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Merge pull request #329 from dmgav/srx-fix-step
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ENH: working code for loading step scan data from Tiled (SRX)
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@dmgav
dmgav authored Oct 11, 2024
2 parents 87a4b75 + ab0a6fe commit 0b6f68e
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Showing 3 changed files with 43 additions and 56 deletions.
4 changes: 2 additions & 2 deletions pyxrf/model/draw_image.py
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Original file line number Diff line number Diff line change
Expand Up @@ -742,7 +742,7 @@ def _adjust_data_range_using_min_ratio(c_min, c_max, c_axis_range, *, min_ratio=
cmap=grey_use,
vmin=low_limit,
vmax=high_limit,
linewidths=1,
# linewidths=1,
linewidth=0,
)
grid[i].set_ylim(yd_axis_max, yd_axis_min)
Expand Down Expand Up @@ -810,7 +810,7 @@ def _adjust_data_range_using_min_ratio(c_min, c_max, c_axis_range, *, min_ratio=
s=500,
alpha=1.0, # Originally: alpha=0.8
cmap=grey_use,
linewidths=1,
# linewidths=1,
linewidth=0,
)
grid[i].set_ylim(yd_axis_min, yd_axis_max)
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4 changes: 2 additions & 2 deletions pyxrf/model/lineplot.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1869,7 +1869,7 @@ def _adjust_data_range_using_min_ratio(c_min, c_max, c_axis_range, *, min_ratio=
cmap=grey_use,
vmin=low_limit,
vmax=high_limit,
linewidths=1,
# linewidths=1,
linewidth=0,
)
grid[i].set_ylim(yd_axis_max, yd_axis_min)
Expand Down Expand Up @@ -1922,7 +1922,7 @@ def _adjust_data_range_using_min_ratio(c_min, c_max, c_axis_range, *, min_ratio=
s=500,
alpha=1.0, # Originally: alpha=0.8
cmap=grey_use,
linewidths=1,
# linewidths=1,
linewidth=0,
)
grid[i].set_ylim(yd_axis_min, yd_axis_max)
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91 changes: 39 additions & 52 deletions pyxrf/model/load_data_from_db.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2244,7 +2244,6 @@ def map_data2D_srx_new_tiled(
)

scan_doc = start_doc["scan"]
stop_doc = hdr.stop

logger.info("Start document:\n%s", pprint.pformat(start_doc))

Expand Down Expand Up @@ -2399,18 +2398,16 @@ def map_data2D_srx_new_tiled(
slow_key = slow_motor + "_user_setpoint"

# Collect motor positions
fast_pos = data_primary[fast_key]
slow_pos = data_primary[fast_key]
fast_pos = data_primary[fast_key].read()
slow_pos = data_primary[slow_key].read()

# Reshape motor positions
num_events = stop_doc["num_events"]["primary"]
_, n_scan_fast = scan_doc["shape"]
num_events = len(fast_pos)
n_scan_fast, n_scan_slow = scan_doc["shape"]
n_scan_fast, n_scan_slow = int(n_scan_fast), int(n_scan_slow)
num_rows = len(fast_pos) / n_scan_fast
n_scan_total = n_scan_fast * num_rows
fast_pos = fast_pos[:, n_scan_total]
slow_pos = slow_pos[:, n_scan_total]
fast_pos = da.reshape(fast_pos, (n_scan_slow, n_scan_fast))
slow_pos = da.reshape(slow_pos, (n_scan_slow, n_scan_fast))
fast_pos = da.reshape(fast_pos, (num_rows, n_scan_fast))
slow_pos = da.reshape(slow_pos, (num_rows, n_scan_fast))

# Put into one array for h5 file
pos_pos = da.zeros((2, num_rows, n_scan_fast))
Expand All @@ -2425,10 +2422,12 @@ def map_data2D_srx_new_tiled(
# Get detector data
keys = list(data_primary)
MAX_DET_ELEMENTS = 8
# !!!!!! The following code for stepscan needs to be revised (still the old code)
N_xs, det_name_prefix, ndigits = None, None, 1

N_xs, det_name_prefix, det_name_suffix, ndigits = None, None, "", 1
for i in np.arange(1, MAX_DET_ELEMENTS + 1):
if f"xs_channel{i}" in keys:
if f"xs_channel{i:02d}_fluor" in keys: # This is the latest
N_xs, det_name_prefix, det_name_suffix, ndigits = i, "xs_channel", "_fluor", 2
elif f"xs_channel{i}" in keys:
N_xs, det_name_prefix, ndigits = i, "xs_channel", 1
elif f"xs_channel{i:02d}" in keys:
N_xs, det_name_prefix, ndigits = i, "xs_channel", 2
Expand All @@ -2439,45 +2438,33 @@ def map_data2D_srx_new_tiled(
N_pts = num_events
N_bins = 4096
if "xs" in dets or "xs4" in dets:
d_xs = np.empty((N_xs, N_pts, N_bins))
d_xs = da.empty((N_xs, N_pts, N_bins))
for i in np.arange(0, N_xs):
chnum = f"{i + 1}" if ndigits == 1 else f"{i + 1:02d}"
dname = det_name_prefix + chnum

