initial commit

.gitignore

@@ -0,0 +1,3 @@
+*.pyc
+/dist/
+/*.egg-info

MANIFEST.in

@@ -0,0 +1 @@
+include e80analysis/e80data.json

README.md

@@ -0,0 +1 @@
+# e80analysis

build/lib/e80analysis/__init__.py

@@ -0,0 +1,143 @@
+from matplotlib import pyplot as plt
+import itertools, json, os
+
+OS = os.name
+USER_HOME = os.environ.get('Homepath' if OS == 'nt' else 'HOME')
+USER_DOC_PATH = USER_HOME + '\\Documents\\' if OS == 'nt' else USER_HOME + '/Documents/'
+
+def sumlist(x):
+    """
+    sumlist(x)
+
+    Returns the running sum of a list of numbers, x. For example:
+    sumlist([1,2,3]) would return [1,3,6].
+    """
+    try:
+        return list(itertools.accumulate(x))
+    except TypeError:
+        raise TypeError("unsupported argument type for 'sumlist'")
+
+class AnalysisError(Exception):
+    pass
+
+class E80Analysis:
+    def __init__(self):
+        with open(os.path.join(os.path.dirname(__file__),'e80data.json'), 'r') as f:
+            self.e80data = json.load(f)
+            self.spans = range(10,201)
+
+    def set_spans(self, span_lengths):
+        self.spans = span_lengths
+
+    def _run_train_single_span(self, span_length, axles):
+        incr = 1
+
+        axle_loads = axles[0]
+        axle_spaces = axles[1]
+        axle_locs = sumlist(axle_spaces)
+
+        train_tot = sum(axle_spaces)
+
+        positions = []
+        point = -span_length
+        while point <= train_tot:
+            positions.append(point)
+            point += incr
+        m_array = []
+        v_array = []
+        for i in range(len(positions)):
+            x_locs_total = [-x + positions[i] + span_length for x in axle_locs]
+            x_locs = [x for x in x_locs_total if (x <= span_length and x >= 0)]
+            axles_ = [axle for axle in axle_locs if axle <= span_length + positions[i] and axle >= positions[i]]
+            axle_loads_ = [axle_loads[k] for k, axle in enumerate(axle_locs) if axle in axles_]
+            num_axles_ = len(axles_)
+            # a and b arrays store a and b values or each axle
+            # r1 and r2 arrays store reactions at ends 1 and 2 for each axle
+            # m and v arrays store m and v caused by each axle
+            r1 = []
+            r2 = []
+            m = []
+            v = []
+
+            # This loop calculates individual values for each of the above
+            # arrays and appends each value to the array.
+            for j in range(num_axles_):
+                a_val = span_length + positions[i] - axles_[j]
+
+                b_val = span_length - a_val
+
+                if 0 < b_val < span_length:
+                    r1_val = axle_loads_[j]*b_val/span_length
+                else:
+                    r1_val = 0
+                r1.append(r1_val)
+
+                if 0 < a_val < span_length:
