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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def calc_actualrelease_v1(self):
 """Calculate the actual water release that can be supplied by the dam considering the targeted release and the given water level. Required control parameter: |WaterLevelMinimumThreshold| Required derived parameters: |WaterLevelMinimumSmoothPar| Required flux sequence: |TargetedRelease| Required aide sequence: |WaterLevel| Calculated flux sequence: |ActualRelease| Basic equation: :math:`ActualRelease = TargetedRelease \\cdot smooth_{logistic1}(WaterLevelMinimumThreshold-WaterLevel, WaterLevelMinimumSmoothPar)` Used auxiliary method: |smooth_logistic1| Examples: Prepare the dam model: Assume the required release has previously been estimated to be 2 m³/s: Prepare a test function, that calculates the targeted water release for water levels ranging between -1 and 5 m: .. _dam_calc_actualrelease_v1_ex01: **Example 1** Firstly, we define a sharp minimum water level of 0 m: The following test results show that the water releae is reduced to 0 m³/s for water levels (even slightly) lower than 0 m and is identical with the required value of 2 m³/s (even slighlty) above 0 m: | ex. | waterlevel | actualrelease | | 1 | -1.0 | 0.0 | | 2 | 0.0 | 1.0 | | 3 | 1.0 | 2.0 | | 4 | 2.0 | 2.0 | | 5 | 3.0 | 2.0 | | 6 | 4.0 | 2.0 | | 7 | 5.0 | 2.0 | One may have noted that in the above example the calculated water release is 1 m³/s (which is exactly the half of the targeted release) at a water level of 1 m. This looks suspiciously lake a flaw but is not of any importance considering the fact, that numerical integration algorithms will approximate the analytical solution of a complete emptying of a dam emtying (which is a water level of 0 m), only with a certain accuracy. .. _dam_calc_actualrelease_v1_ex02: **Example 2** Nonetheless, it can (besides some other possible advantages) dramatically increase the speed of numerical integration algorithms to define a smooth transition area instead of sharp threshold value, like in the following example: Now, 98 % of the variation of the total range from 0 m³/s to 2 m³/s occurs between a water level of 3 m and 5 m: | ex. | waterlevel | actualrelease | | 1 | -1.0 | 0.0 | | 2 | 0.0 | 0.0 | | 3 | 1.0 | 0.000002 | | 4 | 2.0 | 0.000204 | | 5 | 3.0 | 0.02 | | 6 | 4.0 | 1.0 | | 7 | 5.0 | 1.98 | .. _dam_calc_actualrelease_v1_ex03: **Example 3** Note that it is possible to set both parameters in a manner that might result in negative water stages beyond numerical inaccuracy: Here, the actual water release is 0.18 m³/s for a water level of 0 m. Hence water stages in the range of 0 m to -1 m or even -2 m might occur during the simulation of long drought events: | ex. | waterlevel | actualrelease | | 1 | -1.0 | 0.02 | | 2 | 0.0 | 0.18265 | | 3 | 1.0 | 1.0 | | 4 | 2.0 | 1.81735 | | 5 | 3.0 | 1.98 | | 6 | 4.0 | 1.997972 | | 7 | 5.0 | 1.999796 | """

    con = self.parameters.control.fastaccess
    der = self.parameters.derived.fastaccess
    flu = self.sequences.fluxes.fastaccess
    aid = self.sequences.aides.fastaccess
    flu.actualrelease = (flu.targetedrelease *
                         smoothutils.smooth_logistic1(
                             aid.waterlevel-con.waterlevelminimumthreshold,
                             der.waterlevelminimumsmoothpar))