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ACS
P
Public
VILLASframework
Data Processing
Commits
3b7427a1
Commit
3b7427a1
authored
Feb 14, 2019
by
Markus Mirz
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updated timeseries functions
parent
3c55c530
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1 changed file
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81 additions
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83 deletions
+81
-83
villas/dataprocessing/timeseries.py
villas/dataprocessing/timeseries.py
+81
-83
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villas/dataprocessing/timeseries.py
View file @
3b7427a1
...
...
@@ -3,7 +3,7 @@ import cmath
class
TimeSeries
:
"""Stores data from different simulation sources.
A TimeSeries object always consists of timestamps and datapoints.
A TimeSeries object always consists of timestamps and datapoints.
"""
def
__init__
(
self
,
name
,
time
,
values
,
label
=
""
):
self
.
time
=
np
.
array
(
time
)
...
...
@@ -11,43 +11,108 @@ class TimeSeries:
self
.
name
=
name
self
.
label
=
name
def
scale
(
self
,
name
,
factor
):
def
scale
(
self
,
factor
):
"""Returns scaled timeseries.
Assumes the same time steps for both timeseries.
"""
ts_scaled
=
TimeSeries
(
name
,
self
.
time
,
self
.
values
*
factor
)
ts_scaled
=
TimeSeries
(
self
.
name
+
'_scl'
,
self
.
time
,
self
.
values
*
factor
)
return
ts_scaled
def
abs
(
self
,
name
):
def
abs
(
self
):
""" Calculate absolute value of complex time series.
"""
abs_values
=
[]
for
value
in
self
.
values
:
abs_values
.
append
(
np
.
abs
(
value
))
ts_abs
=
TimeSeries
(
name
,
self
.
time
,
abs_values
)
ts_abs
=
TimeSeries
(
self
.
name
+
'_abs'
,
self
.
time
,
abs_values
)
return
ts_abs
def
phase
(
self
,
name
):
""" Calculate
absolute valu
e of complex time series.
def
phase
(
self
):
""" Calculate
phas
e of complex time series.
"""
phase_values
=
[]
for
value
in
self
.
values
:
phase_values
.
append
(
np
.
angle
(
value
,
deg
=
True
))
ts_abs
=
TimeSeries
(
name
,
self
.
time
,
phase_values
)
ts_phase
=
TimeSeries
(
name
,
self
.
time
,
phase_values
)
ts_phase
=
TimeSeries
(
self
.
name
+
'_phase'
,
self
.
time
,
phase_values
)
return
ts_phase
def
phasor
(
self
,
name
):
"""Calculate phasor of complex time series and return dict with abs and phase.
def
phasor
(
self
):
"""Calculate phasors of complex time series
and return dict with absolute value and phase.
"""
ts_abs
=
self
.
abs
(
self
.
name
+
'_abs'
)
ts_phase
=
self
.
phase
(
self
.
name
+
'_phase'
)
ts_abs
=
self
.
abs
()
ts_phase
=
self
.
phase
()
ts_phasor
=
{}
ts_phasor
[
'abs'
]
=
ts_abs
ts_phasor
[
'phase'
]
=
ts_phase
return
ts_phasor
def
frequency_shift
(
self
,
freq
):
""" Shift dynamic phasor values to EMT by frequency freq.
Only the real part is considered.
Assumes the same time steps for both timeseries.
:param freq: shift frequency
:return: new timeseries with shifted time domain values
"""
ts_shift
=
TimeSeries
(
self
.
name
+
'_shift'
,
self
.
time
,
self
.
values
.
real
*
np
.
cos
(
2
*
np
.
pi
*
freq
*
self
.
time
)
-
self
.
values
.
imag
*
np
.
sin
(
2
*
np
.
pi
*
freq
*
self
.
time
))
return
ts_shift
def
calc_freq_spectrum
(
self
):
""" Calculates frequency spectrum of the time series using FFT
"""
Ts
=
self
.
time
[
1
]
-
self
.
time
[
0
]
fft_values
=
np
.
fft
.
fft
(
self
.
values
)
freqs_num
=
int
(
len
(
fft_values
)
/
2
)
fft_freqs
=
np
.
fft
.
fftfreq
(
len
(
fft_values
),
d
=
Ts
)
return
fft_freqs
[:
freqs_num
],
np
.
abs
(
fft_values
[:
freqs_num
])
/
freqs_num
def
interpolate_cmpl
(
self
,
timestep
):
""" Not tested yet!
Interpolates complex timeseries with timestep
:param timestep:
:return:
"""
interpl_time
=
np
.
arange
(
self
.
time
[
0
],
self
.
time
[
-
1
],
timestep
)
realValues
=
interp1d
(
interpl_time
,
self
.
values
.
real
)
imagValues
=
interp1d
(
interpl_time
,
self
.
values
.
imag
)
ts_return
=
TimeSeries
(
self
.
name
+
'_intpl'
,
time
,
np
.
vectorize
(
complex
)(
realValues
,
imagValues
))
return
timeseries
@
staticmethod
def
multi_frequency_shift
(
timeseries_list
,
freqs_list
):
""" Calculate shifted frequency results of all time series
in list by using the frequency with the same index in the frequency list.
