Merge pull request #161 from VTDA-Group/additional_small_changes

hotfix to allow old LCs to be read

src/superphot_plus/data_generation/make_fake_spp_data.py

@@ -204,23 +204,20 @@ def create_ztf_model(plot=False):
     tdata = np.random.uniform(-100, 100, num_observations)
     filter_data = np.random.choice(["g", "r"], size=num_observations)
 
-    cube = create_prior(cube)
-    A, beta, gamma, t0, tau_rise, tau_fall, es = cube[:7]  # pylint: disable=unused-variable
-
     found_valid = False
     num_tried = 0
 
     # Now re-attempts to regenerate until it gets a "good" model
     while not found_valid and num_tried < 100:
-        cube = create_prior(cube)
-        A, beta, gamma, t0, tau_rise, tau_fall, es = cube[:7]  # pylint: disable=unused-variable
+        params = create_prior(np.copy(cube))
+        A, beta, gamma, t0, tau_rise, tau_fall, es = params[:7]  # pylint: disable=unused-variable
         found_valid = params_valid(beta, gamma, tau_rise, tau_fall)
         num_tried += 1
 
     if not found_valid:
         return "Failure"
 
-    f_model = flux_model(cube, tdata, filter_data, ["g", "r"], "r")
+    f_model = flux_model(params, tdata, filter_data, ["r", "g"], "r")
     snr = ztf_noise_model(f_model, filter_data)
 
     gind = np.where(snr > 3)  # any points with SNR < 3 are ignored
@@ -238,7 +235,9 @@ def create_ztf_model(plot=False):
         plt.xlabel("Time (days)")
         plt.ylabel("Flux (arbitrary units)")
         plt.show()
-    return cube[:7], tdata, filter_data, dirty_model, sigmas
+    return params[:7], tdata, filter_data, dirty_model, sigmas
 
 
 # Can run this with create_model(plot=True)
+if __name__ == "__main__":
+    create_ztf_model(plot=True)

src/superphot_plus/lightcurve.py

@@ -329,7 +329,7 @@ def from_file(cls, filename, ref_band="r", t0_lim=None, shift_time=True):
         arr = None
         property_dict = {}
         for k in npy_array.files:
-            if k == "lcs":
+            if k == "lcs" or k == "arr_0": #hotfix to handle old LC format
                 arr = npy_array[k]
             else:
                 property_dict[k] = npy_array[k]
@@ -340,6 +340,11 @@ def from_file(cls, filename, ref_band="r", t0_lim=None, shift_time=True):
         fdata = arr[1][good_rows].astype(float)
         edata = arr[2][good_rows].astype(float)
         bdata = arr[3][good_rows]
+
+        if 'name' not in property_dict:
+            file_prefix = filename.split("/")[-1].split(".")[0]
+            property_dict['name'] = file_prefix
+
         lc = Lightcurve(
             tdata, fdata, edata, bdata,
             **property_dict

src/superphot_plus/utils.py

@@ -249,6 +249,11 @@ def params_valid(beta, gamma, tau_rise, tau_fall):
     bool
         True if parameters are valid, False otherwise.
     """
+    if np.any(np.isnan(
+        [beta, gamma, tau_rise, tau_fall]
+    )):
+        return False
+
     if tau_fall > 1.0 / beta:
         return False