Merge pull request #89 from UW-SASWE/sm-main

Added Visualization feature and function to convert relative to absolute path for users' convenience.

.gitignore

@@ -217,4 +217,5 @@ params/*
 models/*
 *dask-worker-space/*
 !src/params/rat_mekong.yml
-src/RAT/ee_utils/ee_config.py
+src/RAT/ee_utils/ee_config.py
+data*/*

src/rat/toolbox/MiscUtil.py

@@ -0,0 +1,24 @@
+from pathlib import Path #to work with relative paths
+
+## Function to convert a relative path to absolute path
+def rel2abs(relative_path: str) -> str:
+    '''
+    Convert a relative path to an absolute path.
+
+    Parameters:
+    - relative_path (str): The relative path to be converted.
+
+    Returns:
+    - str: The absolute path.
+
+    Example:
+    ```
+    relative_path = 'subfolder/file.txt'
+    absolute_path = rel2abs(relative_path)
+    ```
+    '''
+    # Get the absolute path
+    absolute_path = Path(relative_path).resolve()
+
+    # Convert Path object to string
+    return str(absolute_path)

src/rat/toolbox/visualize.py

@@ -0,0 +1,150 @@
+import plotly.graph_objects as go
+import pandas as pd
+from pathlib import Path
+
+class RAT_RESERVOIR:
+    """
+    A class for representing various reservoir-related variables using Plotly.
+
+    Attributes:
+    - rat_output_vars (dict): Description of properties useful for creating plots for each reservoir variable.
+    - final_outputs (str): Path to the final outputs directory.
+    - file_name (str): Name of the reservoir file to be plotted.
+    - reservoir_name (str): Optional parameter for specifying the reservoir name.
+
+    Methods:
+    - __init__: Initializes the RAT_RESERVOIR instance.
+    - plot_var: Plots a reservoir variable from inflow, outflow, storage change, evaporation, surface area and area elevation curve.
+    """
+
+    rat_output_vars = {
+        'Storage Change': {
+                  'x_var_name'    : 'Date',
+                  'y_var_name'    : '∆S',
+                  'data_folder'   : 'dels',
+                  'x_data_column' : 'date',
+                  'y_data_column' : 'dS (m3)',
+                  'colors'        : ['#FB931D'],
+                },
+        'Inflow': {
+                  'x_var_name'    : 'Date',
+                  'y_var_name'    : 'Inflow',  
+                  'data_folder'   : 'inflow',
+                  'x_data_column' : 'date',
+                  'y_data_column' : 'inflow (m3/d)',
+                  'colors'        : ['#06CCD3'],
+              },
+        'Outflow': {
+                  'x_var_name'    : 'Date',
+                  'y_var_name'    : 'Outflow',
+                  'data_folder'   : 'outflow',
+                  'x_data_column' : 'date',
+                  'y_data_column' : 'outflow (m3/d)',
+                  'colors'        : ['#146698'],
+          },
+        'Surface Area': {
+                  'x_var_name'    : 'Date',
+                  'y_var_name'    : 'Surface Area',
+                  'data_folder'   : 'sarea_tmsos',
+                  'x_data_column' : 'date',
+                  'y_data_column' : 'area (km2)',
+                  'colors'        : ['#F7675E'],
+                    },
+        'Evaporation': {
+                  'x_var_name'    : 'Date',
+                  'y_var_name'    : 'Evaporation',
+                  'data_folder'   : 'evaporation',
+                  'x_data_column' : 'date',
+                  'y_data_column' : 'evaporation (mm)',
+                  'colors'        : ['green'],
+                    },
+        'A-E Curve'    : {
+                  'x_var_name'    : 'Area Inundated',
+                  'y_var_name'    : 'Elevation',
+                  'data_folder'   : 'aec',
+                  'x_data_column' : 'area',
+                  'y_data_column' : 'elevation',
+                  'colors'      : ['brown'],
+                   }
+    }
+
+    def __init__(self,final_outputs, file_name, reservoir_name=None):
+        """
+        Initializes the RAT_RESERVOIR instance.
+
+        Parameters:
+        - final_outputs (str): Path to the final outputs directory.
+        - file_name (str): Name of the reservoir file to be plotted.
+        - reservoir_name (str): Optional parameter for specifying the reservoir name.
+        """
+        self.final_outputs = final_outputs
+        self.reservoir_file_name = file_name
+        self.reservoir_name = reservoir_name
+
+    def plot_var(self, var_to_observe, title_for_plot, xlabel='', ylabel='', 
+                 x_axis_units='', y_axis_units='', x_scaling_factor=1, 
+                 y_scaling_factor=1, new_plot=True, width=950, height=450, savepath=None):
+        """
+        Plots a specified Reservoir variable using plotly. The variables that can be plotted are 
+        Inflow, Outflow, Storage Change, Surface Area, Evaporation and A-E Curve.
+
+        Parameters:
+        - var_to_observe (str): Variable to be plotted. Acceptable values are 'Inflow', 'Outflow',
+          'Storage Change', 'Surface Area', 'Evaporation' and 'A-E Curve'.
+        - title_for_plot (str): Title for the plot.
+        - xlabel (str): Label for the x-axis.
+        - ylabel (str): Label for the y-axis.
+        - x_axis_units (str): Units for the x-axis.
+        - y_axis_units (str): Units for the y-axis.
+        - x_scaling_factor (float): Scaling factor for the x-axis data.
+        - y_scaling_factor (float): Scaling factor for the y-axis data.
+        - new_plot (bool): Whether to create a new plot instance.
+        - width (int): Width of the plot.
+        - height (int): Height of the plot.
+        - savepath (str): Optional path to save the plot as an HTML file.
+
+        Returns:
+        -fig: The plotly figure instance
+        """
+        # Read dataframe 
+        df = pd.read_csv(Path(self.final_outputs)/self.rat_output_vars[var_to_observe]['data_folder']/self.reservoir_file_name)
+
+        # Scale data to change units
+        df[self.rat_output_vars[var_to_observe]['x_data_column']]=df[self.rat_output_vars[var_to_observe]['x_data_column']]*x_scaling_factor
+        df[self.rat_output_vars[var_to_observe]['y_data_column']]=df[self.rat_output_vars[var_to_observe]['y_data_column']]*y_scaling_factor
+
+        # Create a figure instance if new_plot is true
+        if new_plot:
+            fig = go.Figure()
+        elif self.prev_fig:
+            fig = self.prev_fig
+        else:
+            fig = go.Figure()
+
+        # Create a trace to plot
+        trace = go.Scatter(x=df[self.rat_output_vars[var_to_observe]['x_data_column']], # Change x axis column 
+                        y=df[self.rat_output_vars[var_to_observe]['y_data_column']], # Change y axis column,
+                        mode='lines', # Line plot
+                        name=var_to_observe, # Name of trace
+                        line=dict(color=self.rat_output_vars[var_to_observe]['colors'][0]) # Color of line plot
+                        )
+
+        # Add the trace to the plot
+        fig.add_trace(trace)
+
+        # Update layout
+        fig.update_layout(title=title_for_plot, # plot title
+                        xaxis_title=xlabel+f' {x_axis_units}', # x axis label
+                        yaxis_title=ylabel+f' {y_axis_units}', # y axis label
+                        showlegend=True, # show legend
+                        width=width, # width of plot
+                        height=height) # height of plot
+
+        # Saving the previous figure to add traces if needed.
+        self.prev_fig = fig
+
+        if savepath:
+            # Save the plot 
+            fig.write_html(savepath)
+
+        return fig