Specify stacklevel in calls to warnings.warn

rdtools/analysis_chains.py

@@ -358,7 +358,8 @@ def _pvwatts_norm(self, poa_global, temperature_cell):
 
  if self.gamma_pdc is None:
  warnings.warn('Temperature coefficient not passed in to TrendAnalysis'
- '. No temperature correction will be conducted.')
+ '. No temperature correction will be conducted.',
+ stacklevel=3)
  pvwatts_kws = {"poa_global": poa_global,
  "power_dc_rated": power_dc_rated,
  "temperature_cell": temperature_cell,
@@ -455,13 +456,15 @@ def _filter(self, energy_normalized, case):
  ad_hoc_filter = self.filter_params['ad_hoc_filter']
 
  if ad_hoc_filter.isnull().any():
- warnings.warn('ad_hoc_filter contains NaN values; setting to False (excluding)')
+ warnings.warn('ad_hoc_filter contains NaN values; setting to False (excluding)',
+ stacklevel=3)
  ad_hoc_filter = ad_hoc_filter.fillna(False)
 
  if not filter_components.index.equals(ad_hoc_filter.index):
  warnings.warn('ad_hoc_filter index does not match index of other filters; missing '
  'values will be set to True (kept). Align the index with the index '
- 'of the filter_components attribute to prevent this warning')
+ 'of the filter_components attribute to prevent this warning',
+ stacklevel=3)
  ad_hoc_filter = ad_hoc_filter.reindex(filter_components.index).fillna(True)
 
  filter_components['ad_hoc_filter'] = ad_hoc_filter

rdtools/availability.py

@@ -17,7 +17,7 @@
 warnings.warn(
  'The availability module is currently experimental. The API, results, '
  'and default behaviors may change in future releases (including MINOR '
- 'and PATCH releases) as the code matures.'
+ 'and PATCH releases) as the code matures.', stacklevel=2
 )
 
 
@@ -537,7 +537,7 @@ def _combine_losses(self, rollup_period='M'):
  'levels. This is unexpected and could indicate a problem with '
  'the input time series data.'
  )
- warnings.warn(msg, UserWarning)
+ warnings.warn(msg, UserWarning, stacklevel=3)
 
  self.loss_total = self.loss_system + self.loss_subsystem
 

rdtools/clearsky_temperature.py

@@ -52,7 +52,8 @@ def get_clearsky_tamb(times, latitude, longitude, window_size=40,
  if freq_actual is None:
  freq_actual = pd.infer_freq(times[:10])
  warnings.warn("Input 'times' has no frequency attribute. "
- "Inferring frequency from first 10 timestamps.")
+ "Inferring frequency from first 10 timestamps.",
+ stacklevel=2)
  else:
  freq_actual = times.freq
 
@@ -115,7 +116,8 @@ def solar_noon_offset(utc_offset):
  df['solar_noon_offset'].values)
  if df['Clear Sky Temperature (C)'].isna().any():
  warnings.warn("Clear Sky Temperature includes NaNs, "
- "possibly invalid Lat/Lon coordinates.", UserWarning)
+ "possibly invalid Lat/Lon coordinates.", UserWarning,
+ stacklevel=2)
  return df['Clear Sky Temperature (C)']
 
 

rdtools/filtering.py

@@ -157,7 +157,8 @@ def clip_filter(power_ac, model="quantile", **kwargs):
  "parameters have been interpreted as model= "
  f"'quantile_clip_filter', quantile={quantile}. "
  "This syntax will be removed in a future version.",
- rdtools._deprecation.rdtoolsDeprecationWarning)
+ rdtools._deprecation.rdtoolsDeprecationWarning,
+ stacklevel=2)
  kwargs['quantile'] = quantile
  model = 'quantile'
 
@@ -232,7 +233,8 @@ def _format_clipping_time_series(power_ac, mounting_type):
  if not has_timezone.all():
  warnings.warn("Function expects timestamps in local time. "
  "For best results pass a time-zone-localized "
- "time series localized to the correct local time zone.")
+ "time series localized to the correct local time zone.",
+ stacklevel=3)
  # Check the other input variables to ensure that they are the
  # correct format
  if (mounting_type != "single_axis_tracking") & (mounting_type != "fixed"):
@@ -285,7 +287,8 @@ def _check_data_sampling_frequency(power_ac):
  warnings.warn("Variable sampling frequency across time series. "
  "Less than 95% of the time series is sampled at the "
  "same interval. This function was not tested "
- "on variable frequency data--use at your own risk!")
+ "on variable frequency data--use at your own risk!",
+ stacklevel=3)
  return
 
