From c4329441c13e5182313e455467ac4246552e934f Mon Sep 17 00:00:00 2001
From: Nicole <nneveu@stanford.edu>
Date: Mon, 18 Dec 2023 17:37:15 -0800
Subject: [PATCH] Cleanup before doc merge (#124)

* cleaning up mat2py directory

* cleaning up data analysis dir

* adding sphinx to requirements

* cleaning up imports/formatting

* adding matlab emit scan doc

* updating tests imports and directories

* removing old profile monitor files

* updating cor_plot to corr_plot
---
 .../README.MD => docs/source/cor_plot.rst     |   0
 docs/source/index.rst                         |   3 +
 .../source/mat_emit_scan.rst                  |   3 +
 .../data_analysis/fitting/fit_gaussian.py     | 317 ------------------
 lcls_tools/common/devices/profile_monitor.py  | 155 ---------
 .../common/devices/profmon_constants.py       |  57 ----
 lcls_tools/common/devices/screen.py           |   6 +-
 .../image_processing/image_processing.py      |  22 --
 .../common/matlab2py/cor_plot/__init__.py     |   0
 ...plot_mat_scan.py => corr_plot_mat_scan.py} |   0
 .../common/matlab2py/emit_scan/.gitattributes |   1 -
 .../common/matlab2py/emit_scan/__init__.py    |   0
 .../{emit_scan => }/mat_emit_scan.py          |   0
 .../common/matlab2py/{image => }/mat_image.py |   0
 requirements.txt                              |   6 +-
 .../common/data_analysis/fitting/__init__.py  |   0
 .../fitting/test_fit_gaussian.py              |  29 --
 .../common/devices/test_constants.py          |   0
 .../common/devices/test_profile_monitor.py    |  91 -----
 .../image_processing/test_image_processing.py |   2 +-
 .../common/matlab2py/cor_plot/__init__.py     |   0
 .../common/matlab2py/emit_scan/__init__.py    |   0
 .../common/matlab2py/image/__init__.py        |   0
 ...mat_scan.py => test_corr_plot_mat_scan.py} |   2 +-
 .../{emit_scan => }/test_mat_emit_scan.py     |   2 +-
 .../matlab2py/{image => }/test_mat_image.py   |   2 +-
 26 files changed, 20 insertions(+), 678 deletions(-)
 rename lcls_tools/common/matlab2py/cor_plot/README.MD => docs/source/cor_plot.rst (100%)
 rename lcls_tools/common/matlab2py/emit_scan/README.MD => docs/source/mat_emit_scan.rst (98%)
 delete mode 100755 lcls_tools/common/data_analysis/fitting/fit_gaussian.py
 delete mode 100644 lcls_tools/common/devices/profile_monitor.py
 delete mode 100644 lcls_tools/common/devices/profmon_constants.py
 delete mode 100644 lcls_tools/common/matlab2py/cor_plot/__init__.py
 rename lcls_tools/common/matlab2py/{cor_plot/cor_plot_mat_scan.py => corr_plot_mat_scan.py} (100%)
 delete mode 100644 lcls_tools/common/matlab2py/emit_scan/.gitattributes
 delete mode 100644 lcls_tools/common/matlab2py/emit_scan/__init__.py
 rename lcls_tools/common/matlab2py/{emit_scan => }/mat_emit_scan.py (100%)
 rename lcls_tools/common/matlab2py/{image => }/mat_image.py (100%)
 delete mode 100644 tests/unit_tests/lcls_tools/common/data_analysis/fitting/__init__.py
 delete mode 100644 tests/unit_tests/lcls_tools/common/data_analysis/fitting/test_fit_gaussian.py
 delete mode 100644 tests/unit_tests/lcls_tools/common/devices/test_constants.py
 delete mode 100644 tests/unit_tests/lcls_tools/common/devices/test_profile_monitor.py
 delete mode 100644 tests/unit_tests/lcls_tools/common/matlab2py/cor_plot/__init__.py
 delete mode 100644 tests/unit_tests/lcls_tools/common/matlab2py/emit_scan/__init__.py
 delete mode 100644 tests/unit_tests/lcls_tools/common/matlab2py/image/__init__.py
 rename tests/unit_tests/lcls_tools/common/matlab2py/{cor_plot/test_cor_plot_mat_scan.py => test_corr_plot_mat_scan.py} (97%)
 rename tests/unit_tests/lcls_tools/common/matlab2py/{emit_scan => }/test_mat_emit_scan.py (96%)
 rename tests/unit_tests/lcls_tools/common/matlab2py/{image => }/test_mat_image.py (98%)

diff --git a/lcls_tools/common/matlab2py/cor_plot/README.MD b/docs/source/cor_plot.rst
similarity index 100%
rename from lcls_tools/common/matlab2py/cor_plot/README.MD
rename to docs/source/cor_plot.rst
diff --git a/docs/source/index.rst b/docs/source/index.rst
index 37ac6a58..e850dbd2 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -12,6 +12,9 @@ Welcome to lcls-tools's documentation!
 
