Coverage for csv_manager/DC_CSVManager.py: 7%
201 statements
« prev ^ index » next coverage.py v7.0.4, created at 2023-01-10 09:27 -0600
1"""
2Copyright 1999 Illinois Institute of Technology
4Permission is hereby granted, free of charge, to any person obtaining
5a copy of this software and associated documentation files (the
6"Software"), to deal in the Software without restriction, including
7without limitation the rights to use, copy, modify, merge, publish,
8distribute, sublicense, and/or sell copies of the Software, and to
9permit persons to whom the Software is furnished to do so, subject to
10the following conditions:
12The above copyright notice and this permission notice shall be
13included in all copies or substantial portions of the Software.
15THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
16EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
17MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
18IN NO EVENT SHALL ILLINOIS INSTITUTE OF TECHNOLOGY BE LIABLE FOR ANY
19CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
20TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
21SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
23Except as contained in this notice, the name of Illinois Institute
24of Technology shall not be used in advertising or otherwise to promote
25the sale, use or other dealings in this Software without prior written
26authorization from Illinois Institute of Technology.
27"""
29from os import makedirs
30import csv
31try:
32 from ..utils.file_manager import *
33except: # for coverage
34 from utils.file_manager import *
36class DC_CSVManager():
37 """
38 A class taking care of writing summary file
39 """
40 def __init__(self, dir_path, nFrames, fix_ranges=[]):
41 self.nFrames = nFrames # number of frames that average
43 sum_path = fullPath(dir_path, "dc_results")
45 if not exists(sum_path):
46 makedirs(sum_path)
48 if self.nFrames > 0:
49 # if number of frames that average is specified, summary fill will be summary_nf.csv while n is number of frames
50 self.filename = fullPath(sum_path, "summary_"+str(nFrames)+"f")
51 else:
52 # otherwise, summary file will be summary_m.csv
53 self.filename = fullPath(sum_path, "summary_m")
55 fix_range_names = [fr[0] for fr in fix_ranges]
56 if len(fix_range_names) > 0:
57 for n in fix_range_names:
58 self.filename += ("_" + str(n))
59 self.filename += ".csv"
61 self.allpeaks_data = {} # Collect meridian peaks data
62 self.offmer_data = {} # Collect off-meridian peaks data
63 self.grp_to_key = {} # Map group number with key
64 self.gen_data = {} # general data of Diffraction Centroid. Now, there's only integrated width
65 self.headers = [] # header of csv file
66 self.keyToImages = {} # Map key to image names
67 self.loadSummary() # load exist summary file before adding new data
69 def getRow(self, key):
70 """
71 Return index of key in header.
72 """
73 return self.headers.index(key)
75 def loadSummary(self):
76 """
77 Load exist summary file, and encapsulate them
78 """
79 self.allpeaks_data = {}
80 self.offmer_data = {}
81 self.gen_data = {}
82 self.keyToImages = {}
83 self.grp_to_key = {}
84 currentGroup = -1
85 header = []
86 # Files are selected by auto-grouping
87 if exists(self.filename):
88 with open(self.filename, "r") as csvfile:
89 reader = csv.reader(csvfile)
90 peak_data = []
91 images = []
92 g_data = {}
93 off_mer = {}
95 for row in reader:
96 if len(row) == 0:
97 continue
99 if row[0] == "group":
100 header = row[:]
101 continue
103 if len(row[0]) > 0:
104 if len(images) > 0:
105 k = "...".join([images[0], images[-1]])
106 self.allpeaks_data[k] = peak_data
107 self.offmer_data[k] = off_mer
108 self.gen_data[k] = g_data
109 self.keyToImages[k] = images
110 self.grp_to_key[int(currentGroup)] = k
111 peak_data = []
