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fix docstrings

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This commit is contained in:
Benoît Sierro
2023-07-27 12:12:10 +02:00
parent bb03a1896f
commit a8f0379c38
15 changed files with 332 additions and 218 deletions
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9
src/scgenerator/evaluator.py
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@@ -57,7 +57,8 @@ class Rule:
args_const: list[str] = None, args_const: list[str] = None,
priorities: Union[int, list[int]] = None, priorities: Union[int, list[int]] = None,
) -> list["Rule"]: ) -> list["Rule"]:
"""given a function that doesn't need all its keyword arguemtn specified, will """
given a function that doesn't need all its keyword arguemtn specified, will
return a list of Rule obj, one for each combination of n_var specified kwargs return a list of Rule obj, one for each combination of n_var specified kwargs
Parameters Parameters
@@ -145,7 +146,8 @@ class Evaluator:
self.rules[t].sort(key=lambda el: el.targets[t], reverse=True) self.rules[t].sort(key=lambda el: el.targets[t], reverse=True)
def set(self, dico: dict[str, Any] = None, **params: Any): def set(self, dico: dict[str, Any] = None, **params: Any):
"""sets the internal set of parameters """
sets the internal set of parameters
Parameters Parameters
---------- ----------
@@ -169,7 +171,8 @@ class Evaluator:
self.eval_stats = defaultdict(EvalStat) self.eval_stats = defaultdict(EvalStat)
def compute(self, target: str, check_only=False) -> Any: def compute(self, target: str, check_only=False) -> Any:
"""computes a target """
computes a target
Parameters Parameters
---------- ----------

9
src/scgenerator/helpers.py
View File

@@ -30,7 +30,8 @@ def w_from_wl(wl_min_nm: float, wl_max_nm: float, n: int) -> np.ndarray:
def capillary_dispersion( def capillary_dispersion(
wl: np.ndarray, radius: float, gas_name: str, pressure=None, temperature=None wl: np.ndarray, radius: float, gas_name: str, pressure=None, temperature=None
) -> np.ndarray: ) -> np.ndarray:
"""computes the dispersion (beta2) of a capillary tube """
computes the dispersion (beta2) of a capillary tube
Parameters Parameters
---------- ----------
@@ -67,7 +68,8 @@ def capillary_zdw(
temperature=None, temperature=None,
search_range: tuple[float, float] = (200e-9, 3000e-9), search_range: tuple[float, float] = (200e-9, 3000e-9),
) -> np.ndarray: ) -> np.ndarray:
"""find the zero dispersion wavelength of a capilally """
find the zero dispersion wavelength of a capilally
Parameters Parameters
---------- ----------
@@ -104,7 +106,8 @@ def revolver_dispersion(
pressure=None, pressure=None,
temperature=None, temperature=None,
) -> np.ndarray: ) -> np.ndarray:
"""computes the dispersion (beta2) of a capillary tube """
computes the dispersion (beta2) of a capillary tube
Parameters Parameters
---------- ----------

1
src/scgenerator/io.py
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@@ -6,6 +6,7 @@ import pkg_resources
def data_file(path: str) -> Path: def data_file(path: str) -> Path:
"""returns a `Path` object pointing to the desired data file included in `scgenerator`"""
return Path(pkg_resources.resource_filename("scgenerator", path)) return Path(pkg_resources.resource_filename("scgenerator", path))

7
src/scgenerator/logger.py
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@@ -2,7 +2,6 @@ import logging
from scgenerator.env import log_file_level, log_print_level from scgenerator.env import log_file_level, log_print_level
lvl_map: dict[str, int] = dict( lvl_map: dict[str, int] = dict(
debug=logging.DEBUG, debug=logging.DEBUG,
info=logging.INFO, info=logging.INFO,
@@ -13,7 +12,8 @@ lvl_map: dict[str, int] = dict(
def get_logger(name=None): def get_logger(name=None):
"""returns a logging.Logger instance. This function is there because if scgenerator """
returns a logging.Logger instance. This function is there because if scgenerator
is used with some multiprocessing library, workers are not aware of any configuration done is used with some multiprocessing library, workers are not aware of any configuration done
with the logging and so it must be reconfigured. with the logging and so it must be reconfigured.
@@ -33,7 +33,8 @@ def get_logger(name=None):
def configure_logger(logger: logging.Logger): def configure_logger(logger: logging.Logger):
"""configures a logging.Logger obj """
configures a logging.Logger obj
Parameters Parameters
---------- ----------

34
src/scgenerator/math.py
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@@ -114,11 +114,14 @@ def sigmoid(x):
def u_nm(n, m): def u_nm(n, m):
"""returns the mth zero of the Bessel function of order n-1 """
returns the mth zero of the Bessel function of order n-1
Parameters Parameters
---------- ----------
n-1 : order of the Bessel function n-1 : order of the Bessel function
m : order of the zero m : order of the zero
Returns Returns
---------- ----------
float float
@@ -139,16 +142,16 @@ def wspace(t, t_num=0):
Parameters Parameters
---------- ----------
t : float or array t : float or array
float : total width of the time window float : total width of the time window
array : time array array : time array
t_num : int- t_num : int-
if t is a float, specifies the number of points if t is a float, specifies the number of points
Returns Returns
------- -------
w : array w : array
linspace of frencies corresponding to t linspace of frencies corresponding to t
""" """
if isinstance(t, (np.ndarray, list, tuple)): if isinstance(t, (np.ndarray, list, tuple)):
dt = t[1] - t[0] dt = t[1] - t[0]
@@ -258,7 +261,7 @@ def build_z_grid(z_num: int, length: float) -> np.ndarray:
def build_t_grid( def build_t_grid(
time_window: float = None, t_num: int = None, dt: float = None time_window: float = None, t_num: int = None, dt: float = None
) -> tuple[np.ndarray, float, float, int]: ) -> tuple[np.ndarray, float, float, int]:
"""[summary] """
Returns Returns
------- -------
@@ -308,7 +311,8 @@ def polynom_extrapolation(x: np.ndarray, y: np.ndarray, degree: int) -> np.ndarr
def _polynom_extrapolation_in_place(y: np.ndarray, left_ind: int, right_ind: int, degree: float): def _polynom_extrapolation_in_place(y: np.ndarray, left_ind: int, right_ind: int, degree: float):
"""extrapolates IN PLACE linearily on both side of the support """
extrapolates IN PLACE linearily on both side of the support
Parameters Parameters
---------- ----------
@@ -415,7 +419,8 @@ def envelope_ind(
def envelope_2d(x: np.ndarray, values: np.ndarray) -> np.ndarray: def envelope_2d(x: np.ndarray, values: np.ndarray) -> np.ndarray:
"""returns the envelope of a 2d propagation-like array """
returns the envelope of a 2d propagation-like array
Parameters Parameters
---------- ----------
@@ -472,7 +477,8 @@ class LobeProps:
def measure_lobe(x_in, y_in, /, lobe_pos: int = None, thr_rel: float = 1 / 50) -> LobeProps: def measure_lobe(x_in, y_in, /, lobe_pos: int = None, thr_rel: float = 1 / 50) -> LobeProps:
"""given a fairly smooth signal, finds the highest lobe and returns its position as well """
given a fairly smooth signal, finds the highest lobe and returns its position as well
as its fwhm points as its fwhm points
Parameters Parameters

