HG_REPOSITORIES/LPP/SciQLOP_Repos/SciQLop Commit - r1494:8ad169c5af90

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import traceback

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import traceback

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from SciQLopBindings import PyDataProvider, Product, VectorTimeSerie, ScalarTimeSerie, DataSeriesType

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from SciQLopBindings import PyDataProvider, Product, VectorTimeSerie, ScalarTimeSerie, DataSeriesType

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import numpy as np

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import numpy as np

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import math

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import math

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from spwc.cache import _cache

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from spwc.cache import _cache

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from spwc.common.datetime_range import DateTimeRange

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from spwc.common.datetime_range import DateTimeRange

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from functools import partial

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from functools import partial

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from datetime import datetime, timedelta, timezone

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from datetime import datetime, timedelta, timezone

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from spwc.common.variable import SpwcVariable

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from spwc.common.variable import SpwcVariable

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def make_scalar(x):

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def make_scalar(x):

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y = np.cos(x/10.)

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y = np.cos(x/10.)

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return SpwcVariable(time=x, data=y)

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return SpwcVariable(time=x, data=y)

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def make_vector(x):

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def make_vector(x):

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v=np.ones((len(x),3))

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v=np.ones((len(x),3))

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for i in range(3):

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for i in range(3):

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v.transpose()[:][i] = np.cos(x/10. + float(i)) + (100. * np.cos(x/10000. + float(i)))

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v.transpose()[:][i] = np.cos(x/10. + float(i)) + (100. * np.cos(x/10000. + float(i)))

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return SpwcVariable(time=x, data=v)

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return SpwcVariable(time=x, data=v)

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def make_multicomponent(x):

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def make_multicomponent(x):

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v=np.ones((len(x),4))

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v=np.ones((len(x),4))

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for i in range(4):

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for i in range(4):

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v.transpose()[:][i] = float(i+1) * np.cos(x/10. + float(i))

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v.transpose()[:][i] = float(i+1) * np.cos(x/10. + float(i))

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return SpwcVariable(time=x, data=v)

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return SpwcVariable(time=x, data=v)

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def make_spectrogram(x):

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def make_spectrogram(x):

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v=np.ones((len(x),32))

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v=np.ones((len(x),32))

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for i in range(32):

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for i in range(32):

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v.transpose()[:][i] = 100.*(2.+ float(i+1) * np.cos(x/1024. + float(i)))

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v.transpose()[:][i] = 100.*(2.+ float(i+1) * np.cos(x/1024. + float(i)))

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return SpwcVariable(time=x, data=v)

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return SpwcVariable(time=x, data=v)

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def _get_data(p_type, start, stop):

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def _get_data(p_type, start, stop):

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if type(start) is datetime:

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if type(start) is datetime:

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start = start.timestamp()

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start = start.timestamp()

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stop = stop.timestamp()

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stop = stop.timestamp()

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x = np.arange(math.ceil(start), math.floor(stop))*1.

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x = np.arange(math.ceil(start), math.floor(stop))*1.

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if p_type == 'scalar':

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if p_type == 'scalar':

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return make_scalar(x)

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return make_scalar(x)

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if p_type == 'vector':

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if p_type == 'vector':

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return make_vector(x)

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return make_vector(x)

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if p_type == 'multicomponent':

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if p_type == 'multicomponent':

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return make_multicomponent(x)

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return make_multicomponent(x)

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if p_type == 'spectrogram':

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if p_type == 'spectrogram':

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return make_spectrogram(np.arange(math.ceil(start), math.floor(stop),15.))

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return make_spectrogram(np.arange(math.ceil(start), math.floor(stop),15.))

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return None

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return None

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class MyProvider(PyDataProvider):

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class MyProvider(PyDataProvider):

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def __init__(self):

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def __init__(self):

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super(MyProvider,self).__init__()

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super(MyProvider,self).__init__()

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self.register_products([Product("/tests/without_cache/scalar",[],{"type":"scalar"}),

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self.register_products([Product("/tests/without_cache/scalar",[],{"type":"scalar"}),

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Product("/tests/without_cache/vector",[],{"type":"vector"}),

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Product("/tests/without_cache/vector",[],{"type":"vector"}),

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Product("/tests/without_cache/multicomponent",[],{"type":"multicomponent",'size':'4'}),

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Product("/tests/without_cache/multicomponent",[],{"type":"multicomponent",'size':'4'}),

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Product("/tests/without_cache/spectrogram",[],{"type":"spectrogram",'size':'32'}),

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Product("/tests/without_cache/spectrogram",[],{"type":"spectrogram",'size':'32'}),

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Product("/tests/with_cache/scalar",[],{"type":"scalar", "cache":"true"}),

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Product("/tests/with_cache/scalar",[],{"type":"scalar", "cache":"true"}),

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Product("/tests/with_cache/vector",[],{"type":"vector", "cache":"true"}),

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Product("/tests/with_cache/vector",[],{"type":"vector", "cache":"true"}),

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Product("/tests/with_cache/multicomponent",[],{"type":"multicomponent",'size':'4', "cache":"true"})

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Product("/tests/with_cache/multicomponent",[],{"type":"multicomponent",'size':'4', "cache":"true"})

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])

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])

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def get_data(self,metadata,start,stop):

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def get_data(self,metadata,start,stop):

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ts_type = DataSeriesType.SCALAR

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ts_type = DataSeriesType.SCALAR

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default_ctor_args = 1

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default_ctor_args = 1

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use_cache = False

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use_cache = False

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p_type = 'scalar'

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p_type = 'scalar'

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try:

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try:

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for key,value in metadata.items():

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for key,value in metadata.items():

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if key == 'type':

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if key == 'type':

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p_type = value

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p_type = value

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if value == 'vector':

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if value == 'vector':

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ts_type = DataSeriesType.VECTOR

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ts_type = DataSeriesType.VECTOR

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elif value == 'multicomponent':

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elif value == 'multicomponent':

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ts_type = DataSeriesType.MULTICOMPONENT

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ts_type = DataSeriesType.MULTICOMPONENT

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elif value == 'spectrogram':

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elif value == 'spectrogram':

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ts_type = DataSeriesType.SPECTROGRAM

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ts_type = DataSeriesType.SPECTROGRAM

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if key == 'cache' and value == 'true':

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if key == 'cache' and value == 'true':

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use_cache = True

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use_cache = True

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if use_cache:

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if use_cache:

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cache_product = f"tests/{p_type}"

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cache_product = f"tests/{p_type}"

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var = _cache.get_data(cache_product, DateTimeRange(datetime.fromtimestamp(start, tz=timezone.utc), datetime.fromtimestamp(stop, tz=timezone.utc)), partial(_get_data, p_type), fragment_hours=24)

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var = _cache.get_data(cache_product, DateTimeRange(datetime.fromtimestamp(start, tz=timezone.utc), datetime.fromtimestamp(stop, tz=timezone.utc)), partial(_get_data, p_type), fragment_hours=24)

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else:

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else:

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print("No Cache")

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var = _get_data(p_type, start, stop)

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var = _get_data(p_type, start, stop)

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return ((var.time,var.data), ts_type)

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return ((var.time,var.data), ts_type)

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except Exception as e:

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except Exception as e:

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print(traceback.format_exc())

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print(traceback.format_exc())

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print("Error in test.py ",str(e))

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print("Error in test.py ",str(e))

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return ((np.array(), np.array()), ts_type)

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return ((np.array(), np.array()), ts_type)

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t=MyProvider()

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t=MyProvider()

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             import traceback
             from SciQLopBindings import PyDataProvider, Product, VectorTimeSerie, ScalarTimeSerie, DataSeriesType
             import numpy as np
             import math
             from spwc.cache import _cache
             from spwc.common.datetime_range import DateTimeRange
             from functools import partial
             from datetime import datetime, timedelta, timezone
             from spwc.common.variable import SpwcVariable
             def make_scalar(x):
                 y = np.cos(x/10.)
                 return SpwcVariable(time=x, data=y)
             def make_vector(x):
                 v=np.ones((len(x),3))
                 for i in range(3):
                     v.transpose()[:][i] = np.cos(x/10. + float(i)) + (100. * np.cos(x/10000. + float(i)))
                 return SpwcVariable(time=x, data=v)
             def make_multicomponent(x):
                 v=np.ones((len(x),4))
                 for i in range(4):
                     v.transpose()[:][i] = float(i+1) * np.cos(x/10. + float(i))
                 return SpwcVariable(time=x, data=v)
             def make_spectrogram(x):
                 v=np.ones((len(x),32))
                 for i in range(32):
                     v.transpose()[:][i] = 100.*(2.+ float(i+1) * np.cos(x/1024. + float(i)))
                 return SpwcVariable(time=x, data=v)
             def _get_data(p_type, start, stop):
                 if type(start) is datetime:
                     start = start.timestamp()
                     stop = stop.timestamp()
                 x = np.arange(math.ceil(start), math.floor(stop))*1.
                 if p_type == 'scalar':
                     return make_scalar(x)
                 if p_type == 'vector':
                     return make_vector(x)
                 if p_type == 'multicomponent':
                     return make_multicomponent(x)
                 if p_type == 'spectrogram':
                     return make_spectrogram(np.arange(math.ceil(start), math.floor(stop),15.))
                 return None
             class MyProvider(PyDataProvider):
                 def __init__(self):
                     super(MyProvider,self).__init__()
                     self.register_products([Product("/tests/without_cache/scalar",[],{"type":"scalar"}),
                         Product("/tests/without_cache/vector",[],{"type":"vector"}),
                         Product("/tests/without_cache/multicomponent",[],{"type":"multicomponent",'size':'4'}),
                         Product("/tests/without_cache/spectrogram",[],{"type":"spectrogram",'size':'32'}),
                         Product("/tests/with_cache/scalar",[],{"type":"scalar", "cache":"true"}),
                         Product("/tests/with_cache/vector",[],{"type":"vector", "cache":"true"}),
                         Product("/tests/with_cache/multicomponent",[],{"type":"multicomponent",'size':'4', "cache":"true"})
                         ])
                 def get_data(self,metadata,start,stop):
                     ts_type = DataSeriesType.SCALAR
                     default_ctor_args = 1
                     use_cache = False
                     p_type = 'scalar'
                     try:
                         for key,value in metadata.items():
                             if key == 'type':
                                 p_type = value
                                 if value == 'vector':
                                     ts_type = DataSeriesType.VECTOR
                                 elif value == 'multicomponent':
                                     ts_type = DataSeriesType.MULTICOMPONENT
                                 elif value == 'spectrogram':
                                     ts_type = DataSeriesType.SPECTROGRAM
                             if key == 'cache' and value == 'true':
                                 use_cache = True
                         if use_cache:
                             cache_product = f"tests/{p_type}"
                             var = _cache.get_data(cache_product, DateTimeRange(datetime.fromtimestamp(start, tz=timezone.utc), datetime.fromtimestamp(stop, tz=timezone.utc)), partial(_get_data, p_type), fragment_hours=24)
                         else:
-                            print("No Cache")
                             var = _get_data(p_type, start, stop)
                         return ((var.time,var.data), ts_type)
                     except Exception as e:
                         print(traceback.format_exc())
                         print("Error in test.py ",str(e))
                         return ((np.array(), np.array()), ts_type)
             t=MyProvider()

	@@ -1,1 +1,1
	1	Subproject commit 9868166a1d6d779910b93a996b2b69d399168914		1	Subproject commit b081849458c211dcc59f72b11542959db2301162