RdTools Change Log

v2.1.8 (November 17, 2023)

Bug fixes

• Fix a bug in parallel computing environments (GH #388 GH #399)

Contributors

• Martin Springer (@martin-springer)

v2.1.7 (November 3, 2023)

Requirements

• Limit pandas version to <2.1 (GH #395)

• Several packages updated in``requirements.txt`` and docs/notebook_requirements.txt (GH #398)

Documentation

• Update ReadTheDocs configuration (GH #395)

Contributors

• Michael Deceglie (@mdeceglie)

• Kevin Anderson (@kandersolar)

v2.1.6 (July 31, 2023)

Bug Fixes

• Fix NonExistentTimeError in rdtools.clearsky_temperature.get_clearsky_tamb() (GH #372 GH #373)

Enhancements

• rdtools.degradation.degradation_classical_decomposition() now executes significantly faster. (GH #371)

Requirements

• Increased the minimum versions of several dependencies: (GH #371)

  • pandas increased to 1.3.0 (released July 2, 2021)

  • numpy to 1.17.3 (released October 17, 2019)

  • statsmodels to 0.11.0 (released February 21, 2020)

  • scipy to 1.2.0 (released December 17, 2018)

• Add support for pvlib 0.10 (GH #378)

• Updated notebook requirements (GH #360)

• Bumps certifi from 2020.12.5 to 2022.12.7 (GH #357)

Testing

• Extended pip timeout (GH #360)

• Updated example notebooks with new figure sizes (GH #360)

Contributors

• Michael Deceglie (@mdeceglie)

• Bernat Nicolau (@BernatNicolau)

• Kevin Anderson (@kandersolar)

v2.1.5 (May 16, 2023)

Bug Fixes

• Add support for pandas 2.0 (GH #361, GH #362)

Contributors

• Kevin Anderson (@kanderso-nrel)

• Michael Deceglie (@mdeceglie)

v2.1.4 (December 1, 2022)

Bug Fixes

• degradation_year_on_year() no longer raises an error for inputs exactly two years long (GH #339)

• soiling_interval_plot() no longer ignores the optional point_color, profile_color, point_alpha, and profile_alpha parameters. (GH #343, GH #345)

Testing

• Added a CI notebook check (GH #270)

Requirements

• Upgrade the notebook environment from python 3.7 to python 3.10. Several dependency versions in docs/notebook_requirements.txt are updated as well. (GH #319, GH #326)

• Bump ipython==7.16.3, jupyter-console==6.4.0, and prompt-toolkit==3.0.27 in docs/notebook_requirements.txt and bump Pillow==9.3.0 in requirements.txt (GH #314, GH #349)

• Bump jupyter-core==4.11.2 in docs\notebook_requirements.txt (GH #350)

• Bump sphinx version from 3.2 to 4.5 and nbsphinx version from 0.8.5 to 0.8.8 in the optional [doc] requirements (GH #317, GH #325)

• A number of other requirements updates (GH #337)

Contributors

• Sandra Villamar (@SandraVillamar)

• Michael Deceglie (@mdeceglie)

• Chris Deline (@cdeline)

• Kevin Anderson (@kanderso-nrel)

v2.1.3 (January 6, 2022)

Bug fixes

• Fixed a plotting issue in rdtools.plotting.availability_summary_plots() with newer matplotlib versions, as well as an axis labeling error (GH #302)

Requirements

• Added support for python 3.10 and dropped support for python 3.6 (which reached end of life on Dec 23, 2021) (GH #302)

• Bumped several minimum package versions (GH #302):

  • h5py increased to 2.8.0 (released June 4, 2018)

  • pandas increased to 0.23.2 (released July 6, 2018)

  • scipy increased to 1.1.0 (released May 5, 2018)

  • statsmodels increased to 0.9.0 (released May 14, 2018)

• Update pinned versions of several dependencies in requirements.txt (GH #302)

Testing

• Drop python 3.6 and add 3.10 to the CI configuration (GH #302)

• Add new assert_warnings helper function to conftest.py (GH #302)

v2.1.2 (December 22, 2021)

Bug fixes

• XGBoost model saved in a version-stable json. Removes the xgboost version restriction of version 2.1.1. (GH #301, GH #304)

Requirements

• joblib removed as requirement (GH #304)

• XGBoost version in requirements.txt updated to 1.5.1 (GH #304)

Documentation

• Preferred citation updated (GH #296, GH #300)

v2.1.1 (November 30, 2021)

This patch release temporarily requires xgboost < 1.5.0. A future update will allow a wider version range. (GH #301, GH #297)

v2.1.0 (September 17, 2021)

