Add timeplot scaling setting (lanl#58)

* add timeplot setting to choose plot scaling based on values

* update change log

CHANGELOG.rst

@@ -12,8 +12,8 @@ New Features:
 - Add nodes for non-adiabatic coupling vectors (NACR) and phase-less loss.
   See /examples/excited_states_azomethane.py.
 
-- New MultiGradient node for computing multiple partial derivatives of 
-  using one call to automatic differentiation.
+- New MultiGradient node for computing more than one partial derivative
+  using a single call to automatic differentiation.
 
 Improvements:
 -------------
@@ -24,6 +24,11 @@ Improvements:
 
 - Create Memory parent class to remove redundancy.
 
+- New setting TIMEPLOT_AUTOSCALING. If True (default), time plots with 
+  log-scaling on the axes will only be produced if warranted by the data.
+  If False, time plots with linear-scaling and log-scaling will be produced
+  every time.
+
 Bug Fixes:
 ----------
 

hippynn/_settings_setup.py

@@ -72,6 +72,7 @@ def kernel_handler(kernel_string):
     "DEBUG_AUTOINDEXING": (False, strtobool),
     "USE_CUSTOM_KERNELS": ("auto", kernel_handler),
     "WARN_LOW_DISTANCES": (True, strtobool),
+    "TIMEPLOT_AUTOSCALING": (True, strtobool),
 }
 
 settings = SimpleNamespace(**{k: default for k, (default, handler) in default_settings.items()})

hippynn/plotting/timeplots.py

@@ -66,12 +66,13 @@ def plot_over_time(metric_name, metric_data, pltkwd_info, save_dir):
 
     datamin = min(min(arr) for arr in metric_data.values())
     datamax = max(max(arr) for arr in metric_data.values())
-    if datamin > 0 and datamax / datamin > 2:
+    # if settings.TIMEPLOT_AUTOSCALING is set to True, only produce log-scale plots under certain conditions
+    if (not settings.TIMEPLOT_AUTOSCALING) or (datamin > 0 and datamax / datamin > 2):
         plt.yscale("log")
         fname = os.path.join(save_dir, metric_name + "_logplot" + settings.DEFAULT_PLOT_FILETYPE)
         plt.savefig(fname)
 
-        if max(len(arr) for arr in metric_data.values()) > 10:
+        if (not settings.TIMEPLOT_AUTOSCALING) or (max(len(arr) for arr in metric_data.values()) > 10):
             plt.xscale("log")
             fname = os.path.join(save_dir, metric_name + "_loglogplot" + settings.DEFAULT_PLOT_FILETYPE)
             plt.savefig(fname)