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Rerun examples; small fixes.
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misi9170 committed Apr 10, 2024
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Showing 15 changed files with 3,691 additions and 3,780 deletions.
528 changes: 180 additions & 348 deletions examples_artificial_data/01_raw_data_processing/00_filter_ws_power_curves.ipynb
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3,966 changes: 1,980 additions & 1,986 deletions examples_artificial_data/01_raw_data_processing/01_northing_calibration.ipynb
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16 changes: 8 additions & 8 deletions examples_artificial_data/03_energy_ratio/00_demo_energy_ratio_syntax.ipynb
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152 changes: 81 additions & 71 deletions examples_artificial_data/03_energy_ratio/01_demo_energy_ratio_options.ipynb
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340 changes: 170 additions & 170 deletions examples_artificial_data/04_floris_tuning/00_tune_floris_to_artificial_data.ipynb
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12 changes: 6 additions & 6 deletions examples_smarteole/00_inspect_floris_model.ipynb
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80 changes: 64 additions & 16 deletions examples_smarteole/01_precalculate_floris_solutions.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -46,22 +46,70 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Precalculating FLORIS table for 'jensen' model...\n",
"Generating a df_approx table of FLORIS solutions covering a total of 18150 cases.\n",
"Finished calculating the FLORIS solutions for the dataframe.\n",
"Computation time: 3.92 s\n",
"Precalculating FLORIS table for 'turbopark' model...\n",
"Generating a df_approx table of FLORIS solutions covering a total of 18150 cases.\n",
"Finished calculating the FLORIS solutions for the dataframe.\n",
"Computation time: 6.61 s\n",
"Precalculating FLORIS table for 'gch' model...\n",
"Generating a df_approx table of FLORIS solutions covering a total of 18150 cases.\n",
"Finished calculating the FLORIS solutions for the dataframe.\n",
"Computation time: 5.15 s\n",
"Precalculating FLORIS table for 'cc' model...\n",
"Generating a df_approx table of FLORIS solutions covering a total of 18150 cases.\n",
"Finished calculating the FLORIS solutions for the dataframe.\n",
"Computation time: 6.29 s\n"
"Precalculating FLORIS table for 'jensen' model...\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[32m2024-04-09 18:41:38\u001b[0m Generating a df_approx table of FLORIS solutions covering a total of 18150 cases.\n",
"\u001b[32m2024-04-09 18:41:42\u001b[0m Finished calculating the FLORIS solutions for the dataframe.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Computation time: 4.76 s\n",
"Precalculating FLORIS table for 'turbopark' model...\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[32m2024-04-09 18:41:43\u001b[0m Generating a df_approx table of FLORIS solutions covering a total of 18150 cases.\n",
"\u001b[32m2024-04-09 18:41:50\u001b[0m Finished calculating the FLORIS solutions for the dataframe.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Computation time: 7.85 s\n",
"Precalculating FLORIS table for 'gch' model...\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[32m2024-04-09 18:41:50\u001b[0m Generating a df_approx table of FLORIS solutions covering a total of 18150 cases.\n",
"\u001b[32m2024-04-09 18:41:55\u001b[0m Finished calculating the FLORIS solutions for the dataframe.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Computation time: 5.91 s\n",
"Precalculating FLORIS table for 'cc' model...\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[32m2024-04-09 18:41:56\u001b[0m Generating a df_approx table of FLORIS solutions covering a total of 18150 cases.\n",
"\u001b[32m2024-04-09 18:42:03\u001b[0m Finished calculating the FLORIS solutions for the dataframe.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Computation time: 7.31 s\n"
]
}
],
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128 changes: 70 additions & 58 deletions examples_smarteole/02_download_and_format_dataset.ipynb
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Expand Up @@ -49,8 +49,8 @@
"name": "stdout",
"output_type": "stream",
"text": [
"SMARTEOLE data found locally.\n",
"SMARTEOLE data already extracted locally.\n",
"SMARTEOLE data not found locally. Beginning file download from Zenodo...\n",
"Extracting SMARTEOLE zip file\n",
"\n",
"List of SMARTEOLE files:\n",
"SMARTEOLE_WakeSteering_NTF_SMV6_staticData.csv\n",
Expand Down Expand Up @@ -475,62 +475,74 @@
"control_log_offset_active_max\n",
"control_log_offset_active_std\n",
"control_log_offset_active_count\n",
"formatting dataframe...\n",
"Datatype 'datetime64[ns]' not recognized. Not downsampling.\n",
"Column pow_000 ['float64'] was downsampled to float32.\n",
"Max error: 0.00012109374983992893\n",
"Column pow_001 ['float64'] was downsampled to float32.\n",
"Max error: 0.00012109374983992893\n",
"Column pow_002 ['float64'] was downsampled to float32.\n",
"Max error: 0.00011328124992360245\n",
"Column pow_003 ['float64'] was downsampled to float32.\n",
"Max error: 0.00012109374983992893\n",
"Column pow_004 ['float64'] was downsampled to float32.\n",
"Max error: 0.00012109374983992893\n",
"Column pow_005 ['float64'] was downsampled to float32.\n",
"Max error: 0.00012109374983992893\n",
"Column pow_006 ['float64'] was downsampled to float32.\n",
"Max error: 0.00012109374983992893\n",
"Column ws_000 ['float64'] was downsampled to float32.\n",
"Max error: 9.460449206244448e-07\n",
"Column ws_001 ['float64'] was downsampled to float32.\n",
"Max error: 9.460449206244448e-07\n",
"Column ws_002 ['float64'] was downsampled to float32.\n",
"Max error: 9.460449206244448e-07\n",
"Column ws_003 ['float64'] was downsampled to float32.\n",
"Max error: 9.460449206244448e-07\n",
"Column ws_004 ['float64'] was downsampled to float32.\n",
"Max error: 9.460449206244448e-07\n",
