From 7e797d930fc0e31cb8700cae7b3ac9857514db98 Mon Sep 17 00:00:00 2001
From: Tom Body <tbody@cfs.energy>
Date: Thu, 1 Aug 2024 09:15:29 -0400
Subject: [PATCH 1/5] Limit JSON print to 10 significant figures
---
cfspopcon/file_io.py | 11 +
tests/regression_results/AUG_SepOS_minTe.json | 62 +-
tests/regression_results/PRD.json | 790 +++++++++---------
3 files changed, 437 insertions(+), 426 deletions(-)
diff --git a/cfspopcon/file_io.py b/cfspopcon/file_io.py
index b4d81a5..d82cb2e 100644
--- a/cfspopcon/file_io.py
+++ b/cfspopcon/file_io.py
@@ -121,5 +121,16 @@ def write_point_to_file(dataset: xr.Dataset, point_key: str, point_params: dict,
output_dir.mkdir(parents=True, exist_ok=True)
+ class RoundingFloat(float):
+ """A formatter to control how floats are written to JSON.
+
+ From: https://stackoverflow.com/questions/54370322/how-to-limit-the-number-of-float-digits-jsonencoder-produces
+ """
+
+ __repr__ = staticmethod(lambda x: f"{x:#.10g}")
+
+ json.encoder.c_make_encoder = None # type:ignore[attr-defined]
+ json.encoder.float = RoundingFloat # type:ignore[attr-defined]
+
with open(output_dir / f"{point_key}.json", "w") as file:
json.dump(point.to_dict(), file, indent=4, sort_keys=True)
diff --git a/tests/regression_results/AUG_SepOS_minTe.json b/tests/regression_results/AUG_SepOS_minTe.json
index 56d1b0c..fb41f44 100644
--- a/tests/regression_results/AUG_SepOS_minTe.json
+++ b/tests/regression_results/AUG_SepOS_minTe.json
@@ -3,12 +3,12 @@
"coords": {
"dim_separatrix_electron_density": {
"attrs": {},
- "data": 1.443846153846154,
+ "data": 1.443846154,
"dims": []
},
"dim_separatrix_electron_temp": {
"attrs": {},
- "data": 57.51724137931035,
+ "data": 57.51724138,
"dims": []
}
},
@@ -17,203 +17,203 @@
"attrs": {
"units": "tesla"
},
- "data": 0.3265306124226533,
+ "data": 0.3265306124,
"dims": []
},
"B_t_out_mid": {
"attrs": {
"units": "tesla"
},
- "data": 1.927570093457944,
+ "data": 1.927570093,
"dims": []
},
"SepOS_LH_transition": {
"attrs": {
"units": "dimensionless"
},
- "data": 1.0025081265471087,
+ "data": 1.002508127,
"dims": []
},
"SepOS_MHD_limit": {
"attrs": {
"units": "dimensionless"
},
- "data": 0.3560483425183738,
+ "data": 0.3560483425,
"dims": []
},
"SepOS_density_limit": {
"attrs": {
"units": "dimensionless"
},
- "data": 0.5502074424382402,
+ "data": 0.5502074424,
"dims": []
},
"alpha_t": {
"attrs": {
"units": "dimensionless"
},
- "data": 0.5195258259822426,
+ "data": 0.5195258260,
"dims": []
},
"areal_elongation": {
"attrs": {
"units": "dimensionless"
},
- "data": 1.64,
+ "data": 1.640000000,
"dims": []
},
"average_ion_mass": {
"attrs": {
"units": "unified_atomic_mass_unit"
},
- "data": 2.0,
+ "data": 2.000000000,
"dims": []
},
"critical_alpha_MHD": {
"attrs": {
"units": "dimensionless"
},
- "data": 2.5486604604701935,
+ "data": 2.548660460,
"dims": []
},
"cylindrical_safety_factor": {
"attrs": {
"units": "dimensionless"
},
- "data": 4.476700876332845,
+ "data": 4.476700876,
"dims": []
},
"elongation_psi95": {
"attrs": {
"units": "dimensionless"
},
- "data": 1.6,
+ "data": 1.600000000,
"dims": []
},
"elongation_ratio_areal_to_psi95": {
"attrs": {
"units": "dimensionless"
},
- "data": 1.025,
+ "data": 1.025000000,
"dims": []
},
"fraction_of_P_SOL_to_divertor": {
"attrs": {
"units": "dimensionless"
},
- "data": 0.6,
+ "data": 0.6000000000,
