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Merged
uvchik merged 3 commits into from
Jan 7, 2020
Merged

Features/allow data heigts of type string #90

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29167f5
Add failing test if data heights are of type string
uvchik Dec 9, 2019
65e5781
Convert strings to integer
uvchik Dec 9, 2019
0fb61e7
Allow floats for data heights again
uvchik Dec 11, 2019
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23 changes: 23 additions & 0 deletions tests/test_modelchain.py
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Original file line number Diff line number Diff line change
Expand Up @@ -341,3 +341,26 @@ def test_modelchain_with_power_coefficient_curve_as_dict(self):
power_output_model='power_coefficient_curve')
test_mc.run_model(self.weather_df)
assert_series_equal(test_mc.power_output, power_output_exp)

def test_heigths_as_string(self):
"""Test run_model if data heights are of type string."""
test_turbine = {'hub_height': 100,
'rotor_diameter': 80,
'turbine_type': 'E-126/4200'}

# Convert data heights to str
string_weather = self.weather_df.copy()
string_weather.columns = pd.MultiIndex.from_arrays([
string_weather.columns.get_level_values(0),
string_weather.columns.get_level_values(1).astype(str)])

# Heights in the original DataFrame are of type np.int64
assert isinstance(self.weather_df.columns.get_level_values(1)[0],
np.int64)
assert isinstance(string_weather.columns.get_level_values(1)[0], str)

test_modelchain = {'power_output_model': 'power_curve',
'density_corr': True}
test_mc = mc.ModelChain(wt.WindTurbine(**test_turbine),
**test_modelchain)
test_mc.run_model(string_weather)
6 changes: 6 additions & 0 deletions windpowerlib/modelchain.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,7 @@
SPDX-License-Identifier: MIT
"""
import logging
import pandas as pd
from windpowerlib import (wind_speed, density, temperature, power_output,
tools)

Expand Down Expand Up @@ -438,6 +439,11 @@ def run_model(self, weather_df):
'wind_speed'

"""
# Convert data heights to integer. In some case they are strings.
weather_df.columns = pd.MultiIndex.from_arrays([
weather_df.columns.get_level_values(0),
weather_df.columns.get_level_values(1).astype(int)])
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@vezeli vezeli Dec 9, 2019

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Why int and not float type? In the provided example the values are integers but that shouldn't be a rule, right?

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@uvchik uvchik Dec 11, 2019

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In my opinion the inaccuracy of the model is higher than the decimal digit. Therefore I would always prefer integer.

But at them moment floats are allowed and it might be easier to allow floats than to forbid them and to explain why.

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@vezeli vezeli Dec 9, 2019

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Maybe putting in a try statement and re-raising the error? In case someone passes in 80 m that cannot be converted to a number?

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@uvchik uvchik Dec 11, 2019

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For me the error message is quite clear. It also indicates the exact value that causes the problem. For us it would be more difficult to indicate the problematic value. We could add something like "The heights should be convertible to numeric." but it in my opinion the original message is better. We could also check the array and show all problematic values but I think it is not worth it.


wind_speed_hub = self.wind_speed_hub(weather_df)
density_hub = (None if (self.power_output_model == 'power_curve' and
self.density_correction is False)
Expand Down