Merge pull request #87 from NSLS-II/updates-20240515-generic-function

modified the verbos status

chx_packages_local.py

@@ -44,9 +44,13 @@
 from chx_compress import (
     MultifileBNLCustom,
     combine_binary_files,
+    compress_eigerdata,
     create_compress_header,
+    get_eigerImage_per_file,
+    init_compress_eigerdata,
     para_compress_eigerdata,
     para_segment_compress_eigerdata,
+    read_compressed_eigerdata,
     segment_compress_eigerdata,
 )
 
@@ -306,6 +310,7 @@
     get_seg_from_ring_mask,
     get_t_iq,
     get_t_iqc,
+    get_t_iqc_imstack,
     multi_uids_saxs_xpcs_analysis,
     plot_circular_average,
     plot_qIq_with_ROI,

pyCHX/XPCS_SAXS.py

@@ -761,6 +761,83 @@ def get_t_iqc(FD, frame_edge, mask, pargs, nx=1500, plot_=False, save=False, sho
     return qp, np.array(iqs), q
 
 
+def get_t_iqc_imstack(
+    imgs, frame_edge, mask, pargs, nx=1500, plot_=False, save=False, show_progress=True, *argv, **kwargs
+):
+    """
+    Get t-dependent Iq
+
+    variant of get_t_iqc that takes an image stack like a dask array to calculate average images and then does the radial integration
+    variant by LW 05/162024
+
+    Parameters
+    ----------
+    imgs:  image stack like dask array
+    frame_edge: list, the ROI frame regions, e.g., [  [0,100], [200,400] ]
+    mask:  a image mask
+
+    nx : int, optional
+        number of bins in x
+        defaults is 1500 bins
+    plot_: a boolen type, if True, plot the time~one-D curve with qp as x-axis
+    Returns
+    ---------
+    qp: q in pixel
+    iq: intensity of circular average
+    q: q in real unit (A-1)
+
+    """
+
+    Nt = len(frame_edge)
+    iqs = list(np.zeros(Nt))
+    for i in range(Nt):
+        t1, t2 = frame_edge[i]
+        # print (t1,t2)
+        avg_img = np.average(imgs[t1:t2, :, :], axis=0)
+        qp, iqs[i], q = get_circular_average(avg_img, mask, pargs, nx=nx, plot_=False)
+
+    if plot_:
+        fig, ax = plt.subplots(figsize=(8, 6))
+        for i in range(Nt):
+            t1, t2 = frame_edge[i]
+            ax.semilogy(q, iqs[i], label="frame: %s--%s" % (t1, t2))
+            # ax.set_xlabel("q in pixel")
+            ax.set_xlabel("Q " r"($\AA^{-1}$)")
+            ax.set_ylabel("I(q)")
+
+        if "xlim" in kwargs.keys():
+            ax.set_xlim(kwargs["xlim"])
+        if "ylim" in kwargs.keys():
+            ax.set_ylim(kwargs["ylim"])
+
+        ax.legend(
+            loc="best",
+        )
+
+        uid = pargs["uid"]
+        title = ax.set_title("uid= %s--t~I(q)" % uid)
+        title.set_y(1.01)
+        if save:
+            # dt =datetime.now()
+            # CurTime = '%s%02d%02d-%02d%02d-' % (dt.year, dt.month, dt.day,dt.hour,dt.minute)
+            path = pargs["path"]
+            uid = pargs["uid"]
+            # fp = path + 'uid= %s--Iq~t-'%uid + CurTime + '.png'
+            fp = path + "uid=%s--Iq-t-" % uid + ".png"
+            fig.savefig(fp, dpi=fig.dpi)
+
+            save_arrays(
+                np.vstack([q, np.array(iqs)]).T,
+                label=["q_A-1"] + ["Fram-%s-%s" % (t[0], t[1]) for t in frame_edge],
+                filename="uid=%s-q-Iqt.csv" % uid,
+                path=path,
+            )
+
+        # plt.show()
+
+    return qp, np.array(iqs), q
+
+
 def plot_t_iqc(q, iqs, frame_edge, pargs, save=True, return_fig=False, legend_size=None, *argv, **kwargs):
     """Plot t-dependent Iq
 

