Merge pull request #4 from jpvantassel/dev

In preparation for v1.0.0 release
jpvantassel · Nov 5, 2021 · df5e40d · df5e40d
2 parents c1cfad9 + e3709af
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diff --git a/README.md b/README.md
@@ -3,11 +3,13 @@
 > Joseph P. Vantassel, The University of Texas at Austin
 
 [![DOI](https://zenodo.org/badge/222287042.svg)](https://zenodo.org/badge/latestdoi/222287042)
+[![PyPI - License](https://img.shields.io/pypi/l/hvsrpy)](https://github.com/jpvantassel/swprepost/blob/main/LICENSE.txt)
 [![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&amp;utm_medium=referral&amp;utm_content=jpvantassel/swprepost&amp;utm_campaign=Badge_Grade)
-[![codecov](https://codecov.io/gh/jpvantassel/swprepost/branch/master/graph/badge.svg)](https://codecov.io/gh/jpvantassel/swprepost)
+[![codecov](https://codecov.io/gh/jpvantassel/swprepost/branch/main/graph/badge.svg?token=N5kQxjr2RB)](https://codecov.io/gh/jpvantassel/swprepost)
+![PyPI - Python Version](https://img.shields.io/pypi/pyversions/swprepost)
 
 ## Table of Contents
 
@@ -40,8 +42,8 @@ following:
 
 _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)._
+_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 and rigorous workflow for
@@ -116,11 +118,11 @@ plt.show()
 so. A detailed set of instructions can be found
 [here](https://jpvantassel.github.io/python3-course/#/intro/installing_python).
 
-2.  If you have not installed `swprepost` previously use
+2.  If you have not installed _swprepost_ previously use
 `pip install swprepost`. If you are not familiar with `pip`, a useful tutorial
 can be found [here](https://jpvantassel.github.io/python3-course/#/intro/pip).
 If you have an earlier version and would like to upgrade to the latest version
-of `swprepost` use `pip install swprepost --upgrade`.
+of _swprepost_ use `pip install swprepost --upgrade`.
 
 3.  Confirm that `swprepost` has installed/updated successfully by examining the
 last few lines of text displayed in the console.
@@ -133,13 +135,13 @@ last few lines of text displayed in the console.
 
 2.  Explore the Jupyter notebooks in the
   [basic](https://github.com/jpvantassel/swprepost/tree/main/examples/basic)
-  directory for a no-coding-required introduction to the `swprepost` package.
+  directory for a no-coding-required introduction to the _swprepost_ package.
   If you have not installed `Jupyter`, detailed instructions can be found
   [here](https://jpvantassel.github.io/python3-course/#/intro/installing_jupyter).
 
 3.  Move to the [adv](https://github.com/jpvantassel/swprepost/tree/main/examples/adv)
-  directory and follow the Jupyter notebook title `SWinvertWorkflow.ipynb` for
-  an example application of `swprepost` to the SWinvert workflow
+  directory and follow the Jupyter notebook title `example_swinvert_workflow.ipynb` for
+  an example application of _swprepost_ to the SWinvert workflow
   (Vantassel and Cox, 2021).
 
 4.  Enjoy!
diff --git a/swprepost/dispersioncurve.py b/swprepost/dispersioncurve.py
@@ -76,7 +76,7 @@ def _parse_dc(cls, dc_data):
         ----------
         dc_data : str
             Dispersion curve data of the form `frequency, slowness`.
-            It is assumed that frequencies increases monitonically. If
+            It is assumed that frequencies increases monotonically. If
             this assumption is not true, incorrect results will result.
             See example below.
 

diff --git a/swprepost/groundmodel.py b/swprepost/groundmodel.py
@@ -15,7 +15,7 @@
 #     You should have received a copy of the GNU General Public License
 #     along with this program.  If not, see <https: //www.gnu.org/licenses/>.
 
-"""GroundModel class definiton."""
+"""GroundModel class definition."""
 
 import logging
 
@@ -85,7 +85,7 @@ def check_input_value(**kwargs):
         Specifically:
         1. Check that all `GroundModel` parameters are greater than
         zero.
-        2. Check that identifer and misfit are greater than zero.
+        2. Check that identifier and misfit are greater than zero.
         3. Check that `vp` > `vs`.
 
