Merge pull request #143 from florisvb/make-backers-public

Make backers public

Author: pavelkomarov

docs/source/code.rst

@@ -5,10 +5,9 @@ API documentation
    :maxdepth: 1
 
    finite_difference
-   kalman_smooth
-   linear_model
    smooth_finite_difference
    total_variation_regularization
+   kalman_smooth
+   linear_model
    optimize
    utils
-

docs/source/finite_difference.rst

@@ -2,4 +2,9 @@ finite_difference
 =================
 
 .. automodule:: pynumdiff.finite_difference
-    :members:
+    :no-members:
+
+.. autofunction:: pynumdiff.finite_difference.finite_difference
+.. autofunction:: pynumdiff.finite_difference.first_order
+.. autofunction:: pynumdiff.finite_difference.second_order
+.. autofunction:: pynumdiff.finite_difference.fourth_order

docs/source/kalman_smooth.rst

@@ -2,4 +2,10 @@ kalman_smooth
 =============
 
 .. automodule:: pynumdiff.kalman_smooth
-    :members:
+    :no-members:
+
+.. autofunction:: pynumdiff.kalman_smooth.rts_const_deriv
+.. autofunction:: pynumdiff.kalman_smooth.constant_velocity
+.. autofunction:: pynumdiff.kalman_smooth.constant_acceleration
+.. autofunction:: pynumdiff.kalman_smooth.constant_jerk
+.. autofunction:: pynumdiff.kalman_smooth.known_dynamics

docs/source/total_variation_regularization.rst

@@ -2,4 +2,12 @@ total_variation_regularization
 ==============================
 
 .. automodule:: pynumdiff.total_variation_regularization
-    :members:
+   :no-members:
+
+.. autofunction:: pynumdiff.total_variation_regularization.tvrdiff
+.. autofunction:: pynumdiff.total_variation_regularization.velocity
+.. autofunction:: pynumdiff.total_variation_regularization.acceleration
+.. autofunction:: pynumdiff.total_variation_regularization.jerk
+.. autofunction:: pynumdiff.total_variation_regularization.iterative_velocity
+.. autofunction:: pynumdiff.total_variation_regularization.smooth_acceleration
+.. autofunction:: pynumdiff.total_variation_regularization.jerk_sliding

examples/1_basic_tutorial.ipynb

@@ -1,5 +1,3 @@
 """This module implements some common finite difference schemes
 """
-from ._finite_difference import first_order, second_order, fourth_order
-
-__all__ = ['first_order', 'second_order', 'fourth_order'] # So these get treated as direct members of the module by sphinx
+from ._finite_difference import finite_difference, first_order, second_order, fourth_order

examples/2a_optimizing_parameters_with_dxdt_known.ipynb

@@ -4,11 +4,15 @@
 from warnings import warn
 
 
-def _finite_difference(x, dt, num_iterations, order):
-    """Helper for all finite difference methods, since their iteration structure is all the same.
+def finite_difference(x, dt, num_iterations, order):
+    """Perform iterated finite difference of a given order. This serves as the common backing function for
+    all other methods in this module.
     
+    :param np.array[float] x: data to differentiate
+    :param float dt: step size
+    :param int num_iterations: number of iterations. If >1, the derivative is integrated with trapezoidal
+            rule, that result is finite-differenced again, and the cycle is repeated num_iterations-1 times
     :param int order: 1, 2, or 4, controls which finite differencing scheme to employ
-    For other parameters and return values, see public function docstrings
     """
     if num_iterations < 1: raise ValueError("num_iterations must be >0")
     if order not in [1, 2, 4]: raise ValueError("order must be 1, 2, or 4")
@@ -61,7 +65,7 @@ def _finite_difference(x, dt, num_iterations, order):
 
 
 def first_order(x, dt, params=None, options={}, num_iterations=1):
-    """First-order centered difference method
+    """First-order difference method
 
     :param np.array[float] x: data to differentiate
     :param float dt: step size
@@ -81,7 +85,7 @@ def first_order(x, dt, params=None, options={}, num_iterations=1):
         warn("`params` and `options` parameters will be removed in a future version. Use `num_iterations` instead.", DeprecationWarning)
         num_iterations = params[0] if isinstance(params, list) else params
 
-    return _finite_difference(x, dt, num_iterations, 1)
+    return finite_difference(x, dt, num_iterations, 1)
 
 
 def second_order(x, dt, num_iterations=1):
@@ -96,7 +100,7 @@ def second_order(x, dt, num_iterations=1):
              - **x_hat** -- original x if :code:`num_iterations=1`, else smoothed x that yielded dxdt_hat
              - **dxdt_hat** -- estimated derivative of x
     """
-    return _finite_difference(x, dt, num_iterations, 2)
+    return finite_difference(x, dt, num_iterations, 2)
 
 
 def fourth_order(x, dt, num_iterations=1):
@@ -111,4 +115,4 @@ def fourth_order(x, dt, num_iterations=1):
              - **x_hat** -- original x if :code:`num_iterations=1`, else smoothed x that yielded dxdt_hat
              - **dxdt_hat** -- estimated derivative of x
     """
-    return _finite_difference(x, dt, num_iterations, 4)
+    return finite_difference(x, dt, num_iterations, 4)