Updated docs, dictionary input instead of tuple

Author: jasasonc

FLife Showcase.ipynb

@@ -214,6 +214,7 @@ def __init__(self, input=None, window='hann', nperseg=1280,
 
         # If input is tuple, dictionary is created (backwards compatibility)
         elif isinstance(input, tuple) and len(input) == 2:
+            warnings.warn('Tuple input has been deprecated. Use dictionary input instead.')
             # If input is time signal
             if isinstance(input[0], np.ndarray) and isinstance(input[1], (int, float)):
                 input = {'time_history': input[0], 'dt': input[1]}
@@ -265,7 +266,6 @@ def __init__(self, input=None, window='hann', nperseg=1280,
 
                 # Uniaxial PSD
                 elif input['PSD'].ndim==1:
-                    print('Input PSD is uniaxial')
                     psd = input['PSD']
                     f = input['f']
                     self.psd = np.column_stack((f, psd))
@@ -285,9 +285,6 @@ def __init__(self, input=None, window='hann', nperseg=1280,
                     ):     
                         if self.multiaxial_amplitude_spectrum[0].ndim == 3:
                             self.multipoint = True
-                        
-
-                        #print('Input PSD is correct shape')
 
                         if T is not None and fs is not None:
                             self.t = T

FLife/spectralData.py

@@ -70,7 +70,8 @@ Here is a simple example on how to use the code:
     k = 7.3 # S-N curve inverse slope [/]
 
     # Spectral data
-    sd = FLife.SpectralData(input=(x, dt))
+    input_dict = {'time_history': x, 'dt': dt}
+    sd = FLife.SpectralData(input=input_dict)
 
     # Rainflow reference fatigue life 
     # (do not be confused here, spectral data object also holds the time domain data)
@@ -90,9 +91,8 @@ SpectralData object contains data, required for fatigue-life estimation: power s
 SpectralData is instantiated with `input` parameter:
 
     - `input` = 'GUI' - PSD is provided by user via GUI (graphically and tabulary)
-    - `input` = (PSD, freq) - tuple of PSD and frequency vector is provided.
-    - `input` = (x, dt) - tuple of time history and sampling period is provided.
-
+    - `input` = dictionary with PSD and frequency vector is provided. (keys ``PSD`` and ``f``)
+    - `input` = dictionary with time history and sampling period is provided. (keys ``time_history`` and ``dt``)
 GUI
 ***
 .. code-block:: python
@@ -137,9 +137,11 @@ Optional parameter for time-history is random generator instance `rg` (numpy.ran
     A = 1 # PSD value
     PSD = np.interp(freq, [f_low, f_high], [A,A], left=0, right=0) # Flat-shaped one-sided PSD
     
-    sd4 = FLife.SpectralData(input = (PSD, freq))
+    input_dict = {'PSD': PSD, 'f': freq}
+
+    sd4 = FLife.SpectralData(input = input_dict)
     # time-history can be generated at SpectralData object instantiation. Sampling frequency `fs` and signal length `T` parameter are needed.
-    sd5 = FLife.SpectralData(input = (PSD, freq), T=1, fs=1e5, rg=rg)
+    sd5 = FLife.SpectralData(input = input_dict, T=1, fs=1e5, rg=rg)
 
     time_history = sd5.data
     # time-history duration and sampling period are dependent on frequency vector length and step
@@ -164,7 +166,9 @@ Time history `x` and sampling period `dt` are given as input. `x` must be of typ
     time, signal = FLife.tools.random_gaussian(freq=freq, PSD=PSD, T=10, fs=1e3, rg=rg)
     dt = time[1]
 
-    sd6 = FLife.SpectralData(input=(signal,dt))
+    input_dict = {'time_history': signal, 'dt': dt}
+
+    sd6 = FLife.SpectralData(input=input_dict)
 
     # Get PSD data from spectralData object
     freq = sd6.psd[:,0]

README.rst

@@ -59,7 +59,8 @@ Here is a simple example on how to use the code:
     k = 7.3 # S-N curve inverse slope [/]
 
     # Spectral data
-    sd = FLife.SpectralData(input=(x, dt))
+    input_dict = {'time_history': x, 'dt': dt}
+    sd = FLife.SpectralData(input=input_dict)
 
     # Rainflow reference fatigue life 
     # (do not be confused here, spectral data object also holds the time domain data)
@@ -79,8 +80,8 @@ SpectralData object contains data, required for fatigue-life estimation: power s
 SpectralData is instantiated with `input` parameter:
 
     - `input` = 'GUI' - PSD is provided by user via GUI (graphically and tabulary)
-    - `input` = (PSD, freq) - tuple of PSD and frequency vector is provided.
-    - `input` = (x, dt) - tuple of time history and sampling period is provided.
+    - `input` = dictionary with PSD and frequency vector is provided. (keys ``PSD`` and ``f``)
+    - `input` = dictionary with time history and sampling period is provided. (keys ``time_history`` and ``dt``)
 
 GUI
 ***
@@ -126,9 +127,11 @@ Optional parameter for time-history is random generator instance `rg` (numpy.ran
     A = 1 # PSD value
     PSD = np.interp(freq, [f_low, f_high], [A,A], left=0, right=0) # Flat-shaped one-sided PSD
     
-    sd4 = FLife.SpectralData(input = (PSD, freq))
+    input_dict = {'PSD': PSD, 'f': freq}
+
+    sd4 = FLife.SpectralData(input = input_dict)
     # time-history can be generated at SpectralData object instantiation. Sampling frequency `fs` and signal length `T` parameter are needed.
-    sd5 = FLife.SpectralData(input = (PSD, freq), T=1, fs=1e5, rg=rg)
+    sd5 = FLife.SpectralData(input = input_dict, T=1, fs=1e5, rg=rg)
 
     time_history = sd5.data
     # time-history duration and sampling period are dependent on frequency vector length and step
@@ -153,7 +156,9 @@ Time history `x` and sampling period `dt` are given as input. `x` must be of typ
     time, signal = FLife.tools.random_gaussian(freq=freq, PSD=PSD, T=10, fs=1e3, rg=rg)
     dt = time[1]
 
-    sd6 = FLife.SpectralData(input=(signal,dt))
+    input_dict = {'time_history': signal, 'dt': dt}
+
+    sd6 = FLife.SpectralData(input=input_dict)
 
     # Get PSD data from spectralData object
     freq = sd6.psd[:,0]

docs/source/FLife.rst

@@ -23,7 +23,7 @@ def test_data():
         'coin_liwi': 2044.550993026664, #k_a=1.70, k_phi=0.90
         'EVMS_out_of_phase': 2083.2568582803156,
         'Nieslony': 1592.0621836751761, #s_af = 1, tau_af = 1
-        'Lemaitre': 1942.5082573579468 # poisson_ratio = 0.5
+        'Lemaitre': 1942.5082573579468 # poisson_ratio = 0.3
     }
 
     #test_PSD