"dims": []
},
"inverse_aspect_ratio": {
"attrs": {
"units": "dimensionless"
},
- "data": 0.296969696969697,
+ "data": 0.2969696970,
"dims": []
},
"ion_heat_diffusivity": {
"attrs": {
"units": "meter ** 2 / second"
},
- "data": 0.5,
+ "data": 0.5000000000,
"dims": []
},
"magnetic_field_on_axis": {
"attrs": {
"units": "tesla"
},
- "data": 2.5,
+ "data": 2.500000000,
"dims": []
},
"major_radius": {
"attrs": {
"units": "meter"
},
- "data": 1.65,
+ "data": 1.650000000,
"dims": []
},
"mean_ion_charge_state": {
"attrs": {
"units": "dimensionless"
},
- "data": 1.0,
+ "data": 1.000000000,
"dims": []
},
"minor_radius": {
"attrs": {
"units": "meter"
},
- "data": 0.49,
+ "data": 0.4900000000,
"dims": []
},
"plasma_current": {
"attrs": {
"units": "ampere"
},
- "data": 800000.0,
+ "data": 800000.0000,
"dims": []
},
"poloidal_sound_larmor_radius": {
"attrs": {
"units": "millimeter"
},
- "data": 4.4794720291352315,
+ "data": 4.479472029,
"dims": []
},
"separatrix_electron_density": {
"attrs": {
"units": "_1e19_per_cubic_metre"
},
- "data": 1.443846153846154,
+ "data": 1.443846154,
"dims": []
},
"separatrix_electron_temp": {
"attrs": {
"units": "electron_volt"
},
- "data": 57.51724137931035,
+ "data": 57.51724138,
"dims": []
},
"surface_area": {
"attrs": {
"units": "meter ** 2"
},
- "data": 40.01085451537566,
+ "data": 40.01085452,
"dims": []
},
"sustainment_power_in_electron_channel": {
"attrs": {
"units": "megawatt"
},
- "data": 0.7413990364829475,
+ "data": 0.7413990365,
"dims": []
},
"sustainment_power_in_ion_channel": {
"attrs": {
"units": "megawatt"
},
- "data": 0.16744964593929906,
+ "data": 0.1674496459,
"dims": []
},
"target_electron_temp": {
"attrs": {
"units": "electron_volt"
},
- "data": 10.0,
+ "data": 10.00000000,
"dims": []
},
"triangularity_psi95": {
"attrs": {
"units": "dimensionless"
},
- "data": 0.3,
+ "data": 0.3000000000,
"dims": []
},
"z_effective": {
"attrs": {
"units": "dimensionless"
},
- "data": 1.25,
+ "data": 1.250000000,
"dims": []
}
},
diff --git a/tests/regression_results/PRD.json b/tests/regression_results/PRD.json
index 62d859f..4c0a58a 100644
--- a/tests/regression_results/PRD.json
+++ b/tests/regression_results/PRD.json
@@ -3,12 +3,12 @@
"coords": {
"dim_average_electron_density": {
"attrs": {},
- "data": 25.0,
+ "data": 25.00000000,
"dims": []
},
"dim_average_electron_temp": {
"attrs": {},
- "data": 9.137931034482758,
+ "data": 9.137931034,
"dims": []
},
"dim_species": {
@@ -30,112 +30,112 @@
"attrs": {
"units": "tesla"
},
- "data": 3.0527119151332296,
+ "data": 3.052711915,
"dims": []
},
"B_t_out_mid": {
"attrs": {
"units": "tesla"
},
- "data": 9.326504089901384,
+ "data": 9.326504090,
"dims": []
},
"PB_over_R": {
"attrs": {
"units": "megawatt * tesla / meter"
},
- "data": 168.65128665872822,
+ "data": 168.6512867,
"dims": []
},
"PBpRnSq": {
"attrs": {
"units": "megawatt * tesla / _1e20_per_cubic_metre ** 2 / meter"
},
- "data": 8.20119898533133,
+ "data": 8.201198985,
"dims": []
},
"P_LH_thresh": {
"attrs": {
"units": "megawatt"
},
- "data": 24.59383938922551,
+ "data": 24.59383939,
"dims": []
},
"P_alpha": {
"attrs": {
"units": "megawatt"
},
- "data": 22.55867181683056,
+ "data": 22.55867182,
"dims": []
},
"P_auxillary": {
"attrs": {
"units": "megawatt"
},
- "data": 7.702542635179901,
+ "data": 7.702542635,
"dims": []
},
"P_external": {
