SDT and pytest dependencies made optional

README.md

@@ -40,12 +40,24 @@ MOSQITO is available on [pip](https://pypi.org/project/pip/). Simply type in a s
 
     pip install mosqito
 
-This command line should download and install MOSQITO on your computer, along with all the needed dependencies.
+This command line should download and install MOSQITO on your computer, along with the dependencies needed to compute SQ metrics.
+
+If you want to perform tests, for instance if you developed a new feature, you will need pytest dependency that can be installed using:
+
+    pip install mosqito[testing]
 
 If you need to import .uff or .unv files, you will need the pyuff package dependency. Note that 'pyuff' is released under the GPL license which prevents MOSQITO from being used in other software that must be under a more permissive license. To include the 'pyuff' dependancy anyway, type the following command:
 
     pip install mosqito[uff]
 
+If you want to use MOSQITO coupled with SciDataTool, you will need SDT package dependency. To install it along with MOSQITO, use the following command:
+
+    pip install mosqito[SciDataTool]
+
+Note that all the depencies needed for uff, SDT and tests proceeding can be installed at once using:
+
+    pip install mosqito[all]
+
 ## Contact
 
 You can contact us on Github by opening an issue (to request a feature, ask a question or report a bug). 

full_requirements.txt

@@ -0,0 +1,6 @@
+numpy
+scipy
+matplotlib
+pyuff
+pytest
+scidatatool

mosqito/classes/Audio.py

@@ -5,8 +5,12 @@
 @author: wantysal
 """
 
-# import SciDataTool objects
-from SciDataTool import DataTime, DataLinspace
+# Optional package import
+try:
+    import SciDataTool
+except ImportError:
+    SciDataTool = None
+
 
 # import methods
 from mosqito.functions.shared.load import load
@@ -44,6 +48,10 @@ def __init__(self, file, is_stationary=False, calib=1, mat_signal="", mat_fs="")
             in case of a .mat file, name of the sampling frequency variable
 
         """
+        if SciDataTool is None:
+            raise RuntimeError(
+                "In order to create an audio object you need the 'SciDataTool' package."
+                )
 
         # Import audio signal
         values, fs = load(
@@ -54,7 +62,7 @@ def __init__(self, file, is_stationary=False, calib=1, mat_signal="", mat_fs="")
         )
 
         # Create Data object for time axis
-        time_axis = DataLinspace(
+        time_axis = SciDataTool.DataLinspace(
             name="time",
             unit="s",
             initial=0,
@@ -66,7 +74,7 @@ def __init__(self, file, is_stationary=False, calib=1, mat_signal="", mat_fs="")
         # Create audio signal Data object and populate the object
         self.fs = fs
         self.is_stationary = is_stationary
-        self.signal = DataTime(
+        self.signal = SciDataTool.DataTime(
             name="Audio signal",
             symbol="x",
             unit="Pa",

mosqito/methods/Audio/comp_3oct_spec.py

@@ -1,10 +1,11 @@
 # -*- coding: utf-8 -*-
 
-from numpy import squeeze
+# Optional package import
+try:
+    import SciDataTool
+except ImportError:
+    SciDataTool = None
 
-from SciDataTool import Data1D, DataTime, DataFreq
-
-from mosqito.functions.shared.A_weighting import A_weighting
 from mosqito.functions.loudness_zwicker.calc_third_octave_levels import (
     calc_third_octave_levels,
 )
@@ -26,6 +27,12 @@ def comp_3oct_spec(
         Filter center frequency of the highest 1/3 oct. band [Hz]
 
     """
+
+    if SciDataTool is None:
+        raise RuntimeError(
+            "In order to create an audio object you need the 'SciDataTool' package."
+            )
+
 
     # Compute third octave band spectrum
     if self.is_stationary:
@@ -41,22 +48,22 @@ def comp_3oct_spec(
         third_spec = 2e-5 * 10 ** (third_spec / 20)
 
     # Define axis objects
-    frequency = Data1D(
+    frequency = SciDataTool.Data1D(
         name="freqs",
         unit="Hz",
         values=freq_val,
     )
     axes = [frequency]
     if not self.is_stationary:
-        time = Data1D(
+        time = SciDataTool.Data1D(
             name="time",
             unit="s",
             values=time_val,
         )
         axes.append(time)
 