         Parameters
@@ -357,7 +357,7 @@ def discretize(self, dmax, dy=0.5, parameter='vs'):
         dmax : float
             Maximum depth of discretization.
         dy : float, optional
-            Linear step of discretizaton in terms of depth, default
+            Linear step of discretization in terms of depth, default
             is 0.5 meter.
         parameter : {'vp', 'vs', 'rh', 'pr'}, optional
             Parameter to be discretized, default is 'vs'.
@@ -613,7 +613,7 @@ def write_to_txt(self, fname):
 
     @classmethod
     def _gm(cls):
-        """Helper to allow conveinient subclassing."""
+        """Helper to allow convenient subclassing."""
         return GroundModel
 
     @classmethod
@@ -630,7 +630,7 @@ def _parse_gm(cls, gm_data, identifier, misfit):
             defining multiple GroundModels is provided only the first
             one is parsed.
         identifier : str
-            Indentifier string.
+            Identifier string.
         misfit : str
             Misfit string.
 

diff --git a/swprepost/groundmodelsuite.py b/swprepost/groundmodelsuite.py
@@ -335,9 +335,8 @@ def from_geopsy(cls, fname, nmodels="all", sort=False):
 
         """
         # TODO (jpv): Add warning if nsets < navailable.
-        # TODO (jpv): Strange if statement below.
         if nmodels == "all":
-            nmodels = 1E9
+            nmodels = np.inf
 
         with open(fname, "r") as f:
             lines = f.read()

diff --git a/swprepost/meta.py b/swprepost/meta.py
@@ -17,4 +17,4 @@
 
 """Metadata for swprepost."""
 
-__version__ = "1.0.0rc0"
+__version__ = "1.0.0"
diff --git a/swprepost/parameter.py b/swprepost/parameter.py
@@ -113,7 +113,7 @@ def __init__(self, lay_min, lay_max, par_min, par_max, par_rev,
             Indicate whether to allow parameter reversals, one
             `bool` per layer.
         lay_type : {'thickness', 'depth'}, optional
-            Inidcate whether the layers are defined in terms of
+            Indicate whether the layers are defined in terms of
             depth or thickness.
         """
         if lay_type == "thickness":
@@ -156,7 +156,7 @@ def from_fx(cls, value):
             raise TypeError(msg)
 
         if value <= 0:
-            raise ValueError("`value` must be postive.")
+            raise ValueError("`value` must be positive.")
 
         obj = cls(lay_min=[1824], lay_max=[1883],
                   par_min=[value], par_max=[value], par_rev=[False])
@@ -245,7 +245,7 @@ def depth_ftl(nlayers, thickness):
     def from_ftl(cls, nlayers, thickness, par_min, par_max, par_rev=False):
         """Alternate constructor to instantiate a `Parameter` using FTL.
 
-        Use Fixed Thickenss Layering (FTL) to define the
+        Use Fixed Thickness Layering (FTL) to define the
         parameterization.
 
         Parameters
@@ -294,12 +294,12 @@ def depth_ln_thickness(wmin, wmax, nlayers, depth_factor=2,
         ----------
         wmin, wmax : float
             Minimum and maximum measured wavelengths from the
-            fundemental mode Rayleigh wave dispersion respectively.
+            fundamental mode Rayleigh wave dispersion respectively.
         nlayers : int
             Desired number of layers.
         depth_factor : [float, int], optional
             Factor by which the maximum wavelength is
-            divided to estimate the maxium depth of profiling,
+            divided to estimate the maximum depth of profiling,
             default is 2.
         increasing : bool, optional
             Indicate whether the layering thickness should be
@@ -342,7 +342,7 @@ def from_ln_thickness(cls, wmin, wmax, nlayers, par_min, par_max, par_rev,
         ----------
         wmin, wmax : float
             Minimum and maximum measured wavelength from the
-            fundemental mode Rayleigh wave disperison.
+            fundamental mode Rayleigh wave disperison.
         nlayers : int
             Desired number of layers.
         par_min, par_max : float
@@ -353,15 +353,15 @@ def from_ln_thickness(cls, wmin, wmax, nlayers, par_min, par_max, par_rev,
             default is `False` (i.e., no reversal allowed).
         depth_factor : [float, int], optional
             Factor by which the maximum wavelength is
-            divided to estimate the maxium depth of profiling,
+            divided to estimate the maximum depth of profiling,
             default is 2.
         increasing : bool, optional
             Determines whether LN or LNI layering is used, default
             is `False` meaning LN is used.
         increasing_factor : float, optional
             Factor by which each subsequent layer must be thicker
             than the previous layer previous layer, default is 1.2.
-            Arguement is only used if `increasing=True`.
+            Argument is only used if `increasing=True`.
 
         Returns
         -------
@@ -398,12 +398,12 @@ def depth_ln_depth(wmin, wmax, nlayers, depth_factor=2):
         ----------
         wmin, wmax : float
             Minimum and maximum measured wavelength from the
-            fundemental mode Rayleigh wave disperison.
+            fundamental mode Rayleigh wave disperison.
         nlayers : int
             Desired number of layers.
         depth_factor : [float, int], optional
             Factor by which the maximum wavelength is
-            divided to estimate the maxium depth of profiling,
+            divided to estimate the maximum depth of profiling,
             default is 2.
 
