def check_num_radiation_transitions_other_source(
self,
column,
other_radiation,
num_diff_radiation_transitions_thresold,
radiation_threshold=None,
label_other='_other'):
name_check_function = inspect.getframeinfo(
inspect.currentframe()).function
if radiation_threshold is None:
radiation_threshold = DNI_RADIATION_THRESHOLD
column_other = other_radiation.name + label_other
other_radiation_filt = other_radiation.copy(
)[lambda x: x > radiation_threshold]
radiation_filt = self.df[column][lambda x: x > radiation_threshold]
if len(radiation_filt) == 0: # Avoids future errors
return None
num_radiation_transitions_value = mc_solar.num_radiation_transitions(
radiation_filt)
num_radiation_transitions_value_other = mc_solar.num_radiation_transitions(
other_radiation_filt)
condition_list = abs(num_radiation_transitions_value -
num_radiation_transitions_value_other
) < num_diff_radiation_transitions_thresold
buffer = None
if not condition_list:
plt.figure()
radiation_filt.plot(style='.-')
other_radiation_filt.plot(style='.-')
plt.legend([column, column_other])
plt.title(name_check_function + ':' + column)
plt.suptitle(self.type_data_station, fontsize=18)
buffer = io.BytesIO()
plt.savefig(buffer)
buffer.seek(0)
self.assertion_base(
condition=condition_list,
error_message=
'No coherence of cloudy moments between {} and {} radiation sources with {} and {} respectively. Maximum allowed difference: {}'
.format(column, column_other, num_radiation_transitions_value,
num_radiation_transitions_value_other,
num_diff_radiation_transitions_thresold),
check_type=name_check_function,
figure=buffer)
def check_same_magnitude_total_irradiation(self, column, column_other,
threshold_pct):
name_check_function = inspect.getframeinfo(
inspect.currentframe()).function
irradiation = mc_solar.daily_irradiation(
self.df[column], samples_per_hour=self.samples_per_hour)
irradiation_other = mc_solar.daily_irradiation(
self.df[column_other], samples_per_hour=self.samples_per_hour)
if irradiation < DAILY_IRRADIATION_THRESHOLD: # Avoids future errors
return None
diff_radiation = abs(irradiation -
irradiation_other) / irradiation * 100
condition_list = diff_radiation < threshold_pct
buffer = None
if not (condition_list):
plt.figure()
self.df[column].plot(style='k.')
self.df[column_other].plot(style='r.')
plt.legend([column, column_other])
plt.title(name_check_function + ':' + column + '&' + column_other +
' with thresold_pct=' + str(threshold_pct))
plt.suptitle(self.type_data_station, fontsize=18)
buffer = io.BytesIO()
plt.savefig(buffer)
buffer.seek(0)
irrad_filt = self.df[column][lambda m: m > DNI_RADIATION_THRESHOLD]
num_radiation_transitions_value = mc_solar.num_radiation_transitions(
irrad_filt)
if num_radiation_transitions_value < NUM_RADIATION_TRANSITIONS_THRESHOLD:
self.assertion_base(
condition=condition_list,
error_message=
'Total irradiation from {} is different to {} in more than {}%. It is {:.1f}% while DAILY_IRRADIATION_THRESHOLD is {:.2} kWh/(m2·day)'
.format(column, column_other, threshold_pct, diff_radiation,
DAILY_IRRADIATION_THRESHOLD),
check_type=name_check_function,
figure=buffer)
else:
self.assertion_base(
condition=False,
error_message=
'Comparison of total irradiations {} and {} not checked because the number of cloudy moments={} [with a DRADIATION_DT={}] is higher than threshold={}'
.format(column, column_other, num_radiation_transitions_value,
DRADIATION_DT, NUM_RADIATION_TRANSITIONS_THRESHOLD),
error_level='INFO',
check_type=name_check_function,
figure=buffer)
def check_coherence_isotypes(self,
dni,
top,
mid,
bot,
threshold_pct,
radiation_threshold=None):
# Check radiation coherence between DNI and isotypes
# THRESHOLD is in percentage
name_check_function = inspect.getframeinfo(
inspect.currentframe()).function
if radiation_threshold is None:
radiation_threshold = DNI_RADIATION_THRESHOLD
df_filt = self.df[self.df[dni] > DNI_RADIATION_THRESHOLD]
if len(df_filt) == 0: # Avoids future errors
return None
dni_model = (df_filt[top] * 0.51 + df_filt[mid] * 0.10 +
df_filt[bot] * 0.39)
condition_list = (((df_filt[dni] - dni_model).abs()) / df_filt[dni] *
100 < threshold_pct)
buffer = None
if not condition_list.all():
plt.figure()
df_filt[dni].plot(style='k.')
df_filt[top].plot(style='.')
df_filt[mid].plot(style='.')
df_filt[bot].plot(style='.')