     # Define Data object
-    self.third_spec = DataFreq(
+    self.third_spec = SciDataTool.DataFreq(
         name="Audio signal",
         symbol="x",
         axes=axes,

mosqito/methods/Audio/compute_level.py

@@ -2,7 +2,11 @@
 
 from numpy import log10, linspace, mean, sqrt
 
-from SciDataTool import Data1D, DataTime
+# Optional package import
+try:
+    import SciDataTool
+except ImportError:
+    SciDataTool = None
 
 
 def compute_level(self, nb_points=[], start=[], stop=[]):
@@ -23,6 +27,12 @@ def compute_level(self, nb_points=[], start=[], stop=[]):
         SPL in dB
 
     """
+    if SciDataTool is None:
+        raise RuntimeError(
+            "In order to create an audio object you need the 'SciDataTool' package."
+            )
+
+
     # Check the inputs
     if nb_points != []:
         if type(nb_points) != int:
@@ -67,7 +77,7 @@ def compute_level(self, nb_points=[], start=[], stop=[]):
     # Case of a given number of points
     if nb_points != []:
 
-        time = Data1D(
+        time = SciDataTool.Data1D(
             name="time", unit="s", values=linspace(start, stop, num=nb_points)
         )
 
@@ -77,7 +87,7 @@ def compute_level(self, nb_points=[], start=[], stop=[]):
             peff = sqrt(mean(frame_i ** 2))
             level.append(10 * log10((peff ** 2 / (2e-05) ** 2)))
 
-        self.level = DataTime(
+        self.level = SciDataTool.DataTime(
             name="Sound Pressure Level",
             symbol="SPL",
             unit="dB",

mosqito/methods/Audio/compute_loudness.py

@@ -1,6 +1,10 @@
 # -*- coding: utf-8 -*-
 
-from SciDataTool import DataLinspace, DataTime, DataFreq, Data1D
+# Optional package import
+try:
+    import SciDataTool
+except ImportError:
+    SciDataTool = None
 
 from mosqito.functions.loudness_zwicker.loudness_zwicker_stationary import (
     loudness_zwicker_stationary,
@@ -19,13 +23,17 @@ def compute_loudness(self, field_type="free"):
         'free' by default or 'diffuse'
 
     """
+    if SciDataTool is None:
+        raise RuntimeError(
+            "In order to create an audio object you need the 'SciDataTool' package."
+            )
 
     # Compute third octave band spetrum if necessary
     if self.third_spec == None:
         self.comp_3oct_spec()
 
     # define bark_axis
-    barks = DataLinspace(
+    barks = SciDataTool.DataLinspace(
         name="cr_band",
         unit="Bark",
         initial=0.1,
@@ -49,10 +57,10 @@ def compute_loudness(self, field_type="free"):
         )
         # Get time axis
         # Decimation from temporal resolution 0.5 ms to 2ms
-        time = Data1D(
+        time = SciDataTool.Data1D(
             name="time", unit="s", values=self.third_spec.get_axes()[1].values[::4]
         )
-        self.loudness_zwicker = DataTime(
+        self.loudness_zwicker = SciDataTool.DataTime(
             name="Loudness",
             symbol="N_{zw}",
             unit="sone",
@@ -61,7 +69,7 @@ def compute_loudness(self, field_type="free"):
         )
         axes = [barks, time]
 
-    self.loudness_zwicker_specific = DataFreq(
+    self.loudness_zwicker_specific = SciDataTool.DataFreq(
         name="Specific Loudness",
         symbol="N'_{zw}",
         unit="sone/Bark",

mosqito/methods/Audio/compute_roughness.py

@@ -2,11 +2,13 @@
 """
 Created on Tue Feb 23 14:05:22 2021
 
-@author: Salomé
+@author: wantysal
 """
-# Import SciDataTool objects
-
-from SciDataTool import DataTime, Data1D
+# Optional package import
+try:
+    import SciDataTool
+except ImportError:
+    SciDataTool = None
 
