Minor Docstring cleanups

pycroscopy/analysis/fit_methods.py

@@ -28,6 +28,7 @@ class Fit_Methods(object):
 
         Parameters
         -----------
+        freq_vector : numpy.ndarray
         args : list or tuple
             SHO parameters=(Amp,w0,Q,phi,vector). vector: 1D np.array of frequency values.
             Amp: amplitude.

pycroscopy/analysis/utils/atom_finding_general_gaussian.py

@@ -89,7 +89,7 @@ def gauss2d(X, Y, *parms, **kwargs):
     X, Y : the x and y matrix values from the call "X, Y = np.meshgrid(x,y)" where x and y are
         defined by x = np.arange(-width/2,width/2) and y = np.arange(-height/2,height/2). 
 
-    params: List of 7 parameters defining the gaussian.
+    parms: List of 7 parameters defining the gaussian.
         The parameters are [A, x0, y0, sigma_x, sigma_y, theta, background]
             A : amplitude
             x0: x position
@@ -497,8 +497,6 @@ class Gauss_Fit(object):
         Parameters
         ----------
 
-            None
-
         Returns
         -------
 

pycroscopy/analysis/utils/be_sho.py

@@ -125,8 +125,8 @@ def SHOfastGuess(w_vec, resp_vec, qual_factor=200):
         Quality factor of the SHO peak
 
     Returns
+    -------
     retval : 1D numpy array
-    ---------
         SHO fit parameters arranged as [amplitude, frequency, quality factor, phase]
     """
     amp_vec = abs(resp_vec)

pycroscopy/io/io_utils.py

@@ -30,7 +30,7 @@ def uiGetFile(filter='H5 file (*.h5)', caption='Select File'):
 
     Parameters
     ----------
-    extension : String or list of strings
+    filter : String or list of strings
         file extensions to look for
     caption : (Optional) String
         Title for the file browser window
@@ -84,7 +84,6 @@ def getTimeStamp():
 
     Parameters
     ----------
-    None
 
     Returns
     -------
@@ -101,7 +100,6 @@ def getAvailableMem():
 
     Parameters
     ----------
-    None
 
     Returns
     -------

pycroscopy/io/microdata.py

@@ -91,13 +91,6 @@ class MicroDataGroup(MicroData):
         """
         Return the tree structure given by MicroDataGroup.
         
-        Parameters
-        ----------
-        None
-        
-        Returns
-        -------
-        None
         """
 
         def __tree(child, parent):

pycroscopy/io/translators/df_utils/be_utils.py

@@ -341,6 +341,9 @@ def generatePlotGroups(h5_main, hdf, mean_resp, folder_path, basename, max_resp=
     do_histogram : Boolean (Optional. Default = False)
         Whether or not to generate hisograms. 
         Caution - Histograms can take a fair amount of time to compute.
+    debug : Boolean, Optional
+        If True, then extra debug statements are printed.
+        Default False
     """
 
     grp = h5_main.parent
@@ -1287,9 +1290,15 @@ class BEHistogram():
 
         Parameters
         ----------
-            h5_path : hdf5 reference to Main_Dataset
+        h5_main : hdf5.Dataset
+        max_response : list
+        min_response : list
+        max_mem_mb : int
+        max_bins : int
+        debug : bool
 
-        Outputs:
+        Returns
+        -------
 
         """
 
@@ -1353,13 +1362,13 @@ class BEHistogram():
         ----------
         h5_main : HDF5 Dataset object
             Dataset to be historammed
-        activ_spec_steps : numpy array
+        active_spec_steps : numpy array
             active spectral steps in the current plot group
         max_response : numpy array
             maximum amplitude at each pixel
         min_response : numpy array
             minimum amplitude at each pixel
-        max_mem : Unsigned integer
+        max_mem_mb : Unsigned integer
             maximum number of Mb allowed for use.  Used to calculate the
             number of pixels to load in a chunk
         max_bins : integer

pycroscopy/io/translators/df_utils/io_image.py

@@ -88,6 +88,7 @@ def unnest_parm_dicts(image_parms, prefix=''):
     Parameters
     ----------
     image_parms : dict
+    prefix : str
 
     Returns
     -------

pycroscopy/io/translators/time_series.py

@@ -54,6 +54,9 @@ class MovieTranslator(Translator):
         start_image : int, optional
             Integer denoting which image in the file path should be considered the starting
             point.  Default is 0, start with the first image on the list.
+        image_type : str, optional
+            File extension of images to load.  Used to filter out other files in the same
+            directory.  Default .tif
 