    devices.rst
    image_processing.rst
+   cor_plot.rst
+   emit_scan.rst
+   
    
 
 Indices and tables
diff --git a/lcls_tools/common/matlab2py/emit_scan/README.MD b/docs/source/mat_emit_scan.rst
similarity index 98%
rename from lcls_tools/common/matlab2py/emit_scan/README.MD
rename to docs/source/mat_emit_scan.rst
index ec730e60..530dcc72 100644
--- a/lcls_tools/common/matlab2py/emit_scan/README.MD
+++ b/docs/source/mat_emit_scan.rst
@@ -1,3 +1,6 @@
+Loading Matlab Emittance Scans
+================
+
 This utility can take an emittance scan .mat file and turn it into a python data object. The goal is to present the data from an emittance scan in a meaningful way.  This utility has a test file that is used for testing, but we can use it for examples. All examples are run from this directory. Current example is using Python2.7
 
 Example: 'test_scan.mat'
diff --git a/lcls_tools/common/data_analysis/fitting/fit_gaussian.py b/lcls_tools/common/data_analysis/fitting/fit_gaussian.py
deleted file mode 100755
index 846523c0..00000000
--- a/lcls_tools/common/data_analysis/fitting/fit_gaussian.py
+++ /dev/null
@@ -1,317 +0,0 @@
-#!/usr/local/lcls/package/python/current/bin/python
-################################################################################
-# Modified version of John Sheppard's read_xcor_data script
-# Reads in a matlab file of xcor data and fits gaussians to it
-# Data must have column names posList, ampList, and ampstdList
-################################################################################
-
-from __future__ import division
-
-from pylab import array, plt, floor
-from numpy import argsort, power, exp, zeros
-from scipy.optimize import curve_fit
-from operator import itemgetter
-
-
-NUM_BUCKS = 10
-DEBUG = False
-
-
-# An unfortunate consequence of defining step as max/numbucks is that the
-# maximum point is in its own bucket (bucket 10), which would break a lot of
-# stuff, so it necessitates the error checking
-def get_bucket(val, step):
-    bucket = int(floor(val / step))
-    return bucket if bucket < 10 else 9  # TODO: should this use NUM_BUCKS?
-
-
-def find_max(data, run):
-    max_index = max(enumerate(data[run]), key=itemgetter(1))[0]
-    return run[max_index]
-
-
-# The very ham-fisted way I'm coming up with a guess for the width of a given
-# peak is to get the literal distance between the first element of the
-# subsequent run and the last element of the previous run
-def find_widths(xdata, peak_idxs, runs, run_map):
-    widths = []
-    for peak_idx in peak_idxs:
-        run_idx = run_map[peak_idx]
-
-        # If it's the first run, just double the distance between the peak and
-        # the first element of the next run
-        if run_idx == 0:
-            widths.append((xdata[runs[1][0]] - xdata[peak_idx]) * 2)
-
-        # If it's the last run, just double the distance between the peak and
-        # the last element of the previous run
-        elif run_idx == len(runs) - 1:
-            widths.append((xdata[peak_idx] - xdata[runs[-2][-1]]) * 2)
-
-        else:
-            widths.append(xdata[runs[run_idx + 1][0]] - xdata[runs[run_idx - 1][-1]])
-
-    return widths
-
-
-# Modified from StackOverflow
-def gen_gauss_sum(x, *params):
-    m = params[0]
-    b = params[1]
-
-    y = [m * i + b for i in x]
-
-    for i in range(2, len(params), 3):
-        ctr = params[i]
-        amp = params[i + 1]
-        wid = params[i + 2]
-        y = y + gaussian(x, ctr, wid, amp)
-    return y
-
-
-def gaussian(x, ctr, wid, amp):
-    return amp * exp(-power(x - ctr, 2.0) / (2 * power(wid, 2.0)))
-
-
-def get_slope(x1, y1, x2, y2):
-    return (y2 - y1) / (x2 - x1)
-
-
-# Idea to add a line instead of a really short, fat gaussian was all Ahemd.
-# Thanks, yo. You're great.
-def find_line(zero_runs, runs, xdata, ydata):
-    x1, y1, x2, y2, m, _ = (0, 0, 0, 0, 0, 0)
-
-    # This condition should only be possible if there are peaks on one or both
-    # extremes, or if there is no peak
-    if len(zero_runs) == 1:
-        zero_run = runs[zero_runs[0]]
-        # This should pull out the median index value of the run
-        x_ind1 = zero_run[argsort(ydata[zero_run])[len(zero_run) / 2]]
-        y1 = ydata[x_ind1]
-
-        return [m, y1]
-
-    # 0 shouldn't be possible given that the data is normalized to the lowest
-    # point, so it should otherwise be at least 2.
-    # Currently just fitting the first point of the first zero run and the last
-    # point of the last zero run. Could make it smarter by adding a sum of step
-    # functions, but that seems like overkill
-    else:
-        zero1 = runs[zero_runs[0]]
-        zero2 = runs[zero_runs[-1]]
-
-        x_ind1 = zero1[argsort(ydata[zero1])[len(zero1) / 2]]
-        x1 = xdata[x_ind1]
-        y1 = ydata[x_ind1]
-
-        x_ind2 = zero2[argsort(ydata[zero2])[len(zero2) / 2]]
-        x2 = xdata[x_ind2]
-        y2 = ydata[x_ind2]
-
-        m = get_slope(x1, y1, x2, y2)
