephem'
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train | julian_day_dt | This is the original way to calculate the julian day from the NREL paper.
However, it is much faster to convert to unix/epoch time and then convert
to julian day. Note that the date must be UTC. | pvlib/spa.py | def julian_day_dt(year, month, day, hour, minute, second, microsecond):
"""This is the original way to calculate the julian day from the NREL paper.
However, it is much faster to convert to unix/epoch time and then convert
to julian day. Note that the date must be UTC."""
if month <= 2:
year = y... | def julian_day_dt(year, month, day, hour, minute, second, microsecond):
"""This is the original way to calculate the julian day from the NREL paper.
However, it is much faster to convert to unix/epoch time and then convert
to julian day. Note that the date must be UTC."""
if month <= 2:
year = y... | [
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train | solar_position_loop | Loop through the time array and calculate the solar position | pvlib/spa.py | def solar_position_loop(unixtime, loc_args, out):
"""Loop through the time array and calculate the solar position"""
lat = loc_args[0]
lon = loc_args[1]
elev = loc_args[2]
pressure = loc_args[3]
temp = loc_args[4]
delta_t = loc_args[5]
atmos_refract = loc_args[6]
sst = loc_args[7]
... | def solar_position_loop(unixtime, loc_args, out):
"""Loop through the time array and calculate the solar position"""
lat = loc_args[0]
lon = loc_args[1]
elev = loc_args[2]
pressure = loc_args[3]
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delta_t = loc_args[5]
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train | solar_position_numba | Calculate the solar position using the numba compiled functions
and multiple threads. Very slow if functions are not numba compiled. | pvlib/spa.py | def solar_position_numba(unixtime, lat, lon, elev, pressure, temp, delta_t,
atmos_refract, numthreads, sst=False, esd=False):
"""Calculate the solar position using the numba compiled functions
and multiple threads. Very slow if functions are not numba compiled.
"""
# these args ... | def solar_position_numba(unixtime, lat, lon, elev, pressure, temp, delta_t,
atmos_refract, numthreads, sst=False, esd=False):
"""Calculate the solar position using the numba compiled functions
and multiple threads. Very slow if functions are not numba compiled.
"""
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train | earthsun_distance | Calculates the distance from the earth to the sun using the
NREL SPA algorithm described in [1].
Parameters
----------
unixtime : numpy array
Array of unix/epoch timestamps to calculate solar position for.
Unixtime is the number of seconds since Jan. 1, 1970 00:00:00 UTC.
A pand... | pvlib/spa.py | def earthsun_distance(unixtime, delta_t, numthreads):
"""
Calculates the distance from the earth to the sun using the
NREL SPA algorithm described in [1].
Parameters
----------
unixtime : numpy array
Array of unix/epoch timestamps to calculate solar position for.
Unixtime is the... | def earthsun_distance(unixtime, delta_t, numthreads):
"""
Calculates the distance from the earth to the sun using the
NREL SPA algorithm described in [1].
Parameters
----------
unixtime : numpy array
Array of unix/epoch timestamps to calculate solar position for.
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train | calculate_deltat | Calculate the difference between Terrestrial Dynamical Time (TD)
and Universal Time (UT).
Note: This function is not yet compatible for calculations using
Numba.
Equations taken from http://eclipse.gsfc.nasa.gov/SEcat5/deltatpoly.html | pvlib/spa.py | def calculate_deltat(year, month):
"""Calculate the difference between Terrestrial Dynamical Time (TD)
and Universal Time (UT).
Note: This function is not yet compatible for calculations using
Numba.
Equations taken from http://eclipse.gsfc.nasa.gov/SEcat5/deltatpoly.html
"""
plw = 'Delta... | def calculate_deltat(year, month):
"""Calculate the difference between Terrestrial Dynamical Time (TD)
and Universal Time (UT).
Note: This function is not yet compatible for calculations using
Numba.
Equations taken from http://eclipse.gsfc.nasa.gov/SEcat5/deltatpoly.html
"""
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train | pvfactors_timeseries | Calculate front and back surface plane-of-array irradiance on
a fixed tilt or single-axis tracker PV array configuration, and using
the open-source "pvfactors" package.