         Returns
@@ -451,7 +451,7 @@ def from_ln_depth(cls, wmin, wmax, nlayers, par_min, par_max, par_rev,
         ----------
         wmin, wmax : float
             Minimum and maximum measured wavelength from the
-            fundemental mode Rayleigh wave disperison.
+            fundamental mode Rayleigh wave disperison.
         nlayers : int
             Desired number of layers.
         par_min, par_max : float
@@ -462,7 +462,7 @@ def from_ln_depth(cls, wmin, wmax, nlayers, par_min, par_max, par_rev,
             default is `False` (i.e., no reversal allowed).
         depth_factor : [float, int], optional
             Factor by which the maximum wavelength is
-            divided to estimate the maxium depth of profiling,
+            divided to estimate the maximum depth of profiling,
             default is 2.
 
         Returns
@@ -497,14 +497,14 @@ def depth_lr(wmin, wmax, lr, depth_factor=2):
         ----------
         wmin, wmax : float
             Minimum and maximum measured wavelength from the
-            fundemental mode Rayleigh wave dispersion.
+            fundamental mode Rayleigh wave dispersion.
         lr : float
             Layering Ratio, this controls the number of layers and
             their potential thicknesses, refer to Cox and Teague
             2016 for details.
         depth_factor : [float, int], optional
             Factor by which the maximum wavelength is
-            divided to estimate the maxium depth of profiling,
+            divided to estimate the maximum depth of profiling,
             default is 2.
 
         Returns
@@ -549,7 +549,7 @@ def depth_lr(wmin, wmax, lr, depth_factor=2):
             layer_maxdepth.append(dmax+1)  # Half-space
         # ---> Otherwise, extend the current last layer
         else:
-            # Extend the deepest potential depth of the bottomost layer
+            # Extend the deepest potential depth of the bottom-most layer
             # to dmax.
             layer_maxdepth[-2] = dmax
             # Set the old last layer to the half-space
@@ -568,7 +568,7 @@ def from_lr(cls, wmin, wmax, lr, par_min, par_max, par_rev,
         ----------
         wmin, wmax : float
             Minimum and maximum measured wavelength from the
-            fundemental mode Rayleigh wave dispersion.
+            fundamental mode Rayleigh wave dispersion.
         lr : float
             Layering Ratio, this controls the number of layers and
             their potential thicknesses, refer to Cox and Teague
@@ -581,7 +581,7 @@ def from_lr(cls, wmin, wmax, lr, par_min, par_max, par_rev,
             default is `False` (i.e., no reversal allowed).
         depth_factor : [float, int], optional
             Factor by which the maximum wavelength is
-            divided to estimate the maxium depth of profiling,
+            divided to estimate the maximum depth of profiling,
             default is 2.
 
         Returns
@@ -628,7 +628,7 @@ def from_parameter_and_link(cls, par_min, par_max, par_rev,
             Instantiated `Parameter` object to which you wish to link
             the current parameter. 
         ptype : {'vs', 'pr', 'rh', 'vp'}, optional
-            Inversion parameter, representated by the
+            Inversion parameter, represented by the
             `existing_parameter`, default is `vs`.
 
         Returns
@@ -666,7 +666,7 @@ def make_rectangle(left, right, upper, lower):
         return ([left, left, right, right],
                 [upper, lower, lower, upper])
 
-    def plot(self, ax=None, show_example=True):
+    def plot(self, ax=None, show_example=True): # pragma: no cover
         # TODO (jpv): Add docstring.
         if ax is None:
             ax_was_none = True

diff --git a/swprepost/parameterization.py b/swprepost/parameterization.py
@@ -129,7 +129,7 @@ def from_min_max(cls, vp, pr, vs, rh, wv, factor=2):
 
                 If type = 'LR' 
                     Layering follows the Layering Ratio, the next
-                    arguement is the layering ratio followed by
+                    argument is the layering ratio followed by
                     min, max, and bool.
 
                 Ex. ['LR', lr, min, max, reversal]
@@ -354,7 +354,7 @@ def from_param(cls, fname_prefix):
         Returns
         -------
         Parameterization
-            Instantitated `Parameterization` object.
+            Instantiated `Parameterization` object.
 
         Raises
         ------
Original file line number	Diff line number	Diff line change
Expand Up		@@ -17,4 +17,4 @@

		"""Metadata for swprepost."""

		__version__ = "1.0.0rc0"
		__version__ = "1.0.0"