From 1de5655bafe0a75c7933d93bed7163dba49a26ed Mon Sep 17 00:00:00 2001
From: lukas leufen <l.leufen@fz-juelich.de>
Date: Mon, 13 Jul 2020 17:18:03 +0200
Subject: [PATCH] renamed interpolate to interpolation
---
mlair/configuration/defaults.py | 4 ++--
mlair/data_handling/data_generator.py | 24 +++++++++----------
mlair/run_modules/experiment_setup.py | 18 +++++++-------
mlair/run_modules/pre_processing.py | 6 ++---
.../test_data_handling/test_data_generator.py | 6 ++---
test/test_modules/test_experiment_setup.py | 10 ++++----
6 files changed, 34 insertions(+), 34 deletions(-)
diff --git a/mlair/configuration/defaults.py b/mlair/configuration/defaults.py
index 0038bb55..3f38e14f 100644
--- a/mlair/configuration/defaults.py
+++ b/mlair/configuration/defaults.py
@@ -28,8 +28,8 @@ DEFAULT_TARGET_VAR = "o3"
DEFAULT_TARGET_DIM = "variables"
DEFAULT_WINDOW_LEAD_TIME = 3
DEFAULT_DIMENSIONS = {"new_index": ["datetime", "Stations"]}
-DEFAULT_INTERPOLATE_DIM = "datetime"
-DEFAULT_INTERPOLATE_METHOD = "linear"
+DEFAULT_INTERPOLATION_DIM = "datetime"
+DEFAULT_INTERPOLATION_METHOD = "linear"
DEFAULT_LIMIT_NAN_FILL = 1
DEFAULT_TRAIN_START = "1997-01-01"
DEFAULT_TRAIN_END = "2007-12-31"
diff --git a/mlair/data_handling/data_generator.py b/mlair/data_handling/data_generator.py
index c0a32771..0088d00a 100644
--- a/mlair/data_handling/data_generator.py
+++ b/mlair/data_handling/data_generator.py
@@ -58,8 +58,8 @@ class DataGenerator(keras.utils.Sequence):
"""
def __init__(self, data_path: str, stations: Union[str, List[str]], variables: List[str],
- interpolate_dim: str, target_dim: str, target_var: str, station_type: str = None,
- interpolate_method: str = "linear", limit_nan_fill: int = 1, window_history_size: int = 7,
+ interpolation_dim: str, target_dim: str, target_var: str, station_type: str = None,
+ interpolation_method: str = "linear", limit_nan_fill: int = 1, window_history_size: int = 7,
window_lead_time: int = 4, transformation: Dict = None, extreme_values: num_or_list = None,
data_preparation=None, **kwargs):
"""
@@ -68,11 +68,11 @@ class DataGenerator(keras.utils.Sequence):
:param data_path: path to data
:param stations: list with all stations to include
:param variables: list with all used variables
- :param interpolate_dim: dimension along which interpolation is applied
+ :param interpolation_dim: dimension along which interpolation is applied
:param target_dim: dimension of target variable
:param target_var: name of target variable
:param station_type: TOAR station type classification (background, traffic)
- :param interpolate_method: method of interpolation
+ :param interpolation_method: method of interpolation
:param limit_nan_fill: maximum gab in data to fill by interpolation
:param window_history_size: length of the history window
:param window_lead_time: lenght of the label window
@@ -87,11 +87,11 @@ class DataGenerator(keras.utils.Sequence):
os.makedirs(self.data_path_tmp)
self.stations = helpers.to_list(stations)
self.variables = variables
- self.interpolate_dim = interpolate_dim
+ self.interpolation_dim = interpolation_dim
self.target_dim = target_dim
self.target_var = target_var
self.station_type = station_type
- self.interpolate_method = interpolate_method
+ self.interpolation_method = interpolation_method
self.limit_nan_fill = limit_nan_fill
self.window_history_size = window_history_size
self.window_lead_time = window_lead_time
@@ -104,7 +104,7 @@ class DataGenerator(keras.utils.Sequence):
"""Display all class attributes."""