-
-        return [m, y1 - m * x1]
-
-
-# Every run has the potential to be a peak, but we limit it to the numPeaks
-# largest ones
-def get_peaks(data, num_peaks, runs):
-    # Should be doable in preprocessing
-    len_runs = map(lambda run: len(run), runs)
-
-    # User-proofing. Could probably limit input
-    num_peaks = num_peaks if num_peaks <= len(runs) else len(runs)
-
-    # Would be using linear argpartsort if we were running not 2013 builds.
-    # Can you tell I'm bitter?
-    ind = argsort(array(len_runs))[-num_peaks:]
-
-    # This is inelegant
-    peak_idx, peaks = ([], [])
-    for run in array(runs)[ind]:
-        idx = find_max(data, run)
-        peak_idx.append(idx)
-        peaks.append(data[idx])
-
-    max_index, max_value = max(enumerate(data), key=itemgetter(1))
-
-    # Maybe unnecessary precaution to make sure that the max point is used in
-    # the fit (a run wouldn't be found if the peak were sufficiently narrow)
-    max_info = []
-    if max_value not in peaks:
-        if peaks:
-            min_index = min(enumerate(peaks), key=itemgetter(1))[0]
-            peaks[min_index] = max_value
-            peak_idx[min_index] = max_index
-        else:
-            peak_idx.append(max_index)
-            peaks.append(max_value)
-            max_info = [max_index, max_value]
-
-    return [peaks, peak_idx, max_info]
-
-
-# Checking for inflection points doesn't work because some data points don't
-# follow the trend line; this groups consecutive data points by bucket, which
-# need to be recalculated following an adjustment.
-def get_runs(data, step):
-    # runMap maps each data point to the run that contains it
-    zero_runs, non_zero_runs, runs, curr_run, run_map = ([], [], [], [], [])
-    curr_buck = get_bucket(data[0], step)
-    run_idx = 0
-
-    for idx, point in enumerate(data):
-        new_buck = get_bucket(point, step)
-        if new_buck == curr_buck:
-            curr_run.append(idx)
-        else:
-            # Plotting the end of a run
-            if DEBUG:
-                plt.axvline(x=idx)
-
-            # Three points make a curve!
-            if len(curr_run) > 2:
-                runs.append(curr_run)
-                run_idx += 1
-                if curr_buck == 0:
-                    zero_runs.append(len(runs) - 1)
-                else:
-                    non_zero_runs.append(curr_run)
-
-            curr_run = [idx]
-            curr_buck = new_buck
-
-        run_map.append(run_idx)
-
-    # Effectively flushing the cache. There has to be a way to factor this out
-    if len(curr_run) > 2:
-        runs.append(curr_run)
-        if curr_buck == 0:
-            zero_runs.append(len(runs) - 1)
-        else:
-            non_zero_runs.append(curr_run)
-
-    return [runs, zero_runs, non_zero_runs, run_map]
-
-
-# A whole rigmarole to collapse multiple pedestals.
-# It assumes that the pedestal is the bucket with the most elements
-def adjust_data(data, step):
-    normalized_adjustment = 0
-
-    bucket_count = zeros(NUM_BUCKS)
-    bucket_contents = [[] for i in range(0, NUM_BUCKS)]
-    buckets = zeros(len(data))
-
-    for idx, element in enumerate(data):
-        bucket = get_bucket(element, step)
-        bucket_count[bucket] += 1
-        bucket_contents[bucket] += [idx]
-        buckets[idx] = bucket
-
-    zero_bucket = max(enumerate(bucket_count), key=itemgetter(1))[0]
-
-    needs_adjustment = False
-
-    for idx, bucket in enumerate(buckets):
-        if bucket < zero_bucket:
-            # Inefficient to set this every time, but eh
-            needs_adjustment = True
-            # Sets them arbitrarily to the value of the first element in the
-            # zero bucket, to eliminate the double pedestal
-            data[idx] = data[bucket_contents[zero_bucket][0]]
-
-    if needs_adjustment:
-        normalized_adjustment = min(data[bucket_contents[zero_bucket]])
-        data = data - normalized_adjustment
-        step = max(data) / NUM_BUCKS
-
-    return [data, step, normalized_adjustment]
-
-
-################################################################################
-# So this is a giant clusterfuck of logic where I try to autodetect peaks by
-# detecting "runs" of points, defined as a group of 3 or more consecutive points
-# that belong to the same  bucket, while simultaneously tagging those runs that
-# belong to the "zeroeth" bucket (the pedestal).
-#
-# Note that the format of the guess is a list of the form:
-# [m, b, center_0, amplitude_0, width_0,..., center_k, amplitude_k, width_k]
-# where m and b correspond to the line parameters in y = m*x + b
-# and every following group of three corresponds to a gaussian
-################################################################################
-def get_guess(xdata, ydata, step, use_zeros, num_peaks):
-    runs, zero_runs, non_zero_runs, run_map = get_runs(ydata, step)
-
-    peaks, peak_idx, max_info = (
