From 17593b7764991ba257c0b2e73c77f47b96976a5f Mon Sep 17 00:00:00 2001
From: ryanhammonds <ryan.hammonds@utexas.edu>
Date: Tue, 12 Jan 2021 19:38:52 -0800
Subject: [PATCH 1/9] filter report added

---
 neurodsp/filt/checks.py | 51 +++++++++++++++++++++++++++++++++++++----
 neurodsp/filt/filter.py |  9 +++++---
 neurodsp/filt/fir.py    |  8 +++++--
 neurodsp/filt/iir.py    | 10 +++++---
 neurodsp/filt/utils.py  | 16 +++++++++++--
 5 files changed, 80 insertions(+), 14 deletions(-)

diff --git a/neurodsp/filt/checks.py b/neurodsp/filt/checks.py
index d6cef1b5..f1e76e56 100644
--- a/neurodsp/filt/checks.py
+++ b/neurodsp/filt/checks.py
@@ -90,7 +90,7 @@ def check_filter_definition(pass_type, f_range):
 
 
 def check_filter_properties(filter_coefs, a_vals, fs, pass_type, f_range,
-                            transitions=(-20, -3), verbose=True):
+                            transitions=(-20, -3), filt_type=None, verbose=True):
     """Check a filters properties, including pass band and transition band.
 
     Parameters
@@ -164,7 +164,8 @@ def check_filter_properties(filter_coefs, a_vals, fs, pass_type, f_range,
 
     # Compute pass & transition bandwidth
     pass_bw = compute_pass_band(fs, pass_type, f_range)
-    transition_bw = compute_transition_band(f_db, db, transitions[0], transitions[1])
+    transition_bw, f_range_trans = compute_transition_band(f_db, db, transitions[0], transitions[1],
+                                                           return_freqs=True)
 
     # Raise warning if transition bandwidth is too high
     if transition_bw > pass_bw:
@@ -174,8 +175,50 @@ def check_filter_properties(filter_coefs, a_vals, fs, pass_type, f_range,
 
     # Print out transition bandwidth and pass bandwidth to the user
     if verbose:
-        print('Transition bandwidth is {:.1f} Hz.'.format(transition_bw))
-        print('Pass/stop bandwidth is {:.1f} Hz.'.format(pass_bw))
+
+        # Filter type (high-pass, low-pass, band-pass, band-stop, FIR, IIR)
+        print('Pass Type: {pass_type}'.format(pass_type=pass_type))
+
+        # Cutoff frequency (including definition)
+        cutoff = round(np.min(f_range) + (0.5 * transition_bw), 3)
+        print('Cutoff (half-amplitude): {cutoff} Hz'.format(cutoff=cutoff))
+
+        # Filter order (or length)
+        print('Filter order: {order}'.format(order=len(f_db)-1))
+
+        # Roll-off or transition bandwidth
+        print('Transition bandwidth: {:.1f} Hz'.format(transition_bw))
+        print('Pass/stop bandwidth: {:.1f} Hz'.format(pass_bw))
+
+        # Passband ripple and stopband attenuation
+        pb_ripple = np.max(db[:np.where(f_db < f_range_trans[0])[0][-1]])
+        sb_atten = np.max(db[np.where(f_db > f_range_trans[1])[0][0]:])
+        print('Passband Ripple: {pb_ripple} db'.format(pb_ripple=pb_ripple))
+        print('Stopband Attenuation: {sb_atten} db'.format(sb_atten=sb_atten))
+
+        # Filter delay (zero-phase, linear-phase, non-linear phase)
+        if filt_type == 'FIR' and pass_type in ['bandstop', 'lowpass']:
+            filt_class = 'linear-phase'
+        elif filt_type == 'FIR' and pass_type in ['bandpass', 'highpass']:
+            filt_class = 'zero-phase'
+        elif filt_type == 'IIR':
+            filt_class = 'non-linear-phase'
+        else:
+            filt_class = None
+
+        if filt_type is not None:
+            print('Filter Class: {filt_class}'.format(filt_class=filt_class))
+
+        if filt_class == 'linear-phase':
+            print('Group Delay: {delay}s'.format(delay=(len(f_db)-1) / 2 * fs))
+        elif filt_class == 'zero-phase':
+            print('Group Delay: 0s')
+
+        # Direction of computation (one-pass forward/reverse, or two-pass forward and reverse)
+        if filt_type == 'FIR':
+            print('Direction: one-pass reverse.')
+        else:
+            print('Direction: two-pass forward and reverse')
 
     return passes
 
diff --git a/neurodsp/filt/filter.py b/neurodsp/filt/filter.py
index 1b56f11c..4f716db3 100644
--- a/neurodsp/filt/filter.py
+++ b/neurodsp/filt/filter.py
@@ -10,7 +10,8 @@
 
 def filter_signal(sig, fs, pass_type, f_range, filter_type='fir',
                   n_cycles=3, n_seconds=None, remove_edges=True, butterworth_order=None,
-                  print_transitions=False, plot_properties=False, return_filter=False):
+                  print_transitions=False, plot_properties=False, return_filter=False,
+                  verbose=False):
     """Apply a bandpass, bandstop, highpass, or lowpass filter to a neural signal.
 
     Parameters
@@ -52,6 +53,8 @@ def filter_signal(sig, fs, pass_type, f_range, filter_type='fir',
         If True, plot the properties of the filter, including frequency response and/or kernel.
     return_filter : bool, optional, default: False
         If True, return the filter coefficients.
+    verbose : bool, optional, default: False
+        If True, print out detailed filter information.
 
     Returns
     -------
@@ -74,12 +77,12 @@ def filter_signal(sig, fs, pass_type, f_range, filter_type='fir',
     if filter_type.lower() == 'fir':
         return filter_signal_fir(sig, fs, pass_type, f_range, n_cycles, n_seconds,
                                  remove_edges, print_transitions,
-                                 plot_properties, return_filter)
+                                 plot_properties, return_filter, verbose=verbose)
     elif filter_type.lower() == 'iir':
         _iir_checks(n_seconds, butterworth_order, remove_edges)
         return filter_signal_iir(sig, fs, pass_type, f_range, butterworth_order,
                                  print_transitions, plot_properties,
-                                 return_filter)
+                                 return_filter, verbose=verbose)
     else:
         raise ValueError('Filter type not understood.')
 
diff --git a/neurodsp/filt/fir.py b/neurodsp/filt/fir.py
index f3384015..6f0e1f29 100644
--- a/neurodsp/filt/fir.py
+++ b/neurodsp/filt/fir.py
@@ -14,7 +14,8 @@
 ###################################################################################################
 
 def filter_signal_fir(sig, fs, pass_type, f_range, n_cycles=3, n_seconds=None, remove_edges=True,
-                      print_transitions=False, plot_properties=False, return_filter=False):
+                      print_transitions=False, plot_properties=False, return_filter=False,
+                      verbose=False):
     """Apply an FIR filter to a signal.
 
     Parameters
@@ -48,6 +49,8 @@ def filter_signal_fir(sig, fs, pass_type, f_range, n_cycles=3, n_seconds=None, r
         If True, plot the properties of the filter, including frequency response and/or kernel.
     return_filter : bool, optional, default: False
         If True, return the filter coefficients of the FIR filter.
+    verbose : bool, optional, default: False
+        If True, print out detailed filter information.
 
     Returns
     -------
@@ -78,7 +81,8 @@ def filter_signal_fir(sig, fs, pass_type, f_range, n_cycles=3, n_seconds=None, r
     check_filter_length(sig.shape[-1], len(filter_coefs))
 
     # Check filter properties: compute transition bandwidth & run checks
-    check_filter_properties(filter_coefs, 1, fs, pass_type, f_range, verbose=print_transitions)
+    check_filter_properties(filter_coefs, 1, fs, pass_type, f_range, filt_type="FIR",
+                            verbose=np.any([print_transitions, verbose]))
 
     # Remove any NaN on the edges of 'sig'
     sig, sig_nans = remove_nans(sig)
diff --git a/neurodsp/filt/iir.py b/neurodsp/filt/iir.py
index 70161caf..aeddb6f7 100644
--- a/neurodsp/filt/iir.py
+++ b/neurodsp/filt/iir.py
@@ -1,5 +1,6 @@
 """Filter signals with IIR filters."""
 
+import numpy as np
 from scipy.signal import butter, sosfiltfilt
 
 from neurodsp.utils import remove_nans, restore_nans
@@ -10,8 +11,8 @@
 ###################################################################################################
 ###################################################################################################
 
-def filter_signal_iir(sig, fs, pass_type, f_range, butterworth_order,
-                      print_transitions=False, plot_properties=False, return_filter=False):
+def filter_signal_iir(sig, fs, pass_type, f_range, butterworth_order, print_transitions=False,
+                       plot_properties=False, return_filter=False, verbose=False):
     """Apply an IIR filter to a signal.
 