"attrs": {
"units": "megawatt"
},
- "data": 8.904164505601578,
+ "data": 8.904164506,
"dims": []
},
"P_fusion": {
"attrs": {
"units": "megawatt"
},
- "data": 112.79335908415277,
+ "data": 112.7933591,
"dims": []
},
"P_in": {
"attrs": {
"units": "megawatt"
},
- "data": 31.46283632243214,
+ "data": 31.46283632,
"dims": []
},
"P_launched": {
"attrs": {
"units": "megawatt"
},
- "data": 9.893516117335087,
+ "data": 9.893516117,
"dims": []
},
"P_neutron": {
"attrs": {
"units": "megawatt"
},
- "data": 90.23468726732224,
+ "data": 90.23468727,
"dims": []
},
"P_ohmic": {
"attrs": {
"units": "megawatt"
},
- "data": 1.2016218704216768,
+ "data": 1.201621870,
"dims": []
},
"P_radiation": {
"attrs": {
"units": "megawatt"
},
- "data": 5.8886658045102305,
+ "data": 5.888665805,
"dims": []
},
"P_radiation_from_core_seeded_impurity": {
"attrs": {
"units": "megawatt"
},
- "data": 0.0,
+ "data": 0.000000000,
"dims": []
},
"Q": {
"attrs": {
"units": "dimensionless"
},
- "data": 11.40073536510645,
+ "data": 11.40073537,
"dims": []
},
"SOL_momentum_loss_function": {
@@ -147,91 +147,91 @@
"attrs": {
"units": "dimensionless"
},
- "data": 0.9639499116429592,
+ "data": 0.9639499116,
"dims": []
},
"areal_elongation": {
"attrs": {
"units": "dimensionless"
},
- "data": 1.75,
+ "data": 1.750000000,
"dims": []
},
"average_electron_density": {
"attrs": {
"units": "_1e19_per_cubic_metre"
},
- "data": 25.0,
+ "data": 25.00000000,
"dims": []
},
"average_electron_temp": {
"attrs": {
"units": "kiloelectron_volt"
},
- "data": 9.137931034482758,
+ "data": 9.137931034,
"dims": []
},
"average_ion_density": {
"attrs": {
"units": "_1e19_per_cubic_metre"
},
- "data": 21.35814799897336,
+ "data": 21.35814800,
"dims": []
},
"average_ion_mass": {
"attrs": {
"units": "unified_atomic_mass_unit"
},
- "data": 2.5,
+ "data": 2.500000000,
"dims": []
},
"average_ion_temp": {
"attrs": {
"units": "kiloelectron_volt"
},
- "data": 9.137931034482758,
+ "data": 9.137931034,
"dims": []
},
"average_total_pressure": {
"attrs": {
"units": "pascal"
},
- "data": 732028.9793275861,
+ "data": 732028.9793,
"dims": []
},
"beta_poloidal": {
"attrs": {
"units": "dimensionless"
},
- "data": 0.19742242875250135,
+ "data": 0.1974224288,
"dims": []
},
"beta_toroidal": {
"attrs": {
"units": "dimensionless"
},
- "data": 0.012360853882996833,
+ "data": 0.01236085388,
"dims": []
},
"beta_total": {
"attrs": {
"units": "dimensionless"
},
- "data": 0.011632527455851185,
+ "data": 0.01163252746,
"dims": []
},
"bootstrap_fraction": {
"attrs": {
"units": "dimensionless"
},
- "data": 0.08515124438705672,
+ "data": 0.08515124439,
"dims": []
},
"breakdown_flux_consumption": {
"attrs": {
"units": "weber"
},
- "data": 0.12840000000000001,
+ "data": 0.1284000000,
"dims": []
},
"change_in_dilution": {
@@ -239,11 +239,11 @@
"units": "dimensionless"
},
"data": [
- 0.12,
- 0.024798333717489005,
+ 0.1200000000,
+ 0.02479833372,
NaN,
- 0.0,
- 0.0008757463235765251
+ 0.000000000,
+ 0.0008757463236
],
"dims": [
"dim_species"
@@ -254,11 +254,11 @@
"units": "dimensionless"
},
"data": [
- 0.12,
- 0.1735750066579794,
+ 0.1200000000,
+ 0.1735750067,
NaN,
- 0.0,
- 0.0502530285602768
+ 0.000000000,
+ 0.05025302856
],
"dims": [
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@@ -268,14 +268,14 @@
"attrs": {
"units": "dimensionless"
},
- "data": 1.0,
