Merge pull request #1 from jpvantassel/dev

code quality improvements in preparation for v0.3.1 release

README.md

@@ -5,14 +5,17 @@
 [![DOI](https://zenodo.org/badge/222287042.svg)](https://zenodo.org/badge/latestdoi/222287042)
 [![CircleCI](https://circleci.com/gh/jpvantassel/swprepost.svg?style=svg)](https://circleci.com/gh/jpvantassel/swprepost)
 [![Documentation Status](https://readthedocs.org/projects/swprepost/badge/?version=latest)](https://swprepost.readthedocs.io/en/latest/?badge=latest)
+[![Language grade: Python](https://img.shields.io/lgtm/grade/python/g/jpvantassel/swprepost.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/jpvantassel/swprepost/context:python)
+[![Codacy Badge](https://app.codacy.com/project/badge/Grade/150eb75dee3848f5bbfac0d9f2c33644)](https://www.codacy.com/manual/jpvantassel/swprepost?utm_source=github.com&utm_medium=referral&utm_content=jpvantassel/swprepost&utm_campaign=Badge_Grade)
+[![codecov](https://codecov.io/gh/jpvantassel/swprepost/branch/master/graph/badge.svg)](https://codecov.io/gh/jpvantassel/swprepost)
 
 ## Table of Contents
 
 ---
 
- - [About _SWprepost_](#About-SWprepost)
- - [A Few Examples](#A-Few-Examples)
- - [Getting Started](#Getting-Started)
+- [About _SWprepost_](#About-SWprepost)
+- [A Few Examples](#A-Few-Examples)
+- [Getting Started](#Getting-Started)
 
 ## About _SWprepost_
 
@@ -32,19 +35,20 @@ Geophysical fields, but who do not perform surface wave inversions.
 If you use `SWprepost` in your research or consulting we ask you please cite the
 following:
 
-> Joseph Vantassel. (2020). jpvantassel/swprepost: latest (Concept). Zenodo. http://doi.org/10.5281/zenodo.3839998
+> Joseph Vantassel. (2020). jpvantassel/swprepost: latest (Concept). Zenodo.
+> http://doi.org/10.5281/zenodo.3839998
 
-_Note: For software, version specific citations should be preferred to general
-concept citations, such as that listed above. To generate a version specific
-citation for `SWprepost`, please use the citation tool for that specific version
-on the `SWprepost` archive._
+_Note: For software, version specific citations should be preferred to general_
+_concept citations, such as that listed above. To generate a version specific_
+_citation for `SWprepost`, please use the citation tool for that specific_
+_version on the `SWprepost` [archive](https://doi.org/10.5281/zenodo.3839998)._
 
 For the motivation behind the development of `SWprepost` and its role in a
 larger project focused on developing a complete workflow for surface wave
 inversion please refer to and consider citing the following:
 
 > Joseph P. Vantassel and Brady R. Cox (2020) SWinvert: A workflow for
-performing rigorous surface wave inversion. (Submitted).
+> performing rigorous surface wave inversion. (Submitted).
 
 ## A Few Examples
 

examples/basic/Targets.ipynb

@@ -206,7 +206,7 @@
    "source": [
     "# Perform resampling in log-wavelength\n",
     "tar = swprepost.Target.from_target(\"inputs/from_tar_complex\")\n",
-    "new_tar = tar.resample(pmin=5, pmax=50, pn=20, res_type=\"log\", domain=\"wavelength\", inplace=False)\n",
+    "new_tar = tar.easy_resample(pmin=5, pmax=50, pn=20, res_type=\"log\", domain=\"wavelength\", inplace=False)\n",
     "\n",
     "# Plot\n",
     "fig, ax = plt.subplots(figsize=(4,3), dpi=200)\n",
@@ -247,7 +247,7 @@
    "source": [
     "# Perform resampling in log-frequency\n",
     "tar = swprepost.Target.from_target(\"inputs/from_tar_complex\")\n",
-    "new_tar = tar.resample(pmin=5, pmax=50, pn=20, res_type=\"log\", domain=\"frequency\", inplace=False)\n",
+    "new_tar = tar.easy_resample(pmin=5, pmax=50, pn=20, res_type=\"log\", domain=\"frequency\", inplace=False)\n",
     "\n",
     "# Plot\n",
     "fig, ax = plt.subplots(figsize=(4,3), dpi=200)\n",

setup.py

@@ -7,7 +7,7 @@
 
 setup(
     name='swprepost',
-    version='0.3.0',
+    version='0.3.1',
     description='A Python Package for Surface-Wave Inversion Pre- and Post-Processing',
     long_description=long_description,
     long_description_content_type='text/markdown',

swprepost/curve.py

@@ -91,7 +91,7 @@ def check_input(cls, x, y, check_fxn=None):
         return (x, y)
 
     def __init__(self, x, y, check_fxn=None):
-        """Intialize a curve object from x, y coordinates.
+        """Initialize a curve object from x, y coordinates.
 