+                    r2_val = axle_loads_[j]*a_val/span_length
+                else:
+                    r2_val = 0
+                r2.append(r2_val)
+
+                m_loc = []
+                v_loc = []
+                for x_loc in x_locs:
+                    if 0 < b_val < span_length and a_val > x_loc:
+                        m_val = axle_loads_[j]*(a_val - x_loc)
+                    else:
+                        m_val = 0
+                    m_loc.append(m_val)
+
+                    if 0 < b_val < span_length and a_val < x_loc:
+                        v_val = axle_loads_[j]
+                    else:
+                        v_val = 0
+                    v_loc.append(v_val)
+                m.append(m_loc if m_loc != [] else [0])
+                v.append(v_loc if v_loc != [] else [0])
+            # Calculate the moment and shear at the respective x location
+            # caused by the train at position i and push these values to the
+            # global moment and shear arrays
+            moments = list(zip(*m))
+            if x_locs != []:
+                m_tot = max([sum(r2)*(span_length-x_locs[i]) - sum(moments[i]) for i in range(len(x_locs))])
+            else:
+                m_tot = 0
+            v_tot = max(sum(r1), sum(r2))
+            m_array.append(m_tot)
+            v_array.append(v_tot)
+        return max(m_array), max(v_array)
+
+    def _get_single_E80_env(self, span):
+        if str(span) in self.e80data.keys():
+            return self.e80data[str(span)]
+        else:
+            axles_E80 = ([40,80,80,80,80,52,52,52,52]*2 + [8]*span, [0,8,5,5,5,9,5,6,5,8,8,5,5,5,9,5,6,5,5.5]+[1]*(span-1))
+            axles_E80_alt = ([100,100,100,100], [0,5,6,5])
+            e80_vals = self._run_train_single_span(span, axles_E80)
+            e80_alt_vals = self._run_train_single_span(span, axles_E80_alt)
+            return (max([e80_vals[0], e80_alt_vals[0]]), max([e80_vals[1], e80_alt_vals[1]]))
+
+    def _calc_e80(self, design, e80):
+        return (design[0]/e80[0] * 80, design[1]/e80[1] * 80)
+
+    def span(self, axles, span):
+        return self._calc_e80(self._run_train_single_span(span, axles), self._get_single_E80_env(span))
+
+    def plot(self, axles, save=False):
+
+        span_data = [self.span(axles, span) for span in self.spans]
+        plt.plot(self.spans, [x[0] for x in span_data], label='Moment')
+        plt.plot(self.spans, [x[1] for x in span_data], label='Shear')
+        plt.legend()
+        plt.minorticks_on()
+        plt.grid()
+        plt.title("Equivalent E-Loadings")
+        plt.xlabel('Span Length, ft')
+        plt.ylabel('E-Rating')
+        if save:
+            plt.savefig(USER_DOC_PATH+'E-Loading.png')
+        else:
+            plt.show()
+        plt.clf()
+        plt.cla()
+        plt.close()