return f"DataGenerator(path='{self.data_path}', stations={self.stations}, " \
f"variables={self.variables}, station_type={self.station_type}, " \
- f"interpolate_dim='{self.interpolate_dim}', target_dim='{self.target_dim}', " \
+ f"interpolation_dim='{self.interpolation_dim}', target_dim='{self.target_dim}', " \
f"target_var='{self.target_var}', **{self.kwargs})"
def __len__(self):
@@ -292,11 +292,11 @@ class DataGenerator(keras.utils.Sequence):
**self.kwargs)
if self.transformation is not None:
data.transform("datetime", **helpers.remove_items(self.transformation, "scope"))
- data.interpolate(self.interpolate_dim, method=self.interpolate_method, limit=self.limit_nan_fill)
- data.make_history_window(self.target_dim, self.window_history_size, self.interpolate_dim)
- data.make_labels(self.target_dim, self.target_var, self.interpolate_dim, self.window_lead_time)
- data.make_observation(self.target_dim, self.target_var, self.interpolate_dim)
- data.remove_nan(self.interpolate_dim)
+ data.interpolate(self.interpolation_dim, method=self.interpolation_method, limit=self.limit_nan_fill)
+ data.make_history_window(self.target_dim, self.window_history_size, self.interpolation_dim)
+ data.make_labels(self.target_dim, self.target_var, self.interpolation_dim, self.window_lead_time)
+ data.make_observation(self.target_dim, self.target_var, self.interpolation_dim)
+ data.remove_nan(self.interpolation_dim)
if self.extreme_values is not None:
kwargs = {"extremes_on_right_tail_only": self.kwargs.get("extremes_on_right_tail_only", False)}
data.multiply_extremes(self.extreme_values, **kwargs)
diff --git a/mlair/run_modules/experiment_setup.py b/mlair/run_modules/experiment_setup.py
index 54a51d42..d93b8c02 100644
--- a/mlair/run_modules/experiment_setup.py
+++ b/mlair/run_modules/experiment_setup.py
@@ -13,7 +13,7 @@ from mlair.configuration.defaults import DEFAULT_STATIONS, DEFAULT_VAR_ALL_DICT,
DEFAULT_HPC_LOGIN_LIST, DEFAULT_HPC_HOST_LIST, DEFAULT_CREATE_NEW_MODEL, DEFAULT_TRAINABLE, \
DEFAULT_FRACTION_OF_TRAINING, DEFAULT_EXTREME_VALUES, DEFAULT_EXTREMES_ON_RIGHT_TAIL_ONLY, DEFAULT_PERMUTE_DATA, \
DEFAULT_BATCH_SIZE, DEFAULT_EPOCHS, DEFAULT_TARGET_VAR, DEFAULT_TARGET_DIM, DEFAULT_WINDOW_LEAD_TIME, \
- DEFAULT_DIMENSIONS, DEFAULT_INTERPOLATE_DIM, DEFAULT_INTERPOLATE_METHOD, DEFAULT_LIMIT_NAN_FILL, \
+ DEFAULT_DIMENSIONS, DEFAULT_INTERPOLATION_DIM, DEFAULT_INTERPOLATION_METHOD, DEFAULT_LIMIT_NAN_FILL, \
DEFAULT_TRAIN_START, DEFAULT_TRAIN_END, DEFAULT_TRAIN_MIN_LENGTH, DEFAULT_VAL_START, DEFAULT_VAL_END, \
DEFAULT_VAL_MIN_LENGTH, DEFAULT_TEST_START, DEFAULT_TEST_END, DEFAULT_TEST_MIN_LENGTH, DEFAULT_TRAIN_VAL_MIN_LENGTH, \
DEFAULT_USE_ALL_STATIONS_ON_ALL_DATA_SETS, DEFAULT_EVALUATE_BOOTSTRAPS, DEFAULT_CREATE_NEW_BOOTSTRAPS, \
@@ -66,8 +66,8 @@ class ExperimentSetup(RunEnvironment):
# interpolation
self._set_param("dimensions", dimensions, default={'new_index': ['datetime', 'Stations']})
- self._set_param("interpolate_dim", interpolate_dim, default='datetime')
- self._set_param("interpolate_method", interpolate_method, default='linear')
+ self._set_param("interpolation_dim", interpolation_dim, default='datetime')
+ self._set_param("interpolation_method", interpolation_method, default='linear')
self._set_param("limit_nan_fill", limit_nan_fill, default=1)
# train set parameters
@@ -140,8 +140,8 @@ class ExperimentSetup(RunEnvironment):
:param window_lead_time: number of time steps to predict by model (default 3). Time steps `t_0+1` to `t_0+w` are
predicted.
