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How to use all_bounds method in hypothesis

Best Python code snippet using hypothesis

create_constraint_file.py

Source:create_constraint_file.py

...106                diff_lower = lower - upper107                diff_upper = c1_upper - c2_lower108                diff_constraints_bounds["{} - {}".format(cls1, cls2)] = (diff_lower, diff_upper)109    return diff_constraints_bounds110def get_all_bounds(constraints_path):111    constraints_parser = ConstraintsParser(constraints_path)112    constraints_bounds = build_diff_constraints_from_lower_and_upper(constraints_parser)113    for cls, lower in constraints_parser.lower_bounds.items():114        constraints_bounds[cls] = (lower, None)115    for cls, upper in constraints_parser.upper_bounds.items():116        if cls in constraints_bounds:117            lower = constraints_bounds[cls][0]118            constraints_bounds[cls] = (lower, upper)119        else:120            constraints_bounds[cls] = (None, upper)121    return constraints_bounds122def write_bounds_into_file(all_bounds_dict, dest_full_path):123    first_line=True124    with open(dest_full_path, "w") as f:125        for name, bounds in all_bounds_dict.items():126            if first_line:127                first_line = False128            else:129                f.write("\n")130            if bounds[0] is not None and bounds[1] is not None:131                f.write("{} < {} < {}".format(format(bounds[0], '.2f'), name, format(bounds[1], '.2f')))132            elif bounds[0] is not None:133                f.write("{} > {}".format(name, format(bounds[0], '.2f')))134            else:135                f.write("{} < {}".format(name, format(bounds[1], '.2f')))136def get_args_parser():137    parser = argparse.ArgumentParser(description='Process constraint collector args.')138    parser.add_argument('--src_path', '-s', type=str, required=True)139    parser.add_argument('--dest_path',  '-d', type=str, required=True)140    parser.add_argument('--expand_constraints',  '-expand', action="store_true")141    parser.add_argument('--create_auto_constraints', '-auto', action="store_true")142    parser.add_argument('--parse_crowd', '-crowd', action="store_true")143    parser.add_argument('--data_path',  '-data', type=str, required='-crowd' in sys.argv)144    parser.add_argument('--auto_eps', '-e', type=float, default=0.1)145    parser.add_argument('--neg_label', type=str, default="0")146    parser.add_argument('--pos_label', type=str, default="1")147    return parser148def main():149    args = get_args_parser().parse_args()150    print(vars(args))151    if args.expand_constraints:152        if not os.path.exists(args.dest_path):153            os.makedirs(args.dest_path)154        dest_file = os.path.join(args.dest_path, "{}_full.txt".format(os.path.abspath(args.src_path).split(".")[0]))155        all_bounds = get_all_bounds(args.src_path)156        write_bounds_into_file(all_bounds, dest_file)157    elif args.create_auto_constraints:158        print(os.path.dirname(args.dest_path))159        if not os.path.exists(os.path.dirname(args.dest_path)):160            print("create directory " + os.path.dirname(args.dest_path))161            os.makedirs(os.path.dirname(args.dest_path))162        # creates constraints from split dir163        labels_map = {args.pos_label: 1, args.neg_label: 0}164        true_indoor_percent = get_indoor_size(args.src_path, labels_map)165        bounds = create_lower_and_upper_bounds(true_indoor_percent, args.auto_eps)166        diff_bounds = create_mutual_bounds(true_indoor_percent, args.auto_eps)167        all_bounds = {**bounds, **diff_bounds}168        write_bounds(all_bounds, args.dest_path)169    elif args.parse_crowd:170        if not os.path.exists(args.dest_path):171            os.makedirs(args.dest_path)172        true_positive_percent_for_action = parse_crowd_data(args.src_path, args.data_path)173        for action in true_positive_percent_for_action:174            bounds = create_lower_and_upper_bounds(true_positive_percent_for_action[action], args.auto_eps)175            diff_bounds = create_mutual_bounds(true_positive_percent_for_action[action], args.auto_eps)176            all_bounds = {**bounds, **diff_bounds}177            dest_path = os.path.join(args.dest_path, "{}_constraints.txt".format(action))178            write_bounds(all_bounds, dest_path)179if __name__ == "__main__":180    main()181# PATH = "C:\\Users\\lotan\\Documents\\studies\\phoenix\\projects\\ballpark_indoor_outdoor\\explore_constraints\\teaching_constraints.txt"182# DEST = "C:\\Users\\lotan\\Documents\\studies\\phoenix\\projects\\ballpark_indoor_outdoor\\explore_constraints\\teaching_constraints_full.txt"183# all_bounds = get_all_bounds(PATH)...