6
src/scgenerator/parameter.py
View File

@@ -213,7 +213,8 @@ class Parameter:
default=None, default=None,
display_info: tuple[float, str] = None, display_info: tuple[float, str] = None,
): ):
"""Single parameter """
Single parameter
Parameters Parameters
---------- ----------
@@ -567,7 +568,8 @@ class Parameters:
return "\n".join("{:>{l}} = {:{r}}".format(*p, l=max_left, r=max_right) for p in p_pairs) return "\n".join("{:>{l}} = {:{r}}".format(*p, l=max_left, r=max_right) for p in p_pairs)
def strip_params_dict(self) -> dict[str, Any]: def strip_params_dict(self) -> dict[str, Any]:
"""prepares a dictionary for serialization. Some keys may not be preserved """
prepares a dictionary for serialization. Some keys may not be preserved
(dropped because they take a lot of space and can be exactly reconstructed) (dropped because they take a lot of space and can be exactly reconstructed)
Parameters Parameters

9
src/scgenerator/physics/__init__.py
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@@ -26,7 +26,8 @@ def material_dispersion(
pressure=None, pressure=None,
temperature=None, temperature=None,
): ):
"""returns the dispersion profile (beta_2) of a bulk material. """
returns the dispersion profile (beta_2) of a bulk material.
Parameters Parameters
---------- ----------
@@ -59,7 +60,8 @@ def material_dispersion(
def find_optimal_depth( def find_optimal_depth(
spectrum: T, w_c: np.ndarray, w0: float, material: str, max_z: float = 1.0 spectrum: T, w_c: np.ndarray, w0: float, material: str, max_z: float = 1.0
) -> tuple[T, pulse.OptimizeResult]: ) -> tuple[T, pulse.OptimizeResult]:
"""finds the optimal silica depth to compress a pulse """
finds the optimal silica depth to compress a pulse
Parameters Parameters
---------- ----------
@@ -100,7 +102,8 @@ def find_optimal_depth(
def propagate_field( def propagate_field(
t: np.ndarray, field: np.ndarray, z: float, material: str, center_wl_nm: float t: np.ndarray, field: np.ndarray, z: float, material: str, center_wl_nm: float
) -> np.ndarray: ) -> np.ndarray:
"""propagates a field through bulk material """
propagates a field through bulk material
Parameters Parameters
---------- ----------