:param dimensions:
- :param interpolate_dim:
- :param interpolate_method:
+ :param interpolation_dim:
+ :param interpolation_method:
:param limit_nan_fill:
:param train_start:
:param train_end:
@@ -220,8 +220,8 @@ class ExperimentSetup(RunEnvironment):
target_dim=None,
window_lead_time: int = None,
dimensions=None,
- interpolate_dim=None,
- interpolate_method=None,
+ interpolation_dim=None,
+ interpolation_method=None,
limit_nan_fill=None, train_start=None, train_end=None, val_start=None, val_end=None, test_start=None,
test_end=None, use_all_stations_on_all_data_sets=None, trainable: bool = None, fraction_of_train: float = None,
experiment_path=None, plot_path: str = None, forecast_path: str = None, overwrite_local_data = None, sampling: str = "daily",
@@ -306,8 +306,8 @@ class ExperimentSetup(RunEnvironment):
# interpolation
self._set_param("dimensions", dimensions, default=DEFAULT_DIMENSIONS)
- self._set_param("interpolate_dim", interpolate_dim, default=DEFAULT_INTERPOLATE_DIM)
- self._set_param("interpolate_method", interpolate_method, default=DEFAULT_INTERPOLATE_METHOD)
+ self._set_param("interpolation_dim", interpolation_dim, default=DEFAULT_INTERPOLATION_DIM)
+ self._set_param("interpolation_method", interpolation_method, default=DEFAULT_INTERPOLATION_METHOD)
self._set_param("limit_nan_fill", limit_nan_fill, default=DEFAULT_LIMIT_NAN_FILL)
# train set parameters
diff --git a/mlair/run_modules/pre_processing.py b/mlair/run_modules/pre_processing.py
index c0d53aed..243daf20 100644
--- a/mlair/run_modules/pre_processing.py
+++ b/mlair/run_modules/pre_processing.py
@@ -16,7 +16,7 @@ from mlair.configuration import path_config
from mlair.helpers.join import EmptyQueryResult
from mlair.run_modules.run_environment import RunEnvironment
-DEFAULT_ARGS_LIST = ["data_path", "stations", "variables", "interpolate_dim", "target_dim", "target_var"]
+DEFAULT_ARGS_LIST = ["data_path", "stations", "variables", "interpolation_dim", "target_dim", "target_var"]
DEFAULT_KWARGS_LIST = ["limit_nan_fill", "window_history_size", "window_lead_time", "statistics_per_var", "min_length",
"station_type", "overwrite_local_data", "start", "end", "sampling", "transformation",
"extreme_values", "extremes_on_right_tail_only", "network", "data_preparation"]
@@ -225,8 +225,8 @@ class PreProcessing(RunEnvironment):
loading time are logged in debug mode.
:param args: Dictionary with required parameters for DataGenerator class (`data_path`, `network`, `stations`,
- `variables`, `interpolate_dim`, `target_dim`, `target_var`).
- :param kwargs: positional parameters for the DataGenerator class (e.g. `start`, `interpolate_method`,
+ `variables`, `interpolation_dim`, `target_dim`, `target_var`).
+ :param kwargs: positional parameters for the DataGenerator class (e.g. `start`, `interpolation_method`,
`window_lead_time`).