guided_crop.py

Source:guided_crop.py

1import os2from pyrecon.utils.explore_files import findFiles3from pyrecon.utils.get_input import floatInput4from PIL import Image as PILImage5PILImage.MAX_IMAGE_PIXELS = None6def findBounds(series, obj_name):7    """Finds the bounds of a specified object on a single section file.8    """9    all_bounds = {}10    for section_num in series.sections:11        section = series.sections[section_num]12        # obtain list of all contours with obj_name13        all_contours = []14        for contour in section.contours:15            if contour.name == obj_name:16                all_contours.append(contour)17        # return None if contour not found in section18        if len(all_contours) == 0:19            all_bounds[section.name] = None20        else:21            # compile all transformed points22            all_points = []23            for contour in all_contours:24                fixed_points = contour.transform.transformPoints(contour.points)25                for point in fixed_points:26                    all_points.append(point)27            # get the domain transformation and inverse transformation28            domain_tform = section.images[0].transform # ASSUMES A SINGLE DOMAIN IMAGE29            domain_itform = domain_tform.inverse30            # compile points transformed by domain inverse transformation (ditform)31            all_points_ditform = domain_itform.transformPoints(all_points)32            x_vals = []33            y_vals = []34            for point in all_points_ditform:35                x_vals.append(point[0])36                y_vals.append(point[1])37            # get min and max values from points transformed by ditform38            x_min_ditform = min(x_vals)39            y_min_ditform = min(y_vals)40            x_max_ditform = max(x_vals)41            y_max_ditform = max(y_vals)42            # undo ditform43            bounds = domain_tform.transformPoints([(x_min_ditform, y_min_ditform), (x_max_ditform, y_max_ditform)])44            xmin = bounds[0][0]45            xmax = bounds[1][0]46            ymin = bounds[0][1]47            ymax = bounds[1][1]48            # return bounds fixed to Reconstruct space49            all_bounds[section.name] = (xmin, xmax, ymin, ymax)50    # fill in bounds data on sections where the object doesn't exist51    # if the first section(s) do not have the object, then fill it in with first object instance52    prev_bounds = None53    obj_found = False54    for bounds in all_bounds:55        if all_bounds[bounds] != None:56            prev_bounds = all_bounds[bounds]57            obj_found = True58            break59    # return None if obj was not found in entire series60    if not obj_found:61        return None62    # set any bounds points that are None to the previous bounds63    for bounds in all_bounds:64        if all_bounds[bounds] == None:65            all_bounds[bounds] = prev_bounds66        prev_bounds = all_bounds[bounds]67    # return bounds dictionary68    return all_bounds69def guidedCrop(series, obj_name, tform_data, images_dict, rad, progbar=None):70    """ Create a crop around an object.71    ENSURE THAT CROP FOCUS IS ALREADY SET TO GLOBAL BEFORE CALLING THIS FUNCTION.72    """73    # find the bounds for the object on each section74    bounds_dict = findBounds(series, obj_name)75    # check if trace was found in the series76    if not bounds_dict:77        raise Exception("This trace does not exist in this series.")78    79    # create the folder for the cropped images80    if not os.path.isdir("Cropped Images"):81        os.mkdir("Cropped Images")82    new_dir = "Cropped Images/" + obj_name83    os.mkdir(new_dir)84    # set up the tform_data file85    tform_data["LOCAL_" + obj_name] = {}86    # iterat through all section files87    if progbar:88        final_value = len(series.sections)89        prog_value = 090    for section_num in series.sections:91        if progbar:92            progbar.update_bar(prog_value/final_value * 100)93            prog_value += 194        section = series.sections[section_num]95        # set up the tform_data file96        tform_data["LOCAL_" + obj_name][section.name] = {}97        # fix the coordinates to the picture98        global_tform = section.images[0].transform99        xmin, xmax, ymin, ymax = bounds_dict[section.name]100        min_max_coords = global_tform.inverse.transformPoints([(xmin, ymin), (xmax, ymax)])101        # translate coordinates to pixels102        pix_per_mic = 1.0 / section.images[0].mag # get image magnification103        xshift_pix = int((min_max_coords[0][0] - rad) * pix_per_mic)104        if xshift_pix < 0:105            xshift_pix = 0106        yshift_pix = int((min_max_coords[0][1] - rad) * pix_per_mic)107        if yshift_pix < 0:108            yshift_pix = 0109        # write the shifted origin to the tform_data file110        tform_data["LOCAL_" + obj_name][section.name]["xshift_pix"] = xshift_pix111        tform_data["LOCAL_" + obj_name][section.name]["yshift_pix"] = yshift_pix112        # write identity transformation as Delta transformation113        tform_data["LOCAL_" + obj_name][section.name]["xcoef"] = [0,1,0,0,0,0]114        tform_data["LOCAL_" + obj_name][section.name]["ycoef"] = [0,0,1,0,0,0]115        # get the name/path of the desired image file from dictionary116        file_path = images_dict[section.name]117        file_name = file_path[file_path.rfind("/")+1:]118        print("\nWorking on " + file_name + "...")119        120        # open original image121        img = PILImage.open(file_path)122        # get image dimensions123        img_length, img_height = img.size124        # get the pixel coordinates for each corner of the crop125        left = int((min_max_coords[0][0] - rad) * pix_per_mic)126        bottom = img_height - int((min_max_coords[0][1] - rad) * pix_per_mic)127        right = int((min_max_coords[1][0] + rad) * pix_per_mic)128        top = img_height - int((min_max_coords[1][1] + rad) * pix_per_mic)129        130        # if crop exceeds image boundary, cut it off131        if left < 0: left = 0132        if right >= img_length: right = img_length-1133        if top < 0: top = 0134        if bottom >= img_height: bottom = img_height-1135        # crop the photo136        cropped_src = new_dir + "/" + file_name137        cropped = img.crop((left, top, right, bottom))138        cropped.save(cropped_src)139        # store the local src for the image in tform_data...