60
src/scgenerator/physics/fiber.py
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@@ -19,7 +19,8 @@ T = TypeVar("T")
def lambda_for_envelope_dispersion( def lambda_for_envelope_dispersion(
l: np.ndarray, wavelength_window: tuple[float, float] l: np.ndarray, wavelength_window: tuple[float, float]
) -> tuple[np.ndarray, np.ndarray]: ) -> tuple[np.ndarray, np.ndarray]:
"""Returns a wl vector for dispersion calculation in envelope mode """
Returns a wl vector for dispersion calculation in envelope mode
Returns Returns
------- -------
@@ -50,7 +51,8 @@ def lambda_for_envelope_dispersion(
def lambda_for_full_field_dispersion( def lambda_for_full_field_dispersion(
l: np.ndarray, wavelength_window: tuple[float, float] l: np.ndarray, wavelength_window: tuple[float, float]
) -> tuple[np.ndarray, np.ndarray]: ) -> tuple[np.ndarray, np.ndarray]:
"""Returns a wl vector for dispersion calculation in full field mode """
Returns a wl vector for dispersion calculation in full field mode
Returns Returns
------- -------
@@ -95,7 +97,8 @@ def is_dynamic_dispersion(pressure=None):
def gvd_from_n_eff(n_eff: np.ndarray, wl_for_disp: np.ndarray): def gvd_from_n_eff(n_eff: np.ndarray, wl_for_disp: np.ndarray):
"""computes the dispersion parameter D from an effective index of refraction n_eff """
computes the dispersion parameter D from an effective index of refraction n_eff
Since computing gradients/derivatives of discrete arrays is not well defined on the boundary, Since computing gradients/derivatives of discrete arrays is not well defined on the boundary,
it is advised to chop off the two values on either end of the returned array it is advised to chop off the two values on either end of the returned array
@@ -126,7 +129,8 @@ def D_to_beta2(D, wl_for_disp):
def plasma_dispersion(wl_for_disp, number_density, simple=False): def plasma_dispersion(wl_for_disp, number_density, simple=False):
"""computes dispersion (beta2) for constant plasma """
computes dispersion (beta2) for constant plasma
Parameters Parameters
---------- ----------
@@ -151,7 +155,8 @@ def plasma_dispersion(wl_for_disp, number_density, simple=False):
def n_eff_marcatili(wl_for_disp, n_gas_2, core_radius, he_mode=(1, 1)): def n_eff_marcatili(wl_for_disp, n_gas_2, core_radius, he_mode=(1, 1)):
"""computes the effective refractive index according to the Marcatili model of a capillary """
computes the effective refractive index according to the Marcatili model of a capillary
Parameters Parameters
---------- ----------
@@ -212,7 +217,8 @@ def n_eff_marcatili_adjusted(wl_for_disp, n_gas_2, core_radius, he_mode=(1, 1),
def effective_area_marcatili(core_radius: float) -> float: def effective_area_marcatili(core_radius: float) -> float:
"""Effective mode-field area for fundamental mode hollow capillaries """
Effective mode-field area for fundamental mode hollow capillaries
Parameters Parameters
---------- ----------
@@ -238,7 +244,8 @@ def capillary_spacing_hasan(
def resonance_thickness( def resonance_thickness(
wl_for_disp: np.ndarray, order: int, n_gas_2: np.ndarray, core_radius: float wl_for_disp: np.ndarray, order: int, n_gas_2: np.ndarray, core_radius: float
) -> float: ) -> float:
"""computes at which wall thickness the specified wl is resonant """
computes at which wall thickness the specified wl is resonant
Parameters Parameters
---------- ----------
@@ -361,7 +368,8 @@ def n_eff_hasan(
def effective_area_hasan(core_radius, capillary_num, capillary_spacing): def effective_area_hasan(core_radius, capillary_num, capillary_spacing):
"""computed the effective mode area """
computed the effective mode area
Parameters Parameters
---------- ----------
@@ -413,7 +421,8 @@ def V_eff_step_index(
def V_parameter_koshiba(l: np.ndarray, pcf_pitch: float, pcf_pitch_ratio: float) -> float: def V_parameter_koshiba(l: np.ndarray, pcf_pitch: float, pcf_pitch_ratio: float) -> float:
"""returns the V parameter according to Koshiba2004 """
returns the V parameter according to Koshiba2004
Parameters Parameters
@@ -447,7 +456,8 @@ def V_parameter_koshiba(l: np.ndarray, pcf_pitch: float, pcf_pitch_ratio: float)
def effective_area_from_V(core_radius: float, V_eff: T) -> T: def effective_area_from_V(core_radius: float, V_eff: T) -> T:
"""According to Marcuse1978 """
According to Marcuse1978
Parameters Parameters
---------- ----------
@@ -508,7 +518,8 @@ def HCPCF_dispersion(
temperature=None, temperature=None,
**model_params, **model_params,
): ):
"""returns the dispersion profile (beta_2) of a hollow-core photonic crystal fiber. """
returns the dispersion profile (beta_2) of a hollow-core photonic crystal fiber.
Parameters Parameters
---------- ----------
@@ -643,7 +654,8 @@ def saitoh_paramters(pcf_pitch_ratio: float) -> tuple[float, float]:
def load_custom_effective_area(effective_area_file: str, l: np.ndarray) -> np.ndarray: def load_custom_effective_area(effective_area_file: str, l: np.ndarray) -> np.ndarray:
"""loads custom effective area file """
loads custom effective area file
Parameters Parameters
---------- ----------
@@ -673,7 +685,8 @@ def load_custom_dispersion(dispersion_file: str) -> tuple[np.ndarray, np.ndarray
def load_custom_loss(l: np.ndarray, loss_file: str) -> np.ndarray: def load_custom_loss(l: np.ndarray, loss_file: str) -> np.ndarray:
"""loads a npz loss file that contains a wavelength and a loss entry """
loads a npz loss file that contains a wavelength and a loss entry
Parameters Parameters
---------- ----------
@@ -699,7 +712,8 @@ def dispersion_coefficients(
w0: float, w0: float,
interpolation_degree: int, interpolation_degree: int,
): ):
"""Computes the taylor expansion of beta2 to be used in dispersion_op """
Computes the taylor expansion of beta2 to be used in dispersion_op
Parameters Parameters
---------- ----------
@@ -735,7 +749,8 @@ def dispersion_coefficients(
def dispersion_from_coefficients( def dispersion_from_coefficients(
w_c: np.ndarray, beta2_coefficients: Iterable[float] w_c: np.ndarray, beta2_coefficients: Iterable[float]
) -> np.ndarray: ) -> np.ndarray:
"""computes the dispersion profile (beta2) from the beta coefficients """
computes the dispersion profile (beta2) from the beta coefficients
Parameters Parameters
---------- ----------
@@ -810,8 +825,10 @@ def delayed_raman_t(t: np.ndarray, raman_type: str) -> np.ndarray:
def delayed_raman_w(t: np.ndarray, raman_type: str) -> tuple[np.ndarray, float]: def delayed_raman_w(t: np.ndarray, raman_type: str) -> tuple[np.ndarray, float]:
"""returns the delayed raman response function as function of w """
see delayed_raman_t for detailes as well as the raman fraction""" returns the delayed raman response function as function of w
see delayed_raman_t for detailes as well as the raman fraction
"""
hr_w = fft(delayed_raman_t(t, raman_type)) * (t[1] - t[0]) hr_w = fft(delayed_raman_t(t, raman_type)) * (t[1] - t[0])
return hr_w, raman_fraction(raman_type) return hr_w, raman_fraction(raman_type)
@@ -851,7 +868,8 @@ def _fast_disp_loop(dispersion: np.ndarray, beta_arr, power_fact_arr):
def direct_dispersion(w: np.ndarray, w0: float, n_eff: np.ndarray) -> np.ndarray: def direct_dispersion(w: np.ndarray, w0: float, n_eff: np.ndarray) -> np.ndarray:
"""returns the dispersive operator in direct form (without polynomial interpolation) """
returns the dispersive operator in direct form (without polynomial interpolation)
i.e. -1j * (beta(w) - beta1 * (w - w0) - beta0) i.e. -1j * (beta(w) - beta1 * (w - w0) - beta0)
Parameters Parameters
@@ -879,7 +897,8 @@ def fast_direct_dispersion(w: np.ndarray, w0: float, n_eff: np.ndarray, w0_ind:
def effective_core_radius(wl_for_disp, core_radius, s=0.08, h=200e-9): def effective_core_radius(wl_for_disp, core_radius, s=0.08, h=200e-9):
"""return the variable core radius according to Eq. S2.2 from Köttig2017 """
return the variable core radius according to Eq. S2.2 from Köttig2017
Parameters Parameters
---------- ----------
@@ -910,7 +929,8 @@ def scalar_loss(alpha: float, w_num: int) -> np.ndarray:
def capillary_loss(wl: np.ndarray, he_mode: tuple[int, int], core_radius: float) -> np.ndarray: def capillary_loss(wl: np.ndarray, he_mode: tuple[int, int], core_radius: float) -> np.ndarray:
"""computes the wavelenth dependent capillary loss according to Marcatili """
computes the wavelenth dependent capillary loss according to Marcatili
Parameters Parameters
---------- ----------