 
@@ -416,7 +419,8 @@ def logic_clip_filter(power_ac,
  warnings.warn("The logic-based filter is an experimental clipping filter "
  "that is still under development. The API, results, and "
  "default behaviors may change in future releases (including "
- "MINOR and PATCH). Use at your own risk!")
+ "MINOR and PATCH). Use at your own risk!",
+ stacklevel=2)
  # Format the time series
  power_ac, index_name = _format_clipping_time_series(power_ac,
  mounting_type)
@@ -641,7 +645,8 @@ def xgboost_clip_filter(power_ac,
  warnings.warn("The XGBoost filter is an experimental clipping filter "
  "that is still under development. The API, results, and "
  "default behaviors may change in future releases (including "
- "MINOR and PATCH). Use at your own risk!")
+ "MINOR and PATCH). Use at your own risk!",
+ stacklevel=2)
  # Load in the XGBoost model
  xgboost_clipping_model = _load_xgboost_clipping_model()
  # Format the power or energy time series

rdtools/normalization.py

@@ -727,7 +727,7 @@ def _interpolate_series(time_series, target_index, max_timedelta=None,
  warnings.warn("Fraction of excluded data "
  f"({100*fraction_excluded:0.02f}%) "
  "exceeded threshold",
- UserWarning)
+ UserWarning, stacklevel=3)
 
  # put data on index that includes both original and target indicies
  target_timestamps = pd.Index(target_index.view('int64'))

rdtools/plotting.py

@@ -165,7 +165,7 @@ def soiling_monte_carlo_plot(soiling_info, normalized_yield, point_alpha=0.5,
  warnings.warn(
  'The soiling module is currently experimental. The API, results, '
  'and default behaviors may change in future releases (including MINOR '
- 'and PATCH releases) as the code matures.'
+ 'and PATCH releases) as the code matures.', stacklevel=2
  )
 
  fig, ax = plt.subplots()
@@ -225,7 +225,7 @@ def soiling_interval_plot(soiling_info, normalized_yield, point_alpha=0.5,
  warnings.warn(
  'The soiling module is currently experimental. The API, results, '
  'and default behaviors may change in future releases (including MINOR '
- 'and PATCH releases) as the code matures.'
+ 'and PATCH releases) as the code matures.', stacklevel=2
  )
 
  sratio = soiling_info['soiling_ratio_perfect_clean']
@@ -265,7 +265,7 @@ def soiling_rate_histogram(soiling_info, bins=None):
  warnings.warn(
  'The soiling module is currently experimental. The API, results, '
  'and default behaviors may change in future releases (including MINOR '
- 'and PATCH releases) as the code matures.'
+ 'and PATCH releases) as the code matures.', stacklevel=2
  )
 
  soiling_summary = soiling_info['soiling_interval_summary']
@@ -385,7 +385,7 @@ def availability_summary_plots(power_system, power_subsystem, loss_total,
  warnings.warn(
  'The availability module is currently experimental. The API, results, '
  'and default behaviors may change in future releases (including MINOR '
- 'and PATCH releases) as the code matures.'
+ 'and PATCH releases) as the code matures.', stacklevel=2
  )
 
  fig = plt.figure(figsize=(16, 8))

rdtools/soiling.py

@@ -14,7 +14,7 @@
 warnings.warn(
  'The soiling module is currently experimental. The API, results, '
  'and default behaviors may change in future releases (including MINOR '
- 'and PATCH releases) as the code matures.'
+ 'and PATCH releases) as the code matures.', stacklevel=2
 )
 
 
@@ -110,7 +110,8 @@ def _calc_daily_df(self, day_scale=13, clean_threshold='infer',
  warnings.warn('An even value of day_scale was passed. An odd value is '
  'recommended, otherwise, consecutive days may be erroneously '
  'flagged as cleaning events. '
- 'See https://github.com/NREL/rdtools/issues/189')
+ 'See https://github.com/NREL/rdtools/issues/189',
+ stacklevel=2)
 
  df = self.pm.to_frame()
  df.columns = ['pi']
@@ -369,8 +370,8 @@ def _calc_monte(self, monte, method='half_norm_clean'):
  'validity criteria such as increasing "max_relative_slope_error" '
  'and/or "max_negative_step" and/or decreasing "min_interval_length".'
  ' Alternatively, consider using method="perfect_clean". For more'
- ' info see https://github.com/NREL/rdtools/issues/272'
- )
+ ' info see https://github.com/NREL/rdtools/issues/272',
+ stacklevel=3)
  monte_losses = []
  random_profiles = []
  for _ in range(monte):
@@ -891,7 +892,8 @@ def annual_soiling_ratios(stochastic_soiling_profiles,
  'The indexes of stochastic_soiling_profiles are not entirely '
  'contained within the index of insolation_daily. Every day in '
  'stochastic_soiling_profiles should be represented in '
- 'insolation_daily. This may cause erroneous results.')
+ 'insolation_daily. This may cause erroneous results.',
+ stacklevel=2)
 
  insolation_daily = insolation_daily.reindex(all_profiles.index)