     Parameters
@@ -41,6 +42,8 @@ def filter_signal_iir(sig, fs, pass_type, f_range, butterworth_order,
         If True, plot the properties of the filter, including frequency response and/or kernel.
     return_filter : bool, optional, default: False
         If True, return the second order series coefficients of the IIR filter.
+    verbose : bool, optional, default: False
+        If True, print out detailed filter information.
 
     Returns
     -------
@@ -65,7 +68,8 @@ def filter_signal_iir(sig, fs, pass_type, f_range, butterworth_order,
     sos = design_iir_filter(fs, pass_type, f_range, butterworth_order)
 
     # Check filter properties: compute transition bandwidth & run checks
-    check_filter_properties(sos, None, fs, pass_type, f_range, verbose=print_transitions)
+    check_filter_properties(sos, None, fs, pass_type, f_range, filt_type="IIR",
+                            verbose=np.any([print_transitions, verbose]))
 
     # Remove any NaN on the edges of 'sig'
     sig, sig_nans = remove_nans(sig)
diff --git a/neurodsp/filt/utils.py b/neurodsp/filt/utils.py
index 93629bfe..dcc3aef8 100644
--- a/neurodsp/filt/utils.py
+++ b/neurodsp/filt/utils.py
@@ -136,7 +136,7 @@ def compute_pass_band(fs, pass_type, f_range):
     return pass_bw
 
 
-def compute_transition_band(f_db, db, low=-20, high=-3):
+def compute_transition_band(f_db, db, low=-20, high=-3, return_freqs=False):
     """Compute transition bandwidth of a filter.
 
     Parameters
@@ -149,11 +149,15 @@ def compute_transition_band(f_db, db, low=-20, high=-3):
         The lower limit that defines the transition band, in dB.
     high : float, optional, default: -3
         The upper limit that defines the transition band, in dB.
+    return_freqs : bool, optional, default: False
+        Whether to return a tuple of (lower, upper) frequency bounds for the transition band.
 
     Returns
     -------
     transition_band : float
         The transition bandwidth of the filter.
+    f_range : tuple of (float, float), optional, default: False
+        The lower and upper frequencies of the transition band.
 
     Examples
     --------
@@ -178,7 +182,15 @@ def compute_transition_band(f_db, db, low=-20, high=-3):
     # This gets the indices of transitions to the values in searched for range
     inds = np.where(np.diff(np.logical_and(db > low, db < high)))[0]
     # This steps through the indices, in pairs, selecting from the vector to select from
-    transition_band = np.max([(b - a) for a, b in zip(f_db[inds[0::2]], f_db[inds[1::2]])])
+    transition_pairs = [(a, b) for a, b in zip(f_db[inds[0::2]], f_db[inds[1::2]])]
+    pair_idx = np.argmax([(tran[1] - tran[0]) for tran in transition_pairs])
+    f_lo = transition_pairs[pair_idx][0]
+    f_hi = transition_pairs[pair_idx][1]
+    transition_band = f_hi - f_lo
+
+    if return_freqs:
+
+        return transition_band, (f_lo, f_hi)
 
     return transition_band
 

From 6a5695ef881a9635538a840958c696b2c94c8ff5 Mon Sep 17 00:00:00 2001
From: ryanhammonds <ryan.hammonds@utexas.edu>
Date: Wed, 13 Jan 2021 17:59:20 -0800
Subject: [PATCH 2/9] save_properties of a filt

---
 neurodsp/filt/checks.py            |  68 ++++++-------------
 neurodsp/filt/filter.py            |  17 ++---
 neurodsp/filt/fir.py               |   9 ++-
 neurodsp/filt/iir.py               |   8 ++-
 neurodsp/filt/utils.py             | 105 +++++++++++++++++++++++++++++
 neurodsp/tests/filt/test_checks.py |   7 +-
 neurodsp/tests/filt/test_utils.py  |  38 ++++++++++-
 7 files changed, 187 insertions(+), 65 deletions(-)

diff --git a/neurodsp/filt/checks.py b/neurodsp/filt/checks.py
index f1e76e56..29748896 100644
--- a/neurodsp/filt/checks.py
+++ b/neurodsp/filt/checks.py
@@ -1,6 +1,8 @@
 """Checker functions for filtering."""
 
 from warnings import warn
+import os
+import json
 
 import numpy as np
 
@@ -89,8 +91,8 @@ def check_filter_definition(pass_type, f_range):
     return f_lo, f_hi
 
 
-def check_filter_properties(filter_coefs, a_vals, fs, pass_type, f_range,
-                            transitions=(-20, -3), filt_type=None, verbose=True):
+def check_filter_properties(filter_coefs, a_vals, fs, pass_type, f_range, transitions=(-20, -3),
+                            filt_type=None, verbose=True, save_properties=None):
     """Check a filters properties, including pass band and transition band.
 
     Parameters
@@ -117,8 +119,12 @@ def check_filter_properties(filter_coefs, a_vals, fs, pass_type, f_range,
         a tuple and is assumed to be (None, f_hi) for 'lowpass', and (f_lo, None) for 'highpass'.
     transitions : tuple of (float, float), optional, default: (-20, -3)
         Cutoffs, in dB, that define the transition band.
+    filt_type : str, optional, {'FIR', 'IIR'}
+        The type of filter being applied.
     verbose : bool, optional, default: True
-        Whether to print out transition and pass bands.
+        Whether to print out filter properties.
+    save_properties : str
+        Path, including file name, to save filter properites to as a json.
 
     Returns
     -------
@@ -138,8 +144,8 @@ def check_filter_properties(filter_coefs, a_vals, fs, pass_type, f_range,
     """
 
     # Import utility functions inside function to avoid circular imports
-    from neurodsp.filt.utils import (compute_frequency_response,
-                                     compute_pass_band, compute_transition_band)
+    from neurodsp.filt.utils import (compute_frequency_response, compute_pass_band,
+                                     compute_transition_band, gen_filt_report, save_filt_report)
 
     # Initialize variable to keep track if all checks pass
     passes = True
@@ -173,52 +179,16 @@ def check_filter_properties(filter_coefs, a_vals, fs, pass_type, f_range,
         warn('Transition bandwidth is  {:.1f}  Hz. This is greater than the desired'\
              'pass/stop bandwidth of  {:.1f} Hz'.format(transition_bw, pass_bw))
 
-    # Print out transition bandwidth and pass bandwidth to the user
+    # Report filter properties
+    if verbose or save_properties:
+        filt_report = gen_filt_report(pass_type, filt_type, fs, f_db, db, pass_bw,
+                                      transition_bw, f_range, f_range_trans)
+
     if verbose:
+        print('\n'.join('{} : {}'.format(key, value) for key, value in filt_report.items()))
 
-        # Filter type (high-pass, low-pass, band-pass, band-stop, FIR, IIR)
-        print('Pass Type: {pass_type}'.format(pass_type=pass_type))
-
-        # Cutoff frequency (including definition)
-        cutoff = round(np.min(f_range) + (0.5 * transition_bw), 3)
-        print('Cutoff (half-amplitude): {cutoff} Hz'.format(cutoff=cutoff))
-
-        # Filter order (or length)
-        print('Filter order: {order}'.format(order=len(f_db)-1))
-
-        # Roll-off or transition bandwidth
-        print('Transition bandwidth: {:.1f} Hz'.format(transition_bw))
-        print('Pass/stop bandwidth: {:.1f} Hz'.format(pass_bw))
-
-        # Passband ripple and stopband attenuation
-        pb_ripple = np.max(db[:np.where(f_db < f_range_trans[0])[0][-1]])
-        sb_atten = np.max(db[np.where(f_db > f_range_trans[1])[0][0]:])
-        print('Passband Ripple: {pb_ripple} db'.format(pb_ripple=pb_ripple))
-        print('Stopband Attenuation: {sb_atten} db'.format(sb_atten=sb_atten))
-
-        # Filter delay (zero-phase, linear-phase, non-linear phase)
-        if filt_type == 'FIR' and pass_type in ['bandstop', 'lowpass']:
-            filt_class = 'linear-phase'
-        elif filt_type == 'FIR' and pass_type in ['bandpass', 'highpass']:
-            filt_class = 'zero-phase'
-        elif filt_type == 'IIR':
-            filt_class = 'non-linear-phase'
-        else:
-            filt_class = None
-
-        if filt_type is not None:
-            print('Filter Class: {filt_class}'.format(filt_class=filt_class))
-
-        if filt_class == 'linear-phase':
-            print('Group Delay: {delay}s'.format(delay=(len(f_db)-1) / 2 * fs))
-        elif filt_class == 'zero-phase':
-            print('Group Delay: 0s')
-
-        # Direction of computation (one-pass forward/reverse, or two-pass forward and reverse)
-        if filt_type == 'FIR':
-            print('Direction: one-pass reverse.')
-        else:
-            print('Direction: two-pass forward and reverse')
+    if save_properties is not None:
+        save_filt_report(save_properties, filt_report)
 
     return passes
 
diff --git a/neurodsp/filt/filter.py b/neurodsp/filt/filter.py
index 4f716db3..cc61229b 100644
--- a/neurodsp/filt/filter.py
+++ b/neurodsp/filt/filter.py
@@ -8,10 +8,9 @@
 ###################################################################################################
 ###################################################################################################
 