:param all_stations: All stations to check.
:param name: name to display in the logging info message
diff --git a/test/test_data_handling/test_data_generator.py b/test/test_data_handling/test_data_generator.py
index cb86d174..413d25dd 100644
--- a/test/test_data_handling/test_data_generator.py
+++ b/test/test_data_handling/test_data_generator.py
@@ -80,10 +80,10 @@ class TestDataGenerator:
assert gen.stations == ['DEBW107']
assert gen.variables == ['o3', 'temp']
assert gen.station_type is None
- assert gen.interpolate_dim == 'datetime'
+ assert gen.interpolation_dim == 'datetime'
assert gen.target_dim == 'variables'
assert gen.target_var == 'o3'
- assert gen.interpolate_method == "linear"
+ assert gen.interpolation_method == "linear"
assert gen.limit_nan_fill == 1
assert gen.window_history_size == 7
assert gen.window_lead_time == 4
@@ -93,7 +93,7 @@ class TestDataGenerator:
def test_repr(self, gen):
path = os.path.join(os.path.dirname(__file__), 'data')
assert gen.__repr__().rstrip() == f"DataGenerator(path='{path}', stations=['DEBW107'], " \
- f"variables=['o3', 'temp'], station_type=None, interpolate_dim='datetime', " \
+ f"variables=['o3', 'temp'], station_type=None, interpolation_dim='datetime', " \
f"target_dim='variables', target_var='o3', **{{'start': 2010, 'end': 2014}})" \
.rstrip()
diff --git a/test/test_modules/test_experiment_setup.py b/test/test_modules/test_experiment_setup.py
index 60f0d2f9..0f1f7a0c 100644
--- a/test/test_modules/test_experiment_setup.py
+++ b/test/test_modules/test_experiment_setup.py
@@ -64,8 +64,8 @@ class TestExperimentSetup:
assert data_store.get("window_lead_time", "general") == 3
# interpolation
assert data_store.get("dimensions", "general") == {'new_index': ['datetime', 'Stations']}
- assert data_store.get("interpolate_dim", "general") == "datetime"
- assert data_store.get("interpolate_method", "general") == "linear"
+ assert data_store.get("interpolation_dim", "general") == "datetime"
+ assert data_store.get("interpolation_method", "general") == "linear"
assert data_store.get("limit_nan_fill", "general") == 1
# train parameters
assert data_store.get("start", "general.train") == "1997-01-01"
@@ -93,7 +93,7 @@ class TestExperimentSetup:
stations=['DEBY053', 'DEBW059', 'DEBW027'], network="INTERNET", station_type="background",
variables=["o3", "temp"], start="1999-01-01", end="2001-01-01", window_history_size=4,
target_var="relhum", target_dim="target", window_lead_time=10, dimensions="dim1",
- interpolate_dim="int_dim", interpolate_method="cubic", limit_nan_fill=5, train_start="2000-01-01",
+ interpolation_dim="int_dim", interpolation_method="cubic", limit_nan_fill=5, train_start="2000-01-01",
train_end="2000-01-02", val_start="2000-01-03", val_end="2000-01-04", test_start="2000-01-05",
test_end="2000-01-06", use_all_stations_on_all_data_sets=False, trainable=False,
fraction_of_train=0.5, experiment_path=experiment_path, create_new_model=True, val_min_length=20)
@@ -125,8 +125,8 @@ class TestExperimentSetup:
assert data_store.get("window_lead_time", "general") == 10
# interpolation
assert data_store.get("dimensions", "general") == "dim1"
- assert data_store.get("interpolate_dim", "general") == "int_dim"
- assert data_store.get("interpolate_method", "general") == "cubic"
+ assert data_store.get("interpolation_dim", "general") == "int_dim"
+ assert data_store.get("interpolation_method", "general") == "cubic"
assert data_store.get("limit_nan_fill", "general") == 5
# train parameters
assert data_store.get("start", "general.train") == "2000-01-01"
--
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