pyCHX/chx_generic_functions.py

@@ -3401,7 +3401,7 @@ def get_sid_filenames(hdr, verbose=False):
     else:
         if verbose:
             print('Found detector filename from "data_path" in metadata!')
-            success = True
+        success = True
 
     if not success:  # looking at path in metadata, but taking the date from the run start document
         data_path = start_doc["data path"][:-11] + strftime("%Y/%m/%d/", localtime(start_doc["time"]))
@@ -3416,7 +3416,7 @@ def get_sid_filenames(hdr, verbose=False):
         else:
             if verbose:
                 print("Found detector filename in %s" % data_path)
-                success = True
+            success = True
 
     if (
         not success
@@ -3433,7 +3433,7 @@ def get_sid_filenames(hdr, verbose=False):
         else:
             if verbose:
                 print("Found detector filename in %s" % data_path)
-                success = True
+            success = True
     return ret
 
 
@@ -3494,6 +3494,8 @@ def load_dask_data(uid, detector, mask_path_full, reverse=False, rot90=False):
     returns detector_images(dask-array), image_md
     LW 04/26/2024
     """
+    import json
+
     import dask
 
     hdr = db[uid]
@@ -3511,24 +3513,25 @@ def load_dask_data(uid, detector, mask_path_full, reverse=False, rot90=False):
     img_md = {}
     for k in list(img_md_dict.keys()):
         img_md[k] = hdr.config_data(det)["primary"][0]["%s_%s" % (det, img_md_dict[k])]
-    if md["detector"] in ["eiger4m_single_image", "eiger1m_single_image", "eiger500K_single_image"]:
+    if detector in ["eiger4m_single_image", "eiger1m_single_image", "eiger500K_single_image"]:
         img_md.update({"y_pixel_size": 7.5e-05, "x_pixel_size": 7.5e-05})
         got_pixel_mask = True
     else:
         img_md.update({"y_pixel_size": None, "x_pixel_size": None})
         got_pixel_mask = False
     # load pixel mask from static location
     if got_pixel_mask:
-        json_open = open(_mask_path_ + "pixel_masks/pixel_mask_compression_%s.json" % detector.split("_")[0])
+        # json_open = open(_mask_path_ + "pixel_masks/pixel_mask_compression_%s.json" % detector.split("_")[0])
+        json_open = open(mask_path_full + "pixel_mask_compression_%s.json" % detector.split("_")[0])
         mask_dict = json.load(json_open)
         img_md["pixel_mask"] = np.array(mask_dict["pixel_mask"])
         img_md["binary_mask"] = np.array(mask_dict["binary_mask"])
         del mask_dict
 
     # load image data as dask-arry:
-    dimg = hdr.xarray_dask()[md["detector"]][0]
+    dimg = hdr.xarray_dask()[detector][0]
     if reverse:
-        dimg = dask.array.flip(dimg, axis=(0, 1))
+        dimg = dask.array.flip(dimg, axis=(1, 1))
     if rot90:
         dimg = dask.array.rot90(dimg, axes=(1, 2))
     return dimg, img_md

pyCHX/chx_packages.py

@@ -34,9 +34,13 @@
 from pyCHX.chx_compress import (
     MultifileBNLCustom,
     combine_binary_files,
+    compress_eigerdata,
     create_compress_header,
+    get_eigerImage_per_file,
+    init_compress_eigerdata,
     para_compress_eigerdata,
     para_segment_compress_eigerdata,
+    read_compressed_eigerdata,
     segment_compress_eigerdata,
 )
 from pyCHX.chx_compress_analysis import (
@@ -242,6 +246,7 @@
     get_seg_from_ring_mask,
     get_t_iq,
     get_t_iqc,
+    get_t_iqc_imstack,
     multi_uids_saxs_xpcs_analysis,
     plot_circular_average,
     plot_qIq_with_ROI,