fixed documentation for pypi release; v. 0.9.11

metabolabpy/__init__.py

@@ -1,4 +1,4 @@
 __author__ = 'Christian Ludwig ([email protected])'
 __credits__ = 'Christian Ludwig ([email protected])'
-__version__ = '0.9.9'
+__version__ = '0.9.11'
 __license__ = 'GPLv3'

metabolabpy/nmr/nmrData.py

@@ -343,7 +343,7 @@ def autobaseline1d(self, lam=1e6, alg='rolling_ball', max_iter=50, alpha=0.1, be
         if alg == 'irsqr':
             baseline_fitter = Baseline(spc, check_finite=False)
             baseline, params = baseline_fitter.irsqr(spc, lam=lam, quantile=quantile) # poly_order=poly_order, method='imodpoly')
-        if alg == 'airpls':
+        if alg == 'irsqr':
             baseline_fitter = Baseline(spc, check_finite=False)
             baseline, params = baseline_fitter.airpls(spc, 1e5)  # poly_order=poly_order, method='imodpoly')
             #baseline = airpls(spc, lam=lam, max_iter=max_iter)
@@ -386,11 +386,8 @@ def autobaseline1d(self, lam=1e6, alg='rolling_ball', max_iter=50, alpha=0.1, be
         elif alg == 'noise_median':
             baseline = noise_median(spc)
         elif alg == 'snip':
-            print('111111')
             baseline_fitter = Baseline(spc, check_finite=False)
-            print('222222')
             baseline, params = baseline_fitter.snip(spc, 32, decreasing=True, extrapolating_window=34, smooth_window=8)
-            print(f'len(spc): {len(spc)}, len(baseline): {len(baseline)}')
         elif alg == 'adaptive_minimax':
             baseline_fitter = Baseline(spc, check_finite=False)
             poly_order = 4
@@ -810,7 +807,7 @@ def conv(self, fid):
                 win[k] = math.cos((math.pi * (k - ws2)) / (2 * ws2 + 2))
                 s_win += win[k]
 
-        fid2 = np.convolve(win, fid) / s_win
+        fid2 = np.convolve(fid, win) / s_win
         # Extrapolation of first sw2 data points
         idx = np.linspace(2 * ws2 - 1, 0, 2 * ws2, dtype='int')
         idx2 = np.linspace(0, 2 * ws2 - 1, 2 * ws2, dtype='int')
@@ -1279,6 +1276,12 @@ def proc_spc1d(self, reset_spline=False):
 
     def proc_spc2d(self, test_quad_2d=False, no_abs=False):
         fid = np.copy(self.fid)
+        if self.proc.n_points[0] < len(fid[0]):
+            self.proc.n_points[0] = len(fid[0])
+
+        if self.proc.n_points[1] < len(fid):
+            self.proc.n_points[1] = len(fid)
+
         if self.proc.mult_factor[0] == 0:
             self.proc.mult_factor[0] = self.proc.n_points[0] / len(self.fid[0])
 
@@ -2298,7 +2301,8 @@ def wavewat(self, fid):
         fida = np.zeros(2*npts2, dtype='complex128')
         fida[npts2:npts2 + npts - gd] = fid[gd:]
         fida[npts2 - npts +gd:npts2] = np.flip(fid[gd:])
-        fid2 = pywt.mra(data=fida, wavelet=self.proc.ww_wavelet, transform='dwt')
+        ww_wavelet = self.proc.ww_wavelet_type + self.proc.ww_wavelet_type_number
+        fid2 = pywt.mra(data=fida, wavelet=ww_wavelet, transform='dwt')
         fid3 = np.zeros(2*npts2, dtype='complex128')
         n_mra = len(fid2)
         for k in range(self.proc.ww_start, n_mra):