112 images = []
113 g_data = {}
114 off_mer = {}
116 if row[0] != "":
117 currentGroup = row[0]
118 images.append(row[1])
119 g_data["integration area width"] = row[2]
120 for i in range(3, len(row) - 3):
121 if "centroid" in header[i]:
122 if "average" in header[i]:
123 continue
124 head = header[i]
125 head = head.split(" ")
126 if "_" in head[0] and head[1] == "59":
127 quadrant = head[0]
128 off_mer[quadrant] = {
129 "centroid": [row[header.index(quadrant + " 59 " +"centroid")],
130 row[header.index(quadrant + " 51 " +"centroid")]],
131 "baseline": [row[header.index(quadrant + " 59 " + "baseline")],
132 row[header.index(quadrant + " 51 " + "baseline")]],
133 "intensity": [row[header.index(quadrant + " 59 " + "intensity")],
134 row[header.index(quadrant + " 51 " + "intensity")]],
135 }
136 else:
137 side = head[0]
138 name = head[1]
139 new_peak = {
140 "side": side,
141 "name": name,
142 "centroid": row[i],
143 "baseline": row[header.index(side + " " + name + " " + "baseline")],
144 "intensity": row[header.index(side + " " + name + " " + "intensity")]
145 }
146 peak_data.append(new_peak)
147 else:
148 images.append(row[1])
150 if len(images) > 0:
151 k = "...".join([images[0], images[-1]])
152 self.allpeaks_data[k] = peak_data
153 self.offmer_data[k] = off_mer
154 self.gen_data[k] = g_data
155 self.keyToImages[k] = images
156 self.grp_to_key[int(currentGroup)] = k
158 def writeNewData(self, info):
159 """
160 Add new data (DiffractionCentroids info) to encapsulated member, and rewrite summary
161 :param info: DiffractionCentroids info (dict)
162 """
163 fileList = info["filelist"]
164 k = "...".join([fileList[0], fileList[-1]])
165 if "summary_m" in self.filename:
166 grpnum = len(self.grp_to_key.keys()) + 1
167 for (group, key) in self.grp_to_key.items():
168 if key == k:
169 grpnum = group
170 self.grp_to_key[grpnum] = k
171 else:
172 self.grp_to_key[info["grp_num"]] = k
173 self.keyToImages[k] = fileList
175 if k in self.allpeaks_data:
176 del self.allpeaks_data[k]
178 if k in self.offmer_data:
179 del self.offmer_data[k]
181 data = []
182 for side in ["top", "bottom"]:
183 centroids = info[side + "_centroids"]
184 peaks = info[side + "_peaks"]
185 baselines = info[side + "_baselines"]
186 areas = info[side + "_areas"]
187 names = info[side + "_names"]
188 reject_state = info["reject"][side]
189 for i in range(len(peaks)):
190 peak_dict = {}
191 peak_dict["side"] = side
192 peak_dict["name"] = names[i]
193 if names[i] in reject_state:
194 peak_dict["centroid"] = "_"+str(centroids[i])
195 peak_dict["peak"] = "_"+str(peaks[i])
196 peak_dict["intensity"] = "_"+str(areas[i])
197 peak_dict["baseline"] = "_"+str(baselines[i])
198 else:
199 peak_dict["centroid"] = str(centroids[i])
200 peak_dict["peak"] = str(peaks[i])
201 peak_dict["intensity"] = str(areas[i])
202 peak_dict["baseline"] = str(baselines[i])
204 data.append(peak_dict)
206 off_mer_data = {}
207 if "off_mer_baselines" in info:
208 for q in ["top_left", "top_right", "bottom_left", "bottom_right"]:
209 dat = {
210 "baseline" : info["off_mer_baselines"][q],
211 "centroid" : info["off_mer_peak_info"][q]["centroids"],
212 "intensity" : info["off_mer_peak_info"][q]["areas"]
213 }
214 off_mer_data[q] = dat
216 self.allpeaks_data[k] = data
217 self.offmer_data[k] = off_mer_data
218 l,r = info["int_area"]
219 self.gen_data[k] = {"integration area width":abs(r-l)}
220 self.rewriteSummary()
222 def getOffMerHeaders(self):
223 """
224 Get Off-meridian header for csv file
225 """
226 header = []
227 for t in ["centroid", "baseline", "intensity"]:
228 for p in ["59", "51"]:
229 for q in ["top_left", "top_right", "bottom_left", "bottom_right"]:
230 header.append(q + " " + p + " "+t)
231 header.append(p + " average "+t)
232 return header
234 def toInt(self, s):
235 """