build/lib/e80analysis/e80data.json

@@ -0,0 +1 @@
+{"1": [25.0, 75.0], "2": [50.0, 87.5], "3": [75.0, 91.66666666666667], "4": [100.0, 93.75], "5": [125.0, 95.0], "6": [150.0, 108.33333333333333], "7": [175.0, 121.42857142857143], "8": [200.0, 131.25], "9": [234.72222222222229, 138.88888888888889], "10": [281.25, 145.0], "11": [328.40909090909093, 150.0], "12": [376.04166666666674, 160.41666666666669], "13": [425.4807692307693, 171.15384615384616], "14": [500.44642857142844, 180.35714285714286], "15": [575.4166666666665, 188.33333333333331], "16": [650.390625, 195.3125], "17": [725.3676470588239, 205.88235294117646], "18": [800.3472222222222, 216.66666666666669], "19": [875.328947368421, 226.31578947368422], "20": [950.3125, 235.0], "21": [1042.8571428571431, 242.85714285714286], "22": [1140.909090909091, 250.0], "23": [1239.1304347826087, 256.5217391304348], "24": [1337.4999999999998, 262.5], "25": [1436.0, 268.0], "26": [1534.6153846153843, 273.0769230769231], "27": [1633.3333333333335, 277.77777777777777], "28": [1732.1428571428573, 282.14285714285717], "29": [1831.034482758621, 286.2068965517242], "30": [1930.0000000000005, 290.0], "31": [2029.032258064516, 293.5483870967742], "32": [2128.125, 296.875], "33": [2227.2727272727275, 300.0], "34": [2326.4705882352946, 302.94117647058823], "35": [2425.714285714286, 305.7142857142857], "36": [2525.0, 308.33333333333337], "37": [2624.324324324324, 310.81081081081084], "38": [2723.684210526316, 313.15789473684214], "39": [2823.076923076924, 315.3846153846154], "40": [2922.5, 317.5], "41": [3021.951219512195, 319.5121951219512], "42": [3121.4285714285716, 321.42857142857144], "43": [3220.9302325581393, 323.25581395348837], "44": [3320.454545454545, 325.0], "45": [3420.0, 326.6666666666667], "46": [3519.565217391305, 328.30434782608694], "47": [3619.1489361702133, 332.7659574468086], "48": [3718.750000000001, 337.2083333333333], "49": [3818.367346938776, 341.6326530612244], "50": [3918.0, 346.0399999999999], "51": [4017.6470588235297, 350.4313725490196], "52": [4117.307692307692, 354.8076923076923], "53": [4216.981132075472, 359.1698113207547], "54": [4324.00925925926, 363.5185185185184], "55": [4466.009090909092, 367.8545454545456], "56": [4608.008928571428, 372.17857142857144], "57": [4750.008771929826, 376.4912280701755], "58": [4892.008620689655, 380.7931034482758], "59": [5040.682203389828, 385.084745762712], "60": [5195.354166666666, 389.3666666666667], "61": [5350.036885245903, 393.6393442622951], "62": [5504.729838709678, 397.90322580645164], "63": [5659.432539682541, 402.31746031746025], "64": [5822.0, 407.40625], "65": [5990.000000000002, 412.3384615384617], "66": [6157.999999999998, 417.1212121212121], "67": [6326.0, 422.65671641791045], "68": [6494.000000000002, 428.3235294117647], "69": [6661.999999999998, 433.82608695652175], "70": [6830.000000000004, 439.1714285714286], "71": [6998.725352112675, 444.3661971830986], "72": [7168.715277777779, 450.2500000000001], "73": [7340.219178082189, 456.24657534246575], "74": [7519.027027027025, 462.08108108108104], "75": [7702.009999999998, 467.76], "76": [7886.917763157897, 473.2894736842105], "77": [8072.847402597401, 478.67532467532465], "78": [8259.798076923076, 483.92307692307696], "79": [8448.708860759496, 489.03797468354423], "80": [8638.440625, 494.025], "81": [8830.000000000004, 499.37037037037044], "82": [9026.000000000002, 504.7439024390244], "83": [9222.969879518072, 509.9879518072289], "84": [9425.291666666664, 515.1071428571429], "85": [9631.088235294119, 520.1058823529412], "86": [9837.953488372092, 525.4418604651162], "87": [10045.81609195402, 530.8045977011495], "88": [10255.727272727272, 536.0454545454546], "89": [10466.516853932582, 541.1685393258426], "90": [10678.466666666664, 546.1777777777777], "91": [10892.131868131866, 551.0769230769231], "92": [11106.641304347828, 556.2934782608697], "93": [11322.634408602149, 561.5376344086022], "94": [11540.000000000015, 566.6702127659574], "95": [11758.21052631579, 571.6947368421052], "96": [11978.208333333332, 576.6145833333333], "97": [12199.257731958758, 581.8350515463917], "98": [12421.244897959183, 587.0816326530614], "99": [12645.888888888876, 592.2222222222221], "100": [12893.129999999997, 597.2599999999999], "101": [13141.861386138604, 602.1980198019803], "102": [13391.470588235294, 607.0588235294116], "103": [13642.951456310679, 611.9029126213592], "104": [13895.538461538465, 616.7307692307692], "105": [14149.12380952383, 