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import http.client
import json
import time
HOST = 'localhost' #'127.0.0.1'
PORT = 8085
headers = {'Content-type': 'application/json'}
bouncing_scroll = 'http://mathhub.info/FrameIT/frameworld?W3DBouncingScroll'
pos_ref = {'uri': 'http://mathhub.info/FrameIT/frameworld?W3DBouncingScroll/Problem?position'}
vel_ref = {'uri': 'http://mathhub.info/FrameIT/frameworld?W3DBouncingScroll/Problem?velocity'}
G_ref = {'uri': 'http://mathhub.info/FrameIT/frameworld?W3DBouncingScroll/Problem?g_base'}
B_ref = {'uri': 'http://mathhub.info/FrameIT/frameworld?W3DBouncingScroll/Problem?bounce'}
W_ref = {'uri': 'http://mathhub.info/FrameIT/frameworld?W3DBouncingScroll/Problem?wallsr'}
real_list = 'http://mathhub.info/FrameIT/frameworld?DefaultSituationSpace/SituationTheory2?real_list'
list_type = 'http://gl.mathhub.info/MMT/LFX/Datatypes?ListSymbols?ListType'
product = 'http://gl.mathhub.info/MMT/LFX/Sigma?Symbols?Product'
real_lit = 'http://mathhub.info/MitM/Foundation?RealLiterals?real_lit'
cons = 'http://gl.mathhub.info/MMT/LFX/Datatypes?ListSymbols?cons'
cons_nil = 'http://gl.mathhub.info/MMT/LFX/Datatypes?ListSymbols?nil_constant'
tuple_mmt = 'http://gl.mathhub.info/MMT/LFX/Sigma?Symbols?Tuple'
point_mmt = 'http://mathhub.info/MitM/core/geometry?3DGeometry?point'
def list_element_4point(p1, p2, p3, p4):
return {'applicant': {'uri': tuple_mmt, 'kind': 'OMS'},
'arguments': [{'applicant': {'uri': tuple_mmt, 'kind': 'OMS'},
'arguments': [{'float': p1[0], 'kind': 'OMF'},
{'float': p1[1], 'kind': 'OMF'},
{'float': p1[2], 'kind': 'OMF'}],
'kind': 'OMA'},
{'applicant': {'uri': tuple_mmt, 'kind': 'OMS'},
'arguments': [{'float': p2[0], 'kind': 'OMF'},
{'float': p2[1], 'kind': 'OMF'},
{'float': p2[2], 'kind': 'OMF'}],
'kind': 'OMA'},
{'applicant': {'uri': tuple_mmt, 'kind': 'OMS'},
'arguments': [{'float': p3[0], 'kind': 'OMF'},
{'float': p3[1], 'kind': 'OMF'},
{'float': p3[2], 'kind': 'OMF'}],
'kind': 'OMA'},
{'applicant': {'uri': tuple_mmt, 'kind': 'OMS'},
'arguments': [{'float': p4[0], 'kind': 'OMF'},
{'float': p4[1], 'kind': 'OMF'},
{'float': p4[2], 'kind': 'OMF'}],
'kind': 'OMA'}],
'kind': 'OMA'}
def list_element_4point_plus_nil(p1, p2, p3, p4):
return {'applicant': {'uri': cons, 'kind': 'OMS'},
'arguments': [{'applicant': {'uri': cons_nil, 'kind': 'OMS'},
'arguments': [{'applicant': {'uri': product, 'kind': 'OMS'},
'arguments': [{'applicant': {'uri': product, 'kind': 'OMS'},
'arguments': [{'uri': real_lit, 'kind': 'OMS'},
{'uri': real_lit, 'kind': 'OMS'},
{'uri': real_lit, 'kind': 'OMS'}],
'kind': 'OMA'},
{'applicant': {'uri': product, 'kind': 'OMS'},
'arguments': [{'uri': real_lit, 'kind': 'OMS'},
{'uri': real_lit, 'kind': 'OMS'},
{'uri': real_lit, 'kind': 'OMS'}],
'kind': 'OMA'},