-        get_peaks(ydata, num_peaks, non_zero_runs)
-        if not use_zeros
-        else get_peaks(ydata, num_peaks, runs)
-    )
-
-    # Gross error handling for the case where the max val isn't detected as a
-    # peak (making sure it's added to runs in the correct order)
-    if max_info:
-        max_idx = max_info[0]
-        if run_map[max_idx] >= len(runs):
-            runs.append(max_idx)
-        else:
-            runs[run_map[max_idx]].append(max_idx)
-
-    # This plots my guesses for the peaks
-    if DEBUG:
-        for idx in peak_idx:
-            plt.axvline(x=idx)
-
-    # Should rethink widths calculation, it's usually about 1/5 of acutal,
-    # which means the algorithm needs more iterations to get closer.
-    widths = find_widths(xdata, peak_idx, runs, run_map)
-
-    guess = find_line(zero_runs, runs, xdata, ydata)
-
-    # This plots my guess for the line
-    if DEBUG:
-        plt.plot([guess[0] * j + guess[1] for j in xdata], "--")
-
-    for idx, amp in enumerate(peaks):
-        guess += [xdata[peak_idx[idx]], amp, widths[idx] / 4]
-
-        # Plot my initial guesses for the gaussian(s)
-        if DEBUG:
-            plt.plot(
-                [
-                    gaussian(i, xdata[peak_idx[idx]], widths[idx] / 4, amp)
-                    for i in xdata
-                ],
-                "--",
-            )
-
-    return [guess, len(runs) if use_zeros else len(non_zero_runs)]
-
-
-def process_data(data):
-    first_adjustment = min(data)
-
-    # Removing the pedestal
-    data = data - first_adjustment
-
-    # Define the step size by the number of vertical buckets
-    step = max(data) / NUM_BUCKS
-
-    data, step, normalized_adjustment = adjust_data(data, step)
-
-    # This prints my vertical buckets
-    if DEBUG:
-        for i in range(1, NUM_BUCKS):
-            plt.plot([i * step for _ in range(0, len(data))])
-
-    total_adjustment = first_adjustment + normalized_adjustment
-
-    return [data, total_adjustment, step]
-
-
-def get_fit(data, x, guess):
-    # Someday the ability to bound the fit will be available...
-    # ...When we're no longer running builds from 2013 :P
-    return curve_fit(gen_gauss_sum, x, data, p0=guess)[0]
diff --git a/lcls_tools/common/devices/profile_monitor.py b/lcls_tools/common/devices/profile_monitor.py
deleted file mode 100644
index 0a12d3c3..00000000
--- a/lcls_tools/common/devices/profile_monitor.py
+++ /dev/null
@@ -1,155 +0,0 @@
-#!/usr/local/lcls/package/python/current/bin/python
-
-from epics import PV
-import lcls_tools.common.devices.profmon_constants as pc
-from time import sleep
-from threading import Thread
-from numpy import array_equal
-
-
-# Implementation needs to be thought out, just a POC
-
-
-def get_profile_monitors():
-    """Return MAD names of all profile monitors that have models"""
-    return sorted(pc.PROFS.keys())
-
-
-class ProfMon(object):
-    """Generic Profile Monitor Object Class that references profile monitor MAD name"""
-
-    def __init__(self, prof_name="OTR02"):
-        if prof_name not in pc.PROFS.keys():
-            raise ValueError("You have not specified a valid profile monitor")
-        prof_dict = pc.PROFS[prof_name]
-        self._prof_name = prof_name
-        self._prof_set = PV(prof_dict["set"])
-        self._prof_get = PV(prof_dict["get"])
-        self._prof_image = PV(prof_dict["image"])
-        self._prof_res = PV(prof_dict["res"])
-        self._x_size = PV(prof_dict["xsize"])
-        self._y_size = PV(prof_dict["ysize"])
-        self._rate = PV(prof_dict["rate"])
-        self._images = []
-        self._data_thread = None
-        self._gathering_data = False
-        self._get_vars = self._prof_get.get_ctrlvars()["enum_strs"]
-        self._set_vars = self._prof_set.get_ctrlvars()["enum_strs"]
-        self._motion_state = self._get_vars[self._prof_get.get()]
-        self._prof_get.add_callback(self._state_clbk, index=1)
-        self._insert_clbk = None
-        self._extract_clbk = None
-
-    def _state_clbk(self, pvName=None, value=None, char_value=None, **kw):
-        """Keep track of position/motion state"""
-        self._motion_state = self._get_vars[value]
-
-    @property
-    def prof_name(self):
-        """Get the profile monitor MAD name"""
-        return self._prof_name
-
-    @property
-    def cur_image(self):
-        """Get the current image array"""
-        return self._prof_image.get()
-
-    @property
-    def saved_images(self):
-        """Get the images collected"""
-        return self._images
-
-    @property
-    def resolution(self):
-        """Get the resolution"""
-        return self._prof_res.get()
-
-    @property
-    def arr_dims(self):
-        """Get the x and y dimensions"""
-        return (self._x_size.get(), self._y_size.get())
-
-    @property
-    def rate(self):
-        """Get the current rate"""
-        return self._rate.get()
-
-    @property
-    def motion_state(self):