621.5428571428572], "106": [14417.292452830188, 626.3396226415094], "107": [14696.523364485984, 631.1214953271028], "108": [14976.648148148146, 635.8888888888887], "109": [15258.825688073397, 640.6422018348624], "110": [15542.113636363632, 645.3818181818184], "111": [15826.509009009002, 650.108108108108], "112": [16113.000000000007, 654.8214285714287], "113": [16400.367256637168, 659.5221238938054], "114": [16689.118421052663, 664.2105263157893], "115": [16979.513043478262, 668.8869565217387], "116": [17270.78017241379, 673.551724137931], "117": [17563.833333333343, 678.205128205128], "118": [17858.101694915247, 682.8474576271187], "119": [18153.294117647085, 687.4789915966389], "120": [18450.59999999999, 692.1], "121": [18748.909090909074, 696.7107438016529], "122": [19052.155737704903, 701.3114754098361], "123": [19360.0325203252, 705.90243902439], "124": [19668.9677419355, 710.4838709677417], "125": [19980.032000000007, 715.0560000000002], "126": [20291.98809523809, 719.6190476190478], "127": [20605.185039370088, 724.1732283464567], "128": [20920.125, 728.71875], "129": [21235.93410852713, 733.2558139534883], "130": [21553.35, 737.7846153846154], "131": [21872.122137404585, 742.30534351145], "132": [22191.76136363636, 746.8181818181818], "133": [22513.357142857145, 751.3233082706768], "134": [22835.992537313432, 755.820895522388], "135": [23159.66666666667, 760.3111111111112], "136": [23485.352941176476, 764.7941176470589], "137": [23811.897810218987, 769.2700729927006], "138": [24140.89855072466, 773.7391304347825], "139": [24476.11510791367, 778.2014388489209], "140": [24812.38928571427, 782.657142857143], "141": [25149.719858155942, 787.1063829787238], "142": [25489.126760563384, 791.549295774648], "143": [25829.423076923085, 795.9860139860142], "144": [26170.940972222204, 800.4166666666665], "145": [26514.206896551732, 804.841379310345], "146": [26858.3595890411, 809.2602739726025], "147": [27204.03061224489, 813.6734693877551], "148": [27551.13513513514, 818.0810810810809], "149": [27899.124161073836, 822.48322147651], "150": [28248.91666666667, 826.8799999999999], "151": [28599.84105960258, 831.2715231788089], "152": [28951.684210526306, 835.6578947368422], "153": [29305.56862745098, 840.0392156862744], "154": [29660.435064935067, 844.4155844155844], "155": [30016.35483870969, 848.7870967741936], "156": [30374.128205128203, 853.1538461538461], "157": [30732.777070063697, 857.5159235668791], "158": [31092.74683544304, 861.873417721519], "159": [31454.289308176085, 866.2264150943395], "160": [31816.706250000003, 870.575], "161": [32180.701863354057, 874.9192546583852], "162": [32545.999999999985, 879.2592592592594], "163": [32912.17177914108, 883.5950920245398], "164": [33280.17073170731, 887.9268292682926], "165": [33649.21212121213, 892.2545454545455], "166": [34019.2048192771, 896.5783132530122], "167": [34391.18562874251, 900.8982035928143], "168": [34764.08035714286, 905.214285714286], "169": [35138.04437869825, 909.5266272189351], "170": [35513.78823529411, 913.8352941176471], "171": [35890.40058479521, 918.1403508771923], "172": [36268.316860465115, 922.4418604651162], "173": [36647.76878612719, 926.7398843930637], "174": [37028.08908045979, 931.0344827586207], "175": [37409.94000000001, 935.3257142857143], "176": [37793.09090909092, 939.6136363636364], "177": [38177.11016949153, 943.8983050847459], "178": [38562.879213483175, 948.1797752808994], "179": [38954.83798882681, 952.4581005586593], "180": [39349.58333333333, 956.7333333333335], "181": [39745.55248618784, 961.0055248618786], "182": [40143.16483516483, 965.2747252747251], "183": [40541.66120218577, 969.5409836065573], "184": [40941.58695652173, 973.8043478260868], "185": [41342.94054054053, 978.064864864865], "186": [41745.17741935483, 982.3225806451613], "187": [42149.042780748656, 986.5775401069516], "188": [42554.12765957447, 990.8297872340424], "189": [42960.09523809524, 995.0793650793651], "190": [43367.8842105263, 999.3263157894736], "191": [43776.69109947648, 1003.5706806282722], "192": [44186.4375, 1007.8125], "193": [44598.13471502594, 1012.0518134715027], "194": [45010.750000000015, 1016.2886597938146], "195": [45424.39743589741, 1020.5230769230769], "196": [45839.83673469386, 1024.7551020408168], "197": [46256.154822335026, 1028.9847715736043], "198": [46673.68939393945, 1033.2121212121199], "199": [47092.82412060301, 1037.4371859296482], "200": [47512.83750000001, 1041.66]}