         Returns
         ----------

pycroscopy/processing/atom_finding.py

@@ -811,7 +811,7 @@ def return_pos(file_in_h5, img_num):
     image_path = "/Frame_%04i/Channel_Finished" % (img_num)
     type_ref = type(main_h5_handle.get(image_path))
     temp = 1
-    x = -1;
+    x = -1
     while temp:
         x = x + 1
         image_path = "%s/Filter_Step_%04i" % (image_path, x)
@@ -890,7 +890,7 @@ def run_PCA_atoms(file_in_h5, img_num, box_width):
                         box_width <= pos[k1, 1].round() <= len(img[0, :]) - box_width):
             sel_vec[k1] = 1
             new_pos.append(pos[k1, :])
-            vector = img[pos[k1, 0] - box_width:pos[k1, 0] + box_width, pos[k1, 1] - box_width:pos[k1, 1] + box_width];
+            vector = img[pos[k1, 0] - box_width:pos[k1, 0] + box_width, pos[k1, 1] - box_width:pos[k1, 1] + box_width]
             img_vectors.append(vector.reshape([(box_width * 2) ** 2]))
 
     new_pos = array(new_pos)

pycroscopy/processing/fft.py

@@ -136,7 +136,12 @@ def noiseBandFilter(num_pts, samp_rate, freqs, freq_widths, show_plots=False):
         Target frequencies as unsigned ints    
     freq_widths : 1D array or list
         Width around the target frequency that should be set to 0\n    
-    Note: sampRate, freqs, freq_widths have same units - eg MHz
+    show_plots : bool
+        If True, plots will be displayed during calculation.  Default False
+
+    Note
+    ----
+    sampRate, freqs, freq_widths have same units - eg MHz
     
     Returns
     -------

pycroscopy/processing/proc_utils.py

@@ -39,6 +39,8 @@ def buildHistogram(x_hist, data_mat, N_x_bins, N_y_bins, weighting_vec=1, min_re
     func : function
         function to be used to bin data_vec.  All functions should take as input data_vec.
         Arguments should be passed properly to func.  This has not been heavily tested.
+    debug : bool, optional
+        If True, extra debugging statements are printed.  Default False
 
     Returns
     -------

pycroscopy/processing/process.py

@@ -111,13 +111,6 @@ class Process(object):
         Parameters
         ----------
         func
-        strategy: string
-            Default is 'Wavelet_Peaks'.
-            Can be one of ['wavelet_peaks', 'relative_maximum', 'gaussian_processes'].
-            For updated list, run GuessMethods.methods
-        options: dict
-            Default {"peaks_widths": np.array([10,200])}}.
-            Dictionary of options passed to strategy. For more info see GuessMethods documentation.
 
         kwargs:
             processors: int

pycroscopy/viz/plot_utils.py

@@ -558,14 +558,14 @@ def plot_complex_loop_stack(loop_stack, x_axis, heading='BE Loops', subtitle='Ei
         Loops rearranged as - [component, points]
     x_axis : 1D real numpy array
         The vector to plot against
+    heading : str
+        Title to plot above everything else
+    subtitle : str
+        Subtile to of Figure
     num_comps : int
         Number of components to plot
-    title : String
-        Title to plot above everything else
-    x_label : String
+    x_label : str
         Label for x axis
-    stdevs : int
-        Number of standard deviations to consider for plotting
 
     Returns
     ---------
@@ -601,6 +601,8 @@ def plotScree(scree, title='Scree'):
     -------------
     scree : 1D real numpy array
         The scree vector from SVD
+    title : str
+        Figure title.  Default Scree
 
     Returns
     ---------
@@ -637,6 +639,10 @@ def plot_map_stack(map_stack, num_comps=9, stdevs=2, color_bar_mode=None, evenly
         Number of standard deviations to consider for plotting
     color_bar_mode : String, Optional
         Options are None, single or each. Default None
+    evenly_spaced : bool
+        Default False
+    reverse_dims : Boolean (Optional)
+        Set this to False to accept data structured as [component, rows, cols]
     title : String or list of strings
         The titles for each of the plots.
         If a single string is provided, the plot titles become ['title 01', title 02', ...].
@@ -650,8 +656,6 @@ def plot_map_stack(map_stack, num_comps=9, stdevs=2, color_bar_mode=None, evenly
         Multipliers for the axis padding between plots in the stack.  Padding is calculated as
         (pad_mult[0]*fig_mult[1], pad_mult[1]*fig_mult[0]) for the width and height padding respectively.
         Default (0.1, 0.07)
-    reverse_dims : Boolean (Optional)
-        Set this to False to accept data structured as [component, rows, cols]
     kwargs : dictionary
         Keyword arguments to be passed to either matplotlib.pyplot.figure, mpl_toolkits.axes_grid1.ImageGrid, or
         pycroscopy.vis.plot_utils.plot_map.  See specific function documentation for the relavent options.
@@ -1286,7 +1290,6 @@ def plot_image_cleaning_results(raw_image, clean_image, stdevs=2, heading='Image
     raw_image
     clean_image
     stdevs
-    color_bar_mode
     fig_mult
     fig_args
     heading