df_filt[dni][~condition_list].plot(marker='P',
markersize=8,
color='darkred',
markeredgecolor='yellow',
markeredgewidth=2)
plt.legend([top, mid, bot])
plt.title(name_check_function)
plt.suptitle(self.type_data_station, fontsize=18)
buffer = io.BytesIO()
plt.savefig(buffer)
buffer.seek(0)
irrad_filt = self.df[dni][lambda m: m > DNI_RADIATION_THRESHOLD]
num_radiation_transitions_value = mc_solar.num_radiation_transitions(
irrad_filt)
if num_radiation_transitions_value < NUM_RADIATION_TRANSITIONS_THRESHOLD:
self.assertion_base(
condition=condition_list.all(),
error_message=
'No coherence between DNI radiation and isotypes considering a percentage threshold of {} % in {}'
.format(threshold_pct, df_filt[dni][~condition_list].index),
check_type=name_check_function,
figure=buffer)
else:
self.assertion_base(
condition=False,
error_message=
'DNI vs isotypes comparison not checked because the number of cloudy moments={} [with a DRADIATION_DT={}] is higher than threshold={}'
.format(num_radiation_transitions_value, DRADIATION_DT,
NUM_RADIATION_TRANSITIONS_THRESHOLD),
error_level='INFO',
check_type=name_check_function,
figure=buffer)
def check_radiation_other_source(self,
column,
other_radiation,
threshold_pct,
radiation_threshold=None,
label_other='_other'):
name_check_function = inspect.getframeinfo(
inspect.currentframe()).function
if radiation_threshold is None:
radiation_threshold = DNI_RADIATION_THRESHOLD
other_radiation_copy = other_radiation.copy()
other_radiation_copy.name += label_other
column_other = other_radiation_copy.name
df_joined = self.df.join(other_radiation_copy, how='inner')
df_filt = df_joined[df_joined[column] > radiation_threshold]
if len(df_filt) == 0: # Avoids future errors
return None
condition_list = (df_filt[column] - df_filt[column_other]
).abs() / df_filt[column_other] * 100 < threshold_pct
buffer = None
if not condition_list.all():
plt.figure()
df_filt[column].plot(style='.')
df_filt[column_other].plot(style='.')
df_filt[column][~condition_list].plot(style='rP')
plt.legend([column, column_other])
plt.title(name_check_function + ':' + column)
plt.suptitle(self.type_data_station, fontsize=18)
buffer = io.BytesIO()
plt.savefig(buffer)
buffer.seek(0)
irrad_filt = self.df[column][lambda m: m > DNI_RADIATION_THRESHOLD]
num_radiation_transitions_value = mc_solar.num_radiation_transitions(
irrad_filt)
if num_radiation_transitions_value < NUM_RADIATION_TRANSITIONS_THRESHOLD:
self.assertion_base(
condition=condition_list.all(),
error_message=
'No coherence between {} and {} radiation sources considering a percentage THRESHOLD of {} % in {}'
.format(column, column_other, threshold_pct,
df_filt[column][~condition_list].index),
check_type=name_check_function,
figure=buffer)
else:
self.assertion_base(
condition=False,
error_message=
'Comparison of radiation {} and {} from different sources not checked because the number of cloudy moments={} [with a DRADIATION_DT={}] is higher than threshold={}'
.format(column, column_other, num_radiation_transitions_value,
DRADIATION_DT, NUM_RADIATION_TRANSITIONS_THRESHOLD),
error_level='INFO',
check_type=name_check_function,
figure=buffer)
def check_coherence_radiation(self,
threshold_pct,
dni,
ghi,
dhi,
radiation_threshold=None):
# Check radiation coherence between GHI and DNI&DHI
# THRESHOLD is in percentage
name_check_function = inspect.getframeinfo(
inspect.currentframe()).function
if radiation_threshold is None:
radiation_threshold = GHI_RADIATION_THRESHOLD
df_filt = self.df[self.df[ghi] > GHI_RADIATION_THRESHOLD]
if len(df_filt) == 0: # Avoids future errors
return None
_, Zz = mc_solar.solpos(df_filt.index)
ghi_model = (df_filt[dhi] + df_filt[dni] * np.cos(Zz))
condition_list = (((df_filt[ghi] - ghi_model).abs()) / df_filt[ghi] *
100 < threshold_pct)
buffer = None
if not condition_list.all():
plt.figure()
df_filt[ghi].plot(style='.')
df_filt[ghi][~condition_list].plot(style='rP')
# plt.legend()
plt.title(name_check_function)
plt.suptitle(self.type_data_station, fontsize=18)
buffer = io.BytesIO()
plt.savefig(buffer)
buffer.seek(0)
num_radiation_transitions_value = mc_solar.num_radiation_transitions(
self.df[ghi])
if num_radiation_transitions_value < NUM_RADIATION_TRANSITIONS_THRESHOLD:
self.assertion_base(
condition=condition_list.all(),
error_message=
'No coherence between radiations considering a percentage threshold of GHI {}% in {}'
.format(threshold_pct, df_filt[~condition_list].index),
check_type=name_check_function,
figure=buffer)
else:
self.assertion_base(
condition=False,
error_message=
'Radiation coherence based on GHI not checked because the number of cloudy moments={} [with a DRADIATION_DT={}] is higher than threshold={}'
.format(num_radiation_transitions_value, DRADIATION_DT,
NUM_RADIATION_TRANSITIONS_THRESHOLD),
error_level='INFO',
check_type=name_check_function,
figure=buffer)