-def filter_signal(sig, fs, pass_type, f_range, filter_type='fir',
-                  n_cycles=3, n_seconds=None, remove_edges=True, butterworth_order=None,
-                  print_transitions=False, plot_properties=False, return_filter=False,
-                  verbose=False):
+def filter_signal(sig, fs, pass_type, f_range, filter_type='fir', n_cycles=3, n_seconds=None,
+                  remove_edges=True, butterworth_order=None, print_transitions=False,
+                  plot_properties=False, save_properties=None, return_filter=False, verbose=False):
     """Apply a bandpass, bandstop, highpass, or lowpass filter to a neural signal.
 
     Parameters
@@ -51,6 +50,8 @@ def filter_signal(sig, fs, pass_type, f_range, filter_type='fir',
         If True, print out the transition and pass bandwidths.
     plot_properties : bool, optional, default: False
         If True, plot the properties of the filter, including frequency response and/or kernel.
+    save_properties : str, optional, default: None
+        Path, including file name, to save filter properites to as a json.
     return_filter : bool, optional, default: False
         If True, return the filter coefficients.
     verbose : bool, optional, default: False
@@ -76,13 +77,13 @@ def filter_signal(sig, fs, pass_type, f_range, filter_type='fir',
 
     if filter_type.lower() == 'fir':
         return filter_signal_fir(sig, fs, pass_type, f_range, n_cycles, n_seconds,
-                                 remove_edges, print_transitions,
-                                 plot_properties, return_filter, verbose=verbose)
+                                 remove_edges, print_transitions, plot_properties,
+                                 save_properties, return_filter, verbose)
     elif filter_type.lower() == 'iir':
         _iir_checks(n_seconds, butterworth_order, remove_edges)
         return filter_signal_iir(sig, fs, pass_type, f_range, butterworth_order,
-                                 print_transitions, plot_properties,
-                                 return_filter, verbose=verbose)
+                                 print_transitions, plot_properties, save_properties,
+                                 return_filter, verbose)
     else:
         raise ValueError('Filter type not understood.')
 
diff --git a/neurodsp/filt/fir.py b/neurodsp/filt/fir.py
index 6f0e1f29..6e2042ae 100644
--- a/neurodsp/filt/fir.py
+++ b/neurodsp/filt/fir.py
@@ -14,8 +14,8 @@
 ###################################################################################################
 
 def filter_signal_fir(sig, fs, pass_type, f_range, n_cycles=3, n_seconds=None, remove_edges=True,
-                      print_transitions=False, plot_properties=False, return_filter=False,
-                      verbose=False):
+                      print_transitions=False, plot_properties=False, save_properties=None,
+                      return_filter=False, verbose=False, file_path=None, file_name=None):
     """Apply an FIR filter to a signal.
 
     Parameters
@@ -47,6 +47,8 @@ def filter_signal_fir(sig, fs, pass_type, f_range, n_cycles=3, n_seconds=None, r
         If True, print out the transition and pass bandwidths.
     plot_properties : bool, optional, default: False
         If True, plot the properties of the filter, including frequency response and/or kernel.
+    save_properties : str
+        Path, including file name, to save filter properites to as a json.
     return_filter : bool, optional, default: False
         If True, return the filter coefficients of the FIR filter.
     verbose : bool, optional, default: False
@@ -82,7 +84,8 @@ def filter_signal_fir(sig, fs, pass_type, f_range, n_cycles=3, n_seconds=None, r
 
     # Check filter properties: compute transition bandwidth & run checks
     check_filter_properties(filter_coefs, 1, fs, pass_type, f_range, filt_type="FIR",
-                            verbose=np.any([print_transitions, verbose]))
+                            verbose=np.any([print_transitions, verbose]),
+                            save_properties=save_properties)
 
     # Remove any NaN on the edges of 'sig'
     sig, sig_nans = remove_nans(sig)
diff --git a/neurodsp/filt/iir.py b/neurodsp/filt/iir.py
index aeddb6f7..08c8fb56 100644
--- a/neurodsp/filt/iir.py
+++ b/neurodsp/filt/iir.py
@@ -12,7 +12,8 @@
 ###################################################################################################
 
 def filter_signal_iir(sig, fs, pass_type, f_range, butterworth_order, print_transitions=False,
-                       plot_properties=False, return_filter=False, verbose=False):
+                      plot_properties=False, save_properties=None, return_filter=False,
+                      verbose=False):
     """Apply an IIR filter to a signal.
 
     Parameters
@@ -40,6 +41,8 @@ def filter_signal_iir(sig, fs, pass_type, f_range, butterworth_order, print_tran
         If True, print out the transition and pass bandwidths.
     plot_properties : bool, optional, default: False
         If True, plot the properties of the filter, including frequency response and/or kernel.
+    save_properties : str
+        Path, including file name, to save filter properites to as a json.
     return_filter : bool, optional, default: False
         If True, return the second order series coefficients of the IIR filter.
     verbose : bool, optional, default: False
@@ -69,7 +72,8 @@ def filter_signal_iir(sig, fs, pass_type, f_range, butterworth_order, print_tran
 
     # Check filter properties: compute transition bandwidth & run checks
     check_filter_properties(sos, None, fs, pass_type, f_range, filt_type="IIR",
-                            verbose=np.any([print_transitions, verbose]))
+                            verbose=np.any([print_transitions, verbose]),
+                            save_properties=save_properties)
 
     # Remove any NaN on the edges of 'sig'
     sig, sig_nans = remove_nans(sig)
diff --git a/neurodsp/filt/utils.py b/neurodsp/filt/utils.py
index dcc3aef8..6ba90e1a 100644
--- a/neurodsp/filt/utils.py
+++ b/neurodsp/filt/utils.py
@@ -1,5 +1,8 @@
 """Utility functions for filtering."""
 
+import os
+import json
+
 import numpy as np
 from scipy.signal import freqz, sosfreqz
 
@@ -253,3 +256,105 @@ def remove_filter_edges(sig, filt_len):
     sig[-n_rmv:] = np.nan
 