Please refer to pvfactors online documentation for more details:
https://sunpower.github.io/pvfactors/
Parameters
----------
... | pvlib/bifacial.py | def pvfactors_timeseries(
solar_azimuth, solar_zenith, surface_azimuth, surface_tilt,
timestamps, dni, dhi, gcr, pvrow_height, pvrow_width, albedo,
n_pvrows=3, index_observed_pvrow=1,
rho_front_pvrow=0.03, rho_back_pvrow=0.05,
horizon_band_angle=15.,
run_parallel_calculat... | def pvfactors_timeseries(
solar_azimuth, solar_zenith, surface_azimuth, surface_tilt,
timestamps, dni, dhi, gcr, pvrow_height, pvrow_width, albedo,
n_pvrows=3, index_observed_pvrow=1,
rho_front_pvrow=0.03, rho_back_pvrow=0.05,
horizon_band_angle=15.,
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train | main | File based sample for the Google Assistant API.
Examples:
$ python -m audiofileinput -i <input file> -o <output file> | google-assistant-sdk/googlesamples/assistant/grpc/audiofileinput.py | def main(api_endpoint, credentials,
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block_size, grpc_deadline, *args, **kwargs):
"""File based sample for the Google Assistant API.
Examples:
$ python -m audiofileinput -i <input file> -o <output fi... | def main(api_endpoint, credentials,
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input_audio_file, output_audio_file,
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"""File based sample for the Google Assistant API.
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train | process_event | Pretty prints events.
Prints all events that occur with two spaces between each new
conversation and a single space between turns of a conversation.
Args:
event(event.Event): The current event to process. | google-assistant-sdk/googlesamples/assistant/library/hotword.py | def process_event(event):
"""Pretty prints events.
Prints all events that occur with two spaces between each new
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Args:
event(event.Event): The current event to process.
"""
if event.type == EventType.ON_CONVERSATION_TURN_... | def process_event(event):
"""Pretty prints events.
Prints all events that occur with two spaces between each new
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Args:
event(event.Event): The current event to process.
"""
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] | googlesamples/assistant-sdk-python | python | https://github.com/googlesamples/assistant-sdk-python/blob/84995692f35be8e085de8dfa7032039a13ae3fab/google-assistant-sdk/googlesamples/assistant/library/hotword.py#L49-L68 | [
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train | failed_request_exception | Build ClickException from a failed request. | google-assistant-sdk/googlesamples/assistant/grpc/devicetool.py | def failed_request_exception(message, r):
"""Build ClickException from a failed request."""
try:
resp = json.loads(r.text)
message = '%s: %d\n%s' % (message, resp['error']['code'],
resp['error']['message'])
return click.ClickException(message)
except... | def failed_request_exception(message, r):
"""Build ClickException from a failed request."""
try:
resp = json.loads(r.text)
message = '%s: %d\n%s' % (message, resp['error']['code'],
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train | pretty_print_model | Prints out a device model in the terminal by parsing dict. | google-assistant-sdk/googlesamples/assistant/grpc/devicetool.py | def pretty_print_model(devicemodel):
"""Prints out a device model in the terminal by parsing dict."""
PRETTY_PRINT_MODEL = """Device Model ID: %(deviceModelId)s
Project ID: %(projectId)s
Device Type: %(deviceType)s"""
logging.info(PRETTY_PRINT_MODEL % devicemodel)
if 'traits' in devicemo... | def pretty_print_model(devicemodel):
"""Prints out a device model in the terminal by parsing dict."""
PRETTY_PRINT_MODEL = """Device Model ID: %(deviceModelId)s
Project ID: %(projectId)s
Device Type: %(deviceType)s"""
logging.info(PRETTY_PRINT_MODEL % devicemodel)
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train | pretty_print_device | Prints out a device instance in the terminal by parsing dict. | google-assistant-sdk/googlesamples/assistant/grpc/devicetool.py | def pretty_print_device(device):
"""Prints out a device instance in the terminal by parsing dict."""
logging.info('Device Instance ID: %s' % device['id'])
if 'nickname' in device:
logging.info(' Nickname: %s' % device['nickname'])
if 'modelId' in device:
logging.info(' Model: %s' %... | def pretty_print_device(device):
"""Prints out a device instance in the terminal by parsing dict."""
logging.info('Device Instance ID: %s' % device['id'])
if 'nickname' in device:
logging.info(' Nickname: %s' % device['nickname'])
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train | register | Registers a device model and instance.
