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Commit 6f3405d7 authored by Lucas-He's avatar Lucas-He
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Added a python file to connect to the seerver and run the WBouncingScroll.

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connect_to_mmt_WBounce.py 0 → 100644
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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?WBouncingScroll'
X_ref = {'uri': 'http://mathhub.info/FrameIT/frameworld?WBouncingScroll/Problem?xposition'}
Y_ref = {'uri': 'http://mathhub.info/FrameIT/frameworld?WBouncingScroll/Problem?yposition'}
Xv_ref = {'uri': 'http://mathhub.info/FrameIT/frameworld?WBouncingScroll/Problem?xvelocity'}
Yv_ref = {'uri': 'http://mathhub.info/FrameIT/frameworld?WBouncingScroll/Problem?yvelocity'}
G_ref = {'uri': 'http://mathhub.info/FrameIT/frameworld?WBouncingScroll/Problem?g_base'}
B_ref = {'uri': 'http://mathhub.info/FrameIT/frameworld?WBouncingScroll/Problem?bounce'}
W_ref = {'uri': 'http://mathhub.info/FrameIT/frameworld?WBouncingScroll/Problem?walls'}
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'
def list_element_4tuple(x1, y1, x2, y2):
return {'applicant': {'uri': tuple_mmt, 'kind': 'OMS'},
'arguments': [{'applicant': {'uri': tuple_mmt, 'kind': 'OMS'},
'arguments': [{'float': x1, 'kind': 'OMF'},
{'float': y1, 'kind': 'OMF'}],
'kind': 'OMA'},
{'applicant': {'uri': tuple_mmt, 'kind': 'OMS'},
'arguments': [{'float': x2, 'kind': 'OMF'},
{'float': y2, 'kind': 'OMF'}],
'kind': 'OMA'}],
'kind': 'OMA'}
def list_element_4tuple_plus_nil(x1, y1, x2, y2):
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'}],
'kind': 'OMA'},
{'applicant': {'uri': product, 'kind': 'OMS'},
'arguments': [{'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': x1, 'kind': 'OMF'},
{'float': y1, 'kind': 'OMF'}],
'kind': 'OMA'},
{'applicant': {'uri': tuple_mmt, 'kind': 'OMS'},
'arguments': [{'float': x2, 'kind': 'OMF'},
{'float': y2, '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_4tuple_df(values):
# Values needs to be of the form [[x1, y1, x2, y2], [x1, y1, x2, y2], ...]
prev_ele = {}
for ci, cv in enumerate(values[::-1]):
if ci == 0:
prev_ele = list_element_4tuple_plus_nil(cv[0], cv[1], cv[2], cv[3])
else:
cur_ele = list_element_4tuple(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': 'Walls',
'tp': {'applicant': {'uri': list_type, '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'}],
'kind': 'OMA'},
{'applicant': {'uri': product, 'kind': 'OMS'},
'arguments': [{'uri': real_lit, 'kind': 'OMS'},
{'uri': real_lit, 'kind': 'OMS'}],
'kind': 'OMA'}],
'kind': 'OMA'}],
'kind': 'OMA'},
'kind': 'general',
'df': construct_list_4tuple_df(values)
}
def create_R_fact(val, ref):
return {"ref": ref,
"label": "X",
"kind": "general",
"tp": {'uri': 'http://mathhub.info/MitM/Foundation?RealLiterals?real_lit',
'kind': 'OMS'},
"df": {"kind": "OMF", "float": val}
}
g = -200.0
X_fact = create_R_fact(380.0, X_ref)
Y_fact = create_R_fact(300.0, Y_ref)
Xv_fact = create_R_fact(-490.0, Xv_ref)
Yv_fact = create_R_fact(150.0, Yv_ref)
G_fact = create_R_fact(g, G_ref)
B_fact = create_R_fact(0.8, B_ref)
#walls_fact = create_walls_fact([[-10000.0, 0.0, 10000.0, 0.0]])
walls_list = [[-1.0, 0.0, 401.0, 0.0],
[0.0, -1.0, 0.01, 401.0],
[400.0, -1.0, 400.01, 401.0],
[-1.0, 400.0, 401.0, 400.0],
[50.0, 200.0, 120.0, 270.0],
[150.0, 100.0, 200.0, 100.0],
[150.0, 285.0, 200.0, 200.0],
[230.0, 360.0, 300.0, 300.0],
[300.0, 100.0, 385.0, 150.0],
[50.0, 50.0, 100.0, 135.0]]
walls_fact = create_walls_fact(walls_list)
fact_list = [X_fact, Y_fact, Xv_fact, Yv_fact, G_fact, B_fact, walls_fact]
fact_list_encoded = json.dumps(fact_list).encode('utf-8')
scroll_assignment_list = [{"fact": X_ref, "assignment": {"kind": "OMS", "uri": 'http://mathhub.info/FrameIT/frameworld?DefaultSituationSpace/SituationTheory1?fact1'}},
{"fact": Y_ref, "assignment": {"kind": "OMS", "uri": 'http://mathhub.info/FrameIT/frameworld?DefaultSituationSpace/SituationTheory1?fact2'}},
{"fact": Xv_ref, "assignment": {"kind": "OMS", "uri": 'http://mathhub.info/FrameIT/frameworld?DefaultSituationSpace/SituationTheory1?fact3'}},
{"fact": Yv_ref, "assignment": {"kind": "OMS", "uri": 'http://mathhub.info/FrameIT/frameworld?DefaultSituationSpace/SituationTheory1?fact4'}},
{"fact": G_ref, "assignment": {"kind": "OMS", "uri": 'http://mathhub.info/FrameIT/frameworld?DefaultSituationSpace/SituationTheory1?fact5'}},
{"fact": B_ref, "assignment": {"kind": "OMS", "uri": 'http://mathhub.info/FrameIT/frameworld?DefaultSituationSpace/SituationTheory1?fact6'}},
{"fact": W_ref, "assignment": {"kind": "OMS", "uri": 'http://mathhub.info/FrameIT/frameworld?DefaultSituationSpace/SituationTheory1?fact7'}}]
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 = []
def rec_vals(facts):
for rf in facts:
if rf["applicant"]["uri"] == cons_nil:
continue
elif len(rf["arguments"]) == 3:
rfa = rf["arguments"]
cvals = []
for ri2, rrf in enumerate(rfa):
cvals.extend([x["float"] for x in rrf["arguments"]])
values.append(cvals)
continue
else:
rec_vals(rf["arguments"])
return
rec_vals(rel_fact)
print("Step\tX\tY\tXv\tYv\tht\tm")
for i, v in enumerate(values):
print("%d\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]))
import matplotlib.pyplot as plt
import numpy as np
def get_xy(xs, ys, xv, yv, ct):
rx = xs + ct * xv
ry = ys + ct * yv + 0.5 * g * ct**2
return [rx, ry]
plt.figure()
for wl in walls_list:
plt.plot([wl[0], wl[2]], [wl[1], wl[3]], color="blue", linewidth=3)
for i, vl in enumerate(values):
pvals = np.array([get_xy(vl[0], vl[1], vl[2], vl[3], cct) for cct in np.arange(0, vl[4], 0.01)])
plt.scatter(pvals[:, 0], pvals[:, 1], color="green", s=1)
plt.show()
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