{'applicant': {'uri': product, 'kind': 'OMS'},
'arguments': [{'uri': real_lit, 'kind': 'OMS'},
{'uri': real_lit, 'kind': 'OMS'},
{'uri': real_lit, 'kind': 'OMS'}],
'kind': 'OMA'},
{'applicant': {'uri': product, 'kind': 'OMS'},
'arguments': [{'uri': real_lit, 'kind': 'OMS'},
{'uri': real_lit, 'kind': 'OMS'},
{'uri': real_lit, 'kind': 'OMS'}],
'kind': 'OMA'}],
'kind': 'OMA'}],
'kind': 'OMA'},
{'applicant': {'uri': tuple_mmt, 'kind': 'OMS'},
'arguments': [{'applicant': {'uri': tuple_mmt, 'kind': 'OMS'},
'arguments': [{'float': p1[0], 'kind': 'OMF'},
{'float': p1[1], 'kind': 'OMF'},
{'float': p1[2], 'kind': 'OMF'}],
'kind': 'OMA'},
{'applicant': {'uri': tuple_mmt, 'kind': 'OMS'},
'arguments': [{'float': p2[0], 'kind': 'OMF'},
{'float': p2[1], 'kind': 'OMF'},
{'float': p2[2], 'kind': 'OMF'}],
'kind': 'OMA'},
{'applicant': {'uri': tuple_mmt, 'kind': 'OMS'},
'arguments': [{'float': p3[0], 'kind': 'OMF'},
{'float': p3[1], 'kind': 'OMF'},
{'float': p3[2], 'kind': 'OMF'}],
'kind': 'OMA'},
{'applicant': {'uri': tuple_mmt, 'kind': 'OMS'},
'arguments': [{'float': p4[0], 'kind': 'OMF'},
{'float': p4[1], 'kind': 'OMF'},
{'float': p4[2], 'kind': 'OMF'}],
'kind': 'OMA'}],
'kind': 'OMA'}],
'kind': 'OMA'}
def cons_2elements(e1, e2):
return {'applicant': {'uri': cons, 'kind': 'OMS'},
'arguments': [e1, e2],
'kind': 'OMA'}
def construct_list_4point_df(values):
# Values needs to be of the form [[[x1, y1, z1], [x2, y2, z2], [x3, y3, z3], [x4, y4, z4]], ...]
prev_ele = {}
for ci, cv in enumerate(values[::-1]):
if ci == 0:
prev_ele = list_element_4point_plus_nil(cv[0], cv[1], cv[2], cv[3])
else:
cur_ele = list_element_4point(cv[0], cv[1], cv[2], cv[3])
prev_ele = cons_2elements(prev_ele, cur_ele)
return prev_ele
def create_walls_fact(values):
# Values needs to be of the form [[x1, y1, x2, y2], [x1, y1, x2, y2], ...]
return {'ref': W_ref,
'label': 'Wallsr',
'tp': {'applicant': {'uri': list_type, 'kind': 'OMS'},
'arguments': [{'applicant': {'uri': product, 'kind': 'OMS'},
'arguments': [{'uri': point_mmt, 'kind': 'OMS'},
{'uri': point_mmt, 'kind': 'OMS'},
{'uri': point_mmt, 'kind': 'OMS'},
{'uri': point_mmt, 'kind': 'OMS'}],
'kind': 'OMA'}],
'kind': 'OMA'},
'kind': 'general',
'df': construct_list_4point_df(values)
}
def create_R_fact(val, ref):
return {"ref": ref,
"label": "X",
"kind": "general",
"tp": {'uri': real_lit,
'kind': 'OMS'},
"df": {"kind": "OMF", "float": val}
}
def create_point_fact(val, ref):
return {"ref": ref,
"label": "P",
"kind": "general",
"tp": {"kind": "OMS", "uri": point_mmt},
"df": {"kind": "OMA", "applicant": {"kind": "OMS", "uri": tuple_mmt},
"arguments": [{"kind": "OMF", "float": val[0]},
{"kind": "OMF", "float": val[1]},
{"kind": "OMF", "float": val[2]}]}}
g = [0.0, 0.0, -200.0]
pos_fact = create_point_fact([380.0, 0.0, 300.0], pos_ref)