     return sig
+
+
+def gen_filt_report(pass_type, filt_type, fs, f_db, db, pass_bw,
+                    transition_bw, f_range, f_range_trans):
+    """Create a filter report.
+
+    Parameters
+    ----------
+    pass_type : {'bandpass', 'bandstop', 'lowpass', 'highpass'}
+        Which type of filter was applied.
+    filt_type : str, {'FIR', 'IIR'}
+        The type of filter being applied.
+    fs : float
+        Sampling rate, in Hz.
+    f_db : 1d array
+        Frequency vector corresponding to attenuation decibels, in Hz.
+    db : 1d array
+        Degree of attenuation for each frequency specified in `f_db`, in dB.
+    pass_bw : float
+        The pass bandwidth of the filter.
+    transition_band : float
+        The transition bandwidth of the filter.
+    f_range : tuple of (float, float) or float
+        Cutoff frequency(ies) used for filter, specified as f_lo & f_hi.
+    f_range_trans : tuple of (float, float)
+        The lower and upper frequencies of the transition band.
+
+    Returns
+    -------
+    filt_report : dict
+        A dicionary of filter parameter keys and corresponding values.
+    """
+    filt_report = {}
+
+    # Filter type (high-pass, low-pass, band-pass, band-stop, FIR, IIR)
+    filt_report['Pass Type'] = '{pass_type}'.format(pass_type=pass_type)
+
+    # Cutoff frequenc(ies) (including definition)
+    filt_report['Cutoff (half-amplitude)'] = '{cutoff} Hz'.format(cutoff=f_range)
+
+    # Filter order (or length)
+    filt_report['Filter order'] = '{order}'.format(order=len(f_db)-1)
+
+    # Roll-off or transition bandwidth
+    filt_report['Transition bandwidth'] = '{:.1f} Hz'.format(transition_bw)
+    filt_report['Pass/stop bandwidth'] = '{:.1f} Hz'.format(pass_bw)
+
+    # Passband ripple and stopband attenuation
+    pb_ripple = np.max(db[:np.where(f_db < f_range_trans[0])[0][-1]])
+    sb_atten = np.max(db[np.where(f_db > f_range_trans[1])[0][0]:])
+    filt_report['Passband Ripple'] = '{pb_ripple} db'.format(pb_ripple=pb_ripple)
+    filt_report['Stopband Attenuation'] = '{sb_atten} db'.format(sb_atten=sb_atten)
+
+    # Filter delay (zero-phase, linear-phase, non-linear phase)
+    filt_report['Filter Type'] = filt_type
+
+    if filt_type == 'FIR' and pass_type in ['bandstop', 'lowpass']:
+
+        filt_report['Filter Class'] = '{filt_class}'.format(filt_class='linear-phase')
+        filt_report['Group Delay'] = '{delay}s'.format(delay=(len(f_db)-1) / 2 * fs)
+
+    elif filt_type == 'FIR' and pass_type in ['bandpass', 'highpass']:
+
+        filt_report['Filter Class'] = '{filt_class}'.format(filt_class='zero-phase')
+        filt_report['Group Delay'] = '0s'
+
+    elif filt_type == 'IIR':
+
+        # Group delay isn't reported for IIR since it varies from sample to sample
+        filt_report['Filter Class'] = '{filt_class}'.format(filt_class='non-linear-phase')
+
+    # Direction of computation (one-pass forward/reverse, or two-pass forward and reverse)
+    if filt_type == 'FIR':
+        filt_report['Direction'] = 'one-pass reverse'
+    else:
+        filt_report['Direction'] = 'two-pass forward and reverse'
+
+    return filt_report
+
+
+def save_filt_report(save_properties, filt_report):
+    """Save filter properties as a json file.
+
+    Parameters
+    ----------
+    save_properties : str
+        Path, including file name, to save filter properites to as a json.
+    filt_report : dict
+        Contains filter report info.
+    """
+
+    # Ensure parents exists
+    if not os.path.isdir(os.path.dirname(save_properties)):
+        raise ValueError("Unable to save properties. Parent directory does not exist.")
+
+    # Enforce file extension
+    if not save_properties.endswith('.json'):
+        save_properties = save_properties + '.json'
+
+    # Save
+    with open(save_properties, 'w') as file_path:
+        json.dump(filt_report, file_path)
diff --git a/neurodsp/tests/filt/test_checks.py b/neurodsp/tests/filt/test_checks.py
index 32b5776e..d5b07324 100644
--- a/neurodsp/tests/filt/test_checks.py
+++ b/neurodsp/tests/filt/test_checks.py
@@ -1,5 +1,6 @@
 """Tests for filter check functions."""
 
+import tempfile
 from pytest import raises
 
 from neurodsp.tests.settings import FS
@@ -46,7 +47,7 @@ def test_check_filter_definition():
 def test_check_filter_properties():
 
     filter_coefs = design_fir_filter(FS, 'bandpass', (8, 12))
-    
+
     passes = check_filter_properties(filter_coefs, 1, FS, 'bandpass', (8, 12))
     assert passes is True
 
@@ -58,6 +59,10 @@ def test_check_filter_properties():
     passes = check_filter_properties(filter_coefs, 1, FS, 'bandpass', (8, 12))
     assert passes is False
 
+    temp_path = tempfile.NamedTemporaryFile()
+    check_filter_properties(filter_coefs, 1, FS, 'bandpass', (8, 12),
+                            verbose=True, save_properties=temp_path.name)
+    temp_path.close()
 
 def test_check_filter_length():
 
diff --git a/neurodsp/tests/filt/test_utils.py b/neurodsp/tests/filt/test_utils.py
index c839a75d..9b8f338d 100644
--- a/neurodsp/tests/filt/test_utils.py
+++ b/neurodsp/tests/filt/test_utils.py
@@ -1,8 +1,11 @@
 """Tests for filter utilities."""
 
-from pytest import raises
-from neurodsp.tests.settings import FS
+import tempfile
+from pytest import raises, mark, param
+
+import numpy as np
 
+from neurodsp.tests.settings import FS
 from neurodsp.filt.utils import *
 from neurodsp.filt.fir import design_fir_filter, compute_filter_length
 
@@ -53,3 +56,34 @@ def test_remove_filter_edges():
     assert np.all(np.isnan(dropped_sig[:n_rmv]))
     assert np.all(np.isnan(dropped_sig[-n_rmv:]))
     assert np.all(~np.isnan(dropped_sig[n_rmv:-n_rmv]))
+
+
+@mark.parametrize("pass_type", ['bandpass', 'bandstop', 'lowpass', 'highpass'])
+@mark.parametrize("filt_type", ['IIR', 'FIR'])
+def test_gen_filt_report(pass_type, filt_type):
+
+    fs = 1000
+    f_db = np.arange(0, 50)
+    db = np.random.rand(50)
+    pass_bw = 10
+    transition_bw = 4
+    f_range = (10, 40)
+    f_range_trans = (40, 44)
+
+    report = gen_filt_report(pass_type, filt_type, fs, f_db, db, pass_bw,
+                             transition_bw, f_range, f_range_trans)
+
+    assert pass_type in report.values()
+    assert filt_type in report.values()
+
+
+@mark.parametrize("dir_exists", [True, param(False, marks=mark.xfail)])
+def test_save_filt_report(dir_exists):
+
+    filt_report = {'Pass Type': 'bandpass', 'Cutoff (half-amplitude)': 50}
+    temp_path = tempfile.NamedTemporaryFile()
+    if not dir_exists:
+        save_filt_report('/bad/path/', filt_report)
+    else:
+        save_filt_report(temp_path.name, filt_report)
+    temp_path.close()

From 04e5de7c44cc2a4c83290121e7f3d2f725bf07f3 Mon Sep 17 00:00:00 2001
From: ryanhammonds <ryan.hammonds@utexas.edu>
Date: Thu, 14 Jan 2021 11:42:02 -0800
Subject: [PATCH 3/9] report update - all fir is linear-phase

---
 neurodsp/filt/utils.py | 25 ++++++++-----------------
 1 file changed, 8 insertions(+), 17 deletions(-)

diff --git a/neurodsp/filt/utils.py b/neurodsp/filt/utils.py
index 6ba90e1a..30e7fa49 100644
--- a/neurodsp/filt/utils.py
+++ b/neurodsp/filt/utils.py
@@ -294,14 +294,14 @@ def gen_filt_report(pass_type, filt_type, fs, f_db, db, pass_bw,
     filt_report['Pass Type'] = '{pass_type}'.format(pass_type=pass_type)
 
     # Cutoff frequenc(ies) (including definition)
-    filt_report['Cutoff (half-amplitude)'] = '{cutoff} Hz'.format(cutoff=f_range)
+    filt_report['Cutoff (Half-Amplitude)'] = '{cutoff} Hz'.format(cutoff=f_range)
 
     # Filter order (or length)
-    filt_report['Filter order'] = '{order}'.format(order=len(f_db)-1)
+    filt_report['Filter Order'] = '{order}'.format(order=len(f_db)-1)
 
     # Roll-off or transition bandwidth
-    filt_report['Transition bandwidth'] = '{:.1f} Hz'.format(transition_bw)
-    filt_report['Pass/stop bandwidth'] = '{:.1f} Hz'.format(pass_bw)
+    filt_report['Transition Bandwidth'] = '{:.1f} Hz'.format(transition_bw)
+    filt_report['Pass/Stop Bandwidth'] = '{:.1f} Hz'.format(pass_bw)
 
     # Passband ripple and stopband attenuation
     pb_ripple = np.max(db[:np.where(f_db < f_range_trans[0])[0][-1]])
@@ -312,25 +312,16 @@ def gen_filt_report(pass_type, filt_type, fs, f_db, db, pass_bw,
     # Filter delay (zero-phase, linear-phase, non-linear phase)
     filt_report['Filter Type'] = filt_type
 
-    if filt_type == 'FIR' and pass_type in ['bandstop', 'lowpass']:
+    if filt_type == 'FIR':
 
-        filt_report['Filter Class'] = '{filt_class}'.format(filt_class='linear-phase')
+        filt_report['Phase'] = '{filt_class}'.format(filt_class='linear-phase')
         filt_report['Group Delay'] = '{delay}s'.format(delay=(len(f_db)-1) / 2 * fs)
-
-    elif filt_type == 'FIR' and pass_type in ['bandpass', 'highpass']:
-
-        filt_report['Filter Class'] = '{filt_class}'.format(filt_class='zero-phase')
-        filt_report['Group Delay'] = '0s'
+        filt_report['Direction'] = 'one-pass reverse'
 
     elif filt_type == 'IIR':
 