26
src/scgenerator/physics/materials.py
View File

@@ -142,7 +142,8 @@ class Gas:
return self.sellmeier.temperature_ref / temperature * density * self.sellmeier.pressure_ref return self.sellmeier.temperature_ref / temperature * density * self.sellmeier.pressure_ref
def density_factor(self, temperature: float, pressure: float, ideal_gas: bool) -> float: def density_factor(self, temperature: float, pressure: float, ideal_gas: bool) -> float:
"""returns the number density relative to reference values """
returns the number density relative to reference values
Parameters Parameters
---------- ----------
@@ -176,7 +177,8 @@ class Gas:
def number_density( def number_density(
self, temperature: float = None, pressure: float = None, ideal_gas: bool = False self, temperature: float = None, pressure: float = None, ideal_gas: bool = False
) -> float: ) -> float:
"""returns the number density in 1/m^3 using van der Waals equation """
returns the number density in 1/m^3 using van der Waals equation
Parameters Parameters
---------- ----------
@@ -198,7 +200,8 @@ class Gas:
return self.number_density_van_der_waals(pressure, temperature) return self.number_density_van_der_waals(pressure, temperature)
def number_density_van_der_waals(self, pressure: float = None, temperature: float = None): def number_density_van_der_waals(self, pressure: float = None, temperature: float = None):
"""returns the number density of a gas """
returns the number density of a gas
Parameters Parameters
---------- ----------
@@ -324,28 +327,34 @@ def n_gas_2(wl_for_disp: np.ndarray, gas_name: str, pressure: float, temperature
def pressure_from_gradient(ratio: float, p0: float, p1: float) -> float: def pressure_from_gradient(ratio: float, p0: float, p1: float) -> float:
"""returns the pressure as function of distance with eq. 20 in Markos et al. (2017) """
returns the pressure as function of distance with eq. 20 in Markos et al. (2017)
Parameters Parameters
---------- ----------
ratio : relative position in the fiber (0 = start, 1 = end) ratio : relative position in the fiber (0 = start, 1 = end)
p0 : pressure at the start p0 : pressure at the start
p1 : pressure at the end p1 : pressure at the end
Returns Returns
---------- -------
the pressure (float) the pressure (float)
""" """
return np.sqrt(p0**2 - ratio * (p0**2 - p1**2)) return np.sqrt(p0**2 - ratio * (p0**2 - p1**2))
def delta_gas(w: np.ndarray, gas: Gas) -> np.ndarray: def delta_gas(w: np.ndarray, gas: Gas) -> np.ndarray:
"""returns the value delta_t (eq. 24 in Markos(2017)) """
returns the value delta_t (eq. 24 in Markos(2017))
Parameters Parameters
---------- ----------
w : np.ndarray w : np.ndarray
angular frequency array angular frequency array
gas : Gas gas : Gas
Returns Returns
---------- -------
delta_t delta_t
since 2 gradients are computed, it is recommended to exclude the 2 extremum values since 2 gradients are computed, it is recommended to exclude the 2 extremum values
""" """
@@ -377,7 +386,8 @@ def gas_n2(gas_name: str, pressure: float, temperature: float) -> float:
def gas_chi3(gas_name: str, wavelength: float, pressure: float, temperature: float) -> float: def gas_chi3(gas_name: str, wavelength: float, pressure: float, temperature: float) -> float:
"""returns the chi3 of a particular material """
returns the chi3 of a particular material
Parameters Parameters
---------- ----------

3
src/scgenerator/physics/plasma.py
View File

@@ -85,7 +85,8 @@ class Plasma:
self.rate = create_ion_rate_func(self.ionization_energy) self.rate = create_ion_rate_func(self.ionization_energy)
def __call__(self, field: np.ndarray, N0: float) -> PlasmaInfo: def __call__(self, field: np.ndarray, N0: float) -> PlasmaInfo:
"""returns the number density of free electrons as function of time """
returns the number density of free electrons as function of time
Parameters Parameters
---------- ----------