-        """Get the current motion state of the profile monitor"""
-        return self._motion_state
-
-    @property
-    def state(self):
-        """Get the overall state of the profile monitor"""
-        return self.__dict__
-
-    def insert(self, user_clbk=None):
-        """Generic call to insert profile monitor, can specify callback to be run"""
-        if self._motion_state == pc.IN:
-            print("{0}: {1}".format(self._prof_name, pc.ALREADY_INSERTED))
-            return
-
-        if user_clbk:
-            self._insert_clbk = user_clbk
-
-        self._prof_get.add_callback(self._inserted, index=0)
-        self._prof_set.put(pc.IN)
-
-    def _inserted(self, pv_name=None, value=None, char_value=None, **kw):
-        """Generic callback after profile monitor has been inserted, default"""
-        if self._get_vars[value] == pc.IN:
-            print("{0}: {1}".format(self._prof_name, pc.INSERTED))
-
-            if self._insert_clbk:
-                self._insert_clbk()
-                self._insert_clbk = None
-
-            self._prof_get.remove_callback(index=0)
-
-    def extract(self, usr_clbk=None):
-        """Extract profile monitor command, can specify callback to be run"""
-        if self._motion_state == pc.OUT:
-            print("{0}: {1}".format(self._prof_name, pc.ALREADY_EXTRACTED))
-            return
-
-        if usr_clbk:
-            self._extract_clbk = usr_clbk
-
-        self._prof_get.add_callback(self._extracted, index=0)
-        self._prof_set.put(pc.OUT)
-
-    def _extracted(self, pv_name=None, value=None, char_value=None, **kw):
-        """Generic Callback for profile monitor that has been extracted, default"""
-        if self._get_vars[value] == pc.OUT:
-            print("{0}: {1}".format(self._prof_name, pc.EXTRACTED))
-
-            if self._extract_clbk:
-                self._extract_clbk()
-                self._extract_clbk = None
-
-            self._prof_get.remove_callback(index=0)
-
-    def acquire_images(self, images=1):
-        """Start the thread"""
-        self._data_thread = Thread(target=self._collect_image_data, args=(images,))
-        self._data_thread.start()
-
-    def _collect_image_data(self, images, callback):
-        """Threaded data collection"""
-        self._gathering_data = True
-        delay = 1.0 / self._rate.get()  # Rate must be in Hz
-        i = 0
-        while i < images:
-            image = self._prof_image.get()
-            if len(self._images) > 0 and array_equal(image, self._images[-1]):
-                sleep(0.01)
-            else:
-                self._images.append(image)
-                sleep(delay)
-                i += 1
-        if callback:
-            # Would want this to be pyqtSignal or Event notification type thing
-            callback()
-        self._gathering_data = False
-        return  # No join, waste of a function
diff --git a/lcls_tools/common/devices/profmon_constants.py b/lcls_tools/common/devices/profmon_constants.py
deleted file mode 100644
index fd634697..00000000
--- a/lcls_tools/common/devices/profmon_constants.py
+++ /dev/null
@@ -1,57 +0,0 @@
-# There are likely redundancy issues and can be
-# optimized further, this is just a POC.  A Database would be nice
-# to reference as this is Database schema
-
-# TODO: Make this a .yaml file for cleanliness and
-# cross language reference if needed
-
-# Error Strings
-ALREADY_INSERTED = "Profile Monitor is already inserted"
-ALREADY_EXTRACTED = "Profile Monitor is already extracted"
-
-# Completed Action Strings
-INSERTED = "Profile Monitor has been inserted"
-EXTRACTED = "Profile Monitor has been extracted"
-
-# Profile Monitor State
-IN = "IN"
-OUT = "OUT"
-
-############# LCLS Profile Monitor ###########
-
-
-def create_profmon_dict(base):
-    profmon_dict = {
-        "set": base + ":PNEUMATIC",
-        "get": base + ":TGT_STS",
-        "image": base + ":IMAGE",
-        "res": base + ":RESOLUTION",
-        "xsize": base + ":N_OF_COL",
-        "ysize": base + ":N_OF_ROW",
-        "rate": base + ":FRAME_RATE",
-    }
-
-    return profmon_dict
-
-
-# ROI_BITS, ROI_X/YBIN???
-def create_profmon2_dict(base):
-    profmon_dict = {
-        "set": base + ":PNEUMATIC",
-        "get": base + ":TGT_STS",
-        "image": base + ":Image:ArrayData",
-        "res": base + ":RESOLUTION",
-        "xsize": base + ":ArraySizeX_RBV",
-        "ysize": base + ":ArraySizeY_RBV",
-        "rate": base + ":FRAME_RATE",
-    }
-
-    return profmon_dict
-
-
-YAG01 = create_profmon_dict("YAGS:IN20:211")
-OTR02 = create_profmon_dict("OTRS:IN20:571")
-YAG01B = create_profmon2_dict("YAGS:GUNB:753")
-
-# Dict of Profile Monitors
-PROFS = {"YAG01B": YAG01B, "YAG01": YAG01, "OTR02": OTR02}
diff --git a/lcls_tools/common/devices/screen.py b/lcls_tools/common/devices/screen.py
index b1a35671..868f00d6 100644
--- a/lcls_tools/common/devices/screen.py
+++ b/lcls_tools/common/devices/screen.py
@@ -77,7 +77,7 @@ def image(self) -> np.ndarray:
 