d = hdr.data(dname, fill=True)
d = np.array(list(d))
d_xs[i, :, :] = np.copy(d)
dname = det_name_prefix + chnum + det_name_suffix
d = data_primary[dname].read()
d_xs[i, :, :] = d
del d
# Reshape data
if num_events != (n_scan_slow * n_scan_fast):
tmp = np.zeros((N_xs, num_rows, n_scan_fast, N_bins))
for i in range(num_rows):
for j in range(n_scan_fast):
tmp[:, i, j, :] = fast_pos[:, i * n_scan_fast + j, :]
d_xs = np.copy(tmp)
del tmp
else:
d_xs = np.reshape(d_xs, (N_xs, n_scan_slow, n_scan_fast, N_bins))

d_xs = da.reshape(d_xs, (N_xs, num_rows, n_scan_fast, N_bins))

# Sum data
d_xs_sum = np.squeeze(np.sum(d_xs, axis=0))
d_xs_sum = da.squeeze(da.sum(d_xs, axis=0))

d_xs2, d_xs2_sum = None, None

# Scaler list
sclr_list = ["sclr_i0", "sclr_im", "sclr_it"]
sclr_name = []
sclr_names = []
for s in sclr_list:
if s in keys:
sclr_name.append(s)
sclr = np.array(hdr.table()[sclr_name].values)
# Reshape data
if num_events != (n_scan_slow * n_scan_fast):
tmp = np.zeros((num_rows, n_scan_fast))
for i in range(num_rows):
for j in range(n_scan_fast):
tmp[i, j] = fast_pos[i * n_scan_fast + j]
sclr = np.copy(tmp)
del tmp
sclr_names.append(s)
if sclr_names:
sclr_list = [data_primary[_].read() for _ in sclr_names]
sclr_list = [da.reshape(_, (n_scan_slow, n_scan_fast)) for _ in sclr_list]
sclr = da.stack(sclr_list, axis=-1)
else:
sclr = np.reshape(sclr, (n_scan_slow, n_scan_fast, len(sclr_name)))
sclr = None

# Consider snake
# pos_pos, d_xs, d_xs_sum, sclr
Expand All @@ -2493,7 +2480,8 @@ def map_data2D_srx_new_tiled(
d_xs2[:, 1::2, :, :] = d_xs2[:, 1::2, ::-1, :]
if d_xs2_sum is not None:
d_xs2_sum[1::2, :, :] = d_xs2_sum[1::2, ::-1, :]
sclr[1::2, :, :] = sclr[1::2, ::-1, :]
if sclr is not None:
sclr[1::2, :, :] = sclr[1::2, ::-1, :]

def swap_axes():
nonlocal pos_name, pos_pos, d_xs, d_xs_sum, d_xs2, d_xs2_sum, sclr
Expand All @@ -2510,23 +2498,22 @@ def swap_axes():
d_xs2 = da.swapaxes(d_xs2, 0, 1)
if d_xs2_sum is not None:
d_xs2_sum = da.swapaxes(d_xs2_sum, 0, 1)
sclr = da.swapaxes(sclr, 0, 1)
if sclr is not None:
sclr = da.swapaxes(sclr, 0, 1)

if scan_doc["type"] == "XRF_FLY":
if fast_motor in ("nano_stage_sy", "nano_stage_y"):
swap_axes()
elif scan_doc["type"] == "XRF_STEP":
if "xs" in dets or "xs4" in dets:
d_xs = np.swapaxes(d_xs, 0, 1)
d_xs = np.swapaxes(d_xs, 1, 2)
d_xs = da.swapaxes(d_xs, 0, 1)
d_xs = da.swapaxes(d_xs, 1, 2)
if "xs2" in dets:
d_xs2 = np.swapaxes(d_xs2, 0, 1)
d_xs2 = np.swapaxes(d_xs2, 1, 2)
if fast_motor not in ("nano_stage_sy", "nano_stage_y"):
d_xs2 = da.swapaxes(d_xs2, 0, 1)
d_xs2 = da.swapaxes(d_xs2, 1, 2)
if fast_motor in ("nano_stage_sy", "nano_stage_y"):
swap_axes()
pos_name = pos_name[::-1] # Swap the positions back
else:
pos_name = pos_name[::-1] # Swap the positions back

print("Data is loaded successfully. Preparing to save data ...")

Expand All @@ -2552,7 +2539,7 @@ def swap_axes():
# loaded_data["det" + str(i + 1)] = np.nan_to_num(da.squeeze(tmp_data[:, :, i, :]).compute())
loaded_data["det" + str(i + 1)] = da.squeeze(tmp_data[:, :, i, :])

if save_scaler:
if save_scaler and sclr is not None:
loaded_data["scaler_data"] = sclr.compute()
loaded_data["scaler_names"] = sclr_names

Expand Down

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