283
src/scgenerator/physics/pulse.py
View File

@@ -106,7 +106,8 @@ def initial_full_field(
w0: float, w0: float,
n0: float, n0: float,
) -> np.ndarray: ) -> np.ndarray:
"""initial field in full field simulations """
initial field in full field simulations
Parameters Parameters
---------- ----------
@@ -136,7 +137,8 @@ def initial_full_field(
def initial_field_envelope(t: np.ndarray, shape: str, t0: float, peak_power: float) -> np.ndarray: def initial_field_envelope(t: np.ndarray, shape: str, t0: float, peak_power: float) -> np.ndarray:
"""returns the initial field """
returns the initial field
Parameters Parameters
---------- ----------
@@ -176,7 +178,8 @@ def modify_field_ratio(
intensity_noise: float = None, intensity_noise: float = None,
noise_correlation: float = 0, noise_correlation: float = 0,
) -> float: ) -> float:
"""multiply a field by this number to get the desired specifications """
multiply a field by this number to get the desired specifications
Parameters Parameters
---------- ----------
@@ -204,7 +207,8 @@ def modify_field_ratio(
def convert_field_units(envelope: np.ndarray, n: np.ndarray, effective_area: float) -> np.ndarray: def convert_field_units(envelope: np.ndarray, n: np.ndarray, effective_area: float) -> np.ndarray:
"""[summary] """
[summary]
Parameters Parameters
---------- ----------
@@ -249,7 +253,8 @@ def conform_pulse_params(
gamma: float = None, gamma: float = None,
beta2: float = None, beta2: float = None,
): ):
"""makes sure all parameters of the pulse are set and consistent """
makes sure all parameters of the pulse are set and consistent
Parameters Parameters
---------- ----------
@@ -464,14 +469,15 @@ def technical_noise(rms_noise, noise_correlation=-0.4):
Parameters Parameters
---------- ----------
rms_noise : float rms_noise : float
RMS amplitude noise of the laser RMS amplitude noise of the laser
relative factor : float relative factor : float
magnitude of the anticorrelation between peak_power and pulse width noise magnitude of the anticorrelation between peak_power and pulse width noise
Returns Returns
---------- ----------
delta_int : float delta_int : float
delta_T0 : float delta_T0 : float
""" """
psy = np.random.normal(1, rms_noise) psy = np.random.normal(1, rms_noise)
return psy, 1 + noise_correlation * (psy - 1) return psy, 1 + noise_correlation * (psy - 1)
@@ -482,19 +488,19 @@ def shot_noise(w: np.ndarray, T: float, dt: float, additional_noise_factor=1.0):
Parameters Parameters
---------- ----------
w_c : array, shape (n,) w_c : array, shape (n,)
angular frequencies centered around 0 angular frequencies centered around 0
T : float T : float
length of the time windows length of the time windows
dt : float dt : float
resolution of time grid resolution of time grid
additional_noise_factor : float additional_noise_factor : float
resulting noise spectrum is multiplied by this number resulting noise spectrum is multiplied by this number
Returns Returns
------- -------
out : array, shape (n,) out : array, shape (n,)
noise field to be added on top of initial field in time domain noise field to be added on top of initial field in time domain
""" """
rand_phase = np.random.rand(len(w)) * 2 * pi rand_phase = np.random.rand(len(w)) * 2 * pi
A_oppm = np.sqrt(hbar * (np.abs(w)) * T) * np.exp(-1j * rand_phase) A_oppm = np.sqrt(hbar * (np.abs(w)) * T) * np.exp(-1j * rand_phase)
@@ -531,21 +537,25 @@ def C_to_A(C: np.ndarray, effective_area_arr: np.ndarray) -> np.ndarray:
def mean_phase(spectra): def mean_phase(spectra):
"""computes the mean phase of spectra """
Parameter computes the mean phase of spectra
Parameters
---------- ----------
spectra : 2D array spectra : 2D array
The mean is taken on the 0th axis. This means the array has to be of shape (n, nt) The mean is taken on the 0th axis. This means the array has to be of shape (n, nt)
Returns Returns
---------- ----------
mean_phase : 1D array of shape (len(spectra[0])) mean_phase : 1D array of shape (len(spectra[0]))
array of complex numbers of unit length representing the mean phase array of complex numbers of unit length representing the mean phase
Example Example
---------- ----------
>>> x = np.array([[1 + 1j, 0 + 2j, -3 - 1j], >>> x = np.array([[1 + 1j, 0 + 2j, -3 - 1j],
[1 + 0j, 2 + 3j, -3 + 1j]]) [1 + 0j, 2 + 3j, -3 + 1j]])
>>> mean_phase(x) >>> mean_phase(x)
array([ 0.92387953+0.38268343j, 0.28978415+0.95709203j, -1. +0.j ]) array([ 0.92387953+0.38268343j, 0.28978415+0.95709203j, -1. +0.j ])
""" """
@@ -564,12 +574,12 @@ def flatten_phase(spectra):
Parameters Parameters
---------- ----------
spectra : 2D array of shape (n, nt) spectra : 2D array of shape (n, nt)
spectra arranged in the same fashion as in `scgenerator.physics.pulse.mean_phase` spectra arranged in the same fashion as in `scgenerator.physics.pulse.mean_phase`
Returns Returns
---------- ----------
output : array of same dimensions and amplitude, but with a flattened phase output : array of same dimensions and amplitude, but with a flattened phase
""" """
mean_theta = mean_phase(spectra) mean_theta = mean_phase(spectra)
tiled = np.tile(mean_theta, (len(spectra), 1)) tiled = np.tile(mean_theta, (len(spectra), 1))
@@ -578,19 +588,20 @@ def flatten_phase(spectra):
def compress_pulse(spectra): def compress_pulse(spectra):
"""given some complex spectrum, returns the compressed pulse in the time domain """
given some complex spectrum, returns the compressed pulse in the time domain
Parameters Parameters
---------- ----------
spectra : ND array spectra : ND array
spectra to compress. The shape must be at least 2D. Compression occurs along spectra to compress. The shape must be at least 2D. Compression occurs along
the -2th axis. This means spectra have to be of shape ([what, ever,] n, nt) where n the -2th axis. This means spectra have to be of shape ([what, ever,] n, nt) where n
is the number of spectra brought together for one compression operation and nt the is the number of spectra brought together for one compression operation and nt the
resolution of the grid. resolution of the grid.
Returns Returns
---------- ----------
out : array of shape ([what, ever,] nt) out : array of shape ([what, ever,] nt)
compressed inverse Fourier-transformed pulse compressed inverse Fourier-transformed pulse
""" """
if spectra.ndim > 2: if spectra.ndim > 2:
return np.array([compress_pulse(spec) for spec in spectra]) return np.array([compress_pulse(spec) for spec in spectra])
@@ -599,14 +610,16 @@ def compress_pulse(spectra):
def ideal_compressed_pulse(spectra): def ideal_compressed_pulse(spectra):
"""returns the ideal compressed pulse assuming flat phase """
returns the ideal compressed pulse assuming flat phase
Parameters Parameters
---------- ----------
spectra : 2D array, sc-ordering spectra : 2D array, sc-ordering
Returns Returns
---------- ----------
compressed : 1D array compressed : 1D array
time envelope of the compressed field time envelope of the compressed field
""" """
return math.abs2(fftshift(ifft(np.sqrt(np.mean(math.abs2(spectra), axis=0))))) return math.abs2(fftshift(ifft(np.sqrt(np.mean(math.abs2(spectra), axis=0)))))
@@ -622,18 +635,18 @@ def spectrogram(
Parameters Parameters
---------- ----------
time : np.ndarray, shape (nt,) time : np.ndarray, shape (nt,)
time in the co-moving frame of reference time in the co-moving frame of reference
delays : np.ndarray, shape (nd,) delays : np.ndarray, shape (nd,)
delays overs which to compute the spectrogram delays overs which to compute the spectrogram
signal : np.ndarray, shape (nt,) signal : np.ndarray, shape (nt,)
signal array that matches the time array signal array that matches the time array
old_w : np.ndarray, shape (nt,) old_w : np.ndarray, shape (nt,)
angular frequency array corresponding to the fourier space of the `time` array angular frequency array corresponding to the fourier space of the `time` array
new_w : np.ndarray, shape (nw,) new_w : np.ndarray, shape (nw,)
angural frequency grid of the spectrogram angural frequency grid of the spectrogram
gate_width : float, optional gate_width : float, optional
full width at half maximum of the gaussian gate pulse full width at half maximum of the gaussian gate pulse
Returns Returns
---------- ----------
@@ -656,9 +669,11 @@ def g12(values):
Parameters Parameters
---------- ----------
values : 2D array values : 2D array
complex values following sc-ordering complex values following sc-ordering
return:
Returns
-------
g12_arr : coherence function as a n-D array g12_arr : coherence function as a n-D array
""" """
@@ -677,11 +692,11 @@ def g12(values):
def avg_g12(values): def avg_g12(values):
""" """
comptutes the average of the coherence function weighted by amplitude of spectrum computes the average of the coherence function weighted by amplitude of spectrum
