Merge pull request #97 from lgbouma/master

Add `verbose` kwarg

Author: hippke

docs/source/Python interface.rst

@@ -7,11 +7,12 @@ This describes the Python interface to TLS.
 Define data for a search
 ------------------------
 
-.. class:: transitleastsquares.model(t, y, dy)
+.. class:: transitleastsquares.model(t, y, dy, verbose=True)
 
 :t: *(array)* Time series of the data (**in units of days**)
 :y: *(array)* Flux series of the data, so that ``1`` is nominal flux (out of transit) and ``0`` is darkness. A transit may be represented by a flux of e.g., ``0.99``
 :dy: *(array, optional)* Measurement errors of the data
+:verbose: *(bool, optional)* Whether to print important information about the TLS run.  Default True.
 
 .. note::
 

transitleastsquares/main.py

@@ -44,13 +44,15 @@
 class transitleastsquares(object):
     """Compute the transit least squares of limb-darkened transit models"""
 
-    def __init__(self, t, y, dy=None):
+    def __init__(self, t, y, dy=None, verbose=True):
         self.t, self.y, self.dy = validate_inputs(t, y, dy)
+        self.verbose = verbose
 
     def power(self, **kwargs):
         """Compute the periodogram for a set of user-defined parameters"""
 
-        print(tls_constants.TLS_VERSION)
+        if self.verbose:
+            print(tls_constants.TLS_VERSION)
         self, kwargs = validate_args(self, kwargs)
 
         periods = period_grid(
@@ -81,36 +83,39 @@ def power(self, **kwargs):
             w=self.w,
             u=self.u,
             limb_dark=self.limb_dark,
+            verbose=self.verbose
         )
 
-        print(
-            "Searching "
-            + str(len(self.y))
-            + " data points, "
-            + str(len(periods))
-            + " periods from "
-            + str(round(min(periods), 3))
-            + " to "
-            + str(round(max(periods), 3))
-            + " days"
-        )
+        if self.verbose:
+            print(
+                "Searching "
+                + str(len(self.y))
+                + " data points, "
+                + str(len(periods))
+                + " periods from "
+                + str(round(min(periods), 3))
+                + " to "
+                + str(round(max(periods), 3))
+                + " days"
+            )
 
         # Python 2 multiprocessing with "partial" doesn't work
         # For now, only single-threading in Python 2 is supported
         if sys.version_info[0] < 3:
             self.use_threads = 1
             warnings.warn("This TLS version supports no multithreading on Python 2")
 
-        if self.use_threads == multiprocessing.cpu_count():
-            print("Using all " + str(self.use_threads) + " CPU threads")
-        else:
-            print(
-                "Using "
-                + str(self.use_threads)
-                + " of "
-                + str(multiprocessing.cpu_count())
-                + " CPU threads"
-            )
+        if self.verbose:
+            if self.use_threads == multiprocessing.cpu_count():
+                print("Using all " + str(self.use_threads) + " CPU threads")
+            else:
+                print(
+                    "Using "
+                    + str(self.use_threads)
+                    + " of "
+                    + str(multiprocessing.cpu_count())
+                    + " CPU threads"
+                )
 
         if self.show_progress_bar:
             bar_format = "{desc}{percentage:3.0f}%|{bar}| {n_fmt}/{total_fmt} periods | {elapsed}<{remaining}"

transitleastsquares/transit.py

@@ -95,12 +95,14 @@ def fractional_transit(
     return result
 
 
-def get_cache(durations, maxwidth_in_samples, per, rp, a, inc, ecc, w, u, limb_dark):
+def get_cache(durations, maxwidth_in_samples, per, rp, a, inc, ecc, w, u,
+              limb_dark, verbose=True):
     """Fetches (size(durations)*size(depths)) light curves of length 
         maxwidth_in_samples and returns these LCs in a 2D array, together with 
         their metadata in a separate array."""
 
-    print("Creating model cache for", str(len(durations)), "durations")
+    if verbose:
+        print("Creating model cache for", str(len(durations)), "durations")
     lc_arr = []
     rows = numpy.size(durations)
     lc_cache_overview = numpy.zeros(