--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/timeseries.py	Sun Jul 31 21:23:21 2022 +0000
@@ -0,0 +1,182 @@
+#!/usr/bin/env python3
+#
+#
+# usage:  netCDF_timeseries.py [-h] [--output output.png]
+#                               [--save timeseries.tabular]
+#                               [--config config-file]
+#                               [-v]
+#                               input varname
+# positional arguments:
+#  input            input filename with geographical coordinates (netCDF
+#                   format)
+#  varname          Specify which variable to extract (case sensitive)
+#
+# optional arguments:
+#  -h, --help                 show this help message and exit
+#  --output output.png        filename to store image (png format)
+#  --save timeseries.tabular  filename to store timeseries (tabular format)
+#  --config                   config file extract parameters
+#  -v, --verbose              switch on verbose mode
+#
+import argparse
+import ast
+import warnings
+
+import cftime  # noqa: F401
+
+import matplotlib as mpl
+mpl.use('Agg')
+
+import matplotlib.pyplot as plt   # noqa: I202,E402
+from matplotlib.dates import DateFormatter   # noqa: I202,E402
+
+import xarray as xr  # noqa: I202,E402
+
+
+class TimeSeries ():
+    def __init__(self, input, varname, output, save, verbose=False,
+                 config_file=""):
+
+        li = list(input.split(","))
+        if len(li) > 1:
+            self.input = li
+        else:
+            self.input = input
+
+        self.varname = varname
+        self.xylim_supported = True
+        if output == "" or output is None:
+            self.output = "Timeseries.png"
+        else:
+            self.output = output
+        if save == "" or save is None:
+            self.save = "Timeseries.tabular"
+        else:
+            self.save = save
+        self.verbose = verbose
+        self.time_start_value = ""
+        self.time_end_value = ""
+        self.lon_value = ""
+        self.lat_value = ""
+        self.lat_name = 'lat'
+        self.lon_name = 'lon'
+        self.time_name = 'time'
+        self.title = ''
+        self.xlabel = ''
+        self.ylabel = ''
+        self.format_date = ''
+        if config_file != "" and config_file is not None:
+            with open(config_file) as f:
+                sdict = ''.join(
+                    f.read().replace("\n", "").split('{')[1].split('}')[0]
+                    )
+                tmp = ast.literal_eval('{' + sdict.strip() + '}')
+                for key in tmp:
+                    if key == 'time_start_value':
+                        self.time_start_value = tmp[key]
+                    if key == 'time_end_value':
+                        self.time_end_value = tmp[key]
+                    if key == 'lon_value':
+                        self.lon_value = tmp[key]
+                    if key == 'lat_value':
+                        self.lat_value = tmp[key]
+                    if key == 'lon_name':
+                        self.lon_name = tmp[key]
+                    if key == 'lat_name':
+                        self.lat_name = tmp[key]
+                    if key == 'time_name':
+                        self.time_name = tmp[key]
+                    if key == 'title':
+                        self.title = tmp[key]
+                    if key == 'xlabel':
+                        self.xlabel = tmp[key]
+                    if key == 'ylabel':
+                        self.ylabel = tmp[key]
+                    if key == 'format_date':
+                        self.format_date = tmp[key]
+                        self.format_date = self.format_date.replace('X', '%')
+
+        if type(self.input) is list:
+            self.dset = xr.open_mfdataset(self.input, use_cftime=True)
+        else:
+            self.dset = xr.open_dataset(self.input, use_cftime=True)
+
+        if verbose:
+            print("input: ", self.input)
+            print("varname: ", self.varname)
+            if self.time_start_value:
+                print("time_start_value: ", self.time_start_value)
+            if self.time_end_value:
+                print("time_end_value: ", self.time_end_value)
+            print("output: ", self.output)
+            if self.lon_value:
+                print(self.lon_name, self.lon_value)
+            if self.lat_value:
+                print(self.lat_name, self.lat_value)
+
+    def plot(self):
+        if self.lon_value:
+            lon_c = float(self.lon_value)
+        if self.lat_value:
+            lat_c = float(self.lat_value)
+        if self.lat_value and self.lon_value:
+            self.df = self.dset.sel({self.lat_name: lat_c,
+                                     self.lon_name: lon_c},
+                                    method='nearest')
+        else:
+            self.df = self.dset
+        if self.time_start_value or self.time_end_value:
+            self.df = self.df.sel({self.time_name: slice(self.time_start_value,
+                                                         self.time_end_value)})
+        # Saving the time series into a tabular
+        self.df = self.df[self.varname].squeeze().to_dataframe()
+        self.df.dropna().to_csv(self.save, sep='\t')
+        # Plot the time series into png image
+        fig = plt.figure(figsize=(15, 5))
+        ax = plt.subplot(111)
+        self.df[self.varname].plot(ax=ax)
+        if self.title:
+            plt.title(self.title)
+        if self.xlabel:
+            plt.xlabel(self.xlabel)
+        if self.ylabel:
+            plt.ylabel(self.ylabel)
+        if self.format_date:
+            ax.xaxis.set_major_formatter(DateFormatter(self.format_date))
+        fig.tight_layout()
+        fig.savefig(self.output)
+
+
+if __name__ == '__main__':
+    warnings.filterwarnings("ignore")
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        'input',
+        help='input filename with geographical coordinates (netCDF format)'
+    )
+    parser.add_argument(
+        'varname',
+        help='Specify which variable to plot (case sensitive)'
+    )
+    parser.add_argument(
+        '--output',
+        help='output filename to store resulting image (png format)'
+    )
+    parser.add_argument(
+        '--save',
+        help='save resulting tabular file (tabular format) into filename'
+    )
+    parser.add_argument(
+        '--config',
+        help='pass timeseries parameters via a config file'
+    )
+    parser.add_argument(
+        "-v", "--verbose",
+        help="switch on verbose mode",
+        action="store_true")
+    args = parser.parse_args()
+
+    dset = TimeSeries(input=args.input, varname=args.varname,
+                      output=args.output, save=args.save, verbose=args.verbose,
+                      config_file=args.config)
+    dset.plot()