Parameters Parameters
---------- ----------
values : (m, n)-D array containing m complex values values : np.ndarray, shape (nd, nt)
Returns Returns
---------- ----------
@@ -697,17 +712,20 @@ def avg_g12(values):
def fwhm_ind(values, mam=None): def fwhm_ind(values, mam=None):
"""returns the indices where values is bigger than half its maximum """
returns the indices where values is bigger than half its maximum
Parameters Parameters
---------- ----------
values : array values : array
real values with ideally only one smooth peak real values with ideally only one smooth peak
mam : tupple (float, int) mam : tupple (float, int)
(maximum value, index of the maximum value) (maximum value, index of the maximum value)
Returns Returns
---------- -------
left_ind, right_ind : int left_ind, right_ind : int
indices of the the left and right spots where values drops below 1/2 the maximum indices of the the left and right spots where values drops below 1/2 the maximum
""" """
if mam is None: if mam is None:
@@ -722,18 +740,20 @@ def fwhm_ind(values, mam=None):
def peak_ind(values, mam=None): def peak_ind(values, mam=None):
"""returns the indices that encapsulate the entire peak """
returns the indices that encapsulate the entire peak
Parameters Parameters
---------- ----------
values : array values : array
real values with ideally only one smooth peak real values with ideally only one smooth peak
mam : tupple (float, int) mam : tupple (float, int)
(maximum value, index of the maximum value) (maximum value, index of the maximum value)
Returns Returns
---------- -------
left_ind, right_ind : int left_ind, right_ind : int
indices of the the left and right spots where values starts rising again, indices of the the left and right spots where values starts rising again,
with a margin of 3 with a margin of 3
""" """
if mam is None: if mam is None:
@@ -761,33 +781,36 @@ def peak_ind(values, mam=None):
def setup_splines(x_axis, values, mam=None): def setup_splines(x_axis, values, mam=None):
"""sets up spline interpolation to better measure a peak. Different splines with different """
sets up spline interpolation to better measure a peak. Different splines with different
orders are necessary because derivatives and second derivatives are computed to find extremea orders are necessary because derivatives and second derivatives are computed to find extremea
and inflection points and inflection points
Parameters Parameters
---------- ----------
x_axis : 1D array x_axis : 1D array
domain of values domain of values
values : 1D array values : 1D array
real values that ideally contain only one smooth peak to measure real values that ideally contain only one smooth peak to measure
mam : tupple (float, int) mam : tupple (float, int)
(maximum value, index of the maximum value) (maximum value, index of the maximum value)
Returns Returns
---------- -------
small_spline : scipy.interpolate.UnivariateSpline small_spline : scipy.interpolate.UnivariateSpline
order 3 spline that interpolates `values - m/2` around the peak order 3 spline that interpolates `values - m/2` around the peak
spline_4 : scipy.interpolate.UnivariateSpline spline_4 : scipy.interpolate.UnivariateSpline
order 4 spline that interpolate values around the peak order 4 spline that interpolate values around the peak
spline 5 : scipy.interpolate.UnivariateSpline spline 5 : scipy.interpolate.UnivariateSpline
order 5 spline that interpolates values around the peak order 5 spline that interpolates values around the peak
d_spline : scipy.interpolate.UnivariateSpline d_spline : scipy.interpolate.UnivariateSpline
order 3 spline that interpolates the derivative of values around the peak order 3 spline that interpolates the derivative of values around the peak
d_roots : list d_roots : list
roots of d_spline roots of d_spline
dd_roots : list dd_roots : list
inflection points of spline_5 inflection points of spline_5
l_ind, r_ind : int l_ind, r_ind : int
return values of peak_ind return values of peak_ind
""" """
# Isolate part thats roughly above max/2 # Isolate part thats roughly above max/2
@@ -814,31 +837,32 @@ def setup_splines(x_axis, values, mam=None):
def find_lobe_limits(x_axis, values, debug="", already_sorted=True): def find_lobe_limits(x_axis, values, debug="", already_sorted=True):
"""find the limits of the centra lobe given 2 derivatives of the values and """
find the limits of the centra lobe given 2 derivatives of the values and
the position of the FWHM the position of the FWHM
Parameters Parameters
---------- ----------
x_axis : 1D array x_axis : 1D array
domain of values domain of values
values : 1D array values : 1D array
real values that present a peak whose properties we want to meausure real values that present a peak whose properties we want to meausure
debug : str debug : str
if the peak is not distinct, a plot is made to assess the measurement if the peak is not distinct, a plot is made to assess the measurement
providing a debug label can help identify which plot correspond to which function call providing a debug label can help identify which plot correspond to which function call
sorted : bool sorted : bool
faster computation if arrays are already sorted faster computation if arrays are already sorted
Returns Returns
---------- -------
peak_lim : 1D array (left_lim, right_lim, peak_pos) peak_lim : 1D array (left_lim, right_lim, peak_pos)
values that delimit the left, right and maximum of the peak in units of x_axis values that delimit the left, right and maximum of the peak in units of x_axis
fwhm_pos : 1D array (left_pos, right_pos) fwhm_pos : 1D array (left_pos, right_pos)
values corresponding to fwhm positions in units of x_axis values corresponding to fwhm positions in units of x_axis
good_roots : 1D array good_roots : 1D array
all candidate values that could delimit the peak position all candidate values that could delimit the peak position
spline_4 : scipy.interpolate.UnivariateSpline spline_4 : scipy.interpolate.UnivariateSpline
order 4 spline that interpolate values around the peak order 4 spline that interpolate values around the peak
""" """
if not already_sorted: if not already_sorted:
@@ -910,7 +934,8 @@ def find_lobe_limits(x_axis, values, debug="", already_sorted=True):
def _select_roots(d_spline, d_roots, dd_roots, fwhm_pos): def _select_roots(d_spline, d_roots, dd_roots, fwhm_pos):
"""selects the limits of a lobe """
selects the limits of a lobe
Parameters Parameters
---------- ----------
@@ -1036,7 +1061,8 @@ def _detailed_find_lobe_limits(
def measure_properties(spectra, t, compress=True, return_limits=False, debug="") -> PulseProperties: def measure_properties(spectra, t, compress=True, return_limits=False, debug="") -> PulseProperties:
"""measure the quality factor, the fwhm variation, the peak power variation, """
measure the quality factor, the fwhm variation, the peak power variation,
Parameters Parameters
---------- ----------
@@ -1052,7 +1078,7 @@ def measure_properties(spectra, t, compress=True, return_limits=False, debug="")
return the time values of the limits return the time values of the limits
Returns Returns
---------- -------
PulseProperties object: PulseProperties object:
quality : float quality : float
quality factor of the pulse ensemble quality factor of the pulse ensemble
@@ -1123,7 +1149,8 @@ def measure_properties(spectra, t, compress=True, return_limits=False, debug="")
def rin_curve(spectra: np.ndarray) -> np.ndarray: def rin_curve(spectra: np.ndarray) -> np.ndarray:
"""computes the rin curve, i.e. the rin at every single point """
computes the rin curve, i.e. the rin at every single point
Parameters Parameters
---------- ----------
@@ -1159,7 +1186,8 @@ def measure_field(t: np.ndarray, field: np.ndarray) -> Tuple[float, float, float
def remove_2nd_order_dispersion( def remove_2nd_order_dispersion(
spectrum: T, w_c: np.ndarray, beta2: float, max_z: float = -100.0 spectrum: T, w_c: np.ndarray, beta2: float, max_z: float = -100.0
) -> tuple[T, OptimizeResult]: ) -> tuple[T, OptimizeResult]:
"""attempts to remove 2nd order dispersion from a complex spectrum """
attempts to remove 2nd order dispersion from a complex spectrum
Parameters Parameters
---------- ----------
@@ -1189,7 +1217,8 @@ def remove_2nd_order_dispersion(
def remove_2nd_order_dispersion2( def remove_2nd_order_dispersion2(
spectrum: T, w_c: np.ndarray, max_gdd: float = 1000e-30 spectrum: T, w_c: np.ndarray, max_gdd: float = 1000e-30
) -> tuple[T, OptimizeResult]: ) -> tuple[T, OptimizeResult]:
"""attempts to remove 2nd order dispersion from a complex spectrum """
attempts to remove 2nd order dispersion from a complex spectrum
Parameters Parameters
---------- ----------