:param timeseries_list: timeseries list retrieved from dpsim results
:param freq: frequency by which the timeseries should be shifted
:return: dict of shifted time series
"""
result_list
=
{}
for
ts
,
freq
in
zip
(
timeseries_list
,
freqs_list
):
ts_shift
=
ts
.
frequency_shift
(
freq
)
result_list
[
ts
.
name
]
=
ts_shift
return
result_list
@
staticmethod
def
create_emt_from_dp
(
timeseries_list
,
freqs_list
):
"""Calculate shifted frequency results of all time series
:param timeseries_list: timeseries list retrieved from dpsim results
:param freq: frequency by which the timeseries should be shifted
:return: list of shifted time series
"""
result
=
np
.
zeros_like
(
timeseries_list
[
0
].
values
)
for
ts
,
freq
in
zip
(
timeseries_list
,
freqs_list
):
ts_shift
=
ts
.
frequency_shift
(
freq
)
result
=
result
+
ts_shift
.
values
ts_result
=
TimeSeries
(
'emt_signal'
,
timeseries_list
[
0
].
time
,
result
.
real
)
return
ts_result
@
staticmethod
def
frequency_shift_list
(
timeseries_list
,
freq
):
"""Calculate shifted frequency results of all time series
...
...
@@ -57,7 +122,7 @@ class TimeSeries:
"""
result_list
=
{}
for
name
,
ts
in
timeseries_list
.
items
():
ts_emt
=
ts
.
frequency_shift
(
ts
.
name
,
freq
)
ts_emt
=
ts
.
frequency_shift
(
freq
)
result_list
[
ts
.
name
]
=
ts_emt
return
result_list
...
...
@@ -93,78 +158,11 @@ class TimeSeries:
interp_vals_ts2
=
np
.
interp
(
time
,
ts2
.
time
,
ts2
.
values
)
ts_diff
=
TimeSeries
(
name
,
time
,
(
interp_vals_ts2
-
interp_vals_ts1
))
return
ts_diff
def
frequency_shift
(
self
,
name
,
freq
):
""" Shift dynamic phasor values to EMT by frequency freq.
Assumes the same time steps for both timeseries.
:param name: name of returned time series
:param freq: shift frequency
:return: new timeseries with shifted time domain values
"""
ts_shift
=
TimeSeries
(
name
,
self
.
time
,
self
.
values
.
real
*
np
.
cos
(
2
*
np
.
pi
*
freq
*
self
.
time
)
-
self
.
values
.
imag
*
np
.
sin
(
2
*
np
.
pi
*
freq
*
self
.
time
))
return
ts_shift
def
calc_freq_spectrum
(
self
):
""" Calculates frequency spectrum of the time series using FFT
:param name: name of returned time series
:param freq: shift frequency
:return: new timeseries with shifted time domain values
"""
Ts
=
self
.
time
[
1
]
-
self
.
time
[
0
]
fft_values
=
np
.
fft
.
fft
(
self
.
values
)
freqs_num
=
int
(
len
(
fft_values
)
/
2
)
fft_freqs
=
np
.
fft
.
fftfreq
(
len
(
fft_values
),
d
=
Ts
)
return
fft_freqs
[:
freqs_num
],
np
.
abs
(
fft_values
[:
freqs_num
])
/
freqs_num
def
interpolate_cmpl
(
self
,
name
,
timestep
):
""" Not tested yet!
Interpolates complex timeseries with timestep
:param name:
:param timestep:
:return:
"""
interpl_time
=
np
.
arange
(
self
.
time
[
0
],
self
.
time
[
-
1
],
timestep
)
realValues
=
interp1d
(
interpl_time
,
self
.
values
.
real
)
imagValues
=
interp1d
(
interpl_time
,
self
.
values
.
imag
)
ts_return
=
TimeSeries
(
name
,
time
,
np
.
vectorize
(
complex
)(
realValues
,
imagValues
))
return
timeseries
@
staticmethod
def
check_node_number_comp
(
ts_list_comp
,
node
):
"""
Check if node number is available in complex time series.
:param ts_comp: complex time series list
:param node: node number to be checked
:return: true if node number is available, false if out of range
"""
ts_comp_length
=
len
(
ts_comp
)
im_offset
=
int
(
ts_comp_length
/
2
)
if
im_offset
<=
node
or
node
<
0
:
print
(
'Complex node not available'
)
return
false
else
:
return
true
@
staticmethod
def
check_node_number
(
ts_list
,
node
):
"""
Check if node number is available in time series.
:param ts: time series list
:param node: node number to be checked
:return: true if node number is available, false if out of range
"""
ts_length
=
len
(
ts
)
if
ts_length
<=
node
or
node
<
0
:
print
(
'Node not available'
)
return
false
else
:
return
true
@
staticmethod
def
complex_abs
(
name
,
ts_real
,
ts_imag
):
""" Calculate absolute value of complex variable.
Assumes the same time steps for both timeseries.
Assumes the same time steps for both timeseries.
"""
ts_complex
=
np
.
vectorize
(
complex
)(
ts_real
.
values
,
ts_imag
.
values
)
ts_abs
=
TimeSeries
(
name
,
ts_real
.
time
,
np
.
absolute
(
ts_complex
))
...
...
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