"Column ws_005 ['float64'] was downsampled to float32.\n",
"Max error: 9.460449206244448e-07\n",
"Column ws_006 ['float64'] was downsampled to float32.\n",
"Max error: 9.460449206244448e-07\n",
"Column wd_000 ['float64'] was downsampled to float32.\n",
"Max error: 1.5136718729991117e-05\n",
"Column wd_001 ['float64'] was downsampled to float32.\n",
"Max error: 1.5136718729991117e-05\n",
"Column wd_002 ['float64'] was downsampled to float32.\n",
"Max error: 1.5136718729991117e-05\n",
"Column wd_003 ['float64'] was downsampled to float32.\n",
"Max error: 1.5136718729991117e-05\n",
"Column wd_004 ['float64'] was downsampled to float32.\n",
"Max error: 1.5136718729991117e-05\n",
"Column wd_005 ['float64'] was downsampled to float32.\n",
"Max error: 1.5136718729991117e-05\n",
"Column wd_006 ['float64'] was downsampled to float32.\n",
"Max error: 1.5136718729991117e-05\n",
"Datatype 'bool' not recognized. Not downsampling.\n",
"Datatype 'bool' not recognized. Not downsampling.\n",
"Datatype 'bool' not recognized. Not downsampling.\n",
"Datatype 'bool' not recognized. Not downsampling.\n",
"Datatype 'bool' not recognized. Not downsampling.\n",
"Datatype 'bool' not recognized. Not downsampling.\n",
"Datatype 'bool' not recognized. Not downsampling.\n",
"Column wind_vane_005 ['float64'] was downsampled to float32.\n",
"Max error: 7.568359364995558e-06\n",
"Column target_yaw_offset_005 ['float64'] was downsampled to float32.\n",
"Max error: 9.460449206244448e-07\n",
"Datatype 'object' not recognized. Not downsampling.\n",
"formatting dataframe...\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[32m2024-04-09 18:43:13\u001b[0m Datatype 'datetime64[ns]' not recognized. Not downsampling.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column pow_000 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 0.00012109374983992893\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column pow_001 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 0.00012109374983992893\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column pow_002 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 0.00011328124992360245\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column pow_003 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 0.00012109374983992893\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column pow_004 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 0.00012109374983992893\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column pow_005 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 0.00012109374983992893\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column pow_006 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 0.00012109374983992893\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column ws_000 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 9.460449206244448e-07\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column ws_001 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 9.460449206244448e-07\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column ws_002 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 9.460449206244448e-07\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column ws_003 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 9.460449206244448e-07\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column ws_004 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 9.460449206244448e-07\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column ws_005 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 9.460449206244448e-07\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column ws_006 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 9.460449206244448e-07\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column wd_000 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 1.5136718729991117e-05\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column wd_001 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 1.5136718729991117e-05\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column wd_002 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 1.5136718729991117e-05\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column wd_003 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 1.5136718729991117e-05\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column wd_004 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 1.5136718729991117e-05\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column wd_005 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 1.5136718729991117e-05\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column wd_006 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 1.5136718729991117e-05\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Datatype 'bool' not recognized. Not downsampling.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Datatype 'bool' not recognized. Not downsampling.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Datatype 'bool' not recognized. Not downsampling.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Datatype 'bool' not recognized. Not downsampling.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Datatype 'bool' not recognized. Not downsampling.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Datatype 'bool' not recognized. Not downsampling.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Datatype 'bool' not recognized. Not downsampling.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column wind_vane_005 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 7.568359364995558e-06\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Column target_yaw_offset_005 ['float64'] was downsampled to float32.\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Max error: 9.460449206244448e-07\n",
"\u001b[32m2024-04-09 18:43:13\u001b[0m Datatype 'object' not recognized. Not downsampling.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Columns available in df_scada_formatted:\n",
"time\n",
Expand Down
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