diff --git a/environment.yml b/environment.yml index 2b88ead0..02a88e5e 100644 --- a/environment.yml +++ b/environment.yml @@ -8,7 +8,7 @@ dependencies: - python=3.11.0 - cartopy - numba - - scipy<1.16 + - scipy - pyyaml - requests - scikit-learn @@ -18,8 +18,8 @@ dependencies: - tqdm - wget - pip - - pytest - pip: + - pytest - pyhht - dill - '-e .' diff --git a/pyleoclim/core/correns.py b/pyleoclim/core/correns.py index 1653547c..a8830c55 100644 --- a/pyleoclim/core/correns.py +++ b/pyleoclim/core/correns.py @@ -202,7 +202,7 @@ def plot(self, figsize=[4, 4], title=None, ax=None, savefig_settings=None, hist_ # put everything into a dataframe to be able to use seaborn - data = np.empty((len(self.r),3)); data[:] = np.NaN + data = np.empty((len(self.r),3)); data[:] = np.nan col = [f'p < {self.alpha} (w/ FDR)',f'p < {self.alpha} (w/o FDR)', f'p ≥ {self.alpha}'] data[self.signif_fdr,0] = r_signif_fdr data[self.signif, 1] = r_signif diff --git a/pyleoclim/utils/spectral.py b/pyleoclim/utils/spectral.py index e1f61d09..aff15577 100644 --- a/pyleoclim/utils/spectral.py +++ b/pyleoclim/utils/spectral.py @@ -1025,10 +1025,10 @@ def cwt_psd(ys, ts, freq=None, freq_method='log', freq_kwargs=None,scale = None, def beta_estimation(psd, freq, fmin=None, fmax=None, logf_binning_step='max', verbose=False): ''' Estimate the scaling exponent of a power spectral density. - Models the spectrum as :math: `S(f) \propto 1/f^{\beta}`. For instance: - - :math: `\beta = 0` corresponds to white noise - - :math: `\beta = 1` corresponds to pink noise - - :math: `\beta = 2` corresponds to red noise (Brownian motion) + Models the spectrum as :math: `S(f) \\propto 1/f^{\\beta}`. For instance: + - :math: `\\beta = 0` corresponds to white noise + - :math: `\\beta = 1` corresponds to pink noise + - :math: `\\beta = 2` corresponds to red noise (Brownian motion) Parameters @@ -1170,7 +1170,7 @@ def beta2Hurst(beta): Parameters ---------- beta : float - the estimated slope of a power spectral density :math: `S(f) \propto 1/f^{\beta}` + the estimated slope of a power spectral density :math: `S(f) \\propto 1/f^{\\beta}` Returns ------- diff --git a/pyleoclim/utils/tsutils.py b/pyleoclim/utils/tsutils.py index 740dcbb8..beaa0df6 100644 --- a/pyleoclim/utils/tsutils.py +++ b/pyleoclim/utils/tsutils.py @@ -1316,7 +1316,7 @@ def gaussianize(ys): # Create a blank copy of the array. yg = copy.deepcopy(ys) - yg[:] = np.NAN + yg[:] = np.nan nz = np.logical_not(np.isnan(ys)) index = np.argsort(ys[nz]) diff --git a/pyproject.toml b/pyproject.toml index ed2aca4d..e4b5a517 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -25,17 +25,15 @@ dependencies = [ "seaborn>=0.13.0", "scikit-learn>=0.24.2", "pathos>=0.2.8", - "tqdm>=4.61.2", - "tftb>=0.1.3", + "tqdm", "wget>=3.2", "numba>=0.56", "nitime>=0.9", "tabulate>=0.8.9", - "Unidecode>=1.1.1", "cartopy>=0.22.0", "pyyaml", "beautifulsoup4", - "scipy<1.16.0", + "scipy>=1.15.0", "requests", "dill", ]