@@ -102,7 +102,7 @@ def quantify_single_pattern(
102102 plot_correlation_radius = False ,
103103 scale_markers_experiment = 40 ,
104104 scale_markers_calculated = 200 ,
105- max_marker_size = 400 ,
105+ max_marker_size = 400 ,
106106 crystal_inds_plot = None ,
107107 phase_colors = None ,
108108 figsize = (10 , 7 ),
@@ -629,8 +629,7 @@ def quantify_single_pattern(
629629 qx ,
630630 # s = scale_markers_experiment * intensity,
631631 s = np .minimum (
632- scale_markers_experiment
633- * bragg_peaks .data ["intensity" ][keep ],
632+ scale_markers_experiment * bragg_peaks .data ["intensity" ][keep ],
634633 max_marker_size ,
635634 ),
636635 marker = "o" ,
@@ -1230,7 +1229,7 @@ def plot_dominant_phase(
12301229 self ,
12311230 use_correlation_scores = False ,
12321231 reliability_range = (0.0 , 1.0 ),
1233- normalize_exp_intensity = True ,
1232+ normalize_exp_intensity = True ,
12341233 sigma = 0.0 ,
12351234 phase_colors = None ,
12361235 ticks = True ,
@@ -1319,7 +1318,6 @@ def plot_dominant_phase(
13191318 # if normalize_exp_intensity:
13201319 # phase_sig /= self.int_total[None,:,:]
13211320
1322-
13231321 # find highest correlation score for each crystal and match index
13241322 for a0 in range (self .num_crystals ):
13251323 sub = phase_sig [a0 ] > phase_corr
@@ -1349,7 +1347,6 @@ def plot_dominant_phase(
13491347 if normalize_exp_intensity :
13501348 phase_rel /= self .int_total
13511349
1352-
13531350 phase_scale = np .clip (
13541351 (phase_rel - reliability_range [0 ])
13551352 / (reliability_range [1 ] - reliability_range [0 ]),
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