18
src/scgenerator/physics/units.py
View File

@@ -341,7 +341,8 @@ def beta2_coef(beta2_coefficients):
def to_WL(spectrum: np.ndarray, lambda_: np.ndarray) -> np.ndarray: def to_WL(spectrum: np.ndarray, lambda_: np.ndarray) -> np.ndarray:
"""rescales the spectrum because of uneven binning when going from freq to wl """
rescales the spectrum because of uneven binning when going from freq to wl
Parameters Parameters
---------- ----------
@@ -360,12 +361,15 @@ def to_WL(spectrum: np.ndarray, lambda_: np.ndarray) -> np.ndarray:
def to_log(arr, ref=None): def to_log(arr, ref=None):
"""takes the log of each 1D array relative to the max of said array. Useful """
takes the log of each 1D array relative to the max of said array. Useful
to plot spectrum evolution, but use to_log2D for spectrograms to plot spectrum evolution, but use to_log2D for spectrograms
Parameters Parameters
---------- ----------
arr : 1D array of real numbers. >1D array : operation is applied on axis=0 arr : 1D array of real numbers. >1D array : operation is applied on axis=0
ref : reference value corresponding to 0dB (default : max(arr)) ref : reference value corresponding to 0dB (default : max(arr))
Returns Returns
---------- ----------
arr array in dB arr array in dB
@@ -381,11 +385,14 @@ def to_log(arr, ref=None):
def to_log2D(arr, ref=None): def to_log2D(arr, ref=None):
"""computes the log of a 2D array """
computes the log of a 2D array
Parameters Parameters
---------- ----------
arr : 2D array of real numbers arr : 2D array of real numbers
ref : reference value corresponding to 0dB ref : reference value corresponding to 0dB
Returns Returns
---------- ----------
arr array in dB arr array in dB
@@ -431,8 +438,9 @@ def sort_axis(
Parameters Parameters
---------- ----------
axis : 1D array containing the original axis (usual the w or t array) axis : 1D array
plt_range : tupple (min, max, conversion_function) used to crop the axis containing the original axis (usual the w or t array)
plt_range : tupple (min, max, conversion_function) used to crop the axis
Returns Returns
------- -------

35
src/scgenerator/plotting.py
View File

@@ -278,7 +278,8 @@ def propagation_plot(
cbar_label: Optional[str] = "normalized intensity (dB)", cbar_label: Optional[str] = "normalized intensity (dB)",
cmap: str = None, cmap: str = None,
) -> tuple[Figure, Axes, plt.Line2D, np.ndarray, np.ndarray]: ) -> tuple[Figure, Axes, plt.Line2D, np.ndarray, np.ndarray]:
"""transforms and plots a 2D propagation """
transforms and plots a 2D propagation
Parameters Parameters
---------- ----------
@@ -343,7 +344,8 @@ def plot_2D(
cmap: str = None, cmap: str = None,
cbar_label: str = "", cbar_label: str = "",
) -> Union[tuple[Axes, Axes], Axes]: ) -> Union[tuple[Axes, Axes], Axes]:
"""plots given 2D values in a standard """
plots given 2D values in a standard
Parameters Parameters
---------- ----------
@@ -436,7 +438,8 @@ def transform_2D_propagation(
skip: int = 1, skip: int = 1,
params: Parameters = None, params: Parameters = None,
) -> tuple[np.ndarray, np.ndarray, np.ndarray]: ) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
"""transforms raws values into plottable values """
transforms raws values into plottable values
Parameters Parameters
---------- ----------
@@ -640,7 +643,8 @@ def plot_mean(
mean_style: dict[str, Any] = None, mean_style: dict[str, Any] = None,
individual_style: dict[str, Any] = None, individual_style: dict[str, Any] = None,
) -> tuple[plt.Line2D, list[plt.Line2D]]: ) -> tuple[plt.Line2D, list[plt.Line2D]]:
"""plots already transformed 1D values """
plots already transformed 1D values
Parameters Parameters
---------- ----------
@@ -737,7 +741,8 @@ def plot_1D(
transpose: bool = False, transpose: bool = False,
**line_kwargs, **line_kwargs,
) -> plt.Line2D: ) -> plt.Line2D:
"""plots already transformed 1D values """
plots already transformed 1D values
Parameters Parameters
---------- ----------
@@ -788,7 +793,8 @@ def transform_1D_values(
log: Union[int, float, bool] = False, log: Union[int, float, bool] = False,
spacing: Union[int, float] = 1, spacing: Union[int, float] = 1,
) -> tuple[np.ndarray, np.ndarray]: ) -> tuple[np.ndarray, np.ndarray]:
"""transforms raw values to be plotted """
transforms raw values to be plotted
Parameters Parameters
---------- ----------
@@ -852,7 +858,9 @@ def plot_spectrogram(
cmap: str = None, cmap: str = None,
ax: Union[Axes, tuple[Axes, Axes]] = None, ax: Union[Axes, tuple[Axes, Axes]] = None,
): ):
"""Plots a spectrogram given a complex field in the time domain """
Plots a spectrogram given a complex field in the time domain
Parameters Parameters
---------- ----------
values : 2D array values : 2D array
@@ -881,7 +889,6 @@ def plot_spectrogram(
ax : matplotlib.axes._subplots.AxesSubplot object or tupple of 2 axis objects, optional ax : matplotlib.axes._subplots.AxesSubplot object or tupple of 2 axis objects, optional
axis on which to draw the plot axis on which to draw the plot
if only one is given, a new one will be created to draw the colorbar if only one is given, a new one will be created to draw the colorbar
""" """
if values.ndim != 1: if values.ndim != 1:
print("plot_spectrogram can only plot 1D arrays") print("plot_spectrogram can only plot 1D arrays")
@@ -951,7 +958,8 @@ def uniform_axis(
values: np.ndarray, values: np.ndarray,
new_axis_spec: Union[PlotRange, RangeType, str], new_axis_spec: Union[PlotRange, RangeType, str],
) -> tuple[np.ndarray, np.ndarray]: ) -> tuple[np.ndarray, np.ndarray]:
"""given some values(axis), creates a new uniformly spaced axis and interpolates """
given some values(axis), creates a new uniformly spaced axis and interpolates
the values over it. the values over it.
Parameters Parameters
@@ -1001,7 +1009,8 @@ def uniform_axis(
def apply_log(values: np.ndarray, log: Union[str, bool, float, int]) -> np.ndarray: def apply_log(values: np.ndarray, log: Union[str, bool, float, int]) -> np.ndarray:
"""apply log transform """
apply log transform
Parameters Parameters
---------- ----------
@@ -1062,7 +1071,8 @@ def white_bottom_cmap(name, start=0, end=1, new_name="white_background", c_back=
def default_marker_style(k): def default_marker_style(k):
"""returns a style dictionary """
returns a style dictionary
Parameters Parameters
---------- ----------
@@ -1100,7 +1110,8 @@ def measure_and_annotate_fwhm(
arrow_length_pts: float = 20.0, arrow_length_pts: float = 20.0,
arrow_props: dict[str, Any] = None, arrow_props: dict[str, Any] = None,
) -> float: ) -> float:
"""measured the FWHM of a pulse and plots it """
measured the FWHM of a pulse and plots it
Parameters Parameters
---------- ----------