236 Convert to int.
237 """
238 try:
239 result = int(s)
240 except Exception:
241 result = s
242 return result
244 def rewriteSummary(self):
245 """
246 Re-write summary file from encapsulated data
247 :return:
248 """
249 # Files are selected by auto-grouping
250 with open(self.filename, "w") as csvfile:
251 writer = csv.writer(csvfile, delimiter=",")
252 grpKey = sorted(self.grp_to_key.items(), key=lambda gk: int(gk[0]))
253 _, k1 = grpKey[0]
254 peak_data = self.allpeaks_data[k1]
256 ### write header for all group ###
257 header = ["group", "filename", "integration area width"]
258 top_peaks = sorted([d for d in peak_data if d["side"] == "top"], key=lambda d: self.toInt(d["name"]))
259 bottom_peaks = sorted([d for d in peak_data if d["side"] == "bottom"], key=lambda d: self.toInt(d["name"]))
260 nTop = len(top_peaks)
261 nBottom = len(bottom_peaks)
262 min_nPeaks = min(nTop, nBottom)
264 for i in range(min_nPeaks):
265 peak_header = ["top " + top_peaks[i]["name"] + " centroid",
266 "bottom " + bottom_peaks[i]["name"] + " centroid",
267 "average " + bottom_peaks[i]["name"] + " centroid",
268 "top " + top_peaks[i]["name"] + " baseline",
269 "bottom " + bottom_peaks[i]["name"] + " baseline",
270 "average " + bottom_peaks[i]["name"] + " baseline",
271 "top " + top_peaks[i]["name"] + " intensity",
272 "bottom " + bottom_peaks[i]["name"] + " intensity",
273 "average " + bottom_peaks[i]["name"] + " intensity"]
274 header.extend(peak_header)
275 header.extend(self.getOffMerHeaders())
277 writer.writerow(header)
278 self.headers = header
280 ### Write data for each group ###
281 for (g, k) in grpKey:
282 off_mer = self.offmer_data[k]
283 peak_data = self.allpeaks_data[k]
284 g_data = self.gen_data[k]
285 filelist = self.keyToImages[k]
286 top_peaks = sorted([d for d in peak_data if d["side"] == "top"], key=lambda d: d["name"])
287 bottom_peaks = sorted([d for d in peak_data if d["side"] == "bottom"], key=lambda d: d["name"])
289 for i in range(len(filelist)):
290 if i != 0:
291 write_row = ["", str(filelist[i])]
292 else:
293 write_row = [str(g), str(filelist[i]), g_data["integration area width"]]
294 for j in range(min_nPeaks):
295 peak_detail = [top_peaks[j]["centroid"], bottom_peaks[j]["centroid"],
296 self.average(top_peaks[j]["centroid"], bottom_peaks[j]["centroid"]),
297 top_peaks[j]["baseline"], bottom_peaks[j]["baseline"],
298 self.average(top_peaks[j]["baseline"], bottom_peaks[j]["baseline"]),
299 top_peaks[j]["intensity"], bottom_peaks[j]["intensity"],
300 self.average(top_peaks[j]["intensity"], bottom_peaks[j]["intensity"])]
301 write_row.extend(peak_detail)
303 if len(off_mer.keys()) > 0:
304 for h in ["centroid", "baseline", "intensity"]:
305 for p in [0,1]:
306 sum_val = 0.
307 for q in ["top_left", "top_right", "bottom_left", "bottom_right"]:
308 write_row.append(off_mer[q][h][p])
309 sum_val += float(off_mer[q][h][p])
310 write_row.append(sum_val/4.)
312 writer.writerow(write_row)
314 def average(self, s1, s2):
315 """
316 Find average between 2 float string. Remove '_' if necessary.
317 """
318 rejected = False
319 if "_" in s1:
320 rejected = True
321 s1 = s1.lstrip("_")
322 if "_" in s2:
323 rejected = True
324 s2 = s2.lstrip("_")
326 result = str(1.*(float(s1)+float(s2))/2.)
327 if rejected :
328 result = "_" + result
329 return result