Added dynamic function parameter to get_profiles function #21
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Dynamic_function_h0 is an optional parameter. Default = True Fixed minor typos
p-snft
reviewed
Jun 29, 2020
| ann_el_demand_per_sector), axis=1).dropna(how='all', axis=1) * 4 | ||
| if dyn_function_h0 == True: | ||
| quartersinyear = len(self.slp_frame) | ||
| for quarter in range(quartersinyear): |
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This way of doing it is rather inefficient. You should rather calculate an array of all smoothing factors and multiply the SLP by that. The following might work (did not verify):
day_of_year = [(quarter + 1) / (24 * 4) for quarter in range(len(self.slp_frame))]
smoothing_factor = [-3.916649251 * 10 ** -10
* timestep ** 4 + 3.2 * 10 ** -7
* timestep ** 3 - 7.02 * 10 ** -5
* timestep ** 2 + 0.0021
* timestep + 1.24 for timestep in day_of_year]
self.slp_frame['h0'][quarter] = self.slp_frame['h0'] * smoothing_factor(Or - preferably - using numpy.)
p-snft
reviewed
Jun 29, 2020
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Dynamic_function_h0 is an optional parameter. Default = True
Fixed minor typos
Closes #17