e80analysis/__init__.py

@@ -0,0 +1,143 @@
+from matplotlib import pyplot as plt
+import itertools, json, os
+
+OS = os.name
+USER_HOME = os.environ.get('Homepath' if OS == 'nt' else 'HOME')
+USER_DOC_PATH = USER_HOME + '\\Documents\\' if OS == 'nt' else USER_HOME + '/Documents/'
+
+def sumlist(x):
+    """
+    sumlist(x)
+
+    Returns the running sum of a list of numbers, x. For example:
+    sumlist([1,2,3]) would return [1,3,6].
+    """
+    try:
+        return list(itertools.accumulate(x))
+    except TypeError:
+        raise TypeError("unsupported argument type for 'sumlist'")
+
+class AnalysisError(Exception):
+    pass
+
+class E80Analysis:
+    def __init__(self):
+        with open(os.path.join(os.path.dirname(__file__),'e80data.json'), 'r') as f:
+            self.e80data = json.load(f)
+            self.spans = range(10,201)
+
+    def set_spans(self, span_lengths):
+        self.spans = span_lengths
+
+    def _run_train_single_span(self, span_length, axles):
+        incr = 1
+
+        axle_loads = axles[0]
+        axle_spaces = axles[1]
+        axle_locs = sumlist(axle_spaces)
+
+        train_tot = sum(axle_spaces)
+
+        positions = []
+        point = -span_length
+        while point <= train_tot:
+            positions.append(point)
+            point += incr
+        m_array = []
+        v_array = []
+        for i in range(len(positions)):
+            x_locs_total = [-x + positions[i] + span_length for x in axle_locs]
+            x_locs = [x for x in x_locs_total if (x <= span_length and x >= 0)]
+            axles_ = [axle for axle in axle_locs if axle <= span_length + positions[i] and axle >= positions[i]]
+            axle_loads_ = [axle_loads[k] for k, axle in enumerate(axle_locs) if axle in axles_]
+            num_axles_ = len(axles_)
+            # a and b arrays store a and b values or each axle
+            # r1 and r2 arrays store reactions at ends 1 and 2 for each axle
+            # m and v arrays store m and v caused by each axle
+            r1 = []
+            r2 = []
+            m = []
+            v = []
+
+            # This loop calculates individual values for each of the above
+            # arrays and appends each value to the array.
+            for j in range(num_axles_):
+                a_val = span_length + positions[i] - axles_[j]
+
+                b_val = span_length - a_val
+
+                if 0 < b_val < span_length:
+                    r1_val = axle_loads_[j]*b_val/span_length
+                else:
+                    r1_val = 0
+                r1.append(r1_val)
+
+                if 0 < a_val < span_length:
+                    r2_val = axle_loads_[j]*a_val/span_length
+                else:
+                    r2_val = 0
+                r2.append(r2_val)
+
+                m_loc = []
+                v_loc = []
+                for x_loc in x_locs:
+                    if 0 < b_val < span_length and a_val > x_loc:
+                        m_val = axle_loads_[j]*(a_val - x_loc)
+                    else:
+                        m_val = 0
+                    m_loc.append(m_val)
+
+                    if 0 < b_val < span_length and a_val < x_loc:
+                        v_val = axle_loads_[j]
+                    else:
+                        v_val = 0
+                    v_loc.append(v_val)
+                m.append(m_loc if m_loc != [] else [0])
+                v.append(v_loc if v_loc != [] else [0])
+            # Calculate the moment and shear at the respective x location
+            # caused by the train at position i and push these values to the
+            # global moment and shear arrays
+            moments = list(zip(*m))
+            if x_locs != []:
+                m_tot = max([sum(r2)*(span_length-x_locs[i]) - sum(moments[i]) for i in range(len(x_locs))])
+            else:
+                m_tot = 0
+            v_tot = max(sum(r1), sum(r2))
+            m_array.append(m_tot)
+            v_array.append(v_tot)
+        return max(m_array), max(v_array)
+
+    def _get_single_E80_env(self, span):
+        if str(span) in self.e80data.keys():
+            return self.e80data[str(span)]
+        else:
+            axles_E80 = ([40,80,80,80,80,52,52,52,52]*2 + [8]*span, [0,8,5,5,5,9,5,6,5,8,8,5,5,5,9,5,6,5,5.5]+[1]*(span-1))
+            axles_E80_alt = ([100,100,100,100], [0,5,6,5])
+            e80_vals = self._run_train_single_span(span, axles_E80)
+            e80_alt_vals = self._run_train_single_span(span, axles_E80_alt)
+            return (max([e80_vals[0], e80_alt_vals[0]]), max([e80_vals[1], e80_alt_vals[1]]))
+
+    def _calc_e80(self, design, e80):
+        return (design[0]/e80[0] * 80, design[1]/e80[1] * 80)
+
+    def span(self, axles, span):
+        return self._calc_e80(self._run_train_single_span(span, axles), self._get_single_E80_env(span))
+
+    def plot(self, axles, save=False):
+
+        span_data = [self.span(axles, span) for span in self.spans]
+        plt.plot(self.spans, [x[0] for x in span_data], label='Moment')
+        plt.plot(self.spans, [x[1] for x in span_data], label='Shear')
+        plt.legend()
+        plt.minorticks_on()
+        plt.grid()
+        plt.title("Equivalent E-Loadings")
+        plt.xlabel('Span Length, ft')
+        plt.ylabel('E-Rating')
+        if save:
+            plt.savefig(USER_DOC_PATH+'E-Loading.png')
+        else:
+            plt.show()
+        plt.clf()
+        plt.cla()
+        plt.close()