 # Import MOSQITO function
 from mosqito.functions.roughness_danielweber.comp_roughness import comp_roughness
@@ -23,6 +25,11 @@ def compute_roughness(self, method="dw", overlap=0.5):
         overlapping coefficient for the time windows of 200ms, default is 0.5
     """
 
+    if SciDataTool is None:
+        raise RuntimeError(
+            "In order to create an audio object you need the 'SciDataTool' package."
+            )
+
     # check the input parameters
     if method != "dw":
         raise ValueError("ERROR: method must be 'dw'")
@@ -32,9 +39,9 @@ def compute_roughness(self, method="dw", overlap=0.5):
 
     R = comp_roughness(self.signal.values, self.fs, overlap)
 
-    time = Data1D(name="time", unit="s", values=R["time"])
+    time = SciDataTool.Data1D(name="time", unit="s", values=R["time"])
 
-    self.roughness["Daniel Weber"] = DataTime(
+    self.roughness["Daniel Weber"] = SciDataTool.DataTime(
         symbol="R_{dw}",
         axes=[time],
         values=R["values"],

mosqito/methods/Audio/compute_sharpness.py

@@ -6,8 +6,11 @@
 """
 import numpy as np
 
-# Import SciDataTool objects
-from SciDataTool import DataTime, Data1D
+# Optional package import
+try:
+    import SciDataTool
+except ImportError:
+    SciDataTool = None
 
 # Import MOSQITO functions
 from mosqito.functions.sharpness.sharpness_aures import comp_sharpness_aures
@@ -27,6 +30,11 @@ def compute_sharpness(self, method="din", skip=0.2):
         number of second to be cut at the beginning of the analysis
 
     """
+    if SciDataTool is None:
+        raise RuntimeError(
+            "In order to create an audio object you need the 'SciDataTool' package."
+            )
+
     # check the input parameters
     if (
         method != "din"
@@ -72,14 +80,14 @@ def compute_sharpness(self, method="din", skip=0.2):
             S = S[cut_index:]
 
             # Define time axis
-            time = Data1D(
+            time = SciDataTool.Data1D(
                 symbol="T",
                 name="time",
                 unit="s",
                 values=self.loudness_zwicker.get_axes()[0].values[cut_index:],
             )
 
-            self.sharpness["din"] = DataTime(
+            self.sharpness["din"] = SciDataTool.DataTime(
                 symbol="S_{DIN}", axes=[time], values=S, name="Sharpness", unit="Acum"
             )
 
@@ -111,14 +119,14 @@ def compute_sharpness(self, method="din", skip=0.2):
             S = S[cut_index:]
 
             # Define time axis
-            time = Data1D(
+            time = SciDataTool.Data1D(
                 symbol="T",
                 name="time",
                 unit="s",
                 values=self.loudness_zwicker.get_axes()[0].values[cut_index:],
             )
 
-            self.sharpness["aures"] = DataTime(
+            self.sharpness["aures"] = SciDataTool.DataTime(
                 symbol="S_{Aures}", axes=[time], values=S, name="Sharpness", unit="Acum"
             )
 
@@ -149,14 +157,14 @@ def compute_sharpness(self, method="din", skip=0.2):
             S = S[cut_index:]
 
             # Define time axis
-            time = Data1D(
+            time = SciDataTool.Data1D(
                 symbol="T",
                 name="time",
                 unit="s",
                 values=self.loudness_zwicker.get_axes()[0].values[cut_index:],
             )
 
-            self.sharpness["bismarck"] = DataTime(
+            self.sharpness["bismarck"] = SciDataTool.DataTime(
                 symbol="S_{Bismarck}",
                 axes=[time],
                 values=S,
@@ -191,13 +199,13 @@ def compute_sharpness(self, method="din", skip=0.2):
             S = S[cut_index:]
 
             # Define time axis
-            time = Data1D(
+            time = SciDataTool.Data1D(
                 symbol="T",
                 name="time",
                 unit="s",
                 values=self.loudness_zwicker.get_axes()[0].values[cut_index:],
             )
 
-            self.sharpness["fastl"] = DataTime(
+            self.sharpness["fastl"] = SciDataTool.DataTime(
                 symbol="S_{Fastl}", axes=[time], values=S, name="Sharpness", unit="Acum"
             )