         # Group delay isn't reported for IIR since it varies from sample to sample
-        filt_report['Filter Class'] = '{filt_class}'.format(filt_class='non-linear-phase')
-
-    # Direction of computation (one-pass forward/reverse, or two-pass forward and reverse)
-    if filt_type == 'FIR':
-        filt_report['Direction'] = 'one-pass reverse'
-    else:
+        filt_report['Phase'] = '{filt_class}'.format(filt_class='non-linear-phase')
         filt_report['Direction'] = 'two-pass forward and reverse'
 
     return filt_report

From fdd109c4c32863669cc323c344474398d23aaabb Mon Sep 17 00:00:00 2001
From: ryanhammonds <ryan.hammonds@utexas.edu>
Date: Thu, 14 Jan 2021 17:44:00 -0800
Subject: [PATCH 4/9] group delay fix

---
 neurodsp/filt/utils.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/neurodsp/filt/utils.py b/neurodsp/filt/utils.py
index 30e7fa49..73c2205b 100644
--- a/neurodsp/filt/utils.py
+++ b/neurodsp/filt/utils.py
@@ -315,7 +315,7 @@ def gen_filt_report(pass_type, filt_type, fs, f_db, db, pass_bw,
     if filt_type == 'FIR':
 
         filt_report['Phase'] = '{filt_class}'.format(filt_class='linear-phase')
-        filt_report['Group Delay'] = '{delay}s'.format(delay=(len(f_db)-1) / 2 * fs)
+        filt_report['Group Delay'] = '{delay}s'.format(delay=(len(f_db)-1) / (2 * fs))
         filt_report['Direction'] = 'one-pass reverse'
 
     elif filt_type == 'IIR':

From b98d6693bea253f1614170211f852168664e8384 Mon Sep 17 00:00:00 2001
From: ryanhammonds <ryan.hammonds@utexas.edu>
Date: Thu, 21 Jan 2021 14:27:11 -0800
Subject: [PATCH 5/9] review updates

---
 neurodsp/filt/checks.py            |  35 +++----
 neurodsp/filt/filter.py            |  14 ++-
 neurodsp/filt/fir.py               |  33 ++++---
 neurodsp/filt/iir.py               |  34 ++++---
 neurodsp/filt/utils.py             | 152 ++++++++++++++++++++++-------
 neurodsp/tests/filt/test_checks.py |   6 +-
 neurodsp/tests/filt/test_utils.py  |  46 ++++++---
 7 files changed, 222 insertions(+), 98 deletions(-)

diff --git a/neurodsp/filt/checks.py b/neurodsp/filt/checks.py
index 29748896..8a189b14 100644
--- a/neurodsp/filt/checks.py
+++ b/neurodsp/filt/checks.py
@@ -1,8 +1,6 @@
 """Checker functions for filtering."""
 
 from warnings import warn
-import os
-import json
 
 import numpy as np
 
@@ -92,7 +90,7 @@ def check_filter_definition(pass_type, f_range):
 
 
 def check_filter_properties(filter_coefs, a_vals, fs, pass_type, f_range, transitions=(-20, -3),
-                            filt_type=None, verbose=True, save_properties=None):
+                            return_properties=False, verbose=True):
     """Check a filters properties, including pass band and transition band.
 
     Parameters
@@ -119,17 +117,18 @@ def check_filter_properties(filter_coefs, a_vals, fs, pass_type, f_range, transi
         a tuple and is assumed to be (None, f_hi) for 'lowpass', and (f_lo, None) for 'highpass'.
     transitions : tuple of (float, float), optional, default: (-20, -3)
         Cutoffs, in dB, that define the transition band.
-    filt_type : str, optional, {'FIR', 'IIR'}
-        The type of filter being applied.
+    return_properties : bool, optional, default: False
+        Returns the frequency response, pass band and transition band.
     verbose : bool, optional, default: True
-        Whether to print out filter properties.
-    save_properties : str
-        Path, including file name, to save filter properites to as a json.
+        Whether to print out transition and pass bands.
 
     Returns
     -------
     passes : bool
         Whether all the checks pass. False if one or more checks fail.
+    properties : dict
+        The frequency response, pass band and transition band.
+        Only returned if return_properties is True.
 
     Examples
     --------
@@ -145,7 +144,7 @@ def check_filter_properties(filter_coefs, a_vals, fs, pass_type, f_range, transi
 
     # Import utility functions inside function to avoid circular imports
     from neurodsp.filt.utils import (compute_frequency_response, compute_pass_band,
-                                     compute_transition_band, gen_filt_report, save_filt_report)
+                                     compute_transition_band)
 
     # Initialize variable to keep track if all checks pass
     passes = True
@@ -179,16 +178,18 @@ def check_filter_properties(filter_coefs, a_vals, fs, pass_type, f_range, transi
         warn('Transition bandwidth is  {:.1f}  Hz. This is greater than the desired'\
              'pass/stop bandwidth of  {:.1f} Hz'.format(transition_bw, pass_bw))
 
-    # Report filter properties
-    if verbose or save_properties:
-        filt_report = gen_filt_report(pass_type, filt_type, fs, f_db, db, pass_bw,
-                                      transition_bw, f_range, f_range_trans)
-
+    # Print out transition bandwidth and pass bandwidth to the user
     if verbose:
-        print('\n'.join('{} : {}'.format(key, value) for key, value in filt_report.items()))
+        print('Transition bandwidth is {:.1f} Hz.'.format(transition_bw))
+        print('Pass/stop bandwidth is {:.1f} Hz.'.format(pass_bw))
+
+    # Return the filter properties
+    if return_properties:
+
+        properties = {'f_db': f_db, 'db': db, 'pass_bw': pass_bw, 'transition_bw': transition_bw,
+                      'f_range_trans': f_range_trans}
 
-    if save_properties is not None:
-        save_filt_report(save_properties, filt_report)
+        return passes, properties
 
     return passes
 
diff --git a/neurodsp/filt/filter.py b/neurodsp/filt/filter.py
index cc61229b..685c5f8d 100644
--- a/neurodsp/filt/filter.py
+++ b/neurodsp/filt/filter.py
@@ -10,7 +10,7 @@
 
 def filter_signal(sig, fs, pass_type, f_range, filter_type='fir', n_cycles=3, n_seconds=None,
                   remove_edges=True, butterworth_order=None, print_transitions=False,
-                  plot_properties=False, save_properties=None, return_filter=False, verbose=False):
+                  plot_properties=False, return_filter=False, save_report=None):
     """Apply a bandpass, bandstop, highpass, or lowpass filter to a neural signal.
 
     Parameters
@@ -50,12 +50,10 @@ def filter_signal(sig, fs, pass_type, f_range, filter_type='fir', n_cycles=3, n_
         If True, print out the transition and pass bandwidths.
     plot_properties : bool, optional, default: False
         If True, plot the properties of the filter, including frequency response and/or kernel.
-    save_properties : str, optional, default: None
-        Path, including file name, to save filter properites to as a json.
     return_filter : bool, optional, default: False
         If True, return the filter coefficients.
-    verbose : bool, optional, default: False
-        If True, print out detailed filter information.
+    save_report : str, optional, default: None
+        Path, including file name, to save a filter report to as a pdf.
 
     Returns
     -------
@@ -78,12 +76,12 @@ def filter_signal(sig, fs, pass_type, f_range, filter_type='fir', n_cycles=3, n_
     if filter_type.lower() == 'fir':
         return filter_signal_fir(sig, fs, pass_type, f_range, n_cycles, n_seconds,
                                  remove_edges, print_transitions, plot_properties,
-                                 save_properties, return_filter, verbose)
+                                 return_filter, save_report)
     elif filter_type.lower() == 'iir':
         _iir_checks(n_seconds, butterworth_order, remove_edges)
         return filter_signal_iir(sig, fs, pass_type, f_range, butterworth_order,
-                                 print_transitions, plot_properties, save_properties,
-                                 return_filter, verbose)
+                                 print_transitions, plot_properties, return_filter,
+                                 save_report)
     else:
         raise ValueError('Filter type not understood.')
 
diff --git a/neurodsp/filt/fir.py b/neurodsp/filt/fir.py
index 6e2042ae..e139e09e 100644
--- a/neurodsp/filt/fir.py
+++ b/neurodsp/filt/fir.py
@@ -6,7 +6,7 @@
 from neurodsp.utils import remove_nans, restore_nans
 from neurodsp.utils.decorators import multidim
 from neurodsp.plts.filt import plot_filter_properties
-from neurodsp.filt.utils import compute_frequency_response, remove_filter_edges
+from neurodsp.filt.utils import compute_frequency_response, remove_filter_edges, save_filt_report
 from neurodsp.filt.checks import (check_filter_definition, check_filter_properties,
                                   check_filter_length)
 
@@ -14,8 +14,8 @@
 ###################################################################################################
 
 def filter_signal_fir(sig, fs, pass_type, f_range, n_cycles=3, n_seconds=None, remove_edges=True,
-                      print_transitions=False, plot_properties=False, save_properties=None,
-                      return_filter=False, verbose=False, file_path=None, file_name=None):
+                      print_transitions=False, plot_properties=False, return_filter=False,
+                      save_report=None):
     """Apply an FIR filter to a signal.
 