     @property
     def image_timestamp(self):
-        """get last timestamp for last PV activity"""
+        """Get last timestamp for last PV activity"""
         return self.controls_information.PVs.image.timestamp
 
     @property
@@ -123,6 +123,10 @@ def last_save_filepath(self):
         """Location and filename for the last file saved by this screen (set in save_images())"""
         return self._last_save_filepath
 
+    def _inserted_check():
+        """Check if the screen is inserted"""
+        return NotImplementedError
+
     def _generate_new_filename(self, extension: Optional[str] = ".h5") -> str:
         """
         Make a new filename for the HDF5 image file
diff --git a/lcls_tools/common/image_processing/image_processing.py b/lcls_tools/common/image_processing/image_processing.py
index 6f1e1ac7..dc5f810b 100644
--- a/lcls_tools/common/image_processing/image_processing.py
+++ b/lcls_tools/common/image_processing/image_processing.py
@@ -1,8 +1,5 @@
 import numpy as np
 import scipy.ndimage as snd
-from scipy import asarray
-import matplotlib.pyplot as plt
-import lcls_tools.common.data_analysis.fitting.fit_gaussian as fg
 
 
 def fliplr(image):
@@ -46,22 +43,3 @@ def y_projection(image, subtract_baseline=True):
         return proj - min(proj)
 