+ "data": 1.000000000,
"dims": []
},
"confinement_time_scalar": {
"attrs": {
"units": "dimensionless"
},
- "data": 1.0,
+ "data": 1.000000000,
"dims": []
},
"core_impurity_species": {
@@ -287,21 +287,21 @@
"attrs": {
"units": "dimensionless"
},
- "data": 0.1871625858572634,
+ "data": 0.1871625859,
"dims": []
},
"current_relaxation_time": {
"attrs": {
"units": "second"
},
- "data": 16.361422316376107,
+ "data": 16.36142232,
"dims": []
},
"cylindrical_safety_factor": {
"attrs": {
"units": "dimensionless"
},
- "data": 2.675118549054515,
+ "data": 2.675118549,
"dims": []
},
"density_profile_form": {
@@ -313,28 +313,28 @@
"attrs": {
"units": "dimensionless"
},
- "data": 0.8543259199589345,
+ "data": 0.8543259200,
"dims": []
},
"edge_impurity_concentration": {
"attrs": {
"units": "dimensionless"
},
- "data": 0.08439527531343535,
+ "data": 0.08439527531,
"dims": []
},
"edge_impurity_concentration_in_core": {
"attrs": {
"units": "dimensionless"
},
- "data": 0.01687905506268707,
+ "data": 0.01687905506,
"dims": []
},
"edge_impurity_enrichment": {
"attrs": {
"units": "dimensionless"
},
- "data": 5.0,
+ "data": 5.000000000,
"dims": []
},
"edge_impurity_species": {
@@ -346,28 +346,28 @@
"attrs": {
"units": "dimensionless"
},
- "data": 0.0744319988819624,
+ "data": 0.07443199888,
"dims": []
},
"ejima_coefficient": {
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"units": "dimensionless"
},
- "data": 0.6,
+ "data": 0.6000000000,
"dims": []
},
"electron_density_peaking": {
"attrs": {
"units": "dimensionless"
},
- "data": 1.5011364712930257,
+ "data": 1.501136471,
"dims": []
},
"electron_density_peaking_offset": {
"attrs": {
"units": "dimensionless"
},
- "data": -0.1,
+ "data": -0.1000000000,
"dims": []
},
"electron_density_profile": {
@@ -375,56 +375,56 @@
"units": "_1e19_per_cubic_metre"
},
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@@ -435,56 +435,56 @@
"units": "kiloelectron_volt"
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"surface_area": {
"attrs": {
"units": "meter ** 2"
},
- "data": 55.536257947812175,
+ "data": 55.53625795,
"dims": []
},
"surface_inductance_coefficients": {
@@ -1220,28 +1220,28 @@
"attrs": {
"units": "_1e19_per_cubic_metre"
},
- "data": 44.85972984158247,
+ "data": 44.85972984,
"dims": []
},
"target_electron_flux": {
"attrs": {
"units": "1 / meter ** 2 / second"
},
- "data": 1.970617339216083e+25,
+ "data": 1.970617339e+25,
"dims": []
},
"target_electron_temp": {
"attrs": {
"units": "electron_volt"
},
- "data": 25.0,
+ "data": 25.00000000,
"dims": []
},
"target_q_parallel": {
"attrs": {
"units": "gigawatt / meter ** 2"
},
- "data": 0.4128534409629226,
+ "data": 0.4128534410,
"dims": []
},
"temp_profile_form": {
@@ -1253,14 +1253,14 @@
"attrs": {
"units": "dimensionless"
},
- "data": 2.5,
+ "data": 2.500000000,
"dims": []
},
"toroidal_flux_expansion": {
"attrs": {
"units": "dimensionless"
},
- "data": 0.6974,
+ "data": 0.6974000000,
"dims": []
},
"total_flux_available_from_CS": {
@@ -1274,35 +1274,35 @@
"attrs": {
"units": "dimensionless"
},
- "data": 2.377505168672477,
+ "data": 2.377505169,
"dims": []
},
"triangularity_psi95": {
"attrs": {
"units": "dimensionless"
},
- "data": 0.3,
+ "data": 0.3000000000,
"dims": []
},
"triangularity_ratio_sep_to_psi95": {
"attrs": {
"units": "dimensionless"
},
- "data": 1.8,