Device model fields can only contain letters, numbers, and the following
symbols: period (.), hyphen (-), underscore (_), space ( ) and plus (+).
The first character of a field must be a letter or number.
Device instance fields must start with a letter or number.... | google-assistant-sdk/googlesamples/assistant/grpc/devicetool.py | def register(ctx, model, type, trait, manufacturer, product_name, description,
device, nickname, client_type):
"""Registers a device model and instance.
Device model fields can only contain letters, numbers, and the following
symbols: period (.), hyphen (-), underscore (_), space ( ) and plus ... | def register(ctx, model, type, trait, manufacturer, product_name, description,
device, nickname, client_type):
"""Registers a device model and instance.
Device model fields can only contain letters, numbers, and the following
symbols: period (.), hyphen (-), underscore (_), space ( ) and plus ... | [
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train | register_model | Registers a device model.
Device model fields can only contain letters, numbers, and the following
symbols: period (.), hyphen (-), underscore (_), space ( ) and plus (+).
The first character of a field must be a letter or number. | google-assistant-sdk/googlesamples/assistant/grpc/devicetool.py | def register_model(ctx, model, type, trait,
manufacturer, product_name, description):
"""Registers a device model.
Device model fields can only contain letters, numbers, and the following
symbols: period (.), hyphen (-), underscore (_), space ( ) and plus (+).
The first character of ... | def register_model(ctx, model, type, trait,
manufacturer, product_name, description):
"""Registers a device model.
Device model fields can only contain letters, numbers, and the following
symbols: period (.), hyphen (-), underscore (_), space ( ) and plus (+).
The first character of ... | [
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] | googlesamples/assistant-sdk-python | python | https://github.com/googlesamples/assistant-sdk-python/blob/84995692f35be8e085de8dfa7032039a13ae3fab/google-assistant-sdk/googlesamples/assistant/grpc/devicetool.py#L222-L260 | [
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train | register_device | Registers a device instance under an existing device model.
Device instance fields must start with a letter or number. The device ID
can only contain letters, numbers, and the following symbols: period (.),
hyphen (-), underscore (_), and plus (+). The device nickname can only
contain numbers, letters,... | google-assistant-sdk/googlesamples/assistant/grpc/devicetool.py | def register_device(ctx, device, model, nickname, client_type):
"""Registers a device instance under an existing device model.
Device instance fields must start with a letter or number. The device ID
can only contain letters, numbers, and the following symbols: period (.),
hyphen (-), underscore (_), a... | def register_device(ctx, device, model, nickname, client_type):
"""Registers a device instance under an existing device model.
Device instance fields must start with a letter or number. The device ID
can only contain letters, numbers, and the following symbols: period (.),
hyphen (-), underscore (_), a... | [
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train | get | Gets all of the information (fields) for a given device model or
instance. | google-assistant-sdk/googlesamples/assistant/grpc/devicetool.py | def get(ctx, resource, id):
"""Gets all of the information (fields) for a given device model or
instance.
"""
session, api_url, project_id = build_client_from_context(ctx)
url = '/'.join([api_url, resource, id])
r = session.get(url)
if r.status_code != 200:
raise failed_request_excep... | def get(ctx, resource, id):
"""Gets all of the information (fields) for a given device model or
instance.
"""
session, api_url, project_id = build_client_from_context(ctx)
url = '/'.join([api_url, resource, id])
r = session.get(url)
if r.status_code != 200:
raise failed_request_excep... | [
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] | googlesamples/assistant-sdk-python | python | https://github.com/googlesamples/assistant-sdk-python/blob/84995692f35be8e085de8dfa7032039a13ae3fab/google-assistant-sdk/googlesamples/assistant/grpc/devicetool.py#L327-L342 | [
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