     return proj
-
-
-def gauss_func(x, a, x0, sigma):
-    return a * np.exp(-((x - x0) ** 2) / (2 * sigma**2))
-
-
-def gauss_fit(projection, plot=False):
-    x = asarray(range(len(projection)))
-    data, _, step = fg.process_data(projection)
-    guess = fg.get_guess(x, data, step, False, num_peaks=1)[0]
-    x0_x, a_x, sigma_x = fg.get_fit(data, x, guess)[2:]
-
-    if plot:
-        plt.plot(x, projection, label="data")
-        plt.plot(x, gauss_func(x, a_x, x0_x, sigma_x), label="fit")
-        plt.legend()
-        plt.show()
-
-    return x, a_x, x0_x, sigma_x
diff --git a/lcls_tools/common/matlab2py/cor_plot/__init__.py b/lcls_tools/common/matlab2py/cor_plot/__init__.py
deleted file mode 100644
index e69de29b..00000000
diff --git a/lcls_tools/common/matlab2py/cor_plot/cor_plot_mat_scan.py b/lcls_tools/common/matlab2py/corr_plot_mat_scan.py
similarity index 100%
rename from lcls_tools/common/matlab2py/cor_plot/cor_plot_mat_scan.py
rename to lcls_tools/common/matlab2py/corr_plot_mat_scan.py
diff --git a/lcls_tools/common/matlab2py/emit_scan/.gitattributes b/lcls_tools/common/matlab2py/emit_scan/.gitattributes
deleted file mode 100644
index e4f9da3f..00000000
--- a/lcls_tools/common/matlab2py/emit_scan/.gitattributes
+++ /dev/null
@@ -1 +0,0 @@
-test_scan.mat filter=lfs diff=lfs merge=lfs -text
diff --git a/lcls_tools/common/matlab2py/emit_scan/__init__.py b/lcls_tools/common/matlab2py/emit_scan/__init__.py
deleted file mode 100644
index e69de29b..00000000
diff --git a/lcls_tools/common/matlab2py/emit_scan/mat_emit_scan.py b/lcls_tools/common/matlab2py/mat_emit_scan.py
similarity index 100%
rename from lcls_tools/common/matlab2py/emit_scan/mat_emit_scan.py
rename to lcls_tools/common/matlab2py/mat_emit_scan.py
diff --git a/lcls_tools/common/matlab2py/image/mat_image.py b/lcls_tools/common/matlab2py/mat_image.py
similarity index 100%
rename from lcls_tools/common/matlab2py/image/mat_image.py
rename to lcls_tools/common/matlab2py/mat_image.py
diff --git a/requirements.txt b/requirements.txt
index 84501ee1..4e917658 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -7,4 +7,8 @@ pyyaml
 requests
 pydantic
 h5py
-scikit-learn
\ No newline at end of file
+sphinx
+sphinx_rtd_theme
+myst_parser
+scikit-learn
+
diff --git a/tests/unit_tests/lcls_tools/common/data_analysis/fitting/__init__.py b/tests/unit_tests/lcls_tools/common/data_analysis/fitting/__init__.py
deleted file mode 100644
index e69de29b..00000000
diff --git a/tests/unit_tests/lcls_tools/common/data_analysis/fitting/test_fit_gaussian.py b/tests/unit_tests/lcls_tools/common/data_analysis/fitting/test_fit_gaussian.py
deleted file mode 100644
index 44d7b7e9..00000000
--- a/tests/unit_tests/lcls_tools/common/data_analysis/fitting/test_fit_gaussian.py
+++ /dev/null
@@ -1,29 +0,0 @@
-from lcls_tools.common.data_analysis.fitting import fit_gaussian
-import unittest
-
-
-class TestFitGaussian(unittest.TestCase):
-    def setUp(self) -> None:
-        """Add objects that you want to use/setup per-test-case"""
-        return super().setUp()
-
-    def tearDown(self) -> None:
-        """Add instructions for removing objects after each test case"""
-        return super().tearDown()
-
-    def test_get_bucket_returns_nine_if_value_over_step_equal_to_ten(self):
-        """Checks that 9 is returned if the value/step greater than or equal to 10."""
-        result = fit_gaussian.get_bucket(10, 1)
-        self.assertIsInstance(result, int)
-        self.assertEqual(result, 9)
-
-    def test_get_bucket_returns_bucket_if_value_over_step_less_than_ten(self):
-        """Checks that val/step is returned if the value/step less than 10."""
-        result = fit_gaussian.get_bucket(10, 2)
-        self.assertIsInstance(result, int)
-        self.assertEqual(result, 5)
-
-    def test_get_bucket_returns_floor_of_value_over_step_when_less_than_10(self):
-        result = fit_gaussian.get_bucket(9.9, 1.5)
-        self.assertIsInstance(result, int)
-        self.assertEqual(result, 6)
diff --git a/tests/unit_tests/lcls_tools/common/devices/test_constants.py b/tests/unit_tests/lcls_tools/common/devices/test_constants.py
deleted file mode 100644
index e69de29b..00000000
diff --git a/tests/unit_tests/lcls_tools/common/devices/test_profile_monitor.py b/tests/unit_tests/lcls_tools/common/devices/test_profile_monitor.py
deleted file mode 100644
index dfb5bef5..00000000
--- a/tests/unit_tests/lcls_tools/common/devices/test_profile_monitor.py
+++ /dev/null
@@ -1,91 +0,0 @@
-# Built in
-from unittest import mock, TestCase
-import inspect
-
-# Local imports
-import lcls_tools.common.devices.profmon_constants as pc
-from lcls_tools.common.devices.profile_monitor import (
-    ProfMon,
-    get_profile_monitors,
-)
-
-
-PROF = {
-    "set": "test:PNEUMATIC",
-    "get": "test:TGT_STS",
-    "image": "test:IMAGE",
-    "res": "test:RESOLUTION",
-    "xsize": "test:N_OF_COL",
-    "ysize": "test:N_OF_ROW",
-    "rate": "test:FRAME_RATE",
-}
-
-PROF2 = {
-    "set": "test:PNEUMATIC",
-    "get": "test:TGT_STS",
-    "image": "test:Image:ArrayData",
-    "res": "test:RESOLUTION",
-    "xsize": "test:ArraySizeX_RBV",
-    "ysize": "test:ArraySizeY_RBV",
-    "rate": "test:FRAME_RATE",
-}
-
-PROFS = ["OTR02", "YAG01B", "YAG01"]
-
-
-class ProfileMonitorTest(TestCase):
-    ############ Constants ############
-
-    def test_create_profmon_dict(self):
-        """Typical LCLS style PV naming convention"""
-        self.assertEqual(pc.create_profmon_dict("test"), PROF)
-
-    def test_create_profmon2_dict(self):
-        """New LCLS2 style PV naming convention"""
-        self.assertEqual(pc.create_profmon2_dict("test"), PROF2)
-
-    def test_get_profile_monitors(self):
-        """To verify we haven't added any profs"""
-        self.assertEqual(get_profile_monitors(), sorted(PROFS))
-
-    ############# Object ##############
-    @mock.patch("epics.PV.get", new_callable=mock.Mock)
-    @mock.patch("epics.PV.get_ctrlvars", new_callable=mock.Mock)
-    def test_properties(self, mock_get_ctrl_vars, mock_pv_get):
-        """Test that all the properties we expect exist"""
-        mock_get_ctrl_vars.return_value = {"enum_strs": ["IN"]}
-        mock_pv_get.return_value = 0
-        p = ProfMon()
-        self.assertEqual(isinstance(type(p).prof_name, property), True)
-        self.assertEqual(isinstance(type(p).cur_image, property), True)
-        self.assertEqual(isinstance(type(p).saved_images, property), True)
-        self.assertEqual(isinstance(type(p).resolution, property), True)
-        self.assertEqual(isinstance(type(p).arr_dims, property), True)
-        self.assertEqual(isinstance(type(p).rate, property), True)
-        self.assertEqual(isinstance(type(p).motion_state, property), True)
-        self.assertEqual(isinstance(type(p).state, property), True)
-
-    @mock.patch("epics.PV.get", new_callable=mock.Mock)
-    @mock.patch("epics.PV.get_ctrlvars", new_callable=mock.Mock)
-    def test_methods(self, mock_get_ctrl_vars, mock_pv_get):
-        """Test that all the methods we expect exist"""
-        mock_get_ctrl_vars.return_value = {"enum_strs": ["IN"]}
-        mock_pv_get.return_value = 0
-        p = ProfMon()
-        self.assertEqual(inspect.ismethod(p.insert), True)
-        self.assertEqual(inspect.ismethod(p._inserted), True)
-        self.assertEqual(inspect.ismethod(p.extract), True)
-        self.assertEqual(inspect.ismethod(p._extracted), True)
-        self.assertEqual(inspect.ismethod(p.acquire_images), True)
-        self.assertEqual(inspect.ismethod(p._collect_image_data), True)
-
-    @mock.patch("epics.PV.get", new_callable=mock.Mock)
-    @mock.patch("epics.PV.get_ctrlvars", new_callable=mock.Mock)
-    def test_name(self, mock_get_ctrl_vars, mock_pv_get):
-        """Test that we get default name and can hand name in init arg"""
-        mock_get_ctrl_vars.return_value = {"enum_strs": ["IN"]}
-        mock_pv_get.return_value = 0
-        p = ProfMon()
-        self.assertEqual(p.prof_name, "OTR02")
-        p = ProfMon("YAG01")
-        self.assertEqual(p.prof_name, "YAG01")
diff --git a/tests/unit_tests/lcls_tools/common/image_processing/test_image_processing.py b/tests/unit_tests/lcls_tools/common/image_processing/test_image_processing.py
index b453b945..5f6b8e57 100644
--- a/tests/unit_tests/lcls_tools/common/image_processing/test_image_processing.py
+++ b/tests/unit_tests/lcls_tools/common/image_processing/test_image_processing.py
@@ -2,7 +2,7 @@
 import os
 import numpy as np
 import lcls_tools.common.image_processing as ip
-from lcls_tools.common.matlab2py.image.mat_image import MatImage
+from lcls_tools.common.matlab2py.mat_image import MatImage
 