16.py

Source:16.py

1from utils.utils_15 import get_raw_items, get_regex_search, get_regex_findall, regex, translate2from utils.utils_15 import GameConsole, TweakedGameConsole, memo3from inputs.input_16 import main_input4from itertools import combinations5import copy6import re7from collections import Counter8def get_parsed(raw_input):9    sections = get_raw_items(raw_input, split_token='\n\n')10    # section 011    rules = {}12    for line in sections[0].split('\n'):13        search_results = get_regex_search(line, r'(.*): (\d+)\-(\d+) or (\d+)\-(\d+)')14        field = search_results[0]15        lb1, ub1, lb2, ub2 = (int(x) for x in search_results[1:])16        rules[field] = ((lb1, ub1), (lb2, ub2))17    # section 118    section_1 = get_raw_items(sections[1], split_token='\n')[1]19    my_ticket = [int(x) for x in section_1.split(',')]20    # section 221    section_2 = get_raw_items(sections[2], split_token='\n')[1:]22    other_tickets = [[int(x) for x in line.split(',')] for line in section_2]23    return rules, my_ticket, other_tickets24sample_input_0 = """class: 1-3 or 5-725row: 6-11 or 33-4426seat: 13-40 or 45-5027your ticket:287,1,1429nearby tickets:307,3,473140,4,503255,2,203338,6,12"""34sample_input_1 = """class: 0-1 or 4-1935row: 0-5 or 8-1936seat: 0-13 or 16-1937your ticket:3811,12,1339nearby tickets:403,9,184115,1,5425,14,9"""43def part_1(raw_input):44    rules, my_ticket, other_tickets = get_parsed(raw_input)45    all_bounds = []46    for (lb1, ub1), (lb2, ub2) in rules.values():47        all_bounds.append((lb1, ub1))48        all_bounds.append((lb2, ub2))49    answer = 050    for t in other_tickets:51        for x in t:52            if not any(lb <= x <= ub for (lb, ub) in all_bounds):53                answer += x54    print(f'Part1: {answer}')55def is_valid(ticket, all_bounds):56    for x in ticket:57        if not any(lb <= x <= ub for (lb, ub) in all_bounds):58            return False59    return True60def part_2(raw_input):61    rules, my_ticket, other_tickets = get_parsed(raw_input)62    all_bounds = []63    for (lb1, ub1), (lb2, ub2) in rules.values():64        all_bounds.append((lb1, ub1))65        all_bounds.append((lb2, ub2))66    valid_tickets = [my_ticket] + [t for t in other_tickets if is_valid(t, all_bounds)]67    all_possible_fields = []68    for i, fvs in enumerate(zip(*valid_tickets)):69        possible_fields = []70        for field, ((lb1, ub1), (lb2, ub2)) in rules.items():71            if all(((lb1 <= fv <= ub1) or (lb2 <= fv <= ub2)) for fv in fvs):72                possible_fields.append(field)73        all_possible_fields.append(possible_fields)74    finalized_assignments = {}75    while len(finalized_assignments) < len(rules):76        for i, possible_fields in enumerate(all_possible_fields):77            if len(possible_fields) == 1:78                field = possible_fields[0]79                finalized_assignments[field] = i80                for possible_fields in all_possible_fields:81                    try:82                        possible_fields.remove(field)83                    except ValueError:84                        pass85                continue86    print(finalized_assignments)87    answer = 188    for field, index in finalized_assignments.items():89        if field.startswith('departure'):90            answer *= my_ticket[index]91    print(f'Part2: {answer}')92# part_1(sample_input_0)93# part_1(main_input)94part_2(sample_input_1)...

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