+ "data": 1.800000000,
"dims": []
},
"vertical_field_mutual_inductance": {
"attrs": {
"units": "dimensionless"
},
- "data": 1.0293853117575016,
+ "data": 1.029385312,
"dims": []
},
"vertical_magnetic_field": {
"attrs": {
"units": "tesla"
},
- "data": 1.1441875312785694,
+ "data": 1.144187531,
"dims": []
},
"vertical_magnetic_field_equation": {
@@ -1314,14 +1314,14 @@
"attrs": {
"units": "meter"
},
- "data": 1.1221579687499998,
+ "data": 1.122157969,
"dims": []
},
"z_effective": {
"attrs": {
"units": "dimensionless"
},
- "data": 1.3438280352182561,
+ "data": 1.343828035,
"dims": []
}
},
From 73b18ac810849728aef2045382a6613bf06a9680 Mon Sep 17 00:00:00 2001
From: Tom Body <tbody@cfs.energy>
Date: Thu, 1 Aug 2024 19:19:54 -0400
Subject: [PATCH 2/5] Compatibility fix for Py3.9
---
cfspopcon/file_io.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/cfspopcon/file_io.py b/cfspopcon/file_io.py
index d82cb2e..c62fcc9 100644
--- a/cfspopcon/file_io.py
+++ b/cfspopcon/file_io.py
@@ -127,7 +127,7 @@ class RoundingFloat(float):
From: https://stackoverflow.com/questions/54370322/how-to-limit-the-number-of-float-digits-jsonencoder-produces
"""
- __repr__ = staticmethod(lambda x: f"{x:#.10g}")
+ __repr__ = staticmethod(lambda x: f"{x:#.10g}") # type:ignore[assignment,unused-ignore]
json.encoder.c_make_encoder = None # type:ignore[attr-defined]
json.encoder.float = RoundingFloat # type:ignore[attr-defined]
From b64ac22c9d0620691ffbc1ef2c27b684a87fecdc Mon Sep 17 00:00:00 2001
From: Tom Body <tbody@cfs.energy>
Date: Fri, 2 Aug 2024 10:25:27 -0400
Subject: [PATCH 3/5] Add a context manager for modifying the JSON encoder
---
cfspopcon/file_io.py | 50 +++++++++++++++++++++++++++++++-------------
1 file changed, 36 insertions(+), 14 deletions(-)
diff --git a/cfspopcon/file_io.py b/cfspopcon/file_io.py
index c62fcc9..401967a 100644
--- a/cfspopcon/file_io.py
+++ b/cfspopcon/file_io.py
@@ -2,7 +2,7 @@
import json
from pathlib import Path
-from typing import Any, Literal
+from typing import Any, Literal, Self
import numpy as np
import xarray as xr
@@ -91,6 +91,38 @@ def read_dataset_from_netcdf(filepath: Path) -> xr.Dataset:
return dataset
+# These following lines are needed to modify the representation of floats
+# in the JSON file. This is needed, because otherwise small errors in the
+# floats lead to a large, meaningless diff of the reference JSON files.
+
+
+class RoundingFloat(float):
+ """A modified version of the 'float' built-in, with a modified __repr__.
+
+ This is needed because `iterencode` directly uses `float.__repr__` in `floatstr`.
+
+ From: https://stackoverflow.com/questions/54370322/how-to-limit-the-number-of-float-digits-jsonencoder-produces
+ """
+
+ __repr__ = staticmethod(lambda x: f"{x:#.10g}") # type:ignore[assignment,unused-ignore]
+
+
+class ModifyJSONFloatRepr:
+ """A ContextManager to locally modify the representation of floats."""
+
+ def __enter__(self) -> Self:
+ """Change the float representation to fixed precision on entry."""
+ self.c_make_encoder = json.encoder.c_make_encoder # type:ignore[attr-defined]
+ json.encoder.c_make_encoder = None # type:ignore[attr-defined]
+ json.encoder.float = RoundingFloat # type:ignore[attr-defined]
+ return self
+
+ def __exit__(self, *args: Any) -> None:
+ """Change the float representation back to the default."""