vel_fact = create_point_fact([-490.0, 100.0, 150.0], vel_ref)
G_fact = create_point_fact(g, G_ref)
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B_fact = create_R_fact(0.8, B_ref)
#wallsr_list = [[[-400.0, -400.0, 0.0], [400.0, -400.0, 0.0], [400.0, 400.0, 0.0], [-400.0, 400.0, 0.0]]]
wallsr_list = [[[0.0, 0.0, 0.0], [400.0, 0.0, 0.0], [400.0, 0.0, 400.0], [0.0, 0.0, 400.0]],
[[0.0, 400.0, 0.0], [400.0, 400.0, 0.0], [400.0, 400.0, 400.0], [0.0, 400.0, 400.0]],
[[0.0, 0.0, 0.0], [0.0, 0.0, 400.0], [0.0, 400.0, 400.0], [0.0, 400.0, 0.0]],
[[400.0, 0.0, 0.0], [400.0, 0.0, 400.0], [400.0, 400.0, 400.0], [400.0, 400.0, 0.0]],
[[0.0, 0.0, 400.0], [400.0, 0.0, 400.0], [400.0, 400.0, 400.0], [0.0, 400.0, 400.0]],
[[0.0, 0.0, 0.0], [400.0, 0.0, 0.0], [400.0, 400.0, 0.0], [0.0, 400.0, 0.0]],
[[50.0, 0.0, 200.0], [120.7, 0.0, 270.7], [120.7, 200.0, 270.7], [50.0, 200.0, 200.0]],
[[150.0, 0.0, 100.0], [200.0, 0.0, 100.0], [200.0, 200.0, 100.0], [150.0, 200.0, 100.0]],
[[150.0, 0.0, 286.6], [200.0, 0.0, 200.0], [200.0, 200.0, 200.0], [150.0, 200.0, 286.6]],
[[230.7, 0.0, 340.0], [300.0, 0.0, 300.0], [300.0, 200.0, 300.0], [230.7, 200.0, 340.0]],
[[300.0, 0.0, 100.0], [386.6, 0.0, 150.0], [386.6, 200.0, 150.0], [300.0, 200.0, 100.0]],
[[50.0, 0.0, 50.0], [100.0, 0.0, 136.6], [100.0, 200.0, 136.6], [50.0, 200.0, 50.0]]]
wallsr_fact = create_walls_fact(wallsr_list)
fact_list = [pos_fact, vel_fact, G_fact, B_fact, wallsr_fact]
fact_list_encoded = json.dumps(fact_list).encode('utf-8')
scroll_assignment_list = [{"fact": pos_ref, "assignment": {"kind": "OMS", "uri": 'http://mathhub.info/FrameIT/frameworld?DefaultSituationSpace/SituationTheory1?fact1'}},
{"fact": vel_ref, "assignment": {"kind": "OMS", "uri": 'http://mathhub.info/FrameIT/frameworld?DefaultSituationSpace/SituationTheory1?fact2'}},
{"fact": G_ref, "assignment": {"kind": "OMS", "uri": 'http://mathhub.info/FrameIT/frameworld?DefaultSituationSpace/SituationTheory1?fact3'}},
{"fact": B_ref, "assignment": {"kind": "OMS", "uri": 'http://mathhub.info/FrameIT/frameworld?DefaultSituationSpace/SituationTheory1?fact4'}},
{"fact": W_ref, "assignment": {"kind": "OMS", "uri": 'http://mathhub.info/FrameIT/frameworld?DefaultSituationSpace/SituationTheory1?fact5'}}]
scroll_application = {"scroll": bouncing_scroll,
"assignments": scroll_assignment_list}
scroll_encoded = json.dumps(scroll_application).encode('utf-8')
t1 = time.time()
conn = http.client.HTTPConnection(HOST, port=PORT)
conn.request("POST", "/fact/bulkadd", headers=headers, body=fact_list_encoded)
response = conn.getresponse()
data = response.read()
print(response.status, response.reason)
print(time.time() - t1)
data_dict = json.loads(data.decode('utf-8'))
t2 = time.time()
conn = http.client.HTTPConnection(HOST, port=PORT)