     Parameters
@@ -47,12 +47,10 @@ def filter_signal_fir(sig, fs, pass_type, f_range, n_cycles=3, n_seconds=None, r
         If True, print out the transition and pass bandwidths.
     plot_properties : bool, optional, default: False
         If True, plot the properties of the filter, including frequency response and/or kernel.
-    save_properties : str
-        Path, including file name, to save filter properites to as a json.
     return_filter : bool, optional, default: False
         If True, return the filter coefficients of the FIR filter.
-    verbose : bool, optional, default: False
-        If True, print out detailed filter information.
+    save_report : str, optional, default: None
+        Path, including file name, to save a filter report to as a pdf.
 
     Returns
     -------
@@ -83,9 +81,8 @@ def filter_signal_fir(sig, fs, pass_type, f_range, n_cycles=3, n_seconds=None, r
     check_filter_length(sig.shape[-1], len(filter_coefs))
 
     # Check filter properties: compute transition bandwidth & run checks
-    check_filter_properties(filter_coefs, 1, fs, pass_type, f_range, filt_type="FIR",
-                            verbose=np.any([print_transitions, verbose]),
-                            save_properties=save_properties)
+    _, properties = check_filter_properties(filter_coefs, 1, fs, pass_type, f_range,
+                                            return_properties=True, verbose=print_transitions)
 
     # Remove any NaN on the edges of 'sig'
     sig, sig_nans = remove_nans(sig)
@@ -100,11 +97,25 @@ def filter_signal_fir(sig, fs, pass_type, f_range, n_cycles=3, n_seconds=None, r
     # Add NaN back on the edges of 'sig', if there were any at the beginning
     sig_filt = restore_nans(sig_filt, sig_nans)
 
+    # Unpack filter properties
+    if plot_properties or save_report is not None:
+        f_db = properties['f_db']
+        db = properties['db']
+
+    if save_report is not None:
+        pass_bw = properties['pass_bw']
+        transition_bw = properties['transition_bw']
+        f_range_trans = properties['f_range_trans']
+
     # Plot filter properties, if specified
     if plot_properties:
-        f_db, db = compute_frequency_response(filter_coefs, 1, fs)
         plot_filter_properties(f_db, db, fs, filter_coefs)
 
+    # Save a pdf filter report containing plots and parameters
+    if save_report is not None:
+        save_filt_report(save_report, pass_type, 'IIR', fs, f_db, db, pass_bw, transition_bw,
+                         f_range, f_range_trans, len(f_db)-1, filter_coefs=filter_coefs)
+
     if return_filter:
         return sig_filt, filter_coefs
     else:
diff --git a/neurodsp/filt/iir.py b/neurodsp/filt/iir.py
index 08c8fb56..a34b07a8 100644
--- a/neurodsp/filt/iir.py
+++ b/neurodsp/filt/iir.py
@@ -1,10 +1,9 @@
 """Filter signals with IIR filters."""
 
-import numpy as np
 from scipy.signal import butter, sosfiltfilt
 
 from neurodsp.utils import remove_nans, restore_nans
-from neurodsp.filt.utils import compute_nyquist, compute_frequency_response
+from neurodsp.filt.utils import compute_nyquist, compute_frequency_response, save_filt_report
 from neurodsp.filt.checks import check_filter_definition, check_filter_properties
 from neurodsp.plts.filt import plot_frequency_response
 
@@ -12,8 +11,7 @@
 ###################################################################################################
 
 def filter_signal_iir(sig, fs, pass_type, f_range, butterworth_order, print_transitions=False,
-                      plot_properties=False, save_properties=None, return_filter=False,
-                      verbose=False):
+                      plot_properties=False, return_filter=False, save_report=None):
     """Apply an IIR filter to a signal.
 
     Parameters
@@ -41,12 +39,10 @@ def filter_signal_iir(sig, fs, pass_type, f_range, butterworth_order, print_tran
         If True, print out the transition and pass bandwidths.
     plot_properties : bool, optional, default: False
         If True, plot the properties of the filter, including frequency response and/or kernel.
-    save_properties : str
-        Path, including file name, to save filter properites to as a json.
     return_filter : bool, optional, default: False
         If True, return the second order series coefficients of the IIR filter.
-    verbose : bool, optional, default: False
-        If True, print out detailed filter information.
+    save_report : str, optional, default: None
+        Path, including file name, to save a filter report to as a pdf.
 
     Returns
     -------
@@ -71,9 +67,8 @@ def filter_signal_iir(sig, fs, pass_type, f_range, butterworth_order, print_tran
     sos = design_iir_filter(fs, pass_type, f_range, butterworth_order)
 
     # Check filter properties: compute transition bandwidth & run checks
-    check_filter_properties(sos, None, fs, pass_type, f_range, filt_type="IIR",
-                            verbose=np.any([print_transitions, verbose]),
-                            save_properties=save_properties)
+    _, properties = check_filter_properties(sos, None, fs, pass_type, f_range,
+                                            return_properties=True, verbose=print_transitions)
 
     # Remove any NaN on the edges of 'sig'
     sig, sig_nans = remove_nans(sig)
@@ -84,11 +79,26 @@ def filter_signal_iir(sig, fs, pass_type, f_range, butterworth_order, print_tran
     # Add NaN back on the edges of 'sig', if there were any at the beginning
     sig_filt = restore_nans(sig_filt, sig_nans)
 
+    # Unpack filter properties
+    if plot_properties or save_report is not None:
+        f_db = properties['f_db']
+        db = properties['db']
+
+    if save_report is not None:
+        pass_bw = properties['pass_bw']
+        transition_bw = properties['transition_bw']
+        f_range_trans = properties['f_range_trans']
+
     # Plot frequency response, if desired
     if plot_properties:
-        f_db, db = compute_frequency_response(sos, None, fs)
         plot_frequency_response(f_db, db)
 
+    # Save a pdf filter report containing plots and parameters
+    if save_report is not None:
+
+        save_filt_report(save_report, pass_type, 'IIR', fs, f_db, db, pass_bw,
+                         transition_bw, f_range, f_range_trans, butterworth_order)
+
     if return_filter:
         return sig_filt, sos
     else:
diff --git a/neurodsp/filt/utils.py b/neurodsp/filt/utils.py
index 73c2205b..088472ec 100644
--- a/neurodsp/filt/utils.py
+++ b/neurodsp/filt/utils.py
@@ -1,13 +1,14 @@
 """Utility functions for filtering."""
 
 import os
-import json
 
+import matplotlib.pyplot as plt
 import numpy as np
 from scipy.signal import freqz, sosfreqz
 
 from neurodsp.utils.decorators import multidim
 from neurodsp.filt.checks import check_filter_definition
+from neurodsp.plts.filt import plot_frequency_response, plot_impulse_response
 
 ###################################################################################################
 ###################################################################################################
@@ -159,8 +160,9 @@ def compute_transition_band(f_db, db, low=-20, high=-3, return_freqs=False):
     -------
     transition_band : float
         The transition bandwidth of the filter.
-    f_range : tuple of (float, float), optional, default: False
+    f_range : tuple of (float, float)
         The lower and upper frequencies of the transition band.
+        Only returned is return_freqs is True.
 
     Examples
     --------
@@ -184,7 +186,8 @@ def compute_transition_band(f_db, db, low=-20, high=-3, return_freqs=False):
 
     # This gets the indices of transitions to the values in searched for range
     inds = np.where(np.diff(np.logical_and(db > low, db < high)))[0]
-    # This steps through the indices, in pairs, selecting from the vector to select from
+
+    # This determines at which frequencies the transition band occurs
     transition_pairs = [(a, b) for a, b in zip(f_db[inds[0::2]], f_db[inds[1::2]])]
     pair_idx = np.argmax([(tran[1] - tran[0]) for tran in transition_pairs])
     f_lo = transition_pairs[pair_idx][0]
@@ -258,8 +261,8 @@ def remove_filter_edges(sig, filt_len):
     return sig
 
 
-def gen_filt_report(pass_type, filt_type, fs, f_db, db, pass_bw,
-                    transition_bw, f_range, f_range_trans):
+def gen_filt_str(pass_type, filt_type, fs, f_db, db, pass_bw,
+                 transition_bw, f_range, f_range_trans, order):
     """Create a filter report.
 
