[ci skip] fix readme links.

README.md

@@ -70,10 +70,10 @@ output = fit_model(observations, model, sps, **config)
 
 Another change is that spectral response functions (i.e. calibration vectors)
 are now handled by specialized sub-classes of these `Observation` classes.  See
-the [spectroscopy docs](docs/spectra.rst) for details.
+the [spectroscopy docs](doc/spectra.rst) for details.
 
 The interface to `write_model` has been changed and simplified.  See
-[usage](docs/usage.rst) for details.
+[usage](doc/usage.rst) for details.
 
 Finally, the output chain or samples is now stored as a structured array, where
 each row corresponds to a sample, and each column is a parameter (possibly

demo/demo_mock_params.py

@@ -92,7 +92,7 @@ def build_obs(snr=10.0, filterset=["sdss_g0", "sdss_r0"],
     :param add_noise: (optional, boolean, default: True)
         If True, add a realization of the noise to the mock spectrum
     """
-    from prospect.data.observation import Photometry, Spectrum
+    from prospect.observation import Photometry, Spectrum
 
     # We'll put the mock data in this dictionary, just as we would for real
     # data.  But we need to know which bands (and wavelengths if doing
@@ -228,13 +228,16 @@ def build_all(config):
     output = fit_model(obs, model, sps, **config)
 
     print("writing to {}".format(hfile))
-    writer.write_hdf5(hfile, run_params, model, obs,
-                      output["sampling"][0], output["optimization"][0],
-                      tsample=output["sampling"][1],
-                      toptimize=output["optimization"][1],
+    writer.write_hdf5(hfile,
+                      config,
+                      model,
+                      obs,
+                      output["sampling"],
+                      output["optimization"],
                       sps=sps
                       )
 
+
     try:
         hfile.close()
     except(AttributeError):

demo/demo_mpi_params.py

@@ -351,11 +351,15 @@ def build_all(**kwargs):
 
 
     hfile = "{0}_{1}_mcmc.h5".format(args.outfile, int(time.time()))
-    writer.write_hdf5(hfile, run_params, model, obs,
-                      output["sampling"][0], output["optimization"][0],
-                      tsample=output["sampling"][1],
-                      toptimize=output["optimization"][1],
-                      sps=sps)
+    writer.write_hdf5(hfile,
+                      run_params,
+                      model,
+                      obs,
+                      output["sampling"],
+                      output["optimization"],
+                      sps=sps
+                      )
+
 
     try:
         hfile.close()

demo/timing.py → tests/timing_basis.py

@@ -40,12 +40,12 @@ def make_agebins(nbin=5, minage=7.0, **extras):
     allages = np.linspace(minage, np.log10(tuniv), nbin)
     allages = np.insert(allages, 0, 0.)
     agebins = np.array([allages[:-1], allages[1:]]).T
-    return agebins    
+    return agebins
 
 
 
 if __name__ == "__main__":
-    
+
     step_params = {'agebins':[[]],
                    'mass': [],
                    'tage': np.array([13.7]),
@@ -63,8 +63,8 @@ def make_agebins(nbin=5, minage=7.0, **extras):
     zlist = [1, 2]
     nlist = [False, True]
 
-    print("Using {} isochrones and {} spectra.\nAsking for single ages.".format(*libs)) 
-    
+    print("Using {} isochrones and {} spectra.\nAsking for single ages.".format(*libs))
+
     # FSPS
     string = "StellarPopulation takes {:7.5f}s per call {} nebular emission and zcontinuous={}."
     params = deepcopy(csp_params)
@@ -84,15 +84,15 @@ def make_agebins(nbin=5, minage=7.0, **extras):
             sps = CSPBasis(zcontinuous=zcont)
             dur = call_duration(sps, ntry, add_neb_emission=[neb], **params)
             print(string.format(dur, w[int(neb)], zcont))
-            
+
     # Step SFH
     nbin = 10
 
     params = deepcopy(step_params)
     params['agebins'] = make_agebins(nbin)
     params['mass'] = np.ones(nbin) * 1.0
     string = "FastStepBasis ({} bins) takes {:7.5f}s per call {} nebular emission and zcontinuous={}."
-    
+
     for zcont in zlist:
         print("\n")
         for neb in nlist:
@@ -101,12 +101,12 @@ def make_agebins(nbin=5, minage=7.0, **extras):
             #print(sps.params, sps.ssp.params['add_neb_emission'])
             print(string.format(nbin, dur, w[int(neb)], zcont))
 
-
 
-
+
+
    # sys.exit()
 
-    
+
     # Now time calls for random Z (which always causes dirtiness=1)
     #setup = "from __main__ import test; import numpy as np"
     #call = "out=get_model(sps, logzsol=[np.random.uniform(-1, 0)], **params)"