Fix typos

CONTRIBUTING.rst

@@ -40,9 +40,9 @@ $ python -m unittest
 Documentation
 =============
 
-Each new feature should be documented in the documentation. The documention is stored under the directory``docs/``.
+Each new feature should be documented in the documentation. The documentation is stored under the directory``docs/``.
 
-You can build the docmentation in HTML format locally using Sphinx::
+You can build the documentation in HTML format locally using Sphinx::
 
 $ cd docs
 $ make html

sigpy/__init__.py

@@ -5,7 +5,7 @@
 All functions, except wavelet transform, can run on both CPU and GPU.
 
 These functions are wrapped into higher level classes (Linop and Prox)
-that can be used in conjuction with Alg to form an App.
+that can be used in conjunction with Alg to form an App.
 
 """
 from sigpy import (

sigpy/alg.py

@@ -387,7 +387,7 @@ def _update(self):
             util.axpy(self.x, -self.tau, self.AH(self.u))
             backend.copyto(self.x, self.proxg(self.tau, self.x))
 
-        # Update step-size if neccessary.
+        # Update step-size if necessary.
         if self.gamma_primal > 0 and self.gamma_dual == 0:
             with self.x_device:
                 xp = self.x_device.xp
@@ -425,7 +425,7 @@ class AltMin(Alg):
 
     Args:
         min1 (function): Function to minimize over variable 1.
-        min2 (function): Funciton to minimize over variable 2.
+        min2 (function): Function to minimize over variable 2.
         max_iter (int): Maximum number of iterations.
 
     """

sigpy/app.py

@@ -525,7 +525,7 @@ def objective(self):
 
 
 class L2ConstrainedMinimization(App):
-    r"""L2 contrained minimization application.
+    r"""L2 constrained minimization application.
 
     Solves for problem:
 

sigpy/linop.py

@@ -264,7 +264,7 @@ def _adjoint_linop(self):
 
 
 class AllReduceAdjoint(Linop):
-    """All reduce adjoint operator. Equivalant to identity.
+    """All reduce adjoint operator. Equivalent to identity.
 
     Args:
         shape (tuple of ints): Input/output shape.
@@ -460,7 +460,7 @@ class Hstack(Linop):
 
     Creates a Linop that splits the input, applies Linops independently,
     and sums outputs.
-    In matrix form, this is equivalant to given matrices {A1, ..., An},
+    In matrix form, this is equivalent to given matrices {A1, ..., An},
     returns [A1, ..., An].
 
     Input and output devices must be the same.
@@ -553,7 +553,7 @@ class Vstack(Linop):
 
     Creates a Linop that applies linops independently,
     and concatenates outputs.
-    In matrix form, this is equivalant to given matrices {A1, ..., An},
+    In matrix form, this is equivalent to given matrices {A1, ..., An},
     returns [A1.T, ..., An.T].T.
 
     Args:
@@ -722,7 +722,7 @@ def _normal_linop(self):
 
 
 class Transpose(Linop):
-    """Tranpose input with the given axes.
+    """Transpose input with the given axes.
 
     Args:
         ishape (tuple of ints): Input shape.

sigpy/mri/rf/multiband.py

@@ -302,7 +302,7 @@ def dz_pins(
     """
 
     kz_width = tb / sl_thick  # 1/cm, width in k-space we must go
-    # calcualte number of subpulses (odd)
+    # calculate number of subpulses (odd)
     n_pulses = int(2 * np.floor(np.ceil(kz_width / (1 / sl_sep)) / 2))
     # call SLR to get envelope
     rf_soft = slr.dzrf(n_pulses, tb, ptype, ftype, d1, d2)

sigpy/mri/rf/optcont.py

@@ -94,7 +94,7 @@ def deriv(rf, x, g, auxa, auxb, af, bf):
             ar = ar * z
             br = br * z
 
-            # strip off the curent rf rotation from forward sim
+            # strip off the current rf rotation from forward sim
             c = xp.cos(xp.abs(rf[mm]) / 2)
             s = 1j * xp.exp(1j * xp.angle(rf[mm])) * xp.sin(xp.abs(rf[mm]) / 2)
             at = af * c + bf * xp.conj(s)

sigpy/mri/rf/slr.py

@@ -602,7 +602,7 @@ def root_flip(b, d1, flip, tb, verbose=False):
         d1 (float): passband ripple level.
         flip (array): target flip angle.
         tb (int): pulse time bandwidth product.
-        verbose (bool): print feeback on iterations.
+        verbose (bool): print feedback on iterations.
 
     Returns:
         2-element tuple containing

sigpy/mri/rf/trajgrad.py

@@ -862,7 +862,7 @@ def sdotmax(
         # Given a k-space curve C (in [1/cm] units), maximum gradient amplitude
         # (in G/cm) and maximum slew-rate (in G/(cm*ms)).
         # This function calculates the upper bound for the time parametrization
-        # sdot (which is a non scaled max gradient constaint) as a function
+        # sdot (which is a non scaled max gradient constraint) as a function
         # of s.
         #
         #   cs      --  spline polynomial
@@ -894,12 +894,12 @@ def sdotmax(
 
         return sdot, k
 
-    # Curve in arbitrary paramater space, cubic spline
+    # Curve in arbitrary parameter space, cubic spline
     num_p = c.shape[0]
     p = np.linspace(0, 1, num_p, endpoint=True)
     cp = interpolate.CubicSpline(p, c, axis=0)
 
-    # Integrate absolute value to find length and s(arc) vs p(paramater)
+    # Integrate absolute value to find length and s(arc) vs p(parameter)
     cp1_spline = cp.derivative()
     p_highres = np.linspace(0, 1, num_p * 10)
     cp1_highres = cp1_spline(p_highres)

sigpy/mri/sim.py

@@ -7,7 +7,7 @@
 
 
 def birdcage_maps(shape, r=1.5, nzz=8, dtype=np.complex128):
-    """Simulates birdcage coil sensitivies.
+    """Simulates birdcage coil sensitivities.
 
     Args:
         shape (tuple of ints): sensitivity maps shape,

sigpy/prox.py

@@ -84,7 +84,7 @@ def _prox(self, alpha, input):
 
 
 class NoOp(Prox):
-    r"""Proximal operator for empty function. Equivalant to an identity function.
+    r"""Proximal operator for empty function. Equivalent to an identity function.
 
     Args:
        shape (tuple of ints): Input shape

sigpy/thresh.py

@@ -138,7 +138,7 @@ def linf_proj(eps, input, bias=None):
 
 
 def psd_proj(input):
-    """Projection onto postiive semi-definite matrices.
+    """Projection onto positive semi-definite matrices.
 
     Args:
         input (array): a two-dimensional matrix.

sigpy/util.py

@@ -92,7 +92,7 @@ def split(vec, oshapes):
         oshapes (list of tuple of ints): Output shapes.
 
     Returns:
-        list of arrays: Splitted outputs.
+        list of arrays: Split outputs.
     """
     outputs = []
     for oshape in oshapes: