This commit is contained in:
Brantegger Georg
2022-06-13 07:18:44 +02:00
3 changed files with 52 additions and 0 deletions

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import numpy as np
def Volume_trend(influx,outflux,timestep=1,V_0=0):
'''
Returns the trend and the volume and the final volume, defined
by influx and outflux patterns. The optional parameter timestep
defines the time increment over which the fluxes are changing.
'''
net_flux = influx-outflux
delta_V = net_flux*timestep
V_trend = V_0+np.cumsum(delta_V)
V_end = V_trend[-1]
return V_end, V_trend
def Height_trend(V_trend,area=1,h_crit_low=-np.inf,h_crit_high=np.inf):
'''
Returns the trend and the height and the final height, defined
by influx and outflux patterns as well as the crosssection area.
The optional parameters h_crit_low/high indicate limits that the height
should never exceed. If this occures, TRUE is returned in the corresponding
h_crit_flag.
'''
h_trend = V_trend/area
h_crit_flag_low = np.any(h_trend <= h_crit_low)
h_crit_flag_high = np.any(h_trend >= h_crit_high)
h_end = h_trend[-1]
return h_trend,h_end,h_crit_flag_low,h_crit_flag_high
## testing
if __name__ == "__main__":
influx = np.full([1,100], 6)
outflux = np.full_like(influx, 4)
V_end, V_trend = Volume_trend(influx, outflux,timestep=0.5,V_0 = 100)
print(V_end)
print(V_trend)

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import numpy as np
def simple_time_delay(delta_p_profile,delay,timestep):
rounded_delay = timestep * np.round(delay/timestep)
print('Delay was rounded to ', rounded_delay)
n_pad = int(rounded_delay/timestep)
output_delta_p_profile = np.pad(delta_p_profile[0:-n_pad],[n_pad,0],constant_values=0)
return output_delta_p_profile
## testing
if __name__ == "__main__":
delta_p_profile = np.ones([100])
delay = 4
timestep = 0.2
print(simple_time_delay(delta_p_profile, delay, timestep))

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