API Changes

• The calculations internal to the soiling SRR algorithm have changed such that consecutive cleaning events are no longer removed. (GH #199, GH #189)

• The calculations internal to the soiling SRR algorithm have changed such that "invalid" intervals are retained at the beginning and end of the dataset for the purposes of the SRR Monte Carlo. Invalid intervals are those that do not qualify to be fit as soiling intervals based on min_interval_length, max_relative_slope_error, and max_negative_step. (GH #199, GH #272)

• The default day_scale parameter in soiling functions and methods was changed from 14 to 13. A recommendation to use an odd value along with a warning for even values was also added. (GH #199, GH #189)

• The default min_interval_length in soiling functions and methods was changed from 2 to 7. (GH #199)

Enhancements

• New object oriented end-to-end analysis API introduced with the TrendAnalysis class. Note the behavior has been adjusted since its original introduction in v2.1.0-beta.0. (GH #117, GH #232, GH #233, GH #263, GH #278, GH #285, GH #281)

• Add sensor_filter_components and clearsky_filter_components to TrendAnalysis (GH #236, GH #263)

• A new parameter outlier_factor was added to soiling functions and methods to enable better control of cleaning event detection. (GH #199)

• Boolean input kwarg detailed has been added to degradation_summary_plots to color-code degradation plots by the number of times data points are used in the degradation distribution. (GH #269, GH #282)

• degradation_year_on_year adds a new usage_of_points entry in the calc_info return dictionary. (GH #269, GH #282)

• clip_filter() updated to allow for different methods of clipping detection with the model parameter (GH #200)

• Add new function quantile_clip_filter() (GH #200).

• Add new function logic_clip_filter() (GH #200).

• Add new function xgboost_clip_filter() (GH #200).

• Add new function tune_filter_plot() (GH #200).

Bug fixes

• Unexpected recoveries when using method=random_clean in the soiling module have been fixed. (GH #199, GH #234)

• Improved NaN pixel handling in get_clearsky_tamb() (GH #274).

Documentation

• Corrected a typo in the TrendAnalysis docstring (GH #264)

• Enabled intersphinx so that function parameter types are linked to external documentation (GH #258)

Requirements

• Installation (setup.py) now requires plotly, joblib, xgboost, and scikit-learn

• Update pinned versions of several dependencies in requirements.txt and docs/notebook_requirements.txt (GH #289, GH #295)

• Add support for pvlib 0.9 and remove the tables dependency added in v2.1.0b0 (GH #290)

Example Updates

• TrendAnalysis_example_pvdaq4.ipynb added

• degradation_and_soiling_example_pvdaq_4.ipynb updated to use the same artificial soiling signal imposed in new notebook TrendAnalysis_example_pvdaq4.ipynb throughout the analysis.

• degradation_and_soiling_example_pvdaq_4.ipynb updated to illustrate new clipping models and filter-tuning plots.

Contributors

• Mark Mikofski (@mikofski)

• Kevin Anderson (@kanderso-nrel)

• Michael Deceglie (@mdeceglie)

• Matthew Muller (@matt14muller)

• Kirsten Perry (@kperrynrel)

• Chris Deline (@cdeline)

v2.0.6 (July 16, 2021)

Bug Fixes

• Fix a failure of get_clearsky_tamb() with pandas 1.3.0 (GH #284)

• Change internal casting of timestamps into integers to use .view() instead of pandas deprecated .astype() method (GH #284)

Requirements

• Update specified versions of bleach in docs/notebook_requirements.txt and matplotlib in requirements.txt (GH #261)

Contributors

• Kevin Anderson (@kanderso-nrel)

• Michael Deceglie (@mdeceglie)

v2.0.5 (2020-12-30) and v2.1.0-beta.2 (2021-01-29)

Testing

• Add a flake8 code style check to the continuous integration checks (GH #231)

• Moved several pytest fixtures from soiling_test.py and availability_test.py to conftest.py so that they are shared across test files (GH #231)

• Add Python 3.9 to CI testing (GH #249)

• Fix test suite error raised when using pandas 1.2.0 (GH #251)

Documentation

• Organized example notebooks into a sphinx gallery (GH #240)

Requirements

• Add support for python 3.9 (GH #249)

• Update requirements.txt versions for numpy, scipy, pandas, h5py and statsmodels to versions that have wheels available for python 3.6-3.9. Note that the minimum versions are unchanged. (GH #249).