     Parameters
@@ -282,70 +285,149 @@ def gen_filt_report(pass_type, filt_type, fs, f_db, db, pass_bw,
         Cutoff frequency(ies) used for filter, specified as f_lo & f_hi.
     f_range_trans : tuple of (float, float)
         The lower and upper frequencies of the transition band.
+    order : int
+        The filter length for FIR filter or butterworth order for IIR filters.
 
     Returns
     -------
-    filt_report : dict
-        A dicionary of filter parameter keys and corresponding values.
+    filt_str : str
+        Filter properties as a string that is ready to embed into a pdf report.
     """
-    filt_report = {}
+
+    filt_str = []
 
     # Filter type (high-pass, low-pass, band-pass, band-stop, FIR, IIR)
-    filt_report['Pass Type'] = '{pass_type}'.format(pass_type=pass_type)
+    filt_str.append('Pass Type: {pass_type}'.format(pass_type=pass_type))
 
     # Cutoff frequenc(ies) (including definition)
-    filt_report['Cutoff (Half-Amplitude)'] = '{cutoff} Hz'.format(cutoff=f_range)
+    filt_str.append('Cutoff (Half-Amplitude): {cutoff} Hz'.format(cutoff=f_range))
 
-    # Filter order (or length)
-    filt_report['Filter Order'] = '{order}'.format(order=len(f_db)-1)
+    # Filter order (or length-1) for FIR or butterworth order for IIR
+    filt_str.append('Filter Order: {order}'.format(order=order))
 
     # Roll-off or transition bandwidth
-    filt_report['Transition Bandwidth'] = '{:.1f} Hz'.format(transition_bw)
-    filt_report['Pass/Stop Bandwidth'] = '{:.1f} Hz'.format(pass_bw)
+    filt_str.append('Transition Bandwidth: {:.1f} Hz'.format(transition_bw))
+    filt_str.append('Pass/Stop Bandwidth: {:.1f} Hz'.format(pass_bw))
 
     # Passband ripple and stopband attenuation
     pb_ripple = np.max(db[:np.where(f_db < f_range_trans[0])[0][-1]])
     sb_atten = np.max(db[np.where(f_db > f_range_trans[1])[0][0]:])
-    filt_report['Passband Ripple'] = '{pb_ripple} db'.format(pb_ripple=pb_ripple)
-    filt_report['Stopband Attenuation'] = '{sb_atten} db'.format(sb_atten=sb_atten)
+    filt_str.append('Passband Ripple: {:1.4f} db'.format(pb_ripple))
+    filt_str.append('Stopband Attenuation: {:1.4f} db'.format(sb_atten))
 
     # Filter delay (zero-phase, linear-phase, non-linear phase)
-    filt_report['Filter Type'] = filt_type
+    filt_str.append('Filter Type: {filt_type}'.format(filt_type=filt_type))
 
     if filt_type == 'FIR':
 
-        filt_report['Phase'] = '{filt_class}'.format(filt_class='linear-phase')
-        filt_report['Group Delay'] = '{delay}s'.format(delay=(len(f_db)-1) / (2 * fs))
-        filt_report['Direction'] = 'one-pass reverse'
+        filt_str.append('Phase: linear-phase')
+        filt_str.append('Group Delay: {:1.4f} s'.format((len(f_db)-1) / (2 * fs)))
+        filt_str.append('Direction: one-pass reverse')
 
     elif filt_type == 'IIR':
 
         # Group delay isn't reported for IIR since it varies from sample to sample
-        filt_report['Phase'] = '{filt_class}'.format(filt_class='non-linear-phase')
-        filt_report['Direction'] = 'two-pass forward and reverse'
+        filt_str.append('Phase: non-linear-phase')
+        filt_str.append('Direction: two-pass forward and reverse')
+
+    # Format the list into a string
+    filt_str = [
+
+        # Header
+        '=',
+        '',
+        'FILTER REPORT',
+        '',
 
-    return filt_report
+        # Settings
+        *filt_str,
 
+        # Footer
+        '',
+        '='
+    ]
 
-def save_filt_report(save_properties, filt_report):
+    str_len = 50
+    filt_str [0] = filt_str [0] * str_len
+    filt_str [-1] = filt_str [-1] * str_len
+
+    filt_str  = '\n'.join([string.center(str_len) for string in filt_str])
+
+    return filt_str
+
+
+def save_filt_report(pdf_path, pass_type, filt_type, fs, f_db, db,  pass_bw, transition_bw,
+                     f_range, f_range_trans, order, filter_coefs=None):
     """Save filter properties as a json file.
 
-    Parameters
+     Parameters
     ----------
-    save_properties : str
-        Path, including file name, to save filter properites to as a json.
-    filt_report : dict
-        Contains filter report info.
+    pdf_path: str
+        Path, including file name, to save a filter report to as a pdf.
+    pass_type : {'bandpass', 'bandstop', 'lowpass', 'highpass'}
+        Which type of filter was applied.
+    filt_type : str, {'FIR', 'IIR'}
+        The type of filter being applied.
+    fs : float
+        Sampling rate, in Hz.
+    f_db : 1d array
+        Frequency vector corresponding to attenuation decibels, in Hz.
+    db : 1d array
+        Degree of attenuation for each frequency specified in `f_db`, in dB.
+    pass_bw : float
+        The pass bandwidth of the filter.
+    transition_band : float
+        The transition bandwidth of the filter.
+    f_range : tuple of (float, float) or float
+        Cutoff frequency(ies) used for filter, specified as f_lo & f_hi.
+    f_range_trans : tuple of (float, float)
+        The lower and upper frequencies of the transition band.
+    order : int
+        The filter length for FIR filter or butterworth order for IIR filters.
+    filter_coefs : 1d array, optional, default: None
+        Filter coefficients of the FIR filter.
     """
 
-    # Ensure parents exists
-    if not os.path.isdir(os.path.dirname(save_properties)):
+    # Ensure valid path
+    if not pdf_path.startswith('/') and not pdf_path.startswith('./'):
+        pdf_path = './' + pdf_path
+
+    if not os.path.isdir(os.path.dirname(pdf_path)):
+        print(pdf_path)
         raise ValueError("Unable to save properties. Parent directory does not exist.")
 
     # Enforce file extension
-    if not save_properties.endswith('.json'):
-        save_properties = save_properties + '.json'
+    if not pdf_path.endswith('.pdf'):
+        pdf_path = pdf_path + '.pdf'
+
+    # Create properties string
+    filt_str = gen_filt_str(pass_type, filt_type, fs, f_db, db, pass_bw,
+                            transition_bw, f_range, f_range_trans, order)
+
+    # Plot
+    if filter_coefs is not None:
+
+        _, axes = plt.subplots(nrows=3, ncols=1, figsize=(8, 18),
+                                 gridspec_kw={'height_ratios': [1, 4, 4]})
+
+        # Plot impulse response for IIR filters
+        plot_impulse_response(fs, filter_coefs, ax=axes[2])
+
+    else:
+
+        _, axes = plt.subplots(nrows=2, ncols=1, figsize=(8, 10),
+                                 gridspec_kw={'height_ratios': [1, 4]})
+
+    # Plot filter parameter string
+    font = {'family': 'monospace', 'weight': 'normal', 'size': 16}
+    axes[0].text(0.5, 0.7, filt_str, font, ha='center', va='center')
+    axes[0].set_frame_on(False)
+    axes[0].set_xticks([])
+    axes[0].set_yticks([])
+
+    # Plot filter responses
+    plot_frequency_response(f_db, db, ax=axes[1])
 
     # Save
-    with open(save_properties, 'w') as file_path:
-        json.dump(filt_report, file_path)
+    plt.savefig(pdf_path)
+    plt.close()
diff --git a/neurodsp/tests/filt/test_checks.py b/neurodsp/tests/filt/test_checks.py
index d5b07324..c47c639e 100644
--- a/neurodsp/tests/filt/test_checks.py
+++ b/neurodsp/tests/filt/test_checks.py
@@ -1,6 +1,5 @@
 """Tests for filter check functions."""
 