metabolabpy/nmr/nmrDataSet.py

@@ -51,6 +51,24 @@ def __init__(self):
         self.hsqc_spin_sys_connected = True
         self.data_set_name = ''
         self.data_set_number = ''
+        self.baseline_algs = ['irsqr', 'arpls', 'asls', 'aspls', 'derpsalsa', 'drpls', 'iarpls', 'iasls', 'psalsa', 'mpls',
+                         'mor', 'imor', 'mormol', 'amormol', 'rolling_ball', 'mwmv', 'tophat', 'mpspline', 'jbcd',
+                         'noise_median', 'snip', 'adaptive_minimax', 'swima', 'ipsa', 'ria', 'dietrich',
+                         'std_distribution', 'fastchrom', 'cwt_br', 'fabc', 'beads', 'poly', 'modpoly', 'imodpoly',
+                         'penalized_poly', 'quant_reg', 'goldindec', ]
+        self.default_baseline_alg = 'rolling_ball'
+        self.default_lam = 1e5
+        self.default_max_iter = 50
+        self.default_alpha = 0.1
+        self.default_beta = 10
+        self.default_gamma = 15
+        self.default_beta_mult = 0.98
+        self.default_gamma_mult = 0.94
+        self.default_half_window = 4096
+        self.default_smooth_half_window = 16
+        self.default_quantile = 0.3
+        self.default_poly_order = 4
+        self.default_add_ext = 2
         # end __init__
 
     def add_peak(self, start_end=np.array([], dtype='float64'), peak_label=''):

metabolabpy/nmr/procPars.py

@@ -30,7 +30,7 @@ def __init__(self):
         self.ssb = np.array([0.0, 0.0, 0.0])
         self.axis_nucleus = np.array(['      ', '      ', '      '], dtype='str')
         self.aunmp = str('')
-        self.poly_order = 4
+        self.poly_order = 24
         self.water_suppression = 0
         self.gibbs = np.array([True, True, False])
         self.conv_extrapolation_size = np.array([32, 0, 0])
@@ -92,22 +92,41 @@ def __init__(self):
             "Wavewat": 3
         }
         self.data_type = ''
-        self.autobaseline_alg = 'jbcd'
-        self.autobaseline_lam = 1e6
+        self.autobaseline_alg = 'rolling_ball'
+        self.autobaseline_lam = 1e5
         self.autobaseline_max_iter = 50
         self.autobaseline_alpha = 0.1
         self.autobaseline_beta = 10
         self.autobaseline_gamma = 15
         self.autobaseline_beta_mult = 0.98
         self.autobaseline_gamma_mult = 0.94
-        self.autobaseline_half_window = None
+        self.autobaseline_half_window = 4096
         self.autobaseline_quantile = 0.3
         self.autobaseline_poly_order = 4
-        self.autobaseline_smooth_half_window = 32
+        self.autobaseline_smooth_half_window = 16
         self.autobaseline_add_ext = 2
         self.ww_start = 9
         self.ww_zf = 16
-        self.ww_wavelet = 'rbio6.8'
+        self.ww_wavelet_type = 'db'
+        self.ww_wavelet_type_number = '10'
+        self.ww_wavelet_number = 11
+        self.wavelet_names = ['bior', 'coif', 'db', 'dmey', 'haar', 'rbio', 'sym']
+        self.wavelet_numbers = {
+            'bior': ['1.1', '1.3', '1.5', '2.2', '2.4', '2.6', '2.8', '3.1', '3.3', '3.5', '3.7', '3.9', '4.4', '5.5',
+                     '6.8'], 'cgau': ['1', '2', '3', '4', '5', '6', '7', '8'],
+            'coif': ['1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14', '15', '16', '17'],
+            'db': ['1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14', '15', '16', '17', '18',
+                   '19', '20', '21', '22', '23', '24', '25', '26', '27', '28', '29', '30', '31', '32', '33', '34', '35',
+                   '36', '37', '38'], 'dmey': [''], 'haar': [''],
+            'rbio': ['1.1', '1.3', '1.5', '2.2', '2.4', '2.6', '2.8', '3.1', '3.3', '3.5', '3.7', '3.9', '4.4', '5.5',
+                     '6.8'],
+            'sym': ['2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14', '15', '16', '17', '18', '19',
+                    '20']}
+        self.wavelet_default = {'bior': 11, 'coif': 11, 'db': 9, 'dmey': 0,
+                                'haar': 0, 'rbio': 11, 'sym': 7}
+        self.wavelet_start_default = {'bior': 9, 'coif': 7, 'db': 9, 'dmey': 7,
+                                'haar': 7, 'rbio': 9, 'sym': 9}
+
         # end __init__
 
     def __str__(self):  # pragma: no cover

upload_pypi.sh

@@ -1,10 +1,4 @@
 #!/bin/bash
 
-conda activate pypi
-python setup.py sdist
 
-twine upload --repository-url https://test.pypi.org/legacy/ dist/*
-#pip install --index-url https://test.pypi.org/simple --extra-index-url https://pypi.org/simple metabolabpy==0.6.1
-
-conda deactivate 
-#comment
+twine upload -u __token__ -p $ml_token $1