         Parameters
         ----------
@@ -129,8 +129,7 @@ def resample_function(cls, x, y, **kwargs):
         """Wrapper for `interp1d` from `scipy`."""
         return sp.interp1d(x, y, **kwargs)
 
-    def resample(self, xx, inplace=False,
-                 interp1d_kwargs={"kind": "cubic"}, res_fxn=None):
+    def resample(self, xx, inplace=False, interp1d_kwargs=None, res_fxn=None):
         """Resample Curve at select x values.
 
         Parameters
@@ -150,8 +149,8 @@ def resample(self, xx, inplace=False,
             for details.
         res_fxn : function, optional
             Define a custom resampling function. It should accept an
-            ndarray of resampling locations and return the
-            interpolated y-coordinates as an iterable.
+            ndarray of resampling x-coordinates and return the
+            interpolated y-coordinates as an ndarray.
 
         Returns
         -------
@@ -163,6 +162,8 @@ def resample(self, xx, inplace=False,
         xx = np.array(xx, dtype=np.double)
 
         if res_fxn is None:
+            if interp1d_kwargs is None:
+                interp1d_kwargs = {"kind": "cubic"}
             res_fxn = self.resample_function(self._x,
                                              self._y,
                                              **interp1d_kwargs)
@@ -172,3 +173,28 @@ def resample(self, xx, inplace=False,
             self._x, self._y = xx, yy
         else:
             return (xx, yy)
+
+    def __eq__(self, other):
+        """Compare whether two curve objects are equal."""
+        if not isinstance(other, Curve):
+            return False
+
+        for attr in ["_x", "_y"]:
+            my = getattr(self, attr)
+            ur = getattr(other, attr)
+
+            if my.size != ur.size:
+                return False
+
+            if not np.allclose(my, ur):
+                return False
+
+        return True
+
+    def __repr__(self):
+        """Unambiguous representation of a `Curve` object."""
+        return f"Curve(x={self._x}, y={self._y})"
+
+    def __str__(self):
+        """Human-readable representation of a `Curve` object."""
+        return f"Curve with {self._x.size} points."

swprepost/curveuncertain.py

@@ -23,7 +23,7 @@
 
 
 class CurveUncertain(Curve):
-    """Curve object with aribtrary uncertainty in terms of x and y.
+    """Curve object with arbitrary uncertainty in terms of x and y.
 
     Attributes
     ----------
@@ -34,6 +34,22 @@ class CurveUncertain(Curve):
 
     """
 
+    @staticmethod
+    def _check_error(error, npts):
+        """Check error is compatable, specifically:
+
+            1. Can be cast to a ndarray.
+            2. Error has same length of the curve.
+
+        """
+        error = np.array(error, dtype=np.double)
+
+        if error.size != npts:
+            msg = f"Size of error and curve must match exactly. {error.size} != {npts}."
+            raise IndexError(msg)
+
+        return error
+
     def __init__(self, x, y, yerr=None, xerr=None):
         """Initialize a new `CurveUncertain` object.
 
@@ -58,25 +74,17 @@ def __init__(self, x, y, yerr=None, xerr=None):
             provided) are inconsistent.
 
         """
-        # Pass x, y to `Curve` constuctor.
+        # Pass x, y to `Curve`.
         super().__init__(x, y)
 
         # Handle x-error and y-error.
-        for attr, attr_name, attr_bool in zip([yerr, xerr],
-                                              ["_yerr", "_xerr"],
-                                              ["_isyerr", "_isxerr"]):
-            if attr is None:
-                setattr(self, attr_bool, False)
-            else:
-                setattr(self, attr_bool, True)
-                setattr(self, attr_name, np.array(attr))
-
-                if self._x.size != getattr(self, attr_name).size:
-                    msg = "Size of the curve's attributes must be consistent."
-                    raise IndexError(msg)
+        npts = self._x.size
+        self._yerr = None if yerr is None else self._check_error(yerr, npts)
+        self._xerr = None if xerr is None else self._check_error(xerr, npts)
+        self._isyerr = False if yerr is None else True
+        self._isxerr = False if xerr is None else True
 
-    def resample(self, xx, inplace=False,
-                 res_fxn=None, res_fxn_xerr=None, res_fxn_yerr=None):
+    def resample(self, xx, inplace=False, interp1d_kwargs=None, res_fxn=None):
         """Resample curve and its associated uncertainty.
 
         Parameters
@@ -85,42 +93,59 @@ def resample(self, xx, inplace=False,
             Desired x values after resampling.
         inplace : bool, optional
             Indicates whether resampling is performed inplace and
-            the objects attributes are updated or if calculated 
+            the objects attributes are updated or if calculated
             values are returned.
-        res_fxn, res_fxn_xerr, res_fxn_yerr : function, optional
+        interp1d_settings : dict, optional
+            Settings for use with the `interp1d` function from `scipy`.
+            See documentation `here
+            <https://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.interp1d.html>`_
+            for details.
+        res_fxn : tuple of functions, optional
             Functions to define the resampling of the central
             x and y values, xerr and yerr respectively, default is
             `None` indicating default resampling function is used.
 