-import tempfile
 from pytest import raises
 
 from neurodsp.tests.settings import FS
@@ -59,10 +58,9 @@ def test_check_filter_properties():
     passes = check_filter_properties(filter_coefs, 1, FS, 'bandpass', (8, 12))
     assert passes is False
 
-    temp_path = tempfile.NamedTemporaryFile()
+
     check_filter_properties(filter_coefs, 1, FS, 'bandpass', (8, 12),
-                            verbose=True, save_properties=temp_path.name)
-    temp_path.close()
+                            verbose=True, return_properties=True)
 
 def test_check_filter_length():
 
diff --git a/neurodsp/tests/filt/test_utils.py b/neurodsp/tests/filt/test_utils.py
index 9b8f338d..b89d9c2c 100644
--- a/neurodsp/tests/filt/test_utils.py
+++ b/neurodsp/tests/filt/test_utils.py
@@ -5,9 +5,11 @@
 
 import numpy as np
 
-from neurodsp.tests.settings import FS
+from neurodsp.tests.settings import FS, FS_HIGH
 from neurodsp.filt.utils import *
 from neurodsp.filt.fir import design_fir_filter, compute_filter_length
+from neurodsp.filt.iir import design_iir_filter
+from neurodsp.filt.checks import check_filter_definition, check_filter_properties
 
 ###################################################################################################
 ###################################################################################################
@@ -60,30 +62,52 @@ def test_remove_filter_edges():
 
 @mark.parametrize("pass_type", ['bandpass', 'bandstop', 'lowpass', 'highpass'])
 @mark.parametrize("filt_type", ['IIR', 'FIR'])
-def test_gen_filt_report(pass_type, filt_type):
+def test_gen_filt_str(pass_type, filt_type):
 
-    fs = 1000
     f_db = np.arange(0, 50)
     db = np.random.rand(50)
     pass_bw = 10
     transition_bw = 4
     f_range = (10, 40)
     f_range_trans = (40, 44)
+    order = 1
 
-    report = gen_filt_report(pass_type, filt_type, fs, f_db, db, pass_bw,
-                             transition_bw, f_range, f_range_trans)
+    report_str = gen_filt_str(pass_type, filt_type, FS, f_db, db, pass_bw,
+                              transition_bw, f_range, f_range_trans, order)
 
-    assert pass_type in report.values()
-    assert filt_type in report.values()
+    assert pass_type in report_str
+    assert filt_type in report_str
 
 
 @mark.parametrize("dir_exists", [True, param(False, marks=mark.xfail)])
-def test_save_filt_report(dir_exists):
+@mark.parametrize("filt_type", ['IIR', 'FIR'])
+def test_save_filt_report(dir_exists, filt_type):
+
+    pass_type = 'bandpass'
+    f_range = (10, 40)
+
+    f_db = np.arange(1, 100)
+    db = np.random.rand(99)
+
+    pass_bw = 10
+    transition_bw = 4
+    f_range_trans = (40, 44)
+
+    order = 1
+
+    if pass_type == 'FIR':
+        filter_coefs = np.random.rand(10)
+    else:
+        filter_coefs = None
 
-    filt_report = {'Pass Type': 'bandpass', 'Cutoff (half-amplitude)': 50}
     temp_path = tempfile.NamedTemporaryFile()
+
     if not dir_exists:
-        save_filt_report('/bad/path/', filt_report)
+        save_filt_report('/bad/path/', pass_type, filt_type, FS_HIGH, f_db, db,  pass_bw,
+                         transition_bw, f_range, f_range_trans, order, filter_coefs=filter_coefs)
     else:
-        save_filt_report(temp_path.name, filt_report)
+        print(temp_path.name)
+        save_filt_report(temp_path.name, pass_type, filt_type, FS_HIGH, f_db, db,  pass_bw,
+                         transition_bw, f_range, f_range_trans, order, filter_coefs=filter_coefs)
+
     temp_path.close()

From fcc4d93990bafea2e389325a5a1b8284a45bbbe4 Mon Sep 17 00:00:00 2001
From: ryanhammonds <ryan.hammonds@utexas.edu>
Date: Thu, 21 Jan 2021 14:51:16 -0800
Subject: [PATCH 6/9] increased test coverage

---
 neurodsp/tests/filt/test_fir.py | 8 +++++++-
 neurodsp/tests/filt/test_iir.py | 9 ++++++++-
 2 files changed, 15 insertions(+), 2 deletions(-)

diff --git a/neurodsp/tests/filt/test_fir.py b/neurodsp/tests/filt/test_fir.py
index 55fd6488..e7949b3e 100644
--- a/neurodsp/tests/filt/test_fir.py
+++ b/neurodsp/tests/filt/test_fir.py
@@ -1,5 +1,6 @@
 """Tests for FIR filters."""
 
+import tempfile
 from pytest import raises
 import numpy as np
 
@@ -12,7 +13,12 @@
 
 def test_filter_signal_fir(tsig, tsig_sine):
 
-    out = filter_signal_fir(tsig, FS, 'bandpass', (8, 12))
+    temp_path = tempfile.NamedTemporaryFile()
+
+    out = filter_signal_fir(tsig, FS, 'bandpass', (8, 12), save_report=temp_path.name)
+
+    temp_path.close()
+
     assert out.shape == tsig.shape
 
     # Apply lowpass to low-frequency sine. There should be little attenuation.
diff --git a/neurodsp/tests/filt/test_iir.py b/neurodsp/tests/filt/test_iir.py
index 4b209035..005ba39e 100644
--- a/neurodsp/tests/filt/test_iir.py
+++ b/neurodsp/tests/filt/test_iir.py
@@ -1,5 +1,7 @@
 """Tests for IIR filters."""
 
+import tempfile
+
 import numpy as np
 
 from neurodsp.tests.settings import FS
@@ -11,7 +13,12 @@
 
 def test_filter_signal_iir(tsig):
 
-    out = filter_signal_iir(tsig, FS, 'bandpass', (8, 12), 3)
+    temp_path = tempfile.NamedTemporaryFile()
+
+    out = filter_signal_iir(tsig, FS, 'bandpass', (8, 12), 3, save_report=temp_path.name)
+
+    temp_path.close()
+
     assert out.shape == tsig.shape
 
 def test_filter_signal_iir_2d(tsig2d):

From 1607d165373c9fd3eb657a50e9d732e83a1af251 Mon Sep 17 00:00:00 2001
From: ryanhammonds <ryan.hammonds@utexas.edu>
Date: Tue, 26 Jan 2021 16:17:11 -0800
Subject: [PATCH 7/9] remove unneeded print

---
 neurodsp/filt/utils.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/neurodsp/filt/utils.py b/neurodsp/filt/utils.py
index 088472ec..6e5394dc 100644
--- a/neurodsp/filt/utils.py
+++ b/neurodsp/filt/utils.py
@@ -393,7 +393,6 @@ def save_filt_report(pdf_path, pass_type, filt_type, fs, f_db, db,  pass_bw, tra
         pdf_path = './' + pdf_path
 
     if not os.path.isdir(os.path.dirname(pdf_path)):
-        print(pdf_path)
         raise ValueError("Unable to save properties. Parent directory does not exist.")
 
     # Enforce file extension

From 59cd8768ae85adfc950fdbabd88d9587907b2af0 Mon Sep 17 00:00:00 2001
From: ryanhammonds <Ryan.hammonds@utexas.edu>
Date: Thu, 3 Jun 2021 13:44:03 -0700
Subject: [PATCH 8/9] FIR direction updated to one-pass

---
 neurodsp/filt/utils.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/neurodsp/filt/utils.py b/neurodsp/filt/utils.py
index 6e5394dc..eaae4c53 100644
--- a/neurodsp/filt/utils.py
+++ b/neurodsp/filt/utils.py
@@ -322,7 +322,7 @@ def gen_filt_str(pass_type, filt_type, fs, f_db, db, pass_bw,
 
         filt_str.append('Phase: linear-phase')
         filt_str.append('Group Delay: {:1.4f} s'.format((len(f_db)-1) / (2 * fs)))
-        filt_str.append('Direction: one-pass reverse')
+        filt_str.append('Direction: one-pass')
 
     elif filt_type == 'IIR':
 

From 993893c7c5b85ed7791c706ec04478cd7966e40e Mon Sep 17 00:00:00 2001
From: ryanhammonds <Ryan.hammonds@utexas.edu>
Date: Thu, 3 Jun 2021 13:52:11 -0700
Subject: [PATCH 9/9] FIR group delay to zero

---
 neurodsp/filt/utils.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/neurodsp/filt/utils.py b/neurodsp/filt/utils.py
index eaae4c53..825ac28b 100644
--- a/neurodsp/filt/utils.py
+++ b/neurodsp/filt/utils.py
@@ -321,7 +321,7 @@ def gen_filt_str(pass_type, filt_type, fs, f_db, db, pass_bw,
     if filt_type == 'FIR':
 
         filt_str.append('Phase: linear-phase')
-        filt_str.append('Group Delay: {:1.4f} s'.format((len(f_db)-1) / (2 * fs)))
+        filt_str.append('Group Delay: 0s')
         filt_str.append('Direction: one-pass')
 
     elif filt_type == 'IIR':