Contributors

• Kevin Anderson (@kanderso-nrel)

• Michael Deceglie (@mdeceglie)

• Chris Deline (@cdeline)

v2.0.4 and v2.1.0-beta.1 (December 4, 2020)

Bug Fixes

• Fix bug related to leading NaN values with energy_from_power(). This fixed a small normalization error in degradation_and_soiling_example.ipynb and slightly changed the clear-sky degradation results (GH #244, GH #245)

Contributors

• Kevin Anderson (@kanderso-nrel)

v2.1.0-beta.0 (November 20, 2020)

Enhancements

• Add new analysis_chains module to focus on objected-oriented analysis workflows combining other RdTools modules. Includes TrendAnalysis class for sensor- and clear-sky-based soiling and degradation analyses (GH #117).

Requirements

• tables added as a requirement (GH #196).

Example Updates

• New example notebook based on PVDAQ system #4 for the new TrendAnalysis analysis work flow (GH #196 and GH #117).

• Update degradation_and_soiling_example_pvdaq_4.ipynb example to match best practice, including pvlib.get_total_irradiance() in rdtools.interpolate (GH #196 and GH #117).

• Update degradation_and_soiling_example_pvdaq_4.ipynb example to use a single soiling * ac_power signal (GH #196).

Contributors

• Mike Deceglie (@mdeceglie)

• Kevin Anderson (@kanderso-nrel)

• Chris Deline (@cdeline)

v2.0.3 (November 20, 2020)

Requirements

• Change to docs/notebook_requirements.txt: notebook version from 5.7.8 to 6.1.5 and terminado version from 0.8.1 to 0.8.3 (GH #239)

Contributors

• Mike Deceglie (@mdeceglie)

• @dependabot

v2.0.2 (November 17, 2020)

Examples

• degradation_and_soiling_example.ipynb modified to not use max_timedelta parameter in interpolate() and energy_from_power() in Step 0 (GH #237)

Contributors

• Mike Deceglie (@mdeceglie)

v2.0.1 (October 30, 2020)

Deprecations

• The deprecation of pvwatts_dc_power() and normalize_with_pvwatts() has been reversed. (GH #227)

Contributors

• Mike Deceglie (@mdeceglie)

• Kevin Anderson (@kanderso-nrel)

v2.0.0 (October 20, 2020)

Version 2.0.0 adds experimental soiling and availability modules, plotting capability, and includes updates to normalization work flow. This major release introduces some breaking changes to the API. Details below.

API Changes

• The calculations internal to normalize_with_pvwatts() and normalize_with_sapm() have changed. Generally, when working with raw power data it should be converted to right-labeled energy with energy_from_power() before being used with these normalization functions (GH #105, GH #108).

• Remove low_power_cutoff parameter in clip_filter() (GH #84).

• Many kwargs have changed name (but not input order) to bring nomenclature into closer alignment with the DuraMAT pv-terms project: (GH #185)

  • aggregation_insol() first kwarg is now energy_normalized.

  • degradation_year_on_year(), degradation_ols() and degradation_classical_decomposition() first kwarg is now energy_normalized.

  • normalized_filter() input kwargs are now energy_normalized, energy_normalized_low and energy_normalized_high.

  • poa_filter() input kwargs are now poa_global, poa_global_low and poa_global_high.

  • tcell_filter() input kwargs are now temperature_cell, temperature_cell_low and temperature_cell_high.

  • clip_filter() input kwargs are now power_ac and quantile.

  • csi_filter() first two kwargs are now poa_global_measured, poa_global_clearsky.

  • normalize_with_pvwatts() pvwatts_kws dictionary keys have been renamed.

  • pvwatts_dc_power() input kwargs are now poa_global, power_dc_rated, temperature_cell, poa_global_ref, temperature_cell_ref, gamma_pdc.

  • irradiance_rescale() second kwarg is now irrad_sim

Deprecations

• The functions pvwatts_dc_power(), sapm_dc_power(), normalize_with_pvwatts(), and normalize_with_sapm() have been deprecated in favor of normalize_with_expected_power(). (GH #215)

• delta_index() and check_series_frequency() (GH #222)

Enhancements

• Add new soiling module to implement the stochastic rate and recovery method:

  • Create new class SRRAnalysis and helper function soiling_srr() (GH #112, GH #168, GH #169, GH #176, GH #208, GH #213)

  • Create functions monthly_soiling_rates() and annual_soiling_ratios() (GH #193, GH #207)

• Create new module availability with the class AvailabilityAnalysis for estimating timeseries system availability (GH #131)

• Add new function normalize_with_expected_power() (GH #173).

• Add new functions energy_from_power() and interpolate() (GH #105, GH #108, GH #182, GH #212).