 CAMERA = "CAMR:LGUN:210"
 
diff --git a/tests/unit_tests/lcls_tools/common/matlab2py/cor_plot/__init__.py b/tests/unit_tests/lcls_tools/common/matlab2py/cor_plot/__init__.py
deleted file mode 100644
index e69de29b..00000000
diff --git a/tests/unit_tests/lcls_tools/common/matlab2py/emit_scan/__init__.py b/tests/unit_tests/lcls_tools/common/matlab2py/emit_scan/__init__.py
deleted file mode 100644
index e69de29b..00000000
diff --git a/tests/unit_tests/lcls_tools/common/matlab2py/image/__init__.py b/tests/unit_tests/lcls_tools/common/matlab2py/image/__init__.py
deleted file mode 100644
index e69de29b..00000000
diff --git a/tests/unit_tests/lcls_tools/common/matlab2py/cor_plot/test_cor_plot_mat_scan.py b/tests/unit_tests/lcls_tools/common/matlab2py/test_corr_plot_mat_scan.py
similarity index 97%
rename from tests/unit_tests/lcls_tools/common/matlab2py/cor_plot/test_cor_plot_mat_scan.py
rename to tests/unit_tests/lcls_tools/common/matlab2py/test_corr_plot_mat_scan.py
index 6cee1f41..419dad36 100644
--- a/tests/unit_tests/lcls_tools/common/matlab2py/cor_plot/test_cor_plot_mat_scan.py
+++ b/tests/unit_tests/lcls_tools/common/matlab2py/test_corr_plot_mat_scan.py
@@ -1,6 +1,6 @@
 import os
 import unittest
-from lcls_tools.common.matlab2py.cor_plot.cor_plot_mat_scan import (
+from lcls_tools.common.matlab2py.corr_plot_mat_scan import (
     CorPlotMatScan as CPMS,
 )
 
diff --git a/tests/unit_tests/lcls_tools/common/matlab2py/emit_scan/test_mat_emit_scan.py b/tests/unit_tests/lcls_tools/common/matlab2py/test_mat_emit_scan.py
similarity index 96%
rename from tests/unit_tests/lcls_tools/common/matlab2py/emit_scan/test_mat_emit_scan.py
rename to tests/unit_tests/lcls_tools/common/matlab2py/test_mat_emit_scan.py
index b62023dd..59d3d5de 100644
--- a/tests/unit_tests/lcls_tools/common/matlab2py/emit_scan/test_mat_emit_scan.py
+++ b/tests/unit_tests/lcls_tools/common/matlab2py/test_mat_emit_scan.py
@@ -1,6 +1,6 @@
 import os
 import unittest
-from lcls_tools.common.matlab2py.emit_scan.mat_emit_scan import MatEmitScan as MES
+from lcls_tools.common.matlab2py.mat_emit_scan import MatEmitScan as MES
 
 
 ITERS = 3
diff --git a/tests/unit_tests/lcls_tools/common/matlab2py/image/test_mat_image.py b/tests/unit_tests/lcls_tools/common/matlab2py/test_mat_image.py
similarity index 98%
rename from tests/unit_tests/lcls_tools/common/matlab2py/image/test_mat_image.py
rename to tests/unit_tests/lcls_tools/common/matlab2py/test_mat_image.py
index 344bb73c..b838c9ee 100644
--- a/tests/unit_tests/lcls_tools/common/matlab2py/image/test_mat_image.py
+++ b/tests/unit_tests/lcls_tools/common/matlab2py/test_mat_image.py
@@ -1,7 +1,7 @@
 import unittest
 import numpy as np
 import os
-from lcls_tools.common.matlab2py.image.mat_image import MatImage as MI
+from lcls_tools.common.matlab2py.mat_image import MatImage as MI
 
 
 class MatImageTest(unittest.TestCase):