Merge branch 'main' of https://github.com/mcgoldba/pyFoamd

pyfoamd/functions/monitors.py

@@ -0,0 +1,141 @@
+import subprocess
+import sys
+import os
+from pathlib import Path
+import matplotlib.pyplot as plt
+from matplotlib.animation import FuncAnimation
+import numpy as np
+import pandas as pd
+import logging
+import re
+import copy
+from pyfoamd import userMsg
+import pyfoamd.types as pt
+from pyfoamd.functions.getProbe import getProbe
+from pyfoamd.functions.getMonitor import getMonitor
+
+logger = logging.getLogger("pf")
+
+plt.style.use('ggplot')
+
+# def monitor(value='U', time='latestTime', supplement=None, 
+#     workingDir=Path.cwd(), title=None, filter=None, yrange = None,
+#     logScale=False, all=False):
+
+def monitors(monitorDict):
+    """
+    Create plots of multiple monitors in the same plot window
+
+    Parameters:
+        monitorDict [dict(dict)]: dictionary containing monitor parameters, were each 
+            key is the monitor name, and the values are dictionary of argumrents
+            supplied to `pyfoamd.monitor`
+
+
+    Example:
+        >>> pf.monitors({
+            'residuals': {
+                'filter': 'initial'
+                'log': True
+            },
+            'p': {}.
+            'U': {
+                'filter': 'Probe 0'
+            }
+            })
+
+    """
+    for value in monitorDict.keys():
+        if title is None:
+            title = Path(workingDir).name
+
+        try:
+            monitor = getMonitor(name=value, startTime=time, 
+                        workingDir=workingDir)
+        except FileNotFoundError:
+            monitor = getProbe(value, time, workingDir)
+
+        if filter is not None:
+            columns_ = [monitor.data.columns[i] for i, item in 
+            enumerate(monitor.data.columns) if re.search(filter, item)]
+        else:
+            columns_ = monitor.data.columns
+
+    # x = monitor.data.index.to_numpy(dtype=float)
+    # y = monitor.data.iloc[:,filteredColumnIdx].to_numpy(dtype=float)
+
+
+    # fig, ax = plt.subplots(figsize=(4,3))
+    # # line, = ax.plot(x,y)
+    # lines = ax.plot(data=monitor.data)
+    # if yrange is not None:
+    #     ax.set_ylim(yrange)
+    # if logScale:
+    #     ax.set_yscale('log')
+
+
+    # def updatePlot(_, monitor, filterIdx, lines):
+    def updatePlot(i):
+        #TODO:  This function should update existing monitors with new value,
+        # rather than rereading the whole monitor file every loop.
+        # logger.info("Updating monitor data...")
+        monitor.update()
+        x = pd.to_numeric(monitor.data.index).to_numpy().reshape((-1, 1))
+        # try:
+        #     x = [int(v) for v in x]
+        # except:
+        #     x = [float(v) for v in x]
+
+        Y = monitor.data[columns_].apply(pd.to_numeric).to_numpy()
+
+        logger.debug(f"Y: {Y}")
+
+        if any(not np.isnan(v) for v in Y.flatten()) is False:
+            userMsg("No data found for plot!", "WARNING")
+            return
+
+        # lines_ = []
+
+        # for line, y in zip(lines, Y):
+
+        # fig.set_data(x,y)
+
+
+        # logger.info("Redrawing...")
+
+        plt.cla()
+        # df_ = monitor.data.iloc[:,filteredColumnIdx].apply(pd.to_numeric)
+        # fig = df_.plot()
+        for i, label in enumerate(columns_):
+            plt.plot(x,Y[:,i], label=label)
+
+
+
+        # plt.xlabel(monitor.data.index.name)
+        # plt.ylabel('Value')
+        # plt.title(monitor._name)
+        # plt.legend()
+        # if logScale:
+        #     plt.yscale('log')
+        # if yrange is not None:
+        #     plt.ylim(yrange)
+
+        plt.xlabel(monitor.data.index.name)
+        plt.ylabel('Value')
+        if isinstance(monitor, pt.ofProbe):
+            plt.title(monitor._field)
+        else:
+            plt.title(monitor._name)
+        plt.legend()
+        if logScale:
+            plt.yscale('log')
+        if yrange is not None:
+            plt.ylim(yrange)
+
+    ani = FuncAnimation(plt.gcf(), updatePlot, 
+        #fargs=(monitor, filteredColumnIdx, lines),
+        interval=1000)
+
+    plt.tight_layout() 
+
+    plt.show()