• Add new function normalized_filter() (GH #139)

• Add new plotting module for generating standard plots (GH #138, GH #131)

• Add parameter convergence_threshold to irradiance_rescale() (GH #152).

Bug fixes

• Allow max_iterations=0 in irradiance_rescale() (GH #152).

Testing

• Add Python 3.7 and 3.8 to CI testing (GH #135).

• Add CI configuration based on the minimum dependency versions (GH #197)

Documentation

• Create sphinx documentation and set up ReadTheDocs (GH #125).

• Add guides on running tests and building sphinx docs (GH #136).

• Improve module-level docstrings (GH #137).

• Update landing page and add new "Inverter Downtime" documentation page based on the availability notebook (GH #131)

Requirements

• Drop support for Python 2.7, minimum supported version is now 3.6 (GH #135).

• Increase minimum pvlib version to 0.7.0 (GH #170)

• Update requirements.txt and notebook_requirements.txt to avoid conflicting specifications. Taken together, they represent the complete environment for the notebook example (GH #164).

• Add minimum matplotlib requirement of 3.0.0 (released September 18, 2018) (GH #197)

• Increase minimum numpy version from 1.12 (released January 15, 2017) to 1.15 (released July 23, 2018) (GH #197)

Example Updates

• Seed numpy.random to ensure repeatable results (GH #164).

• Use normalized_filter() instead of manually filtering the normalized energy timeseries. Also updated the associated mask variable names (GH #139).

• Add soiling section to the original example notebook.

• Add a new example notebook that analyzes data from a PV system located at NREL's South Table Mountain campus (PVDAQ system #4) (GH #171).

• Explicitly register pandas datetime converters which were deprecated.

• Add new system_availability_example.ipynb notebook (GH #131)

Contributors

• Mike Deceglie (@mdeceglie)

• Kevin Anderson (@kanderso-nrel)

• Chris Deline (@cdeline)

• Will Vining (@wfvining)

v1.2.3 (April 12, 2020)

• Updates dependencies

• Versioneer bug fix

• Licence update

Contributors

• Mike Deceglie (@mdeceglie)

v1.2.2 (October 12, 2018)

Patch that adds author email to enable pypi deployment

Contributors

• Mike Deceglie (@mdeceglie)

v1.2.1 (October 12, 2018)

This update includes automated testing and deployment to support development along with some bug fixes to the library itself, a documented environment for the example notebook, and new example results to reflect changes in the example dataset. It addresses GH #49, GH #76, GH #78, GH #79, GH #80, GH #85, GH #86, and GH #92.

Contributors

• Mike Deceglie (@mdeceglie)

• Adam Shinn (@abshinn)

• Chris Deline (@cdeline)

• nb137 (@nb137)

v1.2.0 (March 30, 2018)

This incorporates changes including:

• Enables users to control confidence intervals reported in degradation calculations (GH #59)

• Adds python 3 support (GH #56 and GH #67)

• Fixes bugs (GH #61 GH #57)

• Improvements/typo fixes to docstrings

• Fixes error in check for two years of data in degradation_year_on_year

• Improves the calculations underlying irradiance_rescale

Contributors

• Mike Deceglie (@mdeceglie)

• Ambarish Nag (@ambarishnag)

• Gregory Kimball (@GregoryKimball)

• Chris Deline (@cdeline)

• Mark Mikofski (@mikofski)

v1.1.3 (December 6, 2017)

This patch includes the following changes:

1. Update the notebook for improved plotting with Pandas v.0.21.0

2. Fix installation bug related to package data

Contributors

• Mike Deceglie (@mdeceglie)

• Chris Deline (@cdeline)

v1.1.2 (November 6, 2017)

This patch includes the following changes:

1. Fix bugs in installation

2. Update requirements

3. Notebook plots made compatible with pandas v.0.21.0

Contributors

• Mike Deceglie (@mdeceglie)

v1.1.1 (November 1, 2017)

This patch:

1. Improves documentation

2. Fixes installation requirements

Contributors

• Mike Deceglie (@mdeceglie)

• Adam Shinn (@abshinn)

• Chris Deline (@cdeline)

v1.1.0 (September 30, 2017)

This update includes the addition of filters, functions to support a clear-sky workflow, and updates to the example notebook.

Contributors

• Mike Deceglie (@mdeceglie)

• Adam Shinn (@abshinn)

• Ambarish Nag (@ambarishnag)

• Gregory Kimball (@GregoryKimball)

• Chris Deline (@cdeline)

• Jiyang Yan (@yjy1663)