conn.request("POST", "/scroll/apply", headers=headers, body=scroll_encoded)
response = conn.getresponse()
data = response.read()
print(response.status, response.reason)
print(time.time() - t2)
data_dict = json.loads(data.decode('utf-8'))
for i in range(len(data_dict["acquiredFacts"])):
print(data_dict["acquiredFacts"][i])
rel_fact = data_dict['acquiredFacts'][0]["df"]["arguments"]
values = []
for rf in rel_fact:
rfa = rf["arguments"]
cvals = []
for ri2, rrf in enumerate(rfa):
if ri2 == len(rfa) - 2:
cvals.extend([x["float"] for x in rrf["arguments"][0]["arguments"]])
cvals.append(rrf["arguments"][1]["float"])
elif ri2 == len(rfa) - 1:
cvals.append(rrf["float"])
else:
cvals.extend([x["float"] for x in rrf["arguments"]])
values.append(cvals)
print("Step\tX\tY\tZ\tXv\tYv\tZv\tht\tnx\tny\tnz")
for i, v in enumerate(values):
print("%d\t%.2f\t%.2f\t%.2f\t%.2f\t%.2f\t%.2f\t%.2f\t%.2f\t%.2f\t%.2f" % (i, v[0], v[1], v[2], v[3], v[4], v[5], v[9], v[6], v[7], v[8]))
import matplotlib.pyplot as plt
import numpy as np
def get_xyz_wrap(xs, ys, zs, xv, yv, zv):
def get_xyz(ct):
rx = xs + ct * xv + 0.5 * g[0] * ct**2
ry = ys + ct * yv + 0.5 * g[1] * ct**2
rz = zs + ct * zv + 0.5 * g[2] * ct**2
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return np.array([rx, ry, rz])
return get_xyz
# plot ---------------------------------------------------- #
def floatRgb(mag, cmin, cmax):
""" Return a tuple of floats between 0 and 1 for R, G, and B. """
# Normalize to 0-1
x = float(mag - cmin) / (cmax - cmin)
blue = np.minimum(np.maximum(4*(0.75-x), 0.), 1.)
red = np.minimum(np.maximum(4*(x-0.25), 0.), 1.)
green = np.minimum(np.maximum(4*np.abs(x-0.5)-1., 0.), 1.)
return red, green, blue
def rgb(mag, cmin, cmax):
""" Return a tuple of integers, as used in AWT/Java plots. """
red, green, blue = floatRgb(mag, cmin, cmax)
return int(red*255), int(green*255), int(blue*255)
def strRgb(mag, cmin, cmax):
""" Return a hex string, as used in Tk plots. """
return "#%02x%02x%02x" % rgb(mag, cmin, cmax)
plt.figure()
ax = plt.axes(projection ="3d")
pos3ds = []
colors = []
for w in wallsr_list:
spos = np.array(w[0])
in1 = np.array(w[1]) -np.array( w[0])
in2 = np.array(w[3]) - np.array(w[0])
for i1 in np.arange(0, 1.01, 0.1):
for i2 in np.arange(0, 1.01, 0.1):
cur_pos = spos + i1 * in1 + i2 * in2
pos3ds.append([cur_pos[0], cur_pos[1], cur_pos[2]])
colors.append(strRgb(cur_pos[1], 0, 400))
for mii, mi in enumerate(values):
xyz_func = get_xyz_wrap(mi[0], mi[1], mi[2], mi[3], mi[4], mi[5])
pos3ds.extend([xyz_func(ct) for ct in np.arange(0, mi[9], 0.01)])
colors.extend([strRgb(xyz_func(ct)[1], 0, 400) for ct in np.arange(0, mi[9], 0.01)])
pos3ds = np.array(pos3ds)
ax.scatter3D(pos3ds[:, 0], pos3ds[:, 1], pos3ds[:, 2], color=colors)
plt.show()
# plot ---------------------------------------------------- #