+ json.encoder.c_make_encoder = self.c_make_encoder # type:ignore[attr-defined]
+ json.encoder.float = float # type:ignore[attr-defined]
+
+
def write_point_to_file(dataset: xr.Dataset, point_key: str, point_params: dict, output_dir: Path) -> None:
"""Write the analysis values at the named points to a json file."""
mask = build_mask_from_dict(dataset, point_params)
@@ -121,16 +153,6 @@ def write_point_to_file(dataset: xr.Dataset, point_key: str, point_params: dict,
output_dir.mkdir(parents=True, exist_ok=True)
- class RoundingFloat(float):
- """A formatter to control how floats are written to JSON.
-
- From: https://stackoverflow.com/questions/54370322/how-to-limit-the-number-of-float-digits-jsonencoder-produces
- """
-
- __repr__ = staticmethod(lambda x: f"{x:#.10g}") # type:ignore[assignment,unused-ignore]
-
- json.encoder.c_make_encoder = None # type:ignore[attr-defined]
- json.encoder.float = RoundingFloat # type:ignore[attr-defined]
-
- with open(output_dir / f"{point_key}.json", "w") as file:
- json.dump(point.to_dict(), file, indent=4, sort_keys=True)
+ with ModifyJSONFloatRepr():
+ with open(output_dir / f"{point_key}.json", "w") as file:
+ json.dump(point.to_dict(), file, indent=4, sort_keys=True)
From 805d36fc1ef7289181639702b772d78dda9534c6 Mon Sep 17 00:00:00 2001
From: Tom Body <tbody@cfs.energy>
Date: Fri, 2 Aug 2024 10:46:26 -0400
Subject: [PATCH 4/5] Arrrgh Py3.9
---
cfspopcon/file_io.py | 8 +++++++-
1 file changed, 7 insertions(+), 1 deletion(-)
diff --git a/cfspopcon/file_io.py b/cfspopcon/file_io.py
index 401967a..6eaea20 100644
--- a/cfspopcon/file_io.py
+++ b/cfspopcon/file_io.py
@@ -1,8 +1,14 @@
"""Functions for saving results to file and loading those files."""
import json
+import sys
from pathlib import Path
-from typing import Any, Literal, Self
+from typing import Any, Literal
+
+if sys.version_info >= (3, 11, 0):
+ from typing import Self # type:ignore[attr-defined,unused-ignore]
+else:
+ from typing_extensions import Self # type:ignore[attr-defined,unused-ignore]
import numpy as np
import xarray as xr
From 10038a1cf11c07b93a42459c10cf700ab122f14e Mon Sep 17 00:00:00 2001
From: Christoph Hasse <hassec@users.noreply.github.com>
Date: Fri, 2 Aug 2024 12:30:14 -0400
Subject: [PATCH 5/5] make names private
---
cfspopcon/file_io.py | 8 ++++----
1 file changed, 4 insertions(+), 4 deletions(-)
diff --git a/cfspopcon/file_io.py b/cfspopcon/file_io.py
index 6eaea20..d12b237 100644
--- a/cfspopcon/file_io.py
+++ b/cfspopcon/file_io.py
@@ -102,7 +102,7 @@ def read_dataset_from_netcdf(filepath: Path) -> xr.Dataset:
# floats lead to a large, meaningless diff of the reference JSON files.
-class RoundingFloat(float):
+class _RoundingFloat(float):
"""A modified version of the 'float' built-in, with a modified __repr__.
This is needed because `iterencode` directly uses `float.__repr__` in `floatstr`.
@@ -113,14 +113,14 @@ class RoundingFloat(float):
__repr__ = staticmethod(lambda x: f"{x:#.10g}") # type:ignore[assignment,unused-ignore]
-class ModifyJSONFloatRepr:
+class _ModifyJSONFloatRepr:
"""A ContextManager to locally modify the representation of floats."""
def __enter__(self) -> Self:
"""Change the float representation to fixed precision on entry."""
self.c_make_encoder = json.encoder.c_make_encoder # type:ignore[attr-defined]
json.encoder.c_make_encoder = None # type:ignore[attr-defined]
- json.encoder.float = RoundingFloat # type:ignore[attr-defined]
+ json.encoder.float = _RoundingFloat # type:ignore[attr-defined]
return self
def __exit__(self, *args: Any) -> None:
@@ -159,6 +159,6 @@ def write_point_to_file(dataset: xr.Dataset, point_key: str, point_params: dict,
output_dir.mkdir(parents=True, exist_ok=True)
- with ModifyJSONFloatRepr():
+ with _ModifyJSONFloatRepr():
with open(output_dir / f"{point_key}.json", "w") as file:
json.dump(point.to_dict(), file, indent=4, sort_keys=True)