from mooda import WaterFrame
# Path where CTD file is
path = r"C:\Users\rbard\Google Drive\Work\EmsoDev\server\ejemplos web\megakit - mio\data\obsea\OS_OBSEA_2016120120170426_R_4381-606.nc"
wf = WaterFrame()
wf.from_netcdf(path)
print(wf)
# Resample 2 hourly
# wf.resample('2H')
# Slice
# wf.slice_time("20170327000000", "20170423000000")
mean = wf.mean('DOX2')
index, max_waves = wf.max('DOX2')
index2, min_waves = wf.min('DOX2')
print(index)
print(index2)
# print(max_waves)
# print(min_waves)
# print("Marea:", (max_waves - min_waves)/2)
# Path of files
# Where the files are:
path_location = r"C:\Users\rbard\Desktop\Azores EGIM Data"
# Where to save the result:
save_location = r"C:\Users\rbard\Google Drive\Work\EmsoDev\server\www\html\graphs\azores"
path_files = glob.glob(path_location)
df = []
for path_file in path_files:
# Load data into a WaterFrame
print("Loading data")
wf = WaterFrame()
wf.from_netcdf(path_file)
print("Done")
print(wf)
# Resample data hourly
print("Resampling data")
wf.resample("H")
print("Done")
# Obtain one of the parameters
parameter = wf.parameters()[0]
intervals = wf.datetime_intervals(parameter)
if "R_4381-606" in path_file:
instrument = "Turbidimeter"
def openData(self, path, concat=False):
"""
It opens the netcdf of the path.
Parameters
----------
path: str or WaterFrame
Path where the file is or WaterFrame object.
concat: bool, optional (concat = False)
It adds the new dataframe to the current dataframe.
Returns
-------
True/False: bool
It indicates if the operation is ok.
"""
self.msg2Statusbar.emit("Opening data")
if isinstance(path, str):
# Obtain type of file
extension = path.split(".")[-1]
# Init ok
ok = False
wf_new = WaterFrame()
if extension == "nc":
ok = wf_new.from_netcdf(path)
elif extension == "pkl":
ok = wf_new.from_pickle(path)
elif extension == "csv":
try:
wf_new = EGIM.from_raw_csv("EMSO-Azores", path)
ok = True
except:
ok = False
if ok:
# Check if we want actual data
if not concat:
self.newWaterFrame()
self.wf.concat(wf_new)
self.msg2TextArea.emit("Working with file {}".format(path))
# Add metadata information into metadataList
self.addMetadata(self.wf.metadata)
# Add other information
self.otherInfoPlainText.setPlainText(repr(self.wf))
# Add data information into dataList
self.addData(self.wf.data)
# Plot QC
self.addQCBarPlot()
self.msg2Statusbar.emit("Ready")
return True
else:
self.msg2Statusbar.emit("Error opening data")
return False
else:
# Path is a WaterFrame
# Check if there is no data in the waterframe
if path.data.empty:
return False
# Check if it is a dataframe of an acoustic data.
# In this case, we are going to delete the previous dataframe.
if "Sequence" in self.wf.data.keys():
self.wf.clear()
self.wf.concat(path)
# Add data information into dataList
self.addData(self.wf.data)
self.addMetadata(self.wf.metadata)
# Plot QC
self.addQCBarPlot()
return True
def open_data(self, path, concat=False):
"""
It opens the netcdf of the path.
Parameters
----------
path: str or WaterFrame
Path where the file is or WaterFrame object.
concat: bool, optional (concat = False)
It adds the new dataframe to the current dataframe.
Returns
-------
True/False: bool
It indicates if the operation is ok.
"""
debug = True # Variable for debug reasons
if debug:
print("In PlotSplitter.open_data():")
print(" - Emit msg2statusbar: Opening data")
self.msg2statusbar.emit("Opening data")
if isinstance(path, str):
if debug:
print(" - path is a string:", path)
# Obtain type of file
extension = path.split(".")[-1]
# Init ok
ok = False # pylint: disable=C0103
wf_new = WaterFrame()
if extension == "nc":
ok = wf_new.from_netcdf(path) # pylint: disable=C0103
elif extension == "pkl":
ok = wf_new.from_pickle(path) # pylint: disable=C0103
if ok:
# Check if we want actual data
if not concat:
self.new_waterframe()
self.wf.concat(wf_new)
self.msg2TextArea.emit("Working with file {}".format(path))
# Add metadata information into metadataList
self.add_metadata(self.wf.metadata)
# Add other information
self.other_info_plain_text.setPlainText(repr(self.wf))
# Add data information into data_list
self.add_data(self.wf.data)
# Plot QC
self.add_qc_bar_plot()
self.msg2statusbar.emit("Ready")
if debug:
print(" - Emit msg2statusbar: Ready")
print(" - Exit from PlotSplitter.open_data()")
return True
else:
self.msg2statusbar.emit("Error opening data")
if debug:
print(" - Emit msg2statusbar: Error opening data")
print(" - Exit from PlotSplitter.open_data()")
return False
else:
# Path is a WaterFrame
if debug:
print(" - path is a WaterFrame")
print(path)
# Check if there is no data in the waterframe
if path.data.empty:
return False
# Check if it is a dataframe of an acoustic data.
# In this case, we are going to delete the previous dataframe.
if "Sequence" in self.wf.data.keys():
self.wf.clear()
self.wf.concat(path)
# Add data information into data_list
self.add_data(self.wf.data)
self.add_metadata(self.wf.metadata)
# Add other information
self.other_info_plain_text.setPlainText(repr(self.wf))
# Plot QC
self.add_qc_bar_plot()
return True
# Path of files
# Where the files are:
path_location = r"C:\Users\rbard\Desktop\Azores EGIM Data"
path_data = path_location + r"\turbidity.csv"
path_data = r"C:\Users\rbard\Desktop\Azores EGIM Data\Oximeter.csv"
# Where to save the result:
save_location = r"C:\Users\rbard\Google Drive\Work\EmsoDev\server\www\html\graphs\azores"
save_start = r"\OXI-"
end_save = r"-AZORES.html"
# Load data into a WaterFrame
print("Loading data")
if path_data[-1] == 'c':
wf = WaterFrame()
wf.from_netcdf(path_data)
elif path_data[-1] == 'v':
print(path_data)
wf = EGIM.from_raw_csv(observatory="EMSO-Azores", path=path_data)
print("Done")
print(wf)
# Check parameters
parameters = wf.parameters()
# Resample data hourly
print("Resampling data")
wf.resample("H")
print("Done")
wf.slice_time(start="20170725000000", end="20180811000000")