12
src/scgenerator/spectra.py
View File

@@ -138,7 +138,8 @@ class SimulationSeries:
fiber_positions: list[tuple[str, float]] fiber_positions: list[tuple[str, float]]
def __init__(self, path: os.PathLike): def __init__(self, path: os.PathLike):
"""Create a SimulationSeries """
Create a SimulationSeries
Parameters Parameters
---------- ----------
@@ -249,7 +250,8 @@ class SimulationSeries:
sim_ind: int = 0, sim_ind: int = 0,
**kwargs, **kwargs,
) -> tuple[np.ndarray, np.ndarray]: ) -> tuple[np.ndarray, np.ndarray]:
"""gives the desired values already tranformes according to the give range """
gives the desired values already tranformes according to the give range
Parameters Parameters
---------- ----------
@@ -299,7 +301,8 @@ class SimulationSeries:
def rin_propagation( def rin_propagation(
self, left: float, right: float, unit: str self, left: float, right: float, unit: str
) -> tuple[np.ndarray, np.ndarray, np.ndarray]: ) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
"""returns the RIN as function of unit and z """
returns the RIN as function of unit and z
Parameters Parameters
---------- ----------
@@ -387,7 +390,8 @@ class SimulatedFiber:
raise ValueError(f"cannot match z={pos} with max length of {self.params.length}") raise ValueError(f"cannot match z={pos} with max length of {self.params.length}")
def _load_1(self, z_ind: int, sim_ind=0) -> np.ndarray: def _load_1(self, z_ind: int, sim_ind=0) -> np.ndarray:
"""loads a spectrum file """
loads a spectrum file
Parameters Parameters
---------- ----------

38
src/scgenerator/utils.py
View File

@@ -8,6 +8,7 @@ from __future__ import annotations
import datetime import datetime
import inspect import inspect
import itertools import itertools
import json
import os import os
import re import re
from collections import defaultdict from collections import defaultdict
@@ -71,9 +72,11 @@ def open_single_config(path: os.PathLike) -> dict[str, Any]:
def _open_config(path: os.PathLike): def _open_config(path: os.PathLike):
"""returns a dictionary parsed from the specified toml file """
returns a dictionary parsed from the specified toml file
This also handle having a 'INCLUDE' argument that will fill This also handle having a 'INCLUDE' argument that will fill
otherwise unspecified keys with what's in the INCLUDE file(s)""" otherwise unspecified keys with what's in the INCLUDE file(s)
"""
path = conform_toml_path(path) path = conform_toml_path(path)
dico = resolve_loadfile_arg(load_toml(path)) dico = resolve_loadfile_arg(load_toml(path))
@@ -150,20 +153,24 @@ def save_toml(path: os.PathLike, dico):
@cache @cache
def load_material_dico(name: str) -> dict[str, Any]: def load_material_dico(name: str) -> dict[str, Any]:
"""loads a material dictionary """
loads a material dictionary
Parameters Parameters
---------- ----------
name : str name : str
name of the material name of the material
Returns Returns
---------- -------
material_dico : dict material_dico : dict
""" """
return json.loads(io.data_file("materials.json").read_text())[name] return json.loads(io.data_file("materials.json").read_text())[name]
def save_data(data: Union[np.ndarray, MutableMapping], data_dir: Path, file_name: str): def save_data(data: Union[np.ndarray, MutableMapping], data_dir: Path, file_name: str):
"""saves numpy array to disk """
saves numpy array to disk
Parameters Parameters
---------- ----------
@@ -186,7 +193,8 @@ def save_data(data: Union[np.ndarray, MutableMapping], data_dir: Path, file_name
def ensure_folder(path: Path, prevent_overwrite: bool = True, mkdir=True) -> Path: def ensure_folder(path: Path, prevent_overwrite: bool = True, mkdir=True) -> Path:
"""ensure a folder exists and doesn't overwrite anything if required """
ensure a folder exists and doesn't overwrite anything if required
Parameters Parameters
---------- ----------
@@ -276,7 +284,8 @@ def to_62(i: int) -> str:
def get_arg_names(func: Callable) -> list[str]: def get_arg_names(func: Callable) -> list[str]:
"""returns the positional argument names of func. """
returns the positional argument names of func.
Parameters Parameters
---------- ----------
@@ -338,7 +347,8 @@ def fft_functions(
def combine_simulations(path: Path, dest: Path = None): def combine_simulations(path: Path, dest: Path = None):
"""combines raw simulations into one folder per branch """
combines raw simulations into one folder per branch
Parameters Parameters
---------- ----------
@@ -393,7 +403,8 @@ def update_params(new_path: Path, file: Path):
def save_parameters( def save_parameters(
params: dict[str, Any], destination_dir: Path, file_name: str = PARAM_FN params: dict[str, Any], destination_dir: Path, file_name: str = PARAM_FN
) -> Path: ) -> Path:
"""saves a parameter dictionary. Note that is does remove some entries, particularly """
saves a parameter dictionary. Note that is does remove some entries, particularly
those that take a lot of space ("t", "w", ...) those that take a lot of space ("t", "w", ...)
Parameters Parameters
@@ -427,7 +438,8 @@ def fiber_folder(i: int, sim_name: str, fiber_name: str) -> str:
def simulations_list(path: os.PathLike) -> list[Path]: def simulations_list(path: os.PathLike) -> list[Path]:
"""finds simulations folders contained in a parent directory """
finds simulations folders contained in a parent directory
Parameters Parameters
---------- ----------