         Returns
-        -------          
+        -------
         None or Tuple
             If `inplace=True`, returns `None`, instead update
             attributes `_x`, `_y`, `_xerr`, and `_yerr` if they exist.
             If `inplace=False`, returns `Tuple` of the form
             `(xx, yy, yyerr, xxerr)`. If `xerr` and/or `yerr` are not
-            defined they are not resampled and ommited from the return
+            defined they are not resampled and omitted from the return
             statement.
 
         """
-        # Create resample functions before resampling mean curve
+        # Unpack res_fxn
+        if res_fxn is None:
+            res_fxn_xerr, res_fxn_yerr = None, None
+        else:
+            res_fxn, res_fxn_xerr, res_fxn_yerr = res_fxn
+
+        # Default interpolation kwargs
+        if interp1d_kwargs is None:
+            interp1d_kwargs = {"kind": "cubic"}
+
+        # Define error resampling first.
         if self._isyerr and res_fxn_yerr is None:
-            res_fxn_yerr = super().resample_function(self._x, self._yerr,
-                                                     kind="cubic")
+            res_fxn_yerr = super().resample_function(self._x,
+                                                     self._yerr,
+                                                     **interp1d_kwargs)
         if self._isxerr and res_fxn_xerr is None:
-            res_fxn_xerr = super().resample_function(self._x, self._xerr,
-                                                     kind="cubic")
+            res_fxn_xerr = super().resample_function(self._x,
+                                                     self._xerr,
+                                                     **interp1d_kwargs)
 
         # Resample mean curve
         new_mean_curve = super().resample(xx=xx, inplace=inplace,
+                                          interp1d_kwargs=interp1d_kwargs,
                                           res_fxn=res_fxn)
-
-        # Resample error
         if inplace:
             xx = self._x
         else:
             xx, yy = new_mean_curve
 
+        # Resample error
         if self._isyerr:
             yerr = res_fxn_yerr(xx)
         if self._isxerr:

swprepost/dispersionset.py

@@ -107,6 +107,8 @@ def _parse_dcs(cls, dcs_data, nmodes="all"):
 
         if nmodes == "all":
             modes = modes[1:]
+        elif nmodes == 0:
+            return None
         else:
             modes = modes[1:nmodes+1]
 

swprepost/dispersionsuite.py

@@ -92,21 +92,7 @@ def append(self, dispersionset, sort=True):
 
         """
         self.check_input(dispersionset, DispersionSet)
-        super().append(dispersionset, sort=sort)
-
-    @property
-    def size(self):
-        return len(self._items)
-
-    # @property
-    # def ids(self):
-    #     """Return the ids corresponding to `sets`."""
-    #     return [cset.identifier for cset in self.sets]
-
-    # @property
-    # def misfits(self):
-    #     """Return the misfits corresponding to `sets`."""
-    #     return [cset.misfit for cset in self.sets]
+        super()._append(dispersionset, sort=sort)
 
     @classmethod
     def from_geopsy(cls, fname, nsets="all", nrayleigh="all", nlove="all",
@@ -144,25 +130,26 @@ def from_geopsy(cls, fname, nsets="all", nrayleigh="all", nlove="all",
         for model_info in regex.dcset.finditer(lines):
             identifier, misfit, wave_type, data = model_info.groups()
 
+            # Encountered new model, save previous and reset.
             if identifier != previous_id and previous_id != "start":
+                if model_count+1 == nsets:
+                    break
+
                 dc_sets.append(cls._dcset()(previous_id,
                                             float(previous_misfit),
                                             rayleigh=rayleigh, love=love))
                 model_count += 1
                 rayleigh, love = None, None
 
+            # Parse data.
             if wave_type == "Rayleigh":
                 rayleigh = cls._dcset()._parse_dcs(data, nmodes=nrayleigh)
             elif wave_type == "Love":
                 love = cls._dcset()._parse_dcs(data, nmodes=nlove)
             else:
                 raise NotImplementedError
 
-            previous_id = identifier
-            previous_misfit = misfit
-
-            if model_count + 1 == nsets:
-                break
+            previous_id, previous_misfit = identifier, misfit
 
         dc_sets.append(cls._dcset()(previous_id,
                                     float(previous_misfit),
@@ -190,7 +177,7 @@ def from_list(cls, dc_sets, sort=True):
         Returns
         -------
         DipsersionSuite
-            Instatiated `DispersionSuite` object.
+            Instantiated `DispersionSuite` object.
 
         """
         obj = cls(dc_sets[0])
@@ -218,7 +205,7 @@ def write_to_txt(self, fname, nbest="all"):
         """
         nbest = self._handle_nbest(nbest)
         with open(fname, "w") as f:
-            f.write("# File written by swipp\n")
+            f.write("# File written by swprepost\n")
             for cit in self